116 citations · 331 across the 22 of their papers we have counts for
14 papers · 1 filter
Fast classical simulation of `Fast, accurate, high-resolution simulation of large-scale Fermi-Hubbard models on a digital quantum processor'
Xiao-Yu Ouyang, Runze Chi, Garnet Kin-Lic Chan
We study the Néel quench dynamics of a 1D Fermi-Hubbard model which has recently been simulated on quantum hardware. We demonstrate that the set of 7260 observable trajectories mea…
Efficient Application of Tensor Network Operators to Tensor Network States Through Successive Deterministic Compression
Richard M. Milbradt, Shuo Sun, Christian B. Mendl +2
We introduce an algorithm to apply tree tensor network operators to tree tensor network states followed by compression. Especially when applying a matrix product operator to matrix…
Partitioned Expansions for Approximate Tensor Network Contractions
Glen Evenbly, Johnnie Gray, Garnet Kin-Lic Chan
We propose a method for approximating the contraction of a tensor network by partitioning the network into a sum of computationally cheaper networks. This method, which we call a p…
Tensor Network Loop Cluster Expansions for Quantum Many-Body Problems
Johnnie Gray, Gunhee Park, Glen Evenbly +3
We analyze the tensor network loop cluster expansion, introduced in [G. Park, J. Gray, and G. K.-L. Chan, Phys. Rev. B 112, 174310 (2025)] as a systematic correction to belief prop…
Coupled Lindblad pseudomode theory for simulating open quantum systems
Zhen Huang, Gunhee Park, Garnet Kin-Lic Chan +1
Coupled Lindblad pseudomode theory is a promising approach for simulating non-Markovian quantum dynamics on both classical and quantum platforms, with dynamics that can be realized…
Simulating quantum dynamics in two-dimensional lattices with tensor network influence functional belief propagation
Gunhee Park, Johnnie Gray, Garnet Kin-Lic Chan
Describing nonequilibrium quantum dynamics remains a significant computational challenge due to the growth of spatial entanglement. The tensor network influence functional (TN-IF)…
Digital quantum magnetism on a trapped-ion quantum computer
Reza Haghshenas, Eli Chertkov, Michael Mills +56
Digital quantum matter -- realized when discrete quantum gates approximate continuous time evolution -- is susceptible to heating into chaotic, structureless states. If digitizatio…
Rapid quantum ground state preparation via dissipative dynamics
Yongtao Zhan, Zhiyan Ding, Jakob Huhn +4
Inspired by natural cooling processes, dissipation has become a promising approach for preparing low-energy states of quantum systems. However, the potential of dissipative protoco…
Quantum linear algebra for disordered electrons
Jielun Chen, Garnet Kin-Lic Chan
We describe how to use quantum linear algebra to simulate a physically realistic model of disordered non-interacting electrons. The physics of disordered electrons outside of one d…
Fermionic tensor network contraction for arbitrary geometries
Yang Gao, Huanchen Zhai, Johnnie Gray +5
We describe our implementation of fermionic tensor network contraction on arbitrary lattices within both a globally ordered and locally ordered formalism. We provide a pedagogical…
Loop Series Expansions for Tensor Networks
Glen Evenbly, Nicola Pancotti, Ashley Milsted +2
Belief propagation (BP) can be a useful tool to approximately contract a tensor network, provided that the contributions from any closed loops in the network are sufficiently weak.…
Real-time operator evolution in two and three dimensions via sparse Pauli dynamics
Tomislav Begušić, Garnet Kin-Lic Chan
We study real-time operator evolution using sparse Pauli dynamics, a recently developed method for simulating expectation values of quantum circuits. On the examples of energy and…
Quasi-Lindblad pseudomode theory for open quantum systems
Gunhee Park, Zhen Huang, Yuanran Zhu +3
We introduce a new framework to study the dynamics of open quantum systems with linearly coupled Gaussian baths. Our approach replaces the continuous bath with an auxiliary discret…
Tensor Network Computations That Capture Strict Variationality, Volume Law Behavior, and the Efficient Representation of Neural Network States
Wen-Yuan Liu, Si-Jing Du, Ruojing Peng +2
We introduce a change of perspective on tensor network states that is defined by the computational graph of the contraction of an amplitude. The resulting class of states, which we…