Calibration and Performance of the REgolith X-Ray Imaging Spectrometer (REXIS) Aboard NASA’s OSIRIS-REx Mission to Bennu

Kavli Affiliate: Rebecca Masterson | First 5 Authors: Jaesub Hong, Richard P. Binzel, Branden Allen, David Guevel, Jonathan Grindlay | Summary: The REgolith X-ray Imaging Spectrometer (REXIS) instrument on board NASA’s OSIRIS-REx mission to the asteroid Bennu is a Class-D student collaboration experiment designed to detect fluoresced X-rays from the asteroid’s surface to measure elemental […]


Continue.. Calibration and Performance of the REgolith X-Ray Imaging Spectrometer (REXIS) Aboard NASA’s OSIRIS-REx Mission to Bennu

Calibration and Performance of the REgolith X-Ray Imaging Spectrometer (REXIS) Aboard NASA’s OSIRIS-REx Mission to Bennu

Kavli Affiliate: Rebecca Masterson | First 5 Authors: Jaesub Hong, Richard P. Binzel, Branden Allen, David Guevel, Jonathan Grindlay | Summary: The REgolith X-ray Imaging Spectrometer (REXIS) instrument on board NASA’s OSIRIS-REx mission to the asteroid Bennu is a Class-D student collaboration experiment designed to detect fluoresced X-rays from the asteroid’s surface to measure elemental […]


Continue.. Calibration and Performance of the REgolith X-Ray Imaging Spectrometer (REXIS) Aboard NASA’s OSIRIS-REx Mission to Bennu

Charge order and superconductivity in a minimal two-band model for infinite-layer nickelates

Kavli Affiliate: Cheng Peng | First 5 Authors: Cheng Peng, Hong-Chen Jiang, Brian Moritz, Thomas P. Devereaux, Chunjing Jia | Summary: The recent discovery of superconductivity in infinite-layer nickelates has drawn considerable attention; however, a consensus on the fundamental building blocks and common ingredients necessary to understand and describe their ground states and emergent properties […]


Continue.. Charge order and superconductivity in a minimal two-band model for infinite-layer nickelates

Self-Supervised Learning by Estimating Twin Class Distributions

Kavli Affiliate: Feng Wang | First 5 Authors: Feng Wang, Tao Kong, Rufeng Zhang, Huaping Liu, Hang Li | Summary: We present TWIST, a simple and theoretically explainable self-supervised representation learning method by classifying large-scale unlabeled datasets in an end-to-end way. We employ a siamese network terminated by a softmax operation to produce twin class […]


Continue.. Self-Supervised Learning by Estimating Twin Class Distributions

A disturbing FABLE of mergers, feedback, turbulence, and mass biases in simulated galaxy clusters

Kavli Affiliate: Debora Sijacki | First 5 Authors: Jake S. Bennett, Debora Sijacki, , , | Summary: The use of galaxy clusters as cosmological probes often relies on understanding the properties and evolution of the intracluster medium (ICM). However, the ICM is a complex plasma, regularly stirred by mergers and feedback, with non-negligible bulk and […]


Continue.. A disturbing FABLE of mergers, feedback, turbulence, and mass biases in simulated galaxy clusters

A disturbing FABLE of mergers, feedback and mass biases

Kavli Affiliate: Debora Sijacki | First 5 Authors: Jake S Bennett, Debora Sijacki, , , | Summary: The use of galaxy clusters as cosmological probes often relies on understanding the properties and evolution of the intracluster medium (ICM). However, the ICM is a complex plasma, regularly stirred by mergers and feedback, with non-negligible bulk and […]


Continue.. A disturbing FABLE of mergers, feedback and mass biases

Finding Local Minimax Points via (Stochastic) Cubic-Regularized GDA: Global Convergence and Complexity

Kavli Affiliate: Yi Zhou | First 5 Authors: Ziyi Chen, Qunwei Li, Yi Zhou, , | Summary: Standard gradient descent-ascent (GDA)-type algorithms can only find stationary points in nonconvex minimax optimization, which are far more sub-optimal than local minimax points. In this work, we develop GDA-type algorithms that globally converge to local minimax points in […]


Continue.. Finding Local Minimax Points via (Stochastic) Cubic-Regularized GDA: Global Convergence and Complexity