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Gram matrix approach to an entanglement analysis of pure states describing $(d,\infty)$ -- quantum systems is being introduced. In particular, maximally entangled states are described as those having a special forms of the corresponding…

Quantum Physics · Physics 2019-12-10 Roman Gielerak , Marek Sawerwain

Counting problems, determining the number of possible states of a large system under certain constraints, play an important role in many areas of science. They naturally arise for complex disordered systems in physics and chemistry, in…

Statistical Mechanics · Physics 2009-05-15 Marc Timme , Frank van Bussel , Denny Fliegner , Sebastian Stolzenberg

Quantum computers can be considered as a natural means for performing machine learning tasks for inherently quantum labeled data. Many quantum machine learning techniques have been developed for solving classification problems, such as…

Quantum Physics · Physics 2025-01-24 Andrey Kardashin , Yerassyl Balkybek , Vladimir V. Palyulin , Konstantin Antipin

Using a graph approach to quantum systems, we prove that descriptions of 3-dim Kochen-Specker (KS) setups as well as descriptions of 3-dim spin systems by means of Greechie lattices that we find in the literature are wrong. Correct lattices…

Quantum Physics · Physics 2010-10-13 Mladen Pavicic , Brendan D. McKay , Norman D. Megill , Kresimir Fresl

The study of multipartite entanglement is much less developed than the bipartite scenario. Recently, a string of results have proposed using tools from Topological Data Analysis (TDA) to attach topological quantities to multipartite states.…

Quantum Physics · Physics 2025-05-08 Raghav Banka , Matthew Hagan , Nathan Wiebe

We propose a method for constructing multi-qubit entangled quantum states representing weighted tripartite graphs. An expression for the entanglement distance for multi-qubit states corresponding to arbitrary tripartite graph structures is…

Quantum Physics · Physics 2026-05-01 Kh. P. Gnatenko

This paper presents a new graph isomorphism invariant, called $\mathfrak{w}$-labeling, that can be used to design a polynomial-time algorithm for solving the graph isomorphism problem for various graph classes. For example, all…

Data Structures and Algorithms · Computer Science 2023-01-24 Alpár Jüttner , Péter Madarasi

Quantum graph states are critical resources for various quantum algorithms, and also determine essential interconnections in distributed quantum computing. There are two schemes for generating graph states probabilistic scheme and…

Hardware Architecture · Computer Science 2025-03-26 Xiangyu Ren , Yuexun Huang , Zhiding Liang , Antonio Barbalace

For graph classification tasks, many traditional kernel methods focus on measuring the similarity between graphs. These methods have achieved great success on resolving graph isomorphism problems. However, in some classification problems,…

Machine Learning · Computer Science 2021-02-18 Jianming Huang , Hiroyuki Kasai

We introduce examples of three- and four-mode entangled Gaussian mixed states that are not detected by the scaling and Peres-Horodecki separability criteria. The presented modification of the scaling criterion resolves this problem. Also it…

Quantum Physics · Physics 2010-12-21 Alexandr Sergeevich , Vladimir I. Man'ko

Conditional correlation networks, within Gaussian Graphical Models (GGM), are widely used to describe the direct interactions between the components of a random vector. In the case of an unlabelled Heterogeneous population, Expectation…

Statistics Theory · Mathematics 2022-03-09 Thomas Lartigue , Stanley Durrleman , Stéphanie Allassonnière

Graph states are a key resource for a number of applications in quantum information theory. Due to the inherent noise in noisy intermediate-scale quantum (NISQ) era devices, it is important to understand the effects noise has on the…

Quantum Physics · Physics 2026-05-27 Aqil Sajjad , Eneet Kaur , Kenneth Goodenough , Don Towsley , Saikat Guha

Molecular graphs generally contain subgraphs (known as groups) that are identifiable and significant in composition, functionality, geometry, etc. Flat latent representations (node embeddings or graph embeddings) fail to represent, and…

Machine Learning · Computer Science 2019-04-05 Daniel T. Chang

The entanglement spectroscopy, initially introduced by Li and Haldane in the context of the fractional quantum Hall effects, has stimulated an extensive range of studies. The entanglement spectrum is the spectrum of the reduced density…

Strongly Correlated Electrons · Physics 2015-10-28 N. Regnault

We consider graph states generated by the action of controlled phase shift operators on a separable state of a multi-qubit system. The case when all the qubits are initially prepared in arbitrary states is investigated. We obtain the…

Quantum Physics · Physics 2024-01-29 N. A. Susulovska

Multi-photon entangled graph states are a fundamental resource in quantum communication networks, distributed quantum computing, and sensing. These states can in principle be created deterministically from quantum emitters such as optically…

Quantum Physics · Physics 2022-08-23 Bikun Li , Sophia E. Economou , Edwin Barnes

Projected Entangled Pair States (PEPS) are recognized as a potent tool for exploring two-dimensional quantum many-body systems. However, a significant challenge emerges when applying conventional PEPS methodologies to systems with periodic…

Strongly Correlated Electrons · Physics 2024-07-23 Shaojun Dong , Chao Wang , Hao Zhang , Meng Zhang , Lixin He

We give combinatorial proofs of some enumeration formulas involving labelled threshold, quasi-threshold, loop-threshold and quasi-loop-threshold graphs. In each case we count by number of vertices and number of components. For threshold…

Combinatorics · Mathematics 2022-03-03 David Galvin , Greyson Wesley , Bailee Zacovic

We introduce techniques for analysing the structure of quantum states of many-body localized (MBL) spin chains by identifying correlation clusters from pairwise correlations. These techniques proceed by interpreting pairwise correlations in…

Disordered Systems and Neural Networks · Physics 2022-02-16 Kévin Hémery , Frank Pollmann , Adam Smith

Graph structures are ubiquitous throughout the natural sciences. Here we consider graph-structured quantum data and describe how to carry out its quantum machine learning via quantum neural networks. In particular, we consider training data…

Quantum Physics · Physics 2021-03-22 Kerstin Beer , Megha Khosla , Julius Köhler , Tobias J. Osborne