Real-time adaptive estimation of decoherence timescales for a single qubit

• URL: http://arxiv.org/abs/2210.06103v4
• Date: Wed, 24 Jan 2024 10:40:22 GMT
• Title: Real-time adaptive estimation of decoherence timescales for a single qubit
• Authors: Muhammad Junaid Arshad, Christiaan Bekker, Ben Haylock, Krzysztof Skrzypczak, Daniel White, Benjamin Griffiths, Joe Gore, Gavin W. Morley, Patrick Salter, Jason Smith, Inbar Zohar, Amit Finkler, Yoann Altmann, Erik M. Gauger and Cristian Bonato
• Abstract summary: 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.
• Score: 2.6938732235832044
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Characterising the time over which quantum coherence survives is critical for any implementation of quantum bits, memories and sensors. The usual method for determining a quantum system's decoherence rate involves a suite of experiments probing the entire expected range of this parameter, and extracting the resulting estimation in post-processing. Here we present an adaptive multi-parameter Bayesian approach, based on a simple analytical update rule, to estimate the key decoherence timescales ($T_1$, $T_2^*$ and $T_2$) and the corresponding decay exponent of a quantum system in real time, using information gained in preceding experiments. This approach reduces the time required to reach a given uncertainty by a factor up to an order of magnitude, depending on the specific experiment, compared to the standard protocol of curve fitting. A further speed-up of a factor $\sim 2$ can be realised by performing our optimisation with respect to sensitivity as opposed to variance.

Related papers

• Optimal Low-Depth Quantum Signal-Processing Phase Estimation [0.029541734875307393]
  We introduce Quantum Signal-Processing Phase Estimation algorithms that are robust against challenges and achieve optimal performance. Our approach achieves an unprecedented standard deviation accuracy of $10-4$ radians for estimating unwanted swap angles in superconducting two-qubit experiments. Our results are rigorously validated against the quantum Fisher information, confirming our protocol's ability to achieve unmatched precision for two-qubit gate learning.
  arXiv  Detail & Related papers  (2024-06-17T10:33:52Z)
• Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise [51.87307904567702]
  Quantile regression is a leading approach for obtaining such intervals via the empirical estimation of quantiles in the distribution of outputs. We propose Relaxed Quantile Regression (RQR), a direct alternative to quantile regression based interval construction that removes this arbitrary constraint. We demonstrate that this added flexibility results in intervals with an improvement in desirable qualities.
  arXiv  Detail & Related papers  (2024-06-05T13:36:38Z)
• Time-adaptive phase estimation [0.0]
  We present Bayesian phase estimation methods that adaptively choose a control phase and the time of coherent evolution based on prior phase knowledge. We find near-optimal performance with respect to known theoretical bounds, and demonstrate some robustness of the estimates to noise that is not accounted for in the model of the estimator. The methods provide optimal solutions accounting for available prior knowledge and experimental imperfections with minimal effort from the user.
  arXiv  Detail & Related papers  (2024-05-14T19:49:22Z)
• Importance sampling for stochastic quantum simulations [68.8204255655161]
  We introduce the qDrift protocol, which builds random product formulas by sampling from the Hamiltonian according to the coefficients. We show that the simulation cost can be reduced while achieving the same accuracy, by considering the individual simulation cost during the sampling stage. Results are confirmed by numerical simulations performed on a lattice nuclear effective field theory.
  arXiv  Detail & Related papers  (2022-12-12T15:06:32Z)
• Optimality and Complexity in Measured Quantum-State Stochastic Processes [0.0]
  We show that optimal prediction requires using an infinite number of temporal features. We identify the mechanism underlying this complicatedness as generator nonunifilarity. This makes it possible to quantitatively explore the influence that measurement choice has on a quantum process' degrees of randomness.
  arXiv  Detail & Related papers  (2022-05-08T21:43:06Z)
• Dual-Frequency Quantum Phase Estimation Mitigates the Spectral Leakage of Quantum Algorithms [76.15799379604898]
  Quantum phase estimation suffers from spectral leakage when the reciprocal of the record length is not an integer multiple of the unknown phase. We propose a dual-frequency estimator, which approaches the Cramer-Rao bound, when multiple samples are available.
  arXiv  Detail & Related papers  (2022-01-23T17:20:34Z)
• The Variational Method of Moments [65.91730154730905]
  conditional moment problem is a powerful formulation for describing structural causal parameters in terms of observables. Motivated by a variational minimax reformulation of OWGMM, we define a very general class of estimators for the conditional moment problem. We provide algorithms for valid statistical inference based on the same kind of variational reformulations.
  arXiv  Detail & Related papers  (2020-12-17T07:21:06Z)
• Optimal frequency estimation and its application to quantum dots [0.0]
  We address the interaction-time optimization for frequency estimation in a two-level system. We devise novel estimation protocols with and without feedback. It can improve current experimental techniques and boost coherence times in quantum computing.
  arXiv  Detail & Related papers  (2020-04-25T03:44:02Z)
• Variationally Scheduled Quantum Simulation [0.0]
  We investigate a variational method for determining the optimal scheduling procedure within the context of adiabatic state preparation. In the absence of quantum error correction, running a quantum device for any meaningful amount of time causes a system to become susceptible to the loss of relevant information. Our variational method is found to exhibit resilience against control errors, which are commonly encountered within the realm of quantum computing.
  arXiv  Detail & Related papers  (2020-03-22T14:47:04Z)
• Quantum probes for universal gravity corrections [62.997667081978825]
  We review the concept of minimum length and show how it induces a perturbative term appearing in the Hamiltonian of any quantum system. We evaluate the Quantum Fisher Information in order to find the ultimate bounds to the precision of any estimation procedure. Our results show that quantum probes are convenient resources, providing potential enhancement in precision.
  arXiv  Detail & Related papers  (2020-02-13T19:35:07Z)
• In and out of equilibrium quantum metrology with mean-field quantum criticality [68.8204255655161]
  We study the influence that collective transition phenomena have on quantum metrological protocols. The single spherical quantum spin (SQS) serves as stereotypical toy model that allows analytical insights on a mean-field level.
  arXiv  Detail & Related papers  (2020-01-09T19:20:42Z)

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.