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The DESI DR1 Peculiar Velocity Survey: global zero-point and $H_0$ constraints
Authors:
A. Carr,
C. Howlett,
A. J. Amsellem,
Tamara M. Davis,
K. Said,
D. Parkinson,
A. Palmese,
J. Aguilar,
S. Ahlen,
J. Bautista,
S. BenZvi,
D. Bianchi,
C. Blake,
D. Brooks,
T. Claybaugh,
A. Cuceu,
A. de la Macorra,
P. Doel,
K. Douglass,
S. Ferraro,
J. E. Forero-Romero,
E. Gaztañaga,
S. Gontcho A Gontcho,
G. Gutierrez,
H. K. Herrera-Alcantar
, et al. (33 additional authors not shown)
Abstract:
The Dark Energy Spectroscopic Instrument (DESI) in its first Data Release (DR1) already provides more than 100,000 galaxies with relative distance measurements. The primary purpose of this paper is to perform the calibration of the zero-point for the DESI Fundamental Plane and Tully-Fisher relations, which allows us to measure the Hubble constant, $H_0$. This sample has a lower statistical uncerta…
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The Dark Energy Spectroscopic Instrument (DESI) in its first Data Release (DR1) already provides more than 100,000 galaxies with relative distance measurements. The primary purpose of this paper is to perform the calibration of the zero-point for the DESI Fundamental Plane and Tully-Fisher relations, which allows us to measure the Hubble constant, $H_0$. This sample has a lower statistical uncertainty than any previously used to measure $H_0$, and we investigate the systematic uncertainties in absolute calibration that could limit the accuracy of that measurement. We improve upon the DESI Early Data Release Fundamental Plane $H_0$ measurement by a) using a group catalog to increase the number of calibrator galaxies and b) investigating alternative calibrators in the nearby universe. Our baseline measurement calibrates to the SH0ES/Pantheon+ type Ia supernovae, and finds $H_0=73.7\pm 0.06\;(\text{stat.})\pm 1.1\;(\text{syst.})$ km s$^{-1}$ Mpc$^{-1}$. Calibrating to surface brightness fluctuation (SBF) distances yields a similar $H_0$. We explore measurements using other calibrators, but these are currently less precise since the overlap with DESI peculiar velocity tracers is much smaller. In future data releases with an even larger peculiar velocity sample, we plan to calibrate directly to Cepheids and the tip of the red giant branch, which will enable the uncertainty to decrease towards a percent-level measurement of $H_0$. This will provide an alternative to supernovae as the Hubble flow sample for $H_0$ measurements.
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Submitted 2 December, 2025;
originally announced December 2025.
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The DESI DR1 Peculiar Velocity Survey: Growth Rate Measurements from the Galaxy Power Spectrum
Authors:
F. Qin,
C. Blake,
C. Howlett,
R. J. Turner,
K. Lodha,
J. Bautista,
Y. Lai,
A. J. Amsellem,
J. Aguilar,
S. Ahlen,
D. Bianchi,
D. Brooks,
S. BenZvi,
A. Carr,
E. Chaussidon,
T. Claybaugh,
A. Cuceu,
A. de la Macorra,
K. Douglass,
P. Doel,
S. Ferraro,
A. Font-Ribera,
J. E. Forero-Romero,
E. Gaztañaga,
S. Gontcho A Gontcho
, et al. (41 additional authors not shown)
Abstract:
The large-scale structure of the Universe and its evolution encapsulate a wealth of cosmological information. A powerful means of unlocking this knowledge lies in measuring the auto-power spectrum and/or the cross-power spectrum of the galaxy density and momentum fields, followed by the estimation of cosmological parameters based on these spectrum measurements. In this study, we generalize the cro…
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The large-scale structure of the Universe and its evolution encapsulate a wealth of cosmological information. A powerful means of unlocking this knowledge lies in measuring the auto-power spectrum and/or the cross-power spectrum of the galaxy density and momentum fields, followed by the estimation of cosmological parameters based on these spectrum measurements. In this study, we generalize the cross-power spectrum model to accommodate scenarios where the density and momentum fields are derived from distinct galaxy surveys. The growth rate of the large-scale structures of the Universe, commonly represented as $fσ_8$, is extracted by jointly fitting the monopole and quadrupole moments of the auto-density power spectrum, the monopole of the auto-momentum power spectrum, and the dipole of the cross-power spectrum. Our estimators, theoretical models and parameter-fitting framework have been tested using mocks, confirming their robustness and accuracy in retrieving the fiducial growth rate from simulation. These techniques are then applied to analyze the power spectrum of the DESI Bright Galaxy Survey and Peculiar Velocity Survey, and the fit result of the growth rate is $fσ_8=0.440^{+0.080}_{-0.096}$ at effective redshift $z_{\rm eff}=0.07$. By synthesizing the fitting outcomes from correlation functions, maximum likelihood estimation and power spectrum, yields a consensus value of $fσ_8(z_{\rm eff}=0.07) = 0.450 ^{+0.055}_{-0.055}$, and correspondingly we obtain $γ=0.580^{+0.110}_{-0.110}$, $Ω_\mathrm{m}=0.301^{+0.011}_{-0.011}$ and $σ_8=0.834^{+0.032}_{-0.032}$. The measured $fσ_8$ and $γ$ are consistent with the prediction of the $Λ$ Cold Dark Matter Model and General Relativity.
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Submitted 2 December, 2025;
originally announced December 2025.
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The DESI DR1 Peculiar Velocity Survey: growth rate measurements from galaxy and momentum correlation functions
Authors:
R. J. Turner,
C. Blake,
F. Qin,
J. Aguilar,
S. Ahlen,
A. J. Amsellem,
J. Bautista,
S. BenZvi,
D. Bianchi,
D. Brooks,
A. Carr,
E. Chaussidon,
T. Claybaugh,
A. Cuceu,
A. de la Macorra,
P. Doel,
K. Douglass,
S. Ferraro,
A. Font-Ribera,
J. E. Forero-Romero,
E. Gaztañaga,
S. Gontcho A Gontcho,
G. Gutierrez,
J. Guy,
H. K. Herrera-Alcantar
, et al. (39 additional authors not shown)
Abstract:
Joint analysis of the local peculiar velocity and galaxy density fields offers a promising route to testing cosmological models of gravity. We present a measurement of the normalised growth rate of structure, $fσ_8$, from the two-point correlations of velocity and density tracers from the DESI DR1 Peculiar Velocity and Bright Galaxy Surveys, the largest catalogues of their kind assembled to date.…
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Joint analysis of the local peculiar velocity and galaxy density fields offers a promising route to testing cosmological models of gravity. We present a measurement of the normalised growth rate of structure, $fσ_8$, from the two-point correlations of velocity and density tracers from the DESI DR1 Peculiar Velocity and Bright Galaxy Surveys, the largest catalogues of their kind assembled to date. We fit the two-point correlation measurements with non-linear correlation function models, constructed from density and momentum power spectra generated using 1-loop Eulerian perturbation theory, and validate our methodology using representative mock catalogues. We find $fσ_8 = 0.391^{+0.080}_{-0.081}$, consistent to within $1σ$ with accompanying analyses of the same datasets using power spectrum and maximum-likelihood fields methods. Combining these growth rate results from different methods including appropriate correlations, we find a consensus determination $fσ_8(z = 0.07) = 0.4497 \pm 0.0548$, consistent with predictions from \textit{Planck}$+Λ$CDM cosmology. Jointly fitting to this consensus low-redshift growth rate and the DESI DR1 full-shape clustering dataset, we measure gravitational growth index $γ_{\rm L} = 0.580^{+0.110}_{-0.110}$, consistent with the prediction of general relativity.
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Submitted 2 December, 2025;
originally announced December 2025.
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The DESI DR1 Peculiar Velocity Survey: The Tully-Fisher Distance Catalog
Authors:
K. Douglass,
S. BenZvi,
A. G. Kim,
S. Moore,
A. Carr,
J. Largett,
N. Ravi,
J. Aguilar,
S. Ahlen,
A. J. Amsellem,
J. Bautista,
D. Bianchi,
C. Blake,
D. Brooks,
T. Claybaugh,
A. Cuceu,
A. de la Macorra,
R. Demina,
P. Doel,
S. Ferraro,
A. Font-Ribera,
J. E. Forero-Romero,
E. Gaztanaga,
S. Gontcho A Gontcho,
G. Gutierrez
, et al. (42 additional authors not shown)
Abstract:
We calibrate the Tully-Fisher relation (TFR) using observations of spiral galaxies taken during the first year (DR1) of the DESI galaxy redshift survey. The rotational velocities of 10,262 galaxies are measured at 0.4 R26 by comparing the redshifts at 0.4 R26 with those at the galaxy centers of spatially-resolved galaxies targeted as part of the DESI Peculiar Velocity Survey. The DESI DR1 TFR slop…
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We calibrate the Tully-Fisher relation (TFR) using observations of spiral galaxies taken during the first year (DR1) of the DESI galaxy redshift survey. The rotational velocities of 10,262 galaxies are measured at 0.4 R26 by comparing the redshifts at 0.4 R26 with those at the galaxy centers of spatially-resolved galaxies targeted as part of the DESI Peculiar Velocity Survey. The DESI DR1 TFR slope is calibrated by separating the spiral galaxies into redshift bins of width dz = 0.005 from 0.03 < z < 0.1 and jointly fitting the TFR across all bins. We find a slope of -7.22+/-0.01 AB mag in the r-band for the TFR, with an intrinsic scatter of 0.466+/-0.001 AB mag. We present a catalog of the distances and peculiar velocities to these 10,262 galaxies using our calibrated TFR. For cosmological analyses, we also present a clustering catalog and associated random catalogs using a subset of 6807 of the DESI DR1 TF galaxies.
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Submitted 2 December, 2025;
originally announced December 2025.
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The DESI DR1 Peculiar Velocity Survey: Fundamental Plane Catalogue
Authors:
C. E. Ross,
C. Howlett,
J. R. Lucey,
K. Said,
T. M. Davis,
J. Aguilar,
S. Ahlen,
A. J. Amsellem,
J. Bautista,
S. BenZvi,
D. Bianchi,
C. Blake,
D. Brooks,
A. Carr,
T. Claybaugh,
A. Cuceu,
A. de la Macorra,
B. Dey,
P. Doel,
K. Douglass,
S. Ferraro,
A. Font-Ribera,
J. E. Forero-Romero,
E. Gaztañaga,
S. Gontcho A Gontcho
, et al. (36 additional authors not shown)
Abstract:
Measurements of peculiar velocities in the local Universe are a powerful tool to study the nature of dark energy at low ($z < 0.1$) redshifts. Here we present the largest single set of $z<0.1$ peculiar velocity measurements to date, obtained using the Fundamental Plane (FP) of galaxies in the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI). We describe the photometric a…
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Measurements of peculiar velocities in the local Universe are a powerful tool to study the nature of dark energy at low ($z < 0.1$) redshifts. Here we present the largest single set of $z<0.1$ peculiar velocity measurements to date, obtained using the Fundamental Plane (FP) of galaxies in the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI). We describe the photometric and spectroscopic selection criteria used to define the sample, as well as extensive quality control checks on the photometry and velocity dispersion measurements. Additionally, we perform detailed systematics checks for the many analysis parameters in our pipeline. Our DESI DR1 catalogue contains FP-based distances and peculiar velocities for $98,292$ unique early-type galaxies, increasing the total number of $z < 0.1$ FP distances ever measured by a factor of $\sim2$. We achieve a precision of $26\%$ random error in our distance measurements which is comparable to previous surveys. A series of companion DESI papers use the distances and peculiar velocities presented in this paper to measure cosmological parameters.
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Submitted 2 December, 2025;
originally announced December 2025.
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OzDES Reverberation Mapping of Active Galactic Nuclei: Final Data Release, Black-Hole Mass Results, & Scaling Relations
Authors:
H. McDougall,
T. M. Davis,
Z. Yu,
P. Martini,
C. Lidman,
U. Malik,
A. Penton,
G. F. Lewis,
B. E. Tucker,
B. J. S. Pope,
S. Allam,
F. Andrade-Oliveira,
J. Asorey,
D. Bacon,
S. Bocquet,
D. Brooks,
A. Carnero Rosell,
D. Carollo,
A. Carr,
J. Carretero,
T. Y. Cheng,
L. N. da Costa,
M. E. da Silva Pereira,
J. De Vicente,
H. T. Diehl
, et al. (31 additional authors not shown)
Abstract:
Over the last decade, the Australian Dark Energy (OzDES) collaboration has used Reverberation Mapping to measure the masses of high redshift supermassive black holes. Here we present the final review and analysis of this OzDES reverberation mapping campaign. These observations use 6-7 years of photometric and spectroscopic observations of 735 Active Galactic Nuclei (AGN) in the redshift range…
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Over the last decade, the Australian Dark Energy (OzDES) collaboration has used Reverberation Mapping to measure the masses of high redshift supermassive black holes. Here we present the final review and analysis of this OzDES reverberation mapping campaign. These observations use 6-7 years of photometric and spectroscopic observations of 735 Active Galactic Nuclei (AGN) in the redshift range $z\in [0.13, 3.85]$ and bolometric luminosity range $\log_{10}(L_{\mathrm{bol}})\in [44.3, 47.5] \mathrm{erg/s}$. Both photometry and spectra are observed in visible wavelengths, allowing for the physical scale of the AGN broad line region to be estimated from reverberations of the Hbeta, MgII and CIV emission lines. We successfully use reverberation mapping to constrain the masses of 62 super-massive black holes, and combine with existing data to fit a power law to the lag-luminosity relation for the Hbeta and MgII lines with a scatter of $\sim0.25$ dex, the tightest and most robust fit yet identified. We fit a similarly constrained relation for CIV, resolving a tension with the low luminosity literature AGN by accounting for selection effects. We also examine the impact of emission line width and luminosity (related to accretion rate) in reducing the scatter of these scaling relationships and find no significant improvement over the lag-only approach for any of the three lines. Using these relations, we further estimate the masses and accretion rates of 246 AGN. We also use these relations to estimate the relative sizes of the Hbeta, MgII and CIV emitting regions, and find evidence that the MgII emission may occur further out than Hbeta. In short, we provide a comprehensive benchmark of high redshift AGN reverberation mapping at the close of this most recent generation of surveys, including light curves, time-delays, and the most reliable radius-luminosity relations to date.
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Submitted 30 November, 2025;
originally announced December 2025.
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Detection of supernova magnitude fluctuations induced by large-scale structure
Authors:
A. Nguyen,
C. Blake,
R. J. Turner,
V. Aronica,
J. Bautista,
J. Aguilar,
S. Ahlen,
S. BenZvi,
D. Bianchi,
D. Brooks,
A. Carr,
T. Claybaugh,
A. Cuceu,
A. de la Macorra,
B. Dey,
P. Doel,
K. Douglass,
S. Ferraro,
J. E. Forero-Romero,
E. Gaztañaga,
S. Gontcho A Gontcho,
G. Gutierrez,
J. Guy,
K. Honscheid,
C. Howlett
, et al. (34 additional authors not shown)
Abstract:
The peculiar velocities of supernovae and their host galaxies are correlated with the large-scale structure of the Universe, and can be used to constrain the growth rate of structure and test the cosmological model. In this work, we measure the correlation statistics of the large-scale structure traced by the Dark Energy Spectroscopic Instrument Bright Galaxy Survey Data Release 1 sample, and magn…
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The peculiar velocities of supernovae and their host galaxies are correlated with the large-scale structure of the Universe, and can be used to constrain the growth rate of structure and test the cosmological model. In this work, we measure the correlation statistics of the large-scale structure traced by the Dark Energy Spectroscopic Instrument Bright Galaxy Survey Data Release 1 sample, and magnitude fluctuations of type Ia supernova from the Pantheon+ compilation across redshifts z < 0.1. We find a detection of the cross-correlation signal between galaxies and type Ia supernova magnitudes. Fitting the normalised growth rate of structure f sigma_8 to the auto- and cross-correlation function measurements we find f sigma_8 = 0.384 +0.094 -0.157, which is consistent with the Planck LambdaCDM model prediction, and indicates that the supernova magnitude fluctuations are induced by peculiar velocities. Using a large ensemble of N-body simulations, we validate our methodology, calibrate the covariance of the measurements, and demonstrate that our results are insensitive to supernova selection effects. We highlight the potential of this methodology for measuring the growth rate of structure, and forecast that the next generation of type Ia supernova surveys will improve f sigma_8 constraints by a further order of magnitude.
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Submitted 8 October, 2025;
originally announced October 2025.
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Forecast for growth-rate measurement using peculiar velocities from LSST supernovae
Authors:
Damiano Rosselli,
Bastien Carreres,
Corentin Ravoux,
Julian E. Bautista,
Dominique Fouchez,
Alex G. Kim,
Benjamin Racine,
Fabrice Feinstein,
Bruno Sánchez,
Aurelien Valade,
The LSST Dark Energy Science Collaboration
Abstract:
In this work, we investigate the feasibility of measuring the cosmic growth-rate parameter, $fσ_8$, using peculiar velocities (PVs) derived from Type Ia supernovae (SNe Ia) in the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST). We produce simulations of different SN types using a realistic LSST observing strategy, incorporating noise, photometric detection from the Difference I…
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In this work, we investigate the feasibility of measuring the cosmic growth-rate parameter, $fσ_8$, using peculiar velocities (PVs) derived from Type Ia supernovae (SNe Ia) in the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST). We produce simulations of different SN types using a realistic LSST observing strategy, incorporating noise, photometric detection from the Difference Image Analysis (DIA) pipeline, and a PV field modeled from the Uchuu UniverseMachine simulations. We test three observational scenarios, ranging from ideal conditions with spectroscopic host-galaxy redshifts and spectroscopic SN classification, to more realistic settings involving photometric classification and contamination from non-Ia supernovae. Using a maximum-likelihood technique, we show that LSST can measure $fσ_8$ with a precision of $10\%$ in the redshift range $ 0.02 < z < 0.14 $ in the most realistic case. Using three tomographic bins, LSST can constrain the growth-rate parameter with errors below $18\%$ up to $z = 0.14$. We also test the impact of contamination on the maximum likelihood method and find that for contamination fractions below $\sim 2\%$, the measurement remains unbiased. These results highlight the potential of the LSST SN Ia sample to complement redshift-space distortion measurements at high redshift, providing a novel avenue for testing general relativity and dark energy models.
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Submitted 30 June, 2025;
originally announced July 2025.
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An Agnostic Approach to Building Empirical Type Ia Supernova Light Curves: Evidence for Intrinsic Chromatic Flux Variation Using Nearby Supernova Factory Data
Authors:
Jared Hand,
A. G. Kim,
G. Aldering,
P. Antilogus,
C. Aragon,
S. Bailey,
C. Baltay,
S. Bongard,
K. Boone,
C. Buton,
Y. Copin,
S. Dixon,
D. Fouchez,
E. Gangler,
R. Gupta,
B. Hayden,
W. Hillebrandt,
Mitchell Karmen,
M. Kowalski,
D. Küsters,
P. -F. Léget,
F. Mondon,
J. Nordin,
R. Pain,
E. Pecontal
, et al. (13 additional authors not shown)
Abstract:
We present a new empirical Type Ia supernova (SN Ia) model with three chromatic flux variation templates: one phase dependent and two phase independent. No underlying dust extinction model or patterns of intrinsic variability are assumed. Implemented with Stan and trained using spectrally binned Nearby Supernova Factory spectrophotometry, we examine this model's 2D, phase-independent flux variatio…
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We present a new empirical Type Ia supernova (SN Ia) model with three chromatic flux variation templates: one phase dependent and two phase independent. No underlying dust extinction model or patterns of intrinsic variability are assumed. Implemented with Stan and trained using spectrally binned Nearby Supernova Factory spectrophotometry, we examine this model's 2D, phase-independent flux variation space using two motivated basis representations. In both, the first phase-independent template captures variation that appears dust-like, while the second captures a combination of effectively intrinsic variability and second-order dust-like effects. We find that approximately 13% of the modeled phase-independent flux variance is not dust-like. Previous empirical SN Ia models either assume an effective dust extinction recipe in their architecture, or only allow for a single mode of phase-independent variation. The presented results demonstrate such an approach may be insufficient, because it could "leak" noticeable intrinsic variation into phase-independent templates.
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Submitted 10 May, 2025;
originally announced May 2025.
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Extended Dark Energy analysis using DESI DR2 BAO measurements
Authors:
K. Lodha,
R. Calderon,
W. L. Matthewson,
A. Shafieloo,
M. Ishak,
J. Pan,
C. Garcia-Quintero,
D. Huterer,
G. Valogiannis,
L. A. Ureña-López,
N. V. Kamble,
D. Parkinson,
A. G. Kim,
G. B. Zhao,
J. L. Cervantes-Cota,
J. Rohlf,
F. Lozano-Rodríguez,
J. O. Román-Herrera,
M. Abdul-Karim,
J. Aguilar,
S. Ahlen,
O. Alves,
U. Andrade,
E. Armengaud,
A. Aviles
, et al. (100 additional authors not shown)
Abstract:
We conduct an extended analysis of dark energy constraints, in support of the findings of the DESI DR2 cosmology key paper, including DESI data, Planck CMB observations, and three different supernova compilations. Using a broad range of parametric and non-parametric methods, we explore the dark energy phenomenology and find consistent trends across all approaches, in good agreement with the…
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We conduct an extended analysis of dark energy constraints, in support of the findings of the DESI DR2 cosmology key paper, including DESI data, Planck CMB observations, and three different supernova compilations. Using a broad range of parametric and non-parametric methods, we explore the dark energy phenomenology and find consistent trends across all approaches, in good agreement with the $w_0w_a$CDM key paper results. Even with the additional flexibility introduced by non-parametric approaches, such as binning and Gaussian Processes, we find that extending $Λ$CDM to include a two-parameter $w(z)$ is sufficient to capture the trends present in the data. Finally, we examine three dark energy classes with distinct dynamics, including quintessence scenarios satisfying $w \geq -1$, to explore what underlying physics can explain such deviations. The current data indicate a clear preference for models that feature a phantom crossing; although alternatives lacking this feature are disfavored, they cannot yet be ruled out. Our analysis confirms that the evidence for dynamical dark energy, particularly at low redshift ($z \lesssim 0.3$), is robust and stable under different modeling choices.
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Submitted 3 April, 2025; v1 submitted 18 March, 2025;
originally announced March 2025.
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DESI DR2 Results II: Measurements of Baryon Acoustic Oscillations and Cosmological Constraints
Authors:
DESI Collaboration,
M. Abdul-Karim,
J. Aguilar,
S. Ahlen,
S. Alam,
L. Allen,
C. Allende Prieto,
O. Alves,
A. Anand,
U. Andrade,
E. Armengaud,
A. Aviles,
S. Bailey,
C. Baltay,
P. Bansal,
A. Bault,
J. Behera,
S. BenZvi,
D. Bianchi,
C. Blake,
S. Brieden,
A. Brodzeller,
D. Brooks,
E. Buckley-Geer,
E. Burtin
, et al. (162 additional authors not shown)
Abstract:
We present baryon acoustic oscillation (BAO) measurements from more than 14 million galaxies and quasars drawn from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2), based on three years of operation. For cosmology inference, these galaxy measurements are combined with DESI Lyman-$α$ forest BAO results presented in a companion paper. The DR2 BAO results are consistent with DESI…
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We present baryon acoustic oscillation (BAO) measurements from more than 14 million galaxies and quasars drawn from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2), based on three years of operation. For cosmology inference, these galaxy measurements are combined with DESI Lyman-$α$ forest BAO results presented in a companion paper. The DR2 BAO results are consistent with DESI DR1 and SDSS, and their distance-redshift relationship matches those from recent compilations of supernovae (SNe) over the same redshift range. The results are well described by a flat $Λ$CDM model, but the parameters preferred by BAO are in mild, $2.3σ$ tension with those determined from the cosmic microwave background (CMB), although the DESI results are consistent with the acoustic angular scale $θ_*$ that is well-measured by Planck. This tension is alleviated by dark energy with a time-evolving equation of state parametrized by $w_0$ and $w_a$, which provides a better fit to the data, with a favored solution in the quadrant with $w_0>-1$ and $w_a<0$. This solution is preferred over $Λ$CDM at $3.1σ$ for the combination of DESI BAO and CMB data. When also including SNe, the preference for a dynamical dark energy model over $Λ$CDM ranges from $2.8-4.2σ$ depending on which SNe sample is used. We present evidence from other data combinations which also favor the same behavior at high significance. From the combination of DESI and CMB we derive 95% upper limits on the sum of neutrino masses, finding $\sum m_ν<0.064$ eV assuming $Λ$CDM and $\sum m_ν<0.16$ eV in the $w_0w_a$ model. Unless there is an unknown systematic error associated with one or more datasets, it is clear that $Λ$CDM is being challenged by the combination of DESI BAO with other measurements and that dynamical dark energy offers a possible solution.
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Submitted 9 October, 2025; v1 submitted 18 March, 2025;
originally announced March 2025.
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The La Silla Schmidt Southern Survey
Authors:
Adam A. Miller,
Natasha S. Abrams,
Greg Aldering,
Shreya Anand,
Charlotte R. Angus,
Iair Arcavi,
Charles Baltay,
Franz E. Bauer,
Daniel Brethauer,
Joshua S. Bloom,
Hemanth Bommireddy,
Marcio Catelan,
Ryan Chornock,
Peter Clark,
Thomas E. Collett,
Georgios Dimitriadis,
Sara Faris,
Francisco Forster,
Anna Franckowiak,
Christopher Frohmaier,
Lluıs Galbany,
Renato B. Galleguillos,
Ariel Goobar,
Claudia P. Gutierrez,
Saarah Hall
, et al. (53 additional authors not shown)
Abstract:
We present the La Silla Schmidt Southern Survey (LS4), a new wide-field, time-domain survey to be conducted with the 1 m ESO Schmidt telescope. The 268 megapixel LS4 camera mosaics 32 2k$\times$4k fully depleted CCDs, providing a $\sim$20 deg$^2$ field of view with $1''$ pixel$^{-1}$ resolution. The LS4 camera will have excellent performance at longer wavelengths: in a standard 45 s exposure the e…
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We present the La Silla Schmidt Southern Survey (LS4), a new wide-field, time-domain survey to be conducted with the 1 m ESO Schmidt telescope. The 268 megapixel LS4 camera mosaics 32 2k$\times$4k fully depleted CCDs, providing a $\sim$20 deg$^2$ field of view with $1''$ pixel$^{-1}$ resolution. The LS4 camera will have excellent performance at longer wavelengths: in a standard 45 s exposure the expected 5$σ$ limiting magnitudes in $g$, $i$, $z$ are $\sim$21.5, $\sim$20.9, and $\sim$20.3 mag (AB), respectively. The telescope design requires a novel filter holder that fixes different bandpasses over each quadrant of the detector. Two quadrants will have $i$ band, while the other two will be $g$ and $z$ band and color information will be obtained by dithering targets across the different quadrants. The majority (90%) of the observing time will be used to conduct a public survey that monitors the extragalactic sky at both moderate (3 d) and high (1 d) cadence, as well as focused observations within the Galactic bulge and plane. Alerts from the public survey will be broadcast to the community via established alert brokers. LS4 will run concurrently with the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST). The combination of LS4+LSST will enable detailed holistic monitoring of many nearby transients: high-cadence LS4 observations will resolve the initial rise and peak of the light curve while less-frequent but deeper observations by LSST will characterize the years before and after explosion. Here, we summarize the primary science objectives of LS4 including microlensing events in the Galaxy, extragalactic transients, the search for electromagnetic counterparts to multi-messenger events, and cosmology.
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Submitted 18 March, 2025;
originally announced March 2025.
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Measuring Type Ia Supernova Angular-Diameter Distances with Intensity Interferometry
Authors:
A. G. Kim,
P. E. Nugent,
Xingzhuo Chen,
L. Wang,
J. T. O'Brien
Abstract:
This paper investigates the potential of intensity interferometry, based on the Hanbury Brown-Twiss effect, for measuring supernova sizes and distances. Through optimized telescope positioning, observing strategy, and advancements in single-photon detection technology, this method can provide precise angular size measurements of Type Ia supernovae as bright as 12~mag, corresponding to a local volu…
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This paper investigates the potential of intensity interferometry, based on the Hanbury Brown-Twiss effect, for measuring supernova sizes and distances. Through optimized telescope positioning, observing strategy, and advancements in single-photon detection technology, this method can provide precise angular size measurements of Type Ia supernovae as bright as 12~mag, corresponding to a local volume out to $z\sim0.004$, with an anticipated rate of $\sim 1$ events per year. The combination of angular size data with known physical dimensions enables accurate distance determination. Multiple telescope pairs at different relative positions allow tomographic mapping of the ejecta structure while reducing distance uncertainties. As Type Ia supernovae serve as standardizable candles for measuring the Universe's expansion history, combining intensity interferometry distances with the supernova Hubble diagram facilitates measurements of the Hubble constant $H_0$.
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Submitted 10 April, 2025; v1 submitted 10 March, 2025;
originally announced March 2025.
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Generalized framework for likelihood-based field-level inference of growth rate from velocity and density fields
Authors:
Corentin Ravoux,
Bastien Carreres,
Damiano Rosselli,
Julian Bautista,
Anthony Carr,
Tyann Dummerchat,
Alex G. Kim,
David Parkinson,
Benjamin Racine,
Dominique Fouchez,
Fabrice Feinstein
Abstract:
Measuring the growth rate of large-scale structures (f) as a function of redshift has the potential to break degeneracies between modified gravity and dark energy models, when combined with expansion-rate probes. Direct estimates of peculiar velocities of galaxies have attracted interest as a means of estimating $fσ_8$. In particular, field-level methods can be used to fit the field nuisance param…
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Measuring the growth rate of large-scale structures (f) as a function of redshift has the potential to break degeneracies between modified gravity and dark energy models, when combined with expansion-rate probes. Direct estimates of peculiar velocities of galaxies have attracted interest as a means of estimating $fσ_8$. In particular, field-level methods can be used to fit the field nuisance parameter along with cosmological parameters simultaneously. This article aims to provide the community with a unified framework for the theoretical modeling of the likelihood-based field-level inference by performing fast field covariance calculations for velocity and density fields. Our purpose is to lay the foundations for a nonlinear extension of the likelihood-based method at the field level. We have developed a generalized framework, implemented in the dedicated software flip to perform a likelihood-based inference of $fσ_8$. We derived a new field covariance model, which includes wide-angle corrections. We also included the models previously described in the literature inside our framework. We compared their performance against ours, and we validated our model by comparing it with the two-point statistics of a recent N-body simulation. The tests we performed have allowed us to validate our software and determine the appropriate wavenumber range to integrate our covariance model and its validity in terms of separation. Our framework allows for a wider wavenumber coverage to be used in our calculations than in previous works. Finally, our generalized framework allows us to efficiently perform a survey geometry-dependent Fisher forecast of the $fσ_8$ parameter. We show that the Fisher forecast method we developed gives an error bar that is 30 % closer to a full likelihood-based estimation than a standard volume Fisher forecast.
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Submitted 21 November, 2025; v1 submitted 28 January, 2025;
originally announced January 2025.
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The rate of extreme coronal line emitters in the Baryon Oscillation Spectroscopic Survey LOWZ sample
Authors:
Joseph Callow,
Or Graur,
Peter Clark,
Alex G. Kim,
Brendan O'Connor,
Jessica Aguilar,
Steven Ahlen,
Davide Bianchi,
David Brooks,
Axel de la Macorra,
Arjun Dey,
Peter Doel,
Jaime E. Forero-Romero,
Enrique Gaztañaga,
Satya Gontcho A Gontcho,
Gaston Gutierrez,
Robert Kehoe,
Andrew Lambert,
Martin Landriau,
Laurent Le Guillou,
Aaron Meisner,
Ramon Miquel,
John Moustakas,
Francisco Prada,
Ignasi Pérez-Ràfols
, et al. (8 additional authors not shown)
Abstract:
Extreme coronal line emitters (ECLEs) are a rare class of galaxy that exhibit strong, high-ionization iron coronal emission lines in their spectra. In some cases, these lines are transient and may be the result of tidal disruption event (TDEs). To test this connection, we calculate the rate of variable ECLEs (vECLEs) at redshift $\sim0.3$. We search for ECLEs in the Baryon Oscillation Spectroscopi…
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Extreme coronal line emitters (ECLEs) are a rare class of galaxy that exhibit strong, high-ionization iron coronal emission lines in their spectra. In some cases, these lines are transient and may be the result of tidal disruption event (TDEs). To test this connection, we calculate the rate of variable ECLEs (vECLEs) at redshift $\sim0.3$. We search for ECLEs in the Baryon Oscillation Spectroscopic Survey (BOSS) LOWZ sample and discover two candidate ECLEs. Using follow-up spectra from the Dark Energy Spectroscopic Instrument and Gemini Multi-Object Spectrograph, and mid-infrared observations from the Wide-field Infrared Survey Explorer, we determine that one of these galaxies is a vECLE. Using this galaxy, we calculate the galaxy-normalized vECLE rate at redshift $\sim0.3$ to be $R_\mathrm{G}=1.6~^{+3.8}_{-1.4}\times10^{-6}~\mathrm{galaxy}^{-1}~\mathrm{yr}^{-1}$ and the mass-normalized rate to be $R_\mathrm{M}=7~^{+16}_{-6}\times10^{-18}~\mathrm{M_\odot^{-1}}~\mathrm{yr}^{-1}$. This is then converted to a volumetric rate of $R_\mathrm{V}=1.8~^{+4.5}_{-1.5}\times10^{-9}~\mathrm{Mpc}^{-3}~\mathrm{yr}^{-1}$. Formally, the LOWZ vECLE rates are $2-4$ times lower than the rates calculated from the Sloan Digital Sky Survey Legacy sample at redshift $\sim0.1$. However, given the large uncertainties on both measurements, they are consistent with each other at $1σ$. Both the galaxy-normalized and volumetric rates are one to two orders of magnitude lower than TDE rates from the literature, consistent with vECLEs being caused by $5-20$ per cent of all TDEs.
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Submitted 25 March, 2025; v1 submitted 23 January, 2025;
originally announced January 2025.
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Detection of Unresolved Strongly Lensed Supernovae with 7-Dimensional Telescope
Authors:
Elahe Khalouei,
Arman Shafieloo,
Alex G. Kim,
Ryan E. Keeley,
William Sheu,
Gregory S. H. Paek,
Myungshin Im,
Xiaosheng Huang,
Hyung Mok Lee
Abstract:
Gravitationally lensed supernovae (glSNe) are a powerful tool for exploring the realms of astronomy and cosmology. Time-delay measurements and lens modeling of glSNe can provide a robust and independent method for constraining the expansion rate of the universe. The study of unresolved glSNe light curves presents a unique opportunity for utilizing small telescopes to investigate these systems. In…
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Gravitationally lensed supernovae (glSNe) are a powerful tool for exploring the realms of astronomy and cosmology. Time-delay measurements and lens modeling of glSNe can provide a robust and independent method for constraining the expansion rate of the universe. The study of unresolved glSNe light curves presents a unique opportunity for utilizing small telescopes to investigate these systems. In this work, we investigate diverse observational strategies for the initial detection of glSNe using the 7-Dimensional Telescope (7DT), a multitelescope system composed of twenty 50-cm telescopes. We implement different observing strategies on a subset of 5807 strong lensing systems and candidates identified within the Dark Energy Camera Legacy Survey (DECaLS), as reported in various publications. Our simulations under ideal observing conditions indicate the maximum expected annual detection rates for various glSNe types (Type Ia and core-collapse (CC)) using the 7DT target observing mode in the $r$-band at a depth of 22.04 mag, as follows: 7.46 events for type Ia, 2.49 for type Ic, 0.8 for type IIb, 0.52 for type IIL, 0.78 for type IIn, 3.75 for type IIP, and 1.15 for type Ib. Furthermore, in the case of medium-band filter observations (m6000) at a depth of 20.61 in the Wide-field Time-domain Survey (WTS)program, the predicted detection rate for glSNe Ia is 2.53 $yr^{-1}$. Given targeted follow-up observations of these initially detected systems with more powerful telescopes, we can apply a model-independent approach to forecast the ability to measure $H_{0}$ using a Gaussian process from Type Ia Supernovae (SNe Ia) data and time-delay distance information derived from glSNe systems, which include both Ia and CC types. We forecast that the expected detection rate of glSNe systems can achieve a $2.7\%$ precision in estimating the $H_{0}$.
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Submitted 30 April, 2025; v1 submitted 21 January, 2025;
originally announced January 2025.
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Comments on the Union3 "Spline-Interpolated Distance Moduli" Model
Authors:
Alex G. Kim
Abstract:
The Union3 "Spline-Interpolated Distance Moduli" model posterior has been distributed for third-party cosmology analysis. The posterior prefers a large value of $Ω_M$, a small absolute value of $w_0$, and a negative $w_a$, but still accommodates $Λ$CDM; the supernova data alone are not strongly constraining. The posterior is built assuming an underlying model and prior, both of which must be made…
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The Union3 "Spline-Interpolated Distance Moduli" model posterior has been distributed for third-party cosmology analysis. The posterior prefers a large value of $Ω_M$, a small absolute value of $w_0$, and a negative $w_a$, but still accommodates $Λ$CDM; the supernova data alone are not strongly constraining. The posterior is built assuming an underlying model and prior, both of which must be made to conform with any new model and prior being analyzed. The posterior is calculated for a prior that is not flat but rather has non-trivial structure in $Ω_M$-$w_0$-$w_a$; the associated likelihood is slightly shifted relative to the posterior. The posterior for a prior that is flat in $Ω_M$-$w_0$-$w_a$ is also shifted relative to the original, but not at a level that is statistically significant. The misapplication of Union3 results in the "DESI2024 VI" cosmology fits are inconsequential.
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Submitted 4 December, 2024;
originally announced December 2024.
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DESI Peculiar Velocity Survey -- Fundamental Plane
Authors:
Khaled Said,
Cullan Howlett,
Tamara Davis,
John Lucey,
Christoph Saulder,
Kelly Douglass,
Alex G. Kim,
Anthony Kremin,
Caitlin Ross,
Greg Aldering,
Jessica Nicole Aguilar,
Steven Ahlen,
Segev BenZvi,
Davide Bianchi,
David Brooks,
Todd Claybaugh,
Kyle Dawson,
Axel de la Macorra,
Biprateep Dey,
Peter Doel,
Kevin Fanning,
Simone Ferraro,
Andreu Font-Ribera,
Jaime E. Forero-Romero,
Enrique Gaztañaga
, et al. (30 additional authors not shown)
Abstract:
The Dark Energy Spectroscopic Instrument (DESI) Peculiar Velocity Survey aims to measure the peculiar velocities of early and late type galaxies within the DESI footprint using both the Fundamental Plane and optical Tully-Fisher relations. Direct measurements of peculiar velocities can significantly improve constraints on the growth rate of structure, reducing uncertainty by a factor of approximat…
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The Dark Energy Spectroscopic Instrument (DESI) Peculiar Velocity Survey aims to measure the peculiar velocities of early and late type galaxies within the DESI footprint using both the Fundamental Plane and optical Tully-Fisher relations. Direct measurements of peculiar velocities can significantly improve constraints on the growth rate of structure, reducing uncertainty by a factor of approximately 2.5 at redshift 0.1 compared to the DESI Bright Galaxy Survey's redshift space distortion measurements alone. We assess the quality of stellar velocity dispersion measurements from DESI spectroscopic data. These measurements, along with photometric data from the Legacy Survey, establish the Fundamental Plane relation and determine distances and peculiar velocities of early-type galaxies. During Survey Validation, we obtain spectra for 6698 unique early-type galaxies, up to a photometric redshift of 0.15. 64\% of observed galaxies (4267) have relative velocity dispersion errors below 10\%. This percentage increases to 75\% if we restrict our sample to galaxies with spectroscopic redshifts below 0.1. We use the measured central velocity dispersion, along with photometry from the DESI Legacy Imaging Surveys, to fit the Fundamental Plane parameters using a 3D Gaussian maximum likelihood algorithm that accounts for measurement uncertainties and selection cuts. In addition, we conduct zero-point calibration using the absolute distance measurements to the Coma cluster, leading to a value of the Hubble constant, $H_0 = 76.05 \pm 0.35$(statistical) $\pm 0.49$(systematic FP) $\pm 4.86$(statistical due to calibration) $\mathrm{km \ s^{-1} Mpc^{-1}}$. This $H_0$ value is within $2σ$ of Planck Cosmic Microwave Background results and within $1σ$, of other low redshift distance indicator-based measurements.
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Submitted 30 April, 2025; v1 submitted 25 August, 2024;
originally announced August 2024.
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Candidate strongly lensed type Ia supernovae in the Zwicky Transient Facility archive
Authors:
A. Townsend,
J. Nordin,
A. Sagués Carracedo,
M. Kowalski,
N. Arendse,
S. Dhawan,
A. Goobar,
J. Johansson,
E. Mörtsell,
S. Schulze,
I. Andreoni,
E. Fernández,
A. G. Kim,
P. E. Nugent,
F. Prada,
M. Rigault,
N. Sarin,
D. Sharma,
E. C. Bellm,
M. W. Coughlin,
R. Dekany,
S. L. Groom,
L. Lacroix,
R. R. Laher,
R. Riddle
, et al. (39 additional authors not shown)
Abstract:
Gravitationally lensed type Ia supernovae (glSNe Ia) are unique astronomical tools that can be used to study cosmological parameters, distributions of dark matter, the astrophysics of the supernovae, and the intervening lensing galaxies themselves. A small number of highly magnified glSNe Ia have been discovered by ground-based telescopes such as the Zwicky Transient Facility (ZTF), but simulation…
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Gravitationally lensed type Ia supernovae (glSNe Ia) are unique astronomical tools that can be used to study cosmological parameters, distributions of dark matter, the astrophysics of the supernovae, and the intervening lensing galaxies themselves. A small number of highly magnified glSNe Ia have been discovered by ground-based telescopes such as the Zwicky Transient Facility (ZTF), but simulations predict that a fainter population may also exist. We present a systematic search for glSNe Ia in the ZTF archive of alerts distributed from June 1 2019 to September 1 2022. Using the AMPEL platform, we developed a pipeline that distinguishes candidate glSNe Ia from other variable sources. Initial cuts were applied to the ZTF alert photometry before forced photometry was obtained for the remaining candidates. Additional cuts were applied to refine the candidates based on their light curve colours, lens galaxy colours, and the resulting parameters from fits to the SALT2 SN Ia template. The candidates were also cross-matched with the DESI spectroscopic catalogue. Seven transients were identified that had an associated galaxy DESI redshift, which we present as glSN Ia candidates. Although superluminous supernovae (SLSNe) cannot be fully rejected as contaminants, two events, ZTF19abpjicm and ZTF22aahmovu, are significantly different from typical SLSNe and their light curves can be modelled as two-image glSN Ia systems. From this two-image modelling, we estimate time delays of 22 $\pm$ 3 and 34 $\pm$ 1 days for the two events, respectively, which suggests that we have uncovered a population of glSNe Ia with longer time delays. The pipeline is currently being applied to the live ZTF alert stream to identify and follow-up future candidates while active, and it could be the foundation for glSNe Ia searches in future surveys, such as the Rubin Observatory Legacy Survey of Space and Time.
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Submitted 25 January, 2025; v1 submitted 28 May, 2024;
originally announced May 2024.
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DESI 2024: Reconstructing Dark Energy using Crossing Statistics with DESI DR1 BAO data
Authors:
R. Calderon,
K. Lodha,
A. Shafieloo,
E. Linder,
W. Sohn,
A. de Mattia,
J. L. Cervantes-Cota,
R. Crittenden,
T. M. Davis,
M. Ishak,
A. G. Kim,
W. Matthewson,
G. Niz,
S. Park,
J. Aguilar,
S. Ahlen,
S. Allen,
D. Brooks,
T. Claybaugh,
A. de la Macorra,
A. Dey,
B. Dey,
P. Doel,
J. E. Forero-Romero,
E. Gaztañaga
, et al. (30 additional authors not shown)
Abstract:
We implement Crossing Statistics to reconstruct in a model-agnostic manner the expansion history of the universe and properties of dark energy, using DESI Data Release 1 (DR1) BAO data in combination with one of three different supernova compilations (PantheonPlus, Union3, and DES-SN5YR) and Planck CMB observations. Our results hint towards an evolving and emergent dark energy behaviour, with negl…
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We implement Crossing Statistics to reconstruct in a model-agnostic manner the expansion history of the universe and properties of dark energy, using DESI Data Release 1 (DR1) BAO data in combination with one of three different supernova compilations (PantheonPlus, Union3, and DES-SN5YR) and Planck CMB observations. Our results hint towards an evolving and emergent dark energy behaviour, with negligible presence of dark energy at $z\gtrsim 1$, at varying significance depending on the data sets combined. In all these reconstructions, the cosmological constant lies outside the $95\%$ confidence intervals for some redshift ranges. This dark energy behaviour, reconstructed using Crossing Statistics, is in agreement with results from the conventional $w_0$--$w_a$ dark energy equation of state parametrization reported in the DESI Key cosmology paper. Our results add an extensive class of model-agnostic reconstructions with acceptable fits to the data, including models where cosmic acceleration slows down at low redshifts. We also report constraints on $H_0r_d$ from our model-agnostic analysis, independent of the pre-recombination physics.
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Submitted 25 October, 2024; v1 submitted 7 May, 2024;
originally announced May 2024.
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The MOST Hosts Survey: spectroscopic observation of the host galaxies of ~40,000 transients using DESI
Authors:
Maayane T. Soumagnac,
Peter Nugent,
Robert A. Knop,
Anna Y. Q. Ho,
William Hohensee,
Autumn Awbrey,
Alexis Andersen,
Greg Aldering,
Matan Ventura,
Jessica N. Aguilar,
Steven Ahlen,
Segev Y. Benzvi,
David Brooks,
Dillon Brout,
Todd Claybaugh,
Tamara M. Davis,
Kyle Dawson,
Axel de la Macorra,
Arjun Dey,
Biprateep Dey,
Peter Doel,
Kelly A. Douglass,
Jaime E. Forero-Romero,
Enrique Gaztanaga,
Satya Gontcho A Gontcho
, et al. (32 additional authors not shown)
Abstract:
We present the MOST Hosts survey (Multi-Object Spectroscopy of Transient Hosts). The survey is planned to run throughout the five years of operation of the Dark Energy Spectroscopic Instrument (DESI) and will generate a spectroscopic catalog of the hosts of most transients observed to date, in particular all the supernovae observed by most public, untargeted, wide-field, optical surveys (PTF/iPTF,…
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We present the MOST Hosts survey (Multi-Object Spectroscopy of Transient Hosts). The survey is planned to run throughout the five years of operation of the Dark Energy Spectroscopic Instrument (DESI) and will generate a spectroscopic catalog of the hosts of most transients observed to date, in particular all the supernovae observed by most public, untargeted, wide-field, optical surveys (PTF/iPTF, SDSS II, ZTF, DECAT, DESIRT). Scientific questions for which the MOST Hosts survey will be useful include Type Ia supernova cosmology, fundamental plane and peculiar velocity measurements, and the understanding of the correlations between transients and their host galaxy properties. Here, we present the first release of the MOST Hosts survey: 21,931 hosts of 20,235 transients. These numbers represent 36% of the final MOST Hosts sample, consisting of 60,212 potential host galaxies of 38,603 transients (a transient can be assigned multiple potential hosts). Of these galaxies, 40% do not appear in the DESI primary target list and therefore require a specific program like MOST Hosts. Of all the transients in the MOST Hosts list, only 26.7% have existing classifications, and so the survey will provide redshifts (and luminosities) for nearly 30,000 transients. A preliminary Hubble diagram and a transient luminosity-duration diagram are shown as examples of future potential uses of the MOST Hosts survey. The survey will also provide a training sample of spectroscopically observed transients for photometry-only classifiers, as we enter an era when most newly observed transients will lack spectroscopic classification. The MOST Hosts DESI survey data will be released through the Wiserep platform on a rolling cadence and updated to match the DESI releases. Dates of future releases and updates are available through the https://mosthosts.desi.lbl.gov website.
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Submitted 6 May, 2024;
originally announced May 2024.
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The Dark Energy Survey: Cosmology Results With ~1500 New High-redshift Type Ia Supernovae Using The Full 5-year Dataset
Authors:
DES Collaboration,
T. M. C. Abbott,
M. Acevedo,
M. Aguena,
A. Alarcon,
S. Allam,
O. Alves,
A. Amon,
F. Andrade-Oliveira,
J. Annis,
P. Armstrong,
J. Asorey,
S. Avila,
D. Bacon,
B. A. Bassett,
K. Bechtol,
P. H. Bernardinelli,
G. M. Bernstein,
E. Bertin,
J. Blazek,
S. Bocquet,
D. Brooks,
D. Brout,
E. Buckley-Geer,
D. L. Burke
, et al. (134 additional authors not shown)
Abstract:
We present cosmological constraints from the sample of Type Ia supernovae (SN Ia) discovered during the full five years of the Dark Energy Survey (DES) Supernova Program. In contrast to most previous cosmological samples, in which SN are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscop…
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We present cosmological constraints from the sample of Type Ia supernovae (SN Ia) discovered during the full five years of the Dark Energy Survey (DES) Supernova Program. In contrast to most previous cosmological samples, in which SN are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscopic redshifts are acquired from a dedicated follow-up survey of the host galaxies. After accounting for the likelihood of each SN being a SN Ia, we find 1635 DES SNe in the redshift range $0.10<z<1.13$ that pass quality selection criteria sufficient to constrain cosmological parameters. This quintuples the number of high-quality $z>0.5$ SNe compared to the previous leading compilation of Pantheon+, and results in the tightest cosmological constraints achieved by any SN data set to date. To derive cosmological constraints we combine the DES supernova data with a high-quality external low-redshift sample consisting of 194 SNe Ia spanning $0.025<z<0.10$. Using SN data alone and including systematic uncertainties we find $Ω_{\rm M}=0.352\pm 0.017$ in flat $Λ$CDM. Supernova data alone now require acceleration ($q_0<0$ in $Λ$CDM) with over $5σ$ confidence. We find $(Ω_{\rm M},w)=(0.264^{+0.074}_{-0.096},-0.80^{+0.14}_{-0.16})$ in flat $w$CDM. For flat $w_0w_a$CDM, we find $(Ω_{\rm M},w_0,w_a)=(0.495^{+0.033}_{-0.043},-0.36^{+0.36}_{-0.30},-8.8^{+3.7}_{-4.5})$. Including Planck CMB data, SDSS BAO data, and DES $3\times2$-point data gives $(Ω_{\rm M},w)=(0.321\pm0.007,-0.941\pm0.026)$. In all cases dark energy is consistent with a cosmological constant to within $\sim2σ$. In our analysis, systematic errors on cosmological parameters are subdominant compared to statistical errors; paving the way for future photometrically classified supernova analyses.
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Submitted 20 July, 2025; v1 submitted 5 January, 2024;
originally announced January 2024.
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Union Through UNITY: Cosmology with 2,000 SNe Using a Unified Bayesian Framework
Authors:
David Rubin,
Greg Aldering,
Marc Betoule,
Andy Fruchter,
Xiaosheng Huang,
Alex G. Kim,
Chris Lidman,
Eric Linder,
Saul Perlmutter,
Pilar Ruiz-Lapuente,
Nao Suzuki
Abstract:
Type Ia supernovae (SNe Ia) were instrumental in establishing the acceleration of the universe's expansion. By virtue of their combination of distance reach, precision, and prevalence, they continue to provide key cosmological constraints, complementing other cosmological probes. Individual SN surveys cover only over about a factor of two in redshift, so compilations of multiple SN datasets are st…
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Type Ia supernovae (SNe Ia) were instrumental in establishing the acceleration of the universe's expansion. By virtue of their combination of distance reach, precision, and prevalence, they continue to provide key cosmological constraints, complementing other cosmological probes. Individual SN surveys cover only over about a factor of two in redshift, so compilations of multiple SN datasets are strongly beneficial. We assemble an up-to-date "Union" compilation of 2087 cosmologically useful SNe Ia from 24 datasets ("Union3"). We take care to put all SNe on the same distance scale and update the light-curve fitting with SALT3 to use the full rest-frame optical. Over the next few years, the number of cosmologically useful SNe Ia will increase by more than a factor of ten, and keeping systematic uncertainties subdominant will be more challenging than ever. We discuss the importance of treating outliers, selection effects, light-curve shape and color populations and standardization relations, unexplained dispersion, and heterogeneous observations simultaneously. We present an updated Bayesian framework, called UNITY1.5 (Unified Nonlinear Inference for Type-Ia cosmologY), that incorporates significant improvements in our ability to model selection effects, standardization, and systematic uncertainties compared to earlier analyses. As an analysis byproduct, we also recover the posterior of the SN-only peculiar-velocity field, although we do not interpret it in this work. We compute updated cosmological constraints with Union3 and UNITY1.5, finding weak 1.7--2.6 sigma tension with LambdaCDM and possible evidence for thawing dark energy (w0 > -1, wa < 0). We release our SN distances, light-curve fits, and UNITY1.5 framework to the community.
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Submitted 20 June, 2025; v1 submitted 20 November, 2023;
originally announced November 2023.
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Fast and efficient identification of anomalous galaxy spectra with neural density estimation
Authors:
Vanessa Böhm,
Alex G. Kim,
Stéphanie Juneau
Abstract:
Current large-scale astrophysical experiments produce unprecedented amounts of rich and diverse data. This creates a growing need for fast and flexible automated data inspection methods. Deep learning algorithms can capture and pick up subtle variations in rich data sets and are fast to apply once trained. Here, we study the applicability of an unsupervised and probabilistic deep learning framewor…
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Current large-scale astrophysical experiments produce unprecedented amounts of rich and diverse data. This creates a growing need for fast and flexible automated data inspection methods. Deep learning algorithms can capture and pick up subtle variations in rich data sets and are fast to apply once trained. Here, we study the applicability of an unsupervised and probabilistic deep learning framework, the Probabilistic Autoencoder (PAE), to the detection of peculiar objects in galaxy spectra from the SDSS survey. Different to supervised algorithms, this algorithm is not trained to detect a specific feature or type of anomaly, instead it learns the complex and diverse distribution of galaxy spectra from training data and identifies outliers with respect to the learned distribution. We find that the algorithm assigns consistently lower probabilities (higher anomaly score) to spectra that exhibit unusual features. For example, the majority of outliers among quiescent galaxies are E+A galaxies, whose spectra combine features from old and young stellar population. Other identified outliers include LINERs, supernovae and overlapping objects. Conditional modeling further allows us to incorporate additional information. Namely, we evaluate the probability of an object being anomalous given a certain spectral class, but other information such as metrics of data quality or estimated redshift could be incorporated as well. We make our code publicly available at https://github.com/VMBoehm/Spectra_PAE
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Submitted 1 August, 2023;
originally announced August 2023.
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Probing the Consistency of Cosmological Contours for Supernova Cosmology
Authors:
P. Armstrong,
H. Qu,
D. Brout,
T. M. Davis,
R. Kessler,
A. G. Kim,
C. Lidman,
M. Sako,
B. E. Tucker
Abstract:
As the scale of cosmological surveys increases, so does the complexity in the analyses. This complexity can often make it difficult to derive the underlying principles, necessitating statistically rigorous testing to ensure the results of an analysis are consistent and reasonable. This is particularly important in multi-probe cosmological analyses like those used in the Dark Energy Survey and the…
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As the scale of cosmological surveys increases, so does the complexity in the analyses. This complexity can often make it difficult to derive the underlying principles, necessitating statistically rigorous testing to ensure the results of an analysis are consistent and reasonable. This is particularly important in multi-probe cosmological analyses like those used in the Dark Energy Survey and the upcoming Legacy Survey of Space and Time, where accurate uncertainties are vital. In this paper, we present a statistically rigorous method to test the consistency of contours produced in these analyses, and apply this method to the Pippin cosmological pipeline used for Type Ia supernova cosmology with the Dark Energy Survey. We make use of the Neyman construction, a frequentist methodology that leverages extensive simulations to calculate confidence intervals, to perform this consistency check. A true Neyman construction is too computationally expensive for supernova cosmology, so we develop a method for approximating a Neyman construction with far fewer simulations. We find that for a simulated data-set, the 68% contour reported by the Pippin pipeline and the 68% confidence region produced by our approximate Neyman construction differ by less than a percent near the input cosmology, however show more significant differences far from the input cosmology, with a maximal difference of 0.05 in $Ω_{M}$, and 0.07 in $w$. This divergence is most impactful for analyses of cosmological tensions, but its impact is mitigated when combining supernovae with other cross-cutting cosmological probes, such as the Cosmic Microwave Background.
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Submitted 25 July, 2023;
originally announced July 2023.
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Target Selection for the DESI Peculiar Velocity Survey
Authors:
Christoph Saulder,
Cullan Howlett,
Kelly A. Douglass,
Khaled Said,
Segev BenZvi,
Steven Ahlen,
Greg Aldering,
Stephen Bailey,
David Brooks,
Tamara Davis,
Axel de la Macorra,
Arjun Dey,
Andreu Font-Ribera,
Jaime E. Forero-Romero,
Satya Gontcho A Gontcho,
Klaus Honscheid,
Alex G. Kim,
Theodore Kisner,
Anthony Kremin,
Martin Landriau,
Michael E. Levi,
John Lucey,
Aaron M. Meisner,
Ramon Miquel,
John Moustakas
, et al. (13 additional authors not shown)
Abstract:
We describe the target selection and characteristics of the DESI Peculiar Velocity Survey, the largest survey of peculiar velocities (PVs) using both the fundamental plane (FP) and the Tully-Fisher (TF) relationship planned to date. We detail how we identify suitable early-type galaxies (ETGs) for the FP and suitable late-type galaxies (LTGs) for the TF relation using the photometric data provided…
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We describe the target selection and characteristics of the DESI Peculiar Velocity Survey, the largest survey of peculiar velocities (PVs) using both the fundamental plane (FP) and the Tully-Fisher (TF) relationship planned to date. We detail how we identify suitable early-type galaxies (ETGs) for the FP and suitable late-type galaxies (LTGs) for the TF relation using the photometric data provided by the DESI Legacy Imaging Survey DR9. Subsequently, we provide targets for 373 533 ETGs and 118 637 LTGs within the DESI 5-year footprint. We validate these photometric selections using existing morphological classifications. Furthermore, we demonstrate using survey validation data that DESI is able to measure the spectroscopic properties to sufficient precision to obtain PVs for our targets. Based on realistic DESI fiber assignment simulations and spectroscopic success rates, we predict the final DESI PV Survey will obtain $\sim$133 000 FP-based and $\sim$53 000 TF-based PV measurements over an area of 14 000 $\mathrm{deg^{2}}$. We forecast the ability of using these data to measure the clustering of galaxy positions and PVs from the combined DESI PV and Bright Galaxy Surveys (BGS), which allows for cancellation of cosmic variance at low redshifts. With these forecasts, we anticipate a $4\%$ statistical measurement on the growth rate of structure at $z<0.15$. This is over two times better than achievable with redshifts from the BGS alone. The combined DESI PV and BGS will enable the most precise tests to date of the time and scale dependence of large-scale structure growth at $z<0.15$.
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Submitted 28 July, 2023; v1 submitted 27 February, 2023;
originally announced February 2023.
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Reconstructing and Classifying SDSS DR16 Galaxy Spectra with Machine-Learning and Dimensionality Reduction Algorithms
Authors:
Felix Pat,
Stéphanie Juneau,
Vanessa Böhm,
Ragadeepika Pucha,
A. G. Kim,
A. S. Bolton,
Cleo Lepart,
Dylan Green,
Adam D. Myers
Abstract:
Optical spectra of galaxies and quasars from large cosmological surveys are used to measure redshifts and infer distances. They are also rich with information on the intrinsic properties of these astronomical objects. However, their physical interpretation can be challenging due to the substantial number of degrees of freedom, various sources of noise, and degeneracies between physical parameters…
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Optical spectra of galaxies and quasars from large cosmological surveys are used to measure redshifts and infer distances. They are also rich with information on the intrinsic properties of these astronomical objects. However, their physical interpretation can be challenging due to the substantial number of degrees of freedom, various sources of noise, and degeneracies between physical parameters that cause similar spectral characteristics. To gain deeper insights into these degeneracies, we apply two unsupervised machine learning frameworks to a sample from the Sloan Digital Sky Survey data release 16 (SDSS DR16). The first framework is a Probabilistic Auto-Encoder (PAE), a two-stage deep learning framework consisting of a data compression stage from 1000 elements to 10 parameters and a density estimation stage. The second framework is a Uniform Manifold Approximation and Projection (UMAP), which we apply to both the uncompressed and compressed data. Exploring across regions on the compressed data UMAP, we construct sequences of stacked spectra which show a gradual transition from star-forming galaxies with narrow emission lines and blue spectra to passive galaxies with absorption lines and red spectra. Focusing on galaxies with broad emission lines produced by quasars, we find a sequence with varying levels of obscuration caused by cosmic dust. The experiments we present here inform future applications of neural networks and dimensionality reduction algorithms for large astronomical spectroscopic surveys.
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Submitted 21 November, 2022;
originally announced November 2022.
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Bump Morphology of the CMAGIC Diagram
Authors:
L. Aldoroty,
L. Wang,
P. Hoeflich,
J. Yang,
N. Suntzeff,
G. Aldering,
P. Antilogus,
C. Aragon,
S. Bailey,
C. Baltay,
S. Bongard,
K. Boone,
C. Buton,
Y. Copin,
S. Dixon,
D. Fouchez,
E. Gangler,
R. Gupta,
B. Hayden,
Mitchell Karmen,
A. G. Kim,
M. Kowalski,
D. Küsters,
P. -F. Léget,
F. Mondon
, et al. (16 additional authors not shown)
Abstract:
We apply the color-magnitude intercept calibration method (CMAGIC) to the Nearby Supernova Factory SNe Ia spectrophotometric dataset. The currently existing CMAGIC parameters are the slope and intercept of a straight line fit to the first linear region in the color-magnitude diagram, which occurs over a span of approximately 30 days after maximum brightness. We define a new parameter, $ω_{XY}$, th…
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We apply the color-magnitude intercept calibration method (CMAGIC) to the Nearby Supernova Factory SNe Ia spectrophotometric dataset. The currently existing CMAGIC parameters are the slope and intercept of a straight line fit to the first linear region in the color-magnitude diagram, which occurs over a span of approximately 30 days after maximum brightness. We define a new parameter, $ω_{XY}$, the size of the ``bump'' feature near maximum brightness for arbitrary filters $X$ and $Y$. We find a significant correlation between the slope of the first linear region, $β_{XY, 1}$, in the CMAGIC diagram and $ω_{XY}$. These results may be used to our advantage, as they are less affected by extinction than parameters defined as a function of time. Additionally, $ω_{XY}$ is computed independently of templates. We find that current empirical templates are successful at reproducing the features described in this work, particularly SALT3, which correctly exhibits the negative correlation between slope and bump size seen in our data. In 1-D simulations, we show that the correlation between the size of the bump feature and $β_{XY, 1}$ can be understood as a result of chemical mixing due to large-scale Rayleigh-Taylor instabilities.
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Submitted 22 June, 2023; v1 submitted 13 October, 2022;
originally announced October 2022.
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Report of the Topical Group on Dark Energy and Cosmic Acceleration: Complementarity of Probes and New Facilities for Snowmass 2021
Authors:
Brenna Flaugher,
Vivian Miranda,
David J. Schlegel,
Adam J. Anderson,
Felipe Andrade-Oliveira,
Eric J. Baxter,
Amy N. Bender,
Lindsey E. Bleem,
Chihway Chang,
Clarence C. Chang,
Thomas Y. Chen,
Kyle S. Dawson,
Seth W. Digel,
Alex Drlica-Wagner,
Simone Ferraro,
Alyssa Garcia,
Katrin Heitmann,
Alex G. Kim,
Eric V. Linder,
Sayan Mandal,
Rachel Mandelbaum,
Phil Marshall,
Joel Meyers,
Laura Newburgh,
Peter E. Nugent
, et al. (5 additional authors not shown)
Abstract:
The mechanism(s) driving the early- and late-time accelerated expansion of the Universe represent one of the most compelling mysteries in fundamental physics today. The path to understanding the causes of early- and late-time acceleration depends on fully leveraging ongoing surveys, developing and demonstrating new technologies, and constructing and operating new instruments. This report presents…
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The mechanism(s) driving the early- and late-time accelerated expansion of the Universe represent one of the most compelling mysteries in fundamental physics today. The path to understanding the causes of early- and late-time acceleration depends on fully leveraging ongoing surveys, developing and demonstrating new technologies, and constructing and operating new instruments. This report presents a multi-faceted vision for the cosmic survey program in the 2030s and beyond that derives from these considerations. Cosmic surveys address a wide range of fundamental physics questions, and are thus a unique and powerful component of the HEP experimental portfolio.
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Submitted 18 September, 2022;
originally announced September 2022.
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The MegaMapper: A Stage-5 Spectroscopic Instrument Concept for the Study of Inflation and Dark Energy
Authors:
David J. Schlegel,
Juna A. Kollmeier,
Greg Aldering,
Stephen Bailey,
Charles Baltay,
Christopher Bebek,
Segev BenZvi,
Robert Besuner,
Guillermo Blanc,
Adam S. Bolton,
Ana Bonaca,
Mohamed Bouri,
David Brooks,
Elizabeth Buckley-Geer,
Zheng Cai,
Jeffrey Crane,
Regina Demina,
Joseph DeRose,
Arjun Dey,
Peter Doel,
Xiaohui Fan,
Simone Ferraro,
Douglas Finkbeiner,
Andreu Font-Ribera,
Satya Gontcho A Gontcho
, et al. (64 additional authors not shown)
Abstract:
In this white paper, we present the MegaMapper concept. The MegaMapper is a proposed ground-based experiment to measure Inflation parameters and Dark Energy from galaxy redshifts at $2<z<5$. In order to achieve path-breaking results with a mid-scale investment, the MegaMapper combines existing technologies for critical path elements and pushes innovative development in other design areas. To this…
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In this white paper, we present the MegaMapper concept. The MegaMapper is a proposed ground-based experiment to measure Inflation parameters and Dark Energy from galaxy redshifts at $2<z<5$. In order to achieve path-breaking results with a mid-scale investment, the MegaMapper combines existing technologies for critical path elements and pushes innovative development in other design areas. To this aim, we envision a 6.5-m Magellan-like telescope, with a newly designed wide field, coupled with DESI spectrographs, and small-pitch robots to achieve multiplexing of at least 26,000. This will match the expected achievable target density in the redshift range of interest and provide a 10x capability over the existing state-of the art, without a 10x increase in project budget.
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Submitted 9 September, 2022;
originally announced September 2022.
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A Spectroscopic Road Map for Cosmic Frontier: DESI, DESI-II, Stage-5
Authors:
David J. Schlegel,
Simone Ferraro,
Greg Aldering,
Charles Baltay,
Segev BenZvi,
Robert Besuner,
Guillermo A. Blanc,
Adam S. Bolton,
Ana Bonaca,
David Brooks,
Elizabeth Buckley-Geer,
Zheng Cai,
Joseph DeRose,
Arjun Dey,
Peter Doel,
Alex Drlica-Wagner,
Xiaohui Fan,
Gaston Gutierrez,
Daniel Green,
Julien Guy,
Dragan Huterer,
Leopoldo Infante,
Patrick Jelinsky,
Dionysios Karagiannis,
Stephen M. Kent
, et al. (40 additional authors not shown)
Abstract:
In this white paper, we present an experimental road map for spectroscopic experiments beyond DESI. DESI will be a transformative cosmological survey in the 2020s, mapping 40 million galaxies and quasars and capturing a significant fraction of the available linear modes up to z=1.2. DESI-II will pilot observations of galaxies both at much higher densities and extending to higher redshifts. A Stage…
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In this white paper, we present an experimental road map for spectroscopic experiments beyond DESI. DESI will be a transformative cosmological survey in the 2020s, mapping 40 million galaxies and quasars and capturing a significant fraction of the available linear modes up to z=1.2. DESI-II will pilot observations of galaxies both at much higher densities and extending to higher redshifts. A Stage-5 experiment would build out those high-density and high-redshift observations, mapping hundreds of millions of stars and galaxies in three dimensions, to address the problems of inflation, dark energy, light relativistic species, and dark matter. These spectroscopic data will also complement the next generation of weak lensing, line intensity mapping and CMB experiments and allow them to reach their full potential.
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Submitted 8 September, 2022;
originally announced September 2022.
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A Probabilistic Autoencoder for Type Ia Supernovae Spectral Time Series
Authors:
George Stein,
Uros Seljak,
Vanessa Bohm,
G. Aldering,
P. Antilogus,
C. Aragon,
S. Bailey,
C. Baltay,
S. Bongard,
K. Boone,
C. Buton,
Y. Copin,
S. Dixon,
D. Fouchez,
E. Gangler,
R. Gupta,
B. Hayden,
W. Hillebrandt,
M. Karmen,
A. G. Kim,
M. Kowalski,
D. Kusters,
P. F. Leget,
F. Mondon,
J. Nordin
, et al. (15 additional authors not shown)
Abstract:
We construct a physically-parameterized probabilistic autoencoder (PAE) to learn the intrinsic diversity of type Ia supernovae (SNe Ia) from a sparse set of spectral time series. The PAE is a two-stage generative model, composed of an Auto-Encoder (AE) which is interpreted probabilistically after training using a Normalizing Flow (NF). We demonstrate that the PAE learns a low-dimensional latent sp…
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We construct a physically-parameterized probabilistic autoencoder (PAE) to learn the intrinsic diversity of type Ia supernovae (SNe Ia) from a sparse set of spectral time series. The PAE is a two-stage generative model, composed of an Auto-Encoder (AE) which is interpreted probabilistically after training using a Normalizing Flow (NF). We demonstrate that the PAE learns a low-dimensional latent space that captures the nonlinear range of features that exists within the population, and can accurately model the spectral evolution of SNe Ia across the full range of wavelength and observation times directly from the data. By introducing a correlation penalty term and multi-stage training setup alongside our physically-parameterized network we show that intrinsic and extrinsic modes of variability can be separated during training, removing the need for the additional models to perform magnitude standardization. We then use our PAE in a number of downstream tasks on SNe Ia for increasingly precise cosmological analyses, including automatic detection of SN outliers, the generation of samples consistent with the data distribution, and solving the inverse problem in the presence of noisy and incomplete data to constrain cosmological distance measurements. We find that the optimal number of intrinsic model parameters appears to be three, in line with previous studies, and show that we can standardize our test sample of SNe Ia with an RMS of $0.091 \pm 0.010$ mag, which corresponds to $0.074 \pm 0.010$ mag if peculiar velocity contributions are removed. Trained models and codes are released at \href{https://github.com/georgestein/suPAErnova}{github.com/georgestein/suPAErnova}
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Submitted 15 July, 2022;
originally announced July 2022.
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Uniform Recalibration of Common Spectrophotometry Standard Stars onto the CALSPEC System using the SuperNova Integral Field Spectrograph
Authors:
David Rubin,
G. Aldering,
P. Antilogus,
C. Aragon,
S. Bailey,
C. Baltay,
S. Bongard,
K. Boone,
C. Buton,
Y. Copin,
S. Dixon,
D. Fouchez,
E. Gangler,
R. Gupta,
B. Hayden,
W. Hillebrandt,
A. G. Kim,
M. Kowalski,
D. Kuesters,
P. -F. Leget,
F. Mondon,
J. Nordin,
R. Pain,
E. Pecontal,
R. Pereira
, et al. (13 additional authors not shown)
Abstract:
We calibrate spectrophotometric optical spectra of 32 stars commonly used as standard stars, referenced to 14 stars already on the HST-based CALSPEC flux system. Observations of CALSPEC and non-CALSPEC stars were obtained with the SuperNova Integral Field Spectrograph over the wavelength range 3300 A to 9400 A as calibration for the Nearby Supernova Factory cosmology experiment. In total, this ana…
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We calibrate spectrophotometric optical spectra of 32 stars commonly used as standard stars, referenced to 14 stars already on the HST-based CALSPEC flux system. Observations of CALSPEC and non-CALSPEC stars were obtained with the SuperNova Integral Field Spectrograph over the wavelength range 3300 A to 9400 A as calibration for the Nearby Supernova Factory cosmology experiment. In total, this analysis used 4289 standard-star spectra taken on photometric nights. As a modern cosmology analysis, all pre-submission methodological decisions were made with the flux scale and external comparison results blinded. The large number of spectra per star allows us to treat the wavelength-by-wavelength calibration for all nights simultaneously with a Bayesian hierarchical model, thereby enabling a consistent treatment of the Type Ia supernova cosmology analysis and the calibration on which it critically relies. We determine the typical per-observation repeatability (median 14 mmag for exposures >~ 5 s), the Maunakea atmospheric transmission distribution (median dispersion of 7 mmag with uncertainty 1 mmag), and the scatter internal to our CALSPEC reference stars (median of 8 mmag). We also check our standards against literature filter photometry, finding generally good agreement over the full 12-magnitude range. Overall, the mean of our system is calibrated to the mean of CALSPEC at the level of ~ 3 mmag. With our large number of observations, careful crosschecks, and 14 reference stars, our results are the best calibration yet achieved with an integral-field spectrograph, and among the best calibrated surveys.
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Submitted 21 June, 2022; v1 submitted 2 May, 2022;
originally announced May 2022.
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Snowmass2021 Cosmic Frontier White Paper: Enabling Flagship Dark Energy Experiments to Reach their Full Potential
Authors:
Jonathan A. Blazek,
Doug Clowe,
Thomas E. Collett,
Ian P. Dell'Antonio,
Mark Dickinson,
Lluís Galbany,
Eric Gawiser,
Katrin Heitmann,
Renée Hložek,
Mustapha Ishak,
Saurabh W. Jha,
Alex G. Kim,
C. Danielle Leonard,
Anja von der Linden,
Michelle Lochner,
Rachel Mandelbaum,
Peter Melchior,
Joel Meyers,
Jeffrey A. Newman,
Peter Nugent,
Saul Perlmutter,
Daniel J. Perrefort,
Javier Sánchez,
Samuel J. Schmidt,
Sukhdeep Singh
, et al. (3 additional authors not shown)
Abstract:
A new generation of powerful dark energy experiments will open new vistas for cosmology in the next decade. However, these projects cannot reach their utmost potential without data from other telescopes. This white paper focuses in particular on the compelling benefits of ground-based spectroscopic and photometric observations to complement the Vera C. Rubin Observatory, as well as smaller program…
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A new generation of powerful dark energy experiments will open new vistas for cosmology in the next decade. However, these projects cannot reach their utmost potential without data from other telescopes. This white paper focuses in particular on the compelling benefits of ground-based spectroscopic and photometric observations to complement the Vera C. Rubin Observatory, as well as smaller programs in aid of a DESI-2 experiment and CMB-S4. These additional data sets will both improve dark energy constraints from these flagship projects beyond what would possible on their own and open completely new windows into fundamental physics. For example, additional photometry and single-object spectroscopy will provide necessary follow-up information for supernova and strong lensing cosmology, while highly-multiplexed spectroscopy both from smaller facilities over wide fields and from larger facilities over narrower regions of sky will yield more accurate photometric redshift estimates for weak lensing and galaxy clustering measurements from the Rubin Observatory, provide critical spectroscopic host galaxy redshifts for supernova Hubble diagrams, provide improved understanding of limiting astrophysical systematic effects, and enable new measurements that probe the nature of gravity. A common thread is that access to complementary data from a range of telescopes/instruments would have a substantial impact on the rate of advance of dark energy science in the coming years.
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Submitted 5 April, 2022;
originally announced April 2022.
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Snowmass2021 Cosmic Frontier CF6 White Paper: Multi-Experiment Probes for Dark Energy -- Transients
Authors:
Alex G. Kim,
Antonella Palmese,
Maria E. S. Pereira,
Greg Aldering,
Felipe Andrade-Oliveira,
James Annis,
Stephen Bailey,
Segev BenZvi,
Ulysses Braga-Neto,
Frédéric Courbin,
Alyssa Garcia,
David Jeffery,
Gautham Narayan,
Saul Perlmutter,
Marcelle Soares-Santos,
Tommaso Treu,
Lifan Wang
Abstract:
This invited Snowmass 2021 White Paper highlights the power of joint-analysis of astronomical transients in advancing HEP Science and presents research activities that can realize the opportunities that come with current and upcoming projects. Transients of interest include gravitational wave events, neutrino events, strongly-lensed quasars and supernovae, and Type~Ia supernovae specifically. Thes…
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This invited Snowmass 2021 White Paper highlights the power of joint-analysis of astronomical transients in advancing HEP Science and presents research activities that can realize the opportunities that come with current and upcoming projects. Transients of interest include gravitational wave events, neutrino events, strongly-lensed quasars and supernovae, and Type~Ia supernovae specifically. These transients can serve as probes of cosmological distances in the Universe and as cosmic laboratories of extreme strong-gravity, high-energy physics. Joint analysis refers to work that requires significant coordination from multiple experiments or facilities so encompasses Multi-Messenger Astronomy and optical transient discovery and distributed follow-up programs.
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Submitted 4 October, 2022; v1 submitted 21 March, 2022;
originally announced March 2022.
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Dark Energy Survey Year 3 results: cosmological constraints from the analysis of cosmic shear in harmonic space
Authors:
C. Doux,
B. Jain,
D. Zeurcher,
J. Lee,
X. Fang,
R. Rosenfeld,
A. Amon,
H. Camacho,
A. Choi,
L. F. Secco,
J. Blazek,
C. Chang,
M. Gatti,
E. Gaztanaga,
N. Jeffrey,
M. Raveri,
S. Samuroff,
A. Alarcon,
O. Alves,
F. Andrade-Oliveira,
E. Baxter,
K. Bechtol,
M. R. Becker,
G. M. Bernstein,
A. Campos
, et al. (113 additional authors not shown)
Abstract:
We present cosmological constraints from the analysis of angular power spectra of cosmic shear maps based on data from the first three years of observations by the Dark Energy Survey (DES Y3). Our measurements are based on the pseudo-$C_\ell$ method and offer a view complementary to that of the two-point correlation functions in real space, as the two estimators are known to compress and select Ga…
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We present cosmological constraints from the analysis of angular power spectra of cosmic shear maps based on data from the first three years of observations by the Dark Energy Survey (DES Y3). Our measurements are based on the pseudo-$C_\ell$ method and offer a view complementary to that of the two-point correlation functions in real space, as the two estimators are known to compress and select Gaussian information in different ways, due to scale cuts. They may also be differently affected by systematic effects and theoretical uncertainties, such as baryons and intrinsic alignments (IA), making this analysis an important cross-check. In the context of $Λ$CDM, and using the same fiducial model as in the DES Y3 real space analysis, we find ${S_8 \equiv σ_8 \sqrt{Ω_{\rm m}/0.3} = 0.793^{+0.038}_{-0.025}}$, which further improves to ${S_8 = 0.784\pm 0.026 }$ when including shear ratios. This constraint is within expected statistical fluctuations from the real space analysis, and in agreement with DES~Y3 analyses of non-Gaussian statistics, but favors a slightly higher value of $S_8$, which reduces the tension with the Planck cosmic microwave background 2018 results from $2.3σ$ in the real space analysis to $1.5σ$ in this work. We explore less conservative IA models than the one adopted in our fiducial analysis, finding no clear preference for a more complex model. We also include small scales, using an increased Fourier mode cut-off up to $k_{\rm max}={5}{h{\rm Mpc}^{-1}}$, which allows to constrain baryonic feedback while leaving cosmological constraints essentially unchanged. Finally, we present an approximate reconstruction of the linear matter power spectrum at present time, which is found to be about 20\% lower than predicted by Planck 2018, as reflected by the $1.5σ$ lower $S_8$ value.
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Submitted 14 March, 2022;
originally announced March 2022.
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DeepZipper: A Novel Deep Learning Architecture for Lensed Supernovae Identification
Authors:
Robert Morgan,
B. Nord,
K. Bechtol,
S. J. González,
E. Buckley-Geer,
A. Möller,
J. W. Park,
A. G. Kim,
S. Birrer,
M. Aguena,
J. Annis,
S. Bocquet,
D. Brooks,
A. Carnero Rosell,
M. Carrasco Kind,
J. Carretero,
R. Cawthon,
L. N. da Costa,
T. M. Davis,
J. De Vicente,
P. Doel,
I. Ferrero,
D. Friedel,
J. Frieman,
J. García-Bellido
, et al. (26 additional authors not shown)
Abstract:
Large-scale astronomical surveys have the potential to capture data on large numbers of strongly gravitationally lensed supernovae (LSNe). To facilitate timely analysis and spectroscopic follow-up before the supernova fades, an LSN needs to be identified soon after it begins. To quickly identify LSNe in optical survey datasets, we designed ZipperNet, a multi-branch deep neural network that combine…
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Large-scale astronomical surveys have the potential to capture data on large numbers of strongly gravitationally lensed supernovae (LSNe). To facilitate timely analysis and spectroscopic follow-up before the supernova fades, an LSN needs to be identified soon after it begins. To quickly identify LSNe in optical survey datasets, we designed ZipperNet, a multi-branch deep neural network that combines convolutional layers (traditionally used for images) with long short-term memory (LSTM) layers (traditionally used for time series). We tested ZipperNet on the task of classifying objects from four categories -- no lens, galaxy-galaxy lens, lensed type Ia supernova, lensed core-collapse supernova -- within high-fidelity simulations of three cosmic survey data sets -- the Dark Energy Survey (DES), Rubin Observatory's Legacy Survey of Space and Time (LSST), and a Dark Energy Spectroscopic Instrument (DESI) imaging survey. Among our results, we find that for the LSST-like dataset, ZipperNet classifies LSNe with a receiver operating characteristic area under the curve of 0.97, predicts the spectroscopic type of the lensed supernovae with 79\% accuracy, and demonstrates similarly high performance for LSNe 1-2 epochs after first detection. We anticipate that a model like ZipperNet, which simultaneously incorporates spatial and temporal information, can play a significant role in the rapid identification of lensed transient systems in cosmic survey experiments.
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Submitted 19 May, 2022; v1 submitted 2 December, 2021;
originally announced December 2021.
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Lensing Without Borders. I. A Blind Comparison of the Amplitude of Galaxy-Galaxy Lensing Between Independent Imaging Surveys
Authors:
A. Leauthaud,
A. Amon,
S. Singh,
D. Gruen,
J. U. Lange,
S. Huang,
N. C. Robertson,
T. N. Varga,
Y. Luo,
C. Heymans,
H. Hildebrandt,
C. Blake,
M. Aguena,
S. Allam,
F. Andrade-Oliveira,
J. Annis,
E. Bertin,
S. Bhargava,
J. Blazek,
S. L. Bridle,
D. Brooks,
D. L. Burke,
A. Carnero Rosell,
M. Carrasco Kind,
J. Carretero
, et al. (82 additional authors not shown)
Abstract:
Lensing Without Borders is a cross-survey collaboration created to assess the consistency of galaxy-galaxy lensing signals ($ΔΣ$) across different data-sets and to carry out end-to-end tests of systematic errors. We perform a blind comparison of the amplitude of $ΔΣ$ using lens samples from BOSS and six independent lensing surveys. We find good agreement between empirically estimated and reported…
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Lensing Without Borders is a cross-survey collaboration created to assess the consistency of galaxy-galaxy lensing signals ($ΔΣ$) across different data-sets and to carry out end-to-end tests of systematic errors. We perform a blind comparison of the amplitude of $ΔΣ$ using lens samples from BOSS and six independent lensing surveys. We find good agreement between empirically estimated and reported systematic errors which agree to better than 2.3$σ$ in four lens bins and three radial ranges. For lenses with $z_{\rm L}>0.43$ and considering statistical errors, we detect a 3-4$σ$ correlation between lensing amplitude and survey depth. This correlation could arise from the increasing impact at higher redshift of unrecognised galaxy blends on shear calibration and imperfections in photometric redshift calibration. At $z_{\rm L}>0.54$ amplitudes may additionally correlate with foreground stellar density. The amplitude of these trends is within survey-defined systematic error budgets which are designed to include known shear and redshift calibration uncertainty. Using a fully empirical and conservative method, we do not find evidence for large unknown systematics. Systematic errors greater than 15% (25%) ruled out in three lens bins at 68% (95%) confidence at $z<0.54$. Differences with respect to predictions based on clustering are observed to be at the 20-30% level. Our results therefore suggest that lensing systematics alone are unlikely to fully explain the "lensing is low" effect at $z<0.54$. This analysis demonstrates the power of cross-survey comparisons and provides a promising path for identifying and reducing systematics in future lensing analyses.
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Submitted 26 November, 2021;
originally announced November 2021.
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Out of One, Many: Distinguishing Time Delays from Lensed Supernovae
Authors:
Mikhail Denissenya,
Satadru Bag,
Alex G. Kim,
Eric V. Linder,
Arman Shafieloo
Abstract:
Gravitationally lensed Type Ia supernovae are an emerging probe with great potential for constraining dark energy, spatial curvature, and the Hubble constant. The multiple images and their time delayed and magnified fluxes may be unresolved, however, blended into a single lightcurve. We demonstrate methods without a fixed source template matching for extracting the individual images, determining w…
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Gravitationally lensed Type Ia supernovae are an emerging probe with great potential for constraining dark energy, spatial curvature, and the Hubble constant. The multiple images and their time delayed and magnified fluxes may be unresolved, however, blended into a single lightcurve. We demonstrate methods without a fixed source template matching for extracting the individual images, determining whether there are one (no lensing) or two or four (lensed) images, and measuring the time delays between them that are valuable cosmological probes. We find 100% success for determining the number of images for time delays greater than $\sim10$ days.
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Submitted 24 February, 2022; v1 submitted 27 September, 2021;
originally announced September 2021.
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Finding quadruply imaged quasars with machine learning. I. Methods
Authors:
A. Akhazhanov,
A. More,
A. Amini,
C. Hazlett,
T. Treu,
S. Birrer,
A. Shajib,
P. Schechter,
C. Lemon,
B. Nord,
M. Aguena,
S. Allam,
F. Andrade-Oliveira,
J. Annis,
D. Brooks,
E. Buckley-Geer,
D. L. Burke,
A. Carnero Rosell,
M. Carrasco Kind,
J. Carretero,
A. Choi,
C. Conselice,
M. Costanzi,
L. N. da Costa,
M. E. S. Pereira
, et al. (46 additional authors not shown)
Abstract:
Strongly lensed quadruply imaged quasars (quads) are extraordinary objects. They are very rare in the sky -- only a few tens are known to date -- and yet they provide unique information about a wide range of topics, including the expansion history and the composition of the Universe, the distribution of stars and dark matter in galaxies, the host galaxies of quasars, and the stellar initial mass f…
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Strongly lensed quadruply imaged quasars (quads) are extraordinary objects. They are very rare in the sky -- only a few tens are known to date -- and yet they provide unique information about a wide range of topics, including the expansion history and the composition of the Universe, the distribution of stars and dark matter in galaxies, the host galaxies of quasars, and the stellar initial mass function. Finding them in astronomical images is a classic "needle in a haystack" problem, as they are outnumbered by other (contaminant) sources by many orders of magnitude. To solve this problem, we develop state-of-the-art deep learning methods and train them on realistic simulated quads based on real images of galaxies taken from the Dark Energy Survey, with realistic source and deflector models, including the chromatic effects of microlensing. The performance of the best methods on a mixture of simulated and real objects is excellent, yielding area under the receiver operating curve in the range 0.86 to 0.89. Recall is close to 100% down to total magnitude i~21 indicating high completeness, while precision declines from 85% to 70% in the range i~17-21. The methods are extremely fast: training on 2 million samples takes 20 hours on a GPU machine, and 10^8 multi-band cutouts can be evaluated per GPU-hour. The speed and performance of the method pave the way to apply it to large samples of astronomical sources, bypassing the need for photometric pre-selection that is likely to be a major cause of incompleteness in current samples of known quads.
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Submitted 20 September, 2021;
originally announced September 2021.
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Accuracy of environmental tracers and consequence for determining the Type Ia Supernovae magnitude step
Authors:
M. Briday,
M. Rigault,
R. Graziani,
Y. Copin,
G. Aldering,
M. Amenouche,
V. Brinnel,
A. G. Kim,
Y. -L. Kim,
J. Lezmy,
N. Nicolas,
J. Nordin,
S. Perlmutter,
P. Rosnet,
M. Smith
Abstract:
Type Ia Supernovae (SNe Ia) are standardizable candles that allow us to measure the recent expansion rate of the Universe. Due to uncertainties in progenitor physics, potential astrophysical dependencies may bias cosmological measurements if not properly accounted for. The dependency of the intrinsic luminosity of SNe Ia with their host-galaxy environment is often used to standardize SNe Ia lumino…
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Type Ia Supernovae (SNe Ia) are standardizable candles that allow us to measure the recent expansion rate of the Universe. Due to uncertainties in progenitor physics, potential astrophysical dependencies may bias cosmological measurements if not properly accounted for. The dependency of the intrinsic luminosity of SNe Ia with their host-galaxy environment is often used to standardize SNe Ia luminosity and is commonly parameterized as a step function. This functional form implicitly assumes two-populations of SNe Ia. In the literature, multiple environmental indicators have been considered, finding different, sometimes incompatible, step function amplitudes. We compare these indicators in the context of a two-populations model, based on their ability to distinguish the two populations. We show that local H$α$-based specific star formation rate (lsSFR) and global stellar mass are better tracers than, for instance, host galaxy morphology. We show that tracer accuracy can explain the discrepancy between the observed SNe Ia step amplitudes found in the literature. Using lsSFR or global mass to distinguish the two populations can explain all other observations, though lsSFR is favoured. As lsSFR is strongly connected to age, our results favour a prompt and delayed population model. In any case, there exists two populations that differ in standardized magnitude by at least $0.121\pm0.010\,\mathrm{mag}$.
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Submitted 6 September, 2021;
originally announced September 2021.
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The Observed Evolution of the Stellar Mass - Halo Mass Relation for Brightest Central Galaxies
Authors:
Jesse B. Golden-Marx,
C. J. Miller,
Y. Zhang,
R. L. C. Ogando,
A. Palmese,
T. M. C. Abbott,
M. Aguena,
S. Allam,
F. Andrade-Oliveira,
J. Annis,
D. Bacon,
E. Bertin,
D. Brooks,
E. Buckley-Geer,
A. Carnero Rosell,
M. Carrasco Kind,
F. J. Castander,
M. Constanzi,
M. Crocce,
L. N. da Costa,
M. E. S. Pereira,
J. de Vicente,
S. Desai,
H. T. Diehl,
P. Doel
, et al. (51 additional authors not shown)
Abstract:
We quantify evolution in the cluster scale stellar mass - halo mass (SMHM) relation's parameters using 2323 clusters and brightest central galaxies (BCGs) over the redshift range $0.03 \le z \le 0.60$. The precision on inferred SMHM parameters is improved by including the magnitude gap ($\rm m_{gap}$) between the BCG and fourth brightest cluster member (M14) as a third parameter in the SMHM relati…
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We quantify evolution in the cluster scale stellar mass - halo mass (SMHM) relation's parameters using 2323 clusters and brightest central galaxies (BCGs) over the redshift range $0.03 \le z \le 0.60$. The precision on inferred SMHM parameters is improved by including the magnitude gap ($\rm m_{gap}$) between the BCG and fourth brightest cluster member (M14) as a third parameter in the SMHM relation. At fixed halo mass, accounting for $\rm m_{gap}$, through a stretch parameter, reduces the SMHM relation's intrinsic scatter. To explore this redshift range, we use clusters, BCGs, and cluster members identified using the Sloan Digital Sky Survey C4 and redMaPPer cluster catalogs and the Dark Energy Survey redMaPPer catalog. Through this joint analysis, we detect no systematic differences in BCG stellar mass, $\rm m_{gap}$, and cluster mass (inferred from richness) between the datsets. We utilize the Pareto function to quantify each parameter's evolution. We confirm prior findings of negative evolution in the SMHM relation's slope (3.5$σ$) and detect negative evolution in the stretch parameter (4.0$σ$) and positive evolution in the offset parameter (5.8$σ$). This observed evolution, combined with the absence of BCG growth, when stellar mass is measured within 50kpc, suggests that this evolution results from changes in the cluster's $\rm m_{gap}$. For this to occur, late-term growth must be in the intra-cluster light surrounding the BCG. We also compare the observed results to Illustris TNG 300-1 cosmological hydrodynamic simulations and find modest qualitative agreement. However, the simulations lack the evolutionary features detected in the real data.
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Submitted 5 July, 2021;
originally announced July 2021.
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The Twins Embedding of Type Ia Supernovae I: The Diversity of Spectra at Maximum Light
Authors:
K. Boone,
G. Aldering,
P. Antilogus,
C. Aragon,
S. Bailey,
C. Baltay,
S. Bongard,
C. Buton,
Y. Copin,
S. Dixon,
D. Fouchez,
E. Gangler,
R. Gupta,
B. Hayden,
W. Hillebrandt,
A. G. Kim,
M. Kowalski,
D. Küsters,
P. -F. Léget,
F. Mondon,
J. Nordin,
R. Pain,
E. Pecontal,
R. Pereira,
S. Perlmutter
, et al. (12 additional authors not shown)
Abstract:
We study the spectral diversity of Type Ia supernovae (SNe Ia) at maximum light using high signal-to-noise spectrophotometry of 173 SNe Ia from the Nearby Supernova Factory. We decompose the diversity of these spectra into different extrinsic and intrinsic components, and we construct a nonlinear parameterization of the intrinsic diversity of SNe Ia that preserves pairings of "twin" SNe Ia. We cal…
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We study the spectral diversity of Type Ia supernovae (SNe Ia) at maximum light using high signal-to-noise spectrophotometry of 173 SNe Ia from the Nearby Supernova Factory. We decompose the diversity of these spectra into different extrinsic and intrinsic components, and we construct a nonlinear parameterization of the intrinsic diversity of SNe Ia that preserves pairings of "twin" SNe Ia. We call this parameterization the "Twins Embedding". Our methodology naturally handles highly nonlinear variability in spectra, such as changes in the photosphere expansion velocity, and uses the full spectrum rather than being limited to specific spectral line strengths, ratios or velocities. We find that the time evolution of SNe Ia near maximum light is remarkably similar, with 84.6% of the variance in common to all SNe Ia. After correcting for brightness and color, the intrinsic variability of SNe Ia is mostly restricted to specific spectral lines, and we find intrinsic dispersions as low as ~0.02 mag between 6600 and 7200 A. With a nonlinear three-dimensional model plus one dimension for color, we can explain 89.2% of the intrinsic diversity in our sample of SNe Ia, which includes several different kinds of "peculiar" SNe Ia. A linear model requires seven dimensions to explain a comparable fraction of the intrinsic diversity. We show how a wide range of previously-established indicators of diversity in SNe Ia can be recovered from the Twins Embedding. In a companion article, we discuss how these results an be applied to standardization of SNe Ia for cosmology.
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Submitted 5 May, 2021;
originally announced May 2021.
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The Twins Embedding of Type Ia Supernovae II: Improving Cosmological Distance Estimates
Authors:
K. Boone,
G. Aldering,
P. Antilogus,
C. Aragon,
S. Bailey,
C. Baltay,
S. Bongard,
C. Buton,
Y. Copin,
S. Dixon,
D. Fouchez,
E. Gangler,
R. Gupta,
B. Hayden,
W. Hillebrandt,
A. G. Kim,
M. Kowalski,
D. Küsters,
P. -F. Léget,
F. Mondon,
J. Nordin,
R. Pain,
E. Pecontal,
R. Pereira,
S. Perlmutter
, et al. (12 additional authors not shown)
Abstract:
We show how spectra of Type Ia supernovae (SNe Ia) at maximum light can be used to improve cosmological distance estimates. In a companion article, we used manifold learning to build a three-dimensional parameterization of the intrinsic diversity of SNe Ia at maximum light that we call the "Twins Embedding". In this article, we discuss how the Twins Embedding can be used to improve the standardiza…
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We show how spectra of Type Ia supernovae (SNe Ia) at maximum light can be used to improve cosmological distance estimates. In a companion article, we used manifold learning to build a three-dimensional parameterization of the intrinsic diversity of SNe Ia at maximum light that we call the "Twins Embedding". In this article, we discuss how the Twins Embedding can be used to improve the standardization of SNe Ia. With a single spectrophotometrically-calibrated spectrum near maximum light, we can standardize our sample of SNe Ia with an RMS of $0.101 \pm 0.007$ mag, which corresponds to $0.084 \pm 0.009$ mag if peculiar velocity contributions are removed and $0.073 \pm 0.008$ mag if a larger reference sample were obtained. Our techniques can standardize the full range of SNe Ia, including those typically labeled as peculiar and often rejected from other analyses. We find that traditional light curve width + color standardization such as SALT2 is not sufficient. The Twins Embedding identifies a subset of SNe Ia including but not limited to 91T-like SNe Ia whose SALT2 distance estimates are biased by $0.229 \pm 0.045$ mag. Standardization using the Twins Embedding also significantly decreases host-galaxy correlations. We recover a host mass step of $0.040 \pm 0.020$ mag compared to $0.092 \pm 0.024$ mag for SALT2 standardization on the same sample of SNe Ia. These biases in traditional standardization methods could significantly impact future cosmology analyses if not properly taken into account.
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Submitted 5 May, 2021;
originally announced May 2021.
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The Impact of Observing Strategy on Cosmological Constraints with LSST
Authors:
Michelle Lochner,
Dan Scolnic,
Husni Almoubayyed,
Timo Anguita,
Humna Awan,
Eric Gawiser,
Satya Gontcho A Gontcho,
Philippe Gris,
Simon Huber,
Saurabh W. Jha,
R. Lynne Jones,
Alex G. Kim,
Rachel Mandelbaum,
Phil Marshall,
Tanja Petrushevska,
Nicolas Regnault,
Christian N. Setzer,
Sherry H. Suyu,
Peter Yoachim,
Rahul Biswas,
Tristan Blaineau,
Isobel Hook,
Marc Moniez,
Eric Neilsen,
Hiranya Peiris
, et al. (2 additional authors not shown)
Abstract:
The generation-defining Vera C. Rubin Observatory will make state-of-the-art measurements of both the static and transient universe through its Legacy Survey for Space and Time (LSST). With such capabilities, it is immensely challenging to optimize the LSST observing strategy across the survey's wide range of science drivers. Many aspects of the LSST observing strategy relevant to the LSST Dark En…
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The generation-defining Vera C. Rubin Observatory will make state-of-the-art measurements of both the static and transient universe through its Legacy Survey for Space and Time (LSST). With such capabilities, it is immensely challenging to optimize the LSST observing strategy across the survey's wide range of science drivers. Many aspects of the LSST observing strategy relevant to the LSST Dark Energy Science Collaboration, such as survey footprint definition, single visit exposure time and the cadence of repeat visits in different filters, are yet to be finalized. Here, we present metrics used to assess the impact of observing strategy on the cosmological probes considered most sensitive to survey design; these are large-scale structure, weak lensing, type Ia supernovae, kilonovae and strong lens systems (as well as photometric redshifts, which enable many of these probes). We evaluate these metrics for over 100 different simulated potential survey designs. Our results show that multiple observing strategy decisions can profoundly impact cosmological constraints with LSST; these include adjusting the survey footprint, ensuring repeat nightly visits are taken in different filters and enforcing regular cadence. We provide public code for our metrics, which makes them readily available for evaluating further modifications to the survey design. We conclude with a set of recommendations and highlight observing strategy factors that require further research.
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Submitted 12 April, 2021;
originally announced April 2021.
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OzDES Reverberation Mapping Program: The first Mg II lags from five years of monitoring
Authors:
Zhefu Yu,
Paul Martini,
A. Penton,
T. M. Davis,
U. Malik,
C. Lidman,
B. E. Tucker,
R. Sharp,
C. S. Kochanek,
B. M. Peterson,
M. Aguena,
S. Allam,
F. Andrade-Oliveira,
J. Annis,
J. Asorey,
E. Bertin,
D. Brooks,
D. L. Burke,
J. Calcino,
A. Carnero Rosell,
D. Carollo,
M. Carrasco Kind,
M. Costanzi,
L. N. da Costa,
M. E. S. Pereira
, et al. (41 additional authors not shown)
Abstract:
Reverberation mapping is a robust method to measure the masses of supermassive black holes (SMBHs) outside of the local Universe. Measurements of the radius -- luminosity ($R-L$) relation using the Mg II emission line are critical for determining these masses near the peak of quasar activity at $z \approx 1 - 2$, and for calibrating secondary mass estimators based on Mg II that can be applied to l…
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Reverberation mapping is a robust method to measure the masses of supermassive black holes (SMBHs) outside of the local Universe. Measurements of the radius -- luminosity ($R-L$) relation using the Mg II emission line are critical for determining these masses near the peak of quasar activity at $z \approx 1 - 2$, and for calibrating secondary mass estimators based on Mg II that can be applied to large samples with only single-epoch spectroscopy. We present the first nine Mg II lags from our five-year Australian Dark Energy Survey (OzDES) reverberation mapping program, which substantially improves the number and quality of Mg II lag measurements. As the Mg II feature is somewhat blended with iron emission, we model and subtract both the continuum and iron contamination from the multi-epoch spectra before analyzing the Mg II line. We also develop a new method of quantifying correlated spectroscopic calibration errors based on our numerous, contemporaneous observations of F-stars. The lag measurements for seven of our nine sources are consistent with both the H$β$ and Mg II $R-L$ relations reported by previous studies. Our simulations verify the lag reliability of our nine measurements, and we estimate that the median false positive rate of the lag measurements is $4\%$.
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Submitted 12 September, 2021; v1 submitted 2 March, 2021;
originally announced March 2021.
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Dark Energy Survey Year 3 Results: Calibration of Lens Sample Redshift Distributions using Clustering Redshifts with BOSS/eBOSS
Authors:
R. Cawthon,
J. Elvin-Poole,
A. Porredon,
M. Crocce,
G. Giannini,
M. Gatti,
A. J. Ross,
E. S. Rykoff,
A. Carnero Rosell,
J. DeRose,
S. Lee,
M. Rodriguez-Monroy,
A. Amon,
K. Bechtol,
J. De Vicente,
D. Gruen,
R. Morgan,
E. Sanchez,
J. Sanchez,
I. Sevilla-Noarbe,
T. M. C. Abbott,
M. Aguena,
S. Allam,
J. Annis,
S. Avila
, et al. (61 additional authors not shown)
Abstract:
We present clustering redshift measurements for Dark Energy Survey (DES) lens sample galaxies to be used in weak gravitational lensing and galaxy clustering studies. To perform this measurement, we cross-correlate with spectroscopic galaxies from the Baryon Acoustic Oscillation Survey (BOSS) and its extension, eBOSS. We validate our methodology in simulations, including a new technique to calibrat…
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We present clustering redshift measurements for Dark Energy Survey (DES) lens sample galaxies to be used in weak gravitational lensing and galaxy clustering studies. To perform this measurement, we cross-correlate with spectroscopic galaxies from the Baryon Acoustic Oscillation Survey (BOSS) and its extension, eBOSS. We validate our methodology in simulations, including a new technique to calibrate systematic errors due to the galaxy clustering bias, finding our method to be generally unbiased in calibrating the mean redshift. We apply our method to the data, and estimate the redshift distribution for eleven different photometrically-selected bins. We find general agreement between clustering redshift and photometric redshift estimates, with differences on the inferred mean redshift to be below $|Δz|=0.01$ in most of the bins. We also test a method to calibrate a width parameter for redshift distributions, which we found necessary to use for some of our samples. Our typical uncertainties on the mean redshift ranged from 0.003 to 0.008, while our uncertainties on the width ranged from 4 to 9\%. We discuss how these results calibrate the photometric redshift distributions used in companion DES Year 3 Results papers.
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Submitted 8 June, 2022; v1 submitted 23 December, 2020;
originally announced December 2020.
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Optimising a magnitude-limited spectroscopic training sample for photometric classification of supernovae
Authors:
Jonathan E. Carrick,
Isobel M. Hook,
Elizabeth Swann,
Kyle Boone,
Chris Frohmaier,
Alex G. Kim,
Mark Sullivan
Abstract:
In preparation for photometric classification of transients from the Legacy Survey of Space and Time (LSST) we run tests with different training data sets. Using estimates of the depth to which the 4-metre Multi-Object Spectroscopic Telescope (4MOST) Time Domain Extragalactic Survey (TiDES) can classify transients, we simulate a magnitude-limited sample reaching $r_{\textrm{AB}} \approx$ 22.5 mag.…
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In preparation for photometric classification of transients from the Legacy Survey of Space and Time (LSST) we run tests with different training data sets. Using estimates of the depth to which the 4-metre Multi-Object Spectroscopic Telescope (4MOST) Time Domain Extragalactic Survey (TiDES) can classify transients, we simulate a magnitude-limited sample reaching $r_{\textrm{AB}} \approx$ 22.5 mag. We run our simulations with the software snmachine, a photometric classification pipeline using machine learning. The machine-learning algorithms struggle to classify supernovae when the training sample is magnitude-limited, in contrast to representative training samples. Classification performance noticeably improves when we combine the magnitude-limited training sample with a simulated realistic sample of faint, high-redshift supernovae observed from larger spectroscopic facilities; the algorithms' range of average area under ROC curve (AUC) scores over 10 runs increases from 0.547-0.628 to 0.946-0.969 and purity of the classified sample reaches 95 per cent in all runs for 2 of the 4 algorithms. By creating new, artificial light curves using the augmentation software avocado, we achieve a purity in our classified sample of 95 per cent in all 10 runs performed for all machine-learning algorithms considered. We also reach a highest average AUC score of 0.986 with the artificial neural network algorithm. Having `true' faint supernovae to complement our magnitude-limited sample is a crucial requirement in optimisation of a 4MOST spectroscopic sample. However, our results are a proof of concept that augmentation is also necessary to achieve the best classification results.
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Submitted 24 September, 2021; v1 submitted 22 December, 2020;
originally announced December 2020.
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Pushing automated morphological classifications to their limits with the Dark Energy Survey
Authors:
J. Vega-Ferrero,
H. Domínguez Sánchez,
M. Bernardi,
M. Huertas-Company,
R. Morgan,
B. Margalef,
M. Aguena,
S. Allam,
J. Annis,
S. Avila,
D. Bacon,
E. Bertin,
D. Brooks,
A. Carnero Rosell,
M. Carrasco Kind,
J. Carretero,
A. Choi,
C. Conselice,
M. Costanzi,
L. N. da Costa,
M. E. S. Pereira,
J. De Vicente,
S. Desai,
I. Ferrero,
P. Fosalba
, et al. (38 additional authors not shown)
Abstract:
We present morphological classifications of $\sim$27 million galaxies from the Dark Energy Survey (DES) Data Release 1 (DR1) using a supervised deep learning algorithm. The classification scheme separates: (a) early-type galaxies (ETGs) from late-types (LTGs); and (b) face-on galaxies from edge-on. Our Convolutional Neural Networks (CNNs) are trained on a small subset of DES objects with previousl…
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We present morphological classifications of $\sim$27 million galaxies from the Dark Energy Survey (DES) Data Release 1 (DR1) using a supervised deep learning algorithm. The classification scheme separates: (a) early-type galaxies (ETGs) from late-types (LTGs); and (b) face-on galaxies from edge-on. Our Convolutional Neural Networks (CNNs) are trained on a small subset of DES objects with previously known classifications. These typically have $\mathrm{m}_r \lesssim 17.7~\mathrm{mag}$; we model fainter objects to $\mathrm{m}_r < 21.5$ mag by simulating what the brighter objects with well determined classifications would look like if they were at higher redshifts. The CNNs reach 97\% accuracy to $\mathrm{m}_r<21.5$ on their training sets, suggesting that they are able to recover features more accurately than the human eye. We then used the trained CNNs to classify the vast majority of the other DES images. The final catalog comprises five independent CNN predictions for each classification scheme, helping to determine if the CNN predictions are robust or not. We obtain secure classifications for $\sim$ 87\% and 73\% of the catalog for the ETG vs. LTG and edge-on vs. face-on models, respectively. Combining the two classifications (a) and (b) helps to increase the purity of the ETG sample and to identify edge-on lenticular galaxies (as ETGs with high ellipticity). Where a comparison is possible, our classifications correlate very well with Sérsic index (\textit{n}), ellipticity ($ε$) and spectral type, even for the fainter galaxies. This is the largest multi-band catalog of automated galaxy morphologies to date.
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Submitted 9 March, 2021; v1 submitted 14 December, 2020;
originally announced December 2020.
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Be It Unresolved: Measuring Time Delays from Lensed Supernovae
Authors:
Satadru Bag,
Alex G. Kim,
Eric V. Linder,
Arman Shafieloo
Abstract:
Gravitationally lensed Type Ia supernovae may be the next frontier in cosmic probes, able to deliver independent constraints on dark energy, spatial curvature, and the Hubble constant. Measurements of time delays between the multiple images become more incisive due to the standardized candle nature of the source, monitoring for months rather than years, and partial immunity to microlensing. While…
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Gravitationally lensed Type Ia supernovae may be the next frontier in cosmic probes, able to deliver independent constraints on dark energy, spatial curvature, and the Hubble constant. Measurements of time delays between the multiple images become more incisive due to the standardized candle nature of the source, monitoring for months rather than years, and partial immunity to microlensing. While currently extremely rare, hundreds of such systems should be detected by upcoming time domain surveys. Even more will have the images spatially unresolved, with the observed lightcurve a superposition of time delayed image fluxes. We investigate whether unresolved images can be recognized as lensed sources given only lightcurve information, and whether time delays can be extracted robustly. We develop a method that successfully identifies such systems, with a false positive rate of $\lesssim 5\%$, and measures the time delays with a completeness of $\gtrsim 93\%$ and with a bias of $\lesssim 0.5\%$ for $Δt_{\rm fit} \gtrsim 10$ days.
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Submitted 8 October, 2020;
originally announced October 2020.