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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

We describe a quantum-assisted machine learning (QAML) method in which multivariate data is encoded into quantum states in a Hilbert space whose dimension is exponentially large in the length of the data vector. Learning in this space…

Quantum Physics · Physics 2021-10-13 Michael L. Wall , Giuseppe D'Aguanno

Invariant theory is concerned with functions that do not change under the action of a given group. Here we communicate an approach based on tensor networks to represent polynomial local unitary invariants of quantum states. This graphical…

Quantum Physics · Physics 2013-11-13 Jacob Biamonte , Ville Bergholm , Marco Lanzagorta

We introduce an optimal strategy to sample quantum outcomes of local measurement strings for isometric tensor network states. Our method generates samples based on an exact cumulative bounding function, without prior knowledge, in the…

Quantum Physics · Physics 2025-04-23 Marco Ballarin , Pietro Silvi , Simone Montangero , Daniel Jaschke

Modern deep learning has enabled unprecedented achievements in various domains. Nonetheless, employment of machine learning for wave function representations is focused on more traditional architectures such as restricted Boltzmann machines…

Quantum Physics · Physics 2019-02-20 Yoav Levine , Or Sharir , Nadav Cohen , Amnon Shashua

The objective of this paper concerns at first the motivation and the method of Shor's algorithm including an excursion into quantum mechanics and quantum computing introducing an algorithmic description of the method. The corner stone of…

Discrete Mathematics · Computer Science 2022-06-03 Gérard Fleury , Philippe Lacomme

This work explores the use of a tree tensor network ansatz to simulate the ground state of a local Hamiltonian on a two-dimensional lattice. By exploiting the entropic area law, the tree tensor network ansatz seems to produce quasi-exact…

Strongly Correlated Electrons · Physics 2009-12-21 L. Tagliacozzo , G. Evenbly , G. Vidal

Along the way initiated by Carleo and Troyer [1], we construct the neural-network quantum state of transverse-field Ising model(TFIM) by an unsupervised machine learning method. Such a wave function is a map from the spin-configuration…

Disordered Systems and Neural Networks · Physics 2020-01-08 Han-qing Shi , Xiao-yue Sun , Ding-fang Zeng

We present a framework for certifying entanglement properties of quantum states and measurements in line networks. The framework is based on the generalised Choi isomorphism, which can be used to map bipartite states and measurements into…

Quantum Physics · Physics 2025-06-13 Sophie Egelhaaf , Roope Uola

We introduce an experimentally accessible network representation for many-body quantum states based on entanglement between all pairs of its constituents. We illustrate the power of this representation by applying it to a paradigmatic spin…

Quantum Physics · Physics 2022-06-30 Boris Sokolov , Matteo A. C. Rossi , Guillermo García-Pérez , Sabrina Maniscalco

Transport through correlated nanoscale systems underpins the operation of quantum-dot and molecular-scale devices, yet accurate simulations of large open quantum systems remain computationally challenging as system size increases.…

Mesoscale and Nanoscale Physics · Physics 2026-04-09 Maximilian Streitberger , Marko J. Rančić

The number of steps any classical computer requires in order to find the prime factors of an $l$-digit integer $N$ increases exponentially with $l$, at least using algorithms known at present. Factoring large integers is therefore…

Tensor networks have been successfully applied in simulation of quantum physical systems for decades. Recently, they have also been employed in classical simulation of quantum computing, in particular, random quantum circuits. This paper…

Quantum Physics · Physics 2025-07-08 Xin Hong , Xiangzhen Zhou , Sanjiang Li , Yuan Feng , Mingsheng Ying

The recognition that large classes of quantum many-body systems have limited entanglement in the ground and low-lying excited states led to dramatic advances in their numerical simulation via so-called tensor networks. However, global…

Strongly Correlated Electrons · Physics 2020-04-02 Marek M. Rams , Michael Zwolak

One of the most promising applications of quantum networks is entanglement assisted sensing. The field of quantum metrology exploits quantum correlations to improve the precision bound for applications such as precision timekeeping, field…

Quantum Physics · Physics 2025-01-10 Emily A. Van Milligen , Christos N. Gagatsos , Eneet Kaur , Don Towsley , Saikat Guha

Although tensor networks are powerful tools for simulating low-dimensional quantum physics, tensor network algorithms are very computationally costly in higher spatial dimensions. We introduce quantum gauge networks: a different kind of…

Quantum Physics · Physics 2023-09-20 Kevin Slagle

We investigate the entanglement of the ground state in the quantum networks that their nodes are considered as quantum harmonic oscillators. To this aim, the Schmidt numbers and entanglement entropy between two arbitrary partitions of a…

Quantum Physics · Physics 2016-11-25 M. A. Jafarizadeh , S. Nami , F. Eghbalifam

When considered as orthogonal bases in distinct vector spaces, the unit vectors of polarization directions and the Laguerre-Gaussian modes of polarization amplitude are inseparable, constituting a so-called classical entangled light beam.…

Quantum Physics · Physics 2023-01-04 Wei Wang , Ziyang You , Shuangpeng Wang , Zikang Tang , Hou Ian

We report an experimental demonstration of a complied version of Shor's algorithm using four photonic qubits. We choose the simplest instance of this algorithm, that is, factorization of N=15 in the case that the period $r=2$ and exploit a…

Quantum Physics · Physics 2008-10-16 Chao-Yang Lu , Daniel E. Browne , Tao Yang , Jian-Wei Pan

We introduce an efficient method TTN-HEOM for exactly calculating the open quantum dynamics for driven quantum systems interacting with highly structured bosonic baths by combining the tree tensor network (TTN) decomposition scheme to the…

Quantum Physics · Physics 2025-10-01 Xinxian Chen , Ignacio Franco