Uncovering and Circumventing Noise in Quantum Algorithms via Metastability

• URL: http://arxiv.org/abs/2511.09821v1
• Date: Fri, 14 Nov 2025 01:11:24 GMT
• Title: Uncovering and Circumventing Noise in Quantum Algorithms via Metastability
• Authors: Antonio Sannia, Pratik Sathe, Luis Pedro García-Pintos,
• Abstract summary: Noise is the primary challenge in realizing fault-tolerant quantum computers.<n>We experimentally validate a novel strategy to circumvent noise by exploiting the phenomenon of metastability.<n>We demonstrate that if quantum hardware noise exhibits metastability, both digital and analog algorithms can be designed in a noise-aware fashion.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The presence of noise is the primary challenge in realizing fault-tolerant quantum computers. In this work, we introduce and experimentally validate a novel strategy to circumvent noise by exploiting the phenomenon of metastability, where a dynamical system exhibits long-lived intermediate states. We demonstrate that if quantum hardware noise exhibits metastability, both digital and analog algorithms can be designed in a noise-aware fashion to achieve intrinsic resilience. We develop a general theoretical framework and introduce an efficiently computable noise resilience metric that avoids the need for full classical simulation of the quantum algorithm. We illustrate the use of our framework with applications to variational quantum algorithms and analog adiabatic state preparation. Crucially, we provide experimental evidence supporting the presence of metastable noise in gate-model quantum processors as well as quantum annealing devices. Thus, we establish that the intrinsic nature of noise in near-term quantum hardware can be leveraged to inform practical implementation strategies, enabling the preparation of final noisy states that more closely approximate the ideal ones.

Related papers

• Variational noise mitigation in quantum circuits: the case of Quantum Fourier Transform [35.18016233072556]
  We perform numerical simulations for two qubits under both coherent and incoherent noise.<n>Our results show that the variational circuit can reproduce the QFT with higher fidelity in scenarios dominated by coherent noise.<n>This demonstrates the potential of the approach as an effective error-mitigation strategy for small- to medium-scale quantum systems.
  arXiv  Detail & Related papers  (2025-11-07T14:35:55Z)
• Digital quantum simulation of many-body systems: Making the most of intermediate-scale, noisy quantum computers [51.56484100374058]
  This thesis is centered around simulating quantum dynamics on quantum devices.<n>We present an overview of the most relevant quantum algorithms for quantum dynamics.<n>We identify relevant problems within quantum dynamics that could benefit from quantum simulation in the near future.
  arXiv  Detail & Related papers  (2025-08-29T10:37:19Z)
• VQC-MLPNet: An Unconventional Hybrid Quantum-Classical Architecture for Scalable and Robust Quantum Machine Learning [50.95799256262098]
  Variational quantum circuits (VQCs) hold promise for quantum machine learning but face challenges in expressivity, trainability, and noise resilience.<n>We propose VQC-MLPNet, a hybrid architecture where a VQC generates the first-layer weights of a classical multilayer perceptron during training, while inference is performed entirely classically.
  arXiv  Detail & Related papers  (2025-06-12T01:38:15Z)
• Provably Robust Training of Quantum Circuit Classifiers Against Parameter Noise [49.97673761305336]
  Noise remains a major obstacle to achieving reliable quantum algorithms.<n>We present a provably noise-resilient training theory and algorithm to enhance the robustness of parameterized quantum circuit classifiers.
  arXiv  Detail & Related papers  (2025-05-24T02:51:34Z)
• Bayesian Quantum Amplitude Estimation [46.03321798937855]
  We present BAE, a problem-tailored and noise-aware Bayesian algorithm for quantum amplitude estimation.<n>In a fault tolerant scenario, BAE is capable of saturating the Heisenberg limit; if device noise is present, BAE can dynamically characterize it and self-adapt.<n>We propose a benchmark for amplitude estimation algorithms and use it to test BAE against other approaches.
  arXiv  Detail & Related papers  (2024-12-05T18:09:41Z)
• Corrupted sensing quantum state tomography [0.0]
  We propose the concept of corrupted sensing quantum state tomography which enables the simultaneous reconstruction of quantum states and structured noise.<n>It is envisaged that the techniques can become a practical tool to greatly reduce the cost and computational effort for quantum tomography in noisy quantum systems.
  arXiv  Detail & Related papers  (2024-05-23T10:13:59Z)
• 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)
• Noise-assisted digital quantum simulation of open systems [1.3124513975412255]
  We present a novel approach that capitalizes on the intrinsic noise of quantum devices to reduce the computational resources required for simulating open quantum systems. Specifically, we selectively enhance or reduce decoherence rates in the quantum circuit to achieve the desired simulation of open system dynamics.
  arXiv  Detail & Related papers  (2023-02-28T14:21:43Z)
• Quantum algorithms for quantum dynamics: A performance study on the spin-boson model [68.8204255655161]
  Quantum algorithms for quantum dynamics simulations are traditionally based on implementing a Trotter-approximation of the time-evolution operator. variational quantum algorithms have become an indispensable alternative, enabling small-scale simulations on present-day hardware. We show that, despite providing a clear reduction of quantum gate cost, the variational method in its current implementation is unlikely to lead to a quantum advantage.
  arXiv  Detail & Related papers  (2021-08-09T18:00:05Z)
• Pulse-level noisy quantum circuits with QuTiP [53.356579534933765]
  We introduce new tools in qutip-qip, QuTiP's quantum information processing package. These tools simulate quantum circuits at the pulse level, leveraging QuTiP's quantum dynamics solvers and control optimization features. We show how quantum circuits can be compiled on simulated processors, with control pulses acting on a target Hamiltonian.
  arXiv  Detail & Related papers  (2021-05-20T17:06:52Z)
• Error mitigation and quantum-assisted simulation in the error corrected regime [77.34726150561087]
  A standard approach to quantum computing is based on the idea of promoting a classically simulable and fault-tolerant set of operations. We show how the addition of noisy magic resources allows one to boost classical quasiprobability simulations of a quantum circuit.
  arXiv  Detail & Related papers  (2021-03-12T20:58:41Z)
• Robustness Verification of Quantum Classifiers [1.3534683694551501]
  We define a formal framework for the verification and analysis of quantum machine learning algorithms against noises. A robust bound is derived and an algorithm is developed to check whether or not a quantum machine learning algorithm is robust with respect to quantum training data. Our approach is implemented on Google's Quantum classifier and can verify the robustness of quantum machine learning algorithms with respect to a small disturbance of noises.
  arXiv  Detail & Related papers  (2020-08-17T11:56:23Z)

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.