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Free-cut elimination in linear logic and an application to a feasible arithmetic Anupam Das Patrick Baillot LIP, Universit e de Lyon, CNRS, ENS de Lyon, INRIA, Universit e Claude-Bernard Lyon 1, Milyon 6 th October, 2016 Bologne ELICA


  1. Free-cut elimination in linear logic and an application to a feasible arithmetic Anupam Das Patrick Baillot LIP, Universit´ e de Lyon, CNRS, ENS de Lyon, INRIA, Universit´ e Claude-Bernard Lyon 1, Milyon 6 th October, 2016 Bologne ELICA meeting 1 / 20

  2. Outline Introduction Normal forms in first-order linear logic An arithmetic in linear logic Bellantoni-Cook programs and the WFM for I Σ N + 1 Conclusions 2 / 20

  3. Implicit computational complexity (ICC) 3 / 20

  4. Implicit computational complexity (ICC) In a nutshell: ICC studies correspondences between features of logic and complexity classes 3 / 20

  5. Implicit computational complexity (ICC) In a nutshell: ICC studies correspondences between features of logic and complexity classes Proof-theoretic approach For a logic or theory, ‘representable’ functions = given complexity class where representability can mean definability, typability etc. 3 / 20

  6. Implicit computational complexity (ICC) In a nutshell: ICC studies correspondences between features of logic and complexity classes Proof-theoretic approach For a logic or theory, ‘representable’ functions = given complexity class where representability can mean definability, typability etc. We distinguish the following two methodologies: 1 Theories whose definable functions = given complexity class. 2 Logics that type terms with normalisation complexity of a given class. 3 / 20

  7. Implicit computational complexity (ICC) In a nutshell: ICC studies correspondences between features of logic and complexity classes Proof-theoretic approach For a logic or theory, ‘representable’ functions = given complexity class where representability can mean definability, typability etc. We distinguish the following two methodologies: 1 Theories whose definable functions = given complexity class. 2 Logics that type terms with normalisation complexity of a given class. This work is about the first methodology. 3 / 20

  8. Provably convergent functions Correspondence between a theory T and a class C : T ⊢ ∀ x . ∃ y . A ( x , y ) ⇔ N | = ∀ x . A ( x , f ( x )) for some f ∈ C 4 / 20

  9. Provably convergent functions Correspondence between a theory T and a class C : T ⊢ ∀ x . ∃ y . A ( x , y ) ⇔ N | = ∀ x . A ( x , f ( x )) for some f ∈ C For example: Theorem (Parsons ’68, Mints ’73, Buss ’95) I Σ 1 proves the totality of precisely the primitive recursive functions. 4 / 20

  10. Provably convergent functions Correspondence between a theory T and a class C : T ⊢ ∀ x . ∃ y . A ( x , y ) ⇔ N | = ∀ x . A ( x , f ( x )) for some f ∈ C For example: Theorem (Parsons ’68, Mints ’73, Buss ’95) I Σ 1 proves the totality of precisely the primitive recursive functions. Parsons’ proof. • Via a Dialectica-style functional interpretation. • Extracted programs: higher-order variant of primitive recursive functions. 4 / 20

  11. Provably convergent functions Correspondence between a theory T and a class C : T ⊢ ∀ x . ∃ y . A ( x , y ) ⇔ N | = ∀ x . A ( x , f ( x )) for some f ∈ C For example: Theorem (Parsons ’68, Mints ’73, Buss ’95) I Σ 1 proves the totality of precisely the primitive recursive functions. Parsons’ proof. • Via a Dialectica-style functional interpretation. • Extracted programs: higher-order variant of primitive recursive functions. Buss’ and Mints’ proof. • Via the witness function method. • Extracted programs: regular primitive recursive functions of ground type. 4 / 20

  12. The witness function method (WFM) The idea • A formal witness predicate over N for each ‘tame’ formula. • Arithmetic proofs � functions from witnesses to witnesses: � witnesses � witnesses � � f π : of � Γ of � ∆ � → π Γ ⊢ ∆ 5 / 20

  13. The witness function method (WFM) The idea • A formal witness predicate over N for each ‘tame’ formula. • Arithmetic proofs � functions from witnesses to witnesses: � witnesses � witnesses � � f π : of � Γ of � ∆ � → π Γ ⊢ ∆ Crucial points • π free-cut free: tames the complexity of formulae; no bad ∀ . 5 / 20

  14. The witness function method (WFM) The idea • A formal witness predicate over N for each ‘tame’ formula. • Arithmetic proofs � functions from witnesses to witnesses: � witnesses � witnesses � � f π : of � Γ of � ∆ � → π Γ ⊢ ∆ Crucial points • π free-cut free: tames the complexity of formulae; no bad ∀ . • De Morgan normal form: only functions at ground type, i.e. N k → N . 5 / 20

  15. The witness function method (WFM) The idea • A formal witness predicate over N for each ‘tame’ formula. • Arithmetic proofs � functions from witnesses to witnesses: � witnesses � witnesses � � f π : of � Γ of � ∆ � → π Γ ⊢ ∆ Crucial points • π free-cut free: tames the complexity of formulae; no bad ∀ . • De Morgan normal form: only functions at ground type, i.e. N k → N . • Right-contraction: tests the witness predicate (should be decidable). 5 / 20

  16. Context and motivation Free-cut elimination • Used in various forms by Gentzen, Parikh, Paris & Wilkie, Cook, Kraj´ ıcek,... • First presented for general fragments of PA by Takeuti. • Further generalised by Buss and others. 6 / 20

  17. Context and motivation Free-cut elimination • Used in various forms by Gentzen, Parikh, Paris & Wilkie, Cook, Kraj´ ıcek,... • First presented for general fragments of PA by Takeuti. • Further generalised by Buss and others. Witness function method • Due to Buss and Mints. • � bounded arithmetic. Theories for NC i , AC i , P , PH ,... • The best method available to delineate hierarchies of classical theories. 6 / 20

  18. Context and motivation Free-cut elimination • Used in various forms by Gentzen, Parikh, Paris & Wilkie, Cook, Kraj´ ıcek,... • First presented for general fragments of PA by Takeuti. • Further generalised by Buss and others. Witness function method • Due to Buss and Mints. • � bounded arithmetic. Theories for NC i , AC i , P , PH ,... • The best method available to delineate hierarchies of classical theories. Question Can WFM be useful for characterising complexity classes via linear logic? 6 / 20

  19. Outline Introduction Normal forms in first-order linear logic An arithmetic in linear logic Bellantoni-Cook programs and the WFM for I Σ N + 1 Conclusions 7 / 20

  20. Linear logic (LL) 8 / 20

  21. Linear logic (LL) • LL is a substructural logic: A ` A � A A � A ` B 8 / 20

  22. Linear logic (LL) • LL is a substructural logic: A ` A � A A � A ` B • It distinguishes multiplicative and additive rules by separate connectives: Γ , A ∆ , B Γ , A Γ , B Γ , ∆ , A ⊗ B Γ , A & B 8 / 20

  23. Linear logic (LL) • LL is a substructural logic: A ` A � A A � A ` B • It distinguishes multiplicative and additive rules by separate connectives: Γ , A ∆ , B Γ , A Γ , B Γ , ∆ , A ⊗ B Γ , A & B • Controlled access to structural rules via modalities: ! A ⊢ ! A ⊗ ! A 8 / 20

  24. Linear logic (LL) • LL is a substructural logic: A ` A � A A � A ` B • It distinguishes multiplicative and additive rules by separate connectives: Γ , A ∆ , B Γ , A Γ , B Γ , ∆ , A ⊗ B Γ , A & B • Controlled access to structural rules via modalities: ! A ⊢ ! A ⊗ ! A (otherwise ! behaves just like � in S4 ) 8 / 20

  25. Linear logic (LL) • LL is a substructural logic: A ` A � A A � A ` B • It distinguishes multiplicative and additive rules by separate connectives: Γ , A ∆ , B Γ , A Γ , B Γ , ∆ , A ⊗ B Γ , A & B • Controlled access to structural rules via modalities: ! A ⊢ ! A ⊗ ! A (otherwise ! behaves just like � in S4 ) • De Morgan duality is everywhere! 8 / 20

  26. Free-cut elimination in linear logic 9 / 20

  27. Free-cut elimination in linear logic A nonlogical rule has the following format: { !Γ , Σ i ⊢ ∆ i , ?Π } i ∈I !Γ , Σ ⊢ ∆ , ?Π The formulae in Σ and ∆ are considered principal. 9 / 20

  28. Free-cut elimination in linear logic A nonlogical rule has the following format: { !Γ , Σ i ⊢ ∆ i , ?Π } i ∈I !Γ , Σ ⊢ ∆ , ?Π The formulae in Σ and ∆ are considered principal. A cut step is anchored if: • its cut-formulae are (almost) principal on both sides. • on at least one side it is (almost) principal for a nonlogical step. 9 / 20

  29. Free-cut elimination in linear logic A nonlogical rule has the following format: { !Γ , Σ i ⊢ ∆ i , ?Π } i ∈I !Γ , Σ ⊢ ∆ , ?Π The formulae in Σ and ∆ are considered principal. A cut step is anchored if: • its cut-formulae are (almost) principal on both sides. • on at least one side it is (almost) principal for a nonlogical step. Theorem Any linear logic proof can be transformed into one where all cuts are anchored. 9 / 20

  30. Free-cut elimination in linear logic A nonlogical rule has the following format: { !Γ , Σ i ⊢ ∆ i , ?Π } i ∈I !Γ , Σ ⊢ ∆ , ?Π The formulae in Σ and ∆ are considered principal. A cut step is anchored if: • its cut-formulae are (almost) principal on both sides. • on at least one side it is (almost) principal for a nonlogical step. Theorem Any linear logic proof can be transformed into one where all cuts are anchored. • Proof similar to usual cut-elimination arguments. • Special cases due to Lincoln et al., Baelde & Miller,... 9 / 20

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