Performance and error modeling of Deutsch's algorithm in IBM Q

Buksman, Efrain; Oliveira, André L. Fonseca de; Allende, Carolina

doi:10.31349/revmexfis.66.239

Cited by 1 publication

(1 citation statement)

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“…Previous error simulation works assessing the success of a quantum computation focus on the impact of noise on one particular quantum algorithm [27]- [33] or i47estigate deviceoriented error models [27], [29], [33]- [35]. Furthermore, previous exhaustive error simulations [28], [32], [33], [35]- [37] employ the density operator formalism that requires more memory and a much larger runtime, effectively halving the number of qubits of analyzable quantum circuits compared to the state vector simulator [22] employed by ArsoNISQ [30]. In addition, ArsoNISQ is flexible with respect to the NISQ algorithm and the success criterion and generates a detailed relation between between success probability and quantum computation size.…”

Section: Related Workmentioning

confidence: 99%

ArsoNISQ: Analyzing Quantum Algorithms on Near-Term Architectures

Brandhofer

Devitt

Polian

2021

2021 IEEE European Test Symposium (ETS)

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While scalable, fully error corrected quantum computing is years or even decades away, there is considerable interest in noisy intermediate-scale quantum computing (NISQ). In this paper, we introduce the ArsoNISQ framework that determines the tolerable error rate of a given quantum algorithm computation, i.e. quantum circuits, and the success probability of the computation given a success criterion and a NISQ computer. ArsoNISQ is based on simulations of quantum circuits subject to errors according to the Pauli error model.ArsoNISQ was evaluated on a set of quantum algorithms that can incur a quantum speedup or are otherwise relevant to NISQ computing. Despite optimistic expectations in recent literature, we did not observe quantum algorithms with intrinsic robustness, i.e. algorithms that tolerate one error on average, in this evaluation. The evaluation demonstrated, however, that the quantum circuit size sets an upper bound for its tolerable error rate and quantified the difference in tolerate error rates for quantum circuits of similar sizes. Thus, the framework can assist quantum algorithm developers in improving their implementation and selecting a suitable NISQ computing platform. Extrapolating the results into the quantum advantage regime suggests that the error rate of larger quantum computers must decrease substantially or active quantum error correction will need to be deployed for most of the evaluated algorithms.

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