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In this paper, we introduce a technique for contracting (i.e. numerically evaluating) ZX-diagrams whose complexity scales with their rank-width, a graph parameter that behaves nicely under ZX rewrite rules. Given a rank-decomposition of…

Quantum Physics · Physics 2026-03-10 Fedor Kuyanov , Aleks Kissinger

Application-specific quantum computers offer the most efficient means to tackle problems intractable by classical computers. Realizing these architectures necessitates a deep understanding of quantum circuit properties and their…

The stabilizer ZX-calculus is a rigorous graphical language for reasoning about quantum mechanics.The language is sound and complete: a stabilizer ZX-diagram can be transformed into another one if and only if these two diagrams represent…

Quantum Physics · Physics 2017-01-04 Miriam Backens , Simon Perdrix , Quanlong Wang

The Scalable ZX-calculus is a compact graphical language used to reason about linear maps between quantum states. These diagrams have multiple applications, but they frequently have to be constructed in a case-by-case basis. In this work we…

Quantum Physics · Physics 2023-11-17 Augustin Borgna , Rafael Romero

The mathematical formalism necessary for the diagramatic evaluation of quantum corrections to a conformally invariant field theory for a self-interacting scalar field on a curved manifold with boundary is considered. The evaluation of…

High Energy Physics - Theory · Physics 2009-11-07 George Tsoupros

Categorical quantum mechanics and the Wolfram model offer distinct but complementary approaches to studying the relationship between diagrammatic rewriting systems over combinatorial structures and the foundations of physics; the objective…

Logic in Computer Science · Computer Science 2020-10-07 Jonathan Gorard , Manojna Namuduri , Xerxes D. Arsiwalla

Quantum algorithms are a promising framework for unfolding the causal configurations of multiloop Feynman diagrams, which is equivalent to querying the \textit{directed acyclic graph} (DAG) configurations of undirected graphs in graph…

Quantum Physics · Physics 2025-07-25 Selomit Ramírez-Uribe , Andrés E. Rentería-Olivo , Germán Rodrigo

We present a system of equations between Clifford circuits, all derivable in the ZX-calculus, and formalised as rewrite rules in the Quantomatic proof assistant. By combining these rules with some non-trivial simplification procedures…

Quantum Physics · Physics 2019-01-30 Andrew Fagan , Ross Duncan

Parameterized quantum circuits (PQC, aka, variational quantum circuits) are among the proposals for a computational advantage over classical computation of near-term (not fault tolerant) digital quantum computers. PQCs have to be "trained"…

Quantum Physics · Physics 2019-04-01 Evgenii Dolzhkov , Bahman Ghandchi , Dirk Oliver Theis

Distributed quantum computing (DQC) connects many small quantum processors into a single logical machine, offering a practical route to scalable quantum computation. However, most existing DQC paradigms are structure-agnostic. Circuit…

Quantum Physics · Physics 2026-03-10 Yuwen Huang , Xiaojun Lin , Bin Luo , John C. S. Lui

Unlike fixed designs, programmable circuit designs support an infinite number of operators. The functionality of a programmable circuit can be altered by simply changing the angle values of the rotation gates in the circuit. Here, we…

Quantum Physics · Physics 2012-12-27 Anmer Daskin , Ananth Grama , Giorgos Kollias , Sabre Kais

ZX-calculus is a high-level graphical formalism for qubit computation. In this paper we give the ZX-rules that enable one to derive all equations between 2-qubit Clifford+T quantum circuits. Our rule set is only a small extension of the…

Quantum Physics · Physics 2018-06-13 Bob Coecke , Quanlong Wang

In the noisy intermediate-scale quantum (NISQ) era, two-qubit gates in quantum circuits are more susceptible to noise than single-qubit gates. Therefore, reducing the number of two-qubit gates is crucial for improving circuit efficiency and…

Quantum Physics · Physics 2025-07-22 Kai Chen , Wen Liu , GuoSheng Xu , Yangzhi Li , Maoduo Li , Shouli He

The quantum approximate optimisation ansatz (QAOA) is one of the flagship algorithms used to tackle combinatorial optimisation on graphs problems using a quantum computer, and is considered a strong candidate for early fault-tolerant…

Quantum Physics · Physics 2025-06-24 Yann Beaujeault-Taudière

Due to the rapid development of quantum computing, the compact representation of quantum operations based on decision diagrams has been received more and more attraction. Since variable orders have a significant impact on the size of the…

Quantum Physics · Physics 2022-07-26 Yonghong Li , Hao Miao

Variational quantum circuits characterise the state of a quantum system through the use of parameters that are optimised using classical optimisation procedures that typically rely on gradient information. The circuit-execution complexity…

Quantum Physics · Physics 2023-07-28 Sayantan Pramanik , Chaitanya Murti , M Girish Chandra

Whether parameterized quantum circuits (PQCs) can be systematically constructed to be both trainable and expressive remains an open question. Highly expressive PQCs often exhibit barren plateaus, while several trainable alternatives admit…

Quantum Physics · Physics 2026-03-17 Peter Röseler , Dennis Willsch , Kristel Michielsen

We study the costs and benefits of different quantum approaches to finding approximate solutions of constrained combinatorial optimization problems with a focus on Maximum Independent Set. In the Lagrange multiplier approach we analyze the…

Quantum Physics · Physics 2024-08-13 Zain H. Saleem , Teague Tomesh , Bilal Tariq , Martin Suchara

Parametrized quantum optical circuits are a class of quantum circuits in which the carriers of quantum information are photons and the gates are optical transformations. Classically optimizing these circuits is challenging due to the…

Quantum Physics · Physics 2020-12-02 Filippo M. Miatto , Nicolás Quesada

Parameterized quantum circuits (PQCs) have emerged as a promising approach for quantum neural networks. However, understanding their expressive power in accomplishing machine learning tasks remains a crucial question. This paper…

Quantum Physics · Physics 2024-10-10 Zhan Yu , Qiuhao Chen , Yuling Jiao , Yinan Li , Xiliang Lu , Xin Wang , Jerry Zhijian Yang