Stability of noisy quantum computing devices
- URL: http://arxiv.org/abs/2105.09472v1
- Date: Thu, 20 May 2021 06:50:44 GMT
- Title: Stability of noisy quantum computing devices
- Authors: Samudra Dasgupta and Travis S. Humble
- Abstract summary: Noisy, intermediate-scale quantum (NISQ) computing devices offer opportunities to test the principles of quantum computing.
We quantify the reliability of NISQ devices by quantifying the stability of performance metrics.
Our observations collected over 22 months reveal large fluctuations in each metric that underscore the limited scales on which current NISQ devices may be considered reliable.
- Score: 0.40611352512781856
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Noisy, intermediate-scale quantum (NISQ) computing devices offer
opportunities to test the principles of quantum computing but are prone to
errors arising from various sources of noise. Fluctuations in the noise itself
lead to unstable devices that undermine the reproducibility of NISQ results.
Here we characterize the reliability of NISQ devices by quantifying the
stability of essential performance metrics. Using the Hellinger distance, we
quantify the similarity between experimental characterizations of several NISQ
devices by comparing gate fidelities, duty cycles, and register addressability
across temporal and spatial scales. Our observations collected over 22 months
reveal large fluctuations in each metric that underscore the limited scales on
which current NISQ devices may be considered reliable.
Related papers
- Enhancing Quantum Variational Algorithms with Zero Noise Extrapolation
via Neural Networks [0.4779196219827508]
Variational Quantum Eigensolver (VQE) is a promising algorithm for solving complex quantum problems.
The ubiquitous presence of noise in quantum devices often limits the accuracy and reliability of VQE outcomes.
This research introduces a novel approach by utilizing neural networks for zero noise extrapolation (ZNE) in VQE computations.
arXiv Detail & Related papers (2024-03-10T15:35:41Z) - Probabilistic Sampling of Balanced K-Means using Adiabatic Quantum Computing [93.83016310295804]
AQCs allow to implement problems of research interest, which has sparked the development of quantum representations for computer vision tasks.
In this work, we explore the potential of using this information for probabilistic balanced k-means clustering.
Instead of discarding non-optimal solutions, we propose to use them to compute calibrated posterior probabilities with little additional compute cost.
This allows us to identify ambiguous solutions and data points, which we demonstrate on a D-Wave AQC on synthetic tasks and real visual data.
arXiv Detail & Related papers (2023-10-18T17:59:45Z) - Impact of unreliable devices on stability of quantum computations [0.1227734309612871]
Noisy intermediate-scale quantum (NISQ) devices are valuable platforms for testing the tenets of quantum computing.
These devices are susceptible to errors arising from de-coherence, leakage, cross-talk and other sources of noise.
Here, we quantify the reliability of NISQ devices by assessing the necessary conditions for generating stable results within a given tolerance.
arXiv Detail & Related papers (2023-07-13T17:53:42Z) - Reliable Devices Yield Stable Quantum Computations [0.34376560669160383]
We address how temporal and spatial variations in noise relate device reliability to quantum computing stability.
Our approach quantifies the differences in statistical distributions of characterization metrics collected at different times and locations.
We find that the stability metric is consistently bounded from above by the corresponding Hellinger distance.
arXiv Detail & Related papers (2023-07-10T14:32:32Z) - Measurement-induced entanglement and teleportation on a noisy quantum
processor [105.44548669906976]
We investigate measurement-induced quantum information phases on up to 70 superconducting qubits.
We use a duality mapping, to avoid mid-circuit measurement and access different manifestations of the underlying phases.
Our work demonstrates an approach to realize measurement-induced physics at scales that are at the limits of current NISQ processors.
arXiv Detail & Related papers (2023-03-08T18:41:53Z) - Ability of error correlations to improve the performance of variational
quantum algorithms [0.0]
We introduce a model for both spatially and temporally (non-Markovian) correlated errors based on classical environmental fluctuators.
We find evidence that the performance of QAOA improves as the correlation time or correlation length of the noise is increased at fixed local error probabilities.
arXiv Detail & Related papers (2022-07-21T17:30:33Z) - Measuring NISQ Gate-Based Qubit Stability Using a 1+1 Field Theory and
Cycle Benchmarking [50.8020641352841]
We study coherent errors on a quantum hardware platform using a transverse field Ising model Hamiltonian as a sample user application.
We identify inter-day and intra-day qubit calibration drift and the impacts of quantum circuit placement on groups of qubits in different physical locations on the processor.
This paper also discusses how these measurements can provide a better understanding of these types of errors and how they may improve efforts to validate the accuracy of quantum computations.
arXiv Detail & Related papers (2022-01-08T23:12:55Z) - Relaxation of a Stationary State on a Quantum Computer Yields Unique
Spectroscopic Fingerprint of the Computer's Noise [0.0]
We simulate the relaxations of stationary states at different frequencies on several quantum computers to obtain unique spectroscopic fingerprints of their noise.
The study suggest that noisy intermediate-scale quantum computers (NISQ) provide a built-in noisy bath that can be analyzed from their simulation.
arXiv Detail & Related papers (2021-04-29T17:58:37Z) - Quantum circuit architecture search for variational quantum algorithms [88.71725630554758]
We propose a resource and runtime efficient scheme termed quantum architecture search (QAS)
QAS automatically seeks a near-optimal ansatz to balance benefits and side-effects brought by adding more noisy quantum gates.
We implement QAS on both the numerical simulator and real quantum hardware, via the IBM cloud, to accomplish data classification and quantum chemistry tasks.
arXiv Detail & Related papers (2020-10-20T12:06:27Z) - On the learnability of quantum neural networks [132.1981461292324]
We consider the learnability of the quantum neural network (QNN) built on the variational hybrid quantum-classical scheme.
We show that if a concept can be efficiently learned by QNN, then it can also be effectively learned by QNN even with gate noise.
arXiv Detail & Related papers (2020-07-24T06:34:34Z) - Quantum Zeno effect with partial measurement and noisy dynamics [64.41511459132334]
We study the Quantum Zeno Effect (QZE) induced by continuous partial measurement in the presence of short-correlated noise in the system Hamiltonian.
We find that, depending on the noise parameters, the quantum Zeno effect can be enhanced or suppressed by the noise in different regions of the parameter space.
arXiv Detail & Related papers (2020-06-24T18:15:05Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.