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Related papers: Q2Graph: a modelling tool for measurement-based qu…

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We present "Diagrams of States", a way to graphically represent and analyze how quantum information is elaborated during the execution of quantum circuits. This introductory tutorial illustrates the basics, providing useful examples of…

Quantum Physics · Physics 2009-04-20 Sara Felloni , Alberto Leporati , Giuliano Strini

This work studies how a suitably-designed classical system generates with a quantum-like (QL) state space mediated by a graph. The graph plays a special dual role by directing the topology of the classical network and defining a state space…

Quantum Physics · Physics 2026-03-24 Gregory D. Scholes

The entangled graph states have emerged as an elegant and powerful quantum resource, indeed almost all multiparty protocols can be written in terms of graph states including measurement based quantum computation (MBQC), error correction and…

Quantum Physics · Physics 2009-11-13 Elham Kashefi , Damian Markham , Mehdi Mhalla , Simon Perdrix

Early but promising results in quantum computing have been enabled by the concurrent development of quantum algorithms, devices, and materials. Classical simulation of quantum programs has enabled the design and analysis of algorithms and…

Quantum Physics · Physics 2022-05-17 Bo Fang , M. Yusuf Özkaya , Ang Li , Ümit V. Çatalyürek , Sriram Krishnamoorthy

In the current noisy intermediate-scale quantum (NISQ) era, quantum machine learning is emerging as a dominant paradigm to program gate-based quantum computers. In quantum machine learning, the gates of a quantum circuit are parametrized,…

Quantum Physics · Physics 2022-06-15 Osvaldo Simeone

Graph states are key resources for measurement-based quantum computing, which is particularly promising for photonic systems. Fusions are probabilistic Bell state measurements, measuring pairs of parity operators of two qubits. Fusions can…

Quantum Physics · Physics 2025-07-21 Matthias C. Löbl , Love A. Pettersson , Stefano Paesani , Anders S. Sørensen

This paper introduces an efficient quantum computing method for reducing special graphs in the context of the graph coloring problem. The special graphs considered include both symmetric and non-symmetric graphs where the axis passes…

Quantum Physics · Physics 2025-10-21 Lord Sen , Shyamapada Mukherjee

Measurement-based quantum computing (MBQC), an alternate paradigm for formulating quantum algorithms, can lead to potentially more flexible and efficient implementations as well as to theoretical insights on the role of entanglement in a…

Quantum Physics · Physics 2024-03-05 M. Schwetz , R. M. Noack

We undertake a study of the notion of a quantum graph over arbitrary finite-dimensional $C^*$-algebras $B$ equipped with arbitrary faithful states. Quantum graphs are realised principally as either certain operators on $L^2(B)$, the quantum…

Operator Algebras · Mathematics 2024-11-27 Matthew Daws

Computational advantages gained by quantum algorithms rely largely on the coherence of quantum devices and are generally compromised by decoherence. As an exception, we present a quantum algorithm for graph isomorphism testing whose…

Quantum Physics · Physics 2016-12-22 M. Bruderer , M. B. Plenio

Transformers are increasingly employed for graph data, demonstrating competitive performance in diverse tasks. To incorporate graph information into these models, it is essential to enhance node and edge features with positional encodings.…

We present Tierkreis, a higher-order dataflow graph program representation and runtime designed for compositional, quantum-classical hybrid algorithms. The design of the system is motivated by the remote nature of quantum computers, the…

Quantum Physics · Physics 2023-02-02 Seyon Sivarajah , Lukas Heidemann , Alan Lawrence , Ross Duncan

Entanglement is a fundamental resource for many applications in quantum information processing. Here, we investigate how quantum transport in simple quantum graphs, modeled as controlled two-level quantum systems, can be utilized to…

Quantum Physics · Physics 2025-10-24 Alison A. Silva , D. Bazeia , Fabiano M. Andrade

Current quantum computers have the potential to overcome classical computational methods, however, the capability of the algorithms that can be executed on noisy intermediate-scale quantum devices is limited due to hardware imperfections.…

Quantum Physics · Physics 2023-08-16 Cristian A. Galvis-Florez , Daniel Reitzner , Simo Särkkä

Current noise levels in physical realizations of qubits and quantum operations limit the applicability of conventional methods to characterize entanglement. In this adverse scenario, we follow a quantum variational approach to estimate the…

Quantum Physics · Physics 2022-09-16 A. D. Muñoz-Moller , L. Pereira , L. Zambrano , J. Cortés-Vega , A. Delgado

We consider quantum graph states that can be mapped to directed weighted graphs, also known as directed networks. The geometric measure of entanglement of the states is calculated for the quantum graph states corresponding to arbitrary…

Quantum Physics · Physics 2024-10-01 Kh. P. Gnatenko

The algorithm-specific graph and circuit etching are two strategies for compiling a graph state to implement quantum computation. Benchmark testing exposed limitations to the proto-compiler, Jabalizer giving rise to Etch…

Quantum Physics · Physics 2025-02-27 Greg Bowen , Athena Caesura , Simon Devitt , Madhav Krishnan Vijayan

The graph state formalism is a useful abstraction of entanglement. It is used in some multipartite purification schemes and it adequately represents universal resources for measurement-only quantum computation. We focus in this paper on the…

Quantum Physics · Physics 2007-05-23 Mehdi Mhalla , Simon Perdrix

A quantum computer promises efficient processing of certain computational tasks that are intractable with classical computer technology. While basic principles of a quantum computer have been demonstrated in the laboratory, scalability of…

Quantum Physics · Physics 2007-05-23 Robert Raussendorf , Hans J. Briegel

Dynamic programming is a cornerstone of graph-based optimization. While effective, it scales unfavorably with problem size. In this work, we present QuantGraph, a two-stage quantum-enhanced framework that casts local and global…