Faster Coherent Quantum Algorithms for Phase, Energy, and Amplitude
Estimation
- URL: http://arxiv.org/abs/2103.09717v4
- Date: Mon, 12 Dec 2022 15:25:54 GMT
- Title: Faster Coherent Quantum Algorithms for Phase, Energy, and Amplitude
Estimation
- Authors: Patrick Rall
- Abstract summary: Most quantum estimation algorithms make assumptions that make them unsuitable for this 'coherent' setting.
We present novel algorithms for phase, energy, and amplitude estimation.
They are both conceptually and computationally simpler than the textbook method.
- Score: 0.30458514384586405
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We consider performing phase estimation under the following conditions: we
are given only one copy of the input state, the input state does not have to be
an eigenstate of the unitary, and the state must not be measured. Most quantum
estimation algorithms make assumptions that make them unsuitable for this
'coherent' setting, leaving only the textbook approach. We present novel
algorithms for phase, energy, and amplitude estimation that are both
conceptually and computationally simpler than the textbook method, featuring
both a smaller query complexity and ancilla footprint. They do not require a
quantum Fourier transform, and they do not require a quantum sorting network to
compute the median of several estimates. Instead, they use block-encoding
techniques to compute the estimate one bit at a time, performing all
amplification via singular value transformation. These improved subroutines
accelerate the performance of quantum Metropolis sampling and quantum Bayesian
inference.
Related papers
- A quantum implementation of high-order power method for estimating geometric entanglement of pure states [39.58317527488534]
This work presents a quantum adaptation of the iterative higher-order power method for estimating the geometric measure of entanglement of multi-qubit pure states.
It is executable on current (hybrid) quantum hardware and does not depend on quantum memory.
We study the effect of noise on the algorithm using a simple theoretical model based on the standard depolarising channel.
arXiv Detail & Related papers (2024-05-29T14:40:24Z) - Near-Term Distributed Quantum Computation using Mean-Field Corrections
and Auxiliary Qubits [77.04894470683776]
We propose near-term distributed quantum computing that involve limited information transfer and conservative entanglement production.
We build upon these concepts to produce an approximate circuit-cutting technique for the fragmented pre-training of variational quantum algorithms.
arXiv Detail & Related papers (2023-09-11T18:00:00Z) - Quantum Clustering with k-Means: a Hybrid Approach [117.4705494502186]
We design, implement, and evaluate three hybrid quantum k-Means algorithms.
We exploit quantum phenomena to speed up the computation of distances.
We show that our hybrid quantum k-Means algorithms can be more efficient than the classical version.
arXiv Detail & Related papers (2022-12-13T16:04:16Z) - Improved Quantum Algorithms for Fidelity Estimation [77.34726150561087]
We develop new and efficient quantum algorithms for fidelity estimation with provable performance guarantees.
Our algorithms use advanced quantum linear algebra techniques, such as the quantum singular value transformation.
We prove that fidelity estimation to any non-trivial constant additive accuracy is hard in general.
arXiv Detail & Related papers (2022-03-30T02:02:16Z) - Reducing the cost of energy estimation in the variational quantum
eigensolver algorithm with robust amplitude estimation [50.591267188664666]
Quantum chemistry and materials is one of the most promising applications of quantum computing.
Much work is still to be done in matching industry-relevant problems in these areas with quantum algorithms that can solve them.
arXiv Detail & Related papers (2022-03-14T16:51:36Z) - Quantum algorithms for estimating quantum entropies [6.211541620389987]
We propose quantum algorithms to estimate the von Neumann and quantum $alpha$-R'enyi entropies of an fundamental quantum state.
We also show how to efficiently construct the quantum entropy circuits for quantum entropy estimation using single copies of the input state.
arXiv Detail & Related papers (2022-03-04T15:44:24Z) - Low-rank quantum state preparation [1.5427245397603195]
We propose an algorithm to reduce state preparation circuit depth by offloading computational complexity to a classical computer.
We show that the approximation is better on today's quantum processors.
arXiv Detail & Related papers (2021-11-04T19:56:21Z) - 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) - Variational Quantum Algorithms for Trace Distance and Fidelity
Estimation [7.247285982078057]
We introduce hybrid quantum-classical algorithms for two distance measures on near-term quantum devices.
First, we introduce the Variational Trace Distance Estimation (VTDE) algorithm.
Second, we introduce the Variational Fidelity Estimation (VFE) algorithm.
arXiv Detail & Related papers (2020-12-10T15:56:58Z) - Algorithms for quantum simulation at finite energies [0.7734726150561088]
We introduce two kinds of quantum algorithms to explore microcanonical and canonical properties of many-body systems.
One is a hybrid quantum algorithm that computes expectation values in a finite energy interval around its mean energy.
The other is a quantum-assisted Monte Carlo sampling method to compute other quantities.
arXiv Detail & Related papers (2020-06-04T17:40:29Z) - A Variational Quantum Algorithm for Preparing Quantum Gibbs States [0.22559617939136506]
Preparation of Gibbs distributions is an important task for quantum computation.
We present a variational approach to preparing Gibbs states that is based on minimizing the free energy of a quantum system.
arXiv Detail & Related papers (2020-01-31T20:52:50Z)
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.