condensed matter physics
PulseAugur coverage of condensed matter physics — every cluster mentioning condensed matter physics across labs, papers, and developer communities, ranked by signal.
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New framework integrates X-ray and neutron scattering data for materials science
Researchers have developed a new modular framework for analyzing data from multiple scientific measurements, particularly X-ray and neutron scattering experiments. This framework, based on prior-amortized flow matching,…
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New neural model forecasts granular slip, but history and geometry pose limits
Researchers have developed a compact neural network model to forecast granular slip in two-dimensional frictional disks. The model analyzes stress, pressure, coordination, non-affine motion, and force-network observable…
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New ANCHOR method enhances crystal structure discovery
Researchers have developed a new method called ANCHOR for de novo crystal generation, separating composition search from structure prediction. ANCHOR utilizes a GRPO composition policy trained with multi-objective rewar…
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New theory analyzes stability of memory patterns in neural networks
Researchers have developed a new theory to analyze the dynamical stability of stored patterns in attractor neural networks, which are models of biological memory. This theory extends previous approaches by considering g…
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Dynamical phase selection controls compute scaling in looped transformers
Researchers have identified that the computational cost of looped transformers during inference is determined by their dynamical phase, which is influenced by initialization. Networks with identical architectures and ob…
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New physics model reveals universal law for entropy production rate
Researchers have developed a new method to quantify irreversibility in complex systems by analyzing directed walks. This approach reveals a universal square-root law governing the entropy production rate, independent of…
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New framework details thermodynamics of learning in finite devices
Researchers have introduced a new framework for understanding learning in finite devices, distinguishing between what a device has recorded and what will hold future value. This framework separates learning into four co…
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New research frames generative models via stochastic thermodynamics
A new paper explores the application of stochastic thermodynamics to SDE-based generative models, such as diffusion models and the Schrödinger bridge. The research introduces trajectory-level definitions for work, heat,…
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Paper reveals interpretability limits in linear regression models
A new paper published on arXiv explores the limitations of interpretability in multiple linear regression models, particularly when dealing with multicollinearity. The research theoretically analyzes how correlated inpu…