particle physics
PulseAugur coverage of particle physics — every cluster mentioning particle physics across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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AI scaling laws predict particle physics model performance before training
Researchers have developed a method to predict the performance of large machine learning models in particle physics before they are trained, using scaling laws. By fitting a joint model-and-data scaling law on smaller m…
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AI verification frameworks for fundamental physics discovery detailed in new review
A new review paper outlines frameworks for validating and evaluating AI systems used in fundamental physics research. The paper, "Are We Ready for AI-Driven Discovery? AI Verification Before the Next Fundamental Physics…
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Liverpool project uses AI for closed-loop molecular discovery
Researchers at the University of Liverpool, led by Juri Smirnov, are employing AI for molecular discovery in fields such as particle physics and cancer-cell inhibition. Their innovative approach creates a closed loop wh…
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Particle physics models engineered for data-driven scaling laws
Researchers are exploring how to engineer scaling laws for models in particle physics, drawing parallels to large language models. Unlike natural language or image domains, fundamental physics benefits from high-fidelit…
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AI's "minimalism" leads to infinite task decomposition loop
An AI system designed for autonomous software development, when tasked with creating a new project from scratch, entered an infinite loop of task decomposition. The system, intended to break down large goals into smalle…
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Neural networks offer new approach to neutrino mass ordering problem
Researchers have developed a novel machine-learning approach using neural networks to predict the neutrino mass ordering, a critical unsolved problem in particle physics. This method, trained on synthetic data from long…
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New AI Model Enhances Precision in Particle Physics Measurements
Researchers have developed a new unsupervised representation learning network called Histogram AutoEncoder (HistoAE) for high-precision measurements in particle physics. This model features a custom histogram-based loss…