142 citations · 174 across the 8 of their papers we have counts for
8 papers
Solving Inverse Problems of Chaotic Systems with Bidirectional Conditional Flow Matching
Peiyan Hu, Jian Zhang, Jiashu Pan +6
Modeling chaotic systems is crucial yet challenging. Inverse problems in chaotic dynamics, namely inferring initial conditions from final states, remain largely unsolved because of…
Learning Intrinsic Alignments from Local Galaxy Environments
Matthew Craigie, Eric Huff, Yuan-Sen Ting +2
We present DELTA (Data-Empiric Learned Tidal Alignments), a deep learning model that isolates galaxy intrinsic alignments (IAs) from weak lensing distortions using only observation…
Learning Balanced Field Summaries of the Large-Scale Structure with the Neural Field Scattering Transform
Matthew Craigie, Yuan-Sen Ting, Rossana Ruggeri +1
We present a cosmology analysis of simulated weak lensing convergence maps using the Neural Field Scattering Transform (NFST) to constrain cosmological parameters. The NFST extends…
Inferring Cosmological Parameters on SDSS via Domain-Generalized Neural Networks and Lightcone Simulations
Jun-Young Lee, Ji-hoon Kim, Minyong Jung +6
We present a proof-of-concept simulation-based inference on and from the SDSS BOSS LOWZ NGC catalog using neural networks and domain generalization techniques w…
Unsupervised Searches for Cosmological Parity Violation: Improving Detection Power with the Neural Field Scattering Transform
Matthew Craigie, Peter L. Taylor, Yuan-Sen Ting +3
Recent studies using four-point correlations suggest a parity violation in the galaxy distribution, though the significance of these detections is sensitive to the choice of simula…
Deep Potential: Recovering the gravitational potential from a snapshot of phase space
Gregory M. Green, Yuan-Sen Ting, Harshil Kamdar
One of the major goals of the field of Milky Way dynamics is to recover the gravitational potential field. Mapping the potential would allow us to determine the spatial distributio…
Deep Potential: Recovering the gravitational potential from a snapshot of phase space
Gregory M. Green, Yuan-Sen Ting
One of the major goals of the field of Milky Way dynamics is to recover the gravitational potential field. Mapping the potential would allow us to determine the spatial distributio…
A new approach to observational cosmology using the scattering transform
Sihao Cheng, Yuan-Sen Ting, Brice Ménard +1
Parameter estimation with non-Gaussian stochastic fields is a common challenge in astrophysics and cosmology. In this paper, we advocate performing this task using the scattering t…