Approximate Equivalence Checking of Noisy Quantum Circuits

We study the fundamental design automation problem of equivalence checking in the NISQ (Noisy Intermediate-Scale Quantum) computing realm where quantum noise is present inevitably. The notion of approximate equivalence of (possibly noisy) quantum circuits is defined based on the Jamiolkowski fidelit...

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Vydáno v:2021 58th ACM/IEEE Design Automation Conference (DAC) s. 637 - 642
Hlavní autoři: Hong, Xin, Ying, Mingsheng, Feng, Yuan, Zhou, Xiangzhen, Li, Sanjiang
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 05.12.2021
Témata:
Approximation algorithms
Benchmark testing
Design automation
equivalence checking
noise
Noise measurement
Quantum circuit
quantum circuits
Quantum computing
Scalability
Tensors
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Abstract We study the fundamental design automation problem of equivalence checking in the NISQ (Noisy Intermediate-Scale Quantum) computing realm where quantum noise is present inevitably. The notion of approximate equivalence of (possibly noisy) quantum circuits is defined based on the Jamiolkowski fidelity which measures the average distance between output states of two super-operators when the input is chosen at random. By employing tensor network contraction, we present two algorithms, aiming at different situations where the number of noises varies, for computing the fidelity between an ideal quantum circuit and its noisy implementation. The effectiveness of our algorithms is demonstrated by experimenting on benchmarks of real NISQ circuits. When compared with the state-of-the-art implementation incorporated in Qiskit, experimental results show that the proposed algorithms outperform in both efficiency and scalability.
AbstractList We study the fundamental design automation problem of equivalence checking in the NISQ (Noisy Intermediate-Scale Quantum) computing realm where quantum noise is present inevitably. The notion of approximate equivalence of (possibly noisy) quantum circuits is defined based on the Jamiolkowski fidelity which measures the average distance between output states of two super-operators when the input is chosen at random. By employing tensor network contraction, we present two algorithms, aiming at different situations where the number of noises varies, for computing the fidelity between an ideal quantum circuit and its noisy implementation. The effectiveness of our algorithms is demonstrated by experimenting on benchmarks of real NISQ circuits. When compared with the state-of-the-art implementation incorporated in Qiskit, experimental results show that the proposed algorithms outperform in both efficiency and scalability.
Author Zhou, Xiangzhen
Li, Sanjiang
Ying, Mingsheng
Hong, Xin
Feng, Yuan
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  organization: University of Technology Sydney,Centre for Quantum Software and Information,Australia
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  givenname: Sanjiang
  surname: Li
  fullname: Li, Sanjiang
  email: sanjiang.li@uts.edu.au
  organization: University of Technology Sydney,Centre for Quantum Software and Information,Australia
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Snippet We study the fundamental design automation problem of equivalence checking in the NISQ (Noisy Intermediate-Scale Quantum) computing realm where quantum noise...
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SubjectTerms Approximation algorithms
Benchmark testing
Design automation
equivalence checking
noise
Noise measurement
Quantum circuit
quantum circuits
Quantum computing
Scalability
Tensors
Title Approximate Equivalence Checking of Noisy Quantum Circuits
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