Gravothermal Catastrophe in Resonant Self-interacting Dark Matter Models

Kavli Affiliate: Mark Vogelsberger | First 5 Authors: Vinh Tran, Daniel Gilman, Mark Vogelsberger, Xuejian Shen, Stephanie O’Neil | Summary: We investigate a self-interacting dark matter (SIDM) model featuring a velocity-dependent cross section with an order-of-magnitude resonant enhancement of the cross section at $sim 16,{rm km},{rm s}^{-1}$. To understand the implications for the structure of […]


Continue.. Gravothermal Catastrophe in Resonant Self-interacting Dark Matter Models

Gravothermal Catastrophe in Resonant Self-interacting Dark Matter Models

Kavli Affiliate: Mark Vogelsberger | First 5 Authors: Vinh Tran, Daniel Gilman, Mark Vogelsberger, Xuejian Shen, Stephanie O’Neil | Summary: We investigate a self-interacting dark matter (SIDM) model featuring a velocity-dependent cross section with an order-of-magnitude resonant enhancement of the cross section at $sim 16,{rm km},{rm s}^{-1}$. To understand the implications for the structure of […]


Continue.. Gravothermal Catastrophe in Resonant Self-interacting Dark Matter Models

Adversarial Attacks on Reinforcement Learning Agents for Command and Control

Kavli Affiliate: John Richardson | First 5 Authors: Ahaan Dabholkar, James Z. Hare, Mark Mittrick, John Richardson, Nicholas Waytowich | Summary: Given the recent impact of Deep Reinforcement Learning in training agents to win complex games like StarCraft and DoTA(Defense Of The Ancients) – there has been a surge in research for exploiting learning based […]


Continue.. Adversarial Attacks on Reinforcement Learning Agents for Command and Control

Adversarial Attacks on Reinforcement Learning Agents for Command and Control

Kavli Affiliate: John Richardson | First 5 Authors: Ahaan Dabholkar, James Z. Hare, Mark Mittrick, John Richardson, Nicholas Waytowich | Summary: Given the recent impact of Deep Reinforcement Learning in training agents to win complex games like StarCraft and DoTA(Defense Of The Ancients) – there has been a surge in research for exploiting learning based […]


Continue.. Adversarial Attacks on Reinforcement Learning Agents for Command and Control

Introducing the DREAMS Project: DaRk mattEr and Astrophysics with Machine learning and Simulations

Kavli Affiliate: Lina Necib | First 5 Authors: Jonah C. Rose, Paul Torrey, Francisco Villaescusa-Navarro, Mariangela Lisanti, Tri Nguyen | Summary: We introduce the DREAMS project, an innovative approach to understanding the astrophysical implications of alternative dark matter models and their effects on galaxy formation and evolution. The DREAMS project will ultimately comprise thousands of […]


Continue.. Introducing the DREAMS Project: DaRk mattEr and Astrophysics with Machine learning and Simulations

NICER Discovery of the Accreting Millisecond X-ray Pulsar SRGA J144459.2-604207

Kavli Affiliate: Deepto Chakrabarty | First 5 Authors: Mason Ng, Paul S. Ray, Andrea Sanna, Tod E. Strohmayer, Alessandro Papitto | Summary: We present the discovery, with the Neutron Star Interior Composition Explorer (NICER), of the 447.9 Hz accreting millisecond X-ray pulsar (AMXP) SRGA J144459.2-604207, which underwent a four-week long outburst starting on 2024 February […]


Continue.. NICER Discovery of the Accreting Millisecond X-ray Pulsar SRGA J144459.2-604207

NICER Discovery that SRGA J144459.2-604207 is an Accreting Millisecond X-ray Pulsar

Kavli Affiliate: Deepto Chakrabarty | First 5 Authors: Mason Ng, Paul S. Ray, Andrea Sanna, Tod E. Strohmayer, Alessandro Papitto | Summary: We present the discovery, with the Neutron Star Interior Composition Explorer (NICER), that SRGA J144459.2-604207 is a 447.9 Hz accreting millisecond X-ray pulsar (AMXP), which underwent a four-week long outburst starting on 2024 […]


Continue.. NICER Discovery that SRGA J144459.2-604207 is an Accreting Millisecond X-ray Pulsar

KAN: Kolmogorov-Arnold Networks

Kavli Affiliate: Max Tegmark | First 5 Authors: Ziming Liu, Yixuan Wang, Sachin Vaidya, Fabian Ruehle, James Halverson | Summary: Inspired by the Kolmogorov-Arnold representation theorem, we propose Kolmogorov-Arnold Networks (KANs) as promising alternatives to Multi-Layer Perceptrons (MLPs). While MLPs have fixed activation functions on nodes ("neurons"), KANs have learnable activation functions on edges ("weights"). […]


Continue.. KAN: Kolmogorov-Arnold Networks

KAN: Kolmogorov-Arnold Networks

Kavli Affiliate: Max Tegmark | First 5 Authors: Ziming Liu, Yixuan Wang, Sachin Vaidya, Fabian Ruehle, James Halverson | Summary: Inspired by the Kolmogorov-Arnold representation theorem, we propose Kolmogorov-Arnold Networks (KANs) as promising alternatives to Multi-Layer Perceptrons (MLPs). While MLPs have fixed activation functions on nodes ("neurons"), KANs have learnable activation functions on edges ("weights"). […]


Continue.. KAN: Kolmogorov-Arnold Networks

KAN: Kolmogorov-Arnold Networks

Kavli Affiliate: Max Tegmark | First 5 Authors: Ziming Liu, Yixuan Wang, Sachin Vaidya, Fabian Ruehle, James Halverson | Summary: Inspired by the Kolmogorov-Arnold representation theorem, we propose Kolmogorov-Arnold Networks (KANs) as promising alternatives to Multi-Layer Perceptrons (MLPs). While MLPs have fixed activation functions on nodes ("neurons"), KANs have learnable activation functions on edges ("weights"). […]


Continue.. KAN: Kolmogorov-Arnold Networks