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IEEE Micro

Quantum Computing—From NISQ to PISQ

Koen Bertels, Aritra Sarkar, Imran Ashraf

Published Sep 1, 2021• 29 citations
Publisher

Abstract

Given the impeding timeline of developing good quality quantum processing units, it is the moment to rethink the approach to advance quantum computing research. Rather than waiting for quantum hardware technologies to mature, we need to start assessing in tandem the impact of the occurrence of quantum computing in various scientific fields. However, to this purpose, we need to use a complementary but quite different approach than proposed by the NISQ vision, which is heavily focused on and burdened by the engineering challenges. That is why we propose and advocate the PISQ approach: Perfect Intermediate Scale Quantum computing based on the already known concept of perfect qubits. This will allow researchers to focus much more on the development of new applications by defining the algorithms in terms of perfect qubits and evaluate them on quantum computing simulators that are executed on supercomputers. It is not the long-term solution but will currently allow universities to research on quantum logic and algorithms and companies can already start developing their internal know-how on quantum solutions.

DOI
10.1109/mm.2021.3099195

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Given the impeding timeline of developing good quality quantum processing units, it is the moment to rethink the approach to advance quantum computing research. Rather than waiting for quantum hardware technologies to mature, we need to start assessing in tandem the impact of the occurrence of quantum computing in various scientific fields. However, to this purpose, we need to use a complementary but quite different approach than proposed by the NISQ vision, which is heavily focused on and burdened by the engineering challenges. That is why we propose and advocate the PISQ approach: Perfect Intermediate Scale Quantum computing based on the already known concept of perfect qubits. This will allow researchers to focus much more on the development of new applications by defining the algorithms in terms of perfect qubits and evaluate them on quantum computing simulators that are executed on supercomputers. It is not the long-term solution but will currently allow universities to research on quantum logic and algorithms and companies can already start developing their internal know-how on quantum solutions.
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The paper provides an exploration of quantum computing, emphasizing its potential and challenges. It begins with the fundamentals of quantum mechanics and differentiates between classical and quantum computing, focusing on concepts like qubits, superposition, and entanglement. The authors identify the existing limitations in practical quantum applications, particularly within the Noisy Intermediate-Scale Quantum (NISQ) era, where issues like noise in quantum circuits hinder scalability and reliability. The paper addresses the need for advancements in hardware, error correction techniques, and practical algorithms tailored for current technological constraints. Additionally, it discusses the implications of quantum computing on cryptography, underscoring the vulnerability of traditional cryptographic methods and the urgency for postquantum cryptographic solutions. The methodology involves literature review, expert consultations, and bibliometric analysis to gauge global research trends in quantum computing. The paper highlights crucial research gaps, particularly in the development of scalable quantum algorithms suitable for near-future applications.
One of the main drivers for growing the field of quantum computation has been the prospect of creating a quantum computer capable of carrying out Shor's algorithm for huge numbers.Nonetheless, it is critical to recognise that quantum computers will probably only significantly speed up a small subset of issues if one wants to acquire a more comprehensive perspective on them.Building a system that can accommodate a lot of qubits while preserving stability and coherence is one of the biggest problems in quantum computing.Due to their extreme sensitivity to noise and mistakes, quantum systems are particularly susceptible to computing errors.Building a usable quantum computer requires error mitigation and correction, but the techniques for doing this are still in the early phases of research.In quantum computing, all processes and schemes must be reversible in accordance with the law of unitary development.The circuit model is taken into account in the NISQ framework, but there is also the one-way or measurement-based quantum computation approach, which is not reversible but is demonstrated to be comparable to the circuit model.Noisy suggests that the computing capacity of such quantum computers is constrained because of sufficiently high error and decoherence rates.While they are likely too huge to be replicated by traditional computers using brute force, Intermediate-Scale suggests that they are still too small to be mistake corrected, which also adds to the preceding argument about how noisy they are.P stands for the usage of perfect qubits with perfect quantum gates and no decoherence.The capability to control and protect our qubits in a quantum computer to the degree necessary to run such algorithms is commonly described as fault-tolerant quantum computation.This review paper examines the numerous quantum computing strategies, such as Noisy Intermediate Scale Computing (NISQ) , Perfect Intermediate Scale Computing (PISQ), and Fault Tolerant Intermediate Scale Computing (FTISQ), as well as potential future lines of inquiry.
In 2017, John Preskill defined Noisy Intermediate Scale Quantum (NISQ) computers as an intermediate step on the road to large scale error corrected fault-tolerant quantum computers (FTQC). The NISQ regime corresponds to noisy qubit quantum computers with the potential to solve actual problems of some commercial value faster than conventional supercomputers, or consuming less energy. Over five years on, it is a good time to review the situation. While rapid progress is being made with quantum hardware and algorithms, and many recent experimental demonstrations, no one has yet successfully implemented a use case matching the original definition of the NISQ regime. This paper investigates the space, fidelity and time resources of various NISQ algorithms and highlights several contradictions between NISQ requirements and actual as well as future quantum hardware capabilities. It then covers various techniques which could help like qubit fidelities improvements, various breeds of quantum error mitigation methods, analog/digital hybridization, using specific qubit types like multimode photons as well as quantum annealers and analog quantum computers (aka quantum simulators or programmable Hamiltonian simulators) which seem closer to delivering useful applications although they have their own mid to longer-term scalability challenges. Given all the constraints of these various solutions, it seems possible to expect some practical use cases for NISQ systems, but with a very narrow window before various scaling issues show up. Turning to the future, a scenario can be envisioned where NISQ will not necessarily be an intermediate step on the road to FTQC. Instead, the two may develop along different paths, due to their different requirements. This leaves open a key question on the trade-offs that may be necessary to make between qubit scale and qubit fidelities in future quantum computers designs.
Quantum Computing is emerging as one of the great hopes for boosting current computational resources and enabling the application of ICT for optimizing processes and solving complex and challenging domain specific problems. However, the Quantum Computing technology has not matured to a level where it can provide a clear advantage over high performance computing yet. Towards achieving this "quantum advantage", a larger number of Qubits is required, leading inevitably to a more complex topology of the computing Qubits. This raises additional difficulties with decoherence times and implies higher Qubit error rates. Nevertheless, the current Noisy Intermediate-Scale Quantum (NISQ) computers can prove useful despite the intrinsic uncertainties on the quantum hardware layer. In order to utilize such error-prone computing resources, various concepts are required to address Qubit errors and to deliver successful computations. In this paper describe and motivate the need for the novel concept of Quantum DevOps. which entails regular checking of the reliability of NISQ Quantum Computing (QC) instances. By means of testing the computational reliability of basic quantum gates and computations (C-NOT, Hadamard, etc.)it consequently estimates the likelihood for a large scale critical computation (e.g. calculating hourly traffic flow models for a city) to provide results of sufficient quality. Following this approach to select the best matching (cloud) QC instance and having it integrated directly with the processes of development, testing and finally the operations of quantum based algorithms and systems enables the Quantum DevOps concept.
A paradigm shift in computation is being brought about by quantum computing, which uses the concepts of quantum mechanics to tackle problems that even the most powerful conventional supercomputers cannot solve. This review provides an in-depth overview of the field, covering everything from basic concepts to the cutting edge. The three fundamental building blocks of quantum processing—the qubit, superposition, and entanglement—are first described.These ideas enable quantum computers to concurrently explore large computational domains. After that, the paper examines the various physical implementations, highlighting the advantages and disadvantages of the top hardware platforms, such as neutral atoms, trapped ions, photonic systems, and superconducting circuits, in terms of coherence and scalability. Shor's method for integer factorization and Grover's algorithm for unstructured search are two examples of groundbreaking quantum algorithms that are highlighted for their potential to achieve exponential and quadratic speedups over their classical counterparts. We also examine how programming languages that bridge the gap between abstract algorithms and physical hardware are being developed, as well as the new quantum software stack. The paper also explores how quantum computing can revolutionize a number of fields, such as machine learning, materials research, medication development, and cryptography. subsequently, we discuss two of the biggest challenges impeding the development of large-scale, fault-tolerant quantum computers: the requirement for robust quantum error correction and decoherence. In the end, a view of the current period of Noisy Intermediate-Scale Quantum (NISQ) and the path towards quantum advantage is presented. Researchers, students, and professionals looking for a comprehensive grasp of this quickly developing and revolutionary topic are expected to find this review to be an invaluable asset.