QAOA-MC: Markov chain Monte Carlo enhanced by Quantum Alternating
Operator Ansatz
- URL: http://arxiv.org/abs/2305.08789v1
- Date: Mon, 15 May 2023 16:47:31 GMT
- Title: QAOA-MC: Markov chain Monte Carlo enhanced by Quantum Alternating
Operator Ansatz
- Authors: Yuichiro Nakano, Hideaki Hakoshima, Kosuke Mitarai, Keisuke Fujii
- Abstract summary: We propose the use of Quantum Alternating Operator Ansatz (QAOA) for quantum-enhanced Monte Carlo.
This work represents an important step toward realizing practical quantum advantage with currently available quantum computers.
- Score: 0.6181093777643575
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Quantum computation is expected to accelerate certain computational task over
classical counterpart. Its most primitive advantage is its ability to sample
from classically intractable probability distributions. A promising approach to
make use of this fact is the so-called quantum-enhanced Markov chain Monte
Carlo (MCMC) [D. Layden, et al., arXiv:2203.12497 (2022)] which uses outputs
from quantum circuits as the proposal distributions. In this work, we propose
the use of Quantum Alternating Operator Ansatz (QAOA) for quantum-enhanced MCMC
and provide a strategy to optimize its parameter to improve convergence speed
while keeping its depth shallow. The proposed QAOA-type circuit is designed to
satisfy the specific constraint which quantum-enhanced MCMC requires with
arbitrary parameters. Through our extensive numerical analysis, we find a
correlation in certain parameter range between an experimentally measurable
value, acceptance rate of MCMC, and the spectral gap of the MCMC transition
matrix, which determines the convergence speed. This allows us to optimize the
parameter in the QAOA circuit and achieve quadratic speedup in convergence.
Since MCMC is used in various areas such as statistical physics and machine
learning makes, this work represents an important step toward realizing
practical quantum advantage with currently available quantum computers through
quantum-enhanced MCMC.
Related papers
- Quantum Simulation for Dynamical Transition Rates in Open Quantum Systems [0.0]
We introduce a novel and efficient quantum simulation method to compute dynamical transition rates in Markovian open quantum systems.
Our new approach holds the potential to surpass the bottlenecks of current quantum chemical research.
arXiv Detail & Related papers (2024-12-23T02:53:05Z) - Quantum-enhanced Markov Chain Monte Carlo for systems larger than your Quantum Computer [0.9208007322096533]
We introduce a framework to coarse grain the algorithm in such a way that the quantum computation can be performed using considerably smaller quantum computers.
Our method can be easily combined with other classical and quantum techniques and is adaptable to various quantum hardware specifications.
arXiv Detail & Related papers (2024-05-07T12:04:07Z) - Quantum Dynamical Hamiltonian Monte Carlo [0.0]
A ubiquitous problem in machine learning is sampling from probability distributions that we only have access to via their log probability.
We extend the well-known Hamiltonian Monte Carlo (HMC) method for Chain Monte Carlo (MCMC) sampling to leverage quantum computation in a hybrid manner.
arXiv Detail & Related papers (2024-03-04T07:08:23Z) - Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the
Quantum Many-Body Schr\"odinger Equation [56.9919517199927]
"Wasserstein Quantum Monte Carlo" (WQMC) uses the gradient flow induced by the Wasserstein metric, rather than Fisher-Rao metric, and corresponds to transporting the probability mass, rather than teleporting it.
We demonstrate empirically that the dynamics of WQMC results in faster convergence to the ground state of molecular systems.
arXiv Detail & Related papers (2023-07-06T17:54:08Z) - A self-consistent field approach for the variational quantum
eigensolver: orbital optimization goes adaptive [52.77024349608834]
We present a self consistent field approach (SCF) within the Adaptive Derivative-Assembled Problem-Assembled Ansatz Variational Eigensolver (ADAPTVQE)
This framework is used for efficient quantum simulations of chemical systems on nearterm quantum computers.
arXiv Detail & Related papers (2022-12-21T23:15:17Z) - Decomposition of Matrix Product States into Shallow Quantum Circuits [62.5210028594015]
tensor network (TN) algorithms can be mapped to parametrized quantum circuits (PQCs)
We propose a new protocol for approximating TN states using realistic quantum circuits.
Our results reveal one particular protocol, involving sequential growth and optimization of the quantum circuit, to outperform all other methods.
arXiv Detail & Related papers (2022-09-01T17:08:41Z) - Squeezing and quantum approximate optimization [0.6562256987706128]
Variational quantum algorithms offer fascinating prospects for the solution of optimization problems using digital quantum computers.
However, the achievable performance in such algorithms and the role of quantum correlations therein remain unclear.
We show numerically as well as on an IBM quantum chip how highly squeezed states are generated in a systematic procedure.
arXiv Detail & Related papers (2022-05-20T18:00:06Z) - Optimal quantum kernels for small data classification [0.0]
We show an algorithm for constructing quantum kernels for support vector machines that adapts quantum gate sequences to data.
The performance of the resulting quantum models for classification problems with a small number of training points significantly exceeds that of optimized classical models.
arXiv Detail & Related papers (2022-03-25T18:26:44Z) - Circuit Symmetry Verification Mitigates Quantum-Domain Impairments [69.33243249411113]
We propose circuit-oriented symmetry verification that are capable of verifying the commutativity of quantum circuits without the knowledge of the quantum state.
In particular, we propose the Fourier-temporal stabilizer (STS) technique, which generalizes the conventional quantum-domain formalism to circuit-oriented stabilizers.
arXiv Detail & Related papers (2021-12-27T21:15:35Z) - Fast Swapping in a Quantum Multiplier Modelled as a Queuing Network [64.1951227380212]
We propose that quantum circuits can be modeled as queuing networks.
Our method is scalable and has the potential speed and precision necessary for large scale quantum circuit compilation.
arXiv Detail & Related papers (2021-06-26T10:55:52Z) - Error mitigation and quantum-assisted simulation in the error corrected
regime [77.34726150561087]
A standard approach to quantum computing is based on the idea of promoting a classically simulable and fault-tolerant set of operations.
We show how the addition of noisy magic resources allows one to boost classical quasiprobability simulations of a quantum circuit.
arXiv Detail & Related papers (2021-03-12T20:58:41Z)
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.