The most likely evolution of diffusing and vanishing particles: Schrodinger Bridges with unbalanced marginals
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Abstract (arXiv)
Stochastic flows of an advective-diffusive nature are ubiquitous in physical sciences. Of particular interest is the problem to reconcile observed marginal distributions with a given prior posed by E. Schrodinger in 1932/32 and known as the Schrodinger Bridge Problem (SBP). Due to its fundamental significance, interest in SBP has in recent years enticed a broad spectrum of disciplines. Yet, while the mathematics and applications of SBP have been developing at a considerable pace, accounting for marginals of unequal mass has received scant attention; the problem to interpolate between unbalanced marginals has been approached by introducing source/sink terms in an Adhoc manner. Nevertheless, losses are inherent in many physical processes and, thereby, models that account for lossy transport may also need to be reconciled with observed marginals following Schrodinger's dictum; that is, to adjust the probability of trajectories of particles, including those that do not make it to the terminal observation point, so that the updated law represents the most likely way that particles may have been transported, or vanished, at some intermediate point. Thus, the purpose of this work is to develop such a natural generalization of the SBP for stochastic evolution with losses, whereupon particles are "killed" according to a probabilistic law. Through a suitable embedding, we turn the problem into an SBP for stochastic processes that combine diffusive and jump characteristics. Then, following a large-deviations formalism, given a prior law that allows for losses, we ask for the most probable evolution of particles along with the most likely killing rate as the particles transition between the specified marginals. Our approach differs sharply from previous work involving a Feynman-Kac multiplicative reweighing of the reference measure: The latter, as we argue, is far from Schrodinger's quest.
Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Aug 2021.
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Citing papers per year: 2023: 2; 2024: 2; 2025: 7; 2026: 3.
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- 2025Modeling Cell Dynamics and Interactions with Unbalanced Mean Field Schr"odinger Bridgecited by 12
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- 2026Globally Solving Unbalanced Optimal Transport and Density Control for Gaussian Distributionscited by 1
- 2025Multi-Marginal Schr"odinger Bridge Matchingcited by 0
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- 2026Schr"odinger Bridges over Kinetic Swarming Models26 Aug 2026
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- 2025Learning of Population Dynamics: Inverse Optimization Meets JKO Scheme2 Jun 2025
- 2025Variational Regularized Unbalanced Optimal Transport: Single Network, Least Action17 May 2025
- 2025Modeling Cell Dynamics and Interactions with Unbalanced Mean Field Schr"odinger Bridge16 May 2025
- 2025On the Hopf-Cole Transform for Control-affine Schr"odinger Bridge22 Mar 2025
- 2025Integrating Dynamical Systems Modeling with Spatiotemporal scRNA-seq Data Analysis14 Mar 2025
- 2024Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport1 Oct 2024
- 2024Solution of the Probabilistic Lambert Problem: Connections with Optimal Mass Transport, Schr"odinger Bridge and Reaction-Diffusion PDEs15 Jan 2024
2 more
- 2023Unbalanced Diffusion Schr"odinger Bridge15 Jun 2023
- 2023Deep Momentum Multi-Marginal Schr"odinger Bridge3 Mar 2023
- 2023Deep Momentum Multi-Marginal Schr"odinger Bridgecited by 40
- 2024Learning stochastic dynamics from snapshots through regularized unbalanced optimal transportcited by 30
- 2025Modeling Cell Dynamics and Interactions with Unbalanced Mean Field Schr"odinger Bridgecited by 12
- 2025Variational Regularized Unbalanced Optimal Transport: Single Network, Least Actioncited by 10
- 2023Unbalanced Diffusion Schr"odinger Bridgecited by 9
- 2025Integrating Dynamical Systems Modeling with Spatiotemporal scRNA-seq Data Analysiscited by 9
- 2025Learning of Population Dynamics: Inverse Optimization Meets JKO Schemecited by 6
- 2025On the Hopf-Cole Transform for Control-affine Schr"odinger Bridgecited by 5
- 2025Branched Schr"odinger Bridge Matchingcited by 4
- 2024Solution of the Probabilistic Lambert Problem: Connections with Optimal Mass Transport, Schr"odinger Bridge and Reaction-Diffusion PDEscited by 3
- 2026Globally Solving Unbalanced Optimal Transport and Density Control for Gaussian Distributionscited by 1
- 2025Multi-Marginal Schr"odinger Bridge Matchingcited by 0
12 most cited of 14 All 14 (JSON)
- 2026Schr"odinger Bridges over Kinetic Swarming Models26 Aug 2026
- 2026Trajectory Inference of Human Aging from Cross-Sectional DNA Methylation Data4 Jul 2026
- 2026Globally Solving Unbalanced Optimal Transport and Density Control for Gaussian Distributions5 May 2026
- 2025Multi-Marginal Schr"odinger Bridge Matching18 Oct 2025
- 2025Branched Schr"odinger Bridge Matching10 Jun 2025
- 2025Learning of Population Dynamics: Inverse Optimization Meets JKO Scheme2 Jun 2025
- 2025Variational Regularized Unbalanced Optimal Transport: Single Network, Least Action17 May 2025
- 2025Modeling Cell Dynamics and Interactions with Unbalanced Mean Field Schr"odinger Bridge16 May 2025
- 2025On the Hopf-Cole Transform for Control-affine Schr"odinger Bridge22 Mar 2025
- 2025Integrating Dynamical Systems Modeling with Spatiotemporal scRNA-seq Data Analysis14 Mar 2025
- 2024Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport1 Oct 2024
- 2024Solution of the Probabilistic Lambert Problem: Connections with Optimal Mass Transport, Schr"odinger Bridge and Reaction-Diffusion PDEs15 Jan 2024
12 newest of 14 All 14 (JSON)