Updated bounds on ultra-light dark matter from the tiniest galaxies

Kavli Affiliate: Andrey Kravtsov | First 5 Authors: Simon May, Simon May, , , | Summary: The particle mass of dark matter (DM) was previously constrained using kinematics of ultra-faint dwarf galaxies to $m > 3 times 10^-19,mathrmeV$. This constraint, which excludes the "fuzzy" range of ultra-light dark matter from comprising all of the DM, […]


Continue.. Updated bounds on ultra-light dark matter from the tiniest galaxies

The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS)

Kavli Affiliate: Salman Habib | First 5 Authors: Andrew Ferguson, Andrew Ferguson, , , | Summary: This community paper developed out of the NSF Workshop on the Future of Artificial Intelligence (AI) and the Mathematical and Physics Sciences (MPS), which was held in March 2025 with the goal of understanding how the MPS domains (Astronomy, […]


Continue.. The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS)

Chemodynamics of BoötesI with $S^5$: Revised Velocity Gradient, Dark Matter Density, and Galactic Chemical Evolution Constraints

Kavli Affiliate: Alexander P. Ji | First 5 Authors: Nathan R. Sandford, Nathan R. Sandford, , , | Summary: We combine new spectroscopic observations of the ultra faint dwarf galaxy (UFD) Bo"otes I (Boo I) from the Southern Stellar Stream Spectroscopic Survey ($S^5$) with $sim$15 years of archival spectroscopic data to create the largest sample […]


Continue.. Chemodynamics of BoötesI with $S^5$: Revised Velocity Gradient, Dark Matter Density, and Galactic Chemical Evolution Constraints

Constraints on Long-Range Forces in De Sitter Space

Kavli Affiliate: Austin Joyce | First 5 Authors: Daniel Baumann, Daniel Baumann, , , | Summary: The representation theory of de Sitter space admits partially massless (PM) particles, but whether such particles can participate in consistent interacting theories remains unclear. We investigate the consistency of theories containing PM fields, particularly when these fields are coupled […]


Continue.. Constraints on Long-Range Forces in De Sitter Space

Constraints on Long-Range Forces in De Sitter Space

Kavli Affiliate: Austin Joyce | First 5 Authors: Daniel Baumann, Daniel Baumann, , , | Summary: The representation theory of de Sitter space admits partially massless (PM) particles, but whether such particles can participate in consistent interacting theories remains unclear. We investigate the consistency of theories containing PM fields, particularly when these fields are coupled […]


Continue.. Constraints on Long-Range Forces in De Sitter Space

A Comparison of Full Spectral Fitting Codes for Measuring the Stellar Initial Mass Function and Other Stellar Population Properties in Elliptical Galaxies

Kavli Affiliate: Wendy L. Freedman | First 5 Authors: , , , , | Summary: We present a comparative test of four widely used full spectral fitting codes, with the aim of answering the question: how robust is the retrieval of the stellar initial mass function (IMF) and other stellar properties of galaxies? We used […]


Continue.. A Comparison of Full Spectral Fitting Codes for Measuring the Stellar Initial Mass Function and Other Stellar Population Properties in Elliptical Galaxies

CelloAI: Leveraging Large Language Models for HPC Software Development in High Energy Physics

Kavli Affiliate: Salman Habib | First 5 Authors: Mohammad Atif, Mohammad Atif, , , | Summary: Next-generation High Energy Physics (HEP) experiments will generate unprecedented data volumes, necessitating High Performance Computing (HPC) integration alongside traditional high-throughput computing. However, HPC adoption in HEP is hindered by the challenge of porting legacy software to heterogeneous architectures and […]


Continue.. CelloAI: Leveraging Large Language Models for HPC Software Development in High Energy Physics

Stabilization of Perturbed Loss Function: Differential Privacy without Gradient Noise

Kavli Affiliate: Salman Habib | First 5 Authors: Salman Habib, Salman Habib, , , | Summary: We propose SPOF (Stabilization of Perturbed Loss Function), a differentially private training mechanism intended for multi-user local differential privacy (LDP). SPOF perturbs a stabilized Taylor expanded polynomial approximation of a model’s training loss function, where each user’s data is […]


Continue.. Stabilization of Perturbed Loss Function: Differential Privacy without Gradient Noise