Pulse-level Noise Mitigation on Quantum Applications

Abstract

Currently available quantum computers are prone to errors. Circuit optimization and error mitigation methods are needed to design quantum circuits to achieve better fidelity when executed on NISQ hardware. Dynamical decoupling (DD) is generally used to suppress the decoherence error and different DD strategies have been proposed. Moreover, the circuit fidelity can be improved by pulselevel optimization, such as creating hardware-native pulse-efficient gates. This paper implements all the popular DD sequences and evaluates their performances on IBM quantum chips with different characteristics for various well-known quantum applications. Also, we investigate combining DD with pulse-level optimization method and apply them to QAOA to solve Max-Cut problem. Based on the experimental results, we found that DD can be a benefit for only certain types of quantum algorithms, while the combination of DD and pulse-level optimization methods always has a positive impact. Finally, we provide several guidelines for users to learn how to use these pulse-level noise mitigation methods to build circuits for quantum applications with high fidelity.

Quantum optimal control in quantum technologies. Strategic report on current status, visions and goals for research in Europe

“…Grover's quantum search problem can be mapped to a time-optimal control problem, and then described through the Pontryagin Maximum Principle [387]. Furthermore, QOCT has been used to optimize drives in quantum algorithms such as QAOA [440] and quantum simulation, for example of a chiral effective-field theory [291] and of an extended Bose-Hubbard model [317].…”

Analyzing Strategies for Dynamical Decoupling Insertion on IBM Quantum Computer

“…(4) What conditions lead to idle qubits and what is the strategy to insert DD to idle qubits under different conditions? The first question was discussed in [17], where the authors comprehensively evaluated the performance [5]. They demonstrated that DD performs better when applied to a subset of qubits rather than all.…”

“…These two techniques need a large overhead of tuning DD sequences with extra circuits. Recently, Niu et al reported the impact of different DD strategies on well-known quantum applications to provide insights for application-specific error mitigation using DD technique [17]. However, these previous methods only concentrate on application-level DD insertion instead of understanding and analyzing the conditions that lead to idle qubits, hence decoherence errors.…”