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International Workshop on Computational Electronics

Optimization Algorithms for Josephson Qubits

Robert Roloff, Markus Wenin, W. Pötz

Published May 1, 2009• 0 citations
Publisher

Abstract

Superconducting nanoelectrical circuits are promising candidates for the physical implementation of the basic building block of a quantum computer, the qubit. We investigate how optimal control theory can be applied to optimize the dynamics of Josephson qubits. For the example of the charge qubit, several numerical methods are employed to search for external control fields which, by current technology, are realistic and induce the desired unitary time evolution within the system (i.e. the desired gate operation) as faithfully as possible in presence of dissipation, decoherence and leakage. Associated calculations which model the environment microscopically are time-intensive so that parallel computing methods are beneficial in the sampling over control fields. In particular, we discuss the performance of differential-evolution-algorithm based optimizations on a cluster. Using a simpler Lindblad model for environmental effects, we compare the performance of a conjugate-gradient approach to that of a genetic algorithm.

DOI
10.1109/iwce.2009.5091135

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Superconducting nanoelectrical circuits are promising candidates for the physical implementation of the basic building block of a quantum computer, the qubit. We investigate how optimal control theory can be applied to optimize the dynamics of Josephson qubits. For the example of the charge qubit, several numerical methods are employed to search for external control fields which, by current technology, are realistic and induce the desired unitary time evolution within the system (i.e. the desired gate operation) as faithfully as possible in presence of dissipation, decoherence and leakage. Associated calculations which model the environment microscopically are time-intensive so that parallel computing methods are beneficial in the sampling over control fields. In particular, we discuss the performance of differential-evolution-algorithm based optimizations on a cluster. Using a simpler Lindblad model for environmental effects, we compare the performance of a conjugate-gradient approach to that of a genetic algorithm.
A process tomography based optimization scheme for open quantum systems is used to determine the performance limits of Josephson charge qubits within current experimental means. The qubit is modeled microscopically as an open quantum system taking into account state leakage, as well as environment-induced dephasing based on experimental noise spectra. Within time-optimal control theory, we show that the competing requirements for suppression of state leakage and dephasing can be met by an external control of the effective qubit-environment interaction, yielding minimal gate fidelity losses of around $\ensuremath{\Delta}F\ensuremath{\approx}{10}^{\ensuremath{-}3}$ under typical experimental conditions.
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Methods of optimal control are applied to a model system of interacting two-level particles (e.g., spin-half atomic nuclei or electrons or two-level atoms) to produce high-fidelity quantum gates while simultaneously negating the detrimental effect of decoherence. One set of particles functions as the quantum information processor, whose evolution is controlled by a time-dependent external field. The other particles are not directly controlled and serve as an effective environment, coupling to which is the source of decoherence. The control objective is to generate target one- and two-qubit unitary gates in the presence of strong environmentally-induced decoherence and under physically motivated restrictions on the control field. The quantum-gate fidelity, expressed in terms of a novel state-independent distance measure, is maximized with respect to the control field using combined genetic and gradient algorithms. The resulting high-fidelity gates demonstrate the feasibility of precisely guiding the quantum evolution via the optimal control, even when the system complexity is exacerbated by environmental coupling. It is found that the gate duration has an important effect on the control mechanism and resulting fidelity. An analysis of the sensitivity of the gate performance to random variations in the system parameters reveals a significant degree of robustness attained by the optimal control solutions.
Typical for qubit realizations are two performance-limiting shortcomings: the physical system is not a perfect two-level system and it couples to an environment. In this work we investigate the limits of performance of the Josephson charge qubit due to the interplay of leakage into unwanted states and dissipative effects due to environmental noise within optimal control theory. For the example of the Hadamard transformation, we show that external control field-gate bias and magnetic flux, which perform the operation for the ideal qubit perfectly, show different robustness regarding leakage into unwanted states and against dissipation. Proper selection of the temporal evolution of gate bias and magnetic flux leads to performance improvements of typically 20% regarding dissipative effects with a predicted optimal fidelity of typically 98%, presuming perfect initial-state preparation and switching times of the order of 500 ps.
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