English
Related papers

Related papers: Entanglement in a quantum annealing processor

200 papers

Using the concept of non-degenerate Bell inequality, we show that quantum entanglement, the critical resource for various quantum information processing tasks, can be quantified for any unknown quantum states in a semi-device-independent…

Efficiently entangling pairs of qubits is essential to fully harness the power of quantum computing. Here, we devise an exact protocol that simultaneously entangles arbitrary pairs of qubits on a trapped-ion quantum computer. The protocol…

Decoherence is a manifestation of the coupling of a system with its environment. The resulting loss of information can hamper the functioning of quantum devices, hence the need of understanding its origin and dynamics. Decoherence can stem…

This paper explores the applications of quantum annealing (QA) and classical simulated annealing (SA) to a suite of combinatorial optimization problems in machine learning, namely feature selection, instance selection, and clustering. We…

Quantum Physics · Physics 2025-07-22 Chloe Pomeroy , Aleksandar Pramov , Karishma Thakrar , Lakshmi Yendapalli

Quantum annealing provides a way of solving optimization problems by encoding them as Ising spin models which are implemented using physical qubits. The solution of the optimization problem then corresponds to the ground state of the…

Quantum Physics · Physics 2017-10-16 Nicholas Chancellor , Stefan Zohren , Paul A. Warburton

Complete and precise characterization of a quantum dynamical process can be achieved via the method of quantum process tomography. Using a source of correlated photons, we have implemented several methods investigating a wide range of…

Quantum entanglement of identical particles is essential in quantum information theory. Yet, its correct determination remains an open issue hindering the general understanding and exploitation of many-particle systems. Operator-based…

Quantum Physics · Physics 2016-03-08 Rosario Lo Franco , Giuseppe Compagno

Entanglement represents one of the most important conceptual advances in physics during the last century and is also one of the most essential resources in quantum information science. However, entanglement is fragile and its potential…

Entanglement is a counterintuitive feature of quantum physics that is at the heart of quantum technology. High-dimensional quantum states offer unique advantages in various quantum information tasks. Integrated photonic chips have recently…

Quantum metrology is the use of genuinely quantum properties such as entanglement as a resource to outperform classical sensing strategies. Typically, entanglement is created by implementing gate operations or inducing many-body…

Quantum Physics · Physics 2021-06-10 Atsuki Yoshinaga , Mamiko Tatsuta , Yuichiro Matsuzaki

We introduce and review briefly the phenomenon of quantum annealing and analog computation. The role of quantum fluctuation (tunneling) in random systems with rugged (free) energy landscapes having macroscopic barriers are discussed to…

Statistical Mechanics · Physics 2023-10-16 Bikas K Chakrabarti , Sudip Mukherjee

Geometry and dimensionality have played crucial roles in our understanding of the fundamental laws of nature, with examples ranging from curved space-time in general relativity to modern theories of quantum gravity. In quantum many-body…

Quantum Physics · Physics 2025-04-10 Qiming Wu , Yue Shi , Jiehang Zhang

Entanglement is an essential resource in current experimental implementations for quantum information processing. We review a class of experiments exploiting photonic entanglement, ranging from one-way quantum computing over quantum…

Quantum Physics · Physics 2009-11-13 Robert Prevedel , Markus Aspelmeyer , Caslav Brukner , Thomas Jennewein , Anton Zeilinger

Quantum annealers are specialized quantum computers for solving combinatorial optimization problems using special characteristics of quantum computing (QC), such as superposition, entanglement, and quantum tunneling. Theoretically, quantum…

Software Engineering · Computer Science 2024-07-29 Xinyi Wang , Asmar Muqeet , Tao Yue , Shaukat Ali , Paolo Arcaini

Quantum computing is an information processing paradigm that uses quantum-mechanical properties to speedup computationally hard problems. Although promising, existing gate-based quantum computers consist of only a few dozen qubits and are…

Quantum Physics · Physics 2021-08-26 Ramin Ayanzadeh , Poulami Das , Swamit S. Tannu , Moinuddin Qureshi

Conventional information processors freely convert information between different physical carriers to process, store, or transmit information. It seems plausible that quantum information will also be held by different physical carriers in…

Quantum Physics · Physics 2020-05-21 Yiheng Lin , David R. Leibrandt , Dietrich Leibfried , Chin-wen Chou

Quantum entanglement is one of the most prominent features of quantum mechanics and forms the basis of quantum information technologies. Here we present a novel method for the creation of quantum entanglement in multipartite and…

Quantum Physics · Physics 2017-02-24 Mario Krenn , Armin Hochrainer , Mayukh Lahiri , Anton Zeilinger

Quantum entanglement offers powerful opportunities for enhancing measurement sensitivity beyond classical limits, with optical atomic clocks serving as a leading platform for such advances. This chapter introduces the principles of…

Quantum Physics · Physics 2025-12-04 Raphael Kaubruegger , Adam M. Kaufman

Quantum annealing aims to solve combinatorial optimization problems mapped on to Ising interactions between quantum spins. A critical factor that limits the success of a quantum annealer is its sensitivity to noise, and intensive research…

Quantum Physics · Physics 2019-01-29 Shruti Puri , Christian Kraglund Andersen , Arne L. Grimsmo , Alexandre Blais

It is a fundamental, but still elusive question whether the schemes based on quantum mechanics, in particular on quantum entanglement, can be used for classical information processing and machine learning. Even partial answer to this…

Machine Learning · Statistics 2022-06-24 Yuhan Liu , Xiao Zhang , Maciej Lewenstein , Shi-Ju Ran