Experimental Determination of Multi-Qubit Ground State via a Cluster
Mean-Field Algorithm
- URL: http://arxiv.org/abs/2110.00941v1
- Date: Sun, 3 Oct 2021 07:12:45 GMT
- Title: Experimental Determination of Multi-Qubit Ground State via a Cluster
Mean-Field Algorithm
- Authors: Ze Zhan, Chongxin Run, Zhiwen Zong, Liang Xiang, Ying Fei, Wenyan Jin,
Zhilong Jia, Peng Duan, Jianlan Wu, Yi Yin, and Guoping Guo
- Abstract summary: A quantum eigensolver is designed under a multi-layer cluster mean-field algorithm.
The method is numerically verified in multi-spin chains and experimentally studied in a fully-connected three-spin network.
- Score: 1.9790421227325208
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: A quantum eigensolver is designed under a multi-layer cluster mean-field
(CMF) algorithm by partitioning a quantum system into spatially-separated
clusters. For each cluster, a reduced Hamiltonian is obtained after a partial
average over its environment cluster. The products of eigenstates from
different clusters construct a compressed Hilbert space, in which an effective
Hamiltonian is diagonalized to determine certain eigenstates of the whole
Hamiltonian. The CMF method is numerically verified in multi-spin chains and
experimentally studied in a fully-connected three-spin network, both yielding
an excellent prediction of their ground states.
Related papers
- Clustering Based on Density Propagation and Subcluster Merging [92.15924057172195]
We propose a density-based node clustering approach that automatically determines the number of clusters and can be applied in both data space and graph space.
Unlike traditional density-based clustering methods, which necessitate calculating the distance between any two nodes, our proposed technique determines density through a propagation process.
arXiv Detail & Related papers (2024-11-04T04:09:36Z) - Two-dimensional correlation propagation dynamics with a cluster discrete phase-space method [0.0]
Nonequilibrium dynamics of highly-controlled quantum systems is a challenging issue in statistical physics.
We develop a discrete phase-space approach for general SU($N$) spin systems that capture non-trivial quantum correlations inside each cluster.
We demonstrate that the cluster discrete truncated Wigner approximation can reproduce key results in a recent experiment on the correlation propagation dynamics in a two dimensional Bose-Hubbard system.
arXiv Detail & Related papers (2024-04-29T11:08:44Z) - Matrix-product-state-based band-Lanczos solver for quantum cluster
approaches [0.0]
We present a matrix-product state (MPS) based band-Lanczos method as solver for quantum cluster methods.
We show that our approach makes it possible to treat cluster geometries well beyond the reach of exact diagonalization methods.
arXiv Detail & Related papers (2023-10-16T19:59:21Z) - Boost clustering with Gaussian Boson Sampling: a full quantum approach [0.09437521840642138]
We propose a novel clustering approach based on Gaussian Boson Sampling (GBS)
We benchmark our approach with two well-known classical clustering algorithms.
Results show that our approach outperforms the two classical algorithms in two out of the three chosen metrics.
arXiv Detail & Related papers (2023-07-25T09:05:24Z) - Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model [79.46465138631592]
We devise an efficient algorithm that recovers clusters using the observed labels.
We present Instance-Adaptive Clustering (IAC), the first algorithm whose performance matches these lower bounds both in expectation and with high probability.
arXiv Detail & Related papers (2023-06-18T08:46:06Z) - DeepCluE: Enhanced Image Clustering via Multi-layer Ensembles in Deep
Neural Networks [53.88811980967342]
This paper presents a Deep Clustering via Ensembles (DeepCluE) approach.
It bridges the gap between deep clustering and ensemble clustering by harnessing the power of multiple layers in deep neural networks.
Experimental results on six image datasets confirm the advantages of DeepCluE over the state-of-the-art deep clustering approaches.
arXiv Detail & Related papers (2022-06-01T09:51:38Z) - Perfect Spectral Clustering with Discrete Covariates [68.8204255655161]
We propose a spectral algorithm that achieves perfect clustering with high probability on a class of large, sparse networks.
Our method is the first to offer a guarantee of consistent latent structure recovery using spectral clustering.
arXiv Detail & Related papers (2022-05-17T01:41:06Z) - Direct solution of multiple excitations in a matrix product state with
block Lanczos [62.997667081978825]
We introduce the multi-targeted density matrix renormalization group method that acts on a bundled matrix product state, holding many excitations.
A large number of excitations can be obtained at a small bond dimension with highly reliable local observables throughout the chain.
arXiv Detail & Related papers (2021-09-16T18:36:36Z) - Clustering by quantum annealing on three-level quantum elements qutrits [0.0]
Clustering is grouping of data by the proximity of some properties.
We report on the possibility of increasing the efficiency of clustering of points in a plane using artificial quantum neural networks.
arXiv Detail & Related papers (2021-02-18T08:06:44Z) - Machine Learning for Vibrational Spectroscopy via Divide-and-Conquer
Semiclassical Initial Value Representation Molecular Dynamics with
Application to N-Methylacetamide [56.515978031364064]
A machine learning algorithm for partitioning the nuclear vibrational space into subspaces is introduced.
The subdivision criterion is based on Liouville's theorem, i.e. best preservation of the unitary of the reduced dimensionality Jacobian determinant.
The algorithm is applied to the divide-and-conquer semiclassical calculation of the power spectrum of 12-atom trans-N-Methylacetamide.
arXiv Detail & Related papers (2021-01-11T14:47:33Z) - Variational Quantum Eigensolver for Approximate Diagonalization of
Downfolded Hamiltonians using Generalized Unitary Coupled Cluster Ansatz [0.0]
Generalized Unitary Coupled Cluster (GUCC) is a formalism for the diagonalization of downfolded/effective Hamiltonians in active spaces.
We consider their form defined by freezing core orbitals, which enables us to deal with larger systems.
We consider various solvers to identify solutions of the GUCC equations.
arXiv Detail & Related papers (2020-11-03T20:03:51Z)
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.