arXiv subjects

Matthijs Vákár

Publications and source records attributed to Matthijs Vákár.

At least 19 recordsLinked to original sources

arXiv2026

Unraveling the iterative CHAD

Combinatory Homomorphic Automatic Differentiation (CHAD) was originally formulated as a semantics-driven source-to-source transformation for reverse-mode automatic differentiation of total functional programs. We extend CHAD to programs with partial operations, data-dependent conditionals, and while-loops, preserving its defining principle of structure-preserving semantics. Our main contribution is the introduction of iteration-extensive indexed categories, which integrate iteration into dependently typed programming languages. Iteration in the base category lifts to parameterized initial algebras in the indexed category, yielding fibred iteration on the op-Grothendieck construction. Its total category is the category of containers associated with the dependently typed target language. This framework characterizes iterative CHAD as the unique iterative Freyd category morphism from the source language's syntactic category to the target language's category of containers that maps each primitive operation to its transposed derivative. Using the universal property of the syntactic model, we prove that the transformed programs compute the reverse-mode derivatives of the original programs. The resulting theory connects fixpoint operators in indexed categories with a structure-preserving construction and correctness proof for iterative CHAD.

cs.PL↗

arXiv2026

Free Doubly-Infinitary Distributive Categories are Cartesian Closed

We study the composite free completion Dist(C) := Fam(Fam(C^op)^op), obtained by first freely adjoining small products and then freely adjoining small coproducts. A natural pseudodistributive law equips this endo-pseudofunctor with a composite pseudomonad structure. Its pseudoalgebras are precisely the categories with small products and small coproducts in which small products distribute over small coproducts. We call such categories doubly-infinitary distributive. This condition is natural, but does not seem to have been systematically isolated in the literature. Thus Dist(C) is the free doubly-infinitary distributive category on C. Our main result is that Dist(C) is cartesian closed. Finally, we compare doubly-infinitary distributivity with extensivity, ordinary infinitary distributivity, and cartesian closedness by means of separating examples.

math.CT↗

arXiv2026

Simply Typed Reverse-Mode Automatic Differentiation with Variants: Denotational Correctness via Idempotent Completion

Reverse-mode automatic differentiation is commonly given a denotational account in which each source type has a single cotangent type. Variant types obstruct this simply typed representation because the valid cotangent space depends on the branch selected at run time. Existing correctness results therefore use primal-indexed families of cotangent spaces, whose natural internal language is dependently typed. We show that the same dependency can be represented in an ordinary nondependent target. The cotangent fibres of each source type are embedded in a common ambient type, and a primal-indexed idempotent selects the valid fibre. Semantically, this amounts to passing from the constant-family model to its Karoubi completion. For a category $\mathcal C$ and a regular infinite cardinal $κ$, we prove that the constant-family inclusion extends to an equivalence $\mathrm{Kar}(\mathrm{Copow}*κ(\mathcal C)) \simeq \mathrm{Fam}*κ(\mathcal C)$ precisely when $\mathcal C$ is Cauchy complete and every $κ$-small family admits a common retract host. We also construct the resulting coproducts explicitly. Applying this theorem, we obtain a bicartesian closed semantics for reverse-mode automatic differentiation with variants using only ordinary target types, projectors, and backpropagators. Splitting the generated idempotents recovers the established dependent semantics. Thus dependent cotangent families and simply typed ambient cotangents equipped with projectors are equivalent presentations of the same denotational transformation.

cs.PL↗

arXiv2026

Backpropagation for Effectful Languages I: Finite Probability and Discrete Output Algebraic Effects

We analyse reverse-mode automatic differentiation (AD) for discrete probabilistic programs. Our construction is formulated in the framework of Combinatory Homomorphic Automatic Differentiation (CHAD), treating AD as a structure-preserving transformation of programs, guided by a denotational semantics. The main case study is the finite atomic distribution monad, whose computations have finite support and differentiable weights. The key point is that differentiating probabilistic programs requires cotangents to flow backwards not only through deterministic computations, but also through the probabilistic structure itself. We define the corresponding reverse-mode code transformation and prove its correctness, for handled real-output programs, by a categorical logical-relations argument. Although the paper focuses on finite discrete probability, the construction gives a reusable pattern for differentiating discrete-output algebraic effects, including finite multiset non-determinism (e.g., from fork-join parallelism), exceptions, and writer-style accumulation (e.g., for in-place accumulation of high-dimensional vectors). More broadly, we view this work as a foundational step towards extending CHAD to richer probabilistic languages and to other algebraic effects with handlers.

cs.PL↗

arXiv2026

Syntax and Semantics of Linear Dependent Types

A type theory is presented that combines (intuitionistic) linear types with type dependency, thus properly generalising both intuitionistic dependent type theory and full linear logic. A syntax and complete categorical semantics are developed, the latter in terms of (strict) indexed symmetric monoidal categories with comprehension. Various optional type formers are treated in a modular way. In particular, we will see that the historically much-debated multiplicative quantifiers and identity types arise naturally from categorical considerations. These new multiplicative connectives are further characterised by several identities relating them to the usual connectives from dependent type theory and linear logic. Finally, one important class of models, given by families with values in some symmetric monoidal category, is investigated in detail.

cs.LO↗

arXiv2026

A Categorical Semantics for Linear Logical Frameworks

A type theory is presented that combines (intuitionistic) linear types with type dependency, thus properly generalising both intuitionistic dependent type theory and full linear logic. A syntax and complete categorical semantics are developed, the latter in terms of (strict) indexed symmetric monoidal categories with comprehension. Various optional type formers are treated in a modular way. In particular, we see that the historically much-debated multiplicative quantifiers and identity types arise naturally from categorical considerations. These new multiplicative connectives are further characterised by several identities relating them to the usual connectives from dependent type theory and linear logic. Finally, one important class of models, given by families with values in some symmetric monoidal category, is investigated in detail.

cs.LO↗

arXiv2026

Higher Order Automatic Differentiation of Higher Order Functions

We present semantic correctness proofs of automatic differentiation (AD). We consider a forward-mode AD method on a higher-order language with algebraic data types and we characterise it as the unique structure-preserving macro given a choice of derivatives for basic operations. We describe a rich semantics for differentiable programming based on diffeological spaces. We show that it interprets our language and we phrase what it means for the AD method to be correct with respect to this semantics. We show that our characterisation of AD gives rise to an elegant semantic proof of its correctness based on a gluing construction on diffeological spaces. We explain how this is in essence a logical relations argument. Throughout we show how the analysis extends to AD methods for computing higher-order derivatives using a Taylor approximation.

cs.PL↗

arXiv2026

On S-Finite Measures and Kernels

In this note, we develop some of the basic theory of s-finite (measures and) kernels, a little-studied class that Staton has recently argued convincingly to be precisely the semantic counterpart of (first-order) probabilistic programs. We discuss their Carathéodory extension and extend Staton's analysis of their product measures. We give various characterisations of such kernels and discuss their relationship to the more commonly studied classes of $σ$-finite, subprobability and probability kernels. We use these characterisations to establish suitable Radon-Nikodým, Lebesgue decomposition and disintegration theorems for s-finite kernels. We discuss s-finite analogues of the classical randomisation lemma for probability kernels. Throughout, we give some examples to explain the connection with (first-order) probabilistic programming. Finally, we briefly explore how some of these results extend to quasi-Borel spaces, and hence how they apply to higher-order probabilistic programming.

math.PR↗

arXiv2026

CHAD: Combinatory Homomorphic Automatic Differentiation

We introduce Combinatory Homomorphic Automatic Differentiation (CHAD), a principled, pure, provably correct define-then-run method for performing forward- and reverse-mode automatic differentiation (AD) on programming languages with expressive features. It implements AD as a compositional, type-respecting source-code transformation that generates purely functional code. This code transformation is principled in the sense that it is the unique homomorphic (structure-preserving) extension to expressive languages of Elliott's well-known and unambiguous definitions of AD for a first-order functional language. Correctness of the method follows by a compositional logical-relations argument that shows that the semantics of the syntactic derivative is the usual calculus derivative of the semantics of the original program. In their most elegant formulation, the transformations generate code with linear types. However, the code transformations can be implemented in a standard functional language lacking linear types: while the correctness proof requires tracking linearity, the actual transformations do not. In fact, even in a standard functional language, we can get all the type safety that linear types give us: we can implement all linear types used to type the transformations as abstract types by using a basic module system. In this paper, we detail the method when applied to a simple higher-order language for manipulating statically sized arrays. However, we explain how the methodology applies, more generally, to functional languages with other expressive features. Finally, we discuss how the scope of CHAD extends beyond applications in AD to other dynamic program analyses that accumulate data in a commutative monoid.

cs.PL↗

arXiv2026

Principal Bundles and Gauge Theories

This set of lecture notes first gives an introduction to the geometry of principal bundles. Next, it demonstrates how they can be used to formalize the concept of gauge theories arising in physics. A basic familiarity with the differential geometry of manifolds and the classical field theories of general relativity and electromagnetism is assumed.

math-ph↗

arXiv2026

Topos-Theoretic Approaches to Quantum Theory

This review paper surveys work by Isham, Butterfield, Döring, Landsman, Spitters, Heunen, and others on topos-theoretic analyses of quantum theory. It aims to provide a synthesized account of their various approaches.

math-ph↗

arXiv2025

Monoidal closure of Grothendieck constructions via $Σ$-tractable monoidal structures and Dialectica formulas

We examine the categorical structure of the Grothendieck construction $Σ_{\mathsf{C}}\mathsf{L}$ of an indexed category $\mathsf{L} \colon \mathsf{C}^{op} \to \mathsf{CAT}$. Our analysis begins with characterisations of fibred limits, colimits, and monoidal (closed) structures. The study of fibred colimits leads naturally to a generalisation of the notion of extensive indexed category introduced in CHAD for Expressive Total Languages, and gives rise to the concept of left Kan extensivity, which provides a uniform framework for computing colimits in Grothendieck constructions. We then establish sufficient conditions for the (non-fibred) monoidal closure of the total category $Σ_{\mathsf{C}}\mathsf{L}$. This extends Gödel's Dialectica interpretation and rests upon a new notion of $Σ$-tractable monoidal structure. Under this notion, $Σ$-tractable coproducts unify and extend cocartesian coclosed structures, biproducts, and extensive coproducts. Finally, we consider when the induced closed structure is fibred, showing that this need not hold in general, even in the presence of a fibred monoidal structure.

math.CT↗

arXiv2025

Parallel Dual-Numbers Reverse AD

Where dual-numbers forward-mode automatic differentiation (AD) pairs each scalar value with its tangent value, dual-numbers reverse-mode AD attempts to achieve reverse AD using a similarly simple idea: by pairing each scalar value with a backpropagator function. Its correctness and efficiency on higher-order input languages have been analysed by Brunel, Mazza and Pagani, but this analysis used a custom operational semantics for which it is unclear whether it can be implemented efficiently. We take inspiration from their use of linear factoring to optimise dual-numbers reverse-mode AD to an algorithm that has the correct complexity and enjoys an efficient implementation in a standard functional language with support for mutable arrays, such as Haskell. Aside from the linear factoring ingredient, our optimisation steps consist of well-known ideas from the functional programming community. We demonstrate the use of our technique by providing a practical implementation that differentiates most of Haskell98. Where previous work on dual numbers reverse AD has required sequentialisation to construct the reverse pass, we demonstrate that we can apply our technique to task-parallel source programs and generate a task-parallel derivative computation.

cs.PL↗

arXiv2025

Slamming the sham: A Bayesian model for adaptive adjustment with noisy control data

It is not always clear how to adjust for control data in causal inference, balancing the goals of reducing bias and variance. We show how, in a setting with repeated experiments, Bayesian hierarchical modeling yields an adaptive procedure that uses the data to determine how much adjustment to perform. The result is a novel analysis with increased statistical efficiency compared to the default analysis based on difference estimates. We demonstrate this procedure on two real examples, as well as on a series of simulated datasets. We show that the increased efficiency can have real-world consequences in terms of the conclusions that can be drawn from the experiments. We also discuss the relevance of this work to causal inference and statistical design and analysis more generally.

stat.ME↗

arXiv2024

Automatic Differentiation for ML-family languages: correctness via logical relations

We give a simple, direct and reusable logical relations technique for languages with term and type recursion and partially defined differentiable functions. We demonstrate it by working out the case of Automatic Differentiation (AD) correctness: namely, we present a correctness proof of a dual numbers style AD code transformation for realistic functional languages in the ML-family. We also show how this code transformation provides us with correct forward- and reverse-mode AD. The starting point is to interpret a functional programming language as a suitable freely generated categorical structure. In this setting, by the universal property of the syntactic categorical structure, the dual numbers AD code transformation and the basic $ω$-cpo semantics arise as structure preserving functors. The proof follows, then, by a novel logical relations argument. The key to much of our contribution is a powerful monadic logical relations technique for term recursion and recursive types. It provides us with a semantic correctness proof based on a simple approach for denotational semantics, making use only of the very basic concrete model of $ω$-cpos.

cs.PL↗

arXiv2024

Free extensivity via distributivity

We consider the canonical pseudodistributive law between various free limit completion pseudomonads and the free coproduct completion pseudomonad. When the class of limits includes pullbacks, we show that this consideration leads to notions of extensive categories. More precisely, we show that extensive categories with pullbacks and infinitary lextensive categories are the pseudoalgebras for the pseudomonads resulting from the pseudodistributive laws. Moreover, we introduce the notion of doubly-infinitary lextensive category, and we establish that the freely generated such categories are cartesian closed. From this result, we further deduce that, in freely generated infinitary lextensive categories, the objects with a finite number of connected components are exponentiable. We conclude our work with remarks on descent theoretical aspects of this work, along with results concerning non-canonical isomorphisms, and relationship with other work.

math.CT↗

arXiv2024

Denotational Correctness of Forward-Mode Automatic Differentiation for Iteration and Recursion

We present semantic correctness proofs of forward-mode Automatic Differentiation (AD) for languages with sources of partiality such as partial operations, lazy conditionals on real parameters, iteration, and term and type recursion. We first define an AD macro on a standard call-by-value language with some primitive operations for smooth partial functions and constructs for real conditionals and iteration, as a unique structure preserving macro determined by its action on the primitive operations. We define a semantics for the language in terms of diffeological spaces, where the key idea is to make use of a suitable partiality monad. A semantic logical relations argument, constructed through a subsconing construction over diffeological spaces, yields a correctness proof of the defined AD macro. A key insight is that, to reason about differentiation at sum types, we work with relations which form sheaves. Next, we extend our language with term and type recursion. To model this in our semantics, we introduce a new notion of space, suitable for modeling both recursion and differentiation, by equipping a diffeological space with a compatible $ω$cpo-structure. We demonstrate that our whole development extends to this setting. By making use of a semantic, rather than syntactic, logical relations argument, we circumvent the usual technicalities of logical relations techniques for type recursion.

cs.PL↗

arXiv2023

Efficient CHAD

We show how the basic Combinatory Homomorphic Automatic Differentiation (CHAD) algorithm can be optimised, using well-known methods, to yield a simple, composable, and generally applicable reverse-mode automatic differentiation (AD) technique that has the correct computational complexity that we would expect of reverse-mode AD. Specifically, we show that the standard optimisations of sparse vectors and state-passing style code (as well as defunctionalisation/closure conversion, for higher-order languages) give us a purely functional algorithm that is most of the way to the correct complexity, with (functional) mutable updates taking care of the final log-factors. We provide an Agda formalisation of our complexity proof. Finally, we discuss how the techniques apply to differentiating parallel functional array programs: the key observations are 1) that all required mutability is (commutative, associative) accumulation, which lets us preserve task-parallelism and 2) that we can write down data-parallel derivatives for most data-parallel array primitives.

cs.PL↗