2 citations · 2 across the 3 of their papers we have counts for
8 papers · 1 filter
Compressing multivariate functions with tree tensor networks
Joseph Tindall, E. Miles Stoudenmire, Ryan Levy
Tensor networks are a compressed format for multi-dimensional data. One dimensional tensor networks -- often referred to as tensor trains (TT) or matrix product states (MPS) -- are…
Recursive Sketched Interpolation: Efficient Hadamard Products of Tensor Trains
Zhaonan Meng, Yuehaw Khoo, Jiajia Li +1
The Hadamard product of two tensors in the tensor-train (TT) format is a fundamental operation across various applications, such as TT-based function multiplication for nonlinear d…
Investigating a Quantum-Inspired Method for Quantum Dynamics
Bo Xiao, Benedikt Kloss, E. Miles Stoudenmire
Building on recent advances in quantum algorithms which measure and reuse qubits and in efficient classical simulation leveraging projective measurements, we extend these framework…
Magic of the Well: assessing quantum resources of fluid dynamics data
Antonio Francesco Mello, Mario Collura, E. Miles Stoudenmire +1
We investigate the quantum resource requirements of a dataset generated from simulations of two-dimensional, periodic, incompressible shear flow, aimed at training machine learning…
Process Tensor Approaches to Non-Markovian Quantum Dynamics
Jonathan Keeling, E. Miles Stoudenmire, Mari-Carmen Bañuls +1
The paradigm of considering open quantum systems -- i.e. focusing only on the system of interest, and treating the rest of the world as an effective environment -- has proven to be…
Control-driven critical fluctuations across quantum trajectories
Haining Pan, Thomas Iadecola, E. M. Stoudenmire +1
Monitored quantum circuits in which entangling unitary dynamics compete with projective local measurements can host measurement-induced phase transitions witnessed by entanglement…