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arXiv:2403.00298 · Physical Review Applied

Multiple classical noise mitigation by multiobjective robust quantum optimal control

Bowen Shao, Xiaodong Yang, Ran Liu, Yue Zhai, Dawei Lu, Tao Xin, Jun Li

Published Mar 20, 2024• 4 citations
arXivHTMLPDF

Abstract

High-quality control is a fundamental requirement for quantum computation, but practically it is often hampered by the presence of various types of noises, which can be static or time dependent. In many realistic scenarios, multiple noise sources coexist, and their resulting noise effects need to be corrected to a sufficient order, posing significant challenges for the design of effective robust control methods. Here, we explore the method of robust quantum optimal control to generally tackle the problem of resisting multiple noises from a complicated noise environment. Specifically, we confine our analysis to classical stochastic noises that can be described by classical noise models. This method employs a gradient-based multiobjective optimization algorithm to maximize the control figure of merit, and meanwhile to minimize the perturbative effects of the noises that are allowed for. To verify its effectiveness, we apply this method to a number of examples, including robust entangling gate in a trapped-ion system and robust controlled-$Z$ gate in superconducting qubits, under commonly encountered static and time-dependent noises. Our simulation results reveal that robust optimal control can find smooth, robust pulses that can simultaneously resist several noises and thus achieve high-fidelity gates. Therefore, we expect that this method will find wide applications on current noisy quantum computing devices.

DOI
10.1103/physrevapplied.21.034042

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High-quality control is a fundamental requirement for quantum computation, but practically it is often hampered by the presence of various types of noises, which can be static or time dependent. In many realistic scenarios, multiple noise sources coexist, and their resulting noise effects need to be corrected to a sufficient order, posing significant challenges for the design of effective robust control methods. Here, we explore the method of robust quantum optimal control to generally tackle the problem of resisting multiple noises from a complicated noise environment. Specifically, we confine our analysis to classical stochastic noises that can be described by classical noise models. This method employs a gradient-based multiobjective optimization algorithm to maximize the control figure of merit, and meanwhile to minimize the perturbative effects of the noises that are allowed for. To verify its effectiveness, we apply this method to a number of examples, including robust entangling gate in a trapped-ion system and robust controlled-ZZZ gate in superconducting qubits, under commonly encountered static and time-dependent noises. Our simulation results reveal that robust optimal control can find smooth, robust pulses that can simultaneously resist several noises and thus achieve high-fidelity gates. Therefore, we expect that this method will find wide applications on current noisy quantum computing devices.
Resisting diverse noise effects is crucial for the accurate manipulation of quantum systems. For static or slowly varying noises, many efficient noise mitigation strategies have been developed, such as composite pulses and dynamical decoupling. However, for fast fluctuating noise in the Markovian limit, whether and to what extent coherent quantum control can enhance quantum engineering tasks remains unclear and less explored. Here, we propose a robust quantum optimal control method to tackle Markovian noises. The basic idea is that, regarding the Markovian noise channel as perturbation, we quantitatively characterize the noise-induced error evolution by the perturbative expansion term, and then take them as the objective functions to be suppressed. During optimization, the optimal controls are obtained by maximizing the control target function and meanwhile minimizing the perturbative terms due to Markovian noise order by order. As demonstration examples, we first apply our method to quantum state transfer tasks on two-level and three-level $\mathrm{\ensuremath{\Lambda}}$ systems, then use it to design quantum gates in two-level and three-level ladder systems, all under Markovian noises. The simulation results illustrate that our method can notably enhance quantum state transfer fidelities and have very limited improvement on gate fidelities. The method presented here is versatile and can be extended to enhance the performance of various control tasks under Markovian noise in multilevel or multiqubit quantum systems.
The effective use of current Noisy Intermediate-Scale Quantum (NISQ) devices is often limited by the noise which is caused by interaction with the environment and affects the fidelity of quantum gates. In transmon qubit systems, the quantum gate fidelity can be improved by applying control pulses that can minimize the effects of the environmental noise. In this work, we employ physics-guided quantum optimal control strategies to design optimal pulses driving quantum gates on superconducting qubit systems. We test our results by conducting experiments on the IBM quantum hardware using their OpenPulse API. We compare the performance of our pulse-optimized quantum gates against the default quantum gates and show that the optimized pulses improve the fidelity of the quantum gates, in particular the single-qubit gates. We discuss the challenges we encountered in our work and point to possible future improvements.
Creating robust quantum operations is a major challenge in the current noisy intermediate-scale quantum computing era. Recently, the importance of noise-resilient control methods has become more pronounced in the field. Ordinarily, noisy quantum systems are described by the Lindblad equation. However, minimizing noise susceptibility using this equation has proven challenging because of its irreversibility. In this study, we propose a method for creating robust pulses based on the stochastic Schr\"odinger equation. This equation describes individual noise realizations under any colored noise process, contrary to the Lindblad equation, which describes mean system behavior under white noise. Using stochastic optimal control techniques, our method, fidelity-enhanced variational quantum optimal control, is able to construct higher-fidelity paths than its nonstochastic counterpart. By accounting for both environmental noise sources as well as noise sources inherent to the control system, highly significant increases in fidelity are noted for both single- and multiple-qubit state preparations.
Quantum systems are inherently sensitive to environmental noise and imperfections in external control fields, which pose a significant challenge for the practical implementation of quantum technologies. These noise sources degrade the fidelity of quantum gates, making their mitigation a key requirement for realizing reliable quantum computing. In this study, we apply Optimal Control Theory (OCT) within a thermodynamically consistent Markovian framework to design high-fidelity quantum gates in the presence of thermal relaxation. Such a description is essential for realistic modeling and optimization of noisy quantum gates in near-term quantum technologies, where strong control fields and thermal environments act simultaneously. Our approach combines OCT with a control-dependent dissipative generator derived from the non-adiabatic master equation framework based on time-dependent invariants of the free evolution. As a result, the driving fields modify both the unitary and dissipative parts of the evolution. We implement the scheme for one- and two-qubit gates embedded in larger Hilbert spaces and compare direct-control and ancilla-assisted architectures. Using logical-subspace-resolved diagnostics, we quantify how the optimized dynamics redistributes the dissipative action between logical and ancillary sectors in the model systems studied here. In particular, we show that ancilla-assisted control can reduce the effective thermal-noise burden on the logical subspace in the relevant parameter regime, while direct control remains the most effective route when available. High-precision propagation of the full open-system dynamics reveals substantial fidelity improvements, in some cases by orders of magnitude, while clarifying the limits of mitigation at large relaxation rates and temperatures.
Quantum computers can significantly speed up the solution of certain classical tasks and even provide solutions to problems that are classically intractable. However, achieving this requires a fault-tolerant architecture with components and quantum operations (gates) whose physical error rates are below a specific threshold. Advanced quantum control methods can suppress environmental noise and implement below-threshold gates, but there are infinitely many ways to do so. These methods can rely entirely on analytical solutions or combine them with numerical optimization, where pulse properties are treated as optimization goals. Analytical constraints are always met exactly, but numerically optimized goals may only be satisfied approximately, leading to tradeoffs. Therefore, a modular analytical framework is needed that fixes some objectives in advance while optimizing only a selected subset. In this dissertation, I employ Space Curve Quantum Control (SCQC), a method that generates noise-resistant quantum gates using differential geometry. In SCQC, a space curve's global geometric properties dictate the gate's noise-robustness, while the controls that realize it are extracted from its local quantities. The first part of the dissertation is devoted to extending SCQC for arbitrary and simultaneous noise suppression, with experimentally-friendly pulses. I first derive the geometric conditions and curve examples for suppressing two separate noise types simultaneously. Then, I extend SCQC by deriving the adjoint representation equations of the associated quantum evolution. This allows one to describe the entire control design in terms of space curve elements and propose a systematic control design approach called the Bézier Ansatz for Robust Quantum (BARQ) control method. BARQ can encode the target gate upfront and allow optimization only for noise-robustness properties. This approach solves the usually unavoidable tradeoff between gate fidelity and noise-sensitivity and is capable of producing control pulses with experimentally-friendly features. The second part of the dissertation applies BARQ in two leading qubit modalities. I first describe my participation in experiments on IBM's superconducting devices, where doubly-robust BARQ pulses demonstrate at least one order-of-magnitude error reduction in the presence of engineered noise. The second platform is a four-qubit trapped-ion register hosted in the Quantum Scientific Computing Open User Testbed (QSCOUT) ecosystem. I show that utilizing BARQ pulses can reduce gate errors up to two times and effectively combat motion-induced decoherence.
High-fidelity quantum gates are crucial for achieving fault-tolerant quantum computing; however, decoherence significantly reduces gate fidelities during long operation times. Although optimal control techniques can theoretically minimize these operation times, they often neglect realistic uncertainties in system parameters. In this work, we demonstrate that by using robust optimal control strategies, the cross-resonance gate in superconducting systems can be operated within 64 ns, achieving fidelities of [Formula: see text] while maintaining robustness against up to 10% uncertainty in a single parameter. Alternatively, by extending the control time to 71 ns, we achieve fidelities of [Formula: see text] with robustness against up to 3% uncertainty. Our results identify the minimal control times attainable with experimentally feasible pulses and system parameters, as well as the maximum allowable static parameter error for high-fidelity operations. Furthermore, we demonstrate simultaneous robustness against both static and time-dependent errors by generating 100 ns control pulses ([Formula: see text]) that maintain robustness against 10% static parameter error and time-dependent parameter fluctuations two orders of magnitude stronger than typical experimental noise. These findings demonstrate a viable open-loop strategy for implementing fast, high-fidelity quantum gates in the presence of realistic system uncertainties that would otherwise degrade conventional control pulses.