{"id":3761,"date":"2026-08-14T04:00:00","date_gmt":"2026-08-14T04:00:00","guid":{"rendered":"https:\/\/futurenews24.com\/index.php\/2026\/08\/14\/2608-09625\/"},"modified":"2026-08-15T03:59:11","modified_gmt":"2026-08-15T03:59:11","slug":"2608-09625","status":"publish","type":"post","link":"https:\/\/futurenews24.com\/index.php\/2026\/08\/14\/2608-09625\/","title":{"rendered":"[2608.09625] A Design House Examine of Density Matrix Parameterizations for Diffusion-Primarily based Quantum State Tomography"},"content":{"rendered":"<p><br \/>\n<\/p>\n<div id=\"content-inner\">\n<div id=\"abs\">\n<div class=\"dateline\">\n  [Submitted on 10 Aug 2026 (v1), last revised 13 Aug 2026 (this version, v2)]<\/div>\n<p>View a PDF of the paper titled A Design House Examine of Density Matrix Parameterizations for Diffusion-Primarily based Quantum State Tomography, by Shuangu Chang<\/p>\n<p>    View PDF<br \/>\n    HTML (experimental)<\/p>\n<blockquote class=\"abstract mathjax\"><p>\n            <span class=\"descriptor\">Summary:<\/span>Diffusion-based quantum state tomography (QST) has proven promising outcomes, however all present strategies implicitly undertake a single parameterization (usually Cholesky) with out systematic analysis. We current the primary design house research of density matrix parameterizations for diffusion QST, introducing a geometrical framework primarily based on the Jacobian Gram matrix $mathbf{J}^topmathbf{J}$. Our calibration of seven parameterizations at 2- and 3-qubit scales, validated by end-to-end coaching, reveals that emph{geometric conditioning alone doesn&#8217;t predict end-to-end efficiency}: at 3-qubit scale, Hermitian direct ($kappa = 2.0times$) performs worse than Cholesky ($kappa = 27times$) in any respect shot levels&#8212;a $13.5times$ isotropy benefit that interprets right into a constancy emph{drawback} of as much as $+0.51$. The two-qubit rating (Hermitian $&gt;$ Bloch) reverses at 3 qubits (Bloch 0.907 vs. Hermitian 0.394). We offer a geometrical clarification: unbounded parameterizations endure projection-induced info loss as a result of the PSD constraint {couples} diagonal and off-diagonal coordinates in methods the unconstrained mannequin can&#8217;t respect, whereas the Bloch illustration locations the maximally combined state on the middle of the legitimate area, minimizing projection loss.\n    <\/p><\/blockquote><\/div>\n<\/div>\n<div>\n<h2>Submission historical past<\/h2>\n<p> From: Shuangju Chang [view email]                  [v1]<br \/>\n        Mon, 10 Aug 2026 14:05:36 UTC (1,867 KB)<br \/>\n    [v2]<br \/>\n        Thu, 13 Aug 2026 08:48:25 UTC (1,632 KB)\n<\/p><\/div>\n<p><br \/>\n<br \/><a href=\"https:\/\/arxiv.org\/abs\/2608.09625\">Source link <\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>[Submitted on 10 Aug 2026 (v1), last revised 13 Aug 2026 (this version, v2)] View a PDF of the paper titled A Design House Examine of Density Matrix Parameterizations for Diffusion-Primarily based Quantum State Tomography, by Shuangu Chang View PDF HTML (experimental) Summary:Diffusion-based quantum state tomography (QST) has proven promising outcomes, however all present strategies [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":3763,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"fifu_image_url":"http:\/\/arxiv.org\/static\/browse\/0.3.4\/images\/arxiv-logo-fb.png","fifu_image_alt":"","jnews-multi-image_gallery":[],"jnews_single_post":[],"jnews_primary_category":[],"jnews_override_bookmark_settings":[],"jnews_social_meta":[],"jnews_override_counter":[],"footnotes":""},"categories":[9],"tags":[4101,824,4103,3503,4102,431,834,1402,713,4104],"class_list":["post-3761","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-quantum-computing","tag-density","tag-design","tag-diffusionbased","tag-matrix","tag-parameterizations","tag-quantum","tag-space","tag-state","tag-study","tag-tomography"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.7 - 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