{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T23:57:02Z","timestamp":1790726222367,"version":"4.1.0"},"reference-count":49,"publisher":"Optica Publishing Group","issue":"20","license":[{"start":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T00:00:00Z","timestamp":1790640000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/doi.org\/10.1364\/OA_License_v2#VOR-OA"},{"start":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T00:00:00Z","timestamp":1790640000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/opg.optica.org\/policies\/opg-tdm-policy.json"}],"content-domain":{"domain":["opg.optica.org"],"crossmark-restriction":false},"short-container-title":["Opt. Express"],"published-print":{"date-parts":[[2026,10,5]]},"abstract":"<jats:p>In this paper, we investigate the robustness and classification performance of conventional Laguerre-Gaussian orbital angular momentum (LG-OAM) beams and space-time wave packet orbital angular momentum (ST-OAM) beams in a scattering medium. Experimental interference patterns are analyzed using the proposed VortexNet deep-learning framework, which performs OAM-state classification while quantitatively evaluating image quality through the peak signal-to-noise ratio (PSNR) and the structural similarity index measure (SSIM) under identical scattering conditions. Our results show that LG-OAM beams degrade significantly during propagation, with low image quality (PSNR \u2248 15\u2005dB, SSIM \u2248 0.26). In contrast. the ST-OAM beams preserve their structural integrity, achieving higher fidelity (PSNR \u2248 21-25\u2005dB, SSIM \u2248 0.75), corresponding to an improvement of \u223c6-10\u2005dB in PSNR. This enhanced physical robustness leads to improved learning performance, with VortexNet reaching \u223c99-100% accuracy for ST-OAM with fast convergence (\u223c5 epochs), compared with \u223c85% validation accuracy and \u223c25 epochs required for LG-OAM. The results demonstrate that ST-OAM significantly enhances resilience against scattering, improving both signal fidelity and deep-learning-based classification performance. These findings highlight ST-OAM as a promising platform for robust optical communication and imaging in complex dynamic environments.<\/jats:p>","DOI":"10.1364\/oe.610777","type":"journal-article","created":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T08:00:08Z","timestamp":1789632008000},"page":"37988","update-policy":"https:\/\/doi.org\/10.1364\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep learning-assisted recognition of space-time wave packets carrying orbital angular momentum in scattering media"],"prefix":"10.1364","volume":"34","author":[{"given":"Sarmad","family":"Maqsood","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00v4yb702","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Duvarakanath","family":"SenthilKumar","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00v4yb702","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5170-4839","authenticated-orcid":true,"given":"Mbaye","family":"Diouf","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00v4yb702","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"285","published-online":{"date-parts":[[2026,9,29]]},"reference":[{"key":"oe-34-20-37988-R1","doi-asserted-by":"publisher","first-page":"2309","DOI":"10.1364\/OL.32.002309","type":"journal-article","volume":"32","author":"Vellekoop","year":"2007","journal-title":"Opt. 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