A hybrid classical-quantum algorithm for solution of nonlinear ordinary
differential equations
- URL: http://arxiv.org/abs/2112.00602v2
- Date: Thu, 26 May 2022 16:56:31 GMT
- Title: A hybrid classical-quantum algorithm for solution of nonlinear ordinary
differential equations
- Authors: Alok Shukla and Prakash Vedula
- Abstract summary: A hybrid classical-quantum approach for the solution of nonlinear ordinary differential equations is proposed.
The computation of the Walsh-Hadamard transform of arbitrary vectors is central to this hybrid approach.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: A hybrid classical-quantum approach for the solution of nonlinear ordinary
differential equations using Walsh-Hadamard basis functions is proposed.
Central to this hybrid approach is the computation of the Walsh-Hadamard
transform of arbitrary vectors, which is enabled in our framework using quantum
Hadamard gates along with state preparation, shifting, scaling, and measurement
operations. It is estimated that the proposed hybrid classical-quantum approach
for the Walsh-Hadamard transform of an input vector of size N results in a
considerably lower computational complexity (O(N) operations) compared to the
Fast Walsh-Hadamard transform (O(N log2(N)) operations). This benefit will also
be relevant in the context of the proposed hybrid classical-quantum approach
for the solution of nonlinear differential equations. Comparisons of results
corresponding to the proposed hybrid classical-quantum approach and a purely
classical approach for the solution of nonlinear differential equations (for
cases involving one and two dependent variables) were found to be satisfactory.
Some new perspectives relevant to the natural ordering of Walsh functions (in
the context of both classical and hybrid approaches for the solution of
nonlinear differential equations) and representation theory of finite groups
are also presented here.
Related papers
- Towards Variational Quantum Algorithms for generalized linear and nonlinear transport phenomena [0.0]
This article proposes a Variational Quantum Algorithm to solve linear and nonlinear thermofluid dynamic transport equations.<n>The hybrid classical-quantum framework is applied to problems governed by the heat, wave, and Burgers' equation in combination with different engineering boundary conditions.
arXiv Detail & Related papers (2024-11-22T13:39:49Z) - A hybrid quantum solver for the Lorenz system [0.2770822269241974]
We develop a hybrid classical-quantum method for solving the Lorenz system.
We use the forward Euler method to discretize the system in time, transforming it into a system of equations.
We present numerical results comparing the hybrid method with the classical approach for solving the Lorenz system.
arXiv Detail & Related papers (2024-10-20T15:20:28Z) - H-DES: a Quantum-Classical Hybrid Differential Equation Solver [0.0]
We introduce an original hybrid quantum-classical algorithm for solving systems of differential equations.
The algorithm relies on a spectral method, which involves encoding the solution functions in the amplitudes of the quantum states generated by different parametrized circuits.
arXiv Detail & Related papers (2024-10-01T23:47:41Z) - Towards Efficient Quantum Hybrid Diffusion Models [68.43405413443175]
We propose a new methodology to design quantum hybrid diffusion models.
We propose two possible hybridization schemes combining quantum computing's superior generalization with classical networks' modularity.
arXiv Detail & Related papers (2024-02-25T16:57:51Z) - An Optimization-based Deep Equilibrium Model for Hyperspectral Image
Deconvolution with Convergence Guarantees [71.57324258813675]
We propose a novel methodology for addressing the hyperspectral image deconvolution problem.
A new optimization problem is formulated, leveraging a learnable regularizer in the form of a neural network.
The derived iterative solver is then expressed as a fixed-point calculation problem within the Deep Equilibrium framework.
arXiv Detail & Related papers (2023-06-10T08:25:16Z) - Time complexity analysis of quantum algorithms via linear
representations for nonlinear ordinary and partial differential equations [31.986350313948435]
We construct quantum algorithms to compute the solution and/or physical observables of nonlinear ordinary differential equations.
We compare the quantum linear systems algorithms based methods and the quantum simulation methods arising from different numerical approximations.
arXiv Detail & Related papers (2022-09-18T05:50:23Z) - Quantum Kernel Methods for Solving Differential Equations [21.24186888129542]
We propose several approaches for solving differential equations (DEs) with quantum kernel methods.
We compose quantum models as weighted sums of kernel functions, where variables are encoded using feature maps and model derivatives are represented.
arXiv Detail & Related papers (2022-03-16T18:56:35Z) - Twisted hybrid algorithms for combinatorial optimization [68.8204255655161]
Proposed hybrid algorithms encode a cost function into a problem Hamiltonian and optimize its energy by varying over a set of states with low circuit complexity.
We show that for levels $p=2,ldots, 6$, the level $p$ can be reduced by one while roughly maintaining the expected approximation ratio.
arXiv Detail & Related papers (2022-03-01T19:47:16Z) - A Variational Inference Approach to Inverse Problems with Gamma
Hyperpriors [60.489902135153415]
This paper introduces a variational iterative alternating scheme for hierarchical inverse problems with gamma hyperpriors.
The proposed variational inference approach yields accurate reconstruction, provides meaningful uncertainty quantification, and is easy to implement.
arXiv Detail & Related papers (2021-11-26T06:33:29Z) - Quantum Approximate Optimization Algorithm Based Maximum Likelihood
Detection [80.28858481461418]
Recent advances in quantum technologies pave the way for noisy intermediate-scale quantum (NISQ) devices.
Recent advances in quantum technologies pave the way for noisy intermediate-scale quantum (NISQ) devices.
arXiv Detail & Related papers (2021-07-11T10:56:24Z) - A Discrete Variational Derivation of Accelerated Methods in Optimization [68.8204255655161]
We introduce variational which allow us to derive different methods for optimization.
We derive two families of optimization methods in one-to-one correspondence.
The preservation of symplecticity of autonomous systems occurs here solely on the fibers.
arXiv Detail & Related papers (2021-06-04T20:21:53Z) - Hybrid Quantum Annealing via Molecular Dynamics [0.0]
We introduce a Hamiltonian dynamics of the classical flux variables associated with the quantum spins of the transverse-field Ising model.
Molecular dynamics of the classical flux can be used as a powerful preconditioner to sort out the frozen and ambivalent spins for quantum annealers.
arXiv Detail & Related papers (2020-04-08T12:34:24Z) - Cross Entropy Hyperparameter Optimization for Constrained Problem
Hamiltonians Applied to QAOA [68.11912614360878]
Hybrid quantum-classical algorithms such as Quantum Approximate Optimization Algorithm (QAOA) are considered as one of the most encouraging approaches for taking advantage of near-term quantum computers in practical applications.
Such algorithms are usually implemented in a variational form, combining a classical optimization method with a quantum machine to find good solutions to an optimization problem.
In this study we apply a Cross-Entropy method to shape this landscape, which allows the classical parameter to find better parameters more easily and hence results in an improved performance.
arXiv Detail & Related papers (2020-03-11T13:52:41Z)
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.