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At least 37 records · Page 2Linked to original sources

From the Dirichlet Integral to Lobachevsky's Formula: A Formalization in Lean 4

We formalize the Dirichlet integral and several of its classical applications in the Lean~4 proof assistant. Since the sinc function is not Lebesgue integrable on the positive half-line, the Dirichlet integral must be represented as the limit of integrals over bounded intervals. To avoid the difficulty of removing an exponential factor from a conditionally convergent integral, we instead pass through the absolutely integrable function \(\operatorname{sinc}^2\). We evaluate its integral by differentiation under the integral sign and dominated convergence, and then recover the Dirichlet integral from an identity between truncated integrals. Using these results, we formalize the convergence of the Dirichlet cutoff to the Heaviside function and derive several quadratic and bilinear trigonometric integral identities. Finally, we formalize Lobachevsky's integral formula for continuous periodic functions satisfying a reflection symmetry, using the density of cosine polynomials obtained from Mathlib's Fourier analysis on the additive circle.

cs.LO↗

Granthi: Higher-Order Quantum Programming via Unitary Wiring

Many mainstream quantum programming languages confine higher-order structure to a classical host while restricting the quantum layer to first-order operations on qubits. This paper presents Granthi, a purely unitary higher-order quantum programming language built on three design commitments: quantum programs are first-class values that may be passed, returned, and coherently composed; additive structure is tag-preserving routing rather than observational branching, so control may remain in superposition; and programmer-facing finite label types with staged reversible-operation bindings provide domain-level control spaces without exposing tag management. These bindings are eliminated by elaboration before Source typing. Granthi deterministically normalizes each Source program to a canonical wiring form. Every well-typed Source program, including a term of function type, has a unitary boundary interpretation. Under backend correctness (BC), the reference compiler produces a unitary circuit realizing that interpretation. Granthi's currently supported executable fragment is implemented end-to-end: an OCaml DSL elaborates surface programs through a higher-order Core IR to executable quantum circuits via pytket. The language directly supports the pure-unitary quantum switch for explicitly supplied operations; closed instances compile to static circuits. It also supports interference on control-flow history and structured finite control, all within the purely unitary fragment

quant-ph↗

Width-Bounded Equational Derivations for Finite Graph Expressions

Completeness of an equational presentation guarantees an equality path but need not control the resources used along it. For finite graph expressions we measure derivational space by the largest input-output interface of an intermediate raw term. For every finite doubly ranked edge alphabet $Σ$, we prove that equal closed expressions of pattern width at most $k$ are joined by a derivation in which every step applies an equation in either direction and every intermediate width is at most a computable $B_Σ(k)$, independently of graph size. The derivation uses only the structural magmoid laws and the fifteen finite-graphoid schemes. The construction compiles each expression through protected cores and finite routing windows to an encoding-canonical representative $\operatorname{NF}_k$ of width at most $4k+4$. We call this property bounded equational coherence. We also prove $\operatorname{bw}(F)\le\operatorname{patw}(F)\le4(\operatorname{tw}(F)+1)$ whenever the underlying simple graph has at least two edges, separate layered linear from branching expressions on cliques, and provide machine-checkable witnesses and finite invariants for the first five nontrivial clique values.

cs.LO↗

Erased Postulates, Identity Types and Quotients

This text is concerned with the question of whether, in type theory with erasure annotations, one can postulate that some type is inhabited and still have a guarantee that a program will not get stuck. Previous work has provided such guarantees for consistent erased postulates, i.e. postulates that are restricted to be used in erased contexts. Here those guarantees are extended to type theory with identity types. Similar ideas provide a simple way to support quotient types: it is shown that one can let things like "the equivalence classes for two related values are equal" be erased postulates and have an eliminator that only computes for the equivalence class constructor, and still get a guarantee that programs will compute correctly. Another question is whether programs compute correctly if one is allowed to transport (cast) using erased identity proofs. It is shown that this is safe in the absence of quotients and postulates, and in the presence of quotients and erased postulates that can be implemented using equality reflection. However, unrestricted transports of this kind are not compatible with erased, postulated univalence. For that reason the text includes a study of the function []-cong, which encapsulates a limited form of transport for erased identity proofs. The text is accompanied by machine-checked Agda proofs.

cs.PL↗

Length Generalization for Transformers via Compression

Recent advancements in transformer length generalization theory enable us to reliably predict when a transformer can learn to solve a task. In particular, the C-RASP hypothesis (a formalized version of the so-called RASP-l conjecture) posits that transformers length-generalize on a task if and only if a solution is expressible in the C-RASP language. While this hypothesis has strong empirical validation, theoretical problems arise from the fact that no computable length generalization bounds exist for C-RASP, alongside the discovery of seemingly contradictory experiments. To address these problems, we refine the C-RASP hypothesis utilizing the recently-proposed fragments C-RASP+ and C-RASP1. These fragments have computable length generalization bounds, though in the worst case requiring an extremely large (double exponential) sample size. It is an open question whether these sample size bounds are tight. In this paper, we resolve this open question by providing an exponentially tighter bound. In doing so, we show a polynomial length generalization bound for transformers if we adopt compressed strings, via a novel connection to power words. As an application, we show how this yields a fine-grained analysis of the C-RASP conjecture that resolves contradicting experimental evidence against it.

cs.LG↗

Fitting and Learning Basis-Restricted Propositional Formulas

For a finite set $O$ of Boolean functions, we consider the class of propositional formulas built using the functions in $O$ as connectives. We determine, for each possible choice of $O$, the complexity of various fitting and learning problems. These include: finding a formula that fits a given labeled sample, finding a small one (an Occam algorithm), minimizing the number of misclassified examples when the sample is not realizable (empirical risk minimization), and several forms of PAC learning. Our results apply both to formulas (represented as trees) and to circuits. We also briefly discuss the status of the same questions for other kinds of propositional fragments.

cs.LO↗

StochBench: A Domain-Specific Benchmark for Stochastic Processes in Lean

Leading benchmarks for formal theorem proving with large language models are small collections drawn from competition math, such as the IMO and Putnam, that poorly represent field-specific applications. We introduce StochBench, a Lean 4 benchmark of 450 graduate stochastic-processes problems at varying abstraction levels, each paired with its natural-language source. Addressing a field underrepresented in Mathlib, it covers finite and countable Markov chains, renewal processes, random walks, martingales, stopping times, queues, Brownian motion, stochastic calculus, weak convergence, and Poisson and continuous-time Markov processes. Our Opus 4.8-based agent achieves a 34.9% proof rate (157/450) under a 15-minute per-problem limit. StochBench better represents domain-specific applied mathematics while remaining challenging for advanced provers.

cs.CL↗

Fast Constraint Extraction for Corrective Control under STL Specifications via Logical Dependency Tracking

Ensuring the satisfaction of Signal Temporal Logic (STL) specifications under uncertainty is challenging, as reachability-based monitoring provides guarantees but does not indicate how to restore satisfaction when it becomes indeterminate. A key difficulty is identifying which uncertain components actually affect global satisfaction, especially for nested formulas. This paper introduces a logical dependency tracking framework that propagates uncertainty through the STL structure and captures the causal contribution of reachable sets to satisfaction. By associating markers to uncertain predicates and propagating them via three-valued semantics, we extract in milliseconds a compact Disjunctive Normal Form (DNF) of sufficient constraints, avoiding combinatorial enumeration. As an application, we formulate control correction as a minimum-effort optimization problem. Using zonotopic reachability, the derived constraints are enforced via linear programming, yielding corrections that guarantee STL satisfaction under bounded uncertainty and provide certified probabilistic bounds in the stochastic case. We demonstrate the approach on a nonlinear system with nested STL specifications, showing that dependency tracking enables efficient and formally guaranteed correction. The tracking implementation is available at https://github.com/Antoine-Bst/STL-Three-Valued-Clause-Filtering/.

cs.LO↗

Homomorphism Indistinguishability, Multiplicity Automata Equivalence, and Polynomial Identity Testing

Two graphs $G$ and $H$ are homomorphism indistinguishable over a graph class $\mathcal{F}$ if they admit the same number of homomorphisms from every graph $F \in \mathcal{F}$. Many graph isomorphism relaxations such as (quantum) isomorphism and cospectrality can be characterised as homomorphism indistinguishability over specific graph classes. Thereby, the problems $\textrm{HomInd}(\mathcal{F})$ of deciding homomorphism indistinguishability over $\mathcal{F}$ subsume diverse graph isomorphism relaxations whose complexities range from logspace to undecidable. Establishing the first general result on the complexity of $\textrm{HomInd}(\mathcal{F})$, Seppelt (MFCS 2024) showed that $\textrm{HomInd}(\mathcal{F})$ is in randomised polynomial time for every graph class $\mathcal{F}$ of bounded treewidth that can be defined in counting monadic second-order logic $\mathsf{CMSO}_2$. We show that this algorithm is conditionally optimal, i.e. it cannot be derandomised unless polynomial identity testing is in $\mathsf{PTIME}$. For $\mathsf{CMSO}_2$-definable graph classes $\mathcal{F}$ of bounded pathwidth, we improve the previous complexity upper bound for $\textrm{HomInd}(\mathcal{F})$ from $\mathsf{PTIME}$ to $\mathsf{C}_=\mathsf{L}$ and show that this is tight. Secondarily, we establish a connection between homomorphism indistinguishability and multiplicity automata equivalence which allows us to pinpoint the complexity of the latter problem as $\mathsf{C}_=\mathsf{L}$-complete.

cs.CC↗

Streaming LRAT Certificates into Lean Theorems

If the certificate produced by a SAT solver is checked by a verified checker, we get a verdict which convinces. But this verdict cannot be named, reused as a lemma, or composed with other formal developments. We propose the tool lrat-catcher, which turns a certificate into a Lean theorem. It checks the certificate as a stream while the solver is still running. Hence the certificate is not required to be saved to a file. Additionally, our tool makes Lean core's verified LRAT checker resumable so that its state can be serialized. We prove that checking divided at such a state still properly refutes the original formula. We propose two import modes. The stream mode reads the certificate from a pipe in blocks and checks it on the fly in memory. The file mode imports a stored certificate in chunks. If interrupted, it rechecks only the chunks it has not yet completed. The soundness theorem for the stream mode guarantees that a garbled or adversarial stream can only fail the check but not yield a false theorem. We find that with compaction at chunk boundaries, the memory required depends only on the live clause set, not on the certificate size. Our tool supports cube-and-conquer and formulas derived by preprocessing, to still form Lean proofs of the original formula. We provide several end-to-end case studies on well-known combinatorial problems. A larger scaling experiment on the empty-hexagon problem shows that 174 TB of certificates can be imported into Lean via streaming.

cs.LO↗

Optimising Metamath Proofs for Human Working Memory

Mathematical proofs vary in legibility. While most proof optimisation techniques seek to minimise proof size, the strategic reordering of inferences can reduce the working memory demand of proof checking without altering overall size. Metamath serves as a prime case study for this approach: its verification architecture requires proof steps to be ordered in a manner that prioritises algorithmic efficiency over readability. In this paper, we introduce algorithms to minimise both peak and cumulative memory consumption, applying the latter as a novel proxy for sustained human cognitive effort. We achieve this by representing proofs as directed acyclic graphs and modelling their execution as a pebbling game. Finding an optimal ordering via brute force is computationally infeasible, so we use heuristics to provide approximations. We apply these algorithms across Metamath's ZFC set theory library and present case studies demonstrating how automated reordering systematically improves the presentation of formal mathematics.

cs.LO↗

Automatic constraints with few subpowers and graphoid recognition

Finite automata can describe relations of unbounded arity that are exponentially larger than their descriptions. We prove that constraint satisfaction for such relations is solvable in polynomial time whenever their length slices are preserved by a common fixed edge operation on a finite domain. The algorithm computes compact representations of the complete solution relation and its projections. Its main ingredient is a polynomial-time compilation of nondeterministic finite automata into the fork witnesses and small projections required by the few-subpowers algorithm. In the Mal'tsev case, a direct proof is polynomial also when the domain and operation table are supplied as input, answering the Mal'tsev tractability question for automatic constraint satisfaction. We also characterize all invariant relations of a family of 3-edge algebras with neither Mal'tsev nor near-unanimity terms. Their normal forms combine Boolean activity constraints with affine value spaces and yield canonical quadratic-bit representations constructible from NFAs or arbitrary generators. For graphoid automata, these results give polynomial-time recognition without a graph-width restriction, effective boundary composition, and comparison of finite graph relations. The quadratic boundary bounds are optimal in the worst case. A fixed three-state example separates polynomial-time recognition from hard exact counting.

cs.LO↗

A Lean 4 Formalization of Scott's Continuous Lattices (1972)

We present a complete machine-checked formalization of Dana Scott's landmark 1972 paper \emph{Continuous Lattices} \textbf{[Sco72]}, carried out in Lean 4 against mathlib and including the March 1972 Milner correction in \textbf{[Sco72]} (pp.~135--136). Scott's paper develops a model for \(λ\)-calculus from a topological starting point. He defines \emph{injective} \(T_0\)-spaces -- those with a strong extension property for continuous maps -- and shows that they are exactly the \emph{continuous lattices}: complete lattices whose Scott topology is determined by the order via the way-below relation (\(\ll\)). On this foundation he studies projections, retractions, products, function spaces, and inverse limits. The capstone (Theorem 4.4) constructs an inverse limit \(D_\infty\) of function-space approximants and proves \(D_\infty \cong [D_\infty \to D_\infty]\), yielding a purely mathematical model for Church's untyped \(λ\)-calculus. Our development formalizes \textbf{43 numbered results} from Scott's Sections 1--4 (Propositions, Corollaries, Lemmas, and Theorems), each as a sorry-free Lean theorem, together with supporting infrastructure (step functions, the \(\Uparrow a\) basis of Scott opens, Milner's coarser-than-Scott hypothesis, the function-space tower, and the \(i_\infty\)/\(j_\infty\) pair). The formalization is \textbf{classical} (uses \texttt{Classical.choice} transitively) and follows Scott's proof dependency order. Where the Lean proof required choices not visible in the original -- or where dead ends were encountered -- we record detailed notes in Section 5. All proofs check with the standard footprint \(\texttt{[propext, Classical.choice, Quot.sound]}\). The formalization has been accepted into the Palomar registry.

cs.LO↗

You may implement this later: Cofunctors as partial implementations

A functor is a familiar model of an implementation, where every operation in a specification is assigned a concrete instantiation at the outset. But some tasks are less eager: we often want to assemble systems while leaving backend choices such as data representations and algorithms for later. We observe that cofunctors admit a direct reading as such partial implementations, which are implementations whose extra argument is a state-dependent family of deferred choices. While cofunctors (also called retrofunctors) are not novel, their conceptual and purposive reading in this manner appears to be.

cs.PL↗

Mechanizing Typed Regulatory Actions for Security Tokens: Semantics, Falsification, and Bounded EVM Evidence

Security-token standards expose privileged controls without identifying the legal effect executed or the evidence and reversal obligations it carries. We formalize in Isabelle/HOL a reference execution semantics for the six ERC-8319 meanings: FREEZE, SEIZE, CONFISCATE, LIQUIDATE, RESTRICT, and RECOVER. It distinguishes applied, rejected, and operational-failure outcomes and mechanizes action-specific reversals, replay and epoch rules, complete frames, case-local terminality, and final receipts; the session builds without unproved placeholders or additional axioms. An indistinguishability theorem shows that bound kernel inputs cannot establish external facts about title, settlement, or entitlement. Constructive witnesses and direct mutations establish reachability and sensitivity for the declared fault set. For a successor ERC-TRUST Solidity/EVM candidate, we report separately scoped Foundry, Certora, Kontrol/KEVM, mutation, deterministic-build, runtime-identity, and independent-reproduction evidence. All twelve named evidence lanes pass with none pending, while the 74-row obligation ledger remains conditional: 70 rows are closed, two runtime-link rows remain successor obligations, and two are inapplicable. The Native runtime is bound separately from an ERC-3643 interoperability reference that explicitly reports Partial and full=false, not Verified Full. These results do not establish complete Isabelle-to-Solidity-to-EVM refinement, compiler correctness, audit completion, production readiness, deployment verification, or external legal truth. They provide a machine-checked domain semantics and an explicit map of proved, bounded, assumed, and open results.

cs.CR↗

Staged Hybrid Quantum-Classical Programming

Hybrid quantum-classical computing systems consist of a classical control system that sends quantum circuits and receives measurement results from a quantum co-processor. Such systems allow us to model algorithms that require the classical control system to generate quantum circuits on the fly, potentially based on prior measurement results. This is challenging, as the classical control system must generate quantum circuits that manipulate live quantum states. In this setting, the classical control system is generating further quantum circuits while the quantum co-processor is internally maintaining the state of the live qubits; this is not ideal, since this not only is costly but also introduces additional sources of noise to the live qubits. Thus, we want to minimize the latency between receiving measurement results and sending the next quantum circuit to be executed by pre-computing quantum circuits. We introduce HyQ (pronounced haiku), a multi-modal language based on adjoint logic that pre-generates quantum circuits before executing a hybrid quantum-classical program. We achieve this by separating our semantics into two distinct stages: 1) compile-time generation of quantum circuits and classical runtime code and 2) execution of the classical runtime code that instruments the quantum co-processor. This separation between stages allows us to formally guarantee that all circuit-generation logic occurs before the instrumentation logic, i.e., the actual runtime, and minimizes the idling of the quantum co-processor at runtime. We give a type system, a circuit-normalization semantics for the compile-time stage, which eagerly performs all circuit-generation logic, and a runtime semantics for HyQ that corresponds to the second stage. We prove type preservation and progress for both semantics.

cs.PL↗

Efficient Hardware Information-Flow Tracking for Pre-Silicon Security Testing

Register-Transfer Level (RTL) simulation is widely used to test hardware before it is fabricated. To allow testing for security related information flow properties, such as confidentiality and integrity, taint logic can be automatically added to the design to track how information flows through it. However, taint logic instrumented by the state-of-the-art, such as CellIFT, makes simulation-based testing prohibitively expensive: On our evaluation of Mega-BOOM (136K cells), it increases the instrumented design to 5.81x the original cell count and causes a 143.72x simulation slowdown. The taint logic could be simplified to improve simulation speed, but it will inevitably trade off its precision. This lightweight, imprecise taint logic will introduce false positives and may eventually result in even more overhead to check these false positives. This paper explores the research question of where precision is actually needed in the design to overcome the overhead of false positives. It presents CEGAR-T, a framework that automatically synthesizes taint logic that minimizes the taint-logic instrumentation overhead while guaranteeing no false positives (relative to the precise CellIFT baseline). We have implemented CEGAR-T and evaluated it on the safe instruction set problem for timing side-channel security across open-source RISC-V cores. Over all evaluated cores, CEGAR-T reduces both instrumentation and simulation overhead, in geometric-mean, from 5.64x to 1.42x and from 34.65x to 1.79x, respectively, without compromising the precision benefit of the CellIFT baseline.

cs.CR↗

From Contexts to Values: Context-Dependent Defeat in Abstract Argumentation

In value-based argumentation, an audience's ordering of values decides which attacks succeed as defeats. In many settings the deciding factor is not the audience but the circumstances: the same attack may succeed at one procedural stage, or under one regulation, and fail at another. Context-dependent argumentation frameworks (CDAFs), a model we recently introduced, capture this directly: one attack relation and a defeat function that switches each attack on or off per context, so every context induces an ordinary Dung framework. This raises a reduction question: can one value assignment with per-context orderings reproduce the defeat function, collapsing the CDAF into a VAF? We present a polynomial-time decision procedure for this question and map the harder neighbouring problems, with upper bounds from NP to $Σ^p_3$. We also present a validated reference implementation and a measurement: representability is rare and falls fast with the number of contexts.

cs.AI↗