39 citations · 39 across the 9 of their papers we have counts for
10 papers
Multiscale passive scalar turbulence in a compressed subspace via tensor trains
Stefano Pisoni, Egor Tiunov, Chiara Calascibetta
Capturing the multiscale statistics of turbulence in compressed form remains a central challenge for reduced-order modeling. We introduce a hybrid Tensor Train (TT) approach for a…
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…
Tensor-network approach to quantum optical state evolution beyond the Fock basis
Nikolay Kapridov, Egor Tiunov, Dmitry Chermoshentsev
Understanding the quantum evolution of light in nonlinear media is central to the development of next-generation quantum technologies. Yet, modeling these processes remains computa…
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…
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…