187 citations · 192 across the 12 of their papers we have counts for
12 papers
Accurate modeling for 32pt analyses in Roman and Rubin: a study of model approximations
Junzhou Zhang, Chihway Chang, Jiachuan Xu +6
One of the pillars of modern cosmology is the use of galaxy imaging surveys to extract information from the large-scale structure. In recent surveys, this measurement is typically…
Raising the reionization optical depth with inflationary CMB features
Tanisha Jhaveri, Wayne Hu, Vivian Miranda
Within the highly successful CDM paradigm established with cosmic microwave background (CMB) anisotropy measurements, the optical depth through reionization is the most unce…
Towards the Two-Loop EFTofLSS in Galaxy Lensing Surveys
Evan Saraivanov, Henrique Rubira, Vivian Miranda +1
Extracting cosmological information from Stage IV weak lensing surveys requires non-linear modelling of the matter power spectrum that is accurate across a broad range of scales an…
Modeling Redshift Uncertainties in Roman Weak Lensing Cosmology
Diogo H. F. de Souza, Boyan Yin, Tim Eifler +7
Cosmological constraints using weak gravitational lensing measurements from the Roman Space Telescope will require a powerful method for modelling uncertainties in the galaxy redsh…
Fisher Forecasts for Cosmological Yields from pt Analysis of the Roman Space Telescope High Latitude Imaging Survey
Kaili Cao, David H. Weinberg, Vivian Miranda +5
The High Latitude Imaging Survey (HLIS) of NASA's Nancy Grace Roman Space Telescope will provide powerful tests of cosmological models through sensitive measurements of cosmic shea…
Constraining baryonic feedback and cosmology from DES Y3 and Planck PR4 62pt data. I. CDM models
Jiachuan Xu, Tim Eifler, Elisabeth Krause +3
We combine weak lensing, galaxy clustering, cosmic microwave background (CMB) lensing, and their cross-correlations (so-called 62pt) to constrain cosmology and baryonic fee…
Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys
Yijie Zhu, Evan Saraivanov, Joshua A. Kable +6
Machine learning can accelerate cosmological inferences that involve many sequential evaluations of computationally expensive data vectors. Previous works in this series have exami…
Cosmology from weak lensing, galaxy clustering, CMB lensing and tSZ: II. Optimizing Roman survey design for CMB cross-correlation science
Tim Eifler, Xiao Fang, Elisabeth Krause +8
We explore synergies between the Nancy Grace Roman Space Telescope High Latitude Wide Area Survey (HLWAS) and CMB experiments, specifically Simons Observatory (SO) and CMB-Stage4 (…
Attention-Based Neural Network Emulators for Multi-Probe Data Vectors Part II: Assessing Tension Metrics
Evan Saraivanov, Kunhao Zhong, Vivian Miranda +3
The next generation of cosmological surveys is expected to generate unprecedented high-quality data, consequently increasing the already substantial computational costs of Bayesian…
Machine Learning LSST 3x2pt analyses -- forecasting the impact of systematics on cosmological constraints using neural networks
Supranta S. Boruah, Tim Eifler, Vivian Miranda +6
Validating modeling choices through simulated analyses and quantifying the impact of different systematic effects will form a major computational bottleneck in the preparation for…
Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part I: Forecasting the Growth-Geometry split
Kunhao Zhong, Evan Saraivanov, James Caputi +4
We present a new class of machine-learning emulators that accurately model the cosmic shear, galaxy-galaxy lensing, and galaxy clustering real space correlation functions in the co…
Simulations of the WFIRST Supernova Survey and Forecasts of Cosmological Constraints
R. Hounsell, D. Scolnic, R. J. Foley +14
The Wide Field InfraRed Survey Telescope (WFIRST) was the highest ranked large space-based mission of the 2010 New Worlds, New Horizons decadal survey. It is now a NASA mission in…