PPO reinforcement learning accelerates identification of gravitational wave signals from supercooled phase transitions in a minimal dark U(1)_x sector compared to Monte Carlo sampling.
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hep-ph 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
DarkAgents is an LLM-powered multi-agent framework for model building, pipeline computation, and assumption auditing in astroparticle physics, demonstrated on first-order phase transitions fitting NANOGrav gravitational wave data.
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Supercool with PPO: Exploring Supercooled Phase Transitions via Reinforcement Learning
PPO reinforcement learning accelerates identification of gravitational wave signals from supercooled phase transitions in a minimal dark U(1)_x sector compared to Monte Carlo sampling.
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DarkAgents
DarkAgents is an LLM-powered multi-agent framework for model building, pipeline computation, and assumption auditing in astroparticle physics, demonstrated on first-order phase transitions fitting NANOGrav gravitational wave data.