Accelerating Quantum Optimal Control of Multi-Qubit Systems with Symmetry-Based Hamiltonian Transformations

TL;DR

This paper introduces a symmetry-based Hamiltonian transformation method that significantly accelerates quantum optimal control calculations for large multi-qubit systems, enabling faster and more efficient quantum computing applications.

Contribution

The authors develop a novel approach leveraging symmetry to decompose and block-diagonalize Hamiltonians, drastically reducing computational complexity and runtime for multi-qubit quantum control.

Findings

Reduces Hamiltonian size from 2^n to O(n) or O(2^n/n) under symmetry.

Achieves orders-of-magnitude speedup in quantum control calculations.

Maintains accuracy comparable to conventional methods.

Abstract

We present a novel, computationally efficient approach to accelerate quantum optimal control calculations of large multi-qubit systems used in a variety of quantum computing applications. By leveraging the intrinsic symmetry of finite groups, the Hilbert space can be decomposed and the Hamiltonians block-diagonalized to enable extremely fast quantum optimal control calculations. Our approach reduces the Hamiltonian size of an $n$-qubit system from 2^n by 2^n to O(n by n) or O((2^n / n) by (2^n / n)) under Sn or Dn symmetry, respectively. Most importantly, this approach reduces the computational runtime of qubit optimal control calculations by orders of magnitude while maintaining the same accuracy as the conventional method. As prospective applications, we show that (1) symmetry-protected subspaces can be potential platforms for quantum error suppression and simulation of other quantum Hamiltonians, and (2) Lie-Trotter-Suzuki decomposition approaches can generalize our method to a general variety of multi-qubit systems.