arXiv subjects

Emmanuel Hainry

Publications and source records attributed to Emmanuel Hainry.

13 recordsLinked to original sources

arXiv2026

Quantum Term Rewrite Systems: Applications to Complexity Analysis

Term Rewrite Systems (TRS) is a computational model offering a level of abstraction well-suited towards static analysis, e.g., termination or complexity analyses. In this paper, we introduce Quantum Term Rewrite Systems (QTRS), an extension of TRS to quantum computing, thus allowing to benefit from quantum advantage while being able to certify the complexity. We ensure that QTRS correspond to physically realizable processes and adapt techniques to obtain termination certificates or generic bounds on the reduction length. We delineate a class of terminating QTRS that can be compiled to uniform families of quantum circuits of size bounded by the reduction length. Conversely, this class is universal for quantum circuits. In particular, we show a characterization of the class of functions computable in quantum polynomial time, known as $\mathtt{FBQP}$.

cs.LO↗

arXiv2025

Resource-Aware Quantum Programming with General Recursion and Quantum Control

This paper introduces the hybrid quantum language with general recursion $\mathtt{Hyrql}$, driven towards resource-analysis. By design, $\mathtt{Hyrql}$ does not require the specification of an initial set of quantum gates. Hence, it is well amenable towards a generic cost analysis, unlike languages that use different sets of quantum gates, which yield quantum circuits of distinct complexity. Regarding resource-analysis, we show how to relate the runtime of an expressive fragment of $\mathtt{Hyrql}$ programs with the size of the corresponding quantum circuits. We also manage to capture the class of functions computable in quantum polynomial time, which, by Yao's Theorem, corresponds to families of circuits of polynomial size. Consequently, this result paves the way for the use of termination and runtime-analysis techniques designed for classical programs to guarantee bounds on the size of quantum circuits.

cs.LO↗

arXiv2025

Quantum Programming in Polylogarithmic Time

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.

cs.LO↗

arXiv2025

Expectation-based Analysis of Higher-Order Quantum Programs

The paper extends the expectation transformer based analysis of higher-order probabilistic programs to the quantum higher-order setting. The quantum language we are considering can be seen as an extension of PCF, featuring unbounded recursion. The language admits classical and quantum data, as well as a tick operator to account for costs. Our quantum expectation transformer translates such programs into a functional, non-quantum language, enriched with a type and operations over so called cost-structures. By specializing the cost-structure, this methodology makes it possible to study several expectation based properties of quantum programs, such as average case cost, probabilities of events or expected values, in terms of the translated non-quantum programs, this way enabling classical reasoning techniques. As a show-case, we adapt a refinement type system, capable of reasoning on upper-bounds.

cs.LO↗

arXiv2024

Branch Sequentialization in Quantum Polytime

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.

cs.LO↗

arXiv2024

Declassification Policy for Program Complexity Analysis

In automated complexity analysis, noninterference-based type systems statically guarantee, via soundness, the property that well-typed programs compute functions of a given complexity class, e.g., the class FP of functions computable in polynomial time. These characterizations are also extensionally complete -- they capture all functions -- but are not intensionally complete as some polytime algorithms are rejected. This impact on expressive power is an unavoidable cost of achieving a tractable characterization. To overcome this issue, an avenue arising from security applications is to find a relaxation of noninterference based on a declassification mechanism that allows critical data to be released in a safe and controlled manner. Following this path, we present a new and intuitive declassification policy preserving FP-soundness and capturing strictly more programs than existing noninterference-based systems. We show the versatility of the approach: it also provides a new characterization of the class BFF of second-order polynomial time computable functions in a second-order imperative language, with first-order procedure calls. Type inference is tractable: it can be done in polynomial time.

cs.LO↗

arXiv2023

A feasible and unitary quantum programming language

We introduce a novel quantum programming language featuring higher-order programs and quantum controlflow which ensures that all qubit transformations are unitary. Our language boasts a type system guaranteeingboth unitarity and polynomial-time normalization. Unitarity is achieved by using a special modality forsuperpositions while requiring orthogonality among superposed terms. Polynomial-time normalization isachieved using a linear-logic-based type discipline employing Barber and Plotkin duality along with a specificmodality to account for potential duplications. This type discipline also guarantees that derived values havepolynomial size. Our language seamlessly combines the two modalities: quantum circuit programs upholdunitarity, and all programs are evaluated in polynomial time, ensuring their feasibility.

cs.LO↗

arXiv2022

A programming language characterizing quantum polynomial time

We introduce a first-order quantum programming language, named FOQ, whose terminating programs are reversible. We restrict FOQ to a strict and tractable subset, named PFOQ, of terminating programs with bounded width, that provides a first programming language-based characterization of the quantum complexity class FBQP. Finally, we present a tractable semantics-preserving algorithm compiling a PFOQ program to a quantum circuit of size polynomial in the number of input qubits.

cs.LO↗

arXiv2022

Complete and tractable machine-independent characterizations of second-order polytime

The class of Basic Feasible Functionals BFF is the second-order counterpart of the class of first-order functions computable in polynomial time. We present several implicit characterizations of BFF based on a typed programming language of terms. These terms may perform calls to non-recursive imperative procedures. The type discipline has two layers: the terms follow a standard simply-typed discipline and the procedures follow a standard tier-based type discipline. BFF consists exactly of the second-order functionals that are computed by typable and terminating programs. The completeness of this characterization surprisingly still holds in the absence of lambda-abstraction. Moreover, the termination requirement can be specified as a completeness-preserving instance, which can be decided in time quadratic in the size of the program. As typing is decidable in polynomial time, we obtain the first tractable (i.e., decidable in polynomial time), sound, complete, and implicit characterization of BFF, thus solving a problem opened for more than 20 years.

cs.LO↗

arXiv2021

A tier-based typed programming language characterizing Feasible Functionals

The class of Basic Feasible Functionals BFF$_2$ is the type-2 counterpart of the class FP of type-1 functions computable in polynomial time. Several characterizations have been suggested in the literature, but none of these present a programming language with a type system guaranteeing this complexity bound. We give a characterization of BFF$_2$ based on an imperative language with oracle calls using a tier-based type system whose inference is decidable. Such a characterization should make it possible to link higher-order complexity with programming theory. The low complexity (cubic in the size of the program) of the type inference algorithm contrasts with the intractability of the aforementioned methods and does not overly constrain the expressive power of the language.

cs.LO↗

arXiv2018

A Type-Based Complexity Analysis of Object Oriented Programs

A type system is introduced for a generic Object Oriented programming language in order to infer resource upper bounds. A sound andcomplete characterization of the set of polynomial time computable functions is obtained. As a consequence, the heap-space and thestack-space requirements of typed programs are also bounded polynomially. This type system is inspired by previous works on ImplicitComputational Complexity, using tiering and non-interference techniques. The presented methodology has several advantages. First, itprovides explicit big $O$ polynomial upper bounds to the programmer, hence its use could allow the programmer to avoid memory errors.Second, type checking is decidable in polynomial time. Last, it has a good expressivity since it analyzes most object oriented featureslike inheritance, overload, override and recursion. Moreover it can deal with loops guarded by objects and can also be extended tostatements that alter the control flow like break or return.

cs.PL↗

arXiv2018

Theory of higher order interpretations and application to Basic Feasible Functions

Interpretation methods and their restrictions to polynomials have been deeply used to control the termination and complexity of first-order term rewrite systems. This paper extends interpretation methods to a pure higher order functional language. We develop a theory of higher order functions that is well-suited for the complexity analysis of this programming language. The interpretation domain is a complete lattice and, consequently, we express program interpretation in terms of a least fixpoint. As an application, by bounding interpretations by higher order polynomials, we characterize Basic Feasible Functions at any order.

cs.LO↗

arXiv2016

A Framework for Algebraic Characterizations in Recursive Analysis

Algebraic characterizations of the computational aspects of functions defined over the real numbers provide very effective tool to understand what computability and complexity over the reals, and generally over continuous spaces, mean. This is relevant for both communities of computer scientists and mathematical analysts, particularly the latter who do not understand (and/or like) the language of machines and string encodings. Recursive analysis can be considered the most standard framework of computation over continuous spaces, it is however defined in a very machine specific way which does not leave much to intuitiveness. Recently several characterizations, in the form of function algebras, of recursively computable functions and some sub-recursive classes were introduced. These characterizations shed light on the hidden behavior of recursive analysis as they convert complex computational operations on sequences of real objects to "simple" intuitive mathematical operations such as integration or taking limits. The authors previously presented a framework for obtaining algebraic characterizations at the complexity level over compact domains. The current paper presents a comprehensive extension to that framework. Though we focus our attention in this paper on functions defined over the whole real line, the framework, and accordingly the obtained results, can be easily extended to functions defined over arbitrary domains.

cs.LO↗