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Disentangling the dark and stellar mass through precise lens modelling of the JWST observation of lensed quasar WFI2033--4723
Authors:
Tian Li,
Thomas E. Collett,
Coleman M. Krawczyk,
Wolfgang J. R. Enzi,
Aymeric Galan
Abstract:
We use high-resolution JWST/NIRCam imaging and measured time delays to model the quadruply imaged quasar WFI2033--4723 with a composite stellar plus dark-matter mass model. We first construct an elliptical power-law baseline model and recover Fermat-potential differences (fpd) consistent with previous HST-based and JWST-based analyses, providing a reference scale for composite modelling. We then r…
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We use high-resolution JWST/NIRCam imaging and measured time delays to model the quadruply imaged quasar WFI2033--4723 with a composite stellar plus dark-matter mass model. We first construct an elliptical power-law baseline model and recover Fermat-potential differences (fpd) consistent with previous HST-based and JWST-based analyses, providing a reference scale for composite modelling. We then replace the total mass profile with a physically motivated decomposition in which the stellar mass follows a multi-Gaussian expansion of the lens light, with a free radial mass-to-light gradient, and the dark matter is described by a generalized Navarro--Frenk--White (gNFW) halo. Using two external cosmological priors, Planck+DESI and Pantheon+SH0ES, the measured time delays constrain the mass-sheet-transformation freedom that would otherwise damage the stellar--dark-matter decomposition. In both cosmological cases, the stellar normalization lies between the expectations for Chabrier and Salpeter initial mass functions, while the radial mass-to-light gradient is not strongly required by the data (mildly positive). The dark matter halo has an inner slope $γ_{\rm in}\simeq1.3$, steeper than a standard NFW cusp, and the main astrophysical conclusions are insensitive to the adopted cosmological prior. This work shows that composite time-delay lens modelling can effectively separate baryons from dark matter. As a qualitative check, we reverse the logic and use our composite lens model without kinematic information to infer the cosmology instead. However, the strong degeneracy between $H_0$ and the halo scale radius $R_s$ prevents a robust standalone constraint.
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Submitted 9 July, 2026;
originally announced July 2026.
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JAXtronomy: A JAX port of lenstronomy
Authors:
Alan Huang,
Simon Birrer,
Daniel Gilman,
Natalie B. Hogg,
Anowar J. Shajib,
Aymeric Galan,
Nan Zhang
Abstract:
Gravitational lensing is a phenomenon where light bends around massive objects, resulting in distorted images seen by an observer. Studying gravitationally lensed systems provides insights into cosmology and astrophysics, including constraints of the expansion rate of the Universe and the distribution of dark matter.
Thus, we introduce JAXtronomy, a re-implementation of the gravitational lensing…
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Gravitational lensing is a phenomenon where light bends around massive objects, resulting in distorted images seen by an observer. Studying gravitationally lensed systems provides insights into cosmology and astrophysics, including constraints of the expansion rate of the Universe and the distribution of dark matter.
Thus, we introduce JAXtronomy, a re-implementation of the gravitational lensing software package lenstronomy (Birrer, 2021; Birrer & Amara, 2018) using JAX (Bradbury et al., 2018). JAX is a Python library that uses an accelerated linear algebra (XLA) compiler to improve the performance of computing software. Our core design principle of JAXtronomy is to maintain an identical API to that of lenstronomy.
The main JAX features utilized in JAXtronomy are just-in-time compilation, which can lead to significant reductions in execution time, and automatic differentiation, which allows for the implementation of gradient-based algorithms that were previously impossible. Additionally, JAX allows code to be run on GPUs or parallelized across CPU cores, further boosting the performance of JAXtronomy.
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Submitted 31 May, 2026;
originally announced June 2026.
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Programmable high-harmonic emission in solids through photon pathways
Authors:
Pieter J. van Essen,
Aday Cárdenas,
Rui E. F. Silva,
Álvaro Jiménez Galán,
Peter M. Kraus
Abstract:
Ultrafast all-optical control of light emission is a central goal of extreme nonlinear optics, with implications for compact short-wavelength sources, petahertz optoelectronics, and label-free superresolution microscopy. High-harmonic generation in solids is a particularly attractive platform for this goal because it is highly sensitive to both the driving field and the material response, yet a ge…
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Ultrafast all-optical control of light emission is a central goal of extreme nonlinear optics, with implications for compact short-wavelength sources, petahertz optoelectronics, and label-free superresolution microscopy. High-harmonic generation in solids is a particularly attractive platform for this goal because it is highly sensitive to both the driving field and the material response, yet a generally applicable framework for controlling harmonic emission has remained elusive. Here, we demonstrate programmable control of high-harmonic emission in solids and show that it can be quantitatively described within a photon-pathway framework. We find that harmonic emission can be suppressed or enhanced by tuning two experimentally accessible quantities: the effective nonlinear order and the intrinsic emission phase. Across a wide range of semiconductors and dielectrics, this approach unifies parametric and non-parametric modulation, explains distinct delay-dependent spectral responses, and reproduces strong suppression, enhancement, and higher-order pathway revivals. Semiconductor Bloch equation simulations support the model and provide a complementary time-domain picture in which the control field reshapes the interference of sub-cycle emission events. These results establish high-harmonic generation in solids as a programmable emission process and provide a general route towards ultrafast optical switching, compact coherent short-wavelength sources, and label-free attosecond super-resolution microscopy.
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Submitted 22 May, 2026;
originally announced May 2026.
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Euclid Quick Data Release (Q1). AgileLens: A scalable CNN-based pipeline for strong gravitational lens identification
Authors:
Euclid Collaboration,
X. Xu,
R. Chen,
T. Li,
A. R. Cooray,
S. Schuldt,
J. A. Acevedo Barroso,
D. Stern,
D. Scott,
M. Meneghetti,
G. Despali,
J. Chopra,
Y. Cao,
M. Cheng,
J. Buda,
J. Zhang,
J. Furumizo,
R. Valencia,
Z. Jiang,
C. Tortora,
N. E. P. Lines,
T. E. Collett,
S. Fotopoulou,
A. Galan,
A. Manjón-García
, et al. (286 additional authors not shown)
Abstract:
We present an end-to-end, iterative pipeline for efficient identification of strong galaxy--galaxy lensing systems, applied to the Euclid Q1 imaging data. Starting from VIS catalogues, we reject point sources, apply a magnitude cut (I$_E$ $\leq$ 24) on deflectors, and run a pixel-level artefact/noise filter to build 96 $\times$ 96 pix cutouts; VIS+NISP colour composites are constructed with a VIS-…
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We present an end-to-end, iterative pipeline for efficient identification of strong galaxy--galaxy lensing systems, applied to the Euclid Q1 imaging data. Starting from VIS catalogues, we reject point sources, apply a magnitude cut (I$_E$ $\leq$ 24) on deflectors, and run a pixel-level artefact/noise filter to build 96 $\times$ 96 pix cutouts; VIS+NISP colour composites are constructed with a VIS-anchored luminance scheme that preserves VIS morphology and NISP colour contrast. A VIS-only seed classifier supplies clear positives and typical impostors, from which we curate a morphology-balanced negative set and augment scarce positives. Among the six CNNs studied initially, a modified VGG16 (GlobalAveragePooling + 256/128 dense layers with the last nine layers trainable) performs best; the training set grows from 27 seed lenses (augmented to 1809) plus 2000 negatives to a colour dataset of 30,686 images. After three rounds of iterative fine-tuning, human grading of the top 4000 candidates ranked by the final model yields 441 Grade A/B candidate lensing systems, including 311 overlapping with the existing Q1 strong-lens catalogue, and 130 additional A/B candidates (9 As and 121 Bs) not previously reported. Independently, the model recovers 740 out of 905 (81.8%) candidate Q1 lenses within its top 20,000 predictions, considering off-centred samples. Candidates span I$_E$ $\simeq$ 17--24 AB mag (median 21.3 AB mag) and are redder in Y$_E$--H$_E$ than the parent population, consistent with massive early-type deflectors. Each training iteration required a week for a small team, and the approach easily scales to future Euclid releases; future work will calibrate the selection function via lens injection, extend recall through uncertainty-aware active learning, explore multi-scale or attention-based neural networks with fast post-hoc vetters that incorporate lens models into the classification.
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Submitted 7 April, 2026;
originally announced April 2026.
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Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine F -- Bright and low-redshift strong lenses
Authors:
Euclid Collaboration,
L. R. Ecker,
M. Fabricius,
S. Seitz,
R. Saglia,
N. E. P. Lines,
P. Holloway,
T. Li,
A. Verma,
F. Balzer,
Q. Jin,
A. Manjón-García,
S. H. Vincken,
J. Wilde,
J. A. Acevedo Barroso,
J. W. Nightingale,
K. Rojas,
S. Schuldt,
M. Walmsley,
T. E. Collett,
G. Despali,
A. Sonnenfeld,
C. Tortora,
R. B. Metcalf,
R. Bender
, et al. (324 additional authors not shown)
Abstract:
We present 72 additional galaxy-galaxy strong lenses that complement the sample discovered in the Euclid Quick Release 1 data (63.1 deg^2) of the Strong Lens Discovery Engine (SLDE) papers A-E. It is shown that previous pre-selection of potential lenses, which excluded objects from the Gaia catalogue, led to missing several bright and low-redshift strong lenses, adding more than 10% new strong len…
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We present 72 additional galaxy-galaxy strong lenses that complement the sample discovered in the Euclid Quick Release 1 data (63.1 deg^2) of the Strong Lens Discovery Engine (SLDE) papers A-E. It is shown that previous pre-selection of potential lenses, which excluded objects from the Gaia catalogue, led to missing several bright and low-redshift strong lenses, adding more than 10% new strong lens candidates compared to the previous search. In total, the catalogue includes 38 "grade A" (confident) and 34 "grade B" (probable) candidates. These lenses are identified through a combination of two independent searches for bright nearby objects: one based on machine-learning models followed by expert visual inspection, and the other based solely on expert visual inspection, targeting objects not included in the initial machine-learning selection (a limitation identified only after extensive visual inspection). With these additional strong lens candidates, we augment the expected number of high-confidence candidates in the Euclid Wide Survey from previous forecasts to 120000. Detailed semi-automated lens modelling confirms at least 41 systems out of 72, a fraction consistent with that found in SLDE A (315 out of 488). These include: multiple edge-on disc lenses; sources with arcs near the lens centre; "red sources"; and an edge-on disk galaxy lensing a galaxy merger, producing two sets of lensed features, an Einstein ring and a doubly imaged component. The median redshift of these systems is $Δ$ z ~ 0.3 lower than that of the SLDE A sample.
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Submitted 30 March, 2026;
originally announced March 2026.
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The Stellar IMF and Dark Matter Halo of ESO0286: Constraints from Strong Lensing and Dynamics
Authors:
Han Wang,
Jens Thomas,
Mathias Lipka,
Sherry H. Suyu,
Aymeric Galan,
Stefano de Nicola,
Tian Li
Abstract:
The internal mass structure of elliptical galaxies offers critical insights into galaxy formation, yet disentangling stellar mass from dark matter and determining the stellar initial mass function (IMF) remains challenging. We present a detailed analysis of ESO0286-G022 ($z=0.0312$), a rare nearby strong-lens system with a fast-rotating elliptical galaxy, combining high-resolution Hubble Space Tel…
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The internal mass structure of elliptical galaxies offers critical insights into galaxy formation, yet disentangling stellar mass from dark matter and determining the stellar initial mass function (IMF) remains challenging. We present a detailed analysis of ESO0286-G022 ($z=0.0312$), a rare nearby strong-lens system with a fast-rotating elliptical galaxy, combining high-resolution Hubble Space Telescope (HST) imaging with VLT/MUSE integral-field stellar kinematics. We construct axisymmetric and triaxial Schwarzschild orbit-superposition models to reconstruct its intrinsic shape and mass distribution. Despite being a fast rotator, ESO0286 exhibits clear kinematic signatures of intrinsic triaxiality, characterized by rotation along both the major and minor axes, making it only the second such confirmed case. By incorporating the mass enclosed within the Einstein radius from strong lensing as a complementary constraint, we tightly anchor the total mass at large radii. This significantly reduces the uncertainty on the outer mass profile and orbital structure, demonstrating that only models with strong radial anisotropy beyond the IFU field of view are compatible with the data. In the inner regions, we robustly constrain an upper limit for the stellar mass around $r \sim 0.7$ kpc, ruling out an IMF more bottom-heavy than Kroupa, though a gentle gradient toward a slightly heavier central IMF is permitted. This aligns with recent dynamical studies of local massive early-type galaxies but contrasts with heavier IMFs reported for lenses at $z>0.1$. Our work demonstrates the power of combining lensing and dynamical modeling to resolve the detailed inner structure of massive galaxies.
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Submitted 27 March, 2026;
originally announced March 2026.
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HOLISMOKES XX. Lens models of binary lens galaxies with five images of Supernova Winny
Authors:
L. R. Ecker,
A. G. Schweinfurth,
R. Saglia,
L. Deng,
S. H. Suyu,
C. Saulder,
J. Snigula,
R. Bender,
R. Cañameras,
T. -W. Chen,
A. Galan,
A. Halkola,
E. Mamuzic,
A. Melo,
S. Schuldt,
S. Taubenberger
Abstract:
Strongly lensed supernovae (SNe) provide a powerful way to study cosmology, SNe and galaxies. Modelling the lens system is key to extracting astrophysical and cosmological information. We present adaptive-optics-assisted high-resolution images of SN Winny (SN 2025wny) in the J and K filters obtained with the Large Binocular Telescope (LBT). The LBT imaging confirms the presence of a fifth point so…
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Strongly lensed supernovae (SNe) provide a powerful way to study cosmology, SNe and galaxies. Modelling the lens system is key to extracting astrophysical and cosmological information. We present adaptive-optics-assisted high-resolution images of SN Winny (SN 2025wny) in the J and K filters obtained with the Large Binocular Telescope (LBT). The LBT imaging confirms the presence of a fifth point source, whose colour is consistent with that of the other SN images at similar phases, while lens modelling robustly supports its interpretation as an additional image of SN~Winny. We measure the positions of the five SN images with uncertainties varying between 1 and 14 milliarcseconds. We build the first mass models using lenstronomy and GLEE, and explore three classes of mass models for the two lens galaxies G1 and G2. The optimal model class of the three is a singular isothermal ellipsoid for G1, a singular isothermal sphere for G2, and an external shear. We infer the enclosed masses within the Einstein radius as 4.61^{+0.06}_{-0.04} \times 10^{11}\,M_\odot for G1 and 1.01\pm0.02 \times 10^{11}\,M_\odot for G2. The lensing configuration by the two lens galaxies can produce two additional magnified SN images beyond the five observed ones; the exclusion of such model configurations further constrains the lens model parameters. Our model fits to the observed image positions with an RMS of ~0.0012" - 0.0025", within the observed positional uncertainties. The predicted magnifications of the multiple images vary between ~1.6 (for the faintest fifth image E) to ~10 (for the brightest image A). The predicted relative lensing magnifications of the multiple images do not match that of the observed within 2σuncertainties. The differences in the relative magnifications could be due to millilensing/microlensing. Our mass models form the basis for future analyses of this unique system. (abridged)
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Submitted 18 February, 2026;
originally announced February 2026.
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Algorithms for the local and the global postage stamp problem
Authors:
Léo Colisson Palais,
Jean-Guillaume Dumas,
Alexis Galan,
Bruno Grenet,
Aude Maignan
Abstract:
We consider stamps with different values (denominations) and same dimensions, and an envelope with a fixed maximum number of stamp positions. The local postage stamp problem is to find the smallest value that cannot be realized by the sum of the stamps on the envelope. The global postage stamp problem is to find the set of denominations that maximize that smallest value for a fixed number of disti…
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We consider stamps with different values (denominations) and same dimensions, and an envelope with a fixed maximum number of stamp positions. The local postage stamp problem is to find the smallest value that cannot be realized by the sum of the stamps on the envelope. The global postage stamp problem is to find the set of denominations that maximize that smallest value for a fixed number of distinct denominations. The local problem is NP-hard and we propose here a novel algorithm that improves on both the time complexity bound and the amount of required memory. We also propose a polynomial approximation algorithm for the global problem together with its complexity analysis. Finally we show that our algorithms allow to improve secure multi-party computations on sets via a more efficient homomorphic evaluation of polynomials on ciphered values.
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Submitted 29 January, 2026;
originally announced January 2026.
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TDCOSMO. XXIII. Measurement of the Hubble constant from the doubly lensed quasar HE1104-1805
Authors:
Eric Paic,
Frédéric Courbin,
Christopher D. Fassnacht,
Aymeric Galan,
Martin Millon,
Dominique Sluse,
Devon M. Williams,
Simon Birrer,
Elizabeth J. Buckley-Geer,
Michele Cappellari,
Frédéric Dux,
Xiang-Yu Huang,
Shawn Knabel,
Cameron Lemon,
Anowar J. Shajib,
Sherry H. Suyu,
Tommaso Treu,
Kenneth C. Wong,
Lise Christensen,
Veronica Motta,
Alessandro Sonnenfeld
Abstract:
Time-delay cosmography leverages strongly lensed quasars to measure the Universe's current expansion rate, H_0, independently from other methods. While the latest TDCOSMO results relied mainly on quadruply lensed quasars, doubly lensed systems are far more common and offer precise time delays, potentially enlarging the usable sample by a factor of five and enabling percent-level constraints on H_0…
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Time-delay cosmography leverages strongly lensed quasars to measure the Universe's current expansion rate, H_0, independently from other methods. While the latest TDCOSMO results relied mainly on quadruply lensed quasars, doubly lensed systems are far more common and offer precise time delays, potentially enlarging the usable sample by a factor of five and enabling percent-level constraints on H_0. We present the first TDCOSMO analysis of a doubly imaged source, HE1104-1805, including the measurement of the four necessary ingredients. First, by combining 17 years of data from the SMARTS, Euler and WFI telescopes, we measure a time delay of 176.3\pm 10.8 days. Second, using MUSE data, we extract stellar velocity dispersion measurements in three radial bins with up to 5% precision. Third, employing F160W HST imaging for lens modelling and marginalising over various modelling choices, we measure the Fermat potential difference between the images. Fourth, using wide-field imaging, we measure the convergence added by objects not included in the lens modelling. Hence, we measure the time delay distance and the angular diameter distance to the deflector, favouring a power-law mass model over a baryonic and dark matter composite model. The measurement was performed blindly and yielded H_0 = 64.2^{+5.8}_{-5.0} x $λ_{int} km s^{-1} Mpc^{-1}, where λ_{int} is the internal mass sheet degeneracy parameter. This is in agreement with the TDCOSMO-2025 milestone and its precision for λ_{int}=1 is comparable to that obtained with the best-observed quadruply lensed quasars (4-6%). This work is a stepping stone towards a precise measurement of H_0 using a large sample of doubly lensed quasars, supplementing the current sample. The next TDCOSMO milestone paper will include this system in its hierarchical analysis, constraining λ_{int} and H_0 jointly with multiple lenses.
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Submitted 23 March, 2026; v1 submitted 2 December, 2025;
originally announced December 2025.
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HOLISMOKES XIX: SN 2025wny at $z=2$, the first strongly lensed superluminous supernova
Authors:
Stefan Taubenberger,
Ana Acebron,
Raoul Cañameras,
Ting-Wan Chen,
Aymeric Galan,
Claudio Grillo,
Alejandra Melo,
Stefan Schuldt,
Allan G. Schweinfurth,
Sherry H. Suyu,
Greg Aldering,
Amar Aryan,
Yu-Hsing Lee,
Elias Mamuzic,
Martin Millon,
Thomas M. Reynolds,
Alexey V. Sergeyev,
Ildar M. Asfandiyarov,
Stéphane Basa,
Stéphane Blondin,
Otabek A. Burkhonov,
Lise Christensen,
Frederic Courbin,
Shuhrat A. Ehgamberdiev,
Tom L. Killestein
, et al. (23 additional authors not shown)
Abstract:
We present imaging and spectroscopic observations of supernova SN 2025wny, associated with the lens candidate PS1 J0716+3821. Photometric monitoring from the Lulin and Maidanak observatories confirms multiple point-like images, consistent with SN 2025wny being strongly lensed by two foreground galaxies. Optical spectroscopy of the brightest image with the Nordic Optical Telescope and the Universit…
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We present imaging and spectroscopic observations of supernova SN 2025wny, associated with the lens candidate PS1 J0716+3821. Photometric monitoring from the Lulin and Maidanak observatories confirms multiple point-like images, consistent with SN 2025wny being strongly lensed by two foreground galaxies. Optical spectroscopy of the brightest image with the Nordic Optical Telescope and the University of Hawaii 88-inch Telescope allows us to determine the redshift to be z_s = 2.008 +- 0.001, based on narrow absorption lines originating in the interstellar medium of the supernova host galaxy. At this redshift, the spectra of SN 2025wny are consistent with those of superluminous supernovae of Type I. We find a high ejecta temperature and depressed spectral lines compared to other similar objects. We also measure, for the first time, the redshift of the fainter of the two lens galaxies (the "perturber") to be z_p = 0.375 +- 0.001, fully consistent with the DESI spectroscopic redshift of the main deflector at z_d = 0.3754. SN 2025wny thus represents the first confirmed galaxy-scale strongly lensed supernova with time delays likely in the range of days to weeks, as judged from the image separations. This makes SN 2025wny suitable for cosmography, offering a promising new system for independent measurements of the Hubble constant. Following a tradition in the field of strongly-lensed SNe, we give SN 2025wny the nickname SN Winny.
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Submitted 24 October, 2025;
originally announced October 2025.
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Strong Lensing Model and Dust Extinction Maps of the Host Galaxy of Type Ia Supernova H0pe
Authors:
A. Galan,
S. Schuldt,
G. B. Caminha,
S. H. Suyu,
R. Cañameras,
S. Ertl,
C. Grillo,
A. Acebron,
B. Frye,
A. M. Koekemoer,
M. Pascale,
R. Windhorst,
J. M. Diego,
N. Foo
Abstract:
Strong gravitational lensing by massive galaxy clusters offers rare opportunities to observe multiple images of distant ($z \gtrsim 2$) Type Ia supernovae (SNe) and to resolve the properties of their host galaxies. A recent outstanding example is the Type Ia SN H0pe ($z = 1.78$), which the James Webb Space Telescope (JWST) discovered in NIRCam images, when the galaxy cluster PLCK G165.7+67.0 (G165…
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Strong gravitational lensing by massive galaxy clusters offers rare opportunities to observe multiple images of distant ($z \gtrsim 2$) Type Ia supernovae (SNe) and to resolve the properties of their host galaxies. A recent outstanding example is the Type Ia SN H0pe ($z = 1.78$), which the James Webb Space Telescope (JWST) discovered in NIRCam images, when the galaxy cluster PLCK G165.7+67.0 (G165, $z = 0.35$) still produced three images of it. In this work, we build a new strong lensing model of G165, first using only the positions of multiple images of background galaxies. We then significantly increase the number of constraints around the position of SN H0pe by modeling the extended surface brightness of the SN host galaxy. Including extended image information reduces the average uncertainty on mass model parameters by more than an order of magnitude. We also study the spatial distribution of dust in the arc to estimate the dust extinction at the position of SN H0pe. We find good statistical agreement of the extinction estimate, at $\lesssim 1σ$, with three fully independent methods based on spectral energy distribution fitting. Moreover, our extended-image lens model of G165 allows us to map the dust distribution of the host galaxy from the image plane to the source plane. Supernova H0pe exploded in a region with a relatively high extinction ($A_V \approx 0.9$ mag) at around $\sim 1$ kpc from its host center. This work shows that extended image modeling in lensing clusters simultaneously reduces the uncertainty on lens model parameters and enables spatially resolved analyses of lensed transients' host galaxies. Such modeling advances are expected to play an important role in future cosmological analyses using strongly lensed SNe.
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Submitted 29 April, 2026; v1 submitted 23 October, 2025;
originally announced October 2025.
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Attosecond high-harmonic interferometry probes orbital- and band-dependent dipole phase in magnesium oxide
Authors:
Nataliia Kuzkova,
Pieter J. van Essen,
Brian de Keijzer,
Rui E. F. Silva,
Alvaro Jimenez Galan,
Peter M. Kraus
Abstract:
Control over the spatial coherence, wavefront, and focusability of emitted light relies on understanding the intrinsic phase of the emission process, and vice versa, measuring phase can reveal insights about microscopic generation mechanisms. A thorough understanding of the origin of the dipole phase in solid-state high-harmonic generation is currently missing. Here, by employing attosecond interf…
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Control over the spatial coherence, wavefront, and focusability of emitted light relies on understanding the intrinsic phase of the emission process, and vice versa, measuring phase can reveal insights about microscopic generation mechanisms. A thorough understanding of the origin of the dipole phase in solid-state high-harmonic generation is currently missing. Here, by employing attosecond interferometry with phase-locked XUV pulses, we directly assess the intensity- and frequency-dependent dipole phases in magnesium oxide (MgO) in solid-state HHG. We also quantify a nonlinear phase shift of the fundamental and disentangle its contribution from the dipole phase. Theoretical models (analytical, two-band, and full-band numerical simulations) support our results. The analytical approach aids future solid-state HHG experiments and simulations, while the full numerical model details orbital- and band-resolved current contributions to the dipole phase. Our research delivers the first combined quantitative measurement and rigorous theoretical description of the harmonic emission phase in solids.
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Submitted 20 August, 2025;
originally announced August 2025.
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TDCOSMO XXIV. First spatially resolved kinematics of the lens galaxy obtained using JWST-NIRSpec to improve time-delay cosmography
Authors:
Anowar J. Shajib,
Tommaso Treu,
Sherry H. Suyu,
David Law,
Akın Yıldırım,
Michele Cappellari,
Aymeric Galan,
Shawn Knabel,
Han Wang,
Simon Birrer,
Frédéric Courbin,
Christopher D. Fassnacht,
Joshua A. Frieman,
Alejandra Melo,
Takahiro Morishita,
Pritom Mozumdar,
Dominique Sluse,
Massimo Stiavelli
Abstract:
Spatially resolved stellar kinematics has become a key ingredient in time-delay cosmography to break the mass-sheet degeneracy in the mass profile and in turn provide a precise constraint on the Hubble constant and other cosmological parameters. In this paper, we present the first measurements of 2D resolved stellar kinematics for the lens galaxy in the quadruply lensed quasar system RXJ1131$-$123…
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Spatially resolved stellar kinematics has become a key ingredient in time-delay cosmography to break the mass-sheet degeneracy in the mass profile and in turn provide a precise constraint on the Hubble constant and other cosmological parameters. In this paper, we present the first measurements of 2D resolved stellar kinematics for the lens galaxy in the quadruply lensed quasar system RXJ1131$-$1231 using integral field spectroscopy from JWST's Near-Infrared Spectrograph (NIRSpec), marking the first such measurement conducted with JWST. In extracting robust kinematic measurements from this first-of-its-kind dataset, we have made methodological improvements both in the data reduction and kinematic extraction. In our kinematic extraction procedure, we performed joint modeling of the lens galaxy, the quasar, and its host galaxy's contributions in the spectra to deblend the lens galaxy component and robustly constrain its stellar kinematics. Our improved methodological frameworks are released as software pipelines for future use: squirrel, for extracting stellar kinematics, and RegalJumper, for JWST-NIRSpec data reduction. We incorporated additional artifact cleaning beyond the standard JWST pipeline. We compared our measured stellar kinematics from the JWST NIRSpec with previously obtained ground-based measurements from the Keck Cosmic Web Imager integral field unit and find that the two datasets are statistically consistent at a $\sim$1.1$σ$ confidence level. Our measured kinematics will be used in a future study to improve the precision of the Hubble constant measurement.
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Submitted 26 February, 2026; v1 submitted 26 June, 2025;
originally announced June 2025.
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TDCOSMO 2025: Cosmological constraints from strong lensing time delays
Authors:
TDCOSMO Collaboration,
Simon Birrer,
Elizabeth J. Buckley-Geer,
Michele Cappellari,
Frédéric Courbin,
Frédéric Dux,
Christopher D. Fassnacht,
Joshua A. Frieman,
Aymeric Galan,
Daniel Gilman,
Xiang-Yu Huang,
Shawn Knabel,
Danial Langeroodi,
Huan Lin,
Martin Millon,
Takahiro Morishita,
Veronica Motta,
Pritom Mozumdar,
Eric Paic,
Anowar J. Shajib,
William Sheu,
Dominique Sluse,
Alessandro Sonnenfeld,
Chiara Spiniello,
Massimo Stiavelli
, et al. (8 additional authors not shown)
Abstract:
We present cosmological constraints from 8 strongly lensed quasars (hereafter, the TDCOSMO-2025 sample). Building on previous work, our analysis incorporated new deflector stellar velocity dispersions measured from spectra obtained with the James Webb Space Telescope (JWST), the Keck Telescopes, and the Very Large Telescope (VLT), utilizing improved methods. We used integrated JWST stellar kinemat…
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We present cosmological constraints from 8 strongly lensed quasars (hereafter, the TDCOSMO-2025 sample). Building on previous work, our analysis incorporated new deflector stellar velocity dispersions measured from spectra obtained with the James Webb Space Telescope (JWST), the Keck Telescopes, and the Very Large Telescope (VLT), utilizing improved methods. We used integrated JWST stellar kinematics for 5 lenses, VLT-MUSE for 2, and resolved kinematics from Keck and JWST for RXJ1131-1231. We also considered two samples of non-time-delay lenses: 11 from the Sloan Lens ACS (SLACS) sample with Keck-KCWI resolved kinematics; and 4 from the Strong Lenses in the Legacy Survey (SL2S) sample. We improved our analysis of line-of-sight effects, the surface brightness profile of the lens galaxies, and orbital anisotropy, and corrected for projection effects in the dynamics. Our uncertainties are maximally conservative by accounting for the mass-sheet degeneracy in the deflectors' mass density profiles. The analysis was blinded to prevent experimenter bias. Our primary result is based on the TDCOSMO-2025 sample, in combination with $Ω_{\rm m}$ constraints from the Pantheon+ Type Ia supernovae (SN) dataset. In the flat $Λ$ cold dark matter (CDM), we find $H_0=71.6^{+3.9}_{-3.3}$ km s$^{-1}$ Mpc$^{-1}$. The SLACS and SL2S samples are in excellent agreement with the TDCOSMO-2025 sample, improving the precision on $H_0$ in flat $Λ$CDM to 4.6%. Using the Dark Energy Survey SN Year-5 dataset (DES-SN5YR) or DESI-DR2 baryonic acoustic oscillations (BAO) likelihoods instead of Pantheon+ yields very similar results. We also present constraints in the open $Λ$CDM, $w$CDM, $w_0w_a$CDM, and $w_φ$CDM cosmologies. The TDCOSMO $H_0$ inference is robust and consistent across all presented cosmological models, and our cosmological constraints in them agree with those from the BAO and SN.
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Submitted 20 December, 2025; v1 submitted 3 June, 2025;
originally announced June 2025.
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TDCOSMO XVII. New time delays in 22 lensed quasars from optical monitoring with the ESO-VST 2.6m and MPG 2.2m telescopes
Authors:
Frédéric Dux,
Martin Millon,
Aymeric Galan,
Eric Paic,
Cameron Lemon,
Frédéric Courbin,
Vivien Bonvin,
Timo Anguita,
Matt Auger,
Simon Birrer,
Elisabeth Buckley-Geer,
Chris Fassnacht,
Joshua Frieman,
Richard G. McMahon,
Philip J. Marshall,
Alejandra Melo,
Verónica Motta,
Favio Neira,
Dominique Sluse,
Sherry H. Suyu,
Tommaso Treu,
Adriano Agnello,
Felipe Ávila,
James Chan,
M. A. Chijani
, et al. (7 additional authors not shown)
Abstract:
We present new time delays, the main ingredient of time delay cosmography, for 22 lensed quasars resulting from high-cadence r-band monitoring on the 2.6 m ESO VLT Survey Telescope and Max-Planck-Gesellschaft 2.2 m telescope. Each lensed quasar was typically monitored for one to four seasons, often shared between the two telescopes to mitigate the interruptions forced by the COVID-19 pandemic. The…
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We present new time delays, the main ingredient of time delay cosmography, for 22 lensed quasars resulting from high-cadence r-band monitoring on the 2.6 m ESO VLT Survey Telescope and Max-Planck-Gesellschaft 2.2 m telescope. Each lensed quasar was typically monitored for one to four seasons, often shared between the two telescopes to mitigate the interruptions forced by the COVID-19 pandemic. The sample of targets consists of 19 quadruply and 3 doubly imaged quasars, which received a total of 1 918 hours of on-sky time split into 21 581 wide-field frames, each 320 seconds long. In a given field, the 5-σ depth of the combined exposures typically reaches the 27th magnitude, while that of single visits is 24.5 mag - similar to the expected depth of the upcoming Vera-Rubin LSST. The fluxes of the different lensed images of the targets were reliably de-blended, providing not only light curves with photometric precision down to the photon noise limit, but also high-resolution models of the targets whose features and astrometry were systematically confirmed in Hubble Space Telescope imaging. This was made possible thanks to a new photometric pipeline, lightcurver, and the forward modelling method STARRED. Finally, the time delays between pairs of curves and their uncertainties were estimated, taking into account the degeneracy due to microlensing, and for the first time the full covariance matrices of the delay pairs are provided. Of note, this survey, with 13 square degrees, has applications beyond that of time delays, such as the study of the structure function of the multiple high-redshift quasars present in the footprint at a new high in terms of both depth and frequency. The reduced images will be available through the European Southern Observatory Science Portal.
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Submitted 3 April, 2025;
originally announced April 2025.
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GPU-Accelerated Gravitational Lensing & Dynamical (GLaD) Modeling for Cosmology and Galaxies
Authors:
Han Wang,
Sherry H. Suyu,
Aymeric Galan,
Aleksi Halkola,
Michele Cappellari,
Anowar J. Shajib,
Miha Cernetic
Abstract:
Time-delay distance measurements from strongly lensed quasars provide a robust, independent method for determining the Hubble constant ($H_0$). This approach cross-checks $H_0$ estimates from the distance ladder in the late universe and the cosmic microwave background in the early universe. However, the mass-sheet degeneracy in lensing models introduces systematic uncertainty, limiting precision.…
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Time-delay distance measurements from strongly lensed quasars provide a robust, independent method for determining the Hubble constant ($H_0$). This approach cross-checks $H_0$ estimates from the distance ladder in the late universe and the cosmic microwave background in the early universe. However, the mass-sheet degeneracy in lensing models introduces systematic uncertainty, limiting precision. Dynamical modeling complements strong lensing by constraining the mass distribution with independent observational data. We develop a methodology and software framework for joint modeling of stellar kinematics and lensing data. Using simulated data for the lensed quasar RXJ1131$-$1131, we demonstrate that high-quality kinematic data can achieve $\sim$4% precision on $H_0$. Through extensive modeling, we examine the impact of the presence of a supermassive black hole in the lens galaxy and potential systematic biases in kinematic data on $H_0$ measurements. Our results show that imposing priors on black hole mass and orbital anisotropy, or excluding central kinematic bins, mitigates biases in $H_0$ estimates. By testing on mock kinematic data with systematic biases, we highlight the need for sub-percent control of kinematic systematics, which is achievable with current technology. Additionally, we leverage GPU parallelization to accelerate Bayesian inference, reducing a previously month-long process by an order of magnitude. This pipeline offers significant potential for advancing cosmological and galaxy evolution studies with large datasets.
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Submitted 17 July, 2025; v1 submitted 1 April, 2025;
originally announced April 2025.
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Euclid Quick Data Release (Q1). The first catalogue of strong-lensing galaxy clusters
Authors:
Euclid Collaboration,
P. Bergamini,
M. Meneghetti,
A. Acebron,
B. Clément,
M. Bolzonella,
C. Grillo,
P. Rosati,
D. Abriola,
J. A. Acevedo Barroso,
G. Angora,
L. Bazzanini,
R. Cabanac,
B. C. Nagam,
A. R. Cooray,
G. Despali,
G. Di Rosa,
J. M. Diego,
M. Fogliardi,
A. Galan,
R. Gavazzi,
G. Granata,
N. B. Hogg,
K. Jahnke,
L. Leuzzi
, et al. (353 additional authors not shown)
Abstract:
We present the first catalogue of strong lensing galaxy clusters identified in the Euclid Quick Release 1 observations (covering $63.1\,\mathrm{deg^2}$). This catalogue is the result of the visual inspection of 1260 cluster fields. Each galaxy cluster was ranked with a probability, $\mathcal{P}_{\mathrm{lens}}$, based on the number and plausibility of the identified strong lensing features. Specif…
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We present the first catalogue of strong lensing galaxy clusters identified in the Euclid Quick Release 1 observations (covering $63.1\,\mathrm{deg^2}$). This catalogue is the result of the visual inspection of 1260 cluster fields. Each galaxy cluster was ranked with a probability, $\mathcal{P}_{\mathrm{lens}}$, based on the number and plausibility of the identified strong lensing features. Specifically, we identified 83 gravitational lenses with $\mathcal{P}_{\mathrm{lens}}>0.5$, of which 14 have $\mathcal{P}_{\mathrm{lens}}=1$, and clearly exhibiting secure strong lensing features, such as giant tangential and radial arcs, and multiple images. Considering the measured number density of lensing galaxy clusters, approximately $0.3\,\mathrm{deg}^{-2}$ for $\mathcal{P}_{\mathrm{lens}}>0.9$, we predict that \Euclid\ will likely see more than 4500 strong lensing clusters over the course of the mission. Notably, only three of the identified cluster-scale lenses had been previously observed from space. Thus, \Euclid has provided the first high-resolution imaging for the remaining $80$ galaxy cluster lenses, including those with the highest probability. The identified strong lensing features will be used for training deep-learning models for identifying gravitational arcs and multiple images automatically in \Euclid observations. This study confirms the huge potential of \Euclid for finding new strong lensing clusters, enabling exciting new discoveries on the nature of dark matter and dark energy and the study of the high-redshift Universe.
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Submitted 19 March, 2025;
originally announced March 2025.
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Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine E -- Ensemble classification of strong gravitational lenses: lessons for Data Release 1
Authors:
Euclid Collaboration,
P. Holloway,
A. Verma,
M. Walmsley,
P. J. Marshall,
A. More,
T. E. Collett,
N. E. P. Lines,
L. Leuzzi,
A. Manjón-García,
S. H. Vincken,
J. Wilde,
R. Pearce-Casey,
I. T. Andika,
J. A. Acevedo Barroso,
T. Li,
A. Melo,
R. B. Metcalf,
K. Rojas,
B. Clément,
H. Degaudenzi,
F. Courbin,
G. Despali,
R. Gavazzi,
S. Schuldt
, et al. (321 additional authors not shown)
Abstract:
The Euclid Wide Survey (EWS) is expected to identify of order $100\,000$ galaxy-galaxy strong lenses across $14\,000$deg$^2$. The Euclid Quick Data Release (Q1) of $63.1$deg$^2$ Euclid images provides an excellent opportunity to test our lens-finding ability, and to verify the anticipated lens frequency in the EWS. Following the Q1 data release, eight machine learning networks from five teams were…
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The Euclid Wide Survey (EWS) is expected to identify of order $100\,000$ galaxy-galaxy strong lenses across $14\,000$deg$^2$. The Euclid Quick Data Release (Q1) of $63.1$deg$^2$ Euclid images provides an excellent opportunity to test our lens-finding ability, and to verify the anticipated lens frequency in the EWS. Following the Q1 data release, eight machine learning networks from five teams were applied to approximately one million images. This was followed by a citizen science inspection of a subset of around $100\,000$ images, of which $65\%$ received high network scores, with the remainder randomly selected. The top scoring outputs were inspected by experts to establish confident (grade A), likely (grade B), possible (grade C), and unlikely lenses. In this paper we combine the citizen science and machine learning classifiers into an ensemble, demonstrating that a combined approach can produce a purer and more complete sample than the original individual classifiers. Using the expert-graded subset as ground truth, we find that this ensemble can provide a purity of $52\pm2\%$ (grade A/B lenses) with $50\%$ completeness (for context, due to the rarity of lenses a random classifier would have a purity of $0.05\%$). We discuss future lessons for the first major Euclid data release (DR1), where the big-data challenges will become more significant and will require analysing more than $\sim300$ million galaxies, and thus time investment of both experts and citizens must be carefully managed.
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Submitted 19 March, 2025;
originally announced March 2025.
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Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine C: Finding lenses with machine learning
Authors:
Euclid Collaboration,
N. E. P. Lines,
T. E. Collett,
M. Walmsley,
K. Rojas,
T. Li,
L. Leuzzi,
A. Manjón-García,
S. H. Vincken,
J. Wilde,
P. Holloway,
A. Verma,
R. B. Metcalf,
I. T. Andika,
A. Melo,
M. Melchior,
H. Domínguez Sánchez,
A. Díaz-Sánchez,
J. A. Acevedo Barroso,
B. Clément,
C. Krawczyk,
R. Pearce-Casey,
S. Serjeant,
F. Courbin,
G. Despali
, et al. (328 additional authors not shown)
Abstract:
Strong gravitational lensing has the potential to provide a powerful probe of astrophysics and cosmology, but fewer than 1000 strong lenses have been confirmed so far. With a 0.16'' resolution covering a third of the sky, the Euclid telescope will revolutionise the identification of strong lenses, with 170 000 lenses forecasted to be discovered amongst the 1.5 billion galaxies it will observe. We…
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Strong gravitational lensing has the potential to provide a powerful probe of astrophysics and cosmology, but fewer than 1000 strong lenses have been confirmed so far. With a 0.16'' resolution covering a third of the sky, the Euclid telescope will revolutionise the identification of strong lenses, with 170 000 lenses forecasted to be discovered amongst the 1.5 billion galaxies it will observe. We present an analysis of the performance of five machine-learning models at finding strong gravitational lenses in the quick release of Euclid data (Q1) covering 63 deg2. The models have been validated by citizen scientists and expert visual inspection. We focus on the best-performing network: a fine-tuned version of the Zoobot pretrained model originally trained to classify galaxy morphologies in heterogeneous astronomical imaging surveys. Of the one million Q1 objects that Zoobot was tasked to find strong lenses within, the top 1000 ranked objects contain 122 grade A lenses (almost-certain lenses) and 41 grade B lenses (probable lenses). A deeper search with the five networks combined with visual inspection yielded 250 (247) grade A (B) lenses, of which 224 (182) are ranked in the top 20 000 by Zoobot. When extrapolated to the full Euclid survey, the highest ranked one million images will contain 75 000 grade A or B strong gravitational lenses.
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Submitted 26 June, 2025; v1 submitted 19 March, 2025;
originally announced March 2025.
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Euclid Quick Data Release (Q1): The Strong Lensing Discovery Engine A -- System overview and lens catalogue
Authors:
Euclid Collaboration,
M. Walmsley,
P. Holloway,
N. E. P. Lines,
K. Rojas,
T. E. Collett,
A. Verma,
T. Li,
J. W. Nightingale,
G. Despali,
S. Schuldt,
R. Gavazzi,
A. Melo,
R. B. Metcalf,
I. T. Andika,
L. Leuzzi,
A. Manjón-García,
R. Pearce-Casey,
S. H. Vincken,
J. Wilde,
V. Busillo,
C. Tortora,
J. A. Acevedo Barroso,
H. Dole,
L. R. Ecker
, et al. (350 additional authors not shown)
Abstract:
We present a catalogue of 497 galaxy-galaxy strong lenses in the Euclid Quick Release 1 data (63 deg$^2$). In the initial 0.45\% of Euclid's surveys, we double the total number of known lens candidates with space-based imaging. Our catalogue includes 250 grade A candidates, the vast majority of which (243) were previously unpublished. Euclid's resolution reveals rare lens configurations of scienti…
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We present a catalogue of 497 galaxy-galaxy strong lenses in the Euclid Quick Release 1 data (63 deg$^2$). In the initial 0.45\% of Euclid's surveys, we double the total number of known lens candidates with space-based imaging. Our catalogue includes 250 grade A candidates, the vast majority of which (243) were previously unpublished. Euclid's resolution reveals rare lens configurations of scientific value including double-source-plane lenses, edge-on lenses, complete Einstein rings, and quadruply-imaged lenses. We resolve lenses with small Einstein radii ($θ_{\rm E} < 1''$) in large numbers for the first time. These lenses are found through an initial sweep by deep learning models, followed by Space Warps citizen scientist inspection, expert vetting, and system-by-system modelling. Our search approach scales straightforwardly to Euclid Data Release 1 and, without changes, would yield approximately 7000 high-confidence (grade A or B) lens candidates by late 2026. Further extrapolating to the complete Euclid Wide Survey implies a likely yield of over 100000 high-confidence candidates, transforming strong lensing science.
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Submitted 19 March, 2025;
originally announced March 2025.
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Euclid: A complete Einstein ring in NGC 6505
Authors:
C. M. O'Riordan,
L. J. Oldham,
A. Nersesian,
T. Li,
T. E. Collett,
D. Sluse,
B. Altieri,
B. Clément,
K. Vasan G. C.,
S. Rhoades,
Y. Chen,
T. Jones,
C. Adami,
R. Gavazzi,
S. Vegetti,
D. M. Powell,
J. A. Acevedo Barroso,
I. T. Andika,
R. Bhatawdekar,
A. R. Cooray,
G. Despali,
J. M. Diego,
L. R. Ecker,
A. Galan,
P. Gómez-Alvarez
, et al. (173 additional authors not shown)
Abstract:
We report the discovery of a complete Einstein ring around the elliptical galaxy NGC 6505, at $z=0.042$. This is the first strong gravitational lens discovered in Euclid and the first in an NGC object from any survey. The combination of the low redshift of the lens galaxy, the brightness of the source galaxy ($I_\mathrm{E}=18.1$ lensed, $I_\mathrm{E}=21.3$ unlensed), and the completeness of the ri…
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We report the discovery of a complete Einstein ring around the elliptical galaxy NGC 6505, at $z=0.042$. This is the first strong gravitational lens discovered in Euclid and the first in an NGC object from any survey. The combination of the low redshift of the lens galaxy, the brightness of the source galaxy ($I_\mathrm{E}=18.1$ lensed, $I_\mathrm{E}=21.3$ unlensed), and the completeness of the ring make this an exceptionally rare strong lens, unidentified until its observation by Euclid. We present deep imaging data of the lens from the Euclid Visible Camera (VIS) and Near-Infrared Spectrometer and Photometer (NISP) instruments, as well as resolved spectroscopy from the Keck Cosmic Web Imager (KCWI). The Euclid imaging in particular presents one of the highest signal-to-noise ratio optical/near-infrared observations of a strong gravitational lens to date. From the KCWI data we measure a source redshift of $z=0.406$. Using data from the Dark Energy Spectroscopic Instrument (DESI) we measure a velocity dispersion for the lens galaxy of $σ_\star=303\pm15\,\mathrm{kms}^{-1}$. We model the lens galaxy light in detail, revealing angular structure that varies inside the Einstein ring. After subtracting this light model from the VIS observation, we model the strongly lensed images, finding an Einstein radius of 2.5 arcsec, corresponding to $2.1\,\mathrm{kpc}$ at the redshift of the lens. This is small compared to the effective radius of the galaxy, $R_\mathrm{eff}\sim 12.3\,\mathrm{arcsec}$. Combining the strong lensing measurements with analysis of the spectroscopic data we estimate a dark matter fraction inside the Einstein radius of $f_\mathrm{DM} = (11.1_{-3.5}^{+5.4})\%$ and a stellar initial mass-function (IMF) mismatch parameter of $α_\mathrm{IMF} = 1.26_{-0.08}^{+0.05}$, indicating a heavier-than-Chabrier IMF in the centre of the galaxy.
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Submitted 10 February, 2025;
originally announced February 2025.
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J1721+8842: The first Einstein zig-zag lens
Authors:
F. Dux,
M. Millon,
C. Lemon,
T. Schmidt,
F. Courbin,
A. J. Shajib,
T. Treu,
S. Birrer,
K. C. Wong,
A. Agnello,
A. Andrade,
A. A. Galan,
J. Hjorth,
E. Paic,
S. Schuldt,
A. Schweinfurth,
D. Sluse,
A. Smette,
S. H. Suyu
Abstract:
We report the discovery of the first example of an Einstein zig-zag lens, an extremely rare lensing configuration. In this system, J1721+8842, six images of the same background quasar are formed by two intervening galaxies, one at redshift $z_1 = 0.184$ and a second one at $z_2 = 1.885$. Two out of the six multiple images are deflected in opposite directions as they pass the first lens galaxy on o…
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We report the discovery of the first example of an Einstein zig-zag lens, an extremely rare lensing configuration. In this system, J1721+8842, six images of the same background quasar are formed by two intervening galaxies, one at redshift $z_1 = 0.184$ and a second one at $z_2 = 1.885$. Two out of the six multiple images are deflected in opposite directions as they pass the first lens galaxy on one side, and the second on the other side -- the optical paths forming zig-zags between the two deflectors. In this letter, we demonstrate that J1721+8842, previously thought to be a lensed dual quasar, is in fact a compound lens with the more distant lens galaxy also being distorted as an arc by the foreground galaxy. Evidence supporting this unusual lensing scenario includes: 1- identical light curves in all six lensed quasar images obtained from two years of monitoring at the Nordic Optical Telescope; 2- detection of the additional deflector at redshift $z_2 = 1.885$ in JWST/NIRSpec IFU data; and 3- a multiple-plane lens model reproducing the observed image positions. This unique configuration offers the opportunity to combine two major lensing cosmological probes: time-delay cosmography and dual source-plane lensing since J1721+8842 features multiple lensed sources forming two distinct Einstein radii of different sizes, one of which being a variable quasar. We expect tight constraints on the Hubble constant and the equation of state of dark energy by combining these two probes on the same system. The $z_2 = 1.885$ deflector, a quiescent galaxy, is also the highest-redshift strong galaxy-scale lens with a spectroscopic redshift measurement.
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Submitted 6 November, 2024;
originally announced November 2024.
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Spatial polarization gating of high-harmonic generation in solids
Authors:
Pieter J. van Essen,
Brian de Keijzer,
Tanya van Horen,
Eduardo B. Molinero,
Álvaro Jiménez Galán,
Rui E. F. Silva,
Peter M. Kraus
Abstract:
High-harmonic generation from solids can be utilized as probe of ultrafast dynamics, but thus far only over extended sample areas, since its spatial resolution is diffraction-limited. Here we propose spatial polarization gating, that is using a spatially varying ellipticity of a driving laser pulse to reduce the spatial profile of high-harmonic emission below the diffraction limit and hence increa…
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High-harmonic generation from solids can be utilized as probe of ultrafast dynamics, but thus far only over extended sample areas, since its spatial resolution is diffraction-limited. Here we propose spatial polarization gating, that is using a spatially varying ellipticity of a driving laser pulse to reduce the spatial profile of high-harmonic emission below the diffraction limit and hence increase spatial resolution. We show experimentally and by numerical simulations that our method is generally applicable as suppressing high harmonics in elliptical fields is a common response in all solids. We also briefly explore the possibility of applying this technique to widefield imaging, specifically to nonlinear structured illumination microscopy. Our findings indicate that spatial polarization gating can enable all-optical femto-to-attosecond label-free imaging beyond the Abbe limit.
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Submitted 4 September, 2024;
originally announced September 2024.
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FoodMem: Near Real-time and Precise Food Video Segmentation
Authors:
Ahmad AlMughrabi,
Adrián Galán,
Ricardo Marques,
Petia Radeva
Abstract:
Food segmentation, including in videos, is vital for addressing real-world health, agriculture, and food biotechnology issues. Current limitations lead to inaccurate nutritional analysis, inefficient crop management, and suboptimal food processing, impacting food security and public health. Improving segmentation techniques can enhance dietary assessments, agricultural productivity, and the food p…
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Food segmentation, including in videos, is vital for addressing real-world health, agriculture, and food biotechnology issues. Current limitations lead to inaccurate nutritional analysis, inefficient crop management, and suboptimal food processing, impacting food security and public health. Improving segmentation techniques can enhance dietary assessments, agricultural productivity, and the food production process. This study introduces the development of a robust framework for high-quality, near-real-time segmentation and tracking of food items in videos, using minimal hardware resources. We present FoodMem, a novel framework designed to segment food items from video sequences of 360-degree unbounded scenes. FoodMem can consistently generate masks of food portions in a video sequence, overcoming the limitations of existing semantic segmentation models, such as flickering and prohibitive inference speeds in video processing contexts. To address these issues, FoodMem leverages a two-phase solution: a transformer segmentation phase to create initial segmentation masks and a memory-based tracking phase to monitor food masks in complex scenes. Our framework outperforms current state-of-the-art food segmentation models, yielding superior performance across various conditions, such as camera angles, lighting, reflections, scene complexity, and food diversity. This results in reduced segmentation noise, elimination of artifacts, and completion of missing segments. Here, we also introduce a new annotated food dataset encompassing challenging scenarios absent in previous benchmarks. Extensive experiments conducted on MetaFood3D, Nutrition5k, and Vegetables & Fruits datasets demonstrate that FoodMem enhances the state-of-the-art by 2.5% mean average precision in food video segmentation and is 58 x faster on average.
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Submitted 10 February, 2025; v1 submitted 16 July, 2024;
originally announced July 2024.
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Exploiting the diversity of modeling methods to probe systematic biases in strong lensing analyses
Authors:
A. Galan,
G. Vernardos,
Q. Minor,
D. Sluse,
L. Van de Vyvere,
M. Gomer
Abstract:
Challenges inherent to high-resolution and high signal-to-noise data as well as model degeneracies can cause systematic biases in analyses of strong lens systems. In the past decade, the number of lens modeling methods has significantly increased, from purely analytical methods, to pixelated and non-parametric ones, or ones based on deep learning. We embraced this diversity by selecting different…
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Challenges inherent to high-resolution and high signal-to-noise data as well as model degeneracies can cause systematic biases in analyses of strong lens systems. In the past decade, the number of lens modeling methods has significantly increased, from purely analytical methods, to pixelated and non-parametric ones, or ones based on deep learning. We embraced this diversity by selecting different software packages and use them to blindly model independently simulated Hubble Space Telescope (HST) imaging data. To overcome the difficulties arising from using different codes and conventions, we used the COde-independent Organized LEns STandard (COOLEST) to store, compare, and release all models in a self-consistent and human-readable manner. From an ensemble of six modeling methods, we studied the recovery of the lens potential parameters and properties of the reconstructed source. We find that, overall, both lens and source properties are recovered reasonably well, but systematic biases arise in all methods. Interestingly, we do not observe that a single method is significantly more accurate than others, and the amount of bias largely depends on the specific lens or source property of interest. By combining posterior distributions from individual methods using equal weights, the maximal systematic biases on lens model parameters inferred from individual models are reduced by a factor of 5.4 on average. We investigated a selection of modeling effects that partly explain the observed biases, such as the cuspy nature of the background source and the accuracy of the point spread function. This work introduces, for the first time, a generic framework to compare and ease the combination of models obtained from different codes and methods, which will be key to retain accuracy in future strong lensing analyses.
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Submitted 9 December, 2024; v1 submitted 12 June, 2024;
originally announced June 2024.
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TDCOSMO. XVI. Measurement of the Hubble Constant from the Lensed Quasar WGD$\,$2038$-$4008
Authors:
Kenneth C. Wong,
Frédéric Dux,
Anowar J. Shajib,
Sherry H. Suyu,
Martin Millon,
Pritom Mozumdar,
Patrick R. Wells,
Adriano Agnello,
Simon Birrer,
Elizabeth J. Buckley-Geer,
Frédéric Courbin,
Christopher D. Fassnacht,
Joshua Frieman,
Aymeric Galan,
Huan Lin,
Philip J. Marshall,
Jason Poh,
Stefan Schuldt,
Dominique Sluse,
Tommaso Treu
Abstract:
Time-delay cosmography is a powerful technique to constrain cosmological parameters, particularly the Hubble constant ($H_{0}$). The TDCOSMO collaboration is performing an ongoing analysis of lensed quasars to constrain cosmology using this method. In this work, we obtain constraints from the lensed quasar WGD 2038-4008 using new time-delay measurements and previous mass models by TDCOSMO. This is…
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Time-delay cosmography is a powerful technique to constrain cosmological parameters, particularly the Hubble constant ($H_{0}$). The TDCOSMO collaboration is performing an ongoing analysis of lensed quasars to constrain cosmology using this method. In this work, we obtain constraints from the lensed quasar WGD 2038-4008 using new time-delay measurements and previous mass models by TDCOSMO. This is the first TDCOSMO lens to incorporate multiple lens modeling codes and the full time-delay covariance matrix into the cosmological inference. The models are fixed before the time delay is measured, and the analysis is performed blinded with respect to the cosmological parameters to prevent unconscious experimenter bias. We obtain $D_{Δt} = 1.68^{+0.40}_{-0.38}$ Gpc using two families of mass models, a power-law describing the total mass distribution, and a composite model of baryons and dark matter, although the composite model is disfavored due to kinematics constraints. In a flat $Λ$CDM cosmology, we constrain the Hubble constant to be $H_{0} = 65^{+23}_{-14}\, \rm km\ s^{-1}\,Mpc^{-1}$. The dominant source of uncertainty comes from the time delays, due to the low variability of the quasar. Future long-term monitoring, especially in the era of the Vera C. Rubin Observatory's Legacy Survey of Space and Time, could catch stronger quasar variability and further reduce the uncertainties. This system will be incorporated into an upcoming hierarchical analysis of the entire TDCOSMO sample, and improved time delays and spatially-resolved stellar kinematics could strengthen the constraints from this system in the future.
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Submitted 5 July, 2024; v1 submitted 4 June, 2024;
originally announced June 2024.
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Strong-lensing and kinematic analysis of CASSOWARY 31: can strong lensing constrain the masses of multi-plane lenses?
Authors:
H. Wang,
R. Canameras,
S. H. Suyu,
A. Galan,
C. Grillo,
G. B. Caminha,
L. Christensen
Abstract:
We present a mass measurement for the secondary lens along the line of sight (LoS) in the multi-plane strong lens modeling of the group-scale lens CASSOWARY 31 (CSWA 31). The secondary lens at redshift $z = 1.49$ is a spiral galaxy well aligned along the LoS with the main lens at $z = 0.683$. Using the MUSE integral-field spectroscopy of this spiral galaxy, we measure its rotation velocities and d…
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We present a mass measurement for the secondary lens along the line of sight (LoS) in the multi-plane strong lens modeling of the group-scale lens CASSOWARY 31 (CSWA 31). The secondary lens at redshift $z = 1.49$ is a spiral galaxy well aligned along the LoS with the main lens at $z = 0.683$. Using the MUSE integral-field spectroscopy of this spiral galaxy, we measure its rotation velocities and determine the mass from the gas kinematics. We compare the mass estimation of the secondary lens from the lensing models to the mass measurement from kinematics, finding that the predictions from strong lensing tend to be higher. By introducing an additional lens plane at $z = 1.36$ for an overdensity known to be present, we find a mass of $\simeq 10^{10}$ M$_\odot$ enclosed within 3.3 kpc from the centroid of the spiral galaxy, approaching the estimate from kinematics. This shows that secondary-lens mass measurements from multiple-plane modeling are affected by systematic uncertainties from the degeneracies between lens planes and the complex LoS structure. Conducting a detailed analysis of the LoS structures is therefore essential to improve the mass measurement of the secondary lens.
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Submitted 13 September, 2024; v1 submitted 19 April, 2024;
originally announced April 2024.
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Improving Galileo OSNMA Time To First Authenticated Fix
Authors:
Aleix Galan,
Ignacio Fernandez-Hernandez,
Wim De Wilde,
Sofie Pollin,
Gonzalo Seco-Granados
Abstract:
Galileo is the first global navigation satellite system to authenticate their civilian signals through the Open Service Galileo Message Authentication (OSNMA) protocol. However, OSNMA delays the time to obtain a first position and time fix, the Time To First Authentication Fix (TTFAF). Reducing the TTFAF as much as possible is crucial to integrate the technology seamlessly into the current product…
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Galileo is the first global navigation satellite system to authenticate their civilian signals through the Open Service Galileo Message Authentication (OSNMA) protocol. However, OSNMA delays the time to obtain a first position and time fix, the Time To First Authentication Fix (TTFAF). Reducing the TTFAF as much as possible is crucial to integrate the technology seamlessly into the current products. In the cases where the receiver already has cryptographic data available, the so-called hot start mode and focus of this article, the currently available implementations achieve an average TTFAF of around 100 seconds in ideal environments. In this work, we explore the TTFAF optimizations available to general OSNMA capable receivers and to receivers with a tighter time synchronization than the required by the OSNMA guidelines. We dissect the TTFAF process, describe the optimizations, and benchmark them in three distinct scenarios with recorded real data (open-sky, soft urban, and hard urban) and the official OSNMA test vectors. The first block of optimizations centers on extracting as much information as possible from broken sub-frames by processing them at page level and combining redundant data from multiple satellites. The second block of optimizations aims to reconstruct missed navigation data by the intelligent use of fields in the authentication tags belonging to the same sub-frame as the authentication key. Combining both optimization ideas improves the TTFAF substantially for all considered scenarios. We obtain an average TTFAF of 60.9 and 68.8 seconds for the test vectors and the open-sky scenario, respectively, with a lowest TTFAF of 44.0 seconds in both. Likewise, the urban scenarios see a drastic reduction of the average TTFAF between the non-optimized and optimized cases. These optimizations have been made available as part of the open-source OSNMAlib library on GitHub.
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Submitted 21 October, 2024; v1 submitted 21 March, 2024;
originally announced March 2024.
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El Gordo needs El Anzuelo: Probing the structure of cluster members with multi-band extended arcs in JWST data
Authors:
A. Galan,
G. B. Caminha,
J. Knollmüller,
J. Roth,
S. H. Suyu
Abstract:
Gravitational lensing by galaxy clusters involves hundreds of galaxies over a large redshift range and increases the likelihood of rare phenomena (supernovae, dark substructures, etc.). We present the detailed analysis of \elanz, a prominent quintuply imaged dusty star-forming galaxy ($\zs=2.29$), mainly lensed by three members of the massive galaxy cluster ACT-CL\,J0102$-$4915, also known as \elg…
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Gravitational lensing by galaxy clusters involves hundreds of galaxies over a large redshift range and increases the likelihood of rare phenomena (supernovae, dark substructures, etc.). We present the detailed analysis of \elanz, a prominent quintuply imaged dusty star-forming galaxy ($\zs=2.29$), mainly lensed by three members of the massive galaxy cluster ACT-CL\,J0102$-$4915, also known as \elgor ($z_{\rm d}=0.87$). We leverage JWST/NIRCam images, which contain lensing features that were unseen in previous HST images, using a Bayesian, multi-wavelength, differentiable and GPU-accelerated modeling framework that combines \herculens (lens modeling) and \nifty (field model and inference) software packages. For one of the deflectors, we complement lensing constraints with stellar kinematics measured from VLT/MUSE data. In our lens model, we explicitly include the mass distribution of the cluster, locally corrected by a constant shear field. We find that the two main deflectors (L1 and L2) have logarithmic mass density slopes steeper than isothermal, with $γ_{\rm L1} = 2.23\pm0.05$ and $γ_{\rm L2} = 2.21\pm0.04$. We argue that such steep density profiles can arise due to tidally truncated mass distributions, which we probe thanks to the cluster lensing boost and the strong asymmetry of the lensing configuration. Moreover, our three-dimensional source model captures most of the surface brightness of the lensed galaxy, revealing a clump with a maximum diameter of $400$ parsecs at the source redshift, visible at wavelengths $λ_{\rm rest}\gtrsim0.6$ $μ$m. Finally, we caution on using point-like features within extended arcs to constrain galaxy-scale lens models before securing them with extended arc modeling.
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Submitted 9 October, 2024; v1 submitted 28 February, 2024;
originally announced February 2024.
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Optimal Communication Unbalanced Private Set Union
Authors:
Jean-Guillaume Dumas,
Alexis Galan,
Bruno Grenet,
Aude Maignan,
Daniel S. Roche
Abstract:
We present new two-party protocols for the Unbalanced Private Set Union (UPSU) problem. Here, the Sender holds a set of data points, and the Receiver holds another (possibly much larger) set, and they would like for the Receiver to learn the union of the two sets and nothing else. Furthermore, the Sender's computational cost, along with the communication complexity, should be smaller when the Send…
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We present new two-party protocols for the Unbalanced Private Set Union (UPSU) problem. Here, the Sender holds a set of data points, and the Receiver holds another (possibly much larger) set, and they would like for the Receiver to learn the union of the two sets and nothing else. Furthermore, the Sender's computational cost, along with the communication complexity, should be smaller when the Sender has a smaller set. While the UPSU problem has numerous applications and has seen considerable recent attention in the literature, our protocols are the first where the Sender's computational cost and communication volume are linear in the size of the Sender's set only, and do not depend on the size of the Receiver's set. Our constructions combine linearly homomorphic encryption (LHE) with fully homomorphic encryption (FHE). The first construction uses multi-point polynomial evaluation (MEv) on FHE, and achieves optimal linear cost for the Sender, but has higher quadratic computational cost for the Receiver. In the second construction we explore another trade-off: the Receiver computes fast polynomial Euclidean remainder in FHE while the Sender computes a fast MEv, in LHE only. This reduces the Receiver's cost to quasi-linear, with a modest increase in the computational cost for the Sender. Preliminary experimental results using HElib indicate that, for example, a Sender holding 1000 elements can complete our first protocol using less than 2s of computation time and less than 10MB of communication volume, independently of the Receiver's set size.
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Submitted 18 November, 2025; v1 submitted 26 February, 2024;
originally announced February 2024.
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Mitigating Algorithmic Bias on Facial Expression Recognition
Authors:
Glauco Amigo,
Pablo Rivas Perea,
Robert J. Marks
Abstract:
Biased datasets are ubiquitous and present a challenge for machine learning. For a number of categories on a dataset that are equally important but some are sparse and others are common, the learning algorithms will favor the ones with more presence. The problem of biased datasets is especially sensitive when dealing with minority people groups. How can we, from biased data, generate algorithms th…
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Biased datasets are ubiquitous and present a challenge for machine learning. For a number of categories on a dataset that are equally important but some are sparse and others are common, the learning algorithms will favor the ones with more presence. The problem of biased datasets is especially sensitive when dealing with minority people groups. How can we, from biased data, generate algorithms that treat every person equally? This work explores one way to mitigate bias using a debiasing variational autoencoder with experiments on facial expression recognition.
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Submitted 23 December, 2023;
originally announced December 2023.
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Nine lensed quasars and quasar pairs discovered through spatially-extended variability in Pan-STARRS
Authors:
Frédéric Dux,
Cameron Lemon,
Frédéric Courbin,
Favio Neira,
Timo Anguita,
Aymeric Galan,
Sam Kim,
Maren Hempel,
Angela Hempel,
Régis Lachaume
Abstract:
We present the proof-of-concept of a method to find strongly lensed quasars using their spatially-extended photometric variability through difference imaging in cadenced imaging survey data. We apply the method to Pan-STARRS, starting with an initial selection of 14 107 Gaia multiplets with quasar-like infrared colours from WISE. We identify 229 candidates showing notable spatially-extended variab…
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We present the proof-of-concept of a method to find strongly lensed quasars using their spatially-extended photometric variability through difference imaging in cadenced imaging survey data. We apply the method to Pan-STARRS, starting with an initial selection of 14 107 Gaia multiplets with quasar-like infrared colours from WISE. We identify 229 candidates showing notable spatially-extended variability during the Pan-STARRS survey period. These include 20 known lenses, alongside an additional 12 promising candidates for which we obtain long-slit spectroscopy follow-up. This process results in the confirmation of four doubly lensed quasars, four unclassified quasar pairs and one projected quasar pair. Only three are pairs of stars or quasar+star projections, the false positive rate is thereby 25%. The lenses have separations between 0.81" and 1.24" and source redshifts between z = 1.47 and z = 2.46. Three of the unclassified quasar pairs are promising dual quasars candidates with separations ranging from 6.6 to 9.3 kpc. We expect that this technique will be a particularly efficient way to select lensed variables in the upcoming Rubin-LSST, which will be crucial given the expected limitations for spectroscopic follow-up
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Submitted 25 July, 2023;
originally announced July 2023.
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Accelerating galaxy dynamical modeling using a neural network for joint lensing and kinematics analyses
Authors:
Matthew R. Gomer,
Sebastian Ertl,
Luca Biggio,
Han Wang,
Aymeric Galan,
Lyne Van de Vyvere,
Dominique Sluse,
Georgios Vernardos,
Sherry H. Suyu
Abstract:
Strong gravitational lensing is a powerful tool to provide constraints on galaxy mass distributions and cosmological parameters, such as the Hubble constant, $H_0$. Nevertheless, inference of such parameters from images of lensing systems is not trivial as parameter degeneracies can limit the precision in the measured lens mass and cosmological results. External information on the mass of the lens…
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Strong gravitational lensing is a powerful tool to provide constraints on galaxy mass distributions and cosmological parameters, such as the Hubble constant, $H_0$. Nevertheless, inference of such parameters from images of lensing systems is not trivial as parameter degeneracies can limit the precision in the measured lens mass and cosmological results. External information on the mass of the lens, in the form of kinematic measurements, is needed to ensure a precise and unbiased inference. Traditionally, such kinematic information has been included in the inference after the image modeling, using spherical Jeans approximations to match the measured velocity dispersion integrated within an aperture. However, as spatially resolved kinematic measurements become available via IFU data, more sophisticated dynamical modeling is necessary. Such kinematic modeling is expensive, and constitutes a computational bottleneck which we aim to overcome with our Stellar Kinematics Neural Network (SKiNN). SKiNN emulates axisymmetric modeling using a neural network, quickly synthesizing from a given mass model a kinematic map which can be compared to the observations to evaluate a likelihood. With a joint lensing plus kinematic framework, this likelihood constrains the mass model at the same time as the imaging data. We show that SKiNN's emulation of a kinematic map is accurate to considerably better precision than can be measured (better than $1\%$ in almost all cases). Using SKiNN speeds up the likelihood evaluation by a factor of $\sim 200$. This speedup makes dynamical modeling economical, and enables lens modelers to make effective use of modern data quality in the JWST era.
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Submitted 19 July, 2023;
originally announced July 2023.
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Strong gravitational lensing by AGNs as a probe of the quasar-host relations in the distant Universe
Authors:
Martin Millon,
Frédéric Courbin,
Aymeric Galan,
Dominique Sluse,
Xuheng Ding,
Malte Tewes,
S. G. Djorgovski
Abstract:
The tight correlations found between masses of supermassive black holes (SMBHs) and the luminosities, total stellar masses, and velocity dispersions of their host galaxies are often interpreted as a sign of their co-evolution. Studying these correlations across redshift provides a powerful insight into the evolutionary path followed by the quasar and its host galaxy. While the mass of the black ho…
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The tight correlations found between masses of supermassive black holes (SMBHs) and the luminosities, total stellar masses, and velocity dispersions of their host galaxies are often interpreted as a sign of their co-evolution. Studying these correlations across redshift provides a powerful insight into the evolutionary path followed by the quasar and its host galaxy. While the mass of the black hole is accessible from single-epoch spectra, measuring the mass of its host galaxy is challenging as the active nucleus largely overshines its host. Here, we present a technique to probe quasar-host relations beyond the local universe with strong gravitational lensing, hence overcoming the use of stellar population models or velocity dispersion measurements, both prone to degeneracies. We study in detail one of the three known cases of strong lensing by a quasar to accurately measure the mass of its host and to infer a total lensing mass of $\log_{10}(M_{\rm Tot, h}/M_{\odot}) = 10.27^{+0.06}_{-0.07}~$ within the Einstein radius of 1.2 kpc. The lensing measurement is more precise than any other alternative technique and compatible with the local $M_{BH}$-$M_{\star, h}$ scaling relation. The sample of such quasar-galaxy or quasar-quasar lensing systems should reach a few hundreds with Euclid and Rubin-LSST, thus enabling the application of such a method with statistically significant sample sizes.
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Submitted 24 July, 2024; v1 submitted 1 June, 2023;
originally announced June 2023.
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Algorithmic Information Forecastability
Authors:
Glauco Amigo,
Daniel Andrés Díaz-Pachón,
Robert J. Marks,
Charles Baylis
Abstract:
The outcome of all time series cannot be forecast, e.g. the flipping of a fair coin. Others, like the repeated {01} sequence {010101...} can be forecast exactly. Algorithmic information theory can provide a measure of forecastability that lies between these extremes. The degree of forecastability is a function of only the data. For prediction (or classification) of labeled data, we propose three c…
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The outcome of all time series cannot be forecast, e.g. the flipping of a fair coin. Others, like the repeated {01} sequence {010101...} can be forecast exactly. Algorithmic information theory can provide a measure of forecastability that lies between these extremes. The degree of forecastability is a function of only the data. For prediction (or classification) of labeled data, we propose three categories for forecastability: oracle forecastability for predictions that are always exact, precise forecastability for errors up to a bound, and probabilistic forecastability for any other predictions. Examples are given in each case.
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Submitted 1 December, 2023; v1 submitted 21 April, 2023;
originally announced April 2023.
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SKA Science Data Challenge 2: analysis and results
Authors:
P. Hartley,
A. Bonaldi,
R. Braun,
J. N. H. S. Aditya,
S. Aicardi,
L. Alegre,
A. Chakraborty,
X. Chen,
S. Choudhuri,
A. O. Clarke,
J. Coles,
J. S. Collinson,
D. Cornu,
L. Darriba,
M. Delli Veneri,
J. Forbrich,
B. Fraga,
A. Galan,
J. Garrido,
F. Gubanov,
H. Håkansson,
M. J. Hardcastle,
C. Heneka,
D. Herranz,
K. M. Hess
, et al. (83 additional authors not shown)
Abstract:
The Square Kilometre Array Observatory (SKAO) will explore the radio sky to new depths in order to conduct transformational science. SKAO data products made available to astronomers will be correspondingly large and complex, requiring the application of advanced analysis techniques to extract key science findings. To this end, SKAO is conducting a series of Science Data Challenges, each designed t…
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The Square Kilometre Array Observatory (SKAO) will explore the radio sky to new depths in order to conduct transformational science. SKAO data products made available to astronomers will be correspondingly large and complex, requiring the application of advanced analysis techniques to extract key science findings. To this end, SKAO is conducting a series of Science Data Challenges, each designed to familiarise the scientific community with SKAO data and to drive the development of new analysis techniques. We present the results from Science Data Challenge 2 (SDC2), which invited participants to find and characterise 233245 neutral hydrogen (Hi) sources in a simulated data product representing a 2000~h SKA MID spectral line observation from redshifts 0.25 to 0.5. Through the generous support of eight international supercomputing facilities, participants were able to undertake the Challenge using dedicated computational resources. Alongside the main challenge, `reproducibility awards' were made in recognition of those pipelines which demonstrated Open Science best practice. The Challenge saw over 100 participants develop a range of new and existing techniques, with results that highlight the strengths of multidisciplinary and collaborative effort. The winning strategy -- which combined predictions from two independent machine learning techniques to yield a 20 percent improvement in overall performance -- underscores one of the main Challenge outcomes: that of method complementarity. It is likely that the combination of methods in a so-called ensemble approach will be key to exploiting very large astronomical datasets.
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Submitted 14 March, 2023;
originally announced March 2023.
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Modeling lens potentials with continuous neural fields in galaxy-scale strong lenses
Authors:
Luca Biggio,
Georgios Vernardos,
Aymeric Galan,
Austin Peel
Abstract:
Strong gravitational lensing is a unique observational tool for studying the dark and luminous mass distribution both within and between galaxies. Given the presence of substructures, current strong lensing observations demand more complex mass models than smooth analytical profiles, such as power-law ellipsoids. In this work, we introduce a continuous neural field to predict the lensing potential…
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Strong gravitational lensing is a unique observational tool for studying the dark and luminous mass distribution both within and between galaxies. Given the presence of substructures, current strong lensing observations demand more complex mass models than smooth analytical profiles, such as power-law ellipsoids. In this work, we introduce a continuous neural field to predict the lensing potential at any position throughout the image plane, allowing for a nearly model-independent description of the lensing mass. We apply our method on simulated Hubble Space Telescope imaging data containing different types of perturbations to a smooth mass distribution: a localized dark subhalo, a population of subhalos, and an external shear perturbation. Assuming knowledge of the source surface brightness, we use the continuous neural field to model either the perturbations alone or the full lensing potential. In both cases, the resulting model is able to fit the imaging data, and we are able to accurately recover the properties of both the smooth potential and of the perturbations. Unlike many other deep learning methods, ours explicitly retains lensing physics (i.e., the lens equation) and introduces high flexibility in the model only where required, namely, in the lens potential. Moreover, the neural network does not require pre-training on large sets of labelled data and predicts the potential from the single observed lensing image. Our model is implemented in the fully differentiable lens modeling code Herculens.
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Submitted 17 October, 2022;
originally announced October 2022.
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Using wavelets to capture deviations from smoothness in galaxy-scale strong lenses
Authors:
Aymeric Galan,
Georgios Vernardos,
Austin Peel,
Frédéric Courbin,
Jean-Luc Starck
Abstract:
Modeling the mass distribution of galaxy-scale strong gravitational lenses is a task of increasing difficulty. The high-resolution and depth of imaging data now available render simple analytical forms ineffective at capturing lens structures spanning a large range in spatial scale, mass scale, and morphology. In this work, we address the problem with a novel multiscale method based on wavelets. W…
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Modeling the mass distribution of galaxy-scale strong gravitational lenses is a task of increasing difficulty. The high-resolution and depth of imaging data now available render simple analytical forms ineffective at capturing lens structures spanning a large range in spatial scale, mass scale, and morphology. In this work, we address the problem with a novel multiscale method based on wavelets. We tested our method on simulated Hubble Space Telescope (HST) imaging data of strong lenses containing the following different types of mass substructures making them deviate from smooth models: (1) a localized small dark matter subhalo, (2) a Gaussian random field (GRF) that mimics a nonlocalized population of subhalos along the line of sight, and (3) galaxy-scale multipoles that break elliptical symmetry. We show that wavelets are able to recover all of these structures accurately. This is made technically possible by using gradient-informed optimization based on automatic differentiation over thousands of parameters, which also allow us to sample the posterior distributions of all model parameters simultaneously. By construction, our method merges the two main modeling paradigms - analytical and pixelated - with machine-learning optimization techniques into a single modular framework. It is also well-suited for the fast modeling of large samples of lenses. All methods presented here are publicly available in our new Herculens package.
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Submitted 21 November, 2022; v1 submitted 12 July, 2022;
originally announced July 2022.
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Gravitationally lensed quasars in Gaia -- IV. 150 new lenses, quasar pairs, and projected quasars
Authors:
C. Lemon,
T. Anguita,
M. Auger,
F. Courbin,
A. Galan,
R. McMahon,
F. Neira,
M. Oguri,
P. Schechter,
A. Shajib,
T. Treu
Abstract:
We report the spectroscopic follow-up of 175 lensed quasar candidates selected using Gaia Data Release 2 observations following Lemon et al. 2019. Systems include 86 confirmed lensed quasars and a further 17 likely lensed quasars based on imaging and/or similar spectra. We also confirm 11 projected quasar pairs and 11 physical quasar pairs, while 25 systems are left as unclassified quasar pairs --…
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We report the spectroscopic follow-up of 175 lensed quasar candidates selected using Gaia Data Release 2 observations following Lemon et al. 2019. Systems include 86 confirmed lensed quasars and a further 17 likely lensed quasars based on imaging and/or similar spectra. We also confirm 11 projected quasar pairs and 11 physical quasar pairs, while 25 systems are left as unclassified quasar pairs -- pairs of quasars at the same redshift, which could be either distinct quasars or potential lensed quasars. Especially interesting objects include 8 quadruply imaged quasars of which two have BAL sources, an apparent triple, and a doubly lensed LoBaL quasar. The source redshifts and image separations of these new lenses range between 0.65 - 3.59 and 0.78 - 6.23 arcseconds respectively. We compare the known population of lensed quasars to an updated mock catalogue at image separations between 1 and 4 arcseconds, showing a very good match at z<1.5. At z>1.5, only 47% of the predicted number are known, with 56% of these missing lenses at image separations below 1.5 arcseconds. The missing higher-redshift, small-separation systems will have fainter lensing galaxies, and are partially explained by the unclassified quasar pairs and likely lenses presented in this work, which require deeper imaging. Of the 11 new reported projected quasar pairs, 5 have impact parameters below 10 kpc, almost tripling the number of such systems, which can probe the innermost regions of quasar host galaxies through absorption studies. We also report four new lensed galaxies discovered through our searches, with source redshifts ranging from 0.62 to 2.79.
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Submitted 15 June, 2022;
originally announced June 2022.
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Lightweight HI source finding for next generation radio surveys
Authors:
Emma Tolley,
Damien Korber,
Aymeric Galan,
Austin Peel,
Mark T. Sargent,
Jean-Paul Kneib,
Frederic Courbin,
Jean-Luc Starck
Abstract:
Future deep HI surveys will be essential for understanding the nature of galaxies and the content of the Universe. However, the large volume of these data will require distributed and automated processing techniques. We introduce LiSA, a set of python modules for the denoising, detection and characterization of HI sources in 3D spectral data. LiSA was developed and tested on the Square Kilometer A…
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Future deep HI surveys will be essential for understanding the nature of galaxies and the content of the Universe. However, the large volume of these data will require distributed and automated processing techniques. We introduce LiSA, a set of python modules for the denoising, detection and characterization of HI sources in 3D spectral data. LiSA was developed and tested on the Square Kilometer Array Science Data Challenge 2 dataset, and contains modules and pipelines for easy domain decomposition and parallel execution. LiSA contains algorithms for 2D-1D wavelet denoising using the starlet transform and flexible source finding using null-hypothesis testing. These algorithms are lightweight and portable, needing only a few user-defined parameters reflecting the resolution of the data. LiSA also includes two convolutional neural networks developed to analyse data cubes which separate HI sources from artifacts and predict the HI source properties. All of these components are designed to be as modular as possible, allowing users to mix and match different components to create their ideal pipeline. We demonstrate the performance of the different components of LiSA on the SDC2 dataset, which is able to find 95% of HI sources with SNR > 3 and accurately predict their properties.
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Submitted 20 April, 2022;
originally announced April 2022.
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TDCOSMO. IX. Systematic comparison between lens modelling software programs: time delay prediction for WGD 2038-4008
Authors:
A. J. Shajib,
K. C. Wong,
S. Birrer,
S. H. Suyu,
T. Treu,
E. Buckley-Geer,
H. Lin,
C. E. Rusu,
J. Poh,
A. Palmese,
A. Agnello,
M. W. Auger-Williams,
A. Galan,
S. Schuldt,
D. Sluse,
F. Courbin,
J. Frieman,
M. Millon
Abstract:
The importance of alternative methods for measuring the Hubble constant, such as time-delay cosmography, is highlighted by the recent Hubble tension. It is paramount to thoroughly investigate and rule out systematic biases in all measurement methods before we can accept new physics as the source of this tension. In this study, we perform a check for systematic biases in the lens modelling procedur…
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The importance of alternative methods for measuring the Hubble constant, such as time-delay cosmography, is highlighted by the recent Hubble tension. It is paramount to thoroughly investigate and rule out systematic biases in all measurement methods before we can accept new physics as the source of this tension. In this study, we perform a check for systematic biases in the lens modelling procedure of time-delay cosmography by comparing independent and blind time-delay predictions of the system WGD 2038-4008 from two teams using two different software programs: GLEE and LENSTRONOMY. The predicted time delays from the two teams incorporate the stellar kinematics of the deflector and the external convergence from line-of-sight structures. The un-blinded time-delay predictions from the two teams agree within $1.2σ$, implying that once the time delay is measured the inferred Hubble constant will also be mutually consistent. However, there is a $\sim$4$σ$ discrepancy between the power-law model slope and external shear, which is a significant discrepancy at the level of lens models before the stellar kinematics and the external convergence are incorporated. We identify the difference in the reconstructed point spread function (PSF) to be the source of this discrepancy. When the same reconstructed PSF was used by both teams, we achieved excellent agreement, within $\sim$0.6$σ$, indicating that potential systematics stemming from source reconstruction algorithms and investigator choices are well under control. We recommend that future studies supersample the PSF as needed and marginalize over multiple algorithms or realizations for the PSF reconstruction to mitigate the systematics associated with the PSF. A future study will measure the time delays of the system WGD 2038-4008 and infer the Hubble constant based on our mass models.
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Submitted 21 September, 2022; v1 submitted 22 February, 2022;
originally announced February 2022.
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TDCOSMO. VII. Boxyness/discyness in lensing galaxies : Detectability and impact on $H_0$
Authors:
Lyne Van de Vyvere,
Matthew R. Gomer,
Dominique Sluse,
Dandan Xu,
Simon Birrer,
Aymeric Galan,
Georgios Vernardos
Abstract:
In the context of gravitational lensing, the density profile of lensing galaxies is often considered to be perfectly elliptical. Potential angular structures are generally ignored, except to explain flux ratios anomalies. Surprisingly, the impact of azimuthal structures on extended images of the source has not been characterized, nor its impact on the H0 inference. We address this task by creating…
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In the context of gravitational lensing, the density profile of lensing galaxies is often considered to be perfectly elliptical. Potential angular structures are generally ignored, except to explain flux ratios anomalies. Surprisingly, the impact of azimuthal structures on extended images of the source has not been characterized, nor its impact on the H0 inference. We address this task by creating mock images of a point source embedded in an extended source, lensed by an elliptical galaxy on which multipolar components are added to emulate boxy/discy isodensity contours. Modeling such images with a density profile free of angular structure allow us to explore the detectability of image deformation induced by the multipoles in the residual frame. Multipole deformations are almost always detectable for our highest signal-to-noise mock data. However the detectability depends on the lens ellipticity and Einstein radius, on the S/N of the data, and on the specific lens modeling strategy. Multipoles also introduce small changes to the time delays. We therefore quantify how undetected multipoles would impact H0 inference. When no multipoles are detected in the residuals, the impact on H0 for a given lens is in general less than a few km/s/Mpc, but in the worst case scenario, combining low S/N in the ring and large intrinsic boxyness/discyness, the bias on H0 can reach 10-12 km/s/Mpc. If we now look at the inference on H0 from a population of lensing galaxies, having a distribution of multipoles representative of what is found in the light-profile of elliptical galaxies, we then find a systematic bias on H0 < 1%. The comparison of our mock systems to the state-of-the-art time delay lens sample studied by the H0LiCOW and TDCOSMO collaborations, indicates that multipoles are currently unlikely to be a source of substantial systematic bias on the inferred value of H0 from time-delay lenses.
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Submitted 3 March, 2022; v1 submitted 7 December, 2021;
originally announced December 2021.
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Generatively Augmented Neural Network Watchdog for Image Classification Networks
Authors:
Justin M. Bui,
Glauco A. Amigo,
Robert J. Marks II
Abstract:
The identification of out-of-distribution data is vital to the deployment of classification networks. For example, a generic neural network that has been trained to differentiate between images of dogs and cats can only classify an input as either a dog or a cat. If a picture of a car or a kumquat were to be supplied to this classifier, the result would still be either a dog or a cat. In order to…
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The identification of out-of-distribution data is vital to the deployment of classification networks. For example, a generic neural network that has been trained to differentiate between images of dogs and cats can only classify an input as either a dog or a cat. If a picture of a car or a kumquat were to be supplied to this classifier, the result would still be either a dog or a cat. In order to mitigate this, techniques such as the neural network watchdog have been developed. The compression of the image input into the latent layer of the autoencoder defines the region of in-distribution in the image space. This in-distribution set of input data has a corresponding boundary in the image space. The watchdog assesses whether inputs are in inside or outside this boundary. This paper demonstrates how to sharpen this boundary using generative network training data augmentation thereby bettering the discrimination and overall performance of the watchdog.
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Submitted 7 September, 2021;
originally announced September 2021.
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Strong lens systems search in the Dark Energy Survey using Convolutional Neural Networks
Authors:
K. Rojas,
E. Savary,
B. Clément,
M. Maus,
F. Courbin,
C. Lemon,
J. H. H. Chan,
G. Vernardos,
R. Joseph,
R. Cañameras,
A. Galan
Abstract:
We performed a search for strong lens galaxy-scale systems in the first data release of the Dark Energy Survey (DES), from a color-selected parent sample of 18~745~029 Luminous Red Galaxies (LRGs). Our search was based on a Convolutional Neural Network (CNN) to grade our LRG selection with values between 0 (non-lens) and 1 (lens). Our training set was data-driven, i.e. using lensed sources taken f…
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We performed a search for strong lens galaxy-scale systems in the first data release of the Dark Energy Survey (DES), from a color-selected parent sample of 18~745~029 Luminous Red Galaxies (LRGs). Our search was based on a Convolutional Neural Network (CNN) to grade our LRG selection with values between 0 (non-lens) and 1 (lens). Our training set was data-driven, i.e. using lensed sources taken from HST COSMOS images and where the light distribution of the lens plane was taken directly from DES images of our LRGs. A total of 76~582 cutouts obtained a score above 0.9. These were visually inspected and resulted in two catalogs. The first one contains 405 lens candidates, where 90 present clear lensing features and counterparts, while the others 315 require more evidence, such as higher resolution images or spectra to be conclusive. A total of 186 candidates were totally new identified in this search. The second catalog includes 539 ring galaxy candidates that will be useful to train CNNs against this type of false positives. For the 90 best lens candidates we carried out color-based deblending of the lens and source light without fitting any analytical profile to the data. The method turned out to be very efficient in the deblending, even for very compact objects and for objects with very complex morphology. Finally, from the 90 best lens candidates we selected 52 systems having one single deflector, to test an automated modeling pipeline which successfully modeled 79\% of the sample within an acceptable amount of computing time.
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Submitted 31 August, 2021;
originally announced September 2021.
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Cascade Watchdog: A Multi-tiered Adversarial Guard for Outlier Detection
Authors:
Glauco Amigo,
Justin M. Bui,
Charles Baylis,
Robert J. Marks
Abstract:
The identification of out-of-distribution content is critical to the successful implementation of neural networks. Watchdog techniques have been developed to support the detection of these inputs, but the performance can be limited by the amount of available data. Generative adversarial networks have displayed numerous capabilities, including the ability to generate facsimiles with excellent accur…
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The identification of out-of-distribution content is critical to the successful implementation of neural networks. Watchdog techniques have been developed to support the detection of these inputs, but the performance can be limited by the amount of available data. Generative adversarial networks have displayed numerous capabilities, including the ability to generate facsimiles with excellent accuracy. This paper presents and empirically evaluates a multi-tiered watchdog, which is developed using GAN generated data, for improved out-of-distribution detection. The cascade watchdog uses adversarial training to increase the amount of available data similar to the out-of-distribution elements that are more difficult to detect. Then, a specialized second guard is added in sequential order. The results show a solid and significant improvement on the detection of the most challenging out-of-distribution inputs while preserving an extremely low false positive rate.
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Submitted 14 June, 2022; v1 submitted 20 August, 2021;
originally announced August 2021.
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lenstronomy II: A gravitational lensing software ecosystem
Authors:
Simon Birrer,
Anowar J. Shajib,
Daniel Gilman,
Aymeric Galan,
Jelle Aalbers,
Martin Millon,
Robert Morgan,
Giulia Pagano,
Ji Won Park,
Luca Teodori,
Nicolas Tessore,
Madison Ueland,
Lyne Van de Vyvere,
Sebastian Wagner-Carena,
Ewoud Wempe,
Lilan Yang,
Xuheng Ding,
Thomas Schmidt,
Dominique Sluse,
Ming Zhang,
Adam Amara
Abstract:
lenstronomy is an Astropy-affiliated Python package for gravitational lensing simulations and analyses. lenstronomy was introduced by Birrer and Amara (2018) and is based on the linear basis set approach by Birrer et a. (2015). The user and developer base of lenstronomy has substantially grown since then, and the software has become an integral part of a wide range of recent analyses, such as meas…
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lenstronomy is an Astropy-affiliated Python package for gravitational lensing simulations and analyses. lenstronomy was introduced by Birrer and Amara (2018) and is based on the linear basis set approach by Birrer et a. (2015). The user and developer base of lenstronomy has substantially grown since then, and the software has become an integral part of a wide range of recent analyses, such as measuring the Hubble constant with time-delay strong lensing or constraining the nature of dark matter from resolved and unresolved small scale lensing distortion statistics. The modular design has allowed the community to incorporate innovative new methods, as well as to develop enhanced software and wrappers with more specific aims on top of the lenstronomy API. Through community engagement and involvement, lenstronomy has become a foundation of an ecosystem of affiliated packages extending the original scope of the software and proving its robustness and applicability at the forefront of the strong gravitational lensing community in an open source and reproducible manner.
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Submitted 10 June, 2021;
originally announced June 2021.
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SLITronomy: towards a fully wavelet-based strong lensing inversion technique
Authors:
A. Galan,
A. Peel,
R. Joseph,
F. Courbin,
J. -L. Starck
Abstract:
Strong gravitational lensing provides a wealth of astrophysical information on the baryonic and dark matter content of galaxies. It also serves as a valuable cosmological probe by allowing us to measure the Hubble constant independently of other methods. These applications all require the difficult task of inverting the lens equation and simultaneously reconstructing the mass profile of the lens a…
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Strong gravitational lensing provides a wealth of astrophysical information on the baryonic and dark matter content of galaxies. It also serves as a valuable cosmological probe by allowing us to measure the Hubble constant independently of other methods. These applications all require the difficult task of inverting the lens equation and simultaneously reconstructing the mass profile of the lens along with the original light profile of the unlensed source. As there is no reason for either the lens or the source to be simple, we need methods that both invert the lens equation with a large number of degrees of freedom and also enforce a well-controlled regularisation that avoids the appearance of spurious structures. This can be beautifully accomplished by representing signals in wavelet space. Building on the Sparse Lens Inversion Technique (SLIT), in this work we present an improved sparsity-based method that describes lensed sources using wavelets and optimises over the parameters given an analytical lens mass profile. We apply our technique on simulated HST and E-ELT data, as well as on real HST images of lenses from the Sloan Lens ACS (SLACS) sample, assuming a lens model. We show that wavelets allow us to reconstruct lensed sources containing detailed substructures when using both present-day data and high-resolution images from future thirty-meter-class telescopes. Wavelets moreover provide a much more tractable solution in terms of quality and computation time compared to using a source model that combines smooth analytical profiles and shapelets. Requiring very little human interaction, our pixel-based technique fits into the effort to devise automated modelling schemes. It can be incorporated in the standard workflow of sampling analytical lens model parameters. The method, which we call SLITronomy, is freely available as a new plug-in to the modelling software Lenstronomy.
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Submitted 4 December, 2020;
originally announced December 2020.
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TDCOSMO IV: Hierarchical time-delay cosmography -- joint inference of the Hubble constant and galaxy density profiles
Authors:
S. Birrer,
A. J. Shajib,
A. Galan,
M. Millon,
T. Treu,
A. Agnello,
M. Auger,
G. C. -F. Chen,
L. Christensen,
T. Collett,
F. Courbin,
C. D. Fassnacht,
L. V. E. Koopmans,
P. J. Marshall,
J. -W. Park,
C. E. Rusu,
D. Sluse,
C. Spiniello,
S. H. Suyu,
S. Wagner-Carena,
K. C. Wong,
M. Barnabè,
A. S. Bolton,
O. Czoske,
X. Ding
, et al. (2 additional authors not shown)
Abstract:
The H0LiCOW collaboration inferred via gravitational lensing time delays a Hubble constant $H_0=73.3^{+1.7}_{-1.8}$ km s$^{-1}{\rm Mpc}^{-1}$, describing deflector mass density profiles by either a power-law or stars plus standard dark matter halos. The mass-sheet transform (MST) that leaves the lensing observables unchanged is considered the dominant source of residual uncertainty in $H_0$. We qu…
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The H0LiCOW collaboration inferred via gravitational lensing time delays a Hubble constant $H_0=73.3^{+1.7}_{-1.8}$ km s$^{-1}{\rm Mpc}^{-1}$, describing deflector mass density profiles by either a power-law or stars plus standard dark matter halos. The mass-sheet transform (MST) that leaves the lensing observables unchanged is considered the dominant source of residual uncertainty in $H_0$. We quantify any potential effect of the MST with flexible mass models that are maximally degenerate with H0. Our calculation is based on a new hierarchical approach in which the MST is only constrained by stellar kinematics. The approach is validated on hydrodynamically simulated lenses. We apply the method to the TDCOSMO sample of 7 lenses (6 from H0LiCOW) and measure $H_0=74.5^{+5.6}_{-6.1}$ km s$^{-1}{\rm Mpc}^{-1}$. In order to further constrain the deflector mass profiles, we then add imaging and spectroscopy for 33 strong gravitational lenses from the SLACS sample. For 9 of the SLAC lenses we use resolved kinematics to constrain the stellar anisotropy. From the joint analysis of the TDCOSMO+SLACS sample, we measure $H_0=67.4^{+4.1}_{-3.2}$ km s$^{-1}{\rm Mpc}^{-1}$, assuming that the TDCOSMO and SLACS galaxies are drawn from the same parent population. The blind H0LiCOW, TDCOSMO-only and TDCOSMO+SLACS analyses are in mutual statistical agreement. The TDCOSMO+SLACS analysis prefers marginally shallower mass profiles than H0LiCOW or TDCOSMO-only. While our new analysis does not statistically invalidate the mass profile assumptions by H0LiCOW, and thus their $H_0$ measurement relying on those, it demonstrates the importance of understanding the mass density profile of elliptical galaxies. The uncertainties on $H_0$ derived in this paper can be reduced by physical or observational priors on the form of the mass profile, or by additional data, chiefly spatially resolved kinematics of lens galaxies.
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Submitted 19 December, 2020; v1 submitted 6 July, 2020;
originally announced July 2020.
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Time Delay Lens Modelling Challenge
Authors:
X. Ding,
T. Treu,
S. Birrer,
G. C. -F. Chen,
J. Coles,
P. Denzel,
M. Frigo A. Galan,
P. J. Marshall,
M. Millon,
A. More,
A. J. Shajib,
D. Sluse,
H. Tak,
D. Xu,
M. W. Auger,
V. Bonvin,
H. Chand,
F. Courbin,
G. Despali,
C. D. Fassnacht,
D. Gilman,
S. Hilbert,
S. R. Kumar,
Y. -Y. Lin,
J. W. Park
, et al. (4 additional authors not shown)
Abstract:
In recent years, breakthroughs in methods and data have enabled gravitational time delays to emerge as a very powerful tool to measure the Hubble constant $H_0$. However, published state-of-the-art analyses require of order 1 year of expert investigator time and up to a million hours of computing time per system. Furthermore, as precision improves, it is crucial to identify and mitigate systematic…
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In recent years, breakthroughs in methods and data have enabled gravitational time delays to emerge as a very powerful tool to measure the Hubble constant $H_0$. However, published state-of-the-art analyses require of order 1 year of expert investigator time and up to a million hours of computing time per system. Furthermore, as precision improves, it is crucial to identify and mitigate systematic uncertainties. With this time delay lens modelling challenge we aim to assess the level of precision and accuracy of the modelling techniques that are currently fast enough to handle of order 50 lenses, via the blind analysis of simulated datasets. The results in Rung 1 and Rung 2 show that methods that use only the point source positions tend to have lower precision ($10 - 20\%$) while remaining accurate. In Rung 2, the methods that exploit the full information of the imaging and kinematic datasets can recover $H_0$ within the target accuracy ($ |A| < 2\%$) and precision ($< 6\%$ per system), even in the presence of poorly known point spread function and complex source morphology. A post-unblinding analysis of Rung 3 showed the numerical precision of the ray-traced cosmological simulations to be insufficient to test lens modelling methodology at the percent level, making the results difficult to interpret. A new challenge with improved simulations is needed to make further progress in the investigation of systematic uncertainties. For completeness, we present the Rung 3 results in an appendix, and use them to discuss various approaches to mitigating against similar subtle data generation effects in future blind challenges.
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Submitted 17 February, 2021; v1 submitted 15 June, 2020;
originally announced June 2020.
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Testing the Evolution of the Correlations between Supermassive Black Holes and their Host Galaxies using Eight Strongly Lensed Quasars
Authors:
Xuheng Ding,
Tommaso Treu,
Simon Birrer,
Adriano Agnello,
Dominique Sluse,
Chris Fassnacht,
Matthew W. Auger,
Kenneth C. Wong,
Sherry H. Suyu,
Takahiro Morishita,
Cristian E. Rusu,
Aymeric Galan
Abstract:
One of the main challenges in using high redshift active galactic nuclei to study the correlations between the mass of the supermassive Black Hole (MBH) and the properties of their active host galaxies is instrumental resolution. Strong lensing magnification effectively increases instrumental resolution and thus helps to address this challenge. In this work, we study eight strongly lensed active g…
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One of the main challenges in using high redshift active galactic nuclei to study the correlations between the mass of the supermassive Black Hole (MBH) and the properties of their active host galaxies is instrumental resolution. Strong lensing magnification effectively increases instrumental resolution and thus helps to address this challenge. In this work, we study eight strongly lensed active galactic nuclei (AGN) with deep Hubble Space Telescope imaging, using the lens modelling code Lenstronomy to reconstruct the image of the source. Using the reconstructed brightness of the host galaxy, we infer the host galaxy stellar mass based on stellar population models. MBH are estimated from broad emission lines using standard methods. Our results are in good agreement with recent work based on non-lensed AGN, demonstrating the potential of using strongly lensed AGNs to extend the study of the correlations to higher redshifts. At the moment, the sample size of lensed AGN is small and thus they provide mostly a consistency check on systematic errors related to resolution for the non-lensed AGN. However, the number of known lensed AGN is expected to increase dramatically in the next few years, through dedicated searches in ground and space based wide field surveys, and they may become a key diagnostic of black hole and galaxy co-evolution.
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Submitted 13 November, 2020; v1 submitted 27 May, 2020;
originally announced May 2020.