physics.soc-ph · 2026-07-23 · No. 62
Physics and Society, 2026-07-23.
2 new papers in physics.soc-ph. Titles, authors,
abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →
01 — The papers
2 entries-
01
When Shippers Become Algorithms: Candidate Exposure, Information Design, and the Concentration of LLM-Mediated Freight Markets
Takahiro Ezaki, Naoto Imura, Katsuhiro Nishinari
physics.soc-ph · cs.AI · cs.CY
Shippers are beginning to delegate carrier selection to large language model (LLM) agents. We ask what such delegation does to a freight matching market, and which platform design choices contain it. We carried out agent-based simulations in which fifty shipper agents, built on commercial LLMs from OpenAI (GPT), Anthropic (Claude), and Google (Gemini), procure truckload capacity for thirty days. The market implements the rules of digital...
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02
Tensor Network Machine Learning for Wildfire Susceptibility Mapping: from Grokking Dynamics to Quantum Mixedness of Class Representations
Domenico Pomarico, Alessandra Costantino, Gabriel Ramirez Sanchez, Loredana Bellantuono, Davide D' Alò, Mario Elia,...
physics.soc-ph · cs.LG · physics.data-an
A quantum-inspired tensor network framework for wildfire susceptibility classification in the Gargano region is introduced, leveraging AlphaEarth embeddings and Matrix Product State models. The approach combines scalable geospatial representations with an interpretable quantum mask, enabling both binary and multiclass classification of wildfire susceptibility. Beyond predictive performance, the study reveals a pronounced grokking transition...
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