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ACM Transactions on Quantum Computing

A Polytime Quantum Programming Language

Emmanuel Hainry F, Romain Péchoux, Mário Silva

Published Sep 30, 2025• 0 citations

Abstract

As quantum computing emerges as a promising computational paradigm, quantum programming languages provide the tools that bridge the distance between abstract programming and its hardware implementation. In some cases, restricted programming languages may even provide an avenue for more efficient circuit compilation strategies. In this work, we introduce foq , a first-order quantum programming language which allows for quantum control and recursion, and where a syntactically restricted subset of programs ( pfoq ) is shown to be sound and complete for quantum polytime computation. This is achieved by bounding both the recursion depth and the branching width of programs, which we demonstrate to still be compatible with various interesting applications, such as quantum teleportation and the quantum Fourier transform. pfoq constitutes the first programming-language-based characterization of the quantum complexity class fbqp , and we provide a semantics-preserving compilation algorithm such that any pfoq program can be compiled into a quantum circuit that grows polynomially on its number of input qubits, using an anchoring-and-merging technique to solve the problem of branch sequentialization.

DOI: 10.1145/3769851

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Polylogarithmic time delineates a relevant notion of feasibility on several classical computational models such as Boolean circuits or parallel random access machines. As far as the quantum paradigm is concerned, this notion yields the complexity class FBQPOLYLOG of functions approximable in polylogarithmic time with a quantum random-access Turing machine. We introduce a quantum programming language with first-order recursive procedures, which provides the first programming-language-based characterization of FBQPOLYLOG. Each program computes a function in FBQPOLYLOG (soundness) and, conversely, each function of this complexity class is computed by a program (completeness). We also provide a compilation strategy from programs to uniform families of quantum circuits of polylogarithmic depth and polynomial size, whose set of computed functions is known as QNC, and recover the well-known separation result FBQPOLYLOG

\subsetneq

QNC.

Quantum algorithms leverage the use of quantumly-controlled data in order to achieve computational advantage. This implies that the programs use constructs depending on quantum data and not just classical data such as measurement outcomes. Current compilation strategies for quantum control flow involve compiling the branches of a quantum conditional, either in-depth or in-width, which in general leads to circuits of exponential size. This problem is coined as the branch sequentialization problem. We introduce and study a compilation technique for avoiding branch sequentialization on a language that is sound and complete for quantum polynomial time, thus, improving on existing polynomial-size-preserving compilation techniques.