{"id":7080081,"date":"2026-10-08T12:39:30","date_gmt":"2026-10-08T12:39:30","guid":{"rendered":"https:\/\/fivemor.com\/?p=7080081"},"modified":"2026-10-08T12:39:30","modified_gmt":"2026-10-08T12:39:30","slug":"diffphd-a-unified-differentiable-solver-for-projective-heterogeneous-materials-in-elastodynamics-with-contact-rich-gpu-acceleration","status":"publish","type":"post","link":"https:\/\/fivemor.com\/?p=7080081","title":{"rendered":"DiffPhD: A Unified Differentiable Solver for Projective Heterogeneous Materials in Elastodynamics with Contact-Rich GPU-Acceleration"},"content":{"rendered":"<p> <br \/>\n<\/p>\n<div id=\"post-4625\">\n<p>\t\t\t\t\t<!-- .entry-meta --><\/p>\n<div class=\"entry-content\">\n<p class=\"wp-block-paragraph\">Shih-Yu Lai, Sung-Han Tien, Jui-I Huang, Yen-Chen Tseng, Yi-Ting Chiu, Siyuan Luo, Ziqiu Zeng, Fan Shi, Peter Yichen Chen, Tiantian Liu, Yu-Lun Liu, Bing-Yu Chen<\/p>\n<p class=\"wp-block-paragraph\">Differentiable simulation of soft bodies is a foundation for system identification, trajectory optimization, and Real2Sim transfer. Yet, existing methods such as the differentiable Projective Dynamics (DiffPD) struggle when faced with heterogeneous materials with extreme stiffness contrasts, hyperelasticity under large deformations, and contact-rich interactions, which are common scenarios in the real world. We present <strong>DiffPhD<\/strong>, a unified GPU-accelerated differentiable Projective Dynamics framework for heterogeneous materials that tackles these intertwined challenges simultaneously. Our key insight is a careful integration of: (i) stiffness-aware projective weights to embed heterogeneity into the global system; (ii) trust-region eigenvalue filtering lifted to the backward pass for stable hyperelastic gradients and a type-II Anderson Acceleration scheme with dual-gate convergence to stabilize forward iteration under large stiffness contrasts; and (iii) a unified GPU pipeline that reuses a single sparse factor across forward, backward, and contact computations, with stiffness-amplified Rayleigh damping folded into the same factor for heterogeneity-aware dissipation at zero recurring cost. DiffPhD delivers analytic adjoints\u2014machine-precision on the elastic path, bounded and quantified under contact\u2014with up to an order-of-magnitude speedup over prior differentiable solvers. Crucially, this speedup does not come at the cost of stability: DiffPhD remains convergent on stiffness contrasts up to 100\u00d7 where prior PD solvers degrade. This unlocks end-to-end gradient-based optimization on regimes previously bottlenecked by either solver fragility or per-iteration cost\u2014shell\u2013joint composite creatures, soft characters wielding stiff weapons, and soft-gripper robotic manipulation\u2014all handled within a single forward\u2013backward pass.<\/p>\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/chabu-tseng.github.io\/diffphd\/\">DiffPhD: A Unified Differentiable Solver for Projective Heterogeneous Materials in Elastodynamics with Contact-Rich GPU-Acceleration<\/a><\/p>\n<\/p><\/div>\n<p><!-- .entry-content --><\/p>\n<div class=\"entry-utility\">\n\t\t\t\t\t\t\tThis entry was posted in <a href=\"https:\/\/www.physicsbasedanimation.com\/category\/uncategorized\/\" rel=\"category tag\">Uncategorized<\/a>. Bookmark the <a href=\"https:\/\/www.physicsbasedanimation.com\/2026\/10\/07\/diffphd-a-unified-differentiable-solver-for-projective-heterogeneous-materials-in-elastodynamics-with-contact-rich-gpu-acceleration\/\" title=\"Permalink to DiffPhD: A Unified Differentiable Solver for Projective Heterogeneous Materials in Elastodynamics with Contact-Rich GPU-Acceleration\" rel=\"bookmark\">permalink<\/a>.\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n<p><!-- .entry-utility -->\n\t\t\t\t\t<\/div>\n\n","protected":false},"excerpt":{"rendered":"<p>Shih-Yu Lai, Sung-Han Tien, Jui-I Huang, Yen-Chen Tseng, Yi-Ting Chiu, Siyuan Luo, Ziqiu Zeng, Fan Shi, Peter Yichen Chen, Tiantian Liu, Yu-Lun Liu, Bing-Yu Chen Differentiable simulation of soft bodies is a foundation for system identification, trajectory optimization, and Real2Sim transfer. Yet, existing methods such as the differentiable Projective Dynamics (DiffPD) struggle when faced with [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":7070236,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[12035],"tags":[240720,93795,240717,43769,240721,240719,6947,240718,41364,26747],"dealstore":[],"offerexpiration":[],"class_list":["post-7080081","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-animation","tag-contactrich","tag-differentiable","tag-diffphd","tag-elastodynamics","tag-gpuacceleration","tag-heterogeneous","tag-materials","tag-projective","tag-solver","tag-unified"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>DiffPhD: A Unified Differentiable Solver for Projective Heterogeneous Materials in Elastodynamics with Contact-Rich GPU-Acceleration - Som2ny Network<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fivemor.com\/?p=7080081\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"DiffPhD: A Unified Differentiable Solver for Projective Heterogeneous Materials in Elastodynamics with Contact-Rich GPU-Acceleration - Som2ny Network\" \/>\n<meta property=\"og:description\" content=\"Shih-Yu Lai, Sung-Han Tien, Jui-I Huang, Yen-Chen Tseng, Yi-Ting Chiu, Siyuan Luo, Ziqiu Zeng, Fan Shi, Peter Yichen Chen, Tiantian Liu, Yu-Lun Liu, Bing-Yu Chen Differentiable simulation of soft bodies is a foundation for system identification, trajectory optimization, and Real2Sim transfer. 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