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Holographic dynamics simulations with a trapped ion quantum computer

Quantum computers have the potential to efficiently simulate the dynamics of many interacting quantum particles, a classically intractable task of central importance to fields ranging from chemistry to high-energy physics. However, precision and memory limitations of existing hardware severely limit...

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Published in:arXiv.org 2021-05
Main Authors: Chertkov, Eli, Bohnet, Justin, Francois, David, Gaebler, John, Gresh, Dan, Hankin, Aaron, Lee, Kenny, Tobey, Ra'anan, Hayes, David, Neyenhuis, Brian, Stutz, Russell, Potter, Andrew C, Foss-Feig, Michael
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container_title arXiv.org
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creator Chertkov, Eli
Bohnet, Justin
Francois, David
Gaebler, John
Gresh, Dan
Hankin, Aaron
Lee, Kenny
Tobey, Ra'anan
Hayes, David
Neyenhuis, Brian
Stutz, Russell
Potter, Andrew C
Foss-Feig, Michael
description Quantum computers have the potential to efficiently simulate the dynamics of many interacting quantum particles, a classically intractable task of central importance to fields ranging from chemistry to high-energy physics. However, precision and memory limitations of existing hardware severely limit the size and complexity of models that can be simulated with conventional methods. Here, we demonstrate and benchmark a new scalable quantum simulation paradigm--holographic quantum dynamics simulation--which uses efficient quantum data compression afforded by quantum tensor networks along with opportunistic mid-circuit measurement and qubit reuse to simulate physical systems that have far more quantum degrees of freedom than can be captured by the available number of qubits. Using a Honeywell trapped ion quantum processor, we simulate the non-integrable (chaotic) dynamics of the self-dual kicked Ising model starting from an entangled state of \(32\) spins using at most \(9\) trapped ion qubits, obtaining excellent quantitative agreement when benchmarking against dynamics computed directly in the thermodynamic limit via recently developed exact analytical techniques. These results suggest that quantum tensor network methods, together with state-of-the-art quantum processor capabilities, enable a viable path to practical quantum advantage in the near term.
doi_str_mv 10.48550/arxiv.2105.09324
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subjects Circuits
Data compression
Dynamics
Entangled states
Holography
Ising model
Mathematical analysis
Microprocessors
Quantum computers
Qubits (quantum computing)
Simulation
Tensors
title Holographic dynamics simulations with a trapped ion quantum computer
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