Methods for classically simulating noisy networked quantum architectures

Vankov, Iskren; Mills, Derek; Wallden, Petros; Kashefi, Elham

doi:10.1088/2058-9565/ab54a4

Cited by 7 publications

(6 citation statements)

References 113 publications

(197 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Noise in a non-fault-tolerant quantum computer results in discrepancies between results obtained from running on real hardware and those that would be obtained from an ideal quantum computer. Noise models are utilised to help identify why these discrepancies occur [76]. However, a perfect model of the noise -which could reproduce the results of real hardware (up to statistical error) -could require many parameters to completely specify it.…”

Section: Insights From Classical Simulationmentioning

confidence: 99%

Application-Motivated, Holistic Benchmarking of a Full Quantum Computing Stack

Mills

Sivarajah

Scholten³

et al. 2021

Quantum

Self Cite

View full text Add to dashboard Cite

Quantum computing systems need to be benchmarked in terms of practical tasks they would be expected to do. Here, we propose 3 "application-motivated" circuit classes for benchmarking: deep (relevant for state preparation in the variational quantum eigensolver algorithm), shallow (inspired by IQP-type circuits that might be useful for near-term quantum machine learning), and square (inspired by the quantum volume benchmark). We quantify the performance of a quantum computing system in running circuits from these classes using several figures of merit, all of which require exponential classical computing resources and a polynomial number of classical samples (bitstrings) from the system. We study how performance varies with the compilation strategy used and the device on which the circuit is run. Using systems made available by IBM Quantum, we examine their performance, showing that noise-aware compilation strategies may be beneficial, and that device connectivity and noise levels play a crucial role in the performance of the system according to our benchmarks.

show abstract

Section: Insights From Classical Simulationmentioning

confidence: 99%

Application-Motivated, Holistic Benchmarking of a Full Quantum Computing Stack

Mills

Sivarajah

Scholten³

et al. 2021

Quantum

Self Cite

View full text Add to dashboard Cite

show abstract

“…The computational capability of the current generation quantum devices is considerably restricted due to poor qubit quality, limited qubit connectivity, and shorter coherence time. In general, in the case of the circuit execution on NISQ devices, this can be realized in terms of noise-induced errors in the system: (1) Memory errors, (2) Gate implementation errors, and (3) Measurement errors [39,40]. The effect of these errors on the result of circuit execution can be understood in the following way.…”

Section: Discussionmentioning

confidence: 99%

Circuit centric quantum architecture design

Azad

Papneja

Saini

et al. 2021

IET Quantum Communication

View full text Add to dashboard Cite

With the development in the field of quantum physics, several methods for building a quantum computer have emerged. These differ in qubit technologies, interaction topologies, and noise characteristics. In this article, insights are given into the circuitcentric architecture design of Noisy Intermediate-Scale Quantum (NISQ) devices. The dependence of the circuit size, circuit depth on the interaction and connection between different qubits present in quantum hardware are discussed. A noise-aware procedure is presented which helps in determining the optimal interactions between different qubits of a quantum chip to execute a given circuit in the most efficient way possible. In this article, the 5-qubit hardware in a noiseless setting is illustrated with an example. Also, a benchmark-driven analysis is performed to show the importance of noise adaptivity in determining the hardware reliability. It is concluded that a generalized and flexible procedure such as this approach can aid in determining the design of hardware accurately for which the circuit runs efficiently, that is, with the least number of clock cycles, the lowest gate operations, and noise-based errors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

show abstract

“…The is because the states and unitaries for Gaussian Boson Sampling are Gaussian, meaning the errors due to finite squeezing in the cluster states can be corrected [19]. This could lead to the implementation of Gaussian Boson Sampling with a large number of modes, and thus may potentially help to achieve quantum supremacy [42,[61][62][63][64].…”

Section: Discussionmentioning

confidence: 99%

Implementing quantum algorithms on temporal photonic cluster states

Sabapathy

Myers

et al. 2018

Phys. Rev. A

View full text Add to dashboard Cite

Implementing quantum algorithms is essential for quantum computation. We study the implementation of three quantum algorithms by performing homodyne measurements on a two-dimensional temporal continuous-variable cluster state. We first review the generation of temporal cluster states and the implementation of gates using the measurement-based model. Alongside this we discuss methods to introduce non-Gaussianity into the cluster states. The first algorithm we consider is Gaussian Boson Sampling in which only Gaussian unitaries need to be implemented. Taking into account the fact that input states are also Gaussian, the errors due to the effect of finite squeezing can be corrected, provided a moderate amount of online squeezing is available. This helps to construct a large Gaussian Boson Sampling machine. The second algorithm is the continuous-variable Instantaneous Quantum Polynomial circuit in which one needs to implement non-Gaussian gates, such as the cubic phase gate. We discuss several methods of implementing the cubic phase gate and fit them into the temporal cluster state architecture. The third algorithm is the continuousvariable version of Grover's search algorithm, the main challenge of which is the implementation of the inversion operator. We propose a method to implement the inversion operator by injecting a resource state into a teleportation circuit. The resource state is simulated using the Strawberry Fields quantum software package.

show abstract

Methods for classically simulating noisy networked quantum architectures

Cited by 7 publications

References 113 publications

Application-Motivated, Holistic Benchmarking of a Full Quantum Computing Stack

Application-Motivated, Holistic Benchmarking of a Full Quantum Computing Stack

Circuit centric quantum architecture design

Implementing quantum algorithms on temporal photonic cluster states

Contact Info

Product

Resources

About