Cyclic Proof Theory of Generalised Inductive Definitions
Abstract
We study cyclic proof systems for , an extension of Peano arithmetic by generalised inductive definitions that is arithmetically equivalent to the (impredicative) subsystem of second-order arithmetic by Möllerfeld.
The main result of this paper is that cyclic and inductive 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 -calculus, whose stronger validity condition allows for a simpler proof of soundness. We then formalise this argument within , 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 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 systemsCopyright and License:
2012 ACM Subject Classification:
Theory of computation Proof theory ; Theory of computation Higher order logicAcknowledgements:
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 KönigSeries and Publisher:
Leibniz International Proceedings in Informatics, Schloss Dagstuhl – Leibniz-Zentrum für Informatik
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 -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 -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 () [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 .
Berardi and Tatsuta’s result was implicitly proven by Simpson, who independently showed that the cyclic variant of Peano Arithmetic () is equivalent to [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 is strictly simpler than . Then, in joint work with Melgaard [16], he studied the extension of with arithmetic (finitely iterated) inductive definitions () and showed that this system and its cyclic version 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 , an extension of by least and greatest fixed points of formulas (see [12]). Proof-theoretically, was first studied by Möllerfeld [23], inspired by Lubarsky’s work on “-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 far exceeds that of . Indeed, Möllerfeld proved that has the same proof-theoretic strength as , an (impredicative) subsystem of second-order arithmetic where the comprehension scheme is restricted to -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 () is arithmetically equivalent to .
Our argument is summarized in Figure 1. We first introduce a reset system for inspired by [1], called . Compared to , 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 , 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 over [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 -calculi.
Outline of the paper.
This paper is structured as follows. In Section 2 we recall the syntax and the semantics of , as well as its sequent calculus system. In Section 3 we define the cyclic proof system and show that the latter can simulate (Theorem 15). Section 4 introduces the reset system and its soundness theorem (Theorem 21), while Section 5 shows that cyclic progressing proofs of can be translated into cyclic reset proofs (Theorem 25). Finally, Section 6 formalises the soundness argument for of Section 4 within (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].
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 that is prefix-closed, i.e., implies for all . Elements of the tree are called nodes, which are denoted by . A successor of a node is a node for some . is the root of and a node with no successor is a leaf. A branch of is a family () such that and for some .
Definition 3 (Rules and (co)derivations).
We consider (inference) rules of the form with , where are called premises and is called conclusion. A coderivation over a set of rules is a pair where is a tree called the support of and is a label function such that, whenever is a rule with premises , then has precisely successors and is a rule with conclusion for all . A coderivation with finite support is called a derivation. The conclusion of a (co)derivation is the conclusion of the rule . Given some , we write for the (co)derivation with support given by . We call such a sub-(co)derivation of . If 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 and its semantics111This theory is often called -calculus in the literature (see, e.g., [17, 23]). To date, however, -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 to stress its arithmetic component.. The theory can be constructed as a formal extension of second-order arithmetic by defining least fixed points 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 , written , is an extension of the language of first-order arithmetic (with inequality) where, as usual, is a constant symbol (i.e. a -ary function symbol), is a unary function symbol, and are binary function symbols, and is a binary relation symbol. Specifically, the language of is obtained from 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 etc, and fixed point binders and .
Definition 4 (Terms and (pre-)formulas).
The (number) terms, the pre-set terms and the pre-formulas of are respectively simultaneously generated by the following grammars:
The notions of free first-order variable and free second-order variable are standard. Notice that and bind the free (individual and set) variables and in . We denote with , , and the set of free first-order variable in and and the set of free second-order variable in , respectively. We will use the standard notation for (capture-avoiding) first-order and second-order substitution , , and .
Pre-formulas of the form , , , , and are called atomic. We define negation as a shorthand using De Morgan equations, e.g., , where is shorthand for . Note that .
Given a set variable , we say that occurs positively in a pre-formula if contains no pre-formulas of the form for any term . We say is a formula if, for any sub-pre-formula in of the form or , occurs positively in . We say a pre-set-term is a set-term if is a formula for some .
From now on, we will work with formulas where every second-order variable is bound. We adopt the standard abbreviations for connectives, such as , and . Finally, we will write for .
Example 5 (Some fixed point formulas).
Consider the following formulas of :
-
-
.
where the term encodes the empty list, and the term encodes the operation of appending (the encoding of) an element to (the encoding of) a list 333With a small abuse of notation we will often not distinguish between lists and numbers coding lists in . Moreover, since the append operation is primitive recursive, we will treat as a binary function symbol, so will be considered a term of .. By definition, contains the set terms , , and . As we will also see later, the latter formula illustrates a key aspect of , 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 , where and are interpreted as least and greatest fixed points of the (parametrised) operator induced by .
To this end, we recall (a version of) the Knaster-Tarski theorem on power sets:
Proposition 6 (Knaster-Tarski).
Let be a set and let be monotone (w.r.t. ). Then has a least fixed point and a greatest fixed point . Moreover:
-
and
-
and
where the -approximants and are inductively defined by and . Notice that and .
Definition 7 (Standard model and satisfaction).
The standard model for is the -structure , whose domain is , , is the successor, is the addition, is the multiplication, and is the natural (strict) order on natural numbers.
An assignment is a map associating an element (resp., a set ) with every first-order variable (resp., set variable ). We denote with (resp., ) the assignment that sends to (resp., to ) and otherwise preserves .
The extension of assignments to terms , written , and the satisfaction relation are defined by induction in the standard way, e.g.:
where, given the monotone function , we set and (see Proposition 6). We simply write to denote when it is clear from the context.
Example 8.
Let be an assignment in . Revisiting Example 5, we have that:
where the set of lists over with length at most (resp. with finite length) is denoted (resp., ), and is the set of (the encodings of) hereditarily finite lists. Therefore, we have: , , and . Alternatively, we can see as the set of (the encodings) of rose trees, i.e., trees with unbounded (but finite) branching.
2.3 The theory
The theory over the language as presented in this paper is essentially the first-order part of Möllerfeld’s [23], which extends Peano arithmetic by the axiom schemas and defined as follows, for formulas and positive in :
and dually for . The first axiom states that is a pre-fixed point. The second axiom states that it is the least among the pre-fixed points.
We will express 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 ).
A sequent is a list of formulas. The sequent calculus for extends (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 and in Figure 2 (bottom).
referring to Figure 2, we call , , , , 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 will be considered as shorthand for . As an example, the rule 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.
Remark 10 (Post-fixed points and numerical induction).
It is easy to see that the sequent calculus system derives the axioms (-) and (-) (as well as their dual for ). On the other hand, the following derivations show that we can recover the rule (Figure 2, bottom) and that, in presence of , numeric induction and the rule are equivalent:
In the latter derivation we let . Notice that the double lines labelled with express a “functoriality” property.
In fact, the choice of 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 based on ideas from the modal -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).
Intuitively, (-)coderivations are built from the same set of rules as except that the rule replaces fixed point induction . 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 be a coderivation, and let be an infinite branch along . A trace along is a sequence of occurrences formulas such that for all , is in the conclusion of a rule , is in a premise of , and one of the following cases applies:
-
is the principal formula and with conclusion and premise
-
is the principal formula and with conclusion and premise
-
is the principal formula of and is an active formula
-
and are the -th side formulas in the context, for some (so they are equal modulo term substitution).
We say that is an immediate ancestor of if they extend to some trace . If (respectively ) for some , the rule is (respectively ) and is principal then we say (respectively ) progresses at . A trace is progressing if there is a -term such that progresses infinitely often and 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 for which each infinite branch has a progressing trace. We write for the class of cyclic progressing proofs, and if there is a cyclic progressing proof of .
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 -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 .
Now, for any infinite branch one of the following cases applies:
-
eventually loops only at : the trace alternating and formulas is progressing, and the smallest -term unfolding infinitely often is (in negative position).
-
eventually loops only at : the trace alternating and formulas is progressing, and the smallest -term unfolding infinitely often is (in negative position).
-
loops infinitely often at both and : the trace alternating and formulas along , and and formulas along , is progressing, and the smallest -term unfolding infinitely often is (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 subsumes by a standard argument:
Theorem 15 (Induction to cycles).
If then .
Proof sketch.
By induction on the structure of proofs. The critical step is , for which we do not have a corresponding rule in . We simulate this rule by the following:
where the rule steps marked can be defined by induction on the structure of . 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
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 , called , inspired by the annotated systems for first-order -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 , where is an ordinal variable, expresses syntactically an ordinal approximant of (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 can then be established by defining a translation of progressing proofs of into reset proofs.
4.1 Syntax and semantics of
The language of , written , is a three-sorted language obtained by augmenting by a countable set of ordinal variables ranging over . We extend Definition 4 to include new set terms and for any ordinal variable .
Concerning semantics of , the standard model is defined as in Definition 7, while assignments are extended to associate with every ordinal variable an ordinal . Satisfaction relation is then extended to the clauses and as follows:
All the remaining definitions and conventions smoothly adapt to the new setting.
derives extended sequents, i.e., sequents equipped with conditions on ordinal variables called constraints. These are pairs where is a finite set of ordinal variables and is a strict partial order such that, for each , the set is linearly ordered by . Intuitively, the condition is interpreted as the assumption that is “smaller” than . Notice that can be seen as a collection of trees with the set of vertices, and the descendant relation is the converse of the order : the children of are then where and for no do we have .
We will sometimes write instead of . Also, we write as shorthand for , and with we denote the empty constraint. We set or .
Definition 16 (Extended sequents).
An (annotated) sequent is a finite list of formulas over . An extended sequent is an expression where is an annotated sequent and is a constraint such that contains all ordinal variables in . Given an annotated sequent , we denote with the sequent without ordinal variables.
The standard interpretation for can be generalised to extended sequents in the obvious way. Given a constraint , and assignment , we define iff implies for all . An extended sequent is satisfied in if, for all assignments for , implies .
4.2 Annotated coderivations and reset proofs
For the purpose of presenting the inference rules we require three operations on constraints:
where . The top left operation adds as a fresh ordinal variable, which becomes the root of a new tree in . In the bottom left operation is added as a fresh child of the ordinal variable . Note that these operations preserve the condition that the set is linearly ordered by for every , and so the tree structure is also preserved. The right operation restricts a constraint set to a subset of ordinal variables.
The rules of our reset system are in Figure 3. They essentially “lift” the rules of to extended sequents, replacing with decorated versions ( and ) internalising fixed points approximants (see Proposition 6), and with the rule removing a set from the constraint. Validity condition will be defined via so-called reset rule (), a special case of , where is the set of the children of in and must be non-empty, and does not occur in . Translating from to requires another special case of , a novelty of this paper called the pruning rule, where is the set of all ordinal variables that have no descendants occurring in (i.e., ), 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 be an annotated coderivation, and let be an infinite branch of . We say that is a stable variable in if there is such that , for every . We say that is a reset variable in if there are infinitely many occurrences of in . We say that is a reset proof if every infinite branch has a stable reset variable. We denote with the class of cyclic reset proofs444 is based on the reset system for the -calculus from [31], and later refined in [1], but differs in many respects. Concerning syntax, is endowed with the language of 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 .
It has only one infinite branch (looping at ) that unfolds infinitely often (annotations of) the formula . The branch contains a stable reset variable . 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 of with conclusion , if then there is a premise of and assignment s.t.
-
1.
and
-
2.
for any we have . If moreover, then .
Theorem 21 (Soundness).
For any reset proof with conclusion , .
Proof.
Assume by contradiction that is a reset proof with conclusion s.t. for some assignment . By Lemma 20 we can construct an infinite branch of and a sequence of assignments such that , and for all :
-
1.
-
2.
for any we have
-
3.
if and is the conclusion of a reset rule then .
Since is a reset proof, there will be some stable reset variable along this branch, and so for some we have for every . Consider the ordinal sequence . By construction we have for every and at every reset step. Since 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 are also provable in . To this end, we define a (parametrised) translation from (-)coderivations with conclusion into annotated coderivations with conclusion , where each “decorates” occurrences of in with ordinal variables. Specifically, the translation corecursively (i.e., bottom-up) turns sequents of 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 .
Definition 22 (Ordinal assignments).
Let be a formula of and . A list over is called an (-)ordinal assignment for , written (sometimes ), if the length of is equal to the number of occurrences of in . We define to be the formula obtained by replacing the -th occurrence of (from left) with if , and with itself otherwise. We extend ordinal assignments to sequents by setting if for all , and .
Example 23.
Consider , and let . Then, is an ordinal assignment for , and .
Definition 24 (Translation).
Let be a -coderivation with conclusion , and let be a constraint such that . We define coinductively the translation mapping into an annotated coderivation with conclusion . We consider only the most relevant case where the coderivation ends with a step, with . If then:
The case is similar.
Theorem 25.
If then .
Proof idea.
Let be a coderivation with conclusion . Let be an infinite branch in . There exists a unique infinite branch of that translates into . By hypothesis, has a progressing trace for some . Let be the smallest infinitely progressing set-term in . Recalling notation (Definition 16), induces a trace of such that enumerates (possibly with repetitions). Moreover, by progressivity of , there is and a sequence of ordinal variables such that, for all :
-
(i)
occurs in .
-
(ii)
Either or is the child of in (i.e., in any case, ).
-
(iii)
There exists s.t. is the child of in .
Let us show that has a stable variable. For set . This is a finite linear order (non-empty by i), and we pick a maximal element (which is also maximal in ). By ii if then unless is removed by a reset or a pruning rule. But cannot be pruned because of i. Also, no -rule or -rule can introduce a parent of , so cannot be removed by a reset rule either.
Now, since contains a stable variable , it also contains a minimal one . Since is applied infinitely often in , the reset and pruning rules are applied infinitely often along (see Definition 24, case ). From this fact, using iii, we can show that is applied infinitely often along .
By inspecting the translation it is not too hard to see that is cyclic when is.
Soundness for progressing proofs follows as a straightforward corollary:
Corollary 26 (Soundness for ).
Let with conclusion . Then, .
Proof.
By Theorem 25 we have that is a cyclic reset proof of . By Theorem 21 we have , and so .
6 Formalising the soundness argument in
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 (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 is a two-sorted extension of basic arithmetic by:
-
Arithmetical comprehension. for each arithmetical formula .
-
Set induction.
From here, is the extension of by the comprehension schema for all formulas. We shall freely use established principles of (as seen, e.g., in [29]) such as -comprehension, -choice and -dependent choice. The term will denote formulas provably equivalent under to a formula of the form with arithmetical, and similarly for and . 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 we can consider as a function by setting .
For the formalised soundness argument we will need that formulas are closed under positive arithmetical combinations (over ).
Theorem 27.
Let be a positive arithmetical combination of . If (resp., ) then (resp., ).
6.2 Countable orders in
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 where and are sets, the latter construed as ranging over pairs. We shall write , etc. to range over countable binary relations. If we may write , and similarly for . We may also write instead of . We write for the statement that is a well-order.
Following Simpson in [Sim99], given , we write if there is an order-isomorphism from onto a proper initial segment of , if and are order-isomorphic and if . We have the following basic facts about comparison:
Proposition 28.
proves that:
-
1.
, and are all .
-
2.
is a total linear order
-
3.
is well-founded:
6.3 Knaster-Tarski Theorem and approximants
We have two ways of interpreting the - and -binders in second-order arithmetic. First:
| (1) | ||||
| (2) |
Another way of interpreting and is through approximants:
Definition 29 (Approximants).
We write:
For the remainder of this section, assume and that is positive in . The results of this section are all proven in [12] for -terms and the dual properties for -terms can then be obtained using the fact and similar for and .
The first proposition shows that has access to the recursive characterizations of -approximants as well as the fact that is a fixed points.
Proposition 30 (Recursion and Knaster-Tarski).
proves
In [12] it is shown that if then and are in . Using this fact and standard prenexing we see that . Also, by standard prenexing and -choice we see that . In [12] it is also shown that the two interpretations of and are provably equivalent in , i.e. and . Putting all this together we get that for :
Corollary 31.
, , , , and are all .
6.4 Interpreting and in
We may define an interpretation from to defined by and . Similarly, we can define an interpretation from to by , and . Writing the two different interpretations of the same is justified by [12]. By Corollary 31 and Theorem 27 we have:
Theorem 32.
If is a formula of then is .
Theorem 32 allows to readily verify the axioms of using -comprehension, and so can be considered a fragment of . In fact, by a result of Möllerfeld’s, not only extends but does so conservatively.
Theorem 33 (Implied by [23]).
is arithmetically conservative over .
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 satisfaction in
We will employ standard metamathematical notations and conventions for coding, e.g. we write for the Gödel code of an expression . 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 proof containing only finitely many ordinal variables and set-terms.
We let where is a formula and so . There are two main properties that we need our partial satisfaction predicate to satisfy. The first is reflection.
Theorem 34 (Reflection).
Let be a subformula of a formula in . Then proves .
Secondly, our partial satisfaction predicate needs to satisfy the proper inductive characterization of satisfaction e.g. and
Theorem 35 (Formalised satisfaction).
proves that satisfies the inductive characterization of satisfaction for every connective.
For the formalized soundness proof we also need to extend our satisfaction predicate so that it works with constraints and extended sequents. This is done in the expected way.
6.6 Formalizing soundness for
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 it is crucial that “knows” that the proof satisfies the reset condition.
Lemma 36.
Let be a proof. Then proves that for all branches in there exists a stable reset variable along .
Proof.
The idea is standard and is covered in detail in [14]. It is provable in (and much weaker theories) that for a derivation , satisfying the reset condition is equivalent to language inclusion of two Büchi automata which can both be computed from . Since by [19] language inclusion for Büchi automata is decidable it follows that, if satisfies the reset condition, then proves that fact.
Theorem 37 (Formalising soundness).
Let be a proof with conclusion . Then
Proof.
Assume for contradiction that . 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 we define the following formulas:
Note that both and are arithmetical in , and , and so they are by Theorem 27. Let . The formal equivalent of Lemma 20 is:
| (3) |
To see that this can be proven within , first note that for with we just let , so the hard case is when 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 -rule, Proposition 30(2) for the -rule and Proposition 28 for the reset rule. More details can be found in the appendix.
Since and are we can apply -dependent choice555( to (3) to get a suitable branch. By -dependent choice there exists s.t.
Note that if then and so , which means by an easy induction that . By comprehension we define and so is a branch witnessing falsity satisfying .
Now we apply Lemma 36 to get a stable reset variable such that, for some and all , occurs in , where . Finally, using this stable reset variable we want to show the existence of an infinitely descending ordinal sequence. By comprehension we get s.t. Then, since we see that 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 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.
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