An iterative quantum-phase-estimation protocol for near-term quantum
hardware
- URL: http://arxiv.org/abs/2206.06392v1
- Date: Mon, 13 Jun 2022 18:00:09 GMT
- Title: An iterative quantum-phase-estimation protocol for near-term quantum
hardware
- Authors: Joseph G. Smith, Crispin H. W. Barnes and David R. M. Arvidsson-Shukur
- Abstract summary: entanglement-free protocols have been developed, which achieve a $mathcalO left[ sqrtlog (log N_textrmtot) / N_textrmtot right]$ mean-absolute-error scaling.
Here, we propose a new two-step protocol for near-term phase estimation, with an improved error scaling.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Given $N_{\textrm{tot}}$ applications of a unitary operation with an unknown
phase $\theta$, a large-scale fault-tolerant quantum system can {reduce} an
estimate's {error} scaling from $\mathcal{O} \left[ 1 / \sqrt{N_{\textrm{tot}}}
\right]$ to $\mathcal{O} \left[ 1 / {N_{\textrm{tot}}} \right]$. Owing to the
limited resources available to near-term quantum devices, entanglement-free
protocols have been developed, which achieve a $\mathcal{O} \left[
\log(N_{\textrm{tot}}) / N_{\textrm{tot}} \right]$ {mean-absolute-error}
scaling. Here, we propose a new two-step protocol for near-term phase
estimation, with an improved {error} scaling. Our protocol's first step
produces several low-{standard-deviation} estimates of $\theta $, within
$\theta$'s parameter range. The second step iteratively hones in on one of
these estimates. Our protocol's {mean absolute error} scales as $\mathcal{O}
\left[ \sqrt{\log (\log N_{\textrm{tot}})} / N_{\textrm{tot}} \right]$.
Furthermore, we demonstrate a reduction in the constant scaling factor and the
required circuit depths: our protocol can outperform the asymptotically optimal
quantum-phase estimation algorithm for realistic values of $N_{\textrm{tot}}$.
Related papers
- Obtaining Lower Query Complexities through Lightweight Zeroth-Order Proximal Gradient Algorithms [65.42376001308064]
We propose two variance reduced ZO estimators for complex gradient problems.
We improve the state-of-the-art function complexities from $mathcalOleft(minfracdn1/2epsilon2, fracdepsilon3right)$ to $tildecalOleft(fracdepsilon2right)$.
arXiv Detail & Related papers (2024-10-03T15:04:01Z) - Variance-Reduced Fast Krasnoselkii-Mann Methods for Finite-Sum Root-Finding Problems [8.0153031008486]
We propose a new class of fast Krasnoselkii--Mann methods with variance reduction to solve a finite-sum co-coercive equation $Gx = 0$.
Our algorithm is single-loop and leverages a new family of unbiased variance-reduced estimators specifically designed for a wider class of root-finding algorithms.
numerical experiments validate our algorithms and demonstrate their promising performance compared to state-of-the-art methods.
arXiv Detail & Related papers (2024-06-04T15:23:29Z) - Multi-level quantum signal processing with applications to ground state preparation using fast-forwarded Hamiltonian evolution [0.8359711817610189]
Preparation of the ground state of a Hamiltonian $H$ with a large spectral radius has applications in many areas.
We develop a multi-level Quantum Signal Processing (QSP)-based algorithm that exploits the fast-forwarding feature.
arXiv Detail & Related papers (2024-06-04T08:09:51Z) - Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction [16.82220229840038]
We introduce two novel algorithms that attain improved convergence rates of $mathcalO(d1/2T-1/2 + dn-1/2)$ and $mathcalO(d1/4T-1/4)$ respectively.
Numerical experiments across different tasks validate the effectiveness of our proposed methods.
arXiv Detail & Related papers (2024-06-01T16:38:43Z) - Estimating the Mixing Coefficients of Geometrically Ergodic Markov
Processes [5.00389879175348]
We estimate the individual $beta$-mixing coefficients of a real-valued geometrically ergodic Markov process from a single sample-path.
Naturally no density assumptions are required in this setting; the expected error rate is shown to be of order $mathcal O(log(n) n-1/2)$.
arXiv Detail & Related papers (2024-02-11T20:17:10Z) - Spacetime-Efficient Low-Depth Quantum State Preparation with
Applications [93.56766264306764]
We show that a novel deterministic method for preparing arbitrary quantum states requires fewer quantum resources than previous methods.
We highlight several applications where this ability would be useful, including quantum machine learning, Hamiltonian simulation, and solving linear systems of equations.
arXiv Detail & Related papers (2023-03-03T18:23:20Z) - Quantum Resources Required to Block-Encode a Matrix of Classical Data [56.508135743727934]
We provide circuit-level implementations and resource estimates for several methods of block-encoding a dense $Ntimes N$ matrix of classical data to precision $epsilon$.
We examine resource tradeoffs between the different approaches and explore implementations of two separate models of quantum random access memory (QRAM)
Our results go beyond simple query complexity and provide a clear picture into the resource costs when large amounts of classical data are assumed to be accessible to quantum algorithms.
arXiv Detail & Related papers (2022-06-07T18:00:01Z) - A lower bound on the space overhead of fault-tolerant quantum computation [51.723084600243716]
The threshold theorem is a fundamental result in the theory of fault-tolerant quantum computation.
We prove an exponential upper bound on the maximal length of fault-tolerant quantum computation with amplitude noise.
arXiv Detail & Related papers (2022-01-31T22:19:49Z) - Calculable lower bounds on the efficiency of universal sets of quantum
gates [0.0]
Currently available quantum computers, so called Noisy Intermediate-Scale Quantum (NISQ) devices, are characterized by relatively low number of qubits and moderate gate fidelities.
In this paper we derive lower bounds on $mathrmgap_r(mathcalS)$ and, as a consequence, on the efficiency of universal sets of $d$-dimensional quantum gates.
arXiv Detail & Related papers (2022-01-27T19:38:13Z) - Random quantum circuits transform local noise into global white noise [118.18170052022323]
We study the distribution over measurement outcomes of noisy random quantum circuits in the low-fidelity regime.
For local noise that is sufficiently weak and unital, correlations (measured by the linear cross-entropy benchmark) between the output distribution $p_textnoisy$ of a generic noisy circuit instance shrink exponentially.
If the noise is incoherent, the output distribution approaches the uniform distribution $p_textunif$ at precisely the same rate.
arXiv Detail & Related papers (2021-11-29T19:26:28Z) - Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and
Variance Reduction [63.41789556777387]
Asynchronous Q-learning aims to learn the optimal action-value function (or Q-function) of a Markov decision process (MDP)
We show that the number of samples needed to yield an entrywise $varepsilon$-accurate estimate of the Q-function is at most on the order of $frac1mu_min (1-gamma)5varepsilon2+ fract_mixmu_min (1-gamma)$ up to some logarithmic factor.
arXiv Detail & Related papers (2020-06-04T17:51:00Z)
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.