Abstract

We consider the optimal control problem of determining electromagnetic pulses for implementing logical gates in a closed quantum system, where the Hamiltonian models the dynamics of coupled superconducting qudits. The quantum state is governed by Schrödinger's equation, which we formulate in terms of the real and imaginary parts of the state vector and solve by the Störmer--Verlet scheme, which is a symplectic partitioned Runge--Kutta method. A novel parameterization of the control functions based on B-splines with carrier waves is introduced. The carrier waves are used to trigger the resonant frequencies in the system Hamiltonian, and the B-spline functions specify their amplitude and phase. This approach allows the number of control parameters to be independent of, and significantly smaller than, the number of time steps for integrating Schrödinger's equation. We present numerical examples of how the proposed technique can be combined with an interior point limited memory BFGS algorithm for realizing quantum gates and generalize our approach to calculate risk-neutral controls that are resilient to noise in the Hamiltonian model. The proposed method is also shown to compare favorably with QuTiP/pulse_optim and Grape-TensorFlow.

Keywords

  1. quantum control
  2. B-splines
  3. symplectic Runge--Kutta method
  4. ODE-constrained optimization
  5. quantum computing

MSC codes

  1. 49M25
  2. 65D07
  3. 65L06
  4. 81Q93

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Information & Authors

Information

Published In

cover image SIAM Journal on Scientific Computing
SIAM Journal on Scientific Computing
Pages: A3592 - A3616
ISSN (online): 1095-7197

History

Submitted: 28 June 2021
Accepted: 11 August 2022
Published online: 14 November 2022

Keywords

  1. quantum control
  2. B-splines
  3. symplectic Runge--Kutta method
  4. ODE-constrained optimization
  5. quantum computing

MSC codes

  1. 49M25
  2. 65D07
  3. 65L06
  4. 81Q93

Authors

Affiliations

Funding Information

DOE Office of Advanced Scientific Computing Research : 2019-LLNL-SCW-1683
LLNL Laboratory Directed Research and Development : 20-ERD-028

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