Quantum Utility-Scale Error Mitigation for Quantum Quench Dynamics in Heisenberg Spin Chains

• URL: http://arxiv.org/abs/2506.20125v1
• Date: Wed, 25 Jun 2025 04:33:39 GMT
• Title: Quantum Utility-Scale Error Mitigation for Quantum Quench Dynamics in Heisenberg Spin Chains
• Authors: Seokwon Choi, Talal Ahmed Chowdhury, Kwangmin Yu,
• Abstract summary: We propose a quantum error mitigation method termed self-mitigation to achieve quantum utility on noisy quantum computers.<n>We simulate quantum quench dynamics for Heisenberg spin chains with system sizes up to 104 qubits using IBM quantum processors.<n>The self-mitigation method shows stable accuracy with the large systems of 104 qubits with more than 3,000 CNOT gates.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose a quantum error mitigation method termed self-mitigation, which is comparable with zero-noise extrapolation, to achieve quantum utility on near-term, noisy quantum computers. We investigate the effectiveness of several quantum error mitigation strategies, including self-mitigation, by simulating quantum quench dynamics for Heisenberg spin chains with system sizes up to 104 qubits using IBM quantum processors. In particular, we discuss the limitations of zero-noise extrapolation and the advantages offered by self-mitigation at a large scale. The self-mitigation method shows stable accuracy with the large systems of 104 qubits with more than 3,000 CNOT gates. Also, we combine the discussed quantum error mitigation methods with practical entanglement entropy measuring methods, and it shows a good agreement with the theoretical estimation. Our study illustrates the usefulness of near-term noisy quantum hardware in examining the quantum quench dynamics of many-body systems at large scales, and lays the groundwork for surpassing classical simulations with quantum methods prior to the development of fault-tolerant quantum computers.

Related papers

• Power Characterization of Noisy Quantum Kernels [52.47151453259434]
  We show that noise may make quantum kernel methods to only have poor prediction capability, even when the generalization error is small. We provide a crucial warning to employ noisy quantum kernel methods for quantum computation.
  arXiv  Detail & Related papers  (2024-01-31T01:02:16Z)
• Quantum data learning for quantum simulations in high-energy physics [55.41644538483948]
  We explore the applicability of quantum-data learning to practical problems in high-energy physics. We make use of ansatz based on quantum convolutional neural networks and numerically show that it is capable of recognizing quantum phases of ground states. The observation of non-trivial learning properties demonstrated in these benchmarks will motivate further exploration of the quantum-data learning architecture in high-energy physics.
  arXiv  Detail & Related papers  (2023-06-29T18:00:01Z)
• Variational Quantum Metrology with Loschmidt Echo [11.587596311060986]
  We propose a scalable scheme with a symmetrical variational quantum circuit which, same as the Loschmidt echo, consists of a forward and a backward evolution.<n>We show that in this scheme the quantum Fisher information, which quantifies the precision limit, can be efficiently obtained from a measurement signal of the Loschmidt echo.<n>We experimentally implement the scheme on an ensemble of 10-spin quantum processor and successfully achieves a precision near the theoretical limit which outperforms the standard quantum limit with 12.4 dB.
  arXiv  Detail & Related papers  (2022-11-22T14:21:59Z)
• Anticipative measurements in hybrid quantum-classical computation [68.8204255655161]
  We present an approach where the quantum computation is supplemented by a classical result. Taking advantage of its anticipation also leads to a new type of quantum measurements, which we call anticipative. In an anticipative quantum measurement the combination of the results from classical and quantum computations happens only in the end.
  arXiv  Detail & Related papers  (2022-09-12T15:47:44Z)
• Simulating large-size quantum spin chains on cloud-based superconducting quantum computers [0.46040036610482665]
  We report on cloud simulations performed on several of IBM's superconducting quantum computers. We find that the ground-state energies extracted from realizations reach the expected values to within errors that are small. By using a 102-qubit system, we have been able to successfully apply up to 3186 CNOT gates in a single circuit.
  arXiv  Detail & Related papers  (2022-07-20T15:55:29Z)
• Circuit Symmetry Verification Mitigates Quantum-Domain Impairments [69.33243249411113]
  We propose circuit-oriented symmetry verification that are capable of verifying the commutativity of quantum circuits without the knowledge of the quantum state. In particular, we propose the Fourier-temporal stabilizer (STS) technique, which generalizes the conventional quantum-domain formalism to circuit-oriented stabilizers.
  arXiv  Detail & Related papers  (2021-12-27T21:15:35Z)
• Model-Independent Error Mitigation in Parametric Quantum Circuits and Depolarizing Projection of Quantum Noise [1.5162649964542718]
  Finding ground states and low-lying excitations of a given Hamiltonian is one of the most important problems in many fields of physics. quantum computing on Noisy Intermediate-Scale Quantum (NISQ) devices offers the prospect to efficiently perform such computations. Current quantum devices still suffer from inherent quantum noise.
  arXiv  Detail & Related papers  (2021-11-30T16:08:01Z)
• Efficient criteria of quantumness for a large system of qubits [58.720142291102135]
  We discuss the dimensionless combinations of basic parameters of large, partially quantum coherent systems. Based on analytical and numerical calculations, we suggest one such number for a system of qubits undergoing adiabatic evolution.
  arXiv  Detail & Related papers  (2021-08-30T23:50:05Z)
• Perturbative quantum simulation [2.309018557701645]
  We introduce perturbative quantum simulation, which combines the complementary strengths of the two approaches. The use of a quantum processor eliminates the need to identify a solvable unperturbed Hamiltonian. We numerically benchmark the method for interacting bosons, fermions, and quantum spins in different topologies.
  arXiv  Detail & Related papers  (2021-06-10T17:38:25Z)
• Neural Error Mitigation of Near-Term Quantum Simulations [0.0]
  We introduce $textitneural error mitigation$, a novel method that uses neural networks to improve estimates of ground states and ground-state observables. Our results show that neural error mitigation improves the numerical and experimental VQE computation to yield low-energy errors. Our method is a promising strategy for extending the reach of near-term quantum computers to solve complex quantum simulation problems.
  arXiv  Detail & Related papers  (2021-05-17T18:00:57Z)
• Preparing random states and benchmarking with many-body quantum chaos [48.044162981804526]
  We show how to predict and experimentally observe the emergence of random state ensembles naturally under time-independent Hamiltonian dynamics. The observed random ensembles emerge from projective measurements and are intimately linked to universal correlations built up between subsystems of a larger quantum system. Our work has implications for understanding randomness in quantum dynamics, and enables applications of this concept in a wider context.
  arXiv  Detail & Related papers  (2021-03-05T08:32:43Z)
• Direct Quantum Communications in the Presence of Realistic Noisy Entanglement [69.25543534545538]
  We propose a novel quantum communication scheme relying on realistic noisy pre-shared entanglement. Our performance analysis shows that the proposed scheme offers competitive QBER, yield, and goodput.
  arXiv  Detail & Related papers  (2020-12-22T13:06:12Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.