Quantum state preparation with multiplicative amplitude transduction
- URL: http://arxiv.org/abs/2006.00975v1
- Date: Mon, 1 Jun 2020 14:36:50 GMT
- Title: Quantum state preparation with multiplicative amplitude transduction
- Authors: Yutaro Iiyama
- Abstract summary: Two variants of the algorithm with different emphases are introduced.
One variant uses fewer qubits and no controlled gates, while the other variant potentially requires fewer gates overall.
A general analysis is given to estimate the number of qubits necessary to achieve a desired precision in the amplitudes of the computational basis states.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Quantum state preparation is an important class of quantum algorithms that is
employed as a black-box subroutine in many algorithms, or used by itself to
generate arbitrary probability distributions. We present a novel state
preparation method that utilizes less quantum computing resource than the
existing methods. Two variants of the algorithm with different emphases are
introduced. One variant uses fewer qubits and no controlled gates, while the
other variant potentially requires fewer gates overall. A general analysis is
given to estimate the number of qubits necessary to achieve a desired precision
in the amplitudes of the computational basis states. The validity of the
algorithm is demonstrated using a prototypical problem of generating Ising
model spin configurations according to its Boltzmann distribution.
Related papers
- Preparing low-variance states using a distributed quantum algorithm [2.1587559138197667]
We present a distributed quantum algorithm inspired by iterative phase estimation to prepare low-variance states.
Our method uses a single auxiliary qubit per quantum device, which controls its dynamics, and a postselection strategy for a joint quantum measurement on such auxiliary qubits.
This allows us to demonstrate that our distributed algorithm reduces the energy variance significantly faster compared to single-device implementations.
arXiv Detail & Related papers (2025-01-22T18:55:51Z) - Quantum Algorithms for Stochastic Differential Equations: A Schrödingerisation Approach [29.662683446339194]
We propose quantum algorithms for linear differential equations.
The gate complexity of our algorithms exhibits an $mathcalO(dlog(Nd))$ dependence on the dimensions.
The algorithms are numerically verified for the Ornstein-Uhlenbeck processes, Brownian motions, and one-dimensional L'evy flights.
arXiv Detail & Related papers (2024-12-19T14:04:11Z) - Evaluation of phase shifts for non-relativistic elastic scattering using quantum computers [39.58317527488534]
This work reports the development of an algorithm that makes it possible to obtain phase shifts for generic non-relativistic elastic scattering processes on a quantum computer.
arXiv Detail & Related papers (2024-07-04T21:11:05Z) - 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) - Quantum Semidefinite Programming with Thermal Pure Quantum States [0.5639904484784125]
We show that a quantization'' of the matrix multiplicative-weight algorithm can provide approximate solutions to SDPs quadratically faster than the best classical algorithms.
We propose a modification of this quantum algorithm and show that a similar speedup can be obtained by replacing the Gibbs-state sampler with the preparation of thermal pure quantum (TPQ) states.
arXiv Detail & Related papers (2023-10-11T18:00:53Z) - Quantum Neural Estimation of Entropies [20.12693323453867]
entropy measures quantify the amount of information and correlation present in a quantum system.
We propose a variational quantum algorithm for estimating the von Neumann and R'enyi entropies, as well as the measured relative entropy and measured R'enyi relative entropy.
arXiv Detail & Related papers (2023-07-03T17:30:09Z) - On adaptive low-depth quantum algorithms for robust multiple-phase
estimation [11.678822620192438]
We present robust multiple-phase estimation (RMPE) algorithms with Heisenberg-limited scaling.
These algorithms are particularly suitable for early fault-tolerant quantum computers.
arXiv Detail & Related papers (2023-03-14T17:38:01Z) - Entanglement and coherence in Bernstein-Vazirani algorithm [58.720142291102135]
Bernstein-Vazirani algorithm allows one to determine a bit string encoded into an oracle.
We analyze in detail the quantum resources in the Bernstein-Vazirani algorithm.
We show that in the absence of entanglement, the performance of the algorithm is directly related to the amount of quantum coherence in the initial state.
arXiv Detail & Related papers (2022-05-26T20:32:36Z) - Quantum algorithms for grid-based variational time evolution [36.136619420474766]
We propose a variational quantum algorithm for performing quantum dynamics in first quantization.
Our simulations exhibit the previously observed numerical instabilities of variational time propagation approaches.
arXiv Detail & Related papers (2022-03-04T19:00:45Z) - Near-Optimal Quantum Algorithms for Multivariate Mean Estimation [0.0]
We propose the first near-optimal quantum algorithm for estimating in Euclidean norm the mean of a vector-valued random variable.
We exploit a variety of additional algorithmic techniques such as amplitude amplification, the Bernstein-Vazirani algorithm, and quantum singular value transformation.
arXiv Detail & Related papers (2021-11-18T16:35:32Z) - 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)
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.