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Normal Distribution of Crab Pulsar Glitch Activity from a Glitch Cluster Perspective
Pei-Xin Zhu, Xiao-Ping Zheng
https://arxiv.org/abs/2506.02925 https://…

Normal Distribution of Crab Pulsar Glitch Activity from a Glitch Cluster Perspective
As the most extensively and continuously monitored neutron star, the Crab pulsar serves as representative of the earliest evolutionary stage. Its unique and complex glitch phenomenology provides an unparalleled testing ground for theoretical models of neutron star interior dynamics. Within the self-organized criticality paradigm, Crab pulsar glitch sizes are modeled by a power-law distribution and waiting times by an exponential distribution. However, this framework is incompatible with neutron…

Learning to Explore: An In-Context Learning Approach for Pure Exploration
Alessio Russo, Ryan Welch, Aldo Pacchiano
https://arxiv.org/abs/2506.01876 https:…

Learning to Explore: An In-Context Learning Approach for Pure Exploration
In this work, we study the active sequential hypothesis testing problem, also known as pure exploration, where the goal is to actively control a data collection process to efficiently identify the correct hypothesis underlying a decision problem. While relevant across multiple domains, devising adaptive exploration strategies remains challenging, particularly due to difficulties in encoding appropriate inductive biases. Existing Reinforcement Learning (RL)-based methods often underperform when …

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