Effects of Dynamical Decoupling and Pulse-level Optimizations on IBM Quantum Computers

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 pulse-level 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 noise mitigation methods to build circuits for quantum applications with high fidelity on IBM quantum computers.

in IEEE Transactions on Quantum Engineering, 2022

References in corpus (7)

• A Quantum Approximate Optimization Algorithm
• Decoherence-protected quantum gates for a hybrid solid-state spin register
• Robust dynamical decoupling for quantum computing and quantum memory
• Software Mitigation of Crosstalk on Noisy Intermediate-Scale Quantum Computers
• Optimized Compilation of Aggregated Instructions for Realistic Quantum Computers
• Optimal pulse spacing for dynamical decoupling in the presence of a purely-dephasing spin-bath
• ADAPT: Mitigating Idling Errors in Qubits via Adaptive Dynamical Decoupling

Cited by in corpus (20)

• A Review on Quantum Approximate Optimization Algorithm and its Variants
• Quantum Annealing vs. QAOA: 127 Qubit Higher-Order Ising Problems on NISQ Computers
• Quantum-centric computation of molecular excited states with extended sample-based quantum diagonalization
• Enhancing quantum utility: simulating large-scale quantum spin chains on superconducting quantum computers
• PANSATZ: Pulse-based Ansatz for Variational Quantum Algorithms
• Incompressible Navier-Stokes solve on noisy quantum hardware via a hybrid quantum-classical scheme
• Pulse-efficient quantum machine learning
• Experimental demonstration of scalable cross-entropy benchmarking to detect measurement-induced phase transitions on a superconducting quantum processor
• Error suppression by a virtual two-qubit gate
• Optimal realization of Yang-Baxter gate on quantum computers
• Synergistic Dynamical Decoupling and Circuit Design for Enhanced Algorithm Performance on Near-Term Quantum Devices
• Ab-initio tree-tensor-network digital twin for quantum computer benchmarking in 2D
• Probing Quantum Telecloning on Superconducting Quantum Processors
• Resource-efficient context-aware dynamical decoupling embedding for arbitrary large-scale quantum algorithms
• Increasing the Measured Effective Quantum Volume with Zero Noise Extrapolation
• Robust Finite-Temperature Many-Body Scarring on a Quantum Computer
• Quantum Utility in Simulating the Real-time Dynamics of the Fermi-Hubbard Model using Superconducting Quantum Computers
• Error Mitigation in Dynamic Circuits for Hamiltonian Simulation
• Secure and Efficient Quantum Signature Scheme Based on the Controlled Unitary Operations Encryption
• EmuPlat: A Framework-Agnostic Platform for Quantum Hardware Emulation with Validated Transpiler-to-Pulse Pipeline