Error estimation in current noisy quantum computers
- URL: http://arxiv.org/abs/2302.06870v3
- Date: Tue, 14 May 2024 10:50:06 GMT
- Title: Error estimation in current noisy quantum computers
- Authors: Unai Aseguinolaza, Nahual Sobrino, Gabriel Sobrino, Joaquim Jornet-Somoza, Juan Borge,
- Abstract summary: We analyze the main sources of errors in current (IBM) quantum computers.
We present a useful tool (TED-qc) designed to facilitate the total error probability expected for any quantum circuit.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: One of the main important features of the noisy intermediate-scale quantum (NISQ) era is the correct evaluation and consideration of errors. In this paper, we analyze the main sources of errors in current (IBM) quantum computers and we present a useful tool (TED-qc) designed to facilitate the total error probability expected for any quantum circuit. We propose this total error probability as the best way to estimate a lower bound for the fidelity in the NISQ era, avoiding the necessity of comparing the quantum calculations with any classical one. In order to contrast the robustness of our tool we compute the total error probability that may occur in three different quantum models: 1) the Ising model, 2) the Quantum-Phase Estimation (QPE), and 3) the Grover's algorithm. For each model, the main quantities of interest are computed and benchmarked against the reference simulator's results as a function of the error probability for a representative and statistically significant sample size. The analysis is satisfactory in more than the $99\%$ of the cases. In addition, we study how error mitigation techniques are able to eliminate the noise induced during the measurement. These results have been calculated for the IBM quantum computers, but both the tool and the analysis can be easily extended to any other quantum computer.
Related papers
- Refining Noise Mitigation in NISQ Hardware Through Qubit Error Probability [0.0]
A new metric, the qubit error probability (QEP), estimates the probability of a qubit to suffer an error.
We show that QEP can be used to improve one of the most important error mitigation techniques, the zero noise extrapolation (ZNE)
Our method, named zero error probability extrapolation (ZEPE), is based on calibration parameters which enables a good scalability in terms of number of qubits and circuit depth.
arXiv Detail & Related papers (2025-03-13T09:42:03Z) - Scalability of quantum error mitigation techniques: from utility to advantage [0.0]
Error mitigation has elevated quantum computing to the scale of hundreds of qubits and tens of layers.
Yet larger scales (deeper circuits) are needed to fully exploit the potential of quantum computing.
Here we demonstrate three key results that pave the way for the leap from quantum utility to quantum advantage.
arXiv Detail & Related papers (2024-03-20T12:26:51Z) - 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) - ArsoNISQ: Analyzing Quantum Algorithms on Near-Term Architectures [0.18188255328029254]
We introduce the ArsoNISQ framework that determines the tolerable error rate of a given quantum algorithm.
ArsoNISQ is based on simulations of quantum circuits subject to errors according to the Pauli error model.
arXiv Detail & Related papers (2023-01-18T02:09:48Z) - Validation tests of GBS quantum computers give evidence for quantum
advantage with a decoherent target [62.997667081978825]
We use positive-P phase-space simulations of grouped count probabilities as a fingerprint for verifying multi-mode data.
We show how one can disprove faked data, and apply this to a classical count algorithm.
arXiv Detail & Related papers (2022-11-07T12:00:45Z) - Testing platform-independent quantum error mitigation on noisy quantum
computers [1.0499611180329804]
We apply quantum error mitigation techniques to a variety of benchmark problems and quantum computers.
We define an empirically motivated, resource-normalized metric of the improvement of error mitigation which we call the improvement factor.
arXiv Detail & Related papers (2022-10-13T17:15:03Z) - On proving the robustness of algorithms for early fault-tolerant quantum computers [0.0]
We introduce a randomized algorithm for the task of phase estimation and give an analysis of its performance under two simple noise models.
We calculate that the randomized algorithm can succeed with arbitrarily high probability as long as the required circuit depth is less than 0.916 times the dephasing scale.
arXiv Detail & Related papers (2022-09-22T21:28:12Z) - 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) - Model-Independent Error Mitigation in Parametric Quantum Circuits and
Depolarizing Projection of Quantum Noise [1.5162649964542718]
Finding ground states and low-lying excitations of a given Hamiltonian is one of the most important problems in many fields of physics.
quantum computing on Noisy Intermediate-Scale Quantum (NISQ) devices offers the prospect to efficiently perform such computations.
Current quantum devices still suffer from inherent quantum noise.
arXiv Detail & Related papers (2021-11-30T16:08:01Z) - Crosstalk Suppression for Fault-tolerant Quantum Error Correction with
Trapped Ions [62.997667081978825]
We present a study of crosstalk errors in a quantum-computing architecture based on a single string of ions confined by a radio-frequency trap, and manipulated by individually-addressed laser beams.
This type of errors affects spectator qubits that, ideally, should remain unaltered during the application of single- and two-qubit quantum gates addressed at a different set of active qubits.
We microscopically model crosstalk errors from first principles and present a detailed study showing the importance of using a coherent vs incoherent error modelling and, moreover, discuss strategies to actively suppress this crosstalk at the gate level.
arXiv Detail & Related papers (2020-12-21T14:20:40Z) - Sampling Overhead Analysis of Quantum Error Mitigation: Uncoded vs.
Coded Systems [69.33243249411113]
We show that Pauli errors incur the lowest sampling overhead among a large class of realistic quantum channels.
We conceive a scheme amalgamating QEM with quantum channel coding, and analyse its sampling overhead reduction compared to pure QEM.
arXiv Detail & Related papers (2020-12-15T15:51:27Z) - 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)
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.