Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

IEEE International Conference on Computer Design: VLSI in Computers and Processors (ICCD)

Special Session: Impact of Noise on Quantum Algorithms in Noisy Intermediate-Scale Quantum Systems

Daniel Volya, Prabhat Mishra

Published Oct 1, 2020• 13 citations
Publisher

Abstract

A major challenge in realizing efficient and powerful quantum algorithms is quantum noise. Quantum noise itself is a sophisticated topic that is not seen in the classical domain. In this paper, we explore the impact of noise on quantum algorithms in Noisy Intermediate-Scale Quantum (NISQ) systems. This paper first introduces the origins of quantum noise. Next, it proposes a common treatment to simplify the view of quantum noise. Finally, it presents a case study to investigate the impact of noise on quantum Fourier transform algorithm.

DOI
10.1109/iccd50377.2020.00013

Related papers

Special Session: Noisy Intermediate-Scale Quantum (NISQ) Computers—How They Work, How They Fail, How to Test Them?

Sebastian Brandhofer, Simon J. Devitt, Thomas Wellens +1 more

First quantum computers very recently have demonstrated “quantum supremacy” or “quantum advantage Executing a computation that would have been impossible on a classical machine. Today's quantum computers follow the NISQ paradigm: They exhibit error rates that are much higher than in conventional electronics and have insufficient quantum resources to support powerful error correction protocols. This raises questions which relevant computations are within the reach of NISQ architectures. Several NISQ-era algorithms” are assumed to match the specifics of such computers; for instance, variational optimisers are based on intertwining relatively short quantum and classical computations, thus maximizing the chances of success. This paper will critically assess the promise and challenge of NISQ computing. What has this field achieved so far, what are we likely to achieve soon, where do we have to be skeptical and wait for the advent of larger-scale fully error-corrected architectures?

arXiv:2301.11739•IEEE VLSI Test Symposium (VTS)•Apr 25, 2021•15 citations

Entanglement Dynamics in Noisy Intermediate-Scale Quantum Systems

Dr. Ruman Singh

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.

International Journal of Integrated Research and Practice•Jan 15, 2026•0 citations

Noisy intermediate-scale quantum algorithms

Kishor Bharti, Alba Cervera-Lierta, Thi Ha Kyaw +11 more

Noisy quantum computers can in principle perform reliable quantum computations, but truly scalable systems require noise levels lower than are presently achieved. Still, moderate-complexity computations can be performed. This review discusses what is possible in this ``noisy intermediate scale'' quantum (NISQ) era. Topic areas include the simulation of many-body physics and chemistry, combinatorial optimization, and machine learning. It is evident that the NISQ era has produced new paradigms for programming that will be built upon as quantum computers are further perfected.

Reviews of Modern Physics•Feb 15, 2022•1,746 citations

The bitter truth about gate-based quantum algorithms in the NISQ era

Frank Leymann, Johanna Barzen

Abstract Implementing a gate-based quantum algorithm on an noisy intermediate scale quantum (NISQ) device has several challenges that arise from the fact that such devices are noisy and have limited quantum resources. Thus, various factors contributing to the depth and width as well as to the noise of an implementation of a gate-based algorithm must be understood in order to assess whether an implementation will execute successfully on a given NISQ device. In this contribution, we discuss these factors and their impact on algorithm implementations. Especially, we will cover state preparation, oracle expansion, connectivity, circuit rewriting, and readout: these factors are very often ignored when presenting a gate-based algorithm but they are crucial when implementing such an algorithm on near-term quantum computers. Our contribution will help developers in charge of realizing gate-based algorithms on such machines in (i) achieving an executable implementation, and (ii) assessing the success of their implementation on a given machine.

arXiv:2006.02856•Quantum Science and Technology•Aug 12, 2020•226 citations

Noisy intermediate-scale quantum (NISQ) algorithms

Kishor Bharti, Alba Cervera-Lierta, Thi Ha Kyaw +11 more

A universal fault-tolerant quantum computer that can solve efficiently problems such as integer factorization and unstructured database search requires millions of qubits with low error rates and long coherence times. While the experimental advancement towards realizing such devices will potentially take decades of research, noisy intermediate-scale quantum (NISQ) computers already exist. These computers are composed of hundreds of noisy qubits, i.e. qubits that are not error-corrected, and therefore perform imperfect operations in a limited coherence time. In the search for quantum advantage with these devices, algorithms have been proposed for applications in various disciplines spanning physics, machine learning, quantum chemistry and combinatorial optimization. The goal of such algorithms is to leverage the limited available resources to perform classically challenging tasks. In this review, we provide a thorough summary of NISQ computational paradigms and algorithms. We discuss the key structure of these algorithms, their limitations, and advantages. We additionally provide a comprehensive overview of various benchmarking and software tools useful for programming and testing NISQ devices.

arXiv:2101.08448•Jan 21, 2021•164 citations

Quantum-Computation and Quantum-Communication

Bhupesh Bishnoi

In this research notebook on quantum computation and quantum communication protocol for quantum engineers, researchers, and scientists, we will discuss and summarize the practical challenges of implementing quantum computing algorithms and quantum communication protocols in today's real-world hardware systems. We will begin the discussion about the noise and its effect on quantum coherence and the mathematical models to represent the impact of noise on the physical systems. Furthermore, we will discuss the basic concepts of noise that practically limit quantum computation and quantum communication. We will discuss several mathematical methods to characterize, model, and represent the practical impact of noise. Next, we will discuss how photon loss impacts quantum communication protocols. We will summarize the current physical limitations and challenges facing quantum computation and quantum communication over optical fiber. We will also discuss technology options that can mitigate or eliminate the physical limitations for realizing quantum computation and quantum communication protocol. Later we will consider the methods being developed to mitigate such losses in larger-scale communication systems. We will investigate the current limitations of quantum computing algorithms and the need to develop near-term practical applications that can be successfully performed on noisy qubits. We will also review the challenges associated with implementing algorithms on the relatively noisy, intermediate-scale qubits used in today's technology domain. Finally, we will investigate how to benchmark qubits and quantum gates in the presence of noise. We will discuss several methods to benchmark quantum states and quantum gates and finally implement benchmarking of qubits in a real physical quantum computer on the IBM Q Experience.

•Jun 4, 2020•0 citations
A major challenge in realizing efficient and powerful quantum algorithms is quantum noise. Quantum noise itself is a sophisticated topic that is not seen in the classical domain. In this paper, we explore the impact of noise on quantum algorithms in Noisy Intermediate-Scale Quantum (NISQ) systems. This paper first introduces the origins of quantum noise. Next, it proposes a common treatment to simplify the view of quantum noise. Finally, it presents a case study to investigate the impact of noise on quantum Fourier transform algorithm.
First quantum computers very recently have demonstrated “quantum supremacy” or “quantum advantage Executing a computation that would have been impossible on a classical machine. Today's quantum computers follow the NISQ paradigm: They exhibit error rates that are much higher than in conventional electronics and have insufficient quantum resources to support powerful error correction protocols. This raises questions which relevant computations are within the reach of NISQ architectures. Several NISQ-era algorithms” are assumed to match the specifics of such computers; for instance, variational optimisers are based on intertwining relatively short quantum and classical computations, thus maximizing the chances of success. This paper will critically assess the promise and challenge of NISQ computing. What has this field achieved so far, what are we likely to achieve soon, where do we have to be skeptical and wait for the advent of larger-scale fully error-corrected architectures?
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.
Noisy quantum computers can in principle perform reliable quantum computations, but truly scalable systems require noise levels lower than are presently achieved. Still, moderate-complexity computations can be performed. This review discusses what is possible in this ``noisy intermediate scale'' quantum (NISQ) era. Topic areas include the simulation of many-body physics and chemistry, combinatorial optimization, and machine learning. It is evident that the NISQ era has produced new paradigms for programming that will be built upon as quantum computers are further perfected.
Abstract Implementing a gate-based quantum algorithm on an noisy intermediate scale quantum (NISQ) device has several challenges that arise from the fact that such devices are noisy and have limited quantum resources. Thus, various factors contributing to the depth and width as well as to the noise of an implementation of a gate-based algorithm must be understood in order to assess whether an implementation will execute successfully on a given NISQ device. In this contribution, we discuss these factors and their impact on algorithm implementations. Especially, we will cover state preparation, oracle expansion, connectivity, circuit rewriting, and readout: these factors are very often ignored when presenting a gate-based algorithm but they are crucial when implementing such an algorithm on near-term quantum computers. Our contribution will help developers in charge of realizing gate-based algorithms on such machines in (i) achieving an executable implementation, and (ii) assessing the success of their implementation on a given machine.
A universal fault-tolerant quantum computer that can solve efficiently problems such as integer factorization and unstructured database search requires millions of qubits with low error rates and long coherence times. While the experimental advancement towards realizing such devices will potentially take decades of research, noisy intermediate-scale quantum (NISQ) computers already exist. These computers are composed of hundreds of noisy qubits, i.e. qubits that are not error-corrected, and therefore perform imperfect operations in a limited coherence time. In the search for quantum advantage with these devices, algorithms have been proposed for applications in various disciplines spanning physics, machine learning, quantum chemistry and combinatorial optimization. The goal of such algorithms is to leverage the limited available resources to perform classically challenging tasks. In this review, we provide a thorough summary of NISQ computational paradigms and algorithms. We discuss the key structure of these algorithms, their limitations, and advantages. We additionally provide a comprehensive overview of various benchmarking and software tools useful for programming and testing NISQ devices.
In this research notebook on quantum computation and quantum communication protocol for quantum engineers, researchers, and scientists, we will discuss and summarize the practical challenges of implementing quantum computing algorithms and quantum communication protocols in today's real-world hardware systems. We will begin the discussion about the noise and its effect on quantum coherence and the mathematical models to represent the impact of noise on the physical systems. Furthermore, we will discuss the basic concepts of noise that practically limit quantum computation and quantum communication. We will discuss several mathematical methods to characterize, model, and represent the practical impact of noise. Next, we will discuss how photon loss impacts quantum communication protocols. We will summarize the current physical limitations and challenges facing quantum computation and quantum communication over optical fiber. We will also discuss technology options that can mitigate or eliminate the physical limitations for realizing quantum computation and quantum communication protocol. Later we will consider the methods being developed to mitigate such losses in larger-scale communication systems. We will investigate the current limitations of quantum computing algorithms and the need to develop near-term practical applications that can be successfully performed on noisy qubits. We will also review the challenges associated with implementing algorithms on the relatively noisy, intermediate-scale qubits used in today's technology domain. Finally, we will investigate how to benchmark qubits and quantum gates in the presence of noise. We will discuss several methods to benchmark quantum states and quantum gates and finally implement benchmarking of qubits in a real physical quantum computer on the IBM Q Experience.