Hybrid Gaussian-exponential zero-noise extrapolation for periodic circuits

• URL: http://arxiv.org/abs/2605.29242v2
• Date: Wed, 03 Jun 2026 15:36:04 GMT
• Title: Hybrid Gaussian-exponential zero-noise extrapolation for periodic circuits
• Abstract summary: We introduce a hybrid Gaussian-exponential extrapolation scheme tailored for quantum circuits with periodic structure.<n>For moderate to large circuit depths, the hybrid model yields measurable reductions in bias relative to previous extrapolation variants.
• Score: 2.932287734903261
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Zero-noise extrapolation provides a practical means of suppressing gate errors in current noisy intermediate-scale quantum hardware. The accuracy of the zero-noise estimate depends sensitively on the fidelity of the assumed noise model to the actual error scaling. This work introduces a hybrid Gaussian-exponential extrapolation scheme tailored for quantum circuits with periodic structure, which are ubiquitous in quantum algorithms. Under Pauli diagonal errors, by constructing and analyzing an approximate Markov process for the transfer of Pauli operators, we prove a central limit theorem: the noise amplification factor weakly approaches a log-normal distribution, which motivates augmenting the standard exponential model with Gaussian variance corrections. The resulting model requires no prior noise characterization and applies directly to arbitrary periodic circuits. Performance is assessed on Trotterized Ising dynamics, random circuits, and Grover search algorithm using Qiskit noise simulators. For moderate to large circuit depths, the hybrid model yields measurable reductions in bias relative to previous extrapolation variants, indicating its utility for error mitigation on near-term quantum hardware.

Related papers

• Scalable Lindblad Noise Learning via Stochastic Tensor-Network Simulation [48.887627688666974]
  Learning dissipation rates in large-scale open quantum systems is a major obstacle for near-term quantum technologies.<n>Here, we propose a scalable noise-learning framework for Lindblad dissipation rates that combines a simulation method, the Jump Method (TJM)<n>We demonstrate the approach on two noise models in the Ising model, in which independent dissipation rates are learned for each site up to $N_mathrmsite=16$.<n>This combination of scalable numerics and rigorous theoretical guarantees positions TJM-based noise learning as a practical foundation for characterizing dissipation in large quantum devices.
  arXiv  Detail & Related papers  (2026-08-25T15:07:11Z)
• Efficient Quantum Error Mitigation for Unitary k-Designs [0.0]
  noisy hardware makes quantum circuits prone to a myriad of error sources.<n>We use unitary k-design Pauli support distributions to estimate circuit-wide depolarization.<n>We show that the method effectively reduces gate-based error for unitary k-designs without incurring any two-qubit gate overhead.
  arXiv  Detail & Related papers  (2026-06-02T16:52:08Z)
• Continuous Noise Model for Quantum Circuits [0.6335848702857038]
  We study a continuous coherent noise model for quantum circuits and compare it with a discrete Pauli model.<n>The focus is on small coherent gate errors that build up across circuit depth.<n>Results show that continuous coherent noise can degrade logical performance more strongly than Pauli noise.
  arXiv  Detail & Related papers  (2026-04-28T18:00:03Z)
• Universal Quantum Error Mitigation via Random Inverse Depolarizing Approximation [45.88028371034407]
  We introduce RIDA (Random Inverse Depolarizing Approximation), a simple universal method that harnesses randomly generated circuits to estimate a given circuit's global depolarization probability and corresponding error-free expectation value.<n> Numerical tests indicate RIDA outperforms key benchmarks, suggestive of significant accuracy improvements for applications of quantum computing across fields including physics and chemistry.
  arXiv  Detail & Related papers  (2025-08-24T20:30:08Z)
• Inverted-circuit zero-noise extrapolation for quantum gate error mitigation [0.0]
  We propose a simple method for estimating the strength of errors occurring in a quantum circuit. The method determines the error strength for a circuit by appending to it the inverted circuit and measuring the probability of the initial state. Our method proves to be particularly effective on current hardware, showcasing its suitability for near-term quantum computing applications.
  arXiv  Detail & Related papers  (2024-03-03T20:27:27Z)
• Dynamical quantum maps for single-qubit gates under universal non-Markovian noise [0.0]
  Noise in quantum devices is ubiquitous and generally deleterious in settings where precision is required. Here we derive a compact microscopic error model for single-qubit gates that only requires a single experimental input. We find that experimental estimates of average gate errors measured through randomized benchmarking and reconstructed via quantum process tomography are tightly lower-bounded by our analytical estimates.
  arXiv  Detail & Related papers  (2024-02-22T13:24:03Z)
• Accurate and Honest Approximation of Correlated Qubit Noise [39.58317527488534]
  We propose an efficient systematic construction of approximate noise channels, where their accuracy can be enhanced by incorporating noise components with higher qubit-qubit correlation degree.<n>We find that, for realistic noise strength typical for fixed-frequency superconducting qubits, correlated noise beyond two-qubit correlation can significantly affect the code simulation accuracy.
  arXiv  Detail & Related papers  (2023-11-15T19:00:34Z)
• Scalable noisy quantum circuits for biased-noise qubits [37.69303106863453]
  We consider biased-noise qubits affected only by bit-flip errors, which is motivated by existing systems of stabilized cat qubits. For realistic noise models, phase-flip will not be negligible, but in the Pauli-Twirling approximation, we show that our benchmark could check the correctness of circuits containing up to $106$ gates.
  arXiv  Detail & Related papers  (2023-05-03T11:27:50Z)
• Optimal Algorithms for the Inhomogeneous Spiked Wigner Model [89.1371983413931]
  We derive an approximate message-passing algorithm (AMP) for the inhomogeneous problem. We identify in particular the existence of a statistical-to-computational gap where known algorithms require a signal-to-noise ratio bigger than the information-theoretic threshold to perform better than random.
  arXiv  Detail & Related papers  (2023-02-13T19:57:17Z)
• Simulating the Mott transition on a noisy digital quantum computer via Cartan-based fast-forwarding circuits [62.73367618671969]
  Dynamical mean-field theory (DMFT) maps the local Green's function of the Hubbard model to that of the Anderson impurity model. Quantum and hybrid quantum-classical algorithms have been proposed to efficiently solve impurity models. This work presents the first computation of the Mott phase transition using noisy digital quantum hardware.
  arXiv  Detail & Related papers  (2021-12-10T17:32:15Z)
• Mitigating depolarizing noise on quantum computers with noise-estimation circuits [1.3375143521862154]
  We present a method to mitigate the depolarizing noise by first estimating its rate with a noise-estimation circuit. We find that our approach in combination with readout-error correction, compiling, randomized, and zero-noise extrapolation produces results close to exact results even for circuits containing hundreds of CNOT gates.
  arXiv  Detail & Related papers  (2021-03-15T17:59:06Z)
• On the robustness of the hybrid qubit computational gates through simulated randomized benchmarking protocols [0.0]
  Noise characterization can be achieved by exploiting different techniques, such as randomization. A scalable and robust algorithm able to benchmark the full set of Clifford gates is called randomized benchmarking. In this study, we simulated randomized benchmarking protocols in a semiconducting all-electrical three-electron double-quantum dot qubit.
  arXiv  Detail & Related papers  (2020-11-03T09:35:39Z)

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.