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Using diffusion models to solve inverse problems is a growing field of research. Current methods assume the degradation to be known and provide impressive results in terms of restoration quality and diversity. In this work, we leverage the…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Charles Laroche , Andrés Almansa , Eva Coupete

Current ground-based cosmological surveys, such as the Dark Energy Survey (DES), are predicted to discover thousands of galaxy-scale strong lenses, while future surveys, such as the Vera Rubin Observatory Legacy Survey of Space and Time…

Instrumentation and Methods for Astrophysics · Physics 2022-11-14 Jason Poh , Ashwin Samudre , Aleksandra Ćiprijanović , Brian Nord , Gourav Khullar , Dimitrios Tanoglidis , Joshua A. Frieman

We present a forward modeling framework for estimating galaxy redshift distributions from photometric surveys. Our forward model is composed of: a detailed population model describing the intrinsic distribution of physical characteristics…

Cosmology and Nongalactic Astrophysics · Physics 2023-02-01 Justin Alsing , Hiranya Peiris , Daniel Mortlock , Joel Leja , Boris Leistedt

Density-equalizing map (DEM) serves as a powerful technique for creating shape deformations with the area changes reflecting an underlying density function. In recent decades, DEM has found widespread applications in fields such as data…

Graphics · Computer Science 2025-11-18 Yanwen Huang , Lok Ming Lui , Gary P. T. Choi

We present $griz$ photometric light curves for the full 5 years of the Dark Energy Survey Supernova program (DES-SN), obtained with both forced Point Spread Function (PSF) photometry on Difference Images (DIFFIMG) performed during survey…

Spatially-varying depth and characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, in particular in deep multi-epoch surveys. We…

Fast pixelated detectors incorporating direct electron detection (DED) technology are increasingly being regarded as universal detectors for scanning transmission electron microscopy (STEM), capable of imaging under multiple modes of…

In this manuscript, we investigate late-time cosmology and the evolution of cosmic structures using an interacting dark fluid model in which dark matter (DM) and dark energy (DE) interact through a diffusive mechanism. To provide a…

Cosmology and Nongalactic Astrophysics · Physics 2025-12-01 Shambel Sahlu , Upala Mukhopadhyay , Remudin R. Mekuria , Amare Abebe

In this white paper, we present an experimental road map for spectroscopic experiments beyond DESI. DESI will be a transformative cosmological survey in the 2020s, mapping 40 million galaxies and quasars and capturing a significant fraction…

Traditional estimators of the galaxy power spectrum and bispectrum are sensitive to the survey geometry. They yield spectra that differ from the true underlying signal since they are convolved with the window function of the survey. For the…

Cosmology and Nongalactic Astrophysics · Physics 2022-12-20 Davit Alkhanishvili , Cristiano Porciani , Emiliano Sefusatti

The discovery of cosmic acceleration has inspired ambitious experimental and observational efforts to understand its origin. Many of these take the form of large astronomical surveys, sometimes using new, special-purpose instrumentation,…

Cosmology and Nongalactic Astrophysics · Physics 2013-09-24 David Weinberg , Deborah Bard , Kyle Dawson , Olivier Dore , Joshua Frieman , Karl Gebhardt , Michael Levi , Jason Rhodes

We present FORECAST, a new flexible and adaptable software package that performs forward modeling of the output of any cosmological hydrodynamical simulations to create a wide range of realistic synthetic astronomical images. With…

We present griz light curves of 251 Type Ia Supernovae (SNe Ia) from the first 3 years of the Dark Energy Survey Supernova Program's (DES-SN) spectroscopically classified sample. The photometric pipeline described in this paper produces the…

Supervised deep learning models depend on massive labeled data. Unfortunately, it is time-consuming and labor-intensive to collect and annotate bitemporal samples containing desired changes. Transfer learning from pre-trained models is…

Computer Vision and Pattern Recognition · Computer Science 2022-09-13 Hao Chen , Wenyuan Li , Song Chen , Zhenwei Shi

Deep learning models are being used for the analysis of parametric statistical models based on simulation-only frameworks. Bayesian models using normalizing flows simulate data from a prior distribution and are composed of two deep neural…

Statistics Theory · Mathematics 2026-03-12 Stefan Böhringer

Recent analyses in the literature suggest that the concordance $\Lambda$CDM model with rigid cosmological term, $\Lambda=$const., may not be the best description of the cosmic acceleration. The class of "running vacuum models", in which…

Cosmology and Nongalactic Astrophysics · Physics 2017-03-29 Joan Sola , Adria Gomez-Valent , Javier de Cruz Perez

The lack of reliable data in developing countries is a major obstacle to sustainable development, food security, and disaster relief. Poverty data, for example, is typically scarce, sparse in coverage, and labor-intensive to obtain. Remote…

Computer Vision and Pattern Recognition · Computer Science 2016-03-01 Michael Xie , Neal Jean , Marshall Burke , David Lobell , Stefano Ermon

Weak lensing by large-scale structure is a powerful probe of cosmology and of the dark universe. This cosmic shear technique relies on the accurate measurement of the shapes and redshifts of background galaxies and requires precise control…

We reconstruct the dark matter density field from spatially overlapping spectroscopic and photometric redshift catalogs through a forward modelling approach. Instead of directly inferring the underlying density field, we find the best…

Cosmology and Nongalactic Astrophysics · Physics 2023-12-01 Benjamin Horowitz , Peter Melchior