Assumption-free fidelity bounds for hardware noise characterization
- URL: http://arxiv.org/abs/2504.07010v1
- Date: Wed, 09 Apr 2025 16:27:52 GMT
- Title: Assumption-free fidelity bounds for hardware noise characterization
- Authors: Nicolo Colombo,
- Abstract summary: In the Quantum Supremacy regime, quantum computers may overcome classical machines on several tasks if we can estimate, mitigate, or correct unavoidable hardware noise.<n>We leverage Machine Learning data-driven approaches and Conformal Prediction to find theoretically valid upper bounds of the fidelity between noiseless and noisy outputs.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In the Quantum Supremacy regime, quantum computers may overcome classical machines on several tasks if we can estimate, mitigate, or correct unavoidable hardware noise. Estimating the error requires classical simulations, which become unfeasible in the Quantum Supremacy regime. We leverage Machine Learning data-driven approaches and Conformal Prediction, a Machine Learning uncertainty quantification tool known for its mild assumptions and finite-sample validity, to find theoretically valid upper bounds of the fidelity between noiseless and noisy outputs of quantum devices. Under reasonable extrapolation assumptions, the proposed scheme applies to any Quantum Computing hardware, does not require modeling the device's noise sources, and can be used when classical simulations are unavailable, e.g. in the Quantum Supremacy regime.
Related papers
- The curse of random quantum data [62.24825255497622]
We quantify the performances of quantum machine learning in the landscape of quantum data.
We find that the training efficiency and generalization capabilities in quantum machine learning will be exponentially suppressed with the increase in qubits.
Our findings apply to both the quantum kernel method and the large-width limit of quantum neural networks.
arXiv Detail & Related papers (2024-08-19T12:18:07Z) - Long-lived Particles Anomaly Detection with Parametrized Quantum Circuits [0.0]
We propose an anomaly detection algorithm based on a parametrized quantum circuit.
This algorithm has been trained on a classical computer and tested with simulations as well as on real quantum hardware.
arXiv Detail & Related papers (2023-12-07T11:50:42Z) - On the feasibility of performing quantum chemistry calculations on quantum computers [0.0]
We propose two criteria for evaluating two leading quantum approaches for finding the ground state of molecules.
The first criterion applies to the variational quantum eigensolver (VQE) algorithm.
The second criterion applies to the quantum phase estimation (QPE) algorithm.
arXiv Detail & Related papers (2023-06-05T06:41:22Z) - Quantum Conformal Prediction for Reliable Uncertainty Quantification in
Quantum Machine Learning [47.991114317813555]
Quantum models implement implicit probabilistic predictors that produce multiple random decisions for each input through measurement shots.
This paper proposes to leverage such randomness to define prediction sets for both classification and regression that provably capture the uncertainty of the model.
arXiv Detail & Related papers (2023-04-06T22:05:21Z) - Adaptive quantum error mitigation using pulse-based inverse evolutions [0.0]
We introduce a QEM method termed Adaptive KIK' that adapts to the noise level of the target device.
The implementation of the method is experimentally simple -- it does not involve any tomographic information or machine-learning stage.
We demonstrate our findings in the IBM quantum computers and through numerical simulations.
arXiv Detail & Related papers (2023-03-09T02:50:53Z) - Noisy Quantum Kernel Machines [58.09028887465797]
An emerging class of quantum learning machines is that based on the paradigm of quantum kernels.
We study how dissipation and decoherence affect their performance.
We show that decoherence and dissipation can be seen as an implicit regularization for the quantum kernel machines.
arXiv Detail & Related papers (2022-04-26T09:52:02Z) - Simulating open quantum many-body systems using optimised circuits in
digital quantum simulation [0.0]
We study models in open quantum systems with Trotterisations for the modified Schr"odinger equation (MSSE)
Minimising the leading error in MSSE enables to optimise the quantum circuits.
We run the algorithm on the IBM Quantum devices, showing that the current machine is challenging to give quantitatively accurate time dynamics due to the noise.
arXiv Detail & Related papers (2022-03-27T13:00:02Z) - Characterizing quantum instruments: from non-demolition measurements to
quantum error correction [48.43720700248091]
In quantum information processing quantum operations are often processed alongside measurements which result in classical data.
Non-unitary dynamical processes can take place on the system, for which common quantum channel descriptions fail to describe the time evolution.
Quantum measurements are correctly treated by means of so-called quantum instruments capturing both classical outputs and post-measurement quantum states.
arXiv Detail & Related papers (2021-10-13T18:00:13Z) - Quantum Noise Sensing by generating Fake Noise [5.8010446129208155]
We propose a framework to characterize noise in a realistic quantum device.
Key idea is to learn about the noise by mimicking it in a way that one cannot distinguish between the real (to be sensed) and the fake (generated) one.
We find that, when applied to the benchmarking case of Pauli channels, the SuperQGAN protocol is able to learn the associated error rates even in the case of spatially and temporally correlated noise.
arXiv Detail & Related papers (2021-07-19T09:42:37Z) - Error mitigation and quantum-assisted simulation in the error corrected
regime [77.34726150561087]
A standard approach to quantum computing is based on the idea of promoting a classically simulable and fault-tolerant set of operations.
We show how the addition of noisy magic resources allows one to boost classical quasiprobability simulations of a quantum circuit.
arXiv Detail & Related papers (2021-03-12T20:58:41Z) - Limitations of optimization algorithms on noisy quantum devices [0.0]
We present a transparent way of comparing classical algorithms to quantum ones running on near-term quantum devices.
Our approach is based on the combination of entropic inequalities that determine how fast the quantum state converges to the fixed point of the noise model.
arXiv Detail & Related papers (2020-09-11T17:07:26Z) - Quantum reservoir computing with a single nonlinear oscillator [0.0]
We propose continuous variable quantum reservoir computing in a single nonlinear oscillator.
We demonstrate quantum-classical performance improvement, and identify its likely source: the nonlinearity of quantum measurement.
We study how the performance of our quantum reservoir depends on Hilbert space dimension, how it is impacted by injected noise, and briefly comment on its experimental implementation.
arXiv Detail & Related papers (2020-04-30T17:14:34Z) - Quantum noise protects quantum classifiers against adversaries [120.08771960032033]
Noise in quantum information processing is often viewed as a disruptive and difficult-to-avoid feature, especially in near-term quantum technologies.
We show that by taking advantage of depolarisation noise in quantum circuits for classification, a robustness bound against adversaries can be derived.
This is the first quantum protocol that can be used against the most general adversaries.
arXiv Detail & Related papers (2020-03-20T17:56:14Z)
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.