Low Cost Bayesian Experimental Design for Quantum Frequency Estimation with Decoherence

• URL: http://arxiv.org/abs/2508.07120v1
• Date: Sat, 09 Aug 2025 23:41:58 GMT
• Title: Low Cost Bayesian Experimental Design for Quantum Frequency Estimation with Decoherence
• Authors: Alexandra Ramôa, Luís Paulo Santos, Akihito Soeda,
• Abstract summary: We introduce WES: a Window Expansion Strategy for low cost adaptive Bayesian experimental design.<n>We employ empirical cost-reduction techniques to keep the optimization overhead low, curb scaling problems, and enable high degrees of parallelism.<n> Numerical simulations show that WES delivers the most reliable performance and fastest learning rate, saturating the Heisenberg limit.
• Score: 45.74830585715129
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: A two-level quantum system evolving under a time-independent Hamiltonian produces oscillatory measurement probabilities. The estimation of the associated frequency is a cornerstone problem in quantum metrology, sensing, calibration and control. In this work, we tackle this task by introducing WES: a Window Expansion Strategy for low cost adaptive Bayesian experimental design. WES employs empirical cost-reduction techniques to keep the optimization overhead low, curb scaling problems, and enable high degrees of parallelism. Unlike previous heuristics, it offers adjustable classical processing costs that determine the performance standard. As a benchmark, we analyze the performance of widely adopted heuristics, comparing them with the fundamental limits of metrology and a baseline random strategy. Numerical simulations show that WES delivers the most reliable performance and fastest learning rate, saturating the Heisenberg limit.

Related papers

• Continual Quantum Architecture Search with Tensor-Train Encoding: Theory and Applications to Signal Processing [68.35481158940401]
  CL-QAS is a continual quantum architecture search framework.<n>It mitigates challenges of costly encoding amplitude and forgetting in variational quantum circuits.<n>It achieves controllable robustness expressivity, sample-efficient generalization, and smooth convergence without barren plateaus.
  arXiv  Detail & Related papers  (2026-01-10T02:36:03Z)
• Exploiting biased noise in variational quantum models [0.0]
  Variational quantum algorithms (VQAs) are promising tools for demonstrating quantum utility on near-term quantum hardware.<n>We study the effect of quantum noise on the classical optimisation process.<n>We find that twirling, which is commonly used in standard error-mitigation strategies to symmetrise noise, actually degrades performance in the variational setting.
  arXiv  Detail & Related papers  (2025-10-28T04:14:20Z)
• Optimal quantum learning in proximity to universality [0.0]
  boundary between classically simulable and computationally superior quantum systems is fundamental to identifying true quantum advantage.<n>We introduce a tunable $N$-qubit random circuit model, where a fraction $p$ of Clifford gates are probabilistically substituted with nonstabilizing conditional-$hatT$ gates.<n>We establish a direct correspondence between the reservoir's performance on temporal processing tasks and its entanglement spectrum statistics and long-range nonstabilizer resource content.
  arXiv  Detail & Related papers  (2025-10-21T13:27:41Z)
• TensoMeta-VQC: A Tensor-Train-Guided Meta-Learning Framework for Robust and Scalable Variational Quantum Computing [60.996803677584424]
  TensoMeta-VQC is a novel tensor-train (TT)-guided meta-learning framework designed to improve the robustness and scalability of VQC significantly.<n>Our framework fully delegates the generation of quantum circuit parameters to a classical TT network, effectively decoupling optimization from quantum hardware.
  arXiv  Detail & Related papers  (2025-08-01T23:37:55Z)
• Resource-Efficient Hadamard Test Circuits for Nonlinear Dynamics on a Trapped-Ion Quantum Computer [1.2063443893298391]
  We propose a low-depth implementation of a class of Hadamard test circuits.<n>We develop a parameterized quantum ansatz specifically tailored for variational algorithms.<n>Our findings demonstrate a significant reduction in single- and two-qubit gate counts.
  arXiv  Detail & Related papers  (2025-07-25T13:16:54Z)
• 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)
• Bayesian Quantum Amplitude Estimation [49.1574468325115]
  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)
• Optimal Low-Depth Quantum Signal-Processing Phase Estimation [0.029541734875307393]
  Quantum effects like entanglement can be used to drastically enhance the accuracy of quantum parameter estimation beyond classical limits.<n>We introduce Quantum Signal-Processing Phase Estimation algorithms that are robust against these challenges.<n>Our approach achieves a standard deviation accuracy of $10-4$ radians for estimating unwanted swap angles in superconducting two-qubit experiments.
  arXiv  Detail & Related papers  (2024-06-17T10:33:52Z)
• Real-time adaptive estimation of decoherence timescales for a single qubit [2.6938732235832044]
  Characterising the time over which quantum coherence survives is critical for any implementation of quantum bits, memories and sensors. We present an adaptive multi- parameter approach, based on a simple analytical update rule, to estimate the key decoherence in real time. A further speed-up of a factor $sim 2$ can be realised by performing our optimisation with respect to sensitivity as opposed to variance.
  arXiv  Detail & Related papers  (2022-10-12T11:28:23Z)
• Realization of arbitrary doubly-controlled quantum phase gates [62.997667081978825]
  We introduce a high-fidelity gate set inspired by a proposal for near-term quantum advantage in optimization problems. By orchestrating coherent, multi-level control over three transmon qutrits, we synthesize a family of deterministic, continuous-angle quantum phase gates acting in the natural three-qubit computational basis.
  arXiv  Detail & Related papers  (2021-08-03T17:49:09Z)
• Quantum circuit architecture search for variational quantum algorithms [88.71725630554758]
  We propose a resource and runtime efficient scheme termed quantum architecture search (QAS) QAS automatically seeks a near-optimal ansatz to balance benefits and side-effects brought by adding more noisy quantum gates. We implement QAS on both the numerical simulator and real quantum hardware, via the IBM cloud, to accomplish data classification and quantum chemistry tasks.
  arXiv  Detail & Related papers  (2020-10-20T12:06:27Z)
• Preparation of excited states for nuclear dynamics on a quantum computer [117.44028458220427]
  We study two different methods to prepare excited states on a quantum computer. We benchmark these techniques on emulated and real quantum devices. These findings show that quantum techniques designed to achieve good scaling on fault tolerant devices might also provide practical benefits on devices with limited connectivity and gate fidelity.
  arXiv  Detail & Related papers  (2020-09-28T17:21:25Z)
• Optimal non-classical correlations of light with a levitated nano-sphere [34.82692226532414]
  Nonclassical correlations provide a resource for many applications in quantum technology. Optomechanical systems can generate nonclassical correlations between the mechanical mode and a mode of travelling light. We propose automated optimization of the production of quantum correlations in such a system.
  arXiv  Detail & Related papers  (2020-06-26T15:27:47Z)

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.