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arXiv:2512.22383

Symbolic Specification and Reasoning for Quantum Data and Operations

Mingsheng Ying

cs.PLcs.LOquant-phSubmitted Dec 26, 2025• Announced Dec 30, 2025• 0 citations
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Abstract

In quantum information and computation research, symbolic methods have been widely used for human specification and reasoning about quantum states and operations. At the same time, they are essential for ensuring the scalability and efficiency of automated reasoning and verification tools for quantum algorithms and programs. However, a formal theory for symbolic specification and reasoning about quantum data and operations is still lacking, which significantly limits the practical applicability of automated verification techniques in quantum computing. In this paper, we present a general logical framework, called Symbolic Operator Logic $\mathbf{SOL}$, which enables symbolic specification and reasoning about quantum data and operations. Within this framework, a classical first-order logical language is embedded into a language of formal operators used to specify quantum data and operations, including their recursive definitions. This embedding allows reasoning about their properties modulo a chosen theory of the underlying classical data (e.g., Boolean algebra or group theory), thereby leveraging existing automated verification tools developed for classical computing. It should be emphasised that this embedding of classical first-order logic into $\mathbf{SOL}$ is precisely what makes the symbolic method possible. We envision that this framework can provide a conceptual foundation for the formal verification and automated theorem proving of quantum computation and information in proof assistants such as Lean, Coq, and related systems.

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In quantum information and computation research, symbolic methods have been widely used for human specification and reasoning about quantum states and operations. At the same time, they are essential for ensuring the scalability and efficiency of automated reasoning and verification tools for quantum algorithms and programs. However, a formal theory for symbolic specification and reasoning about quantum data and operations is still lacking, which significantly limits the practical applicability of automated verification techniques in quantum computing.
In this paper, we present a general logical framework, called Symbolic Operator Logic SOL\mathbf{SOL}SOL, which enables symbolic specification and reasoning about quantum data and operations. Within this framework, a classical first-order logical language is embedded into a language of formal operators used to specify quantum data and operations, including their recursive definitions. This embedding allows reasoning about their properties modulo a chosen theory of the underlying classical data (e.g., Boolean algebra or group theory), thereby leveraging existing automated verification tools developed for classical computing. It should be emphasised that this embedding of classical first-order logic into SOL\mathbf{SOL}SOL is precisely what makes the symbolic method possible.
We envision that this framework can provide a conceptual foundation for the formal verification and automated theorem proving of quantum computation and information in proof assistants such as Lean, Coq, and related systems.
The verification of quantum computing algorithms presents a significant hurdle due to the probabilistic nature of quantum mechanics and the complex entanglement inherent in quantum computations. This paper proposes a novel approach to address this challenge by developing a formal language and a corresponding verification tool tailored explicitly for quantum algorithm specification and verification. The system leverages concepts from quantum information theory and formal methods to provide a rigorous framework for ensuring the correctness of quantum algorithms. We introduce a new formalism that allows for precise description of quantum circuits and their operations, combined with automated theorem proving techniques to systematically verify the algorithm's behavior against a given specification. The key innovation lies in the ability to reason about quantum states and measurements within a formal setting, enabling a more comprehensive understanding and validation of these algorithms. This work lays the foundation for increased confidence in the development and deployment of quantum computing technologies.
CoqQ is a framework for reasoning about quantum programs in the Coq proof assistant. Its main components are: a deeply embedded quantum programming language, in which classic quantum algorithms are easily expressed, and an expressive program logic for proving properties of programs. CoqQ is foundational: the program logic is formally proved sound with respect to a denotational semantics based on state-of-art mathematical libraries (MathComp and MathComp Analysis). CoqQ is also practical: assertions can use Dirac expressions, which eases concise specifications, and proofs can exploit local and parallel reasoning, which minimizes verification effort. We illustrate the applicability of CoqQ with many examples from the literature.
Quantum computing (QC) represents the future of computing systems, but the tools for reasoning about the quantum model of computation, in which the laws obeyed are those on the quantum mechanical scale, are still a mix of linear algebra and Dirac notation; two subjects more suitable for physicists, rather than computer scientists and software engineers. On this ground, we believe it is possible to provide a more intuitive approach to thinking and writing about quantum computing systems, in order to simplify the design of quantum algorithms and the development of quantum software. In this paper, we move the first step in such direction, introducing a specification language as the tool to represent the operations of a quantum computer via axiomatic definitions, by adopting the same symbolisms and reasoning principles used by formal methods in software engineering. We name this approach formal quantum software engineering (F-QSE). This work assumes familiarity with the basic principles of quantum mechanics (QM), with the use of Zed (Z) which is a formal language of software engineering (SE), and with the notation and techniques of first-order logic (FOL) and functional programming (FP).
Automated theorem proving, or more broadly automated reasoning, aims at using computer programs to automatically prove or disprove mathematical theorems and logical statements. It takes on an essential role across a vast array of applications and the quest for enhanced theorem-proving capabilities remains a prominent pursuit in artificial intelligence. Here, we propose a generic framework for quantum automated theorem proving, where the intrinsic quantum superposition and entanglement features would lead to potential advantages. In particular, we introduce quantum representations of knowledge bases and propose corresponding reasoning algorithms for a variety of tasks. We show how automated reasoning can be achieved with quantum resolution in both propositional and first-order logic with quadratically reduced query complexity. In addition, we propose the quantum algebraic proving method for geometric theorems, extending Wu's algebraic approach beyond the classical setting. Through concrete examples, including geometry problems from the International Mathematical Olympiad, we demonstrate how a quantum computer may prove geometric theorems with quadratic better query complexity. Our results establish a primary approach towards building quantum automatic theorem provers, which would be crucial for practical applications of both near-term and future quantum technologies.
A first-order logic with quantum variables is needed as an assertion language for specifying and reasoning about various properties (e.g. correctness) of quantum programs. Surprisingly, such a logic is missing in the literature, and the existing first-order Birkhoff-von Neumann quantum logic deals with only classical variables and quantifications over them. In this paper, we fill in this gap by introducing a first-order extension of Birkhoff-von Neumann quantum logic with universal and existential quantifiers over quantum variables. Examples are presented to show our logic is particularly suitable for specifying some important properties studied in quantum computation and quantum information. We further incorporate this logic into quantum Hoare logic as an assertion logic so that it can play a role similar to that of first-order logic for classical Hoare logic and BI-logic for separation logic. In particular, we show how it can be used to define and derive quantum generalisations of some adaptation rules that have been applied to significantly simplify verification of classical programs. It is expected that the assertion logic defined in this paper - first-order quantum logic with quantum variables - can be combined with various quantum program logics to serve as a solid logical foundation upon which verification tools can be built using proof assistants such as Coq and Isabelle/HOL.
This paper proposes a novel approach to symbolic reasoning utilizing quantum neural networks (QNNs). Traditional symbolic reasoning systems face limitations due to the computational bottlenecks inherent in classical logic processing. This work introduces a framework where logical operations are translated into quantum operations, leveraging the principles of quantum mechanics to perform reasoning. The core mechanism involves utilizing a QNN to process symbolic data, exploiting quantum entanglement to facilitate knowledge representation and propagation. We demonstrate the potential for significantly enhanced efficiency in symbolic inference compared to conventional methods. This research contributes to the burgeoning field of quantum computing by exploring a practical application of QNNs in a domain with well-defined logical structures – symbolic reasoning. The proposed system offers a pathway towards scalable and potentially faster solutions for complex reasoning tasks.