550 citations · 3.9k across the 60 of their papers we have counts for
60 papers
Enhancing WISE Infrared Imaging to Spitzer Resolution Using Deep Learning Super-Resolution
Saeed Rezaee, Shoubaneh Hemmati, Bahram Mobasher +5
We present a deep-learning framework that performs 4.6x spatial super-resolution from WISE W1 (3.4 micron) toward Spitzer IRAC Ch1 (3.6 micron), and characterize its behavior on th…
Diffusion-based Galaxy Simulations for the Roman High Latitude Survey
Diana Scognamiglio, Jake H. Lee, Eric Huff +2
Future weak lensing analyses with the Nancy Grace Roman Space Telescope will require highly realistic image simulations to control shear systematics at unprecedented precision. A k…
Learning to See Sharper: A Physics-Informed Artificial Intelligence Framework for Super-Resolving Galaxy Spectra
Aryana Haghjoo, Shoubaneh Hemmati, Bahram Mobasher +7
The information recoverable from galaxy spectra depends fundamentally on spectral resolution, yet assembling large samples at high resolution remains observationally expensive. We…
Reducing the Dimensions of AGN Lightcurve Manifolds
Shoubaneh Hemmati, Jessica Krick, Daniel Stern +10
The Active Galactic Nuclei (AGN) glossary is vast and complex. Depending on selection method, observing wavelength, and brightness, AGNs are assigned distinct labels, yet the relat…
Mapping the Galaxy Color-Star Formation Rate Relation with Manifold Learning and Infrared Image Stacking
Yu-Heng Lin, Daniel Masters, Andreas L. Faisst +7
Modern surveys present us with billions of faint galaxies for which we only have broadband images in 6-8 optical-to-near-infrared (NIR) filters. Galaxy star formation rates (…
Selection of Dwarf Galaxies Hosting AGNs: A Measure of Bias and Contamination using Unsupervised Machine Learning Techniques
Sogol Sanjaripour, Archana Aravindan, Gabriela Canalizo +4
Identifying AGNs in dwarf galaxies is critical for understanding black hole formation but remains challenging due to their low luminosities, low metallicities, and star formation-d…
Denoising Diffusion Probabilistic Model for realistic and fast generated \textit{Euclid}-like data for weak lensing analysis
Diana Scognamiglio, Jake H. Lee, Eric Huff +2
Understanding and mitigating measurement systematics in weak lensing (WL) analysis requires large datasets of realistic galaxies with diverse morphologies and colors. Missions like…
Searching for Quiescent Galaxies over in JWST Surveys Using Manifold Learning
Alexander de la Vega, Mitchell D. Babcock, Bahram Mobasher +5
Quiescent galaxies over are rare and puzzling. They formed and quenched within two billion years and simulations routinely struggle to predict their observed abundances. De…
UVCANDELS: Catalogs of photometric redshifts and galaxy physical properties
Vihang Mehta, Marc Rafelski, Ben Sunnquist +76
The UltraViolet imaging of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey Fields (UVCANDELS) program provides deep HST F275W and F435W imaging over four CANDELS…
Dynamics of Star-forming Galaxies in a Massive Structure at \lowercase{} 2.2: Evidence for Galaxy Harassment in high- Environments
Behnam Darvish, Nima Chartab, Zahra Sattari +5
We spectroscopically confirm a new protocluster in the COSMOS field at =2.24430 with Keck/MOSFIRE, dubbed CC2.2B, which is in the immediate vicinity of CC2.2A protocluster, orig…
Application of Manifold Learning to Selection of Different Galaxy Populations and Scaling Relation Analysis
Sogol Sanjaripour, Shoubaneh Hemmati, Bahram Mobasher +8
The growing volume of data produced by large astronomical surveys necessitates the development of efficient analysis techniques capable of effectively managing high-dimensional dat…
Euclid. III. The NISP Instrument
Euclid Collaboration, K. Jahnke, W. Gillard +434
The Near-Infrared Spectrometer and Photometer (NISP) on board the Euclid satellite provides multiband photometry and R>=450 slitless grism spectroscopy in the 950-2020nm wavelength…
Euclid. I. Overview of the Euclid mission
Euclid Collaboration, Y. Mellier, Abdurro'uf +1134
The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Eucl…
The Universe SPHEREx Will See: Empirically Based Galaxy Simulations and Redshift Predictions
Richard M. Feder, Daniel C. Masters, Bomee Lee +6
We simulate galaxy properties and redshift estimation for SPHEREx, the next NASA Medium Class Explorer. To make robust models of the galaxy population and test spectro-photometric…
Large Scale Structures in COSMOS2020: Evolution of Star Formation Activity in Different Environments at 0.4 < z < 4
Sina Taamoli, Bahram Mobasher, Nima Chartab +15
To study the role of environment in galaxy evolution, we reconstruct the underlying density field of galaxies based on COSMOS2020 (The Farmer catalog) and provide the density catal…
The UV luminosity function at 0.6 < z < 1 from UVCANDELS
Lei Sun, Xin Wang, Harry I. Teplitz +75
UVCANDELS is a HST Cycle-26 Treasury Program awarded 164 orbits of primary ultraviolet (UV) F275W imaging and coordinated parallel optical F435W imaging in four CANDELS fields: GOO…
The Lyman Continuum Escape Fraction of Star-forming Galaxies at from UVCANDELS
Xin Wang, Harry I. Teplitz, Brent M. Smith +74
The UltraViolet Imaging of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey Fields (UVCANDELS) survey is a Hubble Space Telescope (HST) Cycle-26 Treasury Program,…
The Art of Measuring Physical Parameters in Galaxies: A Critical Assessment of Spectral Energy Distribution Fitting Techniques
Camilla Pacifici, Kartheik G. Iyer, Bahram Mobasher +52
The study of galaxy evolution hinges on our ability to interpret multi-wavelength galaxy observations in terms of their physical properties. To do this, we rely on spectral energy…
Deblending Galaxies with Generative Adversarial Networks
Shoubaneh Hemmati, Eric Huff, Hooshang Nayyeri +6
Deep generative models including generative adversarial networks (GANs) are powerful unsupervised tools in learning the distributions of data sets. Building a simple GAN architectu…
COSMOS-Web: An Overview of the JWST Cosmic Origins Survey
Caitlin M. Casey, Jeyhan S. Kartaltepe, Nicole E. Drakos +82
We present the survey design, implementation, and outlook for COSMOS-Web, a 255 hour treasury program conducted by the James Webb Space Telescope in its first cycle of observations…
A Machine Learning Approach to Predict Missing Flux Densities in Multi-band Galaxy Surveys
Nima Chartab, Bahram Mobasher, Asantha Cooray +21
We present a new method based on information theory to find the optimal number of bands required to measure the physical properties of galaxies with a desired accuracy. As a proof…
COSMOS2020: Manifold Learning to Estimate Physical Parameters in Large Galaxy Surveys
I. Davidzon, K. Jegatheesan, O. Ilbert +16
We present a novel method to estimate galaxy physical properties from spectral energy distributions (SEDs), alternate to template fitting techniques and based on self-organizing ma…
Categorizing models using Self-Organizing Maps: an application to modified gravity theories probed by cosmic shear
Agnès Ferté, Shoubaneh Hemmati, Daniel Masters +4
We propose to use Self-Organizing Maps (SOM) to map the impact of physical models onto observables. Using this approach, we are be able to determine how theories relate to each oth…
Joint Survey Processing of Euclid, Rubin and Roman: Final Report
R. Chary, G. Helou, G. Brammer +22
The Euclid, Rubin/LSST and Roman (WFIRST) projects will undertake flagship optical/near-infrared surveys in the next decade. By mapping thousands of square degrees of sky and cover…