English
Related papers

Related papers: Quantum Closeness Testing: A Streaming Algorithm a…

200 papers

Large classical datasets are often processed in the streaming model, with data arriving one item at a time. In this model, quantum algorithms have been shown to offer an unconditional exponential advantage in space. However, experimentally…

We study which property testing and sublinear time algorithms can be transformed into graph streaming algorithms for random order streams. Our main result is that for bounded degree graphs, any property that is constant-query testable in…

Data Structures and Algorithms · Computer Science 2017-07-25 Morteza Monemizadeh , S. Muthukrishnan , Pan Peng , Christian Sohler

Quantum state tomography is a daunting challenge of experimental quantum computing even in moderate system size. One way to boost the efficiency of state tomography is via local measurements on reduced density matrices, but the…

Quantum Physics · Physics 2019-12-03 Tao Xin , Sirui Lu , Ningping Cao , Galit Anikeeva , Dawei Lu , Jun Li , Guilu Long , Bei Zeng

Quantum state tomography is a powerful, but resource-intensive, general solution for numerous quantum information processing tasks. This motivates the design of robust tomography procedures that use relevant resources as sparingly as…

Quantum Physics · Physics 2022-01-17 Fernando G. S. L. Brandão , Richard Kueng , Daniel Stilck França

Robust, accurate and efficient quantum tomography is key for future quantum technologies. Traditional methods are impractical for even medium sized systems and are not robust against noise and errors. Here we report on an experimental…

Quantum Physics · Physics 2016-07-27 Robert J. Chapman , Christopher Ferrie , Alberto Peruzzo

The emergence of quantum devices has raised a significant issue: how to certify the quantum properties of a device without placing trust in it. To characterise quantum states and measurements in a device-independent way, up to some degree…

Quantum Physics · Physics 2026-03-05 Shubhayan Sarkar , Alexandre C. Orthey, , Remigiusz Augusiak

In many problems in data mining and machine learning, data items that need to be clustered or classified are not points in a high-dimensional space, but are distributions (points on a high dimensional simplex). For distributions, natural…

Data Structures and Algorithms · Computer Science 2007-07-13 Sudipto Guha , Andrew McGregor , Suresh Venkatasubramanian

Quantum state tomography is a technique in quantum information science used to reconstruct the density matrix of an unknown quantum state, providing complete information about the quantum state. It is of significant importance in fields…

Quantum Physics · Physics 2025-07-23 Wenlong Zhao , Da Zhang , Huili Zhang , Haifeng Yu , Zhang-qi Yin

A test of quantumness is a protocol that allows a classical verifier to certify (only) that a prover is not classical. We show that tests of quantumness that follow a certain template, which captures recent proposals such as (Kalai et al.,…

Data streaming, in which a large dataset is received as a "stream" of updates, is an important model in the study of space-bounded computation. Starting with the work of Le Gall [SPAA `06], it has been known that quantum streaming…

Quantum Physics · Physics 2021-11-16 John Kallaugher

Self-testing is a method to certify devices from the result of a Bell test. Although examples of noise tolerant self-testing are known, it is not clear how to deal efficiently with a finite number of experimental trials to certify the…

Quantum Physics · Physics 2021-03-03 Jean-Daniel Bancal , Kai Redeker , Pavel Sekatski , Wenjamin Rosenfeld , Nicolas Sangouard

Self-testing of quantum devices based on observed measurement statistics is a method to certify quantum systems using minimal resources. In Ref. [Phys. Rev. \textbf{A} 101, 032106 (2020)], a scheme based on observing measurement statistics…

Quantum Physics · Physics 2024-12-03 Chellasamy Jebarathinam , Gautam Sharma , Sk Sazim , Remigiusz Augusiak

We use a meta-learning neural-network approach to analyse data from a measured quantum state. Once our neural network has been trained it can be used to efficiently sample measurements of the state in measurement bases not contained in the…

Quantum Physics · Physics 2021-07-01 Alistair W. R. Smith , Johnnie Gray , M. S. Kim

One of the simplest and most effective classical machine learning algorithms is the $k$-nearest neighbors algorithm ($k$NN) which classifies an unknown test state by finding the $k$ nearest neighbors from a set of $M$ train states. Here we…

Quantum Physics · Physics 2021-06-18 Afrad Basheer , A. Afham , Sandeep K. Goyal

Self-testing is a method to characterise an arbitrary quantum system based only on its classical input-output correlations, and plays an important role in device-independent quantum information processing as well as quantum complexity…

Quantum Physics · Physics 2022-05-18 Tony Metger , Thomas Vidick

We study quantum algorithms for testing bipartiteness and expansion of bounded-degree graphs. We give quantum algorithms that solve these problems in time O(N^(1/3)), beating the Omega(sqrt(N)) classical lower bound. For testing expansion,…

Quantum Physics · Physics 2011-09-12 Andris Ambainis , Andrew M. Childs , Yi-Kai Liu

Device-independent certification of quantum devices is of crucial importance for the development of secure quantum information protocols. So far, the most studied scenario corresponds to a system consisting of different non-characterized…

Quantum Physics · Physics 2020-08-26 Ivan Šupić , Matty J. Hoban , Laia Domingo Colomer , Antonio Acín

Self-testing is a phenomenon where the use of specific quantum states or measurements can be inferred solely from the correlations they generate. We introduce a universal method for conducting robustness analysis in the self-testing of…

Quantum Physics · Physics 2026-03-23 Shin-Liang Chen , Nikolai Miklin

Entanglement is a key property in the development of quantum technologies and in the study of quantum many-body simulations. However, entanglement measurement typically requires quantum full-state tomography (FST). Here we present a neural…

Quantum Physics · Physics 2022-09-20 Yulei Huang , Liangyu Che , Chao Wei , Feng Xu , Xinfang Nie , Jun Li , Dawei Lu , Tao Xin

Quantum state tomography (QST) aims at reconstructing the state of a quantum system. However in conventional QST the number of measurements scales exponentially with the number of qubits. Here we propose a QST protocol, in which the…

Quantum Physics · Physics 2024-08-23 Daniele Binosi , Giovanni Garberoglio , Diego Maragnano , Maurizio Dapor , Marco Liscidini