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Benchmarking is how the performance of a computing system is determined. Surprisingly, even for classical computers this is not a straightforward process. One must choose the appropriate benchmark and metrics to extract meaningful results.…

Quantum Physics · Physics 2021-05-07 Salonik Resch , Ulya R. Karpuzcu

The computational power of real-world quantum computers is limited by errors. When using quantum computers to perform algorithms which cannot be efficiently simulated classically, it is important to quantify the accuracy with which the…

Quantum Physics · Physics 2024-01-18 Avi Vadali , Rutuja Kshirsagar , Prasanth Shyamsundar , Gabriel N. Perdue

Learning about physical systems from quantum-enhanced experiments, relying on a quantum memory and quantum processing, can outperform learning from experiments in which only classical memory and processing are available. Whereas quantum…

Quantum Physics · Physics 2024-06-21 Matthias C. Caro

The presence of noise is the primary challenge in realizing fault-tolerant quantum computers. In this work, we introduce and experimentally validate a novel strategy to circumvent noise by exploiting the phenomenon of metastability, where a…

Quantum Physics · Physics 2026-05-28 Antonio Sannia , Pratik Sathe , Luis Pedro García-Pintos

The performance requirements for fault-tolerant quantum computing are very stringent. Qubits must be manipulated, coupled, and measured with error rates well below 1%. For semiconductor implementations, silicon quantum dot spin qubits have…

With the intense interest in small, noisy quantum computing devices comes the push for larger, more accurate -- and hence more useful -- quantum computers. While fully fault-tolerant quantum computers are, in principle, capable of achieving…

Quantum Physics · Physics 2022-04-22 Akshaya Jayashankar , My Duy Hoang Long , Hui Khoon Ng , Prabha Mandayam

The success probability of a quantum algorithm constructed from noisy quantum gates cannot be accurately predicted from single parameter metrics that compare noisy and ideal gates. We illustrate this concept by examining a system with…

Quantum Physics · Physics 2019-03-27 Daniel C. Murphy , Kenneth R. Brown

While the power of quantum computers is commonly acknowledged to rise exponentially, it is often overlooked that the complexity of quantum noise mechanisms generally grows much faster. In particular, quantifying whether the instructions on…

Quantum Physics · Physics 2024-09-04 Pedro Figueroa-Romero , Miha Papič , Adrian Auer , Inés de Vega

We compare the effect of single qubit incoherent and coherent errors on the logical error rate of the Steane [[7,1,3]] quantum error correction code by performing an exact full-density-matrix simulation of an error correction step. We find…

Quantum Physics · Physics 2016-11-02 Mauricio Gutiérrez , Conor Smith , Livia Lulushi , Smitha Janardan , Kenneth R. Brown

Parameterized Quantum Circuits (PQC) are promising towards quantum advantage on near-term quantum hardware. However, due to the large quantum noises (errors), the performance of PQC models has a severe degradation on real quantum devices.…

Machine Learning · Computer Science 2025-01-29 Hanrui Wang , Jiaqi Gu , Yongshan Ding , Zirui Li , Frederic T. Chong , David Z. Pan , Song Han

Given a pair of isolated devices that accept random binary inputs and return binary outputs, a user can deduce from the observed data alone if the underlying mechanism can be explained classically. Bell's theorem further states that a…

Quantum Physics · Physics 2026-05-21 Kuntal Sengupta , Lewis Wooltorton

When modeling the effects of noise on quantum circuits, one often makes the assumption that these effects can be accounted for by individual decoherence events following an otherwise noise-free gate. In this work, we address the validity of…

Quantum Physics · Physics 2023-12-19 Keith R. Fratus , Juha Leppäkangas , Michael Marthaler , Jan-Michael Reiner

Shadow tomography is a scalable technique to characterise the quantum state of a quantum computer or quantum simulator. The protocol is based on the transformation of the outcomes of random measurements into the so-called classical shadows,…

Quantum Physics · Physics 2023-10-27 Hai-Chau Nguyen

Error mitigation (EM) methods are crucial for obtaining reliable results in the realm of noisy intermediate-scale quantum (NISQ) computers, where noise significantly impacts output accuracy. Some EM protocols are particularly efficient for…

Quantum Physics · Physics 2026-03-03 Thibault Scoquart , Hugo Perrin , Kyrylo Snizhko

Quantum magic is a necessary resource for quantum computers to be not efficiently simulable by classical computers. Previous results have linked the amount of quantum magic, characterized by the number of $T$ gates or stabilizer rank, to…

Quantum Physics · Physics 2025-02-07 Yifan Zhang , Yuxuan Zhang

Quantum sensing is an important application of emerging quantum technologies. We explore whether a hybrid system of quantum sensors and quantum circuits can surpass the classical limit of sensing. In particular, we use optimization…

Recently, quantum classifiers have been found to be vulnerable to adversarial attacks, in which quantum classifiers are deceived by imperceptible noises, leading to misclassification. In this paper, we propose the first theoretical study…

The promise of tremendous computational power, coupled with the development of robust error-correcting schemes, has fuelled extensive efforts to build a quantum computer. The requirements for realizing such a device are confounding:…

Quantum Physics · Physics 2011-08-17 J L O'Brien , G J Pryde , A G White , T C Ralph , D Branning

As quantum circuits become more integrated and complex, additional error sources that were previously insignificant start to emerge. Consequently, the fidelity of quantum gates benchmarked under pristine conditions falls short of predicting…

We describe a slightly sub-exponential time algorithm for learning parity functions in the presence of random classification noise. This results in a polynomial-time algorithm for the case of parity functions that depend on only the first…

Machine Learning · Computer Science 2007-05-23 Avrim Blum , Adam Kalai , Hal Wasserman