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Trapped Ion Quantum Computing

A Quantum Algorithm for the Finite Element Method

arXiv
Authors: Ahmad M. Alkadri, Tyler D. Kharazi, K. Birgitta Whaley, Kranthi K. Mandadapu

Year

2025

Paper ID

50975

Status

Preprint

Abstract Read

~2 min

Abstract Words

222

Citations

N/A

Abstract

The finite element method (FEM) is a cornerstone numerical technique for solving partial differential equations (PDEs). Here, we present textbf{Qu-FEM}, a fault-tolerant era quantum algorithm for the finite element method. In contrast to other quantum PDE solvers, Qu-FEM preserves the geometric flexibility of FEM by introducing two new primitives, the unit of interaction and the local-to-global indicator matrix, which enable the assembly of global finite element arrays with a constant-size linear combination of unitaries. We study the modified Poisson equation as an elliptic problem of interest, and provide explicit circuits for Qu-FEM in Cartesian domains. For problems with constant coefficients, our algorithm admits block-encodings of global arrays that require only {mathcal{O}}left\(d2 p2 nright\) Clifford+T gates for d-dimensional, order-p tensor product elements on grids with 2n degrees of freedom in each dimension, where n is the number of qubits representing the N=2n discrete grid points. For problems with spatially varying coefficients, we perform numerical integration directly on the quantum computer to assemble global arrays and force vectors. Dirichlet boundary conditions are enforced via the method of Lagrange multipliers, eliminating the need to modify the block-encodings that emerge from the assembly procedure. This work presents a framework for extending the geometric flexibility of quantum PDE solvers while preserving the possibility of a quantum advantage.

Why This Paper Matters

  • This paper contributes to the Trapped-Ion Quantum Computing research area in the Quantum Articles archive.
  • It adds a 2025 reference point for readers tracking recent quantum research.
  • The finite element method (FEM) is a cornerstone numerical technique for solving partial differential equations (PDEs).

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