Abstract 1 Introduction 2 Arithmetical theories of generalised inductive definitions 3 Cyclic proofs for generalised inductive definitions 4 A reset proof system for 𝝁𝗣𝗔 5 From progressing proofs to reset proofs 6 Formalising the soundness argument in 𝚷𝟐𝟏-𝗖𝗔𝟎 7 Conclusions and future works References

Cyclic Proof Theory of Generalised Inductive Definitions

Gianluca Curzi ORCID Gothenburg University, Sweden Lukas Melgaard ORCID University of Birmingham, UK
Abstract

We study cyclic proof systems for μ𝖯𝖠, an extension of Peano arithmetic by generalised inductive definitions that is arithmetically equivalent to the (impredicative) subsystem of second-order arithmetic Π21-𝖢𝖠0 by Möllerfeld.

The main result of this paper is that cyclic and inductive μ𝖯𝖠 have the same proof-theoretic strength. First, we translate cyclic proofs into an annotated variant based on Sprenger and Dam’s systems for first-order μ-calculus, whose stronger validity condition allows for a simpler proof of soundness. We then formalise this argument within Π21-𝖢𝖠0, leveraging Möllerfeld’s conservativity properties. To this end, we build on prior work by Curzi and Das on the reverse mathematics of the Knaster-Tarski theorem.

As a byproduct of our proof methods we show that, despite the stronger validity condition, annotated and “plain” cyclic proofs for μ𝖯𝖠 prove the same theorems.

This work represents a further step in the non-wellfounded proof-theoretic analysis of theories of arithmetic via impredicative fragments of second-order arithmetic, an approach initiated by Simpson’s Cyclic Arithmetic, and continued by Das and Melgaard in the context of arithmetical inductive definitions.

Keywords and phrases:
cyclic proofs, positive inductive definitions, arithmetic, fixed points, proof theory, reset proof systems
Copyright and License:
[Uncaptioned image] © Gianluca Curzi and Lukas Melgaard; licensed under Creative Commons License CC-BY 4.0
2012 ACM Subject Classification:
Theory of computation Proof theory
; Theory of computation Higher order logic
Related Version:
Full Version: https://arxiv.org/abs/2507.13057 [13]
Acknowledgements:
We would like to thank Anupam Das for his continuous support, and Graham Leigh for his valuable suggestions during the development of this paper.
Funding:
This work was supported by a UKRI Future Leaders Fellowship, “Structure vs Invariants in Proofs” (project reference MR/S035540/1), by the Wallenberg Academy Fellowship Prolongation project “Taming Jörmungandr: The Logical Foundations of Circularity” (project reference 251080003), and by the VR starting grant “Proofs with Cycles in Computation” (project reference 251088801).
Editors:
Stefano Guerrini and Barbara König

1 Introduction

Non-wellfounded proof theory explores generalized notions of proof that allow for infinite branches, where logical soundness is guaranteed by global specifications such as so-called progressivity conditions. A central concept in this area is that of cyclic (or circular) proofs – non-wellfounded proofs that exhibit a regular tree structure often represented as finite graphs. Compared to more traditional notions of proofs, cyclic proofs are particularly well-suited for formalizing (co)inductive reasoning. In particular, they provide a more “analytic” approach to (co)inductive invariants, which is crucial for the mechanisation of proof search [9, 26, 34, 33]. The modern development of cyclic proofs can be traced back to the work of Niwiński and Walukiewicz [24], who anticipated them in the context of tableau methods for the modal μ-calculus. The topic was subsequently advanced by Simpson and Brotherston, who initiated the systematic investigation of cyclic proof theory [8, 11].

Progressivity conditions are the most common validity criterions studied in the literature and they represent a quite robust and logic-independent requirement. However, because of their non-local (and non-modular) nature, checking progressivity is in general PSPACE-complete (see, e.g., [5]). More “efficient” alternatives to validity have been explored in [2, 3, 4, 22] with so-called (cyclic) reset proofs, in which sequents can be annotated to keep track of “progress” in a local way. In particular, Sprenger and Dam introduced in [30, 31] a reset system for first-order μ-calculus where cyclic proofs are decorated with variables ranging over ordinals and equipped with order-theoretic constraints on those ordinals. Their work was later refined by Leigh et al. in [1]. The analysis of the trade-off between progressing and reset conditions has been recently thoroughly conducted in a general, abstract setting by Afshari and Wehr through the connection between Safra automata and reset proofs [20].

One of the primary goals of cyclic proof theory is to study the expressivity of cyclic proofs – for instance, with respect to provability, logical complexity, or proof-theoretic strength – and to compare them with standard, inductive(ly defined) proofs. Because of the non-wellfounded nature of cyclic proofs, this analysis often requires indirect arguments, typically involving formalisation of mathematical principles in first-order or second-order arithmetical theories. In the context of first-order logic with inductive definitions, for example, Berardi and Tatsuta showed that inductive and cyclic proof systems do not prove the same set of theorems [6], and that the equivalence between the two systems can be obtained when these are extended with Peano Arithmetic (𝖯𝖠) [7]. The latter statement was proven by extracting an induction principle from the progressivity condition using (an extension of) Podelski-Rybalchenko termination theorem, and requires formalising infinite Ramsey Theorem within 𝖯𝖠.

Berardi and Tatsuta’s result was implicitly proven by Simpson, who independently showed that the cyclic variant of Peano Arithmetic (𝖢𝖠) is equivalent to 𝖯𝖠 [28]. To establish this, he formalised the meta-theory of cyclic proofs in subsystems of second-order arithmetic using some results from reverse mathematics [29].

Simpson’s work was later refined by Das in two directions. First, he showed in [14] that the logical complexity of inductive invariants in 𝖢𝖠 is strictly simpler than 𝖯𝖠. Then, in joint work with Melgaard [16], he studied the extension of 𝖯𝖠 with arithmetic (finitely iterated) inductive definitions (𝖨𝖣<ω) and showed that this system and its cyclic version 𝖢𝖨𝖣<ω prove the same arithmetic statements, and so have the same proof-theoretic strength.

This paper continues the line of research initiated by Simpson, by exploring the cyclic proof theory of generalised inductive definitions. Its main focus is μ𝖯𝖠, an extension of 𝖯𝖠 by least and greatest fixed points of formulas (see [12]). Proof-theoretically, μ𝖯𝖠 was first studied by Möllerfeld [23], inspired by Lubarsky’s work on “μ-definable sets” [21]. The theory was later used by Curzi and Das to characterise the computational expressivity of constructive fixed point logics [12]. Because of the presence of interleaving (or parametric) fixed points, the expressivity of μ𝖯𝖠 far exceeds that of 𝖨𝖣<ω. Indeed, Möllerfeld proved that μ𝖯𝖠 has the same proof-theoretic strength as Π21-𝖢𝖠0, an (impredicative) subsystem of second-order arithmetic where the comprehension scheme is restricted to Π21-formulas, one of the strongest theories for which we have an ordinal analysis [25].

The main result of this paper can be stated as follows:

Theorem 1.

Cyclic μ𝖯𝖠 (𝖢μ𝖯𝖠) is arithmetically equivalent to μ𝖯𝖠.

Our argument is summarized in Figure 1. We first introduce a reset system for μ𝖯𝖠 inspired by [1], called 𝖢μ𝖯𝖠ann. Compared to 𝖢μ𝖯𝖠, 𝖢μ𝖯𝖠ann is defined by a stronger validity condition that allows for a more local and direct soundness proof. Despite being apparently more permissive, cyclic progressing proofs can be duly turned into cyclic reset proofs (Theorem 25). We then adopt Simpson’s method and we formalise the soundness argument for reset proofs within Π21-𝖢𝖠0, using some results from reverse mathematics from [12] as well as reflection principles (Theorems 37 and 34). We then conclude by appealing to Möllerfeld’s arithmetic conservativity of Π21-𝖢𝖠0 over μ𝖯𝖠 [23]. As a consequence of our proof methods, we also establish the equivalence between progressing-based cyclic proofs and cyclic reset proofs, thus bridging the gap between two major routes to cyclic proof theory in the context of first-order μ-calculi.

Outline of the paper.

This paper is structured as follows. In Section 2 we recall the syntax and the semantics of μ𝖯𝖠, as well as its sequent calculus system. In Section 3 we define the cyclic proof system 𝖢μ𝖯𝖠 and show that the latter can simulate μ𝖯𝖠 (Theorem 15). Section 4 introduces the reset system 𝖢μ𝖯𝖠ann and its soundness theorem (Theorem 21), while Section 5 shows that cyclic progressing proofs of 𝖢μ𝖯𝖠 can be translated into cyclic reset proofs (Theorem 25). Finally, Section 6 formalises the soundness argument for 𝖢μ𝖯𝖠ann of Section 4 within Π21-𝖢𝖠0 (Theorem 37). Full proofs of our results, as well as further discussion and examples, can be found in the extended version of this paper [13].

Figure 1: Diagram illustrating the main results.

Preliminary definitions.

We assume that the reader is familiar with the syntax of sequent calculus (e.g. [27]) as well as basic graph theory. The following two definitions summarise the main notions and notational conventions adopted in this paper.

Definition 2 (Trees).

A (possibly infinite, binary) tree is a non-empty set T{0,1}<ω that is prefix-closed, i.e., b1bnT implies b1biT for all 0in. Elements of the tree are called nodes, which are denoted by u,v,. A successor of a node uT is a node ubT for some b{0,1}. ε is the root of T and a node with no successor is a leaf. A branch of T is a family (vi)iα (αω) such that v0=ε and vi+1=vib for some b{0,1}.

Definition 3 (Rules and (co)derivations).

We consider (inference) rules of the form with n{0,1,2}, where Γ1,,Γn are called premises and Γ is called conclusion. A coderivation over a set of rules X is a pair 𝒟=(T,) where T is a tree called the support of 𝒟 and :TX is a label function such that, whenever (v) is a rule with n premises Γ1,,Γn, then v has precisely successors v1,,vn and (vi) is a rule with conclusion Γi for all 1in. A coderivation with finite support is called a derivation. The conclusion of a (co)derivation is the conclusion of the rule (ε). Given some uT𝒟, we write 𝒟u for the (co)derivation with support T𝒟u={v:uvT𝒟} given by (v):=(uv). We call such 𝒟u a sub-(co)derivation of 𝒟. If 𝒟 has only finitely many sub-coderivations, we call it cyclic (or regular). Cyclic coderivations can be represented as finite graphs.

2 Arithmetical theories of generalised inductive definitions

In what follows, we introduce the theory μ𝖯𝖠 and its semantics111This theory is often called μ-calculus in the literature (see, e.g., [17, 23]). To date, however, μ-calculi represent a rather diverse family of systems. In this paper we adopt the formulation of the theory from [12], which is referred to as μ𝖯𝖠 to stress its arithmetic component.. The theory can be constructed as a formal extension of second-order arithmetic by defining least fixed points μXxφ as relation symbols, as done in [23]. Instead, we choose to treat them syntactically as “binders” and formulate the theory in a first-order fashion following [12].

2.1 Language of arithmetic with fixed points

The language of μ𝖯𝖠, written μ, is an extension of the language of first-order arithmetic (with inequality) 1:={0,𝗌,+,×,<} where, as usual, 0 is a constant symbol (i.e. a 0-ary function symbol), 𝗌 is a unary function symbol, + and × are binary function symbols, and < is a binary relation symbol. Specifically, the language of μ𝖯𝖠 is obtained from 1 by adding countably many set variables 222W.l.o.g., in this paper we restrict the language to second-order variables ranging over sets of individuals., written X,Y etc, and fixed point binders μ and ν.

Definition 4 (Terms and (pre-)formulas).

The (number) terms, the pre-set terms and the pre-formulas of μ𝖯𝖠 are respectively simultaneously generated by the following grammars:

t,s:=x| 0|𝗌t|s+t|s×tφ,ψ:=s<t|st|s=t|st|tS|tS|φψ|φψ|xφ|xφS:=X|μXxφ|νXxφ

The notions of free first-order variable and free second-order variable are standard. Notice that ν and μ bind the free (individual and set) variables X and x in φ. We denote with FV0(φ), FV0(t), and FV1(φ) the set of free first-order variable in φ and t and the set of free second-order variable in φ, respectively. We will use the standard notation for (capture-avoiding) first-order and second-order substitution φ[S/X], φ[s/x], and t[s/x].

Pre-formulas of the form s<t, st, s=t, st, tS and tS are called atomic. We define negation ¬φ as a shorthand using De Morgan equations, e.g., ¬tμXxφ(X):=tνXx¬φ(¬X), where y¬X is shorthand for ¬yX. Note that ¬¬φ=φ.

Given a set variable X, we say that X occurs positively in a pre-formula φ if φ contains no pre-formulas of the form tX for any term t. We say φ is a formula if, for any sub-pre-formula in φ of the form tμXxψ or tνXxψ, X occurs positively in ψ. We say a pre-set-term S is a set-term if tS is a formula for some t.

From now on, we will work with formulas where every second-order variable is bound. We adopt the standard abbreviations for connectives, such as φψ:=¬φψ, and φψ:=(φψ)(ψφ). Finally, we will write φ(νXxφ(X),t) for φ[νXxφ(X)/X,t/x].

Example 5 (Some fixed point formulas).

Consider the following formulas of μ:

  • N(X,x):=x=0y(yXx=𝗌y)

  • L(X,Y,x):=x=εz,w(zXwYx=z::w).

where the term ε encodes the empty list, and the term x::y encodes the operation of appending (the encoding of) an element y to (the encoding of) a list x333With a small abuse of notation we will often not distinguish between lists and numbers coding lists in μ𝖯𝖠. Moreover, since the append operation is primitive recursive, we will treat :: as a binary function symbol, so x::y will be considered a term of μ.. By definition, μ contains the set terms 𝐍:=μXx.N(X,x), 𝐋(Y):=μXx.L(X,Y,x), and 𝐓:=μYy.y𝐋(Y). As we will also see later, the latter formula illustrates a key aspect of μ𝖯𝖠, the ability to define mutually (co)inductive predicates, thanks to the interdependencies of fixed points.

2.2 Interpreting generalised inductive definitions

We now define the standard model of μ, where μXxφ and νXxφ are interpreted as least and greatest fixed points of the (parametrised) operator induced by φ.

To this end, we recall (a version of) the Knaster-Tarski theorem on power sets:

Proposition 6 (Knaster-Tarski).

Let S be a set and let f:𝒫(S)𝒫(S) be monotone (w.r.t. ). Then f has a least fixed point μf and a greatest fixed point νf. Moreover:

  • μf={ASf(A)A} and νf={ASAf(A)}

  • μf=κOrdμκf and νf=κOrdνκf

where the κ-approximants μκf and νκf are inductively defined by μκf=λ<κf(μλf) and νκf=λ<κf(νλf). Notice that μ0f= and ν0f=S.

Definition 7 (Standard model and satisfaction).

The standard model for μ is the μ-structure 𝔑, whose domain is , 0𝔑=0, 𝗌𝔑 is the successor, +𝔑 is the addition, ×𝔑 is the multiplication, and <𝔑 is the natural (strict) order on natural numbers.

An assignment is a map ρ associating an element ρ(x)|𝔑| (resp., a set ρ(X)𝔑) with every first-order variable x (resp., set variable X). We denote with ρ[xa] (resp., ρ[XA]) the assignment that sends x to a (resp., X to A) and otherwise preserves ρ.

The extension of assignments to terms t, written ρ(t), and the satisfaction relation 𝔑,ρφ are defined by induction in the standard way, e.g.:

𝔑,ρtμXxφ iff ρ(t)(μXxφ)𝔑𝔑,ρtνXxφ iff ρ(t)(νXxφ)𝔑

where, given the monotone function φρ,x,X𝔑:A{a|𝔑||𝔑,ρ[x,Xa,A]φ}, we set (μXxφ)𝔑:=μφρ,x,X𝔑 and (νXxφ)𝔑:=νφρ,x,X𝔑 (see Proposition 6). We simply write φ𝔑 to denote φρ,x,X𝔑 when it is clear from the context.

Example 8.

Let ρ be an assignment in 𝔑. Revisiting Example 5, we have that:
μ0N𝔑=μ0L𝔑=μ0T𝔑=μ1N𝔑={0}μ1L𝔑={ε}μ1T𝔑={ε}μ2N𝔑={0,1}μ2L𝔑=ρ(Y)<1μ2T𝔑=(μ1T𝔑)<ωμ3N𝔑={0,1,2}μ3L𝔑=ρ(Y)<2μ3T𝔑=(μ2T𝔑)<ωμωN𝔑=μω+1N𝔑=μωL𝔑=μω+1L𝔑=ρ(Y)<ωμωT𝔑=μω+1T𝔑=HFL

where the set of lists over X with length at most n (resp. with finite length) is denoted X<n (resp., X<ω), and HFL is the set of (the encodings of) hereditarily finite lists. Therefore, we have: 𝐍𝔑=(μXx.N)𝔑=μN𝔑=, 𝐋(Y)𝔑=(μXx.L(X,Y,x))𝔑=μL𝔑=ρ(Y)<ω, and 𝐓𝔑=(μYy.T(Y,y))𝔑=μT𝔑=HFL. Alternatively, we can see 𝐓𝔑 as the set of (the encodings) of rose trees, i.e., trees with unbounded (but finite) branching.

2.3 The theory 𝝁𝗣𝗔

The theory μ𝖯𝖠 over the language μ as presented in this paper is essentially the first-order part of Möllerfeld’s 𝖠𝖢𝖠0(μ) [23], which extends Peano arithmetic by the axiom schemas (pre-μ) and (ind-μ) defined as follows, for formulas ψ(x) and φ(X,x) positive in X:

y(φ(μXxφ,y)yμXxφ)y(φ(ψ,y)ψ(y))y(yμXxφψ(y))

and dually for ν. The first axiom states that μXxφ is a pre-fixed point. The second axiom states that it is the least among the pre-fixed points.

We will express μ𝖯𝖠 in sequent calculus style. In particular, thanks to the dualities of classical logic, we adopt so-called “one-sided” presentation, thus omitting the turnstile symbol “”.

Definition 9 (Sequent calculus for μ𝖯𝖠).

A sequent Γ is a list of formulas. The sequent calculus for μ𝖯𝖠 extends 𝖫𝖪= (first-order logic with equality) in Figure 2 (top) by:

  • the axioms of Peano arithmetic, where arithmetic induction is replaced by the rule

  • the rules μ and 𝗂𝗇𝖽(φ) in Figure 2 (bottom).

referring to Figure 2, we call Γ, Δ, θ(Γ), Γ(t), Γ(s) contexts, which are lists of formulas called side formulas. All the other formulas in the conclusion (resp., in a premise) of a rule are called principal formulas (resp., active formulas).

The one-sided sequent calculus streamlines the proofs. However, the more intuitive two-sided system will still be used for examples to facilitate the reading, and so the notation Δφ will be considered as shorthand for ¬Δ,φ. As an example, the rule 𝗂𝗇𝖽(φ) becomes . Also, in the examples, we will omit applications of structural rules as well as some arithmetical rules, and use double lines to abbreviate multiple applications of rules.

Figure 2: Sequent calculus rules for 𝖫𝖪= (first-order logic with equality), where θ is a substitution, i.e. a map from variables to terms, extended to formulas and sequents in the expected way (top figure), and sequent calculus rules for least and greatest fixed points (bottom figure).
 Remark 10 (Post-fixed points and numerical induction).

It is easy to see that the sequent calculus system μ𝖯𝖠 derives the axioms (pre-μ) and (ind-μ) (as well as their dual for ν). On the other hand, the following derivations show that we can recover the rule ν (Figure 2, bottom) and that, in presence of 𝗂𝗇𝖽(φ), numeric induction and the rule 𝐍 are equivalent:

In the latter derivation we let Γ=x(φ(x)φ(𝗌x)). Notice that the double lines labelled with φ express a “functoriality” property.

In fact, the choice of 𝐍 over numerical induction has the only purpose of simplifying the definition of progressing trace in the next section.

3 Cyclic proofs for generalised inductive definitions

In this section we introduce a cyclic version of the theory μ𝖯𝖠 based on ideas from the modal μ-calculus [24, 32, 2] and calculi of first-order logic with inductive definitions [8, 10]. Notice that this section borrows notions and notation from Definitions 2 and 3.

3.1 Progressivity and cyclic proofs

We define a notion of non-wellfounded (but finitely branching) proof we call “coderivation”.

Definition 11 (Coderivations).

A (μ𝖯𝖠-)coderivation, is a coderivation over the set of rules extending the rules of 𝖫𝖪= (Figure 2, top) by:

  • the axioms of Peano arithmetic, where arithmetic induction is replaced by the rule

  • the fixed point rules μ and ν in Figure 2 (bottom).

Intuitively, (μ𝖯𝖠-)coderivations are built from the same set of rules as μ𝖯𝖠 except that the rule ν replaces fixed point induction 𝗂𝗇𝖽(φ). We will show that the latter can be subsumed by the former in the context of cyclic proofs.

We adapt to our setting a well-known validity criterion from non-wellfounded proof theory.

Definition 12 (Traces and progress).

Let 𝒟 be a coderivation, and let (vi)iω be an infinite branch along 𝒟. A trace along (vi)iω is a sequence of occurrences formulas τ=(φi)ik such that for all ik, φi is in the conclusion of a rule 𝗋, φi+1 is in a premise of 𝗋, and one of the following cases applies:

  • φi is the principal formula and 𝗋=𝖾 with conclusion Γ,φi,ψ,Δ and premise Γ,ψ,φi+1,Δ

  • φi is the principal formula and 𝗋=𝖾 with conclusion Γ,ψ,φi,Δ and premise Γ,φi+1,ψ,Δ

  • φi is the principal formula of 𝗋𝖾 and φi+1 is an active formula

  • φi and φi+1 are the n-th side formulas in the context, for some n (so they are equal modulo term substitution).

We say that φk+1 is an immediate ancestor of φk if they extend to some trace (φi)ik. If φi=tνXx.φ (respectively φi=tμXx.φ) for some t, the rule 𝗋 is ν (respectively μ) and φi is principal then we say νXx.φ (respectively μXx.φ) progresses at i. A trace (φi)ik is progressing if there is a ν-term νXx.φ such that νXx.φ progresses infinitely often and νXx.φ is minimal (w.r.t number of symbols) among all set-terms progressing infinitely often.

Definition 13 (Progressing and cyclic proofs).

A progressing proof is a coderivation 𝒟 for which each infinite branch has a progressing trace. We write 𝖢μ𝖯𝖠 for the class of cyclic progressing proofs, and 𝖢μ𝖯𝖠φ if there is a cyclic progressing proof of φ.

Henceforth, we may mark two rule steps by a special symbol (e.g., or ) in a cyclic coderivation to indicate roots of identical sub-coderivations.

Example 14.

Consider the following two cyclic coderivations (see Example 5):

The left coderivation is not progressing, as its (only) branch looping at has no ν-formula, and so any trace traversing such branch cannot be progressing. On the other hand, the right coderivation is a progressing proof. It syntactically shows that (the encodings of) hereditarily finite lists are natural numbers, a trivial statement. Nonetheless, its argument is rather complex, and involves nesting of cycles because of the interleaving fixed points within 𝐓.

Now, for any infinite branch 𝔟 one of the following cases applies:

  • 𝔟 eventually loops only at : the trace alternating orange and blue formulas is progressing, and the smallest ν-term unfolding infinitely often is 𝐋(𝐓) (in negative position).

  • 𝔟 eventually loops only at : the trace alternating orange and red formulas is progressing, and the smallest ν-term unfolding infinitely often is 𝐓 (in negative position).

  • 𝔟 loops infinitely often at both and : the trace alternating orange and blue formulas along , and orange and red formulas along , is progressing, and the smallest ν-term unfolding infinitely often is 𝐓 (in negative position).

Thus, any infinite branch has a progressing trace, and so the right coderivation is progressing.

3.2 Simulating inductive proofs

Our cyclic system 𝖢μ𝖯𝖠 subsumes μ𝖯𝖠 by a standard argument:

Theorem 15 (Induction to cycles).

If μ𝖯𝖠φ then 𝖢μ𝖯𝖠φ.

Proof sketch.

By induction on the structure of μ𝖯𝖠 proofs. The critical step is 𝗂𝗇𝖽(φ), for which we do not have a corresponding rule in 𝖢μ𝖯𝖠. We simulate this rule by the following:

where the rule steps marked φ can be defined by induction on the structure of φ. To check progressivity of the above coderivation, notice that any infinite branch is either progressing by the induction hypothesis, or loops infinitely on and has the progressing trace coloured in blue.

4 A reset proof system for 𝝁𝗣𝗔

In this section we introduce an alternative route to cyclic proofs that allows for a more local and simpler (although more constrained) validity condition: so-called reset proofs (e.g., [2, 3, 4, 22]. Specifically, we define a cyclic reset proof system for μ𝖯𝖠, called 𝖢μ𝖯𝖠ann, inspired by the annotated systems for first-order μ-calculus in [31, 1]. A key property of reset proof systems is the introduction of variables ranging over ordinals annotating fixed point formulas in a coderivation. Intuitively, an annotated fixed point μκXxφ, where κ is an ordinal variable, expresses syntactically an ordinal approximant of μXxφ (see Proposition 6). The advantage of this approach is the possibility to internalise certain features of the progressivity condition, which can be then subsumed in a much simpler condition called reset condition. This allows for a more straightforward soundness argument. Soundness for 𝖢μ𝖯𝖠 can then be established by defining a translation of progressing proofs of 𝖢μ𝖯𝖠 into reset proofs.

4.1 Syntax and semantics of 𝗖𝝁𝗣𝗔𝐚𝐧𝐧

The language of 𝖢μ𝖯𝖠ann, written μann, is a three-sorted language obtained by augmenting μ by a countable set of ordinal variables 𝒪𝒱 ranging over κ,λ. We extend Definition 4 to include new set terms μκXxφ and νκXxφ for any ordinal variable κ.

Concerning semantics of 𝖢μ𝖯𝖠ann, the standard model is defined as in Definition 7, while assignments ρ are extended to associate with every ordinal variable κ𝒪𝒱 an ordinal ρ(κ). Satisfaction relation is then extended to the clauses tμκXxφ and tνκXxφ as follows:

𝔑,ρtμκXxφiffρ(t)μρ(κ)φρ,x,X𝔑𝔑,ρtνκXxφiffρ(t)νρ(κ)φρ,x,X𝔑

All the remaining definitions and conventions smoothly adapt to the new setting.

𝖢μ𝖯𝖠ann derives extended sequents, i.e., sequents equipped with conditions on ordinal variables called constraints. These are pairs 𝒪=(V𝒪,<𝒪) where V𝒪 is a finite set of ordinal variables and <𝒪 is a strict partial order such that, for each κV𝒪, the set {λV𝒪|κ<𝒪λ} is linearly ordered by <𝒪. Intuitively, the condition λ<𝒪κ is interpreted as the assumption that λ is “smaller” than κ. Notice that 𝒪 can be seen as a collection of trees with V𝒪 the set of vertices, and the descendant relation is the converse of the order <𝒪: the children of κV𝒪 are then λV𝒪 where λ<𝒪κ and for no ξV𝒪 do we have λ<𝒪ξ<𝒪κ.

We will sometimes write 𝒪λ<κ instead of λ<𝒪κ. Also, we write κ𝒪 as shorthand for κV𝒪, and with we denote the empty constraint. We set λ𝒪κ:=λ<𝒪κ or λ=κ.

Definition 16 (Extended sequents).

An (annotated) sequent Γ is a finite list of formulas over μann. An extended sequent is an expression 𝒪:Γ where Γ is an annotated sequent and 𝒪 is a constraint such that V𝒪 contains all ordinal variables in Γ. Given an annotated sequent Γ, we denote with Γ the sequent without ordinal variables.

The standard interpretation for μann can be generalised to extended sequents in the obvious way. Given a constraint 𝒪, and assignment ρ, we define ρ𝒪 iff λ<𝒪κ implies ρ(λ)<𝒪ρ(κ) for all λ,κ𝒪. An extended sequent 𝒪:Γ is satisfied in 𝔑 if, for all assignments ρ for 𝔑, ρ𝒪 implies 𝔑,ρΓ.

4.2 Annotated coderivations and reset proofs

For the purpose of presenting the inference rules we require three operations on constraints:

𝒪+λ:=(V𝒪{λ},<𝒪)𝒪+κλ:=(V𝒪{λ},<𝒪{(λ,ξ)|κ𝒪ξ})𝒪V:=(V𝒪V,<𝒪(V𝒪V)2)

where VV𝒪. The top left operation adds λ as a fresh ordinal variable, which becomes the root of a new tree in 𝒪. In the bottom left operation λ is added as a fresh child of the ordinal variable κ. Note that these operations preserve the condition that the set {λV𝒪|κ<𝒪λ} is linearly ordered by <𝒪 for every κV𝒪, and so the tree structure is also preserved. The right operation restricts a constraint set to a subset V of ordinal variables.

Figure 3: Inference rules for annotated coderivations (notation Γ is introduced in Definition 16).

The rules of our reset system are in Figure 3. They essentially “lift” the rules of 𝖢μ𝖯𝖠 to extended sequents, replacing ν with decorated versions (ν and νκ) internalising fixed points approximants (see Proposition 6), and with the rule 𝖼𝗐 removing a set L𝒪 from the constraint. Validity condition will be defined via so-called reset rule (RS(κ)), a special case of 𝖼𝗐, where C(κ) is the set of the children of κ in 𝒪 and must be non-empty, and κ does not occur in Γ. Translating from μ𝖯𝖠 to 𝖢μ𝖯𝖠ann requires another special case of 𝖼𝗐, a novelty of this paper called the pruning rule, where P(Γ) is the set of all ordinal variables that have no descendants occurring in Γ (i.e., {κ𝒪|λ𝒪(λ𝒪κλ does not occur in Γ)}), and must be non-empty. Intuitively, the pruning rule is used to “refresh” constraints preventing unbounded increase of ordinal variables along infinite branches of reset proofs.

Definition 17 (Annotated coderivations).

An annotated coderivation is a coderivation over the rules in Figure 3.

We are now ready to define the reset condition, which represents a counterpart to the progressivity condition in the setting of annotated coderivations.

Definition 18 (Reset proofs).

Let 𝒟 be an annotated coderivation, and let 𝔟=(𝒪i:Γi)i0 be an infinite branch of 𝒟. We say that κ is a stable variable in 𝔟 if there is i00 such that κ𝒪i, for every ii0. We say that κ is a reset variable in 𝔟 if there are infinitely many occurrences of RS(κ) in 𝔟. We say that 𝒟 is a reset proof if every infinite branch has a stable reset variable. We denote with 𝖢μ𝖯𝖠ann the class of cyclic reset proofs444𝖢μ𝖯𝖠ann is based on the reset system for the μ-calculus from [31], and later refined in [1], but differs in many respects. Concerning syntax, 𝖢μ𝖯𝖠ann is endowed with the language of 𝖯𝖠 and omits quantification over ordinal variables. Concerning the proof system, it is formulated in one-sided sequent calculus style. Also, we avoid working with finite representations of cyclic proofs, which allows us to bypass some syntactic technicalities /such as so-called order-coherence in [1] to check validity and cyclicity conditions). .

Example 19.

Consider the following annotated coderivation of the formula tνXx(xX).

It has only one infinite branch (looping at ) that unfolds infinitely often (annotations of) the formula tνXx(xX). The branch contains a stable reset variable λ. Therefore, the annotated coderivation is a (cyclic) reset proof.

The main result of this section is soundness for cyclic reset proofs. This is a standard argument towards contradiction that leverages a preliminary lemma, which shows that inference rules locally preserve soundness, and constructs an infinite branch of the reset proof that reflects falsity. Specifically, our argument is essentially borrowed from [1].

Lemma 20 (Local soundness).

For any inference rule 𝗋 of 𝖢μ𝖯𝖠ann with conclusion 𝒪:Σ, if 𝔑,ρ𝒪:Σ then there is a premise 𝒪:Σ of 𝗋 and assignment ρ s.t.

  1. 1.

    𝔑,ρ𝒪:Σ and

  2. 2.

    for any κ𝒪𝒪 we have ρ(κ)ρ(κ). If moreover, 𝗋=RS(κ) then ρ(κ)<ρ(κ).

Theorem 21 (Soundness).

For any reset proof 𝒟 with conclusion 𝒪:Γ, 𝔑𝒪:Γ.

Proof.

Assume by contradiction that 𝒟 is a reset proof with conclusion 𝒪:Γ s.t. 𝔑,ρ𝒪:Γ for some assignment ρ. By Lemma 20 we can construct an infinite branch (𝒪i:Γi)i0 of 𝒟 and a sequence of assignments (ρi)i<ω such that 𝒪0:Γ0:=𝒪:Γ, ρ0:=ρ and for all i0:

  1. 1.

    𝔑,ρi𝒪i:Γi

  2. 2.

    for any κ𝒪i𝒪i+1 we have ρi+1(κ)ρi(κ)

  3. 3.

    if κ𝒪i and 𝒪i:Γi is the conclusion of a reset rule RS(κ) then ρi+1(κ)<ρi(κ).

Since 𝒟 is a reset proof, there will be some stable reset variable κ along this branch, and so for some m we have κ𝒪n for every nm. Consider the ordinal sequence (ρn(κ))nm. By construction we have ρn+1(κ)ρn(κ) for every nm and ρn+1(κ)<ρn(κ) at every reset step. Since κ is reset infinitely many times this contradicts wellfoundedness of ordinals.

5 From progressing proofs to reset proofs

In this section we show that sequents provable in 𝖢μ𝖯𝖠 are also provable in 𝖢μ𝖯𝖠ann. To this end, we define a (parametrised) translation (_)𝒪1,,n from (μ𝖯𝖠-)coderivations 𝒟 with conclusion φ1,,φn into annotated coderivations with conclusion 𝒪:φ11,φnn, where each i “decorates” occurrences of ν in φi with ordinal variables. Specifically, the translation corecursively (i.e., bottom-up) turns sequents of 𝒟 into extended sequents (modifying inference rules accordingly). We show that the translation maps, in particular, cyclic progressing proofs into cyclic reset proofs, from which we can derive soundess of 𝖢μ𝖯𝖠.

Definition 22 (Ordinal assignments).

Let φ be a formula of μ and V𝒪𝒱. A list =a1an over V{} is called an (V-)ordinal assignment for φ, written Vφ (sometimes φ), if the length of is equal to the number of occurrences of ν in φ. We define φ to be the formula μann obtained by replacing the i-th occurrence of ν (from left) with νai if ai, and with ν itself otherwise. We extend ordinal assignments to sequents Γ=φ1,,φn by setting 1,,nVΓ if iVφi for all 1in, and Γ1,,n:=φ11,,φnn.

Example 23.

Consider φ:=tνXx(sνYy(xXyY𝐍)), and let κ𝒪𝒱. Then, :=κ is an ordinal assignment for φ, and φ=tνκXx(sνYy(xXyY𝐍))=tνκXx(sνYy(xXyY𝐍)).

Definition 24 (Translation).

Let 𝒟 be a μ𝖯𝖠-coderivation with conclusion Σ, and let 𝒪=(V𝒪,<𝒪) be a constraint such that 1,,nV𝒪Σ. We define coinductively the translation ()𝒪1,,n mapping 𝒟 into an annotated coderivation 𝒟𝒪1,,m with conclusion 𝒪:Σ1,,n. We consider only the most relevant case where the coderivation ends with a ν step, with Σ:=Γ,tνXxφ. If n:=λ then:

The case n:= is similar.

Theorem 25.

If 𝖢μ𝖯𝖠φ then 𝖢μ𝖯𝖠ann:φ.

Proof idea.

Let 𝒟 be a 𝖢μ𝖯𝖠 coderivation with conclusion φ. Let 𝔟=(𝒪i:Γi)i0 be an infinite branch in 𝒟. There exists a unique infinite branch 𝔟^=(Δi)i0 of 𝒟 that translates into 𝔟. By hypothesis, 𝔟^ has a progressing trace τ^=(φi)ii0 for some i00. Let νXx.φ be the smallest infinitely progressing set-term in τ^. Recalling notation () (Definition 16), τ^ induces a trace τ=(ψi)ii1 of 𝔟 such that τ:=(ψi)ii1 enumerates (φi)ii0 (possibly with repetitions). Moreover, by progressivity of τ^, there is i2i1 and a sequence of ordinal variables (κi)ii2 such that, for all ii2:

  1. (i)

    νκiXx.φ occurs in ψi.

  2. (ii)

    Either κi+1=κi or κi+1 is the child of κi in 𝒪i+1 (i.e., in any case, κi𝒪i+1κi+1).

  3. (iii)

    There exists ji s.t. κj+1 is the child of κj in 𝒪j+1.

Let us show that 𝔟 has a stable variable. For ii2 set Ai:={λ𝒪i𝒪iλκi}. This is a finite linear order (non-empty by i), and we pick a maximal element θAi2 (which is also maximal in 𝒪i2). By ii if θAi then θAi+1 unless θ is removed by a reset or a pruning rule. But θ cannot be pruned because of i. Also, no ν-rule or νκ-rule can introduce a parent of θ, so θ cannot be removed by a reset rule either.

Now, since Ai2 contains a stable variable θ, it also contains a minimal one θ. Since ν is applied infinitely often in 𝔟^, the reset and pruning rules are applied infinitely often along 𝔟 (see Definition 24, case ν). From this fact, using iii, we can show that RS(θ) is applied infinitely often along 𝔟.

By inspecting the translation it is not too hard to see that 𝒟 is cyclic when 𝒟 is.

Soundness for progressing proofs follows as a straightforward corollary:

Corollary 26 (Soundness for 𝖢μ𝖯𝖠).

Let 𝒟𝖢μ𝖯𝖠 with conclusion φ. Then, 𝔑φ.

Proof.

By Theorem 25 we have that 𝒟 is a cyclic reset proof of :φ=φ. By Theorem 21 we have 𝔑:φ, and so 𝔑φ.

6 Formalising the soundness argument in 𝚷𝟐𝟏-𝗖𝗔𝟎

The final section of this paper is devoted to proving the converse of Theorem 15. To this end, taking inspiration from previous work [28, 14], we use second-order theories to formalise the soundness theorem for the reset system 𝖢μ𝖯𝖠ann (Theorem 21), and then we appeal to conservativity results (Theorem 33).

6.1 Theories of second-order arithmetic

We shall work with common subsystems of second-order arithmetic, as found in textbooks such as [29], and assume basic facts about them. In particular, recall that 𝖠𝖢𝖠0 is a two-sorted extension of basic arithmetic by:

  • Arithmetical comprehension. Xx(X(x)φ(x)) for each arithmetical formula φ(x).

  • Set induction. X(X(0)x(X(x)X(𝗌x))xX(x))

From here, Π21-𝖢𝖠0 is the extension of 𝖠𝖢𝖠0 by the comprehension schema for all Π21 formulas. We shall freely use established principles of Π21-𝖢𝖠0 (as seen, e.g., in [29]) such as Σ21-comprehension, Σ21-choice and Σ21-dependent choice. The term Σk1 will denote formulas provably equivalent under Π21-𝖢𝖠0 to a formula of the form X0X1Qnφ with φ arithmetical, and similarly for Πk1 and Δk1. We use the notation for the code of a tuple. If the tuple contains a set then will be a second-order object. For any set F we can consider F as a function F:SET by setting F(x):={y|x,yF}.

For the formalised soundness argument we will need that Δ21 formulas are closed under positive arithmetical combinations (over Π21-𝖢𝖠0).

Theorem 27.

Let ψ(φ0,φn) be a positive arithmetical combination of φ0,φn. If φ0,φnΣ21 (resp., Π21) then ψ(φ0,φn)Σ21 (resp., Π21).

6.2 Countable orders in 𝚷𝟐𝟏-𝗖𝗔𝟎

A basic theory of (countable) ordinals can be developed even within weak second-order theories, as shown in [Sim99] and also comprehensively surveyed in [Hir05].

A (countable) binary relation is a pair (X,) where X and are sets, the latter construed as ranging over pairs. We shall write α, β etc. to range over countable binary relations. If α=(X,) we may write xαy:=x,yXxy, and similarly for x<αy. We may also write xα instead of xX. We write WO(α) for the Π11 statement that α is a well-order.

Following Simpson in [Sim99], given α, βWO we write αβ if there is an order-isomorphism from α onto a proper initial segment of β, αβ if α and β are order-isomorphic and αβ if αβαβ. We have the following basic facts about comparison:

Proposition 28.

Π21-𝖢𝖠0 proves that:

  1. 1.

    , and are all Δ11.

  2. 2.

    is a total linear order

  3. 3.

    is well-founded: F:WO((xy>xF(y+1)F(y))x(F(x)F(x+1)))

6.3 Knaster-Tarski Theorem and approximants

We have two ways of interpreting the μ- and ν-binders in second-order arithmetic. First:

tμXx.φ :=X(x(φ(X,x)xX)tX) (1)
tνXx.φ :=X(x(xXφ(X,x))tX) (2)

Another way of interpreting μ and ν is through approximants:

Definition 29 (Approximants).

We write:

tμαXx.φ := F:αSETaα(bαy(yF(b)c<αbφ(F(c),y))tF(a))
tμWOXx.φ := αWOtμαXx.φ
tναXx.φ := F:αSETaα(bαy(c<αbφ(F(c),y)yF(b))tF(a))
tνWOXx.φ := αWOtναXx.φ

For the remainder of this section, assume φ(X,x)Δ21 and that φ(X,x) is positive in X. The results of this section are all proven in [12] for μ-terms and the dual properties for ν-terms can then be obtained using the fact Π21-𝖢𝖠0tμXx.φ(X,x)tνXx.¬φ(¬X,x) and similar for μαXx.φ and μWOXx.φ.

The first proposition shows that Π21-𝖢𝖠0 has access to the recursive characterizations of ν-approximants as well as the fact that μXx.φ is a fixed points.

Proposition 30 (Recursion and Knaster-Tarski).

Π21-𝖢𝖠0 proves

tναXx.φ βαφ(νβXx.φ,t)
tμXx.φ(X,x) φ(μXx.φ,y)

In [12] it is shown that if WO(α) then μαXx.φ and ναXx.φ are in Δ21. Using this fact and standard prenexing we see that μWOXx.φΣ21. Also, by standard prenexing and Σ21-choice we see that μXx.φΠ21. In [12] it is also shown that the two interpretations of μ and ν are provably equivalent in Π21-𝖢𝖠0, i.e. μXx.φ=μWOXx.φ and νXx.φ=νWOXx.φ. Putting all this together we get that for WO(α):

Corollary 31.

μαXx.φ, ναXx.φ, μXx.φ, μWOXx.φ, νXx.φ and νWOXx.φ are all Δ21.

6.4 Interpreting 𝗖𝝁𝗣𝗔 and 𝗖𝝁𝗣𝗔𝐚𝐧𝐧 in 𝚷𝟐𝟏-𝗖𝗔𝟎

We may define an interpretation (_) from 𝖢μ𝖯𝖠 to Π21-𝖢𝖠0 defined by (tμXxφ):=tμXxφ and (tνXxφ):=tνXxφ. Similarly, we can define an interpretation (_) from 𝖢μ𝖯𝖠ann to Π21-𝖢𝖠0 by (tμXx.φ):=tμXx.φ, (tνXx.φ):=tνWOXx.φ and (tνκ.Xxφ):=tνκXx.φ. Writing the two different interpretations of νXxφ the same is justified by Π21-𝖢𝖠0νXx.φ=νWOXx.φ [12]. By Corollary 31 and Theorem 27 we have:

Theorem 32.

If φ is a formula of 𝖢μ𝖯𝖠 then φ is Δ21.

Theorem 32 allows Π21-𝖢𝖠0 to readily verify the axioms of μ𝖯𝖠 using Π21-comprehension, and so μ𝖯𝖠 can be considered a fragment of Π21-𝖢𝖠0. In fact, by a result of Möllerfeld’s, Π21-𝖢𝖠0 not only extends μ𝖯𝖠 but does so conservatively.

Theorem 33 (Implied by [23]).

Π21-𝖢𝖠0 is arithmetically conservative over μ𝖯𝖠.

This is a nontrivial result in proof theory whose details we shall not recount. We will use this theorem as a “black box” henceforth.

6.5 Formalizing 𝗖𝝁𝗣𝗔𝐚𝐧𝐧 satisfaction in 𝚷𝟐𝟏-𝗖𝗔𝟎

We will employ standard metamathematical notations and conventions for coding, e.g. we write E for the Gödel code of an expression E. As usual, a predicate language cannot contain its own universal truth predicate for Tarskian reasons. However we may define partial truth predicates for fragments of the language, in particular, each of our partial satisfaction predicates will be relativized to a single 𝖢μ𝖯𝖠ann proof 𝒟 containing only finitely many ordinal variables and set-terms.

We let Sat𝒟(ρ,m,A,α):=ρ,mμZz.χ(z,Z,A,α) where χ(z,Z,A,α) is a Δ21 formula and so Sat𝒟(ρ,m,A,α)Δ21. There are two main properties that we need our partial satisfaction predicate to satisfy. The first is reflection.

Theorem 34 (Reflection).

Let φ(X,x,κ) be a subformula of a formula in 𝒟. Then Π21-𝖢𝖠0 proves Sat𝒟(ρ,φ(X,x,κ),A,α)φ(A,ρ(x),α).

Secondly, our partial satisfaction predicate needs to satisfy the proper inductive characterization of satisfaction e.g. Sat𝒟(ρ,xφ,A,α)nSat𝒟(ρ{xn},φ,A,α) and
i,j=0kSat𝒟(ρ,tνκjXixi.φi,A,α)ρ(t)ναjYiyi.Sat𝒟(ρ{xiyi},φi,A0,Yi,Ak,α))

Theorem 35 (Formalised satisfaction).

Π21-𝖢𝖠0 proves that Sat𝒟(ρ,m,A,α) satisfies the inductive characterization of satisfaction for every connective.

For the formalized soundness proof we also need to extend our satisfaction predicate Sat𝒟 so that it works with constraints and extended sequents. This is done in the expected way.

6.6 Formalizing soundness for 𝗖𝝁𝗣𝗔𝐚𝐧𝐧

Recall that in Theorem 21, after showing the existence of the branch witnessing falsity, we invoke the reset condition to extract a stable reset variable along the false branch and thereby get a contradiction. To mimic this step inside Π21-𝖢𝖠0 it is crucial that Π21-𝖢𝖠0 “knows” that the proof satisfies the reset condition.

Lemma 36.

Let 𝒟 be a 𝖢μ𝖯𝖠ann proof. Then Π21-𝖢𝖠0 proves that for all branches 𝔟 in 𝒟 there exists a stable reset variable κ along 𝔟.

Proof.

The idea is standard and is covered in detail in [14]. It is provable in Π21-𝖢𝖠0 (and much weaker theories) that for a 𝖢μ𝖯𝖠ann derivation 𝒟, satisfying the reset condition is equivalent to language inclusion of two Büchi automata which can both be computed from 𝒟. Since by [19] language inclusion for Büchi automata is decidable it follows that, if 𝒟 satisfies the reset condition, then Π21-𝖢𝖠0 proves that fact.

Theorem 37 (Formalising soundness).

Let 𝒟 be a 𝖢μ𝖯𝖠ann proof with conclusion 𝒪𝒟:Γ𝒟. Then Π21-𝖢𝖠0αWOρ,ASat𝒟(ρ,𝒪𝒟:Γ𝒟,A,α)

Proof.

Assume for contradiction that ¬Sat𝒟(ρ𝒟,𝒪𝒟:Γ𝒟,A,α𝒟). As in Theorem 21 we will show the existence of a false branch satisfying certain conditions. The key to this is Lemma 20 which says that whenever we have a false extended sequent then we can find a premise which is false and satisfies the right conditions on ordinal variables. To state Lemma 20 inside Π21-𝖢𝖠0 we define the following formulas:

ξ(X):=X=ρ,𝒪:Γ,α𝒪:Γ is in 𝒟WO(α)¬Sat𝒟(ρ,𝒪:Γ,A,α)
χ(X,Y):=X=ρ,𝒪:Γ,αY=ρ,𝒪:Γ,α𝒪:Γ is a premise in 𝒟 of 𝒪:Γnk(κn𝒪𝒪((αnαn)(the rule is RS(κn)αnαn)))

Note that both ξ(X) and χ(X,Y) are arithmetical in Sat𝒟, and WO, and so they are Δ21 by Theorem 27. Let Z𝒟=ρ𝒟,𝒪𝒟:Γ𝒟,α𝒟. The formal equivalent of Lemma 20 is:

XY((ξ(X)(ξ(Y)χ(X,Y)))(¬ξ(X)Y=Z𝒟)) (3)

To see that this can be proven within Π21-𝖢𝖠0, first note that for X with ¬ξ(X) we just let Y=Z𝒟, so the hard case is when ξ(X) holds. The proof of this case mimics directly the meta-level proof of Lemma 20 using the inductive characterization of satisfaction Theorem 35. We also need Proposition 30(1) for the νκ-rule, Proposition 30(2) for the μ-rule and Proposition 28 for the reset rule. More details can be found in the appendix.

Since ξ(X) and χ(X,Y) are Δ21 we can apply Σ21-dependent choice555(Σ21-dependent choice)XYφ(X,Y)F:SETnφ(F(n),F(n+1))φΣ12 to (3) to get a suitable branch. By Σ21-dependent choice there exists F:SET s.t.

n((ξ(F(n))(ξ(F(n+1))χ(F(n),F(n+1))))(¬ξ(F(n))F(n+1)=Z𝒟))

Note that if ¬ξ(F(0)) then F(1)=Z𝒟 and so ξ(F(1)), which means by an easy induction that n1ξ(F(n)). By comprehension we define B(n):=F(n+1) and so B is a branch witnessing falsity satisfying nχ(B(n),B(n+1)).

Now we apply Lemma 36 to get a stable reset variable κj such that, for some m and all nm, κj occurs in 𝒪, where B(n)=ρ,𝒪:Γ,α. Finally, using this stable reset variable we want to show the existence of an infinitely descending ordinal sequence. By comprehension we get G:WO s.t. G:nαB(n+m)=ρ,𝒪:Γ,α0,αj1,α,αk. Then, since nχ(B(n),B(n+1)) we see that G contradicts Proposition 28(3).

7 Conclusions and future works

We studied the cyclic proof theory of arithmetic with generalised inductive definitions. Specifically, we extended Simpson’s equivalence result between Peano arithmetic and its cyclic formulation [28], further generalising Das and Melgaard’s work on (finitely iterated) arithmetical inductive definitions [15]. Along the way, we also established an equivalence between two alternative validity conditions for cyclic proofs in our setting: the commonly adopted condition based on the notion of progressing trace and so-called reset condition for annotated proof systems (e.g., [31, 1]).

Our results easily apply to the intuitionistic context, essentially using negative translations studied in [35, 12]. Because of the absence of classical logic dualities, we can identify weaker versions of generalised inductive definitions, such as the strictly positive ones (defined by fixed points where μ does not bind set variables to the left of an implication). Such subsystems are of great importance for implementation perspectives, as proof assistants (such as Coq or Agda) typically enforce strict positivity conditions on (co)inductive types for consistency reasons. Despite being apparently more restrictive, strictly positive fixed points are commonly believed to have the same proof theoretic strength of the (hereditarily) positive ones (see [18]). These considerations deserve further investigations.

References

  • [1] Bahareh Afshari, Sebastian Enqvist, and Graham E. Leigh. Cyclic proofs for the first-order μ-calculus. Log. J. IGPL, 32(1):1–34, 2024. doi:10.1093/JIGPAL/JZAC053.
  • [2] Bahareh Afshari and Graham E. Leigh. Cut-free completeness for modal mu-calculus. In 32nd Annual ACM/IEEE Symposium on Logic in Computer Science, LICS 2017, Reykjavik, Iceland, June 20-23, 2017, pages 1–12. IEEE Computer Society, 2017. doi:10.1109/LICS.2017.8005088.
  • [3] Bahareh Afshari and Graham E. Leigh. Lyndon interpolation for modal μ-calculus. In Language, Logic, and Computation: 13th International Tbilisi Symposium, TbiLLC 2019, Batumi, Georgia, September 16–20, 2019, Revised Selected Papers, pages 197–213, Berlin, Heidelberg, 2019. Springer-Verlag. doi:10.1007/978-3-030-98479-3_10.
  • [4] Bahareh Afshari, Graham E. Leigh, and Guillermo Menéndez Turata. Uniform interpolation from cyclic proofs: The case of modal μ-calculus. In Automated Reasoning with Analytic Tableaux and Related Methods: 30th International Conference, TABLEAUX 2021, Birmingham, UK, September 6–9, 2021, Proceedings, pages 335–353, Berlin, Heidelberg, 2021. Springer-Verlag. doi:10.1007/978-3-030-86059-2_20.
  • [5] Bahareh Afshari and Dominik Wehr. Abstract cyclic proofs. Math. Struct. Comput. Sci., 34(7):552–577, 2024. doi:10.1017/S0960129524000070.
  • [6] Stefano Berardi and Makoto Tatsuta. Classical system of martin-löf’s inductive definitions is not equivalent to cyclic proof system. In Javier Esparza and Andrzej S. Murawski, editors, Foundations of Software Science and Computation Structures - 20th International Conference, FOSSACS 2017, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2017, Uppsala, Sweden, April 22-29, 2017, Proceedings, volume 10203 of Lecture Notes in Computer Science, pages 301–317, 2017. doi:10.1007/978-3-662-54458-7_18.
  • [7] Stefano Berardi and Makoto Tatsuta. Equivalence of inductive definitions and cyclic proofs under arithmetic. In 32nd Annual ACM/IEEE Symposium on Logic in Computer Science, LICS 2017, Reykjavik, Iceland, June 20-23, 2017, pages 1–12. IEEE Computer Society, 2017. doi:10.1109/LICS.2017.8005114.
  • [8] James Brotherston. Cyclic proofs for first-order logic with inductive definitions. In Bernhard Beckert, editor, Automated Reasoning with Analytic Tableaux and Related Methods, International Conference, TABLEAUX 2005, Koblenz, Germany, September 14-17, 2005, Proceedings, volume 3702 of Lecture Notes in Computer Science, pages 78–92. Springer, 2005. doi:10.1007/11554554_8.
  • [9] James Brotherston, Dino Distefano, and Rasmus Lerchedahl Petersen. Automated cyclic entailment proofs in separation logic. In Nikolaj S. Bjørner and Viorica Sofronie-Stokkermans, editors, Automated Deduction - CADE-23 - 23rd International Conference on Automated Deduction, Wroclaw, Poland, July 31 - August 5, 2011. Proceedings, volume 6803 of Lecture Notes in Computer Science, pages 131–146. Springer, 2011. doi:10.1007/978-3-642-22438-6_12.
  • [10] James Brotherston and Alex Simpson. Complete sequent calculi for induction and infinite descent. In 22nd IEEE Symposium on Logic in Computer Science (LICS 2007), 10-12 July 2007, Wroclaw, Poland, Proceedings, pages 51–62. IEEE Computer Society, 2007. doi:10.1109/LICS.2007.16.
  • [11] James Brotherston and Alex Simpson. Sequent calculi for induction and infinite descent. J. Log. Comput., 21(6):1177–1216, 2011. doi:10.1093/LOGCOM/EXQ052.
  • [12] Gianluca Curzi and Anupam Das. Computational expressivity of (circular) proofs with fixed points. In 38th Annual ACM/IEEE Symposium on Logic in Computer Science, LICS 2023, Boston, MA, USA, June 26-29, 2023, pages 1–13. IEEE, 2023. doi:10.1109/LICS56636.2023.10175772.
  • [13] Gianluca Curzi and Lukas Melgaard. Cyclic proof theory of positive inductive definitions, 2025. doi:10.48550/arXiv.2507.13057.
  • [14] Anupam Das. On the logical complexity of cyclic arithmetic. Logical Methods in Computer Science, Volume 16, Issue 1, January 2020. doi:10.23638/LMCS-16(1:1)2020.
  • [15] Anupam Das. On the logical strength of confluence and normalisation for cyclic proofs. In Naoki Kobayashi, editor, FSCD ’21, July 17-24, 2021, Buenos Aires, Argentina (Virtual Conference), volume 195 of LIPIcs, pages 29:1–29:23. Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2021. doi:10.4230/LIPIcs.FSCD.2021.29.
  • [16] Anupam Das and Lukas Melgaard. Cyclic proofs for arithmetical inductive definitions. In Marco Gaboardi and Femke van Raamsdonk, editors, 8th International Conference on Formal Structures for Computation and Deduction, FSCD 2023, July 3-6, 2023, Rome, Italy, volume 260 of LIPIcs, pages 27:1–27:18. Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2023. doi:10.4230/LIPIcs.FSCD.2023.27.
  • [17] Jacobus W de Bakker and Dana Scott. A theory of programs. In IBM seminar, Vienna, 1969.
  • [18] Solomon Feferman, W Sieg, and W Buchholz. Iterated inductive definitions and subsystems of analysis: Recent proof-theoretical studies. Springer, 1981.
  • [19] Leszek Aleksander Kolodziejczyk, Henryk Michalewski, Pierre Pradic, and Michal Skrzypczak. The logical strength of Büchi’s decidability theorem. Log. Methods Comput. Sci., 15(2), 2019. doi:10.23638/LMCS-15(2:16)2019.
  • [20] Graham E. Leigh and Dominik Wehr. From GTC to : Generating reset proof systems from cyclic proof systems. Ann. Pure Appl. Log., 175(10):103485, 2024. doi:10.1016/J.APAL.2024.103485.
  • [21] Robert S. Lubarsky. μ-definable sets of integers. Journal of Symbolic Logic, 58:291–313, 1993. doi:10.2307/2275338.
  • [22] Johannes Marti and Yde Venema. A focus system for the alternation-free μ-calculus. In Automated Reasoning with Analytic Tableaux and Related Methods: 30th International Conference, TABLEAUX 2021, Birmingham, UK, September 6–9, 2021, Proceedings, pages 371–388, Berlin, Heidelberg, 2021. Springer-Verlag. doi:10.1007/978-3-030-86059-2_22.
  • [23] Michael Möllerfeld. Generalized inductive definitions. PhD thesis, University of Münster, Germany, 2003. URL: https://nbn-resolving.org/urn:nbn:de:hbz:6-85659549572.
  • [24] Damian Niwinski and Igor Walukiewicz. Games for the mu-calculus. Theor. Comput. Sci., 163(1&2):99–116, 1996. doi:10.1016/0304-3975(95)00136-0.
  • [25] Michael Rathjen. Recent advances in ordinal analysis: Π21-CA and related systems. Bulletin of Symbolic Logic, 1(4):468–485, 1995. doi:10.2307/421132.
  • [26] Reuben N. S. Rowe and James Brotherston. Automatic cyclic termination proofs for recursive procedures in separation logic. In Yves Bertot and Viktor Vafeiadis, editors, Proceedings of the 6th ACM SIGPLAN Conference on Certified Programs and Proofs, CPP 2017, Paris, France, January 16-17, 2017, pages 53–65. ACM, 2017. doi:10.1145/3018610.3018623.
  • [27] Harold Schellinx. Basic proof theory, A.S. troelstra and h. schwichtenberg. J. Log. Lang. Inf., 7(2):221–223, 1998. doi:10.1023/A:1008226228293.
  • [28] Alex Simpson. Cyclic arithmetic is equivalent to peano arithmetic. In Javier Esparza and Andrzej S. Murawski, editors, FOSSACS ’17, Held as Part of ETAPS ’17, Uppsala, Sweden, April 22-29, 2017, Proceedings, volume 10203 of Lecture Notes in Computer Science, pages 283–300, 2017. doi:10.1007/978-3-662-54458-7_17.
  • [29] Stephen G. Simpson. Subsystems of second order arithmetic. Perspectives in mathematical logic. Springer, 1999.
  • [30] Christoph Sprenger and Mads Dam. On the structure of inductive reasoning: Circular and tree-shaped proofs in the μ-calculus. In Andrew D. Gordon, editor, Foundations of Software Science and Computational Structures, 6th International Conference, FOSSACS 2003 Held as Part of the Joint European Conference on Theory and Practice of Software, ETAPS 2003, Warsaw, Poland, April 7-11, 2003, Proceedings, volume 2620 of Lecture Notes in Computer Science, pages 425–440. Springer, 2003. doi:10.1007/3-540-36576-1_27.
  • [31] Christoph Sprenger and Mads Dam. On global induction mechanisms in a μ-calculus with explicit approximations. RAIRO Theor. Informatics Appl., 37(4):365–391, 2003. doi:10.1051/ita:2003024.
  • [32] Thomas Studer. On the proof theory of the modal mu-calculus. Stud Logica, 89(3):343–363, 2008. doi:10.1007/s11225-008-9133-6.
  • [33] Gadi Tellez and James Brotherston. Automatically verifying temporal properties of pointer programs with cyclic proof. In Leonardo de Moura, editor, Automated Deduction - CADE 26 - 26th International Conference on Automated Deduction, Gothenburg, Sweden, August 6-11, 2017, Proceedings, volume 10395 of Lecture Notes in Computer Science, pages 491–508. Springer, 2017. doi:10.1007/978-3-319-63046-5_30.
  • [34] Gadi Tellez and James Brotherston. Automatically verifying temporal properties of pointer programs with cyclic proof. J. Autom. Reason., 64(3):555–578, 2020. doi:10.1007/s10817-019-09532-0.
  • [35] Sergei Tupailo. On the intuitionistic strength of monotone inductive definitions. J. Symb. Log., 69(3):790–798, 2004. doi:10.2178/jsl/1096901767.