{"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/cnn-based-vortex-detection-in-atomic-2d-bose","title":"CNN-Based Vortex Detection in Atomic 2D Bose Gases in the Presence of a Phononic Background","arxiv_id":"2410.13829","date":"2024-10-17","proceeding":null,"authors":["Magnus Sesodia","Shinichi Sunami","En Chang","Erik Rydow","Christopher J. Foot","Abel Beregi"],"abstract":"Quantum vortices play a crucial role in both equilibrium and dynamical phenomena in two-dimensional (2D) superfluid systems. Experimental detection of these excitations in 2D ultracold atomic gases typically involves examining density depletions in absorption images, however the presence of a significant phononic background renders the problem challenging, beyond the capability of simple algorithms or the human eye. Here, we utilize a convolutional neural network (CNN) to detect vortices in the presence of strong long- and intermediate-length scale density modulations in finite-temperature 2D Bose gases. We train the model on datasets obtained from ab initio Monte Carlo simulations using the classical-field method for density and phase fluctuations, and Gross-Pitaevskii simulation of realistic expansion dynamics. We use the model to analyze experimental images and benchmark its performance by comparing the results to the matter-wave interferometric detection of vortices, confirming the observed scaling of vortex density across the Berezinskii-Kosterlitz-Thouless (BKT) critical point. The combination of a relevant simulation pipeline with machine-learning methods is a key development towards the comprehensive understanding of complex vortex-phonon dynamics in out-of-equilibrium 2D quantum systems.","url_abs":"https://arxiv.org/abs/2410.13829v2","url_pdf":"https://arxiv.org/pdf/2410.13829v2.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":"cnn-based-vortex-detection-in-atomic-2d-bose","repo_url":"https://github.com/magnus-sesodia/2d_vortex_detection","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}