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Applied Sciences

Quasi-Shor Algorithms for Global Benchmarking of Universal Quantum Processors

Genting Dai, Kaiyong He, Changhao Zhao, Yongcheng He, Jianshe Liu, Wei Chen

Published Dec 22, 2022• 0 citations
Publisher

Abstract

This work generalizes Shor’s algorithm into quasi-Shor algorithms by replacing the modular exponentiation with alternative unitary operations. By using the quantum circuits to generate Bell states as the unitary operations, a specific example called the Bell–Shor algorithm was constructed. The system density matrices in the quantum circuits with four distinct input states were calculated in ideal conditions and illustrated through chromatic graphs to witness the evolution of quantum states in the quantum circuits. For the real part of the density matrices, it was revealed that the number of zero elements dramatically declined to only a few points after the operation of the inverse quantum Fourier transformation. Based on this property, a protocol constituting a pair of error metrics Γa and Γb is proposed for the global benchmarking of universal quantum processors by looking at the locations of the zero entries and normalized average values of non-zero entries. The protocol has polynomial resource requirements with the scale of the quantum processor. The Bell–Shor algorithm is capable of being a feasible setting for the global benchmarking of universal quantum processors.

DOI
10.3390/app13010139

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This work generalizes Shor’s algorithm into quasi-Shor algorithms by replacing the modular exponentiation with alternative unitary operations. By using the quantum circuits to generate Bell states as the unitary operations, a specific example called the Bell–Shor algorithm was constructed. The system density matrices in the quantum circuits with four distinct input states were calculated in ideal conditions and illustrated through chromatic graphs to witness the evolution of quantum states in the quantum circuits. For the real part of the density matrices, it was revealed that the number of zero elements dramatically declined to only a few points after the operation of the inverse quantum Fourier transformation. Based on this property, a protocol constituting a pair of error metrics Γa and Γb is proposed for the global benchmarking of universal quantum processors by looking at the locations of the zero entries and normalized average values of non-zero entries. The protocol has polynomial resource requirements with the scale of the quantum processor. The Bell–Shor algorithm is capable of being a feasible setting for the global benchmarking of universal quantum processors.
Shor's algorithm proved a significant milestone in quantum computing since it promises an exponential speedup over conventional algorithms for integer factorization, a problem critical to modern cryptography systems. This work covers implementation steps of Shor’s algorithm and analyzes Quantum Fourier Transform (QFT) usage for extracting periodicity from quantum superpositions. Firstly, theoretical foundations of algorithm are illustrated concentrating on QFT construction and operation within the setting of the quantum circuit. Thereafter, each implementation step such as qubit optimization, modular exponentiation, and circuit design is discussed. Our findings validate the theoretical effectiveness of the QFT in solving the period-finding subroutine, while also highlighting the practical difficulties and scaling constraints presented by existing quantum hardware. The paper ends with a summary of possible advancements and future paths for error mitigation strategies and quantum algorithm design.
Quantum computing has given rise to significant challenges that make its wide availability difficult, especially when it comes to the accurate calculation of execution costs of Quantum Runtime Services, which in turn complicates the ability of a programmer to take well-informed decisions given an expectation of both cost and success rates. Quantum algorithms are intertwined in a complex web of dependencies, in which modern algorithms commonly incorporate other algorithms as subroutines. This paper studies whether the characterization of success metrics in scaling scenarios of specific quantum subroutines can be extrapolated to the quantum algorithms that integrate them as subroutines. It focuses on Shor’s algorithm, and the Quantum Fourier Transform algorithm as a subroutine, analyzing possible correlations in different scaling scenarios created by modifying the input parameters ’N’ and ’a’, running three jobs with different noise models for each one. The results showed a clear correlation that closely resembles a 2:1 ratio for the circuit where N = 15. For N = 15 circuits, success rates varied significantly, only reflecting ratios close to 2:1 when the period was equal to 2, an ideal, small and even number that reduced the required operations of the modular exponentiation stage. Larger periods such as r = 6 showed lesser success rates due to the necessity of performing more operations during the modular exponentiation stage and the noise accumulation it entails. Results achieved in high noise conditions had similar Shor and QFT success rates, evidencing how the dispersion of shots can alter the expected results. There is a meaningful connection between the success rates of an algorithm and its subroutine, which can be shadowed or decreased when error rates and qubit counts are increased.
A fundamental problem in factorization by Shor's algorithm [1] is the implementation of the modular exponentiation function. The period of this function is important for determining the individual factors, so its accurate implementation is for successful factorization critical.The imprecision of current quantum computers requires that any quantum circuits should be as simple as possible. Both in terms of the number of qubits used, the number of quantum gates and the depth of the quantum circuit. Therefore, it is necessary to search for an optimal variant for the implementation of the above-mentioned modular exponentiation function.The standard method is to implement individual arithmetic functions [2] which can be combined to achieve the desired modular exponentiation function. This process, however, creates a very complex quantum circuit, so that its measured result (probability distribution) will be so skewed that it will not be possible to reliably obtain the period of sought.Another way is to create a special quantum circuit for one particular modular exponentiation function [3]. Such a circuit is of course simpler than the circuit created by the above universal implementation, but in practice it only makes sense for testing the functionality of the surrounding quantum circuit for period detection.A very interesting possibility for the implementation of arithmetic functions is to use the direct and inverse quantum Fourier transform [4]. For a quantum computer, these transformations are very easy operations, and this interesting feature can then be used to advantage in these various implementations.This contribution will explore these possible approaches and show their advantages and disadvantages through concrete examples.
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As quantum processors continue to scale in size and complexity, the need for well-defined, reproducible, and technology-agnostic performance metrics becomes increasingly critical. Here we present a suite of scalable quantum computing benchmarks developed as key performance indicators (KPIs) within the EU Quantum Flagship. These proposed benchmarks are designed to assess holistic system performance rather than isolated components, and to remain applicable across both noisy intermediate-scale quantum (NISQ) devices and future fault-tolerant architectures. We introduce four core benchmarks addressing complementary aspects of quantum computing capability: large multi-qubit circuit execution via a Clifford Volume benchmark, scalable multipartite entanglement generation through GHZ-state preparation, a benchmark based on the application of Shor's period-finding subroutine to simple functions, and a protocol quantifying the benefit of quantum error correction using Bell states. Each benchmark is accompanied by clearly specified protocols, reporting standards, and scalable evaluation methods. Together, these KPIs provide a coherent framework for transparent and fair performance assessment across quantum hardware platforms and for tracking progress late-NISQ toward early fault-tolerant quantum computation.