Hybrid quantum variational algorithm for simulating open quantum systems
with near-term devices
- URL: http://arxiv.org/abs/2008.05321v1
- Date: Wed, 12 Aug 2020 13:49:29 GMT
- Title: Hybrid quantum variational algorithm for simulating open quantum systems
with near-term devices
- Authors: Mahmoud Mahdian and H.Davoodi Yeganeh
- Abstract summary: Hybrid quantum-classical (HQC) algorithms make it possible to use near-term quantum devices supported by classical computational resources.
We develop an HQC algorithm using an efficient variational optimization approach to simulate open system dynamics.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Hybrid quantum-classical (HQC) algorithms make it possible to use near-term
quantum devices supported by classical computational resources by useful
control schemes. In this paper, we develop an HQC algorithm using an efficient
variational optimization approach to simulate open system dynamics under the
Noisy-Intermediate Scale Quantum(NISQ) computer. Using the time-dependent
variational principle (TDVP) method and extending it to McLachlan TDVP for
density matrix which involves minimization of Frobenius norm of the error, we
apply the unitary quantum circuit to obtain the time evolution of the open
quantum system in the Lindblad formalism. Finally, we illustrate the use of our
methods with detailed examples which are in good agreement with analytical
calculations.
Related papers
- Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits [63.733312560668274]
Given a quantum circuit containing d tunable RZ gates and G-d Clifford gates, can a learner perform purely classical inference to efficiently predict its linear properties?
We prove that the sample complexity scaling linearly in d is necessary and sufficient to achieve a small prediction error, while the corresponding computational complexity may scale exponentially in d.
We devise a kernel-based learning model capable of trading off prediction error and computational complexity, transitioning from exponential to scaling in many practical settings.
arXiv Detail & Related papers (2024-08-22T08:21:28Z) - Enabling Large-Scale and High-Precision Fluid Simulations on Near-Term Quantum Computers [17.27937804402152]
Quantum computational fluid dynamics (QCFD) offers a promising alternative to classical computational fluid dynamics (CFD)
This paper introduces a comprehensive QCFD method, including an iterative method "Iterative-QLS" that suppresses error in quantum linear solver.
We implement our method on a superconducting quantum computer, demonstrating successful simulations of steady Poiseuille flow and unsteady acoustic wave propagation.
arXiv Detail & Related papers (2024-06-10T07:21:23Z) - 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) - Variational Quantum Algorithms for Simulation of Lindblad Dynamics [0.0]
We introduce a variational hybrid classical-quantum algorithm to simulate the Lindblad master equation and its adjoint for time-evolving Markovian open quantum systems and quantum observables.
We design and optimize low-depth variational quantum circuits that efficiently capture the unitary and non-unitary dynamics of the solutions.
arXiv Detail & Related papers (2023-05-04T13:25:44Z) - 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) - Identification of topological phases using classically-optimized
variational quantum eigensolver [0.6181093777643575]
Variational quantum eigensolver (VQE) is regarded as a promising candidate of hybrid quantum-classical algorithm for quantum computers.
We propose classically-optimized VQE (co-VQE), where the whole process of the optimization is efficiently conducted on a classical computer.
In co-VQE, we only use quantum computers to measure nonlocal quantities after the parameters are optimized.
arXiv Detail & Related papers (2022-02-07T02:26:58Z) - 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) - 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) - Autoregressive Transformer Neural Network for Simulating Open Quantum Systems via a Probabilistic Formulation [5.668795025564699]
We present an approach for tackling open quantum system dynamics.
We compactly represent quantum states with autoregressive transformer neural networks.
Efficient algorithms have been developed to simulate the dynamics of the Liouvillian superoperator.
arXiv Detail & Related papers (2020-09-11T18:00:00Z) - Incoherent quantum algorithm dynamics of an open system with near-term
devices [0.0]
Hybrid quantum-classical algorithms are among the most promising systems to implement quantum computing.
We investigate a quantum dynamics algorithm for the density matrix obeying the von Neumann equation.
We consider the dynamics of the ensemble-averaged of disordered quantum systems.
arXiv Detail & Related papers (2020-08-12T14:22:42Z)
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.