Showing 1–50 of 490 results for author: Myers, A

Hierarchical Spline-Based Bayesian Beta-Binomial Regression for Estimating Time-Varying Risk in Power Outages

Authors: Justin Jacobs, Jesse Piburn, Aaron Myers

Abstract: We propose a hierarchical Bayesian model for estimating time-varying outage risk from county-level power outage data. The model combines cubic B-spline basis functions with a Beta-Binomial likelihood to capture smooth, nonlinear recovery trajectories while accommodating overdispersion in observed customer counts. A shared hyperprior on the Beta-Binomial concentration parameter enables hierarchical… ▽ More We propose a hierarchical Bayesian model for estimating time-varying outage risk from county-level power outage data. The model combines cubic B-spline basis functions with a Beta-Binomial likelihood to capture smooth, nonlinear recovery trajectories while accommodating overdispersion in observed customer counts. A shared hyperprior on the Beta-Binomial concentration parameter enables hierarchical shrinkage across geographically indexed groups, allowing sparse or short-lived events to borrow statistical strength from the broader population. Posterior inference is conducted via the No-U-Turn Sampler (NUTS) in PyMC, yielding full posterior distributions over latent outage probabilities and derived resilience metrics including the area under the risk curve (AUC). We assess predictive performance using posterior predictive coverage, RMSE, and leave-one-out cross-validation, and demonstrate the model across a heterogeneous set of outage events in southern Wisconsin drawn from the EAGLE-I power outage monitoring platform. A direct comparison against naive trapezoidal AUC estimation confirms that the posterior mean recovers the same point estimates as deterministic integration while providing calibrated uncertainty quantification that deterministic approaches structurally cannot. The framework offers utilities and emergency planners a principled tool for benchmarking recovery dynamics and comparing outage events under uncertainty. △ Less

Submitted 12 August, 2026; originally announced August 2026.

Comments: 23 pages, 6 figures, 6 tables. Submitted to Reliability Engineering & System Safety. Produced under DOE contract DE-AC05-00OR22725

DESI DR2 Results IV: Alcock-Paczyński Measurements from the Lyman Alpha Forest and Cosmological Constraints

Authors: DESI Collaboration, A. G. Adame, J. Aguilar, S. Ahlen, O. Alves, A. Anand, U. Andrade, E. Armengaud, S. Avila, A. Aviles, P. Bansal, A. Bault, J. R. Bermejo-Climent, F. Beutler, D. Bianchi, C. Blake, S. Blasby, M. Bonici, S. Brieden, A. Brodzeller, D. Brooks, A. Carnero Rosell, K. Carrion, L. Casas, F. J. Castander , et al. (130 additional authors not shown)

Abstract: We present Alcock-Paczyński (AP) measurements from the full shape of Lyman-$α$ (Ly$α$) forest correlation functions measured from the second data release (DR2) of the Dark Energy Spectroscopic Instrument (DESI). Our measurements include information from the Ly$α$ forest auto-correlation and its cross-correlation with quasars. We constrain the AP effect with $1\%$ precision at an effective redshift… ▽ More We present Alcock-Paczyński (AP) measurements from the full shape of Lyman-$α$ (Ly$α$) forest correlation functions measured from the second data release (DR2) of the Dark Energy Spectroscopic Instrument (DESI). Our measurements include information from the Ly$α$ forest auto-correlation and its cross-correlation with quasars. We constrain the AP effect with $1\%$ precision at an effective redshift $z_\mathrm{eff}=2.33$, which is twice as tight as the Baryon Acoustic Oscillation (BAO) constraint from the same data. When using the joint Ly$α$ AP and BAO results, we measure the ratios $D_\text{H}(z_\mathrm{eff})/r_\text{d}=8.600 \pm 0.066$ and $D_\text{M}(z_\mathrm{eff})/r_\text{d}=39.32 \pm 0.33$, where $D_\text{M}$ is the transverse comoving distance, $D_\text{H}$ is the Hubble distance, and $r_\text{d}$ is the sound horizon at the drag epoch. Assuming $Λ$CDM, Ly$α$ forest measurements combined with a nucleosynthesis prior produce a constraint on the Hubble constant $H_0=66.5\pm1.3\,\mathrm{km\,s^{-1}\,Mpc^{-1}}$. The Ly$α$ AP result corresponds to a matter fraction constraint $Ω_\text{m}=0.325\pm0.018$ in $Λ$CDM, which is $1.4σ$ higher than DESI BAO. This impacts the DESI results relative to the Cosmic Microwave Background (CMB), slightly reducing their discrepancy from $2.4σ$ to $2.2σ$. We present updated constraints on extended models using the joint DESI DR2 BAO and Ly$α$ forest full shape data, together with external data sets. When considering a time-evolving dark energy equation of state parametrized by $w_0$ and $w_a$, we find it is preferred over $Λ$CDM at $2.7σ$ for the combination of DESI and CMB data, and at $3.2σ$ when also including supernovae. With the new Ly$α$ AP measurement, DESI provides its most precise anchor for the expansion history at $z > 1$ in the matter-dominated Universe. △ Less

Submitted 4 August, 2026; v1 submitted 29 July, 2026; originally announced July 2026.

1000 cataclysmic variables identified from DESI spectroscopy

Authors: K. Inight, B. T. Gänsicke, A. Aungwerojwit, P. Izquierdo, C. J. Manser, A. D. Myers, A. Swan, J. R. Thorstensen, J. Aguilar, S. Ahlen, D. Bianchi, D. Brooks, T. Claybaugh, A. de la Macorra, Biprateep Dey, P. Doel, A. Font-Ribera, J. E. Forero-Romero, Satya Gontcho A Gontcho, G. Gutierrez, J. Guy, R. Joyce, S. Juneau, S. E. Koposov, A. Kremin , et al. (19 additional authors not shown)

Abstract: Most cataclysmic variables (CVs) are discovered when they have an outburst generating an inherent selection bias against CVs that rarely, or never, outburst. CVs discovered by virtue of their spectroscopic characteristics are particularly valuable to offset this bias and we have used an established machine-learning technique to assist in searching 98 966 000 spectra obtained by the Dark Energy Spe… ▽ More Most cataclysmic variables (CVs) are discovered when they have an outburst generating an inherent selection bias against CVs that rarely, or never, outburst. CVs discovered by virtue of their spectroscopic characteristics are particularly valuable to offset this bias and we have used an established machine-learning technique to assist in searching 98 966 000 spectra obtained by the Dark Energy Spectroscopic Survey (DESI) to find such CVs. DESI observations are much deeper than previous spectroscopic surveys and we have identified 1029 CVs, 221 of which are new including ten of the AM CVn subtype. We have spectroscopically confirmed 441 CV candidates and obtained 84 new or improved orbital periods. We present revised space density estimates based upon this new data. We have also added ten more to the eight known examples of an intriguing class of CVs which exhibit peculiar changes in accretion. △ Less

Submitted 24 July, 2026; originally announced July 2026.

Comments: 28 pages, 35 figures plus extensive supplementary information. Submitted to MNRAS

Oblivious Probabilistic Outcome Logic: Verifying Probabilistic Programs with an Oblivious Adversary

Authors: Hanxi Chen, Noam Zilberstein, Andrew C. Myers, Alexandra Silva

Abstract: In the context of probabilistic programs, an oblivious adversary resolves nondeterminism without seeing the outcomes of random draws. Obliviousness is a common assumption in online algorithms and distributed protocols, but the complex interaction between random draws and adversarial choices makes it challenging to reason about correctness. While there has been significant progress toward reasoning… ▽ More In the context of probabilistic programs, an oblivious adversary resolves nondeterminism without seeing the outcomes of random draws. Obliviousness is a common assumption in online algorithms and distributed protocols, but the complex interaction between random draws and adversarial choices makes it challenging to reason about correctness. While there has been significant progress toward reasoning about programs that combine randomization with nondeterminism, most of the work has focused on the adaptive model, whose omniscient view of program state is too powerful to establish correctness for certain classes of programs. We introduce Oblivious Probabilistic Outcome Logic (opOL), a new logic for reasoning about probabilistic programs with nondeterminism controlled by an oblivious adversary. Building on Outcome Logic and Probabilistic Separation Logic, opOL models adversarial choice as a resource and uses probabilistic independence to ensure that random outcomes are hidden from the adversary. The opOL proof system provides expressive and compositional rules for case analysis on both random and nondeterministic outcomes, and for proving almost-sure termination. Expressivity is tested through several case studies, including a paging algorithm and a leader election protocol. The opOL metatheory and case studies are mechanized in Lean 4. △ Less

Submitted 17 July, 2026; originally announced July 2026.

DESI DR2 Reference Mocks: Clustering results from UCHUU ELGs and QSOs

Authors: R. Vaisakh, J. Lasker, R. Kehoe, A. Amalbert, N. Khan, E. Fernandez-Garcia, F. Prada, M. S. Wang, J. DeRose, S. Bailey, A. J. Ross, J. Aguilar, S. Ahlen, D. Bianchi, D. Brooks, F. J. Castander, T. Claybaugh, K. S. Dawson, A. de la Macorra, S. Ferraro, J. E. Forero-Romero, E. Gaztanaga, Satya Gontcho A Gontcho, G. Gutierrez, C. Hahn , et al. (22 additional authors not shown)

Abstract: High-redshift galaxy clustering provides a powerful probe of the growth of structure, testing models of dark matter, dark energy, and galaxy formation during the epoch when the Universe was rapidly evolving. Emission line galaxies (ELGs) and quasars (QSOs) are used as tracers of dark matter by the Dark Energy Spectroscopic Instrument (DESI) to probe this redshift regime. We present results from EL… ▽ More High-redshift galaxy clustering provides a powerful probe of the growth of structure, testing models of dark matter, dark energy, and galaxy formation during the epoch when the Universe was rapidly evolving. Emission line galaxies (ELGs) and quasars (QSOs) are used as tracers of dark matter by the Dark Energy Spectroscopic Instrument (DESI) to probe this redshift regime. We present results from ELG and QSO mock catalogs created from the Uchuu N-body simulation and tuned to DESI Data Release 2 (DR2) clustering. Employing a modified subhalo abundance matching (SHAM) technique, we populate Uchuu halos and subhalos with QSOs between 0.8 < z < 2.1. For ELGs, we modify this method to select satellite galaxies with low velocities relative to their associated central halos, and populate a separate set of Uchuu halos and subhalos with ELGs between 0.8 < z < 1.6. In this paper, we reproduce the redshift evolution of number density and clustering statistics across the fitted range of scales. We also measure the large-scale clustering bias of both the data and mock samples. These results improve simulated lightcone construction from cosmological models and enhance our understanding of the galaxy-halo connection. △ Less

Submitted 26 June, 2026; originally announced June 2026.

Comments: 30 pages, 18 figures

Clustering of high-redshift quasars with DESI DR2

Authors: M. Charles, P. Martini, A. J. Ross, D. H. Weinberg, J. Aguilar, S. Ahlen, D. Bianchi, D. Brooks, F. J. Castander, T. Claybaugh, A. Cuceu, A. de la Macorra, P. Doel, S. Ferraro, A. Font-Ribera, J. E. Forero-Romero, S. Gontcho A Gontcho, G. Gutierrez, J. Guy, C. Hahn, H. K. Herrera-Alcantar, K. Honscheid, C. Howlett, M. Ishak, R. Joyce , et al. (24 additional authors not shown)

Abstract: We present clustering measurements for high-redshift quasars using data from the Dark Energy Spectroscopic Instrument Data Release 2. Our sample consists of quasars with $2.0 < z < 3.5$ in the luminosity range $M_{1450} \leq -19.94$\,mag. We measure the mean quasar bias $b_Q(\bar{z} = 2.48) = 3.61 \pm 0.01$ for the full sample of $\sim 715,000$ quasars and quantify the redshift evolution of quasar… ▽ More We present clustering measurements for high-redshift quasars using data from the Dark Energy Spectroscopic Instrument Data Release 2. Our sample consists of quasars with $2.0 < z < 3.5$ in the luminosity range $M_{1450} \leq -19.94$\,mag. We measure the mean quasar bias $b_Q(\bar{z} = 2.48) = 3.61 \pm 0.01$ for the full sample of $\sim 715,000$ quasars and quantify the redshift evolution of quasar bias by dividing the sample into four equal redshift bins. There is strong evolution of the quasar bias with redshift that is well fit by the function $b_Q(z) = a [(1 + z)^2 - 6.565] + b$ with $a=0.230 \pm 0.007$ and $b=2.394 \pm 0.035$, and this fit is also a good match to lower redshift measurements in the literature. This bias evolution is consistent with a characteristic halo mass of $\bar{M}_{\mathrm{h}} \sim 10^{12}\,\mathrm{M_\odot}$ that does not vary significantly with redshift. The inferred duty cycles for quasars in our sample are $f_{\mathrm{duty}} \sim 10^{-2}$, staying mostly constant over redshifts. We investigate the luminosity dependence of quasar clustering by dividing each of our four redshift bins into three luminosity bins. The size of our quasar sample permits the first statistically significant measurement of the luminosity dependence of quasar bias at these redshifts. We measure weak dependence of quasar bias on luminosity at fixed redshift, inconsistent with no dependence, but weaker than predicted by a model in which quasar luminosity is tightly correlated with halo mass. These clustering measurements provide a stringent test for models of active black hole light curves and the black hole-halo connection at high redshift. △ Less

Submitted 25 June, 2026; originally announced June 2026.

Comments: 44 pages, 15 figures

DESI Data Release 2 ELGs: Property-dependent subsamples, imaging systematics, and clustering

Authors: T. Hagen, K. S. Dawson, Z. Zheng, J. Aguilar, S. Ahlen, D. Bianchi, D. Brooks, T. Claybaugh, A. de la Macorra, B. Dey, S. Ferraro, J. E. Forero-Romero, S. Gontcho A Gontcho, G. Gutierrez, J. Guy, C. Hahn, M. Ishak, R. Joyce, S. Juneau, A. Kremin, O. Lahav, C. Lamman, M. Landriau, L. Le Guillou, M. Manera , et al. (20 additional authors not shown)

Abstract: Using emission-line galaxies (ELGs) from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2, we evaluate a property-dependent correction to imaging systematics. We derive systematic weights following the same linear regression method used for other DESI tracers, but do so separately on ELG subsamples to provide a physically-informed alternative to the fiducial, neural-network-based app… ▽ More Using emission-line galaxies (ELGs) from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2, we evaluate a property-dependent correction to imaging systematics. We derive systematic weights following the same linear regression method used for other DESI tracers, but do so separately on ELG subsamples to provide a physically-informed alternative to the fiducial, neural-network-based approach. In doing so, we show that the deeper imaging in the Dark Energy Survey (DES) footprint leads to a higher overall number density but a lack of targets with extreme $g-r$ and $r-z$ colors. ELGs in the DES region also show a distinct redshift distribution when subsampled by position in the $g-r$ vs. $r-z$ plane. To address these effects, we implement a separate treatment of the DES footprint within the DESI catalog production pipeline, which is generally well-motivated and, in some cases, imperative for accurate clustering measurements. With DES treated separately, we find that property-dependent systematic weights further mitigate spurious clustering signal in $\sim$10% of subsamples, while the fiducial scheme remains optimal for the full sample. △ Less

Submitted 16 June, 2026; originally announced June 2026.

Comments: 35 pages, 13 figures

Tomography of the gamma-ray sky from cross-correlation with DESI DR2 and unWISE galaxies

Authors: Alex Krolewski, Neal Dalal, Will J. Percival, Elena Pinetti, J. Aguilar, S. Ahlen, S. BenZvi, D. Bianchi, D. Brooks, T. Claybaugh, A. Cuceu, A. de la Macorra, P. Doel, S. Ferraro, A. Font-Ribera, J. E. Forero-Romero, E. Gaztanaga, S. Gontcho A Gontcho, G. Gutierrez, J. Guy, D. Huterer, M. Ishak, R. Joyce, A. Kremin, O. Lahav , et al. (17 additional authors not shown)

Abstract: We study the origin of extragalactic gamma-ray emission observed by Fermi-LAT, using the cross-correlation of the gamma-ray sky with maps of large-scale structure provided by the DESI and unWISE surveys. Tomographic cross-correlation reveals the bias-weighted redshift distributions of gamma-ray sources. We first illustrate this method by cross-correlating detected gamma-ray point sources with larg… ▽ More We study the origin of extragalactic gamma-ray emission observed by Fermi-LAT, using the cross-correlation of the gamma-ray sky with maps of large-scale structure provided by the DESI and unWISE surveys. Tomographic cross-correlation reveals the bias-weighted redshift distributions of gamma-ray sources. We first illustrate this method by cross-correlating detected gamma-ray point sources with large-scale structure. We find a significant cross-correlation and infer a point source redshift distribution broadly consistent with the distribution of identified optical counterparts previously reported in the literature, as well as a similar linear bias ($b \approx 2$) to massive galaxies that host bright active galactic nuclei. We then study the clustering of the Fermi unresolved gamma-ray background (UGRB), both in auto-correlation and in cross-correlation with large-scale structure. We detect the cross-correlation of the UGRB and LSS at $\sim 10σ$ in total, with highly significant detections from both DESI and unWISE. Our measurements suggest that the redshift distribution of the UGRB is broadly consistent with the redshift distribution of detected point sources. Additionally, we find a relatively weak amplitude for the cross-correlation with large-scale structure at z < 2, suggesting a significant fraction of the UGRB does not come from z < 2 large-scale structure. A natural candidate is contamination of from residual Galactic emission, and our best estimate of the contamination level derived from the UGRB auto-spectrum suggests that the mean bias of UGRB sources is indeed quite similar to the bias of detected Fermi point sources. However, we cannot exclude additional emission from gamma-ray sources at high redshift, z > 2, and we suggest that cross-correlation with tracers at z > 2, including CMB lensing, would be the ideal way to determine the fraction of z > 2 emission. △ Less

Submitted 15 June, 2026; originally announced June 2026.

Comments: 26 pages, 11+9 figures

EP260321a/SN 2026gzf: The Faintest Shock Breakout Associated with a Broad-Lined Supernova

Authors: Brendan O'Connor, Xander J. Hall, Malte Busmann, Daniel Gruen, Alberto Floris, Tomas Cabrera, Ziyuan Zhu, Antonella Palmese, Dylan Green, John Banovetz, Julius Gassert, Christopher L. Fryer, Roberto Ricci, Eleonora Troja, Surya Shivaprasad, Gregory R. Zeimann, Ariel J. Amsellem, Stephen Bailey, Segev BenZvi, Simone Dichiara, Hendrik van Eerten, Jeremy Hare, Lei Hu, Christopher M. Irwin, Keerthi Kunnumkai , et al. (11 additional authors not shown)

Abstract: The explosion of a star is first marked by the shock wave breaking out of the stellar surface, producing a burst of ultraviolet and X-ray radiation. These events are observationally rare, despite likely accompanying the majority of supernovae. Here, we report on our multi-wavelength observing campaign of the closest Einstein Probe fast X-ray transient EP260321a at $z=0.0344$. The thermal (… ▽ More The explosion of a star is first marked by the shock wave breaking out of the stellar surface, producing a burst of ultraviolet and X-ray radiation. These events are observationally rare, despite likely accompanying the majority of supernovae. Here, we report on our multi-wavelength observing campaign of the closest Einstein Probe fast X-ray transient EP260321a at $z=0.0344$. The thermal ($kT=130$ eV) X-ray emission with peak luminosity $1.0\times10^{45}$ erg s$^{-1}$ points to a shock breakout origin. We demonstrate that EP260321a is accompanied by a broad-lined Type Ic supernova, SN 2026gzf. The supernova properties, including its spectral evolution, lightcurve evolution, and expansion velocities, are all typical of the energetic stripped-envelope supernovae associated with gamma-ray bursts. However, deep X-ray upper limits obtained with the \textit{Chandra X-ray Observatory} do not detect an X-ray afterglow, and instead exclude the afterglow of known gamma-ray bursts or fast X-ray transients. If the stellar explosion launched a successful relativistic jet, we require that it had both a low Lorentz factor $Γ_0$\,$<$\,$30$ and a kinetic energy $E_\textrm{kin}$\,$<$\,$10^{49}$ erg for a stellar wind density of $A_*$\,$\gtrsim$\,$1$. We propose that EP260321a originated from a mildly relativistic, weak outflow that was choked by the progenitor star. This scenario is capable of naturally explaining its low X-ray luminosity and lack of prompt gamma-ray emission. EP260321a bridges the gap between SN 2008D and low-luminosity GRBs, suggesting a greater diversity in the physical parameters of stripped stars as they undergo terminal collapse. △ Less

Submitted 26 June, 2026; v1 submitted 8 June, 2026; originally announced June 2026.

Comments: Accepted for publication in ApJL on June 26, 2026

GRB 260310A/SN 2026fgk: Photometric and Spectroscopic Evolution of a Nearby GRB-Supernova and an Exceptionally Bright Afterglow at z=0.153

Authors: Brendan O'Connor, Malte Busmann, Xander J. Hall, Kenta Taguchi, Masaomi Tanaka, Daniel Gruen, Seiji Toshikage, Ariel J. Amsellem, Ziyuan Zhu, Antonella Palmese, Dylan Green, John Banovetz, Yu-Han Yang, Eleonora Troja, Hendrik van Eerten, Julius Gassert, Mitra Maleki, Stephen Bailey, Segev BenZvi, Tomas Cabrera, Keerthi Kunnumkai, Adam D. Myers, Christoph Ries, David Schlegel, Michael Schmidt , et al. (2 additional authors not shown)

Abstract: The association of broad-lined Type Ic supernovae with long-duration gamma-ray bursts (GRBs) has been known for 28 years. However, only about seventy gamma-ray burst supernovae (GRB-SNe) have been identified, of which only half have spectroscopic classifications. At $z=0.153$, GRB 260310A is the 12th spectroscopically confirmed GRB-SN discovered within 1 Gpc, offering a critical opportunity to fol… ▽ More The association of broad-lined Type Ic supernovae with long-duration gamma-ray bursts (GRBs) has been known for 28 years. However, only about seventy gamma-ray burst supernovae (GRB-SNe) have been identified, of which only half have spectroscopic classifications. At $z=0.153$, GRB 260310A is the 12th spectroscopically confirmed GRB-SN discovered within 1 Gpc, offering a critical opportunity to follow one of these rare supernovae in detail. We present optical to near-infrared imaging and spectroscopy of GRB 260310A and SN 2026fgk out to 65 d after discovery. The optical afterglow is among the brightest ever observed from a GRB. Spectra obtained more than two weeks after the explosion reveal broad absorption features that securely identify SN 2026fgk as a Type Ic-BL supernova. Modeling of the multi-wavelength ($grizJK_s$) lightcurve shows that the supernova is approximately half the luminosity ($k_\textrm{98bw}=0.4-0.6$) of the canonical GRB-SN 1998bw. We derive a nickel mass of $M_\textrm{Ni}=0.4-0.5$ $M_\odot$ with a total ejected mass of $M_\textrm{ej}\approx4-6 $ $M_\odot$ and kinetic energy $E_\textrm{K}=(3-8)\times10^{51}$ erg. The GRB exploded at an extremely large offset of 15 kpc from its host galaxy. Long-slit spectra reveal a ``bridge'' of nebular emission extending along the galaxy's disk to the GRB location, which has a sub-solar metallicity ($\sim$\,$0.4Z_\odot$), compared to a near solar metallicity for the host galaxy. This indicates that the large offset arises from the galaxy's extended light profile rather than an isolated environment. △ Less

Submitted 29 June, 2026; v1 submitted 18 May, 2026; originally announced May 2026.

Comments: Accepted to ApJ on June 28, 2026

bispectrum: Selective $G$-Bispectra Made Practical

Authors: Johan Mathe, Adele Myers, Simon Mataigne, Nina Miolane

Abstract: Many machine learning tasks are invariant under the action of a group $G$ of transformations: signal classification can be invariant under translations, image classification under 2D rotations, and spherical-image classification under 3D rotations. The $G$-bispectrum is a principled complete invariant of a signal (retaining all all signal's information up to the group action) with proven benefits… ▽ More Many machine learning tasks are invariant under the action of a group $G$ of transformations: signal classification can be invariant under translations, image classification under 2D rotations, and spherical-image classification under 3D rotations. The $G$-bispectrum is a principled complete invariant of a signal (retaining all all signal's information up to the group action) with proven benefits in machine learning and as a pooling layer in deep networks. However, its deployment has been hampered by high computational cost and a patchwork of group-specific implementations. We present bispectrum, an open-source, fully unit-tested PyTorch library that implements selective $G$-bispectra for seven different group actions, as differentiable modules that can be directly incorporated into machine learning pipelines and deep learning architectures. For finite groups $G$, selectivity reduces the computational cost from $O(|G|^2)$ to $O(|G|)$. For planar rotations, we leverage the disk bispectrum. For spherical 3D rotations, we introduce an augmented selective bispectrum at band-limit $L$ which reduces the cost from $O(L^3)$ to $Θ(L^2)$ coefficients. We profile the entire library (for which we implemented various compute optimizations), showing that it delivers near-exact $G$-invariance with its selective $G$-bispectra computed in sub-millisecond time on GPU (up to commonly used bandlimits). We evaluate the benefits of incorporating $G$-bispectra as pooling layers into deep learning architectures on three classical benchmark datasets --comparing against norm pooling, gated pooling, Fourier-ELU pooling, max pooling, and (non-equivariant) data-augmented convolutional baselines. Results show that $G$-bispectra consistently outperform alternatives in the low-data, moderate-capacity regime. △ Less

Submitted 8 May, 2026; originally announced May 2026.

The Effect of Mass Loss and Convective Overshooting on the Pre-Collapse Structure, Composition, and Neutrino Emission of Red Supergiants

Authors: McKenzie A. Myers, Claire B. Campbell, Kelly M. Patton, Segen BenZvi, Marta Colomer Molla, Alec Habig, James P. Kneller, Dan Milisavljevic, Jeffrey Tseng

Abstract: Prior to core collapse, the neutrino emission from red supergiants (RSGs) is so large that a nearby ($\lesssim1$kpc) RSG will become visible in current and near-future neutrino detectors. The rate of emission and the spectra of the pre-supernova (pre-SN) neutrinos from RSGs are sensitive to the temperature, density, and detailed isotopic composition of the core. During the last year of the star's… ▽ More Prior to core collapse, the neutrino emission from red supergiants (RSGs) is so large that a nearby ($\lesssim1$kpc) RSG will become visible in current and near-future neutrino detectors. The rate of emission and the spectra of the pre-supernova (pre-SN) neutrinos from RSGs are sensitive to the temperature, density, and detailed isotopic composition of the core. During the last year of the star's life, these properties change considerably. Several factors of stellar evolution modeling - such as the treatment of mass loss and convective overshooting - alter the thermal conditions and composition of the RSG core as it approaches collapse. In this paper we present the first study of how varying the treatment of mass loss and convective overshooting together affects the pre-collapse core properties and neutrino emission of RSGs. We use the stellar evolution instrument MESA and construct a grid of 32 models with zero-age main sequence masses of $\{ 12, 15, 18, 20\}$ $M_\odot$, use the so-called 'Dutch' mass-loss scheme with wind efficiencies of $\{0.2, 0.4, 0.8, 1.0\}$, and consider two convective overshooting schemes. Our models use a large 206-isotope nuclear network in order to accurately compute the structure and composition of the star. We find that, in the last few days of the star's life, the general trend of the conditions and composition in the core of the star is one of contraction, heating, and deleptonization, but that during this phase, this general trend will be interrupted by the initiation of core silicon burning and shell burning episodes that cause the core to expand and undergo convective mixing with material of a higher proton fraction that temporarily reverses the deleptonization. The pre-SN neutrino emission reflects these changes with a gradual shift to higher energies and larger flux that becomes dominated by beta processes a few hours prior to the collapse. △ Less

Submitted 24 April, 2026; originally announced April 2026.

Comments: 17 pages, 12 figures

pyzentropy: A Python package implementing recursive entropy for first-principles thermodynamics

Authors: Nigel Lee En Hew, Luke Allen Myers, Shun-Li Shang, Zi-Kui Liu

Abstract: While the recursive property of entropy is well known in information theory, it is rarely utilized in thermodynamics, despite entropy originating in this field. Moreover, computational tools to implement this concept within first-principles thermodynamics remain lacking. In this work, we introduce an open-source Python package, pyzentropy, to implement this approach. We demonstrate its effectivene… ▽ More While the recursive property of entropy is well known in information theory, it is rarely utilized in thermodynamics, despite entropy originating in this field. Moreover, computational tools to implement this concept within first-principles thermodynamics remain lacking. In this work, we introduce an open-source Python package, pyzentropy, to implement this approach. We demonstrate its effectiveness using $Fe_3Pt$ as a case study, considering a 12-atom supercell with multiple magnetic configurations. By applying the recursive formulation of entropy to compute the total entropy of the system, we reproduce the Invar behavior, along with the anomalous temperature dependence of the linear coefficient of thermal expansion (LCTE), heat capacity $C_P$, and bulk modulus $B$. We also construct the $T$-$V$ and $P$-$T$ phase diagrams in good agreement with experimental observations. Finally, we highlight the importance of determining key high-probability configurations to accurately capture material properties. △ Less

Submitted 19 April, 2026; originally announced April 2026.

Comments: 16 pages, 6 figures

Deep Spectroscopy with DESI for Photometric Redshift Training and Calibration

Authors: Biprateep Dey, Jeffrey A. Newman, Tianqing Zhang, J. Aguilar, S. Ahlen, A. Anand, B. Andrews, S. Bailey, D. Bianchi, D. Brooks, F. J. Castander, T. Claybaugh, A. Cuceu, K. S. Dawson, A. de la Macorra, J. Della Costa, Arjun Dey, P. Doel, S. Ferraro, A. Font-Ribera, E. Gaztañaga, Satya Gontcho A Gontcho, D. Gruen, G. Gutierrez, J. Guy , et al. (40 additional authors not shown)

Abstract: Deep spectroscopic samples can be used to improve photometric redshift (photo-$z$) estimates and reduce uncertainties on redshift distributions. Such improvements can increase the cosmological constraining power of large imaging-based experiments such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) and mitigate what may be a limiting systematic effect. We present results… ▽ More Deep spectroscopic samples can be used to improve photometric redshift (photo-$z$) estimates and reduce uncertainties on redshift distributions. Such improvements can increase the cosmological constraining power of large imaging-based experiments such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) and mitigate what may be a limiting systematic effect. We present results from the ``DESI-Deep pilot'' program, which was designed to assess the capability of the Dark Energy Spectroscopic Instrument (DESI) on the 4m Mayall telescope to measure redshifts of galaxies as faint as expected lensing samples for early LSST data ($m_i \leq 24.5$). We find that DESI is remarkably efficient at this task, with redshift success rates comparable to the results of observations from 10m-class telescopes with only $\sim2\times$ longer integration time (rather than $\sim 8\times$ longer as would be expected from aperture-area scaling), while simultaneously achieving $\sim30$ times larger multiplexing. We also find that the signal-to-noise ratio of the spectra scales as expected for background-limited observations even for the longest exposure times ($\sim 7$ hours) and faintest targets in the program. These results demonstrate that DESI could provide the definitive redshift sample for the early years of LSST with a modest investment of observing time. Based upon the results of this program, we provide updated predictions for the time required to collect benchmark samples for photo-$z$ training and calibration using a variety of spectroscopic facilities. Finally, we describe a potential "DESI-Deep" survey designed to train and calibrate photo-$z$'s for imaging experiments, and provide forecasts of its impact on cosmological inference. △ Less

Submitted 7 April, 2026; originally announced April 2026.

Comments: Data & code available here: https://biprateep.github.io/desi-deep-pilot/

HAMMR-L: Noise Reduction in Quantum Outcomes Using a Richardson-Lucy Deconvolution Algorithm for Quantum State Graphs

Authors: Jake Scally, Austin Myers, Ryan Carmichael, Phat Tran, Xiuwen Liu

Abstract: Current quantum computers present significant noise, especially as circuit depth and qubit count increase. Prior work has demonstrated that erroneous outcomes exhibit some behavior in Hamming space, enabling improvements in the output distributions of NISQ-era computers. We present HAMMR-L: a principled post-processing technique for improving the fidelity of output distributions by applying Richar… ▽ More Current quantum computers present significant noise, especially as circuit depth and qubit count increase. Prior work has demonstrated that erroneous outcomes exhibit some behavior in Hamming space, enabling improvements in the output distributions of NISQ-era computers. We present HAMMR-L: a principled post-processing technique for improving the fidelity of output distributions by applying Richardson-Lucy image deconvolution on a state graph of measurement results connected by Hamming distance. We show that this preliminary implementation of HAMMR-L outperforms existing cutting-edge Hamming-based post-processors such as QBEEP while being circuit and hardware agnostic, which QBEEP is not. HAMMR-L also demonstrates clear potential for future improvements and we discuss how such improvements might be realized while highlighting the strengths, limitations, and generality of the underlying concept. △ Less

Submitted 28 March, 2026; originally announced March 2026.

Comments: 6 pages, 2 figures

ODIN: Spectroscopic Validation of Ly$α$-Emitting Galaxy Samples with DESI

Authors: Ethan Pinarski, Govind Ramgopal, Nicole Firestone, Kyoung-Soo Lee, Eric Gawiser, Arjun Dey, A. Raichoor, Francisco Valdes, Robin Ciardullo, Jessica N. Aguilar, S. Ahlen, D. Bianchi, D. Brooks, F. J. Castander, M. Candela Cerdosino, T. Claybaugh, A. Cuceu, K. S. Dawson, A. de la Macorra, P. Doel, S. Ferraro, A. Font-Ribera, J. E. Forero-Romero, E. Gaztañaga, S. Gontcho A Gontcho , et al. (43 additional authors not shown)

Abstract: The One-hundred-deg^2 DECam Imaging in Narrowbands (ODIN) survey is conducting the widest-field deep narrow-band imaging of the equatorial and southern skies. ODIN uses three custom-built narrow-band (NB) filters that sample Lya-emitting galaxies (LAEs) within thin cosmic slices centered at z=2.4, 3.1, and 4.5. In this work, we utilize extensive DESI spectroscopy of ODIN-selected galaxies in the C… ▽ More The One-hundred-deg^2 DECam Imaging in Narrowbands (ODIN) survey is conducting the widest-field deep narrow-band imaging of the equatorial and southern skies. ODIN uses three custom-built narrow-band (NB) filters that sample Lya-emitting galaxies (LAEs) within thin cosmic slices centered at z=2.4, 3.1, and 4.5. In this work, we utilize extensive DESI spectroscopy of ODIN-selected galaxies in the COSMOS and XMM-LSS fields to validate our LAE selection. 2-4 hr exposures with DESI yielded redshift confirmation of 3,075 ODIN LAE candidates with NB magnitudes brighter than 26~mag. Restricting to objects that yield high-confidence redshifts, the confirmation rates are (93, 96, 92)% at z=(2.4, 3.1, 4.5). The primary contaminants consist of active galactic nuclei at the expected Lya redshift range and lower redshifts (C IV, C III]), with the remainder being star-forming galaxies ([O II] and [O III]). We find minimal contamination from [O II] emitters in our sample (<~1%), implying that our REW>20 A narrow-band excess photometry requirement is sufficient to remove them. △ Less

Submitted 10 March, 2026; originally announced March 2026.

Comments: 15 pages, 6 figures, Submitted to Astrophysical Journal

ODIN: Confirmation and 3D Reconstruction of Six Massive Protoclusters at Cosmic Noon

Authors: Ashley Ortiz, Vandana Ramakrishnan, Kyoung-Soo Lee, Arjun Dey, Yucheng Guo, Ethan Pinarski, Anand Raichoor, Francisco Valdes, J. Aguilar, Steven Ahlen, Maria Celeste Artale, Davide Bianchi, August Bliese, David Brooks, Rebecca Canning, Maria Cerdosino, Todd Claybaugh, Andrei Cuceu, Axel de la Macorra, Peter Doel, Jaime Forero, Eric Gawiser, Enrique Gaztanaga, Satya Gontcho, Caryl Gronwall , et al. (42 additional authors not shown)

Abstract: Protoclusters represent sites of accelerated galaxy formation and extreme astrophysical activity characteristic of dense environments. Identifying massive protoclusters and mapping their spatial structures are therefore crucial first steps in understanding how the large-scale environment influences galaxy evolution. We combine wide-field Ly$α$ imaging from the ODIN survey with extensive DESI and a… ▽ More Protoclusters represent sites of accelerated galaxy formation and extreme astrophysical activity characteristic of dense environments. Identifying massive protoclusters and mapping their spatial structures are therefore crucial first steps in understanding how the large-scale environment influences galaxy evolution. We combine wide-field Ly$α$ imaging from the ODIN survey with extensive DESI and ancillary spectroscopy across the extended COSMOS and XMM-LSS fields ($\approx$14 deg$^2$) to search for massive protoclusters. We confirm six systems at $z\approx 2.4$ and $z\approx 3.1$, reconstruct their three-dimensional structures, estimate descendant halo masses, and, for one structure at $z\approx 3.12$, demonstrate that overlapping narrowband filters ($NB497$ and $N501$) provide accurate redshift tomography for emission-line galaxies. One protocluster at $z\approx 2.45$ overlaps with one of the LATIS tomographic fields, enabling direct comparison between galaxy and H {\sc i} overdensities traced by Ly$α$ forest absorption. Another at $z\approx 3.12$ hosts a massive quiescent galaxy ($M_{\ast} \approx 1.2 \times 10^{11}M_\odot$), indicating early quenching in a dense environment. By comparing Ly$α$ emission properties across environments, we find that protocluster galaxies exhibit higher median line fluxes and a deficit of faint emitters relative to the field. The effect is strongest when both 2D and 3D density information are combined, indicating that galaxies in the densest protocluster cores are most affected by environmental processes. This effect is stronger at $z\approx3.1$ than at $z\approx2.4$, suggesting possible redshift evolution. △ Less

Submitted 11 March, 2026; v1 submitted 10 March, 2026; originally announced March 2026.

Multi-Class Boundary Extraction from Implicit Representations

Authors: Jash Vira, Andrew Myers, Simon Ratcliffe

Abstract: Surface extraction from implicit neural representations modelling a single class surface is a well-known task. However, there exist no surface extraction methods from an implicit representation of multiple classes that guarantee topological correctness and no holes. In this work, we lay the groundwork by introducing a 2D boundary extraction algorithm for the multi-class case focusing on topologica… ▽ More Surface extraction from implicit neural representations modelling a single class surface is a well-known task. However, there exist no surface extraction methods from an implicit representation of multiple classes that guarantee topological correctness and no holes. In this work, we lay the groundwork by introducing a 2D boundary extraction algorithm for the multi-class case focusing on topological consistency and water-tightness, which also allows for setting minimum detail restraint on the approximation. Finally, we evaluate our algorithm using geological modelling data, showcasing its adaptiveness and ability to honour complex topology. △ Less

Submitted 18 February, 2026; originally announced February 2026.

Sequential Group Composition: A Window into the Mechanics of Deep Learning

Authors: Giovanni Luca Marchetti, Daniel Kunin, Adele Myers, Francisco Acosta, Nina Miolane

Abstract: How do neural networks trained over sequences acquire the ability to perform structured operations, such as arithmetic, geometric, and algorithmic computation? To gain insight into this question, we introduce the sequential group composition task. In this task, networks receive a sequence of elements from a finite group encoded in a real vector space and must predict their cumulative product. This… ▽ More How do neural networks trained over sequences acquire the ability to perform structured operations, such as arithmetic, geometric, and algorithmic computation? To gain insight into this question, we introduce the sequential group composition task. In this task, networks receive a sequence of elements from a finite group encoded in a real vector space and must predict their cumulative product. This task can be order-sensitive and cannot be solved by a linear model. Our analysis isolates the roles of the group structure, encoding statistics, and sequence length in shaping learning. We prove that two-layer networks from vanishing initialization learn this task one irreducible representation of the group at a time in an order determined by the Fourier statistics of the encoding. To perfectly learn the task, these networks require a hidden width exponential in the sequence length $k$. In contrast, we construct deeper architectures that exploit associativity to dramatically improve this scaling: recurrent neural networks can compose elements sequentially in $k$ steps, while multilayer networks can compose adjacent pairs in parallel in $\log k$ layers. Overall, the sequential group composition task offers a tractable window into the mechanics of deep learning. △ Less

Submitted 29 May, 2026; v1 submitted 3 February, 2026; originally announced February 2026.

Comments: Accepted at ICML 2026

Tensorized Discontinuous Isogeometric Analysis Method for the 2-D Time-Independent Linearized Boltzmann Transport Equation

Authors: Patrick A. Myers, Joseph A. Bogdan, Majdi I. Radaideh, Brian C. Kiedrowski

Abstract: We present the novel Tensorized Discontinuous Isogeometric Analysis (TDIGA) method applied to the discontinuous Galerkin (DG) time-independent 2-D linearized Boltzmann transport equation (LBTE) with higher-order scattering, discretized with discrete ordinates in angle, multigroup in energy, and isogeometric analysis (IGA) in space. We formulate operator assembly in the tensor train (TT) format, pr… ▽ More We present the novel Tensorized Discontinuous Isogeometric Analysis (TDIGA) method applied to the discontinuous Galerkin (DG) time-independent 2-D linearized Boltzmann transport equation (LBTE) with higher-order scattering, discretized with discrete ordinates in angle, multigroup in energy, and isogeometric analysis (IGA) in space. We formulate operator assembly in the tensor train (TT) format, producing seven-dimensional operators for both fixed-source and $k$-eigenvalue neutron transport problems solved using the restarted Generalized Minimum Residual Method (GMRES) and power iteration with an uncompressed solution vector. Our results on single-patch homogeneous and multi-patch heterogeneous problems, including a cruciform-shaped fuel array inspired by advanced reactor fuel designs, demonstrate the TT format's ability to compress interior operators from petabytes to megabytes, whereas the Compressed Sparse Row (CSR) matrix format requires gigabytes of storage. However, highly coupled boundary operators present a significant challenge for TT. Despite the storage savings, TT formatted operators increase time-to-solution relative to CSR as an uncompressed solution vector forces operator-vector product scaling of $O(dr^2N^d\log(N))$ for TT while CSR scales at $O(\text{nnz})$. We mitigate this discrepancy by using mixed formats with interior operators in TT, while high-rank boundary operators remain in CSR format. We compare all results to Monte Carlo (MC) and analytic reference solutions. While CSR remains $<10\times$ faster than this mixed format, the TDIGA method enables high-fidelity transport for expensive high-order IGA meshes. △ Less

Submitted 26 January, 2026; originally announced January 2026.

Comments: 71 pages, 38 figures, 10 tables, source code is available at https://github.com/myerspat/ttnte_tdiga_jcp2025, raw data is available at https://doi.org/10.5281/zenodo.18294213

Signatures of a Tidally Induced Spiral Arm at the Anticenter of the Milky Way and a Kinematically Extended Anticenter Stream Using DESI DR2

Authors: Mika Lambert, Constance M. Rockosi, Sergey E. Koposov, Ting S. Li, Monica Valluri, Leandro Beraldo e Silva, Songting Li, Joaõ A. S. Amarante, Amanda Byström, Gustavo E. Medina, Nathan R. Sandford, Joan Najita, Namitha Kizhuprakkat, Jessica N. Aguilar, Steven Ahlen, Davide Bianchi, David Brooks, Todd Claybaugh, Kyle Dawson, Axel de la Macorra, Peter Doel, Jaime E. Forero-Romero, Enrique Gaztañaga, Satya Gontcho A Gontcho, Gaston Gutierrez , et al. (24 additional authors not shown)

Abstract: Using the Dark Energy Spectroscopic Instrument Milky Way Survey (DESI MWS), we examine the 6D space of the anticenter region of the stellar disk (150$^\circ$ $<$ Galactic longitude $<$ 220$^\circ$) using 61,883 main-sequence turnoff stars. We focus on two well-known stellar overdensities in the anticenter, the Monoceros Ring (MRi) and Anticenter Stream (ACS). We find that the MRi overdensity has k… ▽ More Using the Dark Energy Spectroscopic Instrument Milky Way Survey (DESI MWS), we examine the 6D space of the anticenter region of the stellar disk (150$^\circ$ $<$ Galactic longitude $<$ 220$^\circ$) using 61,883 main-sequence turnoff stars. We focus on two well-known stellar overdensities in the anticenter, the Monoceros Ring (MRi) and Anticenter Stream (ACS). We find that the MRi overdensity has kinematics consistent with a tidally induced spiral arm, a type of dynamic spiral arm created by an interaction with a satellite galaxy, most likely the Sagittarius dwarf spheroidal galaxy (Sgr). We use the kinematics of the MRi to calculate the two most recent passage times of Sgr are 0.25 $\pm$ 0.09 Gyrs and 1.10 $\pm$ 0.23 Gyrs from the present day. We validate that the ACS is kinematically decoupled from the MRi because they are moving in opposite radial and vertical directions. We find that the kinematics associated with the ACS are not confined to our defined overdensity. The features we see in the ACS region are likely part of a broader distribution of stars with the same kinematic signature as detected in other places, like the vertical wave in the outer disk and phase spiral. △ Less

Submitted 17 June, 2026; v1 submitted 20 January, 2026; originally announced January 2026.

Comments: 26 pages, 14 figures, Accepted to the Astronomical Journal

The DESI Transients Survey: Legacy Classifications and Methodology

Authors: Xander J. Hall, Antonella Palmese, Segev BenZvi, John Banovetz, Brendan O'Connor, Lei Hu, Erica Hammerstein, Ariel Amsellem, Jessica Nicole Aguilar, Steven Ahlen, Steven Bailey, Davide Bianchi, David Brooks, Todd Claybaugh, Andrei Cuceu, Kyle Dawson, Axel de la Macorra, John Della Costa, Arjun Dey, Peter Doel, Simone Ferraro, Andreu Font-Ribera, Jaime E. Forero-Romero, Enrique Gaztanaga, Satya Gontcho A Gontcho , et al. (34 additional authors not shown)

Abstract: We present the first systematic spectroscopic observations of extragalactic transients from the Dark Energy Spectroscopic Instrument (DESI), as part of the DESI Transients Survey program. With 5,000 fibers and an ${\sim} 8$ deg$^2$ field of view, we exploit DESI as a machine for the discovery and classification of transients. We present transient classifications from archival DESI data in Data Rel… ▽ More We present the first systematic spectroscopic observations of extragalactic transients from the Dark Energy Spectroscopic Instrument (DESI), as part of the DESI Transients Survey program. With 5,000 fibers and an ${\sim} 8$ deg$^2$ field of view, we exploit DESI as a machine for the discovery and classification of transients. We present transient classifications from archival DESI data in Data Releases 1 and 2, relying on a combination of a secondary target program and serendipitous observations. We also present observations from the first 6 months of the DESI spare fiber program dedicated to transients. The program is run in coordination with a dedicated DECam time-domain survey, serving as a pathfinder for what we will be able to achieve in conjunction with the Rubin Observatory Legacy Survey of Space and Time (LSST). We classify over 250 transients, of which the majority were previously unclassified. The sample comprises thermonuclear and core-collapse supernovae and tidal disruption events (TDEs), including a TDE observed before its discovery in imaging. We demonstrate DESI's ability to classify a population of faint transients down to $r\sim 22.5$ mag during main survey operations, with negligible impacts on DESI's main observations. △ Less

Submitted 18 January, 2026; originally announced January 2026.

The Wigner-Ville Transform as an Information Theoretic Tool in Radio-frequency Signal Analysis

Authors: Erik Lentz, Emily Ellwein, Bill Kay, Audun Myers, Cameron Mackenzie

Abstract: This paper presents novel interpretations to the field of classical signal processing of the Wigner-Ville transform as an information measurement tool. The transform's utility in detecting and localizing information-laden signals amidst noisy and cluttered backgrounds, and further providing measure of their information volumes, are detailed herein using Tsallis' entropy and information and related… ▽ More This paper presents novel interpretations to the field of classical signal processing of the Wigner-Ville transform as an information measurement tool. The transform's utility in detecting and localizing information-laden signals amidst noisy and cluttered backgrounds, and further providing measure of their information volumes, are detailed herein using Tsallis' entropy and information and related functionals. Example use cases in radio frequency communications are given, where Wigner-Ville-based detection measures can be seen to provide significant sensitivity advantage, for some shown contexts greater than 15~dB advantage, over energy-based measures and without extensive training routines. Such an advantage is particularly significant for applications which have limitations on observation resources including time/space integration pressures and transient and/or feeble signals, where Wigner-Ville-based methods would improve sensing effectiveness by multiple orders of magnitude. The potential for advancement of several such applications is discussed. △ Less

Submitted 30 December, 2025; originally announced December 2025.

Comments: 12 pages, 11 figures

Human-AI Interaction Alignment: Designing, Evaluating, and Evolving Value-Centered AI For Reciprocal Human-AI Futures

Authors: Hua Shen, Tiffany Knearem, Divy Thakkar, Pat Pataranutaporn, Anoop Sinha, Yike, Shi, Jenny T. Liang, Lama Ahmad, Tanu Mitra, Brad A. Myers, Yang Li

Abstract: The rapid integration of generative AI into everyday life underscores the need to move beyond unidirectional alignment models that only adapt AI to human values. This workshop focuses on bidirectional human-AI alignment, a dynamic, reciprocal process where humans and AI co-adapt through interaction, evaluation, and value-centered design. Building on our past CHI 2025 BiAlign SIG and ICLR 2025 Work… ▽ More The rapid integration of generative AI into everyday life underscores the need to move beyond unidirectional alignment models that only adapt AI to human values. This workshop focuses on bidirectional human-AI alignment, a dynamic, reciprocal process where humans and AI co-adapt through interaction, evaluation, and value-centered design. Building on our past CHI 2025 BiAlign SIG and ICLR 2025 Workshop, this workshop will bring together interdisciplinary researchers from HCI, AI, social sciences and more domains to advance value-centered AI and reciprocal human-AI collaboration. We focus on embedding human and societal values into alignment research, emphasizing not only steering AI toward human values but also enabling humans to critically engage with and evolve alongside AI systems. Through talks, interdisciplinary discussions, and collaborative activities, participants will explore methods for interactive alignment, frameworks for societal impact evaluation, and strategies for alignment in dynamic contexts. This workshop aims to bridge the disciplines' gaps and establish a shared agenda for responsible, reciprocal human-AI futures. △ Less

Submitted 25 December, 2025; originally announced December 2025.

Comments: CHI 2026 BiAlign Workshop

Probing the environment around GW170817 with DESI: insights on galaxy group peculiar velocities for standard siren measurements

Authors: A. J. Amsellem, A. Palmese, K. Douglass, C. Howlett, Juliana S. M. Karp, I. Magaña Hernandez, J. Moustakas, R. H. Wechsler, J. Aguilar, S. Ahlen, S. Benzvi, D. Bianchi, D. Brooks, A. Carr, T. Claybaugh, A. Cuceu, Tamara M. Davis, A. de la Macorra, Arjun Dey, Biprateep Dey, P. Doel, A. Font-Ribera, J. E. Forero-Romero, E. Gaztañaga, S. Gontcho A Gontcho , et al. (34 additional authors not shown)

Abstract: We present a new measurement of the Hubble constant, $H_0$, following the gravitational wave event GW170817 and Dark Energy Spectroscopic Instrument (DESI) observations. A standard siren measurement with a nearby (luminosity distance $\sim 40 $ Mpc) event such as GW170817 is typically sensitive to the peculiar motion of the host galaxy due to local dynamics. Previous measurements from this event h… ▽ More We present a new measurement of the Hubble constant, $H_0$, following the gravitational wave event GW170817 and Dark Energy Spectroscopic Instrument (DESI) observations. A standard siren measurement with a nearby (luminosity distance $\sim 40 $ Mpc) event such as GW170817 is typically sensitive to the peculiar motion of the host galaxy due to local dynamics. Previous measurements from this event have taken advantage of peculiar velocity measurements of nearby galaxies, including a handful of objects in the galaxy group that the host of the event, NGC 4993, has been associated with. Still, the group's properties and NGC 4993's membership were debated. We present DESI observations of thousands of galaxies in the vicinity of NGC 4993, resulting in 39 group galaxies and a five-fold increase in galaxies compared to previous observations with many of these galaxies contributing to a peculiar velocity measurement. Examining the local dynamics, our observations support the presence of a galaxy group of which NGC 4993 is part with a halo mass of order $\sim$$10^{13}~M_\odot$. Using peculiar velocity measurements from our Fundamental Plane galaxies observations, we find $H_0 =70.9^{+6.4}_{-8.5}$ km s$^{-1}$ Mpc$^{-1}$. In addition, using a peculiar velocity measurement for NGC 4993 from Surface Brightness Fluctuations in Cosmicflows-4 we find $H_0 =73.4^{+3.3}_{-3.9}$ km s$^{-1}$ Mpc$^{-1}$. We study the impact of different galaxy selection criteria on the determination of the peculiar velocity and, in turn, on the $H_0$ measurement. Our results highlight the importance of multiplexed spectroscopic observations of the environments of gravitational wave events to probe local dynamics, which can ultimately affect standard siren measurements. △ Less

Submitted 9 December, 2025; originally announced December 2025.

Comments: 22 pages, 6 figures, and 1 table

The Binary Fraction of Stars in the Dwarf Galaxy Ursa Minor via Dark Energy Spectroscopic Instrument

Authors: Tian Qiu, Wenting Wang, Sergey Koposov, Ting S. Li, Nathan R. Sandford, Joan Najita, Songting Li, Jiaxin Han, Arjun Dey, Constance Rockosi, Boris Gaensicke, Jesse Han, Benjamin Alan Weaver, Adam Myers, Jessica Nicole Aguilar, Steven Ahlen, Carlos Allende Prieto, Davide Bianchi, David Brooks, Todd Claybaugh, Axel de la Macorra, Peter Doel, Andreu Font-Ribera, Jaime Forero-Romero, Enrique Gaztanaga , et al. (23 additional authors not shown)

Abstract: We utilize multi-epoch line-of-sight velocity measurements from the Milky Way Survey of the Dark Energy Spectroscopic Instrument to estimate the binary fraction for member stars in the dwarf spheroidal galaxy Ursa Minor. Our dataset comprises 670 distinct member stars, with a total of more than 2,000 observations collected over approximately one year. We constrain the binary fraction for UMi to be… ▽ More We utilize multi-epoch line-of-sight velocity measurements from the Milky Way Survey of the Dark Energy Spectroscopic Instrument to estimate the binary fraction for member stars in the dwarf spheroidal galaxy Ursa Minor. Our dataset comprises 670 distinct member stars, with a total of more than 2,000 observations collected over approximately one year. We constrain the binary fraction for UMi to be $0.61^{+0.16}_{-0.20}$ and $0.69^{+0.19}_{-0.17}$, with the binary orbital parameter distributions based on solar neighborhood observation from Duquennoy & Mayor (1991) and Moe & Di Stefano (2017), respectively. Furthermore, by dividing our data into two subsamples at the median metallicity, we identify that the binary fraction for the metal-rich ([Fe/H]>-2.14) population is slightly higher than that of the metal-poor ([Fe/H]<-2.14) population. Based on the Moe & Di Stefano model, the best-constrained binary fractions for metal-rich and metal-poor populations in UMi are $0.86^{+0.14}_{-0.24}$ and $0.48^{+0.26}_{-0.19}$, respectively. After a thorough examination, we find that this offset cannot be attributed to sample selection effects. We also divide our data into two subsamples according to their projected radius to the center of UMi, and find that the more centrally concentrated population in a denser environment has a lower binary fraction of $0.33^{+0.30}_{-0.20}$, compared with $1.00^{+0.00}_{-0.32}$ for the subsample in more outskirts. △ Less

Submitted 10 February, 2026; v1 submitted 4 December, 2025; originally announced December 2025.

Comments: 23 pages, 14 figures

The Composite Spectrum of QSO Absorption Line Systems in DESI DR2

Authors: Lucas Napolitano, Adam D. Myers, Adam Tedeschi, Abhijeet Anand, Hiram K. Herrera-Alcantar, Jessica Aguilar, Steven Ahlen, Stephen Bailey, Segev BenZvi, Davide Bianchi, David Brooks, Todd Claybaugh, Andrei Cuceu, Axel de la Macorra, Arjun Dey, Biprateep Dey, Peter Doel, Andreu Font-Ribera, Jaime E. Forero-Romero, Enrique Gaztanaga, Satya Gontcho A Gontcho, Gaston Gutierrez, Julien Guy, Dick Joyce, Anthony Kremin , et al. (21 additional authors not shown)

Abstract: We present details regarding the construction of a composite spectrum of quasar (QSO) absorption line systems. In this composite spectrum we identify more than 70 absorption lines, and observe oxygen and hydrogen emission features at a higher signal-to-noise ratio than in any previous study. As the light from a distant quasar travels towards an observer, it may interact with the circumgalactic med… ▽ More We present details regarding the construction of a composite spectrum of quasar (QSO) absorption line systems. In this composite spectrum we identify more than 70 absorption lines, and observe oxygen and hydrogen emission features at a higher signal-to-noise ratio than in any previous study. As the light from a distant quasar travels towards an observer, it may interact with the circumgalactic medium environment of an intervening galaxy, forming absorption lines. In order to maximize the signal of these absorption lines, we have selected a sample of 238,838 quasar spectra from the second data release of the Dark Energy Spectroscopic Instrument (DESI), each identified to have absorption lines resulting from such an interaction. By stacking these spectra in the restframe of the absorption, and calculating a median composite spectrum, we are able to isolate and enhance these absorption lines. We provide a full atlas of all detected absorption and emission lines as well as their fit centroids and equivalent width values. This atlas should aid in future studies investigating the compositions and physical conditions of these absorbers. △ Less

Submitted 2 December, 2025; originally announced December 2025.

Comments: 16 pages, 9 figures

Recursive entropy in thermodynamics: expounding the statistical-physics basis of the zentropy approach

Authors: Luke Allen Myers, Nigel Lee En Hew, Shun-Li Shang, Zi-Kui Liu

Abstract: The recursive property of entropy is well known in information theory; however, the concept is underutilized in thermodynamics, despite being the field where the concept of entropy originated. The zentropy approach is built on this idea, and it has emerged as a useful framework for describing thermodynamic systems across multiple scales, yet its statistical-physics foundation has not been fully ar… ▽ More The recursive property of entropy is well known in information theory; however, the concept is underutilized in thermodynamics, despite being the field where the concept of entropy originated. The zentropy approach is built on this idea, and it has emerged as a useful framework for describing thermodynamic systems across multiple scales, yet its statistical-physics foundation has not been fully articulated. In this work, we establish that foundation by showing that the recursive property allows us to coarse-grain thermodynamic systems into the most useful groups, and deriving the Helmholtz energy and partition function by maximizing entropy in its recursive form. This derivation clarifies the thermodynamic meaning of so-called "states that depend on temperature" as coarse-grained configurations, and maintains a clear distinction between the physical and statistical aspects of statistical mechanics. We then illustrate the usefulness of the approach through two representative applications: magnetic materials, where configurations are defined by spin arrangements, and liquids, where configurations are defined by nearest-neighbor environments. In both cases, the framework enables physically meaningful coarse-graining and captures emergent behavior arising from probability redistribution among configurations. These results position zentropy as an exact and flexible multiscale framework for thermodynamics and statistical mechanics, particularly for systems that admit a natural hierarchical grouping of states. △ Less

Submitted 15 May, 2026; v1 submitted 6 November, 2025; originally announced November 2025.

DESI Strong Lens Foundry II: DESI Spectroscopy for Strong Lens Candidates

Authors: Xiaosheng Huang, Jose Carlos Inchausti, Christopher J. Storfer, S. Tabares-Tarquinio, J. Moustakas, W. Sheu, S. Agarwal, M. Tamargo-Arizmendi, D. J. Schlegel, J. Aguilar, S. Ahlen, G. Aldering, S. Bailey, S. Banka, S. BenZvi, D. Bianchi, A. Bolton, D. Brooks, A. Cikota, T. Claybaugh, K. S. Dawson, A. de la Macorra, A. Dey, P. Doel, J. Edelstein , et al. (37 additional authors not shown)

Abstract: We present the Dark Energy Spectroscopic Instrument (DESI) Strong Lensing Secondary Target Program. This is a spectroscopic follow-up program for strong gravitational lens candidates found in the DESI Legacy Imaging Surveys footprint. Spectroscopic redshifts for the lenses and lensed source are crucial for lens modeling to obtain physical parameters. The spectroscopic catalog in this paper consist… ▽ More We present the Dark Energy Spectroscopic Instrument (DESI) Strong Lensing Secondary Target Program. This is a spectroscopic follow-up program for strong gravitational lens candidates found in the DESI Legacy Imaging Surveys footprint. Spectroscopic redshifts for the lenses and lensed source are crucial for lens modeling to obtain physical parameters. The spectroscopic catalog in this paper consists of 73 candidate systems from the DESI Early Data Release (EDR). We have confirmed 20 strong lensing systems and determined four to not be lenses. For the remaining systems, more spectroscopic data from ongoing and future observations will be presented in future publications. We discuss the implications of our results for lens searches with neural networks in existing and future imaging surveys as well as for lens modeling. This Strong Lensing Secondary Target Program is part of the DESI Strong Lens Foundry project, and this is Paper II of a series on this project. △ Less

Submitted 22 September, 2025; originally announced September 2025.

Comments: 67 pages, 77 figures, and 5 tables

DESI Strong Lens Foundry III: Keck Spectroscopy for Strong Lenses Discovered Using Residual Neural Networks

Authors: Shrihan Agarwal, Xiaosheng Huang, William Sheu, Christopher J. Storfer, Marcos Tamargo-Arizmendi, Suchitoto Tabares-Tarquinio, D. J. Schlegel, G. Aldering, A. Bolton, A. Cikota, Arjun Dey, A. Filipp, E. Jullo, K. J. Kwon, S. Perlmutter, Y. Shu, E. Sukay, N. Suzuki, J. Aguilar, S. Ahlen, S. BenZvi, D. Brooks, T. Claybaugh, P. Doel, J. E. Forero-Romero , et al. (27 additional authors not shown)

Abstract: We present spectroscopic data of strong lenses and their source galaxies using the Keck Near-Infrared Echellette Spectrometer (NIRES) and the Dark Energy Spectroscopic Instrument (DESI), providing redshifts necessary for nearly all strong-lensing applications with these systems, especially the extraction of physical parameters from lensing modeling. These strong lenses were found in the DESI Legac… ▽ More We present spectroscopic data of strong lenses and their source galaxies using the Keck Near-Infrared Echellette Spectrometer (NIRES) and the Dark Energy Spectroscopic Instrument (DESI), providing redshifts necessary for nearly all strong-lensing applications with these systems, especially the extraction of physical parameters from lensing modeling. These strong lenses were found in the DESI Legacy Imaging Surveys using Residual Neural Networks (ResNet) and followed up by our Hubble Space Telescope program, with all systems displaying unambiguous lensed arcs. With NIRES, we target eight lensed sources at redshifts difficult to measure in the optical range and determine the source redshifts for six, between $z_s$ = 1.675 and 3.332. DESI observed one of the remaining source redshifts, as well as an additional source redshift within the six systems. The two systems with non-detections by NIRES were observed for a considerably shorter 600s at high airmass. Combining NIRES infrared spectroscopy with optical spectroscopy from our DESI Strong Lensing Secondary Target Program, these results provide the complete lens and source redshifts for six systems, a resource for refining automated strong lens searches in future deep- and wide-field imaging surveys and addressing a range of questions in astrophysics and cosmology. △ Less

Submitted 19 April, 2026; v1 submitted 22 September, 2025; originally announced September 2025.

Comments: 16 pages, 6 figures, 2 tables. Submitted

Journal ref: ApJ 1001 162 (2026)

Density Dependence of the Phases of the $ν= 1$ Integer Quantum Hall Plateau in Low Disorder Electron Gases

Authors: Haoyun Huang, Waseem Hussain, S. A. Myers, L. N. Pfeiffer, K. W. West, G. A. Csáthy

Abstract: Recent magnetotransport measurements in low-disorder electron systems confined to GaAs/AlGaAs samples revealed that the $ν= 1$ integer quantum Hall plateau is broken into three distinct regions. These three regions were associated with two phases with different types of bulk localization: the Anderson insulator is due to random quasiparticle localization, and the integer quantum Hall Wigner solid… ▽ More Recent magnetotransport measurements in low-disorder electron systems confined to GaAs/AlGaAs samples revealed that the $ν= 1$ integer quantum Hall plateau is broken into three distinct regions. These three regions were associated with two phases with different types of bulk localization: the Anderson insulator is due to random quasiparticle localization, and the integer quantum Hall Wigner solid is due to pinning of a stiff quasiparticle lattice. We highlight universal properties of the $ν= 1$ plateau: the structure of the stability diagram, the non-monotonic dependence of the activation energy on the filling factor, and the alignment of features of the activation energy with features of the stability regions of the different phases are found to be similar in three samples spanning a wide range of electron densities. We also discuss quantitative differences between the samples, such as the dependence of the onset temperature and the activation energy of the integer quantum Hall Wigner solid on the electron density. Our findings provide insights into the localization behavior along the $ν= 1$ integer quantum Hall plateau in the low disorder regime. △ Less

Submitted 17 September, 2025; originally announced September 2025.

Journal ref: Physica Status Solidi RRL 19, 2400376 (2025)

Counterpart identification and classification for eRASS1 and characterisation of the AGN content

Authors: M. Salvato, J. Wolf, T. Dwelly, H. Starck, J. Buchner, R. Shirley, A. Merloni, A. Georgakakis, F. Balzer, M. Brusa, A. Rau, S. Freund, D. Lang, T. Liu, G. Lamer, A. Schwope, W. Roster, S. Waddell, M. Scialpi, Z. Igo, M. Kluge, F. Mannucci, S. Tiwari, D. Homan, M. Krumpe , et al. (22 additional authors not shown)

Abstract: [abridged] Accurately accounting for the AGN phase in galaxy evolution requires a large, clean AGN sample. This is now possible with SRG/eROSITA. The public Data Release 1 (DR1, Jan 31, 2024) includes 930,203 sources from the Western Galactic Hemisphere. The data enable the selection of a large AGN sample and the discovery of rare sources. However, scientific return depends on accurate characteris… ▽ More [abridged] Accurately accounting for the AGN phase in galaxy evolution requires a large, clean AGN sample. This is now possible with SRG/eROSITA. The public Data Release 1 (DR1, Jan 31, 2024) includes 930,203 sources from the Western Galactic Hemisphere. The data enable the selection of a large AGN sample and the discovery of rare sources. However, scientific return depends on accurate characterisation of the X-ray emitters, requiring high-quality multiwavelength data. This paper presents the identification and classification of optical and infrared counterparts to eRASS1 sources using Gaia DR3, CatWISE2020, and Legacy Survey DR10 (LS10) with the Bayesian NWAY algorithm and trained priors. Sources were classified as Galactic or extragalactic via a Machine Learning model combining optical/IR and X-ray properties, trained on a reference sample. For extragalactic LS10 sources, photometric redshifts were computed using Circlez. Within the LS10 footprint, all 656,614 eROSITA/DR1 sources have at least one possible optical counterpart; about 570,000 are extragalactic and likely AGN. Half are new detections compared to AllWISE, Gaia, and Quaia AGN catalogues. Gaia and CatWISE2020 counterparts are less reliable, due to the surveys shallowness and the limited amount of features available to assess the probability of being an X-ray emitter. In the Galactic Plane, where the overdensity of stellar sources also increases the chance of associations, using conservative reliability cuts, we identify approximately 18,000 Gaia and 55,000 CatWISE2020 extragalactic sources. We release three high-quality counterpart catalogues, plus the training and validation sets, as a benchmark for the field. These datasets have many applications, but in particular empower researchers to build AGN samples tailored for completeness and purity, accelerating the hunt for the Universes most energetic engines. △ Less

Submitted 21 October, 2025; v1 submitted 2 September, 2025; originally announced September 2025.

Comments: A&A, Paper accepted. The catalogues of LS10, CW2020 Gaia DR3 counterparts and the training samples from 4XMM and Chandra are available via eROSITA web page (https://erosita.mpe.mpg.de/dr1/AllSkySurveyData_dr1/Catalogues_dr1/ ,files 4-12), Zenodo (https://zenodo.org/records/17404798) and Vizier. In Zenodo, the Jupiter notebook for creating samples of AGN is also available

Journal ref: A&A 704, A344 (2025)

Strong Lens Discoveries in DESI Legacy Imaging Surveys DR10 with Two Deep Learning Architectures

Authors: Jose Carlos Inchausti, Christopher J. Storfer, Xiaosheng Huang, Yuan-Ming Hsu, Brandt Kaufmann, Chaitanya Pasupala, S. Banka, A. Dey, D. Lang, A. Meisner, J. Moustakas, A. D. Myers, E. F. Schlafly, D. J. Schlegel

Abstract: We have conducted a search for strong gravitational lensing systems in the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 10 (DR10). This paper is the fourth in a series of searches (following Huang et al. 2020; Huang et al. 2021; Storfer et al. 2024, Paper I, II, & III respectively). This is the first catalog of lens candidates covering nearly the entirety of the… ▽ More We have conducted a search for strong gravitational lensing systems in the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 10 (DR10). This paper is the fourth in a series of searches (following Huang et al. 2020; Huang et al. 2021; Storfer et al. 2024, Paper I, II, & III respectively). This is the first catalog of lens candidates covering nearly the entirety of the extragalactic sky south of declination $δ\approx +32$ deg, all of it observed by the DECam, covering $\sim$14,000 $deg^2$. We impose a $z$-band magnitude cut of < 20 in AB magnitude. We deploy a Residual Neural Network and EfficientNet as an ensemble trained on a compilation of known lensing systems and high-grade candidates as well as nonlenses in the same footprint. The predictions from these two base models are aggregated using a meta-learner. After applying our ensemble to the survey data, we exclude known candidates and systems, and use our own visual inspection portal to rank images in the top 0.01 percentile of all neural network recommendations. We have found 811 new lens candidates. These include 484 new candidates in the Legacy Surveys DR9 footprint, all parts of which have been searched for strong lenses at least once before, either by our group or others. Combining the discoveries from this work with those from Paper I (335), II (1210), and III (1512), we have discovered a total of 3868 new candidates in the DESI Legacy Surveys. △ Less

Submitted 27 August, 2025; originally announced August 2025.

Comments: 21 pages, 13 figures, and 6 tables

Understanding Prompt Programming Tasks and Questions

Authors: Jenny T. Liang, Chenyang Yang, Agnia Sergeyuk, Travis D. Breaux, Brad A. Myers

Abstract: Prompting foundation models (FMs) like large language models (LLMs) have enabled new AI-powered software features (e.g., text summarization) that previously were only possible by fine-tuning FMs. Now, developers are embedding prompts in software, known as prompt programs. The process of prompt programming requires the developer to make many changes to their prompt. Yet, the questions developers as… ▽ More Prompting foundation models (FMs) like large language models (LLMs) have enabled new AI-powered software features (e.g., text summarization) that previously were only possible by fine-tuning FMs. Now, developers are embedding prompts in software, known as prompt programs. The process of prompt programming requires the developer to make many changes to their prompt. Yet, the questions developers ask to update their prompt is unknown, despite the answers to these questions affecting how developers plan their changes. With the growing number of research and commercial prompt programming tools, it is unclear whether prompt programmers' needs are being adequately addressed. We address these challenges by developing a taxonomy of 25 tasks prompt programmers do and 51 questions they ask, measuring the importance of each task and question. We interview 16 prompt programmers, observe 8 developers make prompt changes, and survey 50 developers. We then compare the taxonomy with 48 research and commercial tools. We find that prompt programming is not well-supported: all tasks are done manually, and 16 of the 51 questions -- including a majority of the most important ones -- remain unanswered. Based on this, we outline important opportunities for prompt programming tools. △ Less

Submitted 23 July, 2025; originally announced July 2025.

A Semi-Supervised Learning Method for the Identification of Bad Exposures in Large Imaging Surveys

Authors: Yufeng Luo, Adam D. Myers, Alex Drlica-Wagner, Dario Dematties, Salma Borchani, Francisco Valdes, Arjun Dey, David Schlegel, Rongpu Zhou, DESI Legacy Imaging Surveys Team

Abstract: As the data volume of astronomical imaging surveys rapidly increases, traditional methods for image anomaly detection, such as visual inspection by human experts, are becoming impractical. We introduce a machine-learning-based approach to detect poor-quality exposures in large imaging surveys, with a focus on the DECam Legacy Survey (DECaLS) in regions of low extinction (i.e., $E(B-V)<0.04$). Our… ▽ More As the data volume of astronomical imaging surveys rapidly increases, traditional methods for image anomaly detection, such as visual inspection by human experts, are becoming impractical. We introduce a machine-learning-based approach to detect poor-quality exposures in large imaging surveys, with a focus on the DECam Legacy Survey (DECaLS) in regions of low extinction (i.e., $E(B-V)<0.04$). Our semi-supervised pipeline integrates a vision transformer (ViT), trained via self-supervised learning (SSL), with a k-Nearest Neighbor (kNN) classifier. We train and validate our pipeline using a small set of labeled exposures observed by surveys with the Dark Energy Camera (DECam). A clustering-space analysis of where our pipeline places images labeled in ``good'' and ``bad'' categories suggests that our approach can efficiently and accurately determine the quality of exposures. Applied to new imaging being reduced for DECaLS Data Release 11, our pipeline identifies 780 problematic exposures, which we subsequently verify through visual inspection. Being highly efficient and adaptable, our method offers a scalable solution for quality control in other large imaging surveys. △ Less

Submitted 25 February, 2026; v1 submitted 17 July, 2025; originally announced July 2025.

Comments: 22 pages, 12 figures. Published in the Open Journal of Astrophysics

HIF: The hypergraph interchange format for higher-order networks

Authors: Martín Coll, Cliff A. Joslyn, Nicholas W. Landry, Quintino Francesco Lotito, Audun Myers, Joshua Pickard, Brenda Praggastis, Przemysław Szufel

Abstract: Many empirical systems contain complex interactions of arbitrary size, representing, for example, chemical reactions, social groups, co-authorship relationships, and ecological dependencies. These interactions are known as higher-order interactions and the collection of these interactions comprise a higher-order network, or hypergraph. Hypergraphs have established themselves as a popular and versa… ▽ More Many empirical systems contain complex interactions of arbitrary size, representing, for example, chemical reactions, social groups, co-authorship relationships, and ecological dependencies. These interactions are known as higher-order interactions and the collection of these interactions comprise a higher-order network, or hypergraph. Hypergraphs have established themselves as a popular and versatile mathematical representation of such systems and a number of software packages written in various programming languages have been designed to analyze these networks. However, the ecosystem of higher-order network analysis software is fragmented due to specialization of each software's programming interface and compatible data representations. To enable seamless data exchange between higher-order network analysis software packages, we introduce the Hypergraph Interchange Format (HIF), a standardized format for storing higher-order network data. HIF supports multiple types of higher-order networks, including undirected hypergraphs, directed hypergraphs, and abstract simplicial complexes, while actively exploring extensions to represent multiplex hypergraphs, temporal hypergraphs, and ordered hypergraphs. To accommodate the wide variety of metadata used in different contexts, HIF also includes support for attributes associated with nodes, edges, and incidences. This initiative is a collaborative effort involving authors, maintainers, and contributors from prominent hypergraph software packages. This project introduces a JSON schema with corresponding documentation and unit tests, example HIF-compliant datasets, and tutorials demonstrating the use of HIF with several popular higher-order network analysis software packages. △ Less

Submitted 30 January, 2026; v1 submitted 15 July, 2025; originally announced July 2025.

Comments: 21 pages, 9 figures

Journal ref: Net Sci 13 (2025) e21

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Authors: Gheorghe Comanici, Eric Bieber, Mike Schaekermann, Ice Pasupat, Noveen Sachdeva, Inderjit Dhillon, Marcel Blistein, Ori Ram, Dan Zhang, Evan Rosen, Luke Marris, Sam Petulla, Colin Gaffney, Asaf Aharoni, Nathan Lintz, Tiago Cardal Pais, Henrik Jacobsson, Idan Szpektor, Nan-Jiang Jiang, Krishna Haridasan, Ahmed Omran, Nikunj Saunshi, Dara Bahri, Gaurav Mishra, Eric Chu , et al. (3410 additional authors not shown)

Abstract: In this report, we introduce the Gemini 2.X model family: Gemini 2.5 Pro and Gemini 2.5 Flash, as well as our earlier Gemini 2.0 Flash and Flash-Lite models. Gemini 2.5 Pro is our most capable model yet, achieving SoTA performance on frontier coding and reasoning benchmarks. In addition to its incredible coding and reasoning skills, Gemini 2.5 Pro is a thinking model that excels at multimodal unde… ▽ More In this report, we introduce the Gemini 2.X model family: Gemini 2.5 Pro and Gemini 2.5 Flash, as well as our earlier Gemini 2.0 Flash and Flash-Lite models. Gemini 2.5 Pro is our most capable model yet, achieving SoTA performance on frontier coding and reasoning benchmarks. In addition to its incredible coding and reasoning skills, Gemini 2.5 Pro is a thinking model that excels at multimodal understanding and it is now able to process up to 3 hours of video content. Its unique combination of long context, multimodal and reasoning capabilities can be combined to unlock new agentic workflows. Gemini 2.5 Flash provides excellent reasoning abilities at a fraction of the compute and latency requirements and Gemini 2.0 Flash and Flash-Lite provide high performance at low latency and cost. Taken together, the Gemini 2.X model generation spans the full Pareto frontier of model capability vs cost, allowing users to explore the boundaries of what is possible with complex agentic problem solving. △ Less

Submitted 19 December, 2025; v1 submitted 7 July, 2025; originally announced July 2025.

Comments: 72 pages, 17 figures

Reconstructing Quasar Spectra and Measuring the Ly$α$ Forest with ${\rm S{\scriptsize pender}Q}$

Authors: ChangHoon Hahn, Satya Gontcho A Gontcho, Peter Melchior, Hiram K. Herrera-Alcantar, Jessica Nicole Aguilar, Steven Ahlen, Davide Bianchi, David Brooks, Todd Claybaugh, Axel de la Macorra, Arjun Dey, Peter Doel, Jaime E. Forero-Romero, Gaston Gutierrez, Mustapha Ishak, Stephanie Juneau, David Kirkby, Theodore Kisner, Anthony Kremin, Andrew Lambert, Martin Landriau, Laurent Le Guillou, Marc Manera, Ramon Miquel, John Moustakas , et al. (15 additional authors not shown)

Abstract: Quasar spectra carry the imprint of foreground intergalactic medium (IGM) through absorption features. In particular, absorption caused by neutral hydrogen gas, the ``Ly$α$ forest,'' is a key spectroscopic tracer for cosmological analyses used to measure cosmic expansion and test physics beyond the standard model. Despite their importance, current methods for measuring LyA absorption cannot direct… ▽ More Quasar spectra carry the imprint of foreground intergalactic medium (IGM) through absorption features. In particular, absorption caused by neutral hydrogen gas, the ``Ly$α$ forest,'' is a key spectroscopic tracer for cosmological analyses used to measure cosmic expansion and test physics beyond the standard model. Despite their importance, current methods for measuring LyA absorption cannot directly derive the intrinsic quasar continuum and make strong assumptions on its shape, thus distorting the measured LyA clustering. We present SpenderQ, a ML-based approach for directly reconstructing the intrinsic quasar spectra and measuring the LyA forest from observations. SpenderQ uses the Spender spectrum autoencoder to learn a compact and redshift-invariant latent encoding of quasar spectra, combined with an iterative procedure to identify and mask absorption regions. To demonstrate its performance, we apply SpenderQ to 400,000 synthetic quasar spectra created to validate the Dark Energy Spectroscopic Instrument Year 1 LyA cosmological analyses. SpenderQ accurately reconstructs the true intrinsic quasar spectra, including the broad LyB, LyA, SiIV, CIV, and CIII emission lines. Redward of LyA, SpenderQ provides percent-level reconstructions of the true quasar spectra. Blueward of LyA, SpenderQ reconstructs the true spectra to < 5\%. SpenderQ reproduces the shapes of individual quasar spectra more robustly than the current state-of-the-art. We, thus, expect it will significantly reduce biases in LyA clustering measurements and enable studies of quasars and their physical properties. SpenderQ also provides informative latent variable encodings that can be used to, e.g., classify quasars with Broad Absorption Lines. Overall, SpenderQ provides a new data-driven approach for unbiased LyA forest measurements in cosmological, quasar, and IGM studies. △ Less

Submitted 25 June, 2025; v1 submitted 23 June, 2025; originally announced June 2025.

Comments: 20 pages; 10 figures; comments welcome

The Backup Program of the Dark Energy Spectroscopic Instrument's Milky Way Survey

Authors: Arjun Dey, Sergey E. Koposov, Joan R. Najita, Andrew P. Cooper, B. T. Gänsicke, Adam D. Myers, A. Raichoor, Daniel J. Eisenstein, E. F. Schlafly, C. Allende Prieto, Leandro Beraldo e Silva, Ting S. Li, M. Valluri, Stéphanie Juneau, Mika Lambert, S. Li, Guillaume F. Thomas, Wenting Wang, Alexander H. Riley, N. Kizhuprakkat, J. Aguilar, S. Ahlen, S. Bailey, D. Bianchi, D. Brooks , et al. (44 additional authors not shown)

Abstract: The Milky Way Backup Program (MWBP), a survey currently underway with the Dark Energy Spectroscopic Instrument (DESI) on the Nicholas U. Mayall 4-m Telescope, works at the margins of the DESI Main surveys to obtain spectra of millions of additional stars from the Gaia catalog. Efficiently utilizing twilight times (<18 deg) and poor weather conditions, the MWBP extends the range of stellar sources… ▽ More The Milky Way Backup Program (MWBP), a survey currently underway with the Dark Energy Spectroscopic Instrument (DESI) on the Nicholas U. Mayall 4-m Telescope, works at the margins of the DESI Main surveys to obtain spectra of millions of additional stars from the Gaia catalog. Efficiently utilizing twilight times (<18 deg) and poor weather conditions, the MWBP extends the range of stellar sources studied to both brighter magnitudes and lower Galactic latitude and declination than the stars studied in DESI's Main Milky Way Survey. While the MWBP prioritizes candidate giant stars selected from the Gaia catalog (using color and parallax criteria), it also includes an unbiased sample of bright stars (i.e., 11.2 < G < 16 mag) as well as fainter sources (to G < 19 mag). As of March 1, 2025, the survey had obtained spectra of ~7 million stars, approximately 1.2 million of which are included in the DESI Data Release 1. The full survey, when completed, will cover an area of more than 21,000 square degrees and include approximately 10 million Gaia sources, roughly equal to the number of stellar spectra obtained through the DESI Main Survey, while only utilizing <9% of all DESI observing time. △ Less

Submitted 22 May, 2025; originally announced May 2025.

Comments: 19 pages, 20 figures. Submitted to The Astronomical Journal on 22 May 2025

Using Active Learning to Improve Quasar Identification for the DESI Spectra Processing Pipeline

Authors: Dylan Green, David Kirkby, J. Aguilar, S. Ahlen, D. M. Alexander, E. Armengaud, S. Bailey, A. Bault, D. Bianchi, A. Brodzeller, D. Brooks, T. Claybaugh, R. de Belsunce, A. de la Macorra, P. Doel, V. A. Fawcett, S. Ferraro, A. Font-Ribera, J. E. Forero-Romero, E. Gaztañaga, S. Gontcho A Gontcho, G. Gutierrez, M. Ishak, S. Juneau, R. Kehoe , et al. (29 additional authors not shown)

Abstract: The Dark Energy Spectroscopic Instrument (DESI) survey uses an automatic spectral classification pipeline to classify spectra. QuasarNET is a convolutional neural network used as part of this pipeline originally trained using data from the Baryon Oscillation Spectroscopic Survey (BOSS). In this paper we implement an active learning algorithm to optimally select spectra to use for training a new ve… ▽ More The Dark Energy Spectroscopic Instrument (DESI) survey uses an automatic spectral classification pipeline to classify spectra. QuasarNET is a convolutional neural network used as part of this pipeline originally trained using data from the Baryon Oscillation Spectroscopic Survey (BOSS). In this paper we implement an active learning algorithm to optimally select spectra to use for training a new version of the QuasarNET weights file using only DESI data, specifically to improve classification accuracy. This active learning algorithm includes a novel outlier rejection step using a Self-Organizing Map to ensure we label spectra representative of the larger quasar sample observed in DESI. We perform two iterations of the active learning pipeline, assembling a final dataset of 5600 labeled spectra, a small subset of the approx 1.3 million quasar targets in DESI's Data Release 1. When splitting the spectra into training and validation subsets we meet or exceed the previously trained weights file in completeness and purity calculated on the validation dataset with less than one tenth of the amount of training data. The new weights also more consistently classify objects in the same way when used on unlabeled data compared to the old weights file. In the process of improving QuasarNET's classification accuracy we discovered a systemic error in QuasarNET's redshift estimation and used our findings to improve our understanding of QuasarNET's redshifts. △ Less

Submitted 3 September, 2025; v1 submitted 2 May, 2025; originally announced May 2025.

Comments: 26 pages, 10 figures. Prepared for submission to JCAP

An Algebraic Approach to Asymmetric Delegation and Polymorphic Label Inference (Technical Report)

Authors: Silei Ren, Coşku Acay, Andrew C. Myers

Abstract: Language-based information flow control (IFC) enables reasoning about and enforcing security policies in decentralized applications. While information flow properties are relatively extensional and compositional, designing expressive systems that enforce such properties remains challenging. In particular, it can be difficult to use IFC labels to model certain security assumptions, such as semi-hon… ▽ More Language-based information flow control (IFC) enables reasoning about and enforcing security policies in decentralized applications. While information flow properties are relatively extensional and compositional, designing expressive systems that enforce such properties remains challenging. In particular, it can be difficult to use IFC labels to model certain security assumptions, such as semi-honest agents. Motivated by these modeling limitations, we study the algebraic semantics of lattice-based IFC label models, and propose a semantic framework that allows formalizing asymmetric delegation, which is partial delegation of confidentiality or integrity. Our framework supports downgrading of information and ensures their safety through nonmalleable information flow (NMIF). To demonstrate the practicality of our framework, we design and implement a novel algorithm that statically checks NMIF and a label inference procedure that efficiently supports bounded label polymorphism, allowing users to write code generic with respect to labels. △ Less

Submitted 16 July, 2025; v1 submitted 29 April, 2025; originally announced April 2025.

Density Functional Theory ToolKit (DFTTK) to Automate First-Principles Thermodynamics via the Quasiharmonic Approximation

Authors: Nigel Lee En Hew, Luke Allen Myers, Axel van de Walle, Shun-Li Shang, Zi-Kui Liu

Abstract: The Helmholtz energy is a key thermodynamic quantity representing available energy to do work at a constant temperature and volume. Despite a well-established methodology from first-principles calculations, a comprehensive tool and database are still lacking. To address this gap, we developed an open-source Density Functional Theory Tool Kit (DFTTK), which automates first-principles thermodynamics… ▽ More The Helmholtz energy is a key thermodynamic quantity representing available energy to do work at a constant temperature and volume. Despite a well-established methodology from first-principles calculations, a comprehensive tool and database are still lacking. To address this gap, we developed an open-source Density Functional Theory Tool Kit (DFTTK), which automates first-principles thermodynamics using the quasiharmonic approximation (QHA) for Helmholtz energy predictions. This Python-based package provides a solution for automating the calculation and analysis of various contributions to Helmholtz energy, including the static total energy contributions at 0 K in terms of DFT-based energy-volume curves, vibrational contributions from the Debye-Gruneisen model and phonons, and thermal electronic contributions via the electronic density of states. The QHA is also implemented to calculate the Gibbs energy and associated properties at constant temperature and pressure. The present work demonstrates DFTTK's capabilities through case studies on a simple FCC Al and various collinear magnetic configurations of Invar Fe3Pt, where DFTTK enumerates all unique configurations and their associated multiplicities. DFTTK is freely available on GitHub, and its modular design allows for the easy addition of new workflows. △ Less

Submitted 23 April, 2025; originally announced April 2025.

The Topological Structures of the Orders of Hypergraphs

Authors: Robert E. Green, Cliff A. Joslyn, Audun Myers, Michael G. Rawson, Michael Robinson

Abstract: We provide first a categorical exploration of, and then completion of the mapping of the relationships among, three fundamental perspectives on binary relations: as the incidence matrices of hypergraphs, as the formal contexts of concept lattices, and as specifying topological cosheaves of simplicial (Dowker) complexes on simplicial (Dowker) complexes. We provide an integrative, functorial framewo… ▽ More We provide first a categorical exploration of, and then completion of the mapping of the relationships among, three fundamental perspectives on binary relations: as the incidence matrices of hypergraphs, as the formal contexts of concept lattices, and as specifying topological cosheaves of simplicial (Dowker) complexes on simplicial (Dowker) complexes. We provide an integrative, functorial framework combining previously known with three new results: 1) given a binary relation, there are order isomorphisms among the bounded edge order of the intersection complexes of its dual hypergraphs and its concept lattice; 2) the concept lattice of a context is an isomorphism invariant of the Dowker cosheaf (of abstract simplicial complexes) of that context; and 3) a novel Dowker cosheaf (of chain complexes) of a relation is an isomorphism invariant of the concept lattice of the context that generalizes Dowker's original homological result. We illustrate these concepts throughout with a running example, and demonstrate relationships to past results. △ Less

Submitted 18 April, 2025; v1 submitted 16 April, 2025; originally announced April 2025.

Report number: Information release PNNL-SA-210092

The DESI Y1 RR Lyrae catalog I: Empirical modeling of the cyclic variation of spectroscopic properties and a chemodynamical analysis of the outer halo

Authors: Gustavo E. Medina, Ting S. Li, Sergey E. Koposov, A. H. Riley, L. Beraldo e Silva, M. Valluri, W. Wang, A. Byström, O. Y. Gnedin, R. G. Carlberg, N. Kizhuprakkat, B. A. Weaver, J. Aguilar, S. Ahlen, D. Bianchi, D. Brooks, T. Claybaugh, A. P. Cooper, A. de la Macorra, A. Dey, P. Doel, A. Font-Ribera, J. E. Forero-Romero, E. Gaztañaga, S. Gontcho A Gontcho , et al. (22 additional authors not shown)

Abstract: We present the catalog of RR Lyrae stars (RRLs) observed in the first year of operations of the Dark Energy Spectroscopic Instrument (DESI) survey. This catalog contains 6,240 RRLs out to $\sim120$\,kpc from the Galactic center and over 12,000 individual epochs with homogeneously-derived stellar atmospheric parameters. We introduce a novel methodology to model the cyclical variation of the spectro… ▽ More We present the catalog of RR Lyrae stars (RRLs) observed in the first year of operations of the Dark Energy Spectroscopic Instrument (DESI) survey. This catalog contains 6,240 RRLs out to $\sim120$\,kpc from the Galactic center and over 12,000 individual epochs with homogeneously-derived stellar atmospheric parameters. We introduce a novel methodology to model the cyclical variation of the spectroscopic properties of RRLs from single-epoch measurements. We employ this method to infer the systemic velocities and mean temperatures of fundamental and first-overtone mode RRLs in our sample (without distinguishing between individual spectral lines). For fundamental mode pulsators, we obtain radial velocity curves with amplitudes of $\sim$30--80\,km\,s$^{-1}$ and effective temperature curves with 300--1,000\,K variations, whereas for first-overtone pulsators these amplitudes are $\sim20$\,km\,s$^{-1}$ and $\sim 600$\,K, respectively. We use our sample to study the metallicity distribution of the halo and its dependence on Galactocentric distance ($R_{\rm GC}$). Using a radius-dependent mixture model, we split the data into chemodynamically distinct components and find that our inner halo sample ($R_{\rm GC}\lesssim50$\,kpc) is predominantly composed of stars with [Fe/H] $\sim-1.5$ and largely radial orbits (with an anisotropy parameter $β\sim0.94$), that we associate with the Gaia-Sausage-Enceladus merger. Stars in the halo field exhibit a broader and more metal-poor [Fe/H] distribution with more circular orbits ($β\sim0.39$). The metallicity gradient of the metal-rich and the metal-poor components is found to be $0.005$ and $0.010$\,dex\,kpc$^{-1}$, respectively. Our catalog highlights DESI's tantalizing potential for studying the Milky Way and the pulsation properties of RRLs in the era of large spectroscopic surveys. △ Less

Submitted 3 June, 2026; v1 submitted 3 April, 2025; originally announced April 2025.

Comments: 36 pages, 19 figures, 6 tables. Accepted for publication in ApJ

NEOWISE Data Processing and Color Corrections for Near-Earth Asteroid Observations

Authors: Samuel A. Myers, Ellen S. Howell, Yanga R. Fernández, Sean E. Marshall, Christopher Magri, Ronald J. Vervack Jr., Mary L. Hinkle

Abstract: The Wide-field Infrared Survey Explorer and NEOWISE missions are a key source of thermal data for near-Earth asteroids (NEAs). These missions, which utilized a space-based platform in Earth orbit, produced thermal images across four different wavelength bands, W1 - W4, with effective wavelengths of 3.4, 4.6, 12, and 22 μm respectively. Despite its use for NEA observations though, the mission archi… ▽ More The Wide-field Infrared Survey Explorer and NEOWISE missions are a key source of thermal data for near-Earth asteroids (NEAs). These missions, which utilized a space-based platform in Earth orbit, produced thermal images across four different wavelength bands, W1 - W4, with effective wavelengths of 3.4, 4.6, 12, and 22 μm respectively. Despite its use for NEA observations though, the mission architecture was originally designed to observe stars. Thus, careful data analysis methods are crucial when working with NEA data to account for the differences between these objects. However, detailed information on how to work with these data can be difficult to find for users unfamiliar with the mission. The required information is well documented, but locating it can be challenging, and many details, such as specifics about color corrections, are not fully explained. Therefore, in this work, we provide a set of "lessons learned" for working with NEOWISE data, outline the basics of how to retrieve and process NEOWISE data for NEA investigations, and present an empirical method for color correction determination. We highlight the importance of this process by processing data for three NEAs, finding that nearly half of all available observations should be discarded. Finally, we present simple thermal model results based on different levels of data analysis to highlight how data processing can affect model results. △ Less

Submitted 1 April, 2025; originally announced April 2025.

Comments: 12 pages, 7 figures, 4 tables

Journal ref: Planet. Sci. J. 6 80 (2025)

eROSITA clusters dynamical state and their impact on the BCG luminosity

Authors: A. Zenteno, M. Kluge, R. Kharkrang, D. Hernandez-Lang, G. Damke, A. Saro, R. Monteiro-Oliveira, E. R. Carrasco, M. Salvato, J. Comparat, M. Fabricius, J. Snigula, P. Arevalo, H. Cuevas, J. L. Nilo Castellon, A. Ramirez, S. Véliz Astudillo, M. Landriau, A. D. Myers, E. Schlafly, F. Valdes, B. Weaver, J. J. Mohr, S. Grandis, M. Klein , et al. (8 additional authors not shown)

Abstract: The Spectrum Roentgen Gamma/eROSITA first public release contains 12,247 clusters and groups. We use the offset between the Brightest Cluster Galaxy (BCG) and the X--ray peak (D$_{\rm BCG-X}$) to classify the cluster dynamical state of 3,946 galaxy clusters and groups. The X--ray peaks come from the eROSITA survey while the BCG positions come from the DECaLS DR10 optical data, which includes the D… ▽ More The Spectrum Roentgen Gamma/eROSITA first public release contains 12,247 clusters and groups. We use the offset between the Brightest Cluster Galaxy (BCG) and the X--ray peak (D$_{\rm BCG-X}$) to classify the cluster dynamical state of 3,946 galaxy clusters and groups. The X--ray peaks come from the eROSITA survey while the BCG positions come from the DECaLS DR10 optical data, which includes the DECam eROSITA Survey optical data. We aim to investigate the evolution of the merger and relaxed cluster distributions with redshift and mass, and their impact on the BCG. We model the distribution of D$_{\rm BCG-X}$ as the sum of two Rayleigh distributions representing the cluster's relaxed and disturbed populations, and explore their evolution with redshift and mass. To explore the impact of the cluster's dynamical state on the BCG luminosity, we separate the main sample according to the dynamical state. We define clusters as relaxed if D$_{\rm BCG-X}$ < 0.25$r_{500}$, disturbed if D$_{\rm BCG-X}$>0.5$r_{500}$, and as `diverse' otherwise. We find no evolution of the merging fraction in redshift and mass. We observe that the width of the relaxed distribution to increase with redshift, while the width of the two Rayleigh distributions decreases with mass. The analysis reveals that BCGs in relaxed clusters are brighter than BCGs in both the disturbed and diverse cluster population. The most significant differences are found for high mass clusters at higher redshift. The results suggest that BCGs in low-mass clusters are less centrally bound than those in high-mass systems, irrespective of dynamical state. Over time, BCGs in relaxed clusters progressively align with the potential center. This alignment correlates with their luminosity growth relative to BCGs in dynamically disturbed clusters, underscoring the critical role of the clusters dynamical state in regulating BCG evolution. [Abridged] △ Less

Submitted 26 March, 2025; originally announced March 2025.

Comments: 10 pages, 6 figures, accepted in A&A

Journal ref: A&A 698, A171 (2025)

Backlighting extended gas halos around luminous red galaxies: kinematic Sunyaev-Zel'dovich effect from DESI Y1 x ACT

Authors: Bernardita Ried Guachalla, Emmanuel Schaan, Boryana Hadzhiyska, Simone Ferraro, Jessica N. Aguilar, Steven Ahlen, Nicholas Battaglia, Davide Bianchi, Richard Bond, David Brooks, Todd Claybaugh, William R. Coulton, Axel de la Macorra, Mark J. Devlin, Arjun Dey, Peter Doel, Jo Dunkley, Kevin Fanning, Jaime Forero-Romero, Enrique Gaztañaga, Satya Gontcho A Gontcho, Gaston Gutierrez, Julien Guy, J. Colin Hill, Klaus Honscheid , et al. (36 additional authors not shown)

Abstract: The gas density profile around galaxies, shaped by feedback and affecting the galaxy lensing signal, is imprinted on the cosmic microwave background (CMB) by the kinematic Sunyaev-Zel'dovich effect (kSZ). We precisely measure this effect ($S/N\approx 10$) via velocity stacking with more than 800,000 spectroscopically confirmed luminous red galaxies (LRG) from the Dark Energy Spectroscopic Instrume… ▽ More The gas density profile around galaxies, shaped by feedback and affecting the galaxy lensing signal, is imprinted on the cosmic microwave background (CMB) by the kinematic Sunyaev-Zel'dovich effect (kSZ). We precisely measure this effect ($S/N\approx 10$) via velocity stacking with more than 800,000 spectroscopically confirmed luminous red galaxies (LRG) from the Dark Energy Spectroscopic Instrument (DESI) Y1 survey, which overlap with the Atacama Cosmology Telescope (ACT) Data Release 6 temperature maps over $\geq$ 4,000 deg$^2$. We explore the kSZ dependence with various galaxy parameters and find no significant trend with redshift, but clear trends with stellar mass and absolute magnitude in $g$, $r$, and $z$ bands. Our analysis suggests that the gas extends beyond the dark matter halo (99.5\% confidence, i.e. PTE = 0.005). We find a tentative preference for hydrodynamical simulation models with stronger feedback that drives gas further out (Illustris $z=0.5$, PTE = 0.37) over weaker-feedback cases (IllustrisTNG $z=0.8$, PTE = 0.045), though with limited statistical significance. In all cases, a free multiplicative amplitude was fit to the simulated profiles, and further modeling work is required to firm up these conclusions. We find consistency between kSZ profiles around spectroscopic and photometric LRG, with comparable statistical power, thus increasing our confidence in the photometric analysis. Additionally, we present the first kSZ measurement around DESI Y1 bright galaxy sample (BGS) and emission-line galaxies (ELG), whose features match qualitative expectations. Finally, we forecast $S/N \sim 50$ for future stacked kSZ measurements using data from ACT, DESI Y3, and Rubin Observatory. These measurements will serve as an input for galaxy formation models and baryonic uncertainties in galaxy lensing. △ Less

Submitted 10 November, 2025; v1 submitted 25 March, 2025; originally announced March 2025.

Comments: 21 pages + appendices, matching accepted version PRD, updated a missing citation

Journal ref: Phys. Rev. D (vol=112, issue=10, pages=103512, year=2025)

Entropic Analysis of Time Series through Kernel Density Estimation

Authors: Audun Myers, Bill Kay, Iliana Alvarez, Michael Hughes, Cameron Mackenzie, Carlos Ortiz Marrero, Emily Ellwein, Erik Lentz

Abstract: This work presents a novel framework for time series analysis using entropic measures based on the kernel density estimate (KDE) of the time series' Takens' embeddings. Using this framework we introduce two distinct analytical tools: (1) a multi-scale KDE entropy metric, denoted as $Δ\text{KE}$, which quantifies the evolution of time series complexity across different scales by measuring certain e… ▽ More This work presents a novel framework for time series analysis using entropic measures based on the kernel density estimate (KDE) of the time series' Takens' embeddings. Using this framework we introduce two distinct analytical tools: (1) a multi-scale KDE entropy metric, denoted as $Δ\text{KE}$, which quantifies the evolution of time series complexity across different scales by measuring certain entropy changes, and (2) a sliding baseline method that employs the Kullback-Leibler (KL) divergence to detect changes in time series dynamics through changes in KDEs. The $Δ{\rm KE}$ metric offers insights into the information content and ``unfolding'' properties of the time series' embedding related to dynamical systems, while the KL divergence-based approach provides a noise and outlier robust approach for identifying time series change points (injections in RF signals, e.g.). We demonstrate the versatility and effectiveness of these tools through a set of experiments encompassing diverse domains. In the space of radio frequency (RF) signal processing, we achieve accurate detection of signal injections under varying noise and interference conditions. Furthermore, we apply our methodology to electrocardiography (ECG) data, successfully identifying instances of ventricular fibrillation with high accuracy. Finally, we demonstrate the potential of our tools for dynamic state detection by accurately identifying chaotic regimes within an intermittent signal. These results show the broad applicability of our framework for extracting meaningful insights from complex time series data across various scientific disciplines. △ Less

Submitted 4 December, 2025; v1 submitted 24 March, 2025; originally announced March 2025.

Data Release 1 of the Dark Energy Spectroscopic Instrument

Authors: DESI Collaboration, M. Abdul Karim, A. G. Adame, D. Aguado, J. Aguilar, S. Ahlen, S. Alam, G. Aldering, D. M. Alexander, R. Alfarsy, L. Allen, C. Allende Prieto, O. Alves, A. Anand, U. Andrade, E. Armengaud, S. Avila, A. Aviles, H. Awan, S. Bailey, A. Baleato Lizancos, O. Ballester, A. Bault, J. Bautista, R. Bean , et al. (285 additional authors not shown)

Abstract: In 2021 May the Dark Energy Spectroscopic Instrument (DESI) collaboration began a 5-year spectroscopic redshift survey to produce a detailed map of the evolving three-dimensional structure of the universe between $z=0$ and $z\approx4$. DESI's principle scientific objectives are to place precise constraints on the equation of state of dark energy, the gravitationally driven growth of large-scale st… ▽ More In 2021 May the Dark Energy Spectroscopic Instrument (DESI) collaboration began a 5-year spectroscopic redshift survey to produce a detailed map of the evolving three-dimensional structure of the universe between $z=0$ and $z\approx4$. DESI's principle scientific objectives are to place precise constraints on the equation of state of dark energy, the gravitationally driven growth of large-scale structure, and the sum of the neutrino masses, and to explore the observational signatures of primordial inflation. We present DESI Data Release 1 (DR1), which consists of all data acquired during the first 13 months of the DESI main survey, as well as a uniform reprocessing of the DESI Survey Validation data which was previously made public in the DESI Early Data Release. The DR1 main survey includes high-confidence redshifts for 18.7M objects, of which 13.1M are spectroscopically classified as galaxies, 1.6M as quasars, and 4M as stars, making DR1 the largest sample of extragalactic redshifts ever assembled. We summarize the DR1 observations, the spectroscopic data-reduction pipeline and data products, large-scale structure catalogs, value-added catalogs, and describe how to access and interact with the data. In addition to fulfilling its core cosmological objectives with unprecedented precision, we expect DR1 to enable a wide range of transformational astrophysical studies and discoveries. △ Less

Submitted 4 March, 2026; v1 submitted 18 March, 2025; originally announced March 2025.

Comments: 64 pages, 7 figures, 15 tables, accepted to The Astronomical Journal

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… ▽ More 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. △ Less

Submitted 3 April, 2025; v1 submitted 18 March, 2025; originally announced March 2025.

Comments: 27 pages, 18 figures. This DESI Collaboration Publication is part of the Data Release 2 publication series (see https://data.desi.lbl.gov/doc/papers )