عنوان

Quantum Algorithms for Differential Equations

Number

TLpq2384571537

.Language of Text, Soundtrack etc

انگلیسی

Title Proper

Quantum Algorithms for Differential Equations

General Material Designation

[Thesis]

First Statement of Responsibility

Ostrander, Aaron Jacob

Subsequent Statement of Responsibility

Childs, Andrew

Name of Publisher, Distributor, etc.

University of Maryland, College Park

Date of Publication, Distribution, etc.

2019

Specific Material Designation and Extent of Item

108

Dissertation or thesis details and type of degree

Ph.D.

Body granting the degree

University of Maryland, College Park

Text preceding or following the note

2019

Text of Note

This thesis describes quantum algorithms for Hamiltonian simulation, ordinary differential equations (ODEs), and partial differential equations (PDEs). Product formulas are used to simulate Hamiltonians which can be expressed as a sum of terms which can each be simulated individually. By simulating each of these terms in sequence, the net effect approximately simulates the total Hamiltonian. We find that the error of product formulas can be improved by randomizing over the order in which the Hamiltonian terms are simulated. We prove that this approach is asymptotically better than ordinary product formulas and present numerical comparisons for small numbers of qubits. The ODE algorithm applies to the initial value problem for time-independent first order linear ODEs. We approximate the propagator of the ODE by a truncated Taylor series, and we encode the initial value problem in a large linear system. We solve this linear system with a quantum linear system algorithm (QLSA) whose output we perform a post-selective measurement on. The resulting state encodes the solution to the initial value problem. We prove that our algorithm is asymptotically optimal with respect to several system parameters. The PDE algorithms apply the finite difference method (FDM) to Poisson's equation, the wave equation, and the Klein-Gordon equation. We use high order FDM approximations of the Laplacian operator to develop linear systems for Poisson's equation in cubic volumes under periodic, Neumann, and Dirichlet boundary conditions. Using QLSAs, we output states encoding solutions to Poisson's equation. We prove that our algorithm is exponentially faster with respect to the spatial dimension than analogous classical algorithms. We also consider how high order Laplacian approximations can be used for simulating the wave and Klein-Gordon equations. We consider under what conditions it suffices to use Hamiltonian simulation for time evolution, and we propose an algorithm for these cases that uses QLSAs for state preparation and post-processing.

Computer science

Quantum physics

Childs, Andrew

Ostrander, Aaron Jacob

Electronic name

p

[Thesis]

276903

a

Y