144 citations · 1.4k across the 64 of their papers we have counts for
21 papers · 1 filter
An AI super-resolution field emulator for cosmological hydrodynamics: the Lyman-α forest
Fatemeh Hafezianzadeh, Xiaowen Zhang, Yueying Ni +4
We extend our super-resolution and emulation framework for cosmological dark matter simulations to include hydrodynamics. We present a two-stage deep learning model to emulate high…
The Properties of Little Red Dot Galaxies in the ASTRID Simulation
Patrick LaChance, Rupert A. C. Croft, Tiziana Di Matteo +5
We present simulated counterparts of the ``Little Red Dot'' (LRD) galaxies observed with JWST, using the large cosmological hydrodynamic simulation, ASTRID. We create mock observat…
Large-scale surveys of the quasar proximity effect
Rupert A. C. Croft, Patrick Shaw, Ann-Marsha Alexis +6
The UV radiation from high redshift quasars causes a local deficit in the neutral hydrogen absorption (Lyman-alpha forest) in their spectra, known as the proximity effect. Measurem…
Large-scale dual AGN in large-scale cosmological hydrodynamical simulations
Clara Puerto-Sánchez, Melanie Habouzit, Marta Volonteri +10
Detecting dual active galactic nuclei (DAGN) in observations and understanding theoretically which massive black holes (MBHs) compose them and in which galactic and large-scale env…
AI-assisted super-resolution cosmological simulations IV: An emulator for deterministic realizations
Xiaowen Zhang, Patrick Lachance, Ankita Dasgupta +5
Super-resolution (SR) models in cosmological simulations use deep learning (DL) to rapidly enhance low-resolution (LR) runs with statistically correct fine details. These models pr…
Modeling Quasar Proximity Zones in a Realistic Cosmological Environment with a Self-consistent Light Curve
Yihao Zhou, Huanqing Chen, Tiziana Di Matteo +3
We study quasar proximity zones in a simulation that includes a self-consistent quasar formation model and realistic IGM environments. The quasar host halo is $10^{13}\ M_{\mathrm{…
Efficient Reionization in a Large Hydrodynamic Galaxy Formation Simulation
James E. Davies, Simeon Bird, Simon Mutch +5
Accuracy in the topology and statistics of a simulated Epoch of Reionization (EoR) are vital to draw connections between observations and physical processes. While full radiative t…
PRIYA: A New Suite of Lyman-alpha Forest Simulations for Cosmology
Simeon Bird, Martin Fernandez, Ming-Feng Ho +6
We present the PRIYA suite of cosmological simulations, based on the code and hydrodynamic model of the ASTRID simulation, and designed for cosmological analyses of the Lyman- f…
AI-assisted super-resolution cosmological simulations III: Time evolution
Xiaowen Zhang, Patrick Lachance, Yueying Ni +5
In this work, we extend our recently developed super-resolution (SR) model for cosmological simulations to produce fully time consistent evolving representations of the particle ph…
Cosmology with one galaxy? -- The ASTRID model and robustness
Nicolas Echeverri, Francisco Villaescusa-Navarro, Chaitanya Chawak +7
Recent work has pointed out the potential existence of a tight relation between the cosmological parameter , at fixed , and the properties of individual galax…
The CAMELS project: Expanding the galaxy formation model space with new ASTRID and 28-parameter TNG and SIMBA suites
Yueying Ni, Shy Genel, Daniel Anglés-Alcázar +12
We present CAMELS-ASTRID, the third suite of hydrodynamical simulations in the Cosmology and Astrophysics with MachinE Learning (CAMELS) project, along with new simulation sets tha…
Boosting Line Intensity Map Signal-to-Noise with the Ly- Forest Cross-Correlation
Mahdi Qezlou, Simeon Bird, Adam Lidz +6
We forecast the prospects for cross-correlating future line intensity mapping (LIM) surveys with the current and future Ly- forest data. We use large cosmological hydrodynamic s…
A universal equation to predict from halo and galaxy catalogues
Helen Shao, Natalí S. M de Santi, Francisco Villaescusa-Navarro +13
We discover analytic equations that can infer the value of from the positions and velocity moduli of halo and galaxy catalogues. The equations are derived by combining…
Robust Field-level Likelihood-free Inference with Galaxies
Natalí S. M. de Santi, Helen Shao, Francisco Villaescusa-Navarro +12
We train graph neural networks to perform field-level likelihood-free inference using galaxy catalogs from state-of-the-art hydrodynamic simulations of the CAMELS project. Our mode…
Inferring the impact of feedback on the matter distribution using the Sunyaev Zel'dovich effect: Insights from CAMELS simulations and ACT+DES data
Shivam Pandey, Kai Lehman, Eric J. Baxter +6
Feedback from active galactic nuclei and stellar processes changes the matter distribution on small scales, leading to significant systematic uncertainty in weak lensing constraint…
Super-resolution simulation of the Fuzzy Dark Matter cosmological model
Meris Sipp, Patrick LaChance, Rupert Croft +2
AI super-resolution, combining deep learning and N-body simulations has been shown to successfully reproduce the large scale structure and halo abundances in the Lambda Cold Dark M…
Robust field-level inference with dark matter halos
Helen Shao, Francisco Villaescusa-Navarro, Pablo Villanueva-Domingo +13
We train graph neural networks on halo catalogues from Gadget N-body simulations to perform field-level likelihood-free inference of cosmological parameters. The catalogues contain…
The CAMELS project: public data release
Francisco Villaescusa-Navarro, Shy Genel, Daniel Anglés-Alcázar +44
The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynami…
AI-assisted super-resolution cosmological simulations II: Halo substructures, velocities and higher order statistics
Yueying Ni, Yin Li, Patrick Lachance +4
In this work, we expand and test the capabilities of our recently developed super-resolution (SR) model to generate high-resolution (HR) realizations of the full phase-space matter…
AI-assisted super-resolution cosmological simulations
Yin Li, Yueying Ni, Rupert A. C. Croft +3
Cosmological simulations of galaxy formation are limited by finite computational resources. We draw from the ongoing rapid advances in Artificial Intelligence (specifically Deep Le…
Predictions for the Abundance of High-redshift Galaxies in a Fuzzy Dark Matter Universe
Yueying Ni, Mei-Yu Wang, Yu Feng +1
During the last decades, rapid progress has been made in measurements of the rest-frame ultraviolet (UV) luminosity function (LF) for high-redshift galaxies (). The faint…