{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/random-geometry-and-the-kardar-parisi-zhang","title":"Random geometry and the Kardar-Parisi-Zhang universality class","arxiv_id":"1407.0209","date":"2014-07-01","proceeding":null,"authors":["Silvia N. Santalla","Javier Rodriguez-Laguna","Tom LaGatta","Rodolfo Cuerno"],"abstract":"We consider a model of a quenched disordered geometry in which a random metric is defined on ${\\mathbb R}^2$, which is flat on average and presents short-range correlations. We focus on the statistical properties of balls and geodesics, i.e., circles and straight lines. We show numerically that the roughness of a ball of radius $R$ scales as $R^\\chi$, with a fluctuation exponent $\\chi \\simeq 1/3$, while the lateral spread of the minimizing geodesic between two points at a distance $L$ grows as $L^\\xi$, with wandering exponent value $\\xi\\simeq 2/3$. Results on related first-passage percolation (FPP) problems lead us to postulate that the statistics of balls in these random metrics belong to the Kardar-Parisi-Zhang (KPZ) universality class of surface kinetic roughening, with $\\xi$ and $\\chi$ relating to critical exponents characterizing a corresponding interface growth process. Moreover, we check that the one-point and two-point correlators converge to the behavior expected for the Airy-2 process characterized by the Tracy-Widom (TW) probability distribution function of the largest eigenvalue of large random matrices in the Gaussian unitary ensemble (GUE). Nevertheless extreme-value statistics of ball coordinates are given by the TW distribution associated with random matrices in the Gaussian orthogonal ensemble. Furthermore, we also find TW-GUE statistics with good accuracy in arrival times.","url_abs":"https://arxiv.org/abs/1407.0209v3","url_pdf":"https://arxiv.org/pdf/1407.0209v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"random-geometry-and-the-kardar-parisi-zhang","repo_url":"https://github.com/jvrlag/riemann","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}