Author

K. Garikipati

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Preprint Aug 2026

Resource Analysis for Quantum Simulation of Spatially Varying Transport-Reaction Equations

Spatially varying coefficients are the primary source of circuit complexity in quantum simulation of linear advection-diffusion-reaction equations. This work presents a resource analysis of single-step quantum propagators constructed using sparse FABLE block encodings, Quantum Singular Value Transformation, and linear-...

Benjamin A. Jasperson, K. Garikipati, Siddhartha Srivastava · 0 citations

#machine learning Preprint Sep 2026

Beyond Compression: Training Latent Representations for Stable Long-Horizon Rollout in Neural Surrogate Solvers

The results show that neural compression should be designed not merely to reduce dimensionality, but to restructure the solution space for stable dynamical evolution, a key requirement for reliable, efficient neural surrogates in scientific applications.

Andreas E. Robertson, Ashley Lenau, John D. Shimanek et al. · 0 citations

Jul 2026

Learning Population-Level Dynamics through a Latent Fokker-Planck Model and Discrepancy Transport Maps

This work presents a population-level inference framework that recovers latent stochastic dynamics directly from snapshot probability distributions by decomposing the observed evolution into an intrinsic latent stochastic process and a discrepancy transport map that captures geometric deformation between the latent and...

Cheng-Yang Huang, K. Garikipati · arXiv.org · 0 citations