Hamiltonian simulation for hyperbolic partial differential equations by scalable quantum circuits
- URL: http://arxiv.org/abs/2402.18398v2
- Date: Sun, 8 Sep 2024 01:47:44 GMT
- Title: Hamiltonian simulation for hyperbolic partial differential equations by scalable quantum circuits
- Authors: Yuki Sato, Ruho Kondo, Ikko Hamamura, Tamiya Onodera, Naoki Yamamoto,
- Abstract summary: This paper presents a method that enables us to explicitly implement the quantum circuit for Hamiltonian simulation.
We show that the space and time complexities of the constructed circuit are exponentially smaller than those of conventional classical algorithms.
- Score: 1.6268784011387605
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Solving partial differential equations for extremely large-scale systems within a feasible computation time serves in accelerating engineering developments. Quantum computing algorithms, particularly the Hamiltonian simulations, present a potential and promising approach to achieve this purpose. Actually, there are several oracle-based Hamiltonian simulations with potential quantum speedup, but their detailed implementations and accordingly the detailed computational complexities are all unclear. This paper presents a method that enables us to explicitly implement the quantum circuit for Hamiltonian simulation; the key technique is the explicit gate construction of differential operators contained in the target partial differential equation discretized by the finite difference method. Moreover, we show that the space and time complexities of the constructed circuit are exponentially smaller than those of conventional classical algorithms. We also provide numerical experiments and an experiment on a real device for the wave equation to demonstrate the validity of our proposed method.
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) - Quantum computing of reacting flows via Hamiltonian simulation [13.377719901871027]
We develop the quantum spectral and finite difference methods for simulating reacting flows in periodic and general conditions.
The present quantum computing algorithms offer a one-shot'' solution for a given time without temporal discretization.
arXiv Detail & Related papers (2023-12-13T04:31:49Z) - Depth analysis of variational quantum algorithms for heat equation [0.0]
We consider three approaches to solve the heat equation on a quantum computer.
An exponential number of Pauli products in the Hamiltonian decomposition does not allow for the quantum speed up to be achieved.
The ansatz tree approach exploits an explicit form of the matrix what makes it possible to achieve an advantage over classical algorithms.
arXiv Detail & Related papers (2022-12-23T14:46:33Z) - Numerical Simulations of Noisy Quantum Circuits for Computational
Chemistry [51.827942608832025]
Near-term quantum computers can calculate the ground-state properties of small molecules.
We show how the structure of the computational ansatz as well as the errors induced by device noise affect the calculation.
arXiv Detail & Related papers (2021-12-31T16:33:10Z) - Time-dependent Hamiltonian Simulation of Highly Oscillatory Dynamics and
Superconvergence for Schr\"odinger Equation [2.973326951020451]
We propose a simple quantum algorithm for simulating highly oscillatory quantum dynamics.
To our knowledge, this is the first quantum algorithm that is both insensitive to the rapid changes of the time-dependent Hamiltonian and exhibits commutator scaling.
For the simulation of the Schr"odinger equation, our method exhibits superconvergence and achieves a surprising second order convergence rate.
arXiv Detail & Related papers (2021-11-04T18:50:36Z) - Algebraic Compression of Quantum Circuits for Hamiltonian Evolution [52.77024349608834]
Unitary evolution under a time dependent Hamiltonian is a key component of simulation on quantum hardware.
We present an algorithm that compresses the Trotter steps into a single block of quantum gates.
This results in a fixed depth time evolution for certain classes of Hamiltonians.
arXiv Detail & Related papers (2021-08-06T19:38:01Z) - Variational quantum algorithm based on the minimum potential energy for
solving the Poisson equation [7.620967781722716]
We present a variational quantum algorithm for solving the Poisson equation.
The proposed method defines the total potential energy of the Poisson equation as a Hamiltonian.
Because the number of terms is independent of the size of the problem, this method requires relatively few quantum measurements.
arXiv Detail & Related papers (2021-06-17T09:01:53Z) - Fixed Depth Hamiltonian Simulation via Cartan Decomposition [59.20417091220753]
We present a constructive algorithm for generating quantum circuits with time-independent depth.
We highlight our algorithm for special classes of models, including Anderson localization in one dimensional transverse field XY model.
In addition to providing exact circuits for a broad set of spin and fermionic models, our algorithm provides broad analytic and numerical insight into optimal Hamiltonian simulations.
arXiv Detail & Related papers (2021-04-01T19:06:00Z) - Fast and differentiable simulation of driven quantum systems [58.720142291102135]
We introduce a semi-analytic method based on the Dyson expansion that allows us to time-evolve driven quantum systems much faster than standard numerical methods.
We show results of the optimization of a two-qubit gate using transmon qubits in the circuit QED architecture.
arXiv Detail & Related papers (2020-12-16T21:43:38Z) - Low-depth Hamiltonian Simulation by Adaptive Product Formula [3.050399782773013]
Various Hamiltonian simulation algorithms have been proposed to efficiently study the dynamics of quantum systems on a quantum computer.
Here, we propose an adaptive approach to construct a low-depth time evolution circuit.
Our work sheds light on practical Hamiltonian simulation with noisy-intermediate-scale-quantum devices.
arXiv Detail & Related papers (2020-11-10T18:00:42Z) - Efficient classical simulation of random shallow 2D quantum circuits [104.50546079040298]
Random quantum circuits are commonly viewed as hard to simulate classically.
We show that approximate simulation of typical instances is almost as hard as exact simulation.
We also conjecture that sufficiently shallow random circuits are efficiently simulable more generally.
arXiv Detail & Related papers (2019-12-31T19:00:00Z)
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.