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International Symposium on Quality Electronic Design (ISQED)

Impact of Noise on the Resilience and the Security of Quantum Computing

Abdullah Ash Saki, Mahabubul Alam, Swaroop Ghosh

Published Apr 7, 2021• 18 citations
Publisher

Abstract

Qubits, which are building blocks of quantum computers, are fragile and prone to noise and error. Some prominent errors include decoherence/dephasing, gate error, readout error, leakage, and crosstalk. The computation quality degrades in the presence of errors. Therefore, even though quantum computing can theoretically speed-up certain classes of problems, the present-day Noisy Intermediate-Scale Quantum (NISQ) computers can only solve small-scale ones. In this work, we present an overview of various noise sources and their impact on the resilience and the security of quantum circuits. Our analysis indicates that noise sources (e.g., crosstalk) create a new attack surface (e.g., fault injection), especially for future largescale quantum computers that may employ a multi-programming compute model. We also propose countermeasures against the reliability and security issues.

DOI
10.1109/isqed51717.2021.9424258

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Qubits, which are building blocks of quantum computers, are fragile and prone to noise and error. Some prominent errors include decoherence/dephasing, gate error, readout error, leakage, and crosstalk. The computation quality degrades in the presence of errors. Therefore, even though quantum computing can theoretically speed-up certain classes of problems, the present-day Noisy Intermediate-Scale Quantum (NISQ) computers can only solve small-scale ones. In this work, we present an overview of various noise sources and their impact on the resilience and the security of quantum circuits. Our analysis indicates that noise sources (e.g., crosstalk) create a new attack surface (e.g., fault injection), especially for future largescale quantum computers that may employ a multi-programming compute model. We also propose countermeasures against the reliability and security issues.
Present-day quantum computers suffer from various noises or errors such as, gate error, relaxation, dephasing, readout error, and crosstalk. Besides, they offer a limited number of qubits with restrictive connectivity. Therefore, quantum programs running these computers face resilience issues and low output fidelities. The noise in the cloud-based access of quantum computers also introduce new modes of security and privacy issues. Furthermore, quantum computers face several threat models from insider and outsider adversaries including input tampering, program misallocation, fault injection, Reverse Engineering (RE) and Cloning. This paper provides an overview of various assets embedded in quantum computers and programs, vulnerabilities and attack models and the relation between resilience and security. We also cover countermeasures against the reliability and security issues and present future outlook for security of quantum computing.
The noisy intermediate-scale quantum (NISQ) computers suffer from unwanted coupling across qubits referred to as crosstalk. Existing literature largely ignores the crosstalk effects which can introduce significant error in circuit optimization. In this work, we present a crosstalk modeling analysis framework for near-term quantum computers after extracting the error-rates experimentally. Our analysis reveals that crosstalk can be of the same order of gate error which is considered a dominant error in NISQ devices. We also propose adversarial fault injection using crosstalk in a multiprogramming environment where the victim and the adversary share the same quantum hardware. Our simulation and experimental results from IBM quantum computers demonstrated that the adversary can inject fault and launch a Denial-of-Service attack. Finally, we propose system- and device-level countermeasures.
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.
The advent of noisy intermediate-scale quantum (NISQ) devices has not only opened up new possibilities to studying quantum computational benefits, but it has also presented new challenges associated with noise and short coherence times. Entanglement is one of the inherent resources that can be used to perform quantum computation and implement the performance and reliability of quantum algorithms. This paper looks at entanglement dynamics in NISQ machines subjected to natural noises. The study focuses on the problem of examining the role of various noise channels in the creation, dynamics, and decay of the entanglement during quantum operations, such as depolarizing, amplitude damping, and phase damping. The study is based on theoretical modeling and numerical simulations of multi-qubit quantum circuits to determine the stability of entangled states with respect to circuit depth and intensity of noise. Concurrence and von Neumann entropy are examples of entanglement measures that are used to characterize correlations between qubits as well as to trace the dynamics of these correlations across computational interactions. The results show that noise has major impacts on entanglement distribution, which tends to cause rapid decays in highly entangled states with increase in circuit complexity. The findings, however, also show that there are some circuit architectures and error-mitigation schemes that can somewhat sustain entanglement with moderate levels of noise. The paper also emphasizes the relevance of minimalizing sequence of gates, and reduced circuit depth in an effort to preserve useful entanglement in present-day quantum hardware. These observations help in understanding the behaviour of quantum correlations better in real world quantum devices and provide a way of developing more resilient quantum algorithms that would work on NISQ systems. In general, the article offers a systematic view on entanglement behavior in disordered quantum systems and highlights its value in the development of quantum computing applications in the near term.
Quantum computers are built with fragile and noise/error-prone qubits. Some prominent errors include, decoherence/dephasing, gate error, readout error, leakage, and crosstalk. Furthermore, the qubits vary in terms of their quality. Some qubits are healthy whereas others prone to errors. This presents an opportunity to exploit good quality qubits to improve the computation outcome. This chapter reviews the state-of-the-art mapping techniques for error tolerance. We take quantum benchmarks as well as approximate algorithms for applications covering MaxCut, object detection and factorization to illustrate various optimization challenges and opportunities.
Quantum computing is entering a transitional regime between noisy intermediate-scale quantum (NISQ) processing and early fault-tolerant quantum computation (FTQC), in which increasingly capable hardware is beginning to support repeated syndrome measurements, partial error correction, and logical-qubit operations, while residual physical and logical errors remain non-negligible. In this regime, error suppression, error mitigation, and quantum error correction are increasingly better viewed as complementary layers of a unified error-reduction strategy rather than as separate approaches, with each acting at a different stage of the quantum computation to improve simulation reliability. Thus, in this review, we provide a practical and forward-looking overview of the principal hardware error sources and the corresponding error suppression and mitigation methods for reducing their impact across the current NISQ-FTQC transition. We discuss hardware-aware circuit design, coherent-error suppression, readout mitigation, noise extrapolation, classical inference, and software-supported workflows, with particular emphasis on their implementation on actual quantum processors. We further examine how error mitigation techniques can be adapted to encoded and logical-qubit settings so that they can operate alongside quantum error correction to suppress residual logical errors and improve the accuracy of computation in the early fault-tolerant regime.