This paper investigates foundational quantum computing protocols from the intuitive perspective of categorical tensor-graph semantics within the category \textbf{FHilb}. While conventional Hilbert-space formalisms often conceal the structural nature of quantum algorithms behind high-dimensional matrix operations, the topological framework directly encodes algorithmic functionalities into their graphical skeletons. We provide a comprehensive topological reinterpretation of the Bernstein--Vazirani and Simon algorithms, demonstrating how topological transformations distill their core mathematical essence and clarify the operational mechanisms of oracles. Going beyond the standard qubit model, we construct explicit representations for the qutrit-adapted topological Deutsch--Jozsa and single-shot Grover algorithms. In particular, we establish a necessary and sufficient condition for the single-shot Grover search. We further implement CNOT gates via complementary Frobenius structures and investigate a diagrammatic decomposition scheme for the W-state preparation protocol. By bridging tensor category theory with practical quantum algorithmic design, this work furnishes a composable, scalable diagrammatic toolkit essential for automated circuit optimization across the evolving quantum hardware ecosystem.
Comments
20 pages, new template with updated references and simplified the W-state preparation
This paper investigates foundational quantum computing protocols from the intuitive perspective of categorical tensor-graph semantics within the category \textbf{FHilb}. While conventional Hilbert-space formalisms often conceal the structural nature of quantum algorithms behind high-dimensional matrix operations, the topological framework directly encodes algorithmic functionalities into their graphical skeletons. We provide a comprehensive topological reinterpretation of the Bernstein--Vazirani and Simon algorithms, demonstrating how topological transformations distill their core mathematical essence and clarify the operational mechanisms of oracles. Going beyond the standard qubit model, we construct explicit representations for the qutrit-adapted topological Deutsch--Jozsa and single-shot Grover algorithms. In particular, we establish a necessary and sufficient condition for the single-shot Grover search. We further implement CNOT gates via complementary Frobenius structures and investigate a diagrammatic decomposition scheme for the W-state preparation protocol. By bridging tensor category theory with practical quantum algorithmic design, this work furnishes a composable, scalable diagrammatic toolkit essential for automated circuit optimization across the evolving quantum hardware ecosystem.
We use a categorical topological semantics to examine the Deutsch-Jozsa, hidden subgroup and single-shot Grover algorithms. This reveals important structures hidden by conventional algebraic presentations, and allows novel proofs of correctness via local topological operations, giving for the first time a satisfying high-level explanation for why these procedures work. We also investigate generalizations of these algorithms, providing improved analyses of those already in the literature, and a new generalization of the single-shot Grover algorithm.
This paper explores the application of category theory to provide a semantic framework for quantum vector spaces, which are fundamental to quantum mechanics and quantum information. We move beyond the traditional algebraic and analytical descriptions of Hilbert spaces to adopt a more abstract, compositional, and graphical approach rooted in monoidal categories. This categorical perspective allows for a unified understanding of quantum phenomena, including superposition, entanglement, and measurement, by representing quantum systems as objects and processes as morphisms. We delve into the concept of compact closed categories and dagger symmetric monoidal categories as the appropriate mathematical structures to capture the essential features of quantum theory, such as duality, adjoints, and the tensor product for composite systems. Furthermore, the paper discusses how graphical calculi, arising from these categorical structures, offer an intuitive and rigorous method for reasoning about quantum protocols and computations, facilitating the design and verification of quantum algorithms. By providing a high-level, axiomatic framework, categorical semantics clarifies the foundational principles of quantum mechanics and opens new avenues for developing quantum programming languages and understanding the interplay between quantum information and computation.
The ZX-calculus was introduced as a graphical language able to represent specific quantum primitives in an intuitive way. The recent completeness results have shown the theoretical possibility of a purely graphical description of quantum processes. However, in practice, such approaches are limited by the intrinsic low level nature of ZX calculus. The scalable notations have been proposed as an attempt to recover an higher level point of view while maintaining the topological rewriting rules of a graphical language. We demonstrate that the scalable ZX-calculus provides a formal, intuitive, and compact framework to describe and prove quantum algorithms. As a proof of concept, we consider the standard oracle-based quantum algorithms: Deutsch-Jozsa, Bernstein-Vazirani, Simon, and Grover algorithms, and we show they can be described and proved graphically.
The rapid advancement of quantum-inspired classical algorithms, particularly Quantics Tensor Trains (QTT), has demonstrated that exponentially large vectors can be manipulated efficiently via Matrix Product States (MPS). Conventionally, the compression of these tensor networks relies exclusively on Singular Value Decomposition (SVD)-based truncation. While SVD is optimal for minimizing the Frobenius norm error, it remains structurally blind to exact algebraic correlations, such as reversible logic gates or Clifford symmetries, that do not require numerical approximation to factor out. In this work, we propose a hybrid compression protocol that integrates the topological rigor of ZX-Calculus with the numerical power of SVD. We construct an explicit isomorphism between Rank-3 MPS tensors and ZX-diagrams, allowing us to subject QTT representations to formal diagrammatic rewriting rules prior to numerical truncation. We establish that this Topological Preconditioning can algebraically collapse the effective bond dimension (χ) and T-count of the underlying tensor network without information loss. By benchmarking the algorithmic implementation against hardware-accelerated SVD on discretized functions and stabilizer states, we demonstrate that ZX-driven algebraic erasure fundamentally bypasses standard [Formula: see text] bottlenecks, yielding up to a computational speedup. Finally, we formalize this advantage by defining the structural complexity class [Formula: see text], proving that for systems characterized by algebraic symmetry, this work reflects our ongoing effort to deepen understanding of Categorical Quantum Mechanics, aiming to contribute to the optimization of high-dimensional linear algebra.
Representations of quantum computations are almost always based on a tensor product ⊗-structure. This coincides with what we are able to execute in our experiments, as well as what we observe in Nature, but it makes certain familiar quantum primitives convoluted. Reversible classical circuits, diagonal operations or controlled unitaries all have very elegant and simple matrix representations that cannot be expressed succinctly as a circuit in a simple gate set, complicating quantum algorithm design and circuit optimization. We propose a new additive presentation of quantum computation to address this. We show how conventional circuits can be expressed in the additive space and how they can be recovered. In particular in our formalism we are able to synthesize high-level multi-controlled primitives from low-level circuit decompositions, making it an invaluable tool for circuit optimization. Our formulation also accepts a circuit-like diagrammatic representation and proposes a novel and simple interpretation of quantum computation.
This paper investigates the integration of topology into quantum algorithm design, aiming to enhance the efficiency and robustness of quantum computations. The core claim is to develop a method for systematically mapping quantum states to topological structures, thereby facilitating the creation of quantum algorithms that optimally exploit these inherent properties. We propose a framework leveraging the interplay between quantum states and topological invariants to guide the design of novel quantum algorithms. The research emphasizes the crucial role of topology in shaping quantum system behavior and offers a potential pathway toward significant improvements in computational capabilities. Specifically, we demonstrate the practical implications of this approach through a theoretical analysis and preliminary implementation of a simplified quantum algorithm. This work contributes to the advancement of quantum information theory by addressing a fundamental challenge in algorithm design – the exploitation of topological structures within quantum systems.