arXiv:2509.25311v2 Announce Type: replace-cross
Abstract: We implement physics-informed-neural-networks (PINNs) to compute holographic entanglement entropy and entanglement wedge cross section. This technique allows us to compute these quantities for …
arXiv:2512.20177v2 Announce Type: replace
Abstract: Global gridded crop models (GGCMs) are crucial to project the impacts of climate change on agricultural productivity and assess associated risks for food security. Despite decades of development, sta…
arXiv:2505.11349v3 Announce Type: replace
Abstract: Recent time-series foundation models exhibit strong abilities to predict physical systems. These abilities include zero-shot forecasting, in which a model forecasts future states of a system given on…
arXiv:2603.20253v1 Announce Type: cross
Abstract: Evaluating LLM agents for scientific tasks has focused on token costs while ignoring tool-use costs like simulation time and experimental resources. As a result, metrics like pass@k become impractical …
arXiv:2602.18482v2 Announce Type: replace-cross
Abstract: Sampling equilibrium distributions is fundamental to statistical mechanics. While flow matching has emerged as scalable state-of-the-art paradigm for generative modeling, its potential for equi…
arXiv:2603.27646v1 Announce Type: new
Abstract: AI agents powered by large language models exhibit strong reasoning and problem-solving capabilities, enabling them to assist scientific research tasks such as formula derivation and code generation. How…
arXiv:2603.27886v1 Announce Type: cross
Abstract: Artificial intelligence (AI) and machine learning (ML) models in materials science are predominantly trained on ideal bulk crystals, limiting their transferability to real-world applications where surf…
arXiv:2602.21361v2 Announce Type: replace-cross
Abstract: Ptychographic imaging at synchrotron and XFEL sources requires dense overlapping scans, limiting throughput and increasing dose. Extending coherent diffractive imaging to overlap-free operation…
arXiv:2603.19562v3 Announce Type: replace
Abstract: Adversarial vulnerability in vision and hallucination in large language models are conventionally viewed as separate problems, each addressed with modality-specific patches. This study first reveals …
arXiv:2603.24638v1 Announce Type: cross
Abstract: The requirement of generating predictions that exactly fulfill the fundamental symmetry of the corresponding physical quantities has profoundly shaped the development of machine-learning models for phy…