5 papers
Quantum-inspired space-time PDE solver and dynamic mode decomposition
Raghavendra Dheeraj Peddinti, Stefano Pisoni, Narsimha Rapaka +4
The curse of dimensionality is ubiquitous in both numerical and data-driven methods. This is particularly severe for space-time methods, which treat the combined space-time domain…
A quantum-inspired multi-level tensor-train monolithic space-time method for nonlinear PDEs
N. R. Rapaka, R. Peddinti, E. Tiunov +5
We propose a multilevel tensor-train (TT) framework for solving nonlinear partial differential equations (PDEs) in a global space-time formulation. While space-time TT solvers have…
Compression, simulation, and synthesis of turbulent flows with tensor trains
Stefano Pisoni, Raghavendra Dheeraj Peddinti, Egor Tiunov +2
Numerical simulations of turbulent fluids are paramount to real-life applications, from predicting and modeling flows to diagnostic purposes in engineering. However, they are also…
Technical report on a quantum-inspired solver for simulating compressible flows
Raghavendra Dheeraj Peddinti, Stefano Pisoni, Egor Tiunov +2
This document presents a quantum-inspired solver for 2D Euler equations, accepted at the final phase of the Airbus-BWM Group Quantum Computing Challenge (ABQCC) 2024. We tackle the…
Robust ultra-shallow shadows
Renato M. S. Farias, Raghavendra D. Peddinti, Ingo Roth +1
We present a robust shadow estimation protocol for wide classes of low-depth measurement circuits that mitigates noise as long as the effective measurement map including noise is l…