Efficient Algorithms for Approximating Quantum Partition Functions at
Low Temperature
- URL: http://arxiv.org/abs/2201.06533v2
- Date: Fri, 13 Oct 2023 00:17:28 GMT
- Title: Efficient Algorithms for Approximating Quantum Partition Functions at
Low Temperature
- Authors: Tyler Helmuth, Ryan L. Mann
- Abstract summary: We establish an efficient approximation algorithm for the partition functions of a class of quantum spin systems at low temperature.
Our algorithm is based on combining the contour representation of quantum spin systems of this type due to Borgs, Koteck'y, and Ueltschi.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We establish an efficient approximation algorithm for the partition functions
of a class of quantum spin systems at low temperature, which can be viewed as
stable quantum perturbations of classical spin systems. Our algorithm is based
on combining the contour representation of quantum spin systems of this type
due to Borgs, Koteck\'y, and Ueltschi with the algorithmic framework developed
by Helmuth, Perkins, and Regts, and Borgs et al.
Related papers
- 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) - Variational quantum algorithm for non-Markovian quantum dynamics [5.19702850808286]
We have developed a variational quantum algorithm that is capable of simulating non-Markovian quantum dynamics.
The algorithm naturally fits into the parallel computing platform of the NISQ devices and is well suited for anharmonic system-bath interactions and multi-state systems.
arXiv Detail & Related papers (2024-11-30T09:25:23Z) - Kernel Descent -- a Novel Optimizer for Variational Quantum Algorithms [0.0]
We introduce kernel descent, a novel algorithm for minimizing the functions underlying variational quantum algorithms.
In particular, we showcase scenarios in which kernel descent outperforms gradient descent and quantum analytic descent.
Kernel descent sets itself apart with its employment of reproducing kernel Hilbert space techniques in the construction of the local approximations.
arXiv Detail & Related papers (2024-09-16T13:10:26Z) - Quantum quench dynamics as a shortcut to adiabaticity [31.114245664719455]
We develop and test a quantum algorithm in which the incorporation of a quench step serves as a remedy to the diverging adiabatic timescale.
Our experiments show that this approach significantly outperforms the adiabatic algorithm.
arXiv Detail & Related papers (2024-05-31T17:07:43Z) - Non-equilibrium quantum Monte Carlo algorithm for stabilizer Renyi entropy in spin systems [0.552480439325792]
Quantum magic, or nonstabilizerness, provides a crucial characterization of quantum systems.
We propose a novel and efficient algorithm for computing stabilizer R'enyi entropy, one of the measures for quantum magic, in spin systems with sign-problem free Hamiltonians.
arXiv Detail & Related papers (2024-05-29T23:59:02Z) - Utilizing Quantum Processor for the Analysis of Strongly Correlated Materials [34.63047229430798]
This study introduces a systematic approach for analyzing strongly correlated systems by adapting the conventional quantum cluster method to a quantum circuit model.
We have developed a more concise formula for calculating the cluster's Green's function, requiring only real-number computations on the quantum circuit instead of complex ones.
arXiv Detail & Related papers (2024-04-03T06:53:48Z) - Quantum Subroutine for Variance Estimation: Algorithmic Design and Applications [80.04533958880862]
Quantum computing sets the foundation for new ways of designing algorithms.
New challenges arise concerning which field quantum speedup can be achieved.
Looking for the design of quantum subroutines that are more efficient than their classical counterpart poses solid pillars to new powerful quantum algorithms.
arXiv Detail & Related papers (2024-02-26T09:32:07Z) - Algorithmic Cluster Expansions for Quantum Problems [0.0]
We establish a general framework for developing approximation algorithms for a class of counting problems.
We apply our framework to approximating probability amplitudes of a class of quantum circuits close to the identity.
We show that our algorithmic condition is almost optimal for expectation values and optimal for thermal expectation values in the sense of zero freeness.
arXiv Detail & Related papers (2023-06-15T09:11:48Z) - Optimal quantum control via genetic algorithms for quantum state
engineering in driven-resonator mediated networks [68.8204255655161]
We employ a machine learning-enabled approach to quantum state engineering based on evolutionary algorithms.
We consider a network of qubits -- encoded in the states of artificial atoms with no direct coupling -- interacting via a common single-mode driven microwave resonator.
We observe high quantum fidelities and resilience to noise, despite the algorithm being trained in the ideal noise-free setting.
arXiv Detail & Related papers (2022-06-29T14:34:00Z) - 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) - Efficient Algorithms for Approximating Quantum Partition Functions [0.0]
We establish a time approximation algorithm for partition functions of quantum spin models at high temperature.
Our main contribution is a simple and slightly sharper analysis for the case of pairwise interactions on bounded-degree graphs.
arXiv Detail & Related papers (2020-04-24T07:21:43Z)
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.