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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…
Dynamics of disordered quantum systems with two- and three-dimensional tensor networks
Joseph Tindall, Antonio Mello, Matt Fishman +2
Large scale quantum annealing dynamics of Ising spin glasses were recently implemented on D-Wave's Advantage system on a range of lattices. Following extensive comparison to exi…
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…
Approximate Contraction of Arbitrary Tensor Networks with a Flexible and Efficient Density Matrix Algorithm
Linjian Ma, Matthew Fishman, Miles Stoudenmire +1
Tensor network contractions are widely used in statistical physics, quantum computing, and computer science. We introduce a method to efficiently approximate tensor network contrac…
Efficient tensor network simulation of IBM's Eagle kicked Ising experiment
Joseph Tindall, Matt Fishman, Miles Stoudenmire +1
We report an accurate and efficient classical simulation of a kicked Ising quantum system on the heavy-hexagon lattice. A simulation of this system was recently performed on a 127…
Opening the Black Box Inside Grover's Algorithm
E. M. Stoudenmire, Xavier Waintal
Grover's algorithm is a primary algorithm offered as evidence that quantum computers can provide an advantage over classical computers. It involves an "oracle" specified for a give…
Quantum Fourier Transform Has Small Entanglement
Jielun Chen, E. M. Stoudenmire, Steven R. White
The Quantum Fourier Transform (QFT) is a key component of many important quantum algorithms, most famously as being the essential ingredient in Shor's algorithm for factoring produ…
What limits the simulation of quantum computers?
Yiqing Zhou, E. Miles Stoudenmire, Xavier Waintal
It is imperative that useful quantum computers be very difficult to simulate classically; otherwise classical computers could be used for the applications envisioned for the quantu…
Towards Quantum Machine Learning with Tensor Networks
William Huggins, Piyush Patel, K. Birgitta Whaley +1
Machine learning is a promising application of quantum computing, but challenges remain as near-term devices will have a limited number of physical qubits and high error rates. Mot…