39 citations · 61 across the 8 of their papers we have counts for
9 papers
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…
Efficient upsampling for tensor-network and quantum-state encoded functions
Siddhartha E. Guzman, Egor Tiunov, Leandro Aolita
Both tensor trains (TTs) and quantum states provide compressed representations of grid-structured data with potentially exponential compression power. We present a unified framewor…
Exponential Speed-ups for Structured Goemans-Williamson relaxations via Quantum Gibbs States and Pauli Sparsity
Haomu Yuan, Daniel Stilck França, Ilia Luchnikov +3
Quadratic Unconstrained Binary Optimization (QUBO) problems are prevalent in various applications and are known to be NP-hard. The seminal work of Goemans and Williamson introduced…
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…
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…
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…
Large-scale quantum annealing simulation with tensor networks and belief propagation
Ilia A. Luchnikov, Egor S. Tiunov, Tobias Haug +1
Quantum annealing and quantum approximate optimization algorithms hold a great potential to speed-up optimization problems. This could be game-changing for a plethora of applicatio…
Probing quantum complexity via universal saturation of stabilizer entropies
Tobias Haug, Leandro Aolita, M. S. Kim
Nonstabilizerness or `magic' is a key resource for quantum computing and a necessary condition for quantum advantage. Non-Clifford operations turn stabilizer states into resourcefu…
Complete quantum-inspired framework for computational fluid dynamics
Raghavendra D. Peddinti, Stefano Pisoni, Alessandro Marini +4
Computational fluid dynamics is both a thriving research field and a key tool for advanced industry applications. The central challenge is to simulate turbulent flows in complex ge…