{"ID":2923549,"CreatedAt":"2026-06-02T04:05:25.881865328Z","UpdatedAt":"2026-06-04T13:12:39.622923895Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2606.02455","arxiv_id":"2606.02455","title":"Speculative Sampling For Faster Molecular Dynamics","abstract":"Molecular dynamics (MD) is a key tool for simulating the dynamical behavior of atomic systems. However, MD is inherently serial, which makes it difficult to increase single-system throughput with concurrent compute. To address this, we introduce Langevin Speculative Dynamics (LSD), a distributed and model-agnostic speculative sampler for accelerating MD without adding relative error. Inspired by speculative methods in language and diffusion modeling, LSD uses a draft model to propose fast simulation steps and verifies them in parallel with a slower target model, applying a transport map from the draft to the target distribution. We extend speculative sampling to second-order Langevin dynamics, derive the achievable speedup as a function of physical parameters, show that LSD generalizes across different systems and draft-target combinations with a 3-9x speedup, and confirm theoretically and empirically that LSD samples trajectories from its target model distribution.","short_abstract":"Molecular dynamics (MD) is a key tool for simulating the dynamical behavior of atomic systems. However, MD is inherently serial, which makes it difficult to increase single-system throughput with concurrent compute. To address this, we introduce Langevin Speculative Dynamics (LSD), a distributed and model-agnostic spec...","url_abs":"https://arxiv.org/abs/2606.02455","url_pdf":"https://arxiv.org/pdf/2606.02455v1","authors":"[\"Arthur Kosmala\",\"Stephan Günnemann\",\"Meng Gao\",\"Brandon Wood\"]","published":"2026-06-01T16:25:31Z","proceeding":"cs.LG","tasks":"[\"cs.LG\",\"cond-mat.mtrl-sci\",\"physics.chem-ph\",\"physics.comp-ph\",\"stat.CO\"]","methods":"[\"Diffusion Model\"]","has_code":false}