signature based criteria for computing weak gr bner bases
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Signature-based criteria for computing weak Grbner bases over PIDs Maria Francis 1,2 , Thibaut Verron 1 1. Institute for Algebra, Johannes Kepler University, Linz, Austria 2. Indian Institute of Technology, Hyderabad, India Special session


  1. Signature-based criteria for computing weak Gröbner bases over PIDs Maria Francis 1,2 , Thibaut Verron 1 1. Institute for Algebra, Johannes Kepler University, Linz, Austria 2. Indian Institute of Technology, Hyderabad, India Special session “Algorithms for zero-dimensional ideals” , ACA 2018, 20 June 2018, Santiago de Compostela 1

  2. Introduction and notations Gröbner bases ◮ Valuable tool for many questions related to polynomial equations (resolution, elimination, dimension of the solutions...) ◮ Classically used for polynomials over fields ◮ Some applications with coefficients in general rings (elimination, combinatorics...) Definition (Leading term, monomial, coefficient) R ring, A = R [ X 1 , . . . , X n ] with a monomial order < , f = � a i X b i ◮ Leading term LT ( f ) = a i X b i with X b i > X b j if j � = i ◮ Leading monomial LM ( f ) = X b i ◮ Leading coefficient LC ( f ) = a i 2

  3. Definitions for fields For now R = K is a field. Definition (reduction) f reduces to h mod G if there exists g ∈ G and a X b such that ◮ LT ( f ) = a X b LT ( g ) ◮ h = f − a X b g By extension, f reduces to h mod G if there exists a chain of such reductions from f to h . Definition (Gröbner basis) I ⊂ A ideal, a Gröbner basis of I is a finite set G ⊂ I such that ◮ ∀ f ∈ I , f reduces to 0 mod G or equivalently ◮ � LT ( f ) : f ∈ I � = � LT ( g ) : g ∈ G � 3

  4. Buchberger’s algorithm ◮ Input: F = ( f 1 , . . . , f m ) ⊂ K [ X 1 , . . . , X n ] ◮ Output: G Gröbner basis of � F � 1. G ← { f i : i ∈ { 1 , . . . , m }} 2. P ← pairs of elements of G 3. while P is not empty do 4. Pick ( i , j ) from P 5. M ( i , j ) ← lcm ( LM ( g i ) , LM ( g j )) LM ( g i ) g i − M ( i , j ) M ( i , j ) 6. p ← S-Pol ( g i , g j ) = LM ( g j ) g j ( S -polynomial) 7. r ← Reduce ( p , G ) 8. if r � = 0 then 9. Update G and P using r 10. return G 4

  5. Signature improvements [Faugère 2002 ; Gao, Guan, Volny 2010 ; Arri, Perry 2011... Eder, Faugère 2017] ◮ Idea: keep track of the representation g = � i q i f i for g ∈ � f 1 , . . . , f m � ◮ The algorithm could keep track of the full representation... but it is expensive ◮ Instead define a signature s ( g ) of g as m � s ( g ) = LT ( q j ) e j for some representation g = q i f i , q j being the last non-zero coef. i = 1 ◮ Signatures are ordered by a X b e i < a ′ X b ′ e j ⇐ ⇒ i < j or i = j and X b < X b ′ ◮ If we never add together two elements with similar signature (regular S -polynomials) and only reduce by polynomials with smaller signature (regular reductions), then keeping track of the signature is free! LM ( g i ) g i − M ( i , j ) M ( i , j ) ◮ Example: signature of a regular S -polynomial, S-Pol ( g i , g j ) = LM ( g j ) g j : � M ( i , j ) LM ( g i ) s ( g i ) , M ( i , j ) � s ( S-Pol ( g i , g j )) = S ( i , j ) = max LM ( g j ) s ( g j ) 5

  6. Signature improvements [Faugère 2002 ; Gao, Guan, Volny 2010 ; Arri, Perry 2011... Eder, Faugère 2017] ◮ Idea: keep track of the representation g = � i q i f i for g ∈ � f 1 , . . . , f m � ◮ The algorithm could keep track of the full representation... but it is expensive ◮ Instead define a signature s ( g ) of g as m � s ( g ) = LT ( q j ) e j for some representation g = q i f i , q j being the last non-zero coef. i = 1 ◮ Signatures are ordered by a X b e i < a ′ X b ′ e j ⇐ ⇒ i < j or i = j and X b < X b ′ ◮ If we never add together two elements with similar signature (regular S -polynomials) and only reduce by polynomials with smaller signature (regular reductions), then keeping track of the signature is free! LM ( g i ) g i − M ( i , j ) M ( i , j ) ◮ Example: signature of a regular S -polynomial, S-Pol ( g i , g j ) = LM ( g j ) g j : � M ( i , j ) LM ( g i ) s ( g i ) , M ( i , j ) � s ( S-Pol ( g i , g j )) = S ( i , j ) = max LM ( g j ) s ( g j ) 5

  7. Signature improvements [Faugère 2002 ; Gao, Guan, Volny 2010 ; Arri, Perry 2011... Eder, Faugère 2017] ◮ Idea: keep track of the representation g = � i q i f i for g ∈ � f 1 , . . . , f m � ◮ The algorithm could keep track of the full representation... but it is expensive ◮ Instead define a signature s ( g ) of g as m � s ( g ) = LT ( q j ) e j for some representation g = q i f i , q j being the last non-zero coef. i = 1 ◮ Signatures are ordered by a X b e i < a ′ X b ′ e j ⇐ ⇒ i < j or i = j and X b < X b ′ ◮ If we never add together two elements with similar signature (regular S -polynomials) and only reduce by polynomials with smaller signature (regular reductions), then keeping track of the signature is free! LM ( g i ) g i − M ( i , j ) M ( i , j ) ◮ Example: signature of a regular S -polynomial, S-Pol ( g i , g j ) = LM ( g j ) g j : � M ( i , j ) LM ( g i ) s ( g i ) , M ( i , j ) � s ( S-Pol ( g i , g j )) = S ( i , j ) = max LM ( g j ) s ( g j ) 5

  8. Buchberger’s algorithm with signatures ◮ Input: F = ( f 1 , . . . , f m ) ⊂ K [ X 1 , . . . , X n ] ◮ Output: G Gröbner basis of � F � 1. G ← { f i with signature e i : i ∈ { 1 , . . . , m }} 2. P ← (regular) pairs of elements of G 3. while P is not empty do 4. Pick ( i , j ) from P with smallest signature S ( i , j ) 5. M ( i , j ) ← lcm ( LM ( g i ) , LM ( g j )) LM ( g i ) g i − M ( i , j ) M ( i , j ) 6. p ← S-Pol ( g i , g j ) = LM ( g j ) g j ( S -polynomial) 7. r ← Regular - Reduce ( p , G ) 8. if r � = 0 then 9. Update G and P using r with signature s ( r ) = S ( i , j ) 10. return G 6

  9. Features of signatures Key property Buchberger’s algorithm with signatures computes GB elements with increasing signatures. Then we can add criteria... Singular criterion: eliminate some redundant computations If s ( g ) ≃ s ( g ′ ) then afer regular reduction, LM ( g ) = LM ( g ′ ) . F5 criterion: eliminate Koszul syzygies f i f j − f j f i = 0 If s ( g ) = LT ( g ′ ) e j for some g ′ ∈ G with s ( g ′ ) = ⋆ e i with i < j , then g reduces to 0 modulo the already computed basis. 7

  10. What about signatures for rings? Main difficulty: how to order the signatures? Over fields a X b e i < a ′ X b ′ e j ⇐ ⇒ i < j or i = j and X b < X b ′ is a partial order but we can always normalize Over rings, we need to take the coefficients into account. Over Euclidean rings [Eder, Pfister, Popescu 2017] ◮ Possible to break ties with the absolute value of the coefficients ◮ Problem: signature drops = regular reductions leading to a smaller signature ◮ The algorithm can detect that it happens and serve as a preprocess ◮ Impossible to avoid signature drops? In this work ◮ We use a partial order on the signatures: don’t break the ties ◮ Advantages: no signature drops ◮ Risk: maybe we forbid too many reductions? ◮ Main result: the algorithm is correct and terminates 8

  11. What about signatures for rings? Main difficulty: how to order the signatures? Over fields a X b e i < a ′ X b ′ e j ⇐ ⇒ i < j or i = j and X b < X b ′ is a partial order but we can always normalize Over rings, we need to take the coefficients into account. Over Euclidean rings [Eder, Pfister, Popescu 2017] ◮ Possible to break ties with the absolute value of the coefficients ◮ Problem: signature drops = regular reductions leading to a smaller signature ◮ The algorithm can detect that it happens and serve as a preprocess ◮ Impossible to avoid signature drops? In this work ◮ We use a partial order on the signatures: don’t break the ties ◮ Advantages: no signature drops ◮ Risk: maybe we forbid too many reductions? ◮ Main result: the algorithm is correct and terminates 8

  12. Definitions for rings Definition (strong and weak reduction) f strongly reduces to h mod G if there exists g ∈ G and a X b such that ◮ LT ( f ) = a X b LT ( g ) ◮ h = f − a X b g f weakly reduces to h mod G if there exists { g 1 , . . . , g r } ⊂ G , a 1 X b 1 , . . . , a r X b r such that ◮ LT ( f ) = � a j X b j LT ( g j ) ◮ h = f − � a j X b j g j Definition (strong and weak Gröbner basis) I ⊂ A ideal, a strong Gröbner basis of I is a finite set G ⊂ I such that ◮ ∀ f ∈ I , f strongly reduces to 0 mod G A weak Gröbner basis of I is a finite set G ⊂ I such that ◮ � LT ( f ) : f ∈ I � = � LT ( g ) : g ∈ G � or equivalently ◮ ∀ f ∈ I , f weakly reduces to 0 mod G 9

  13. Definitions for rings Definition (strong and weak reduction) f strongly reduces to h mod G if there exists g ∈ G and a X b such that ◮ LT ( f ) = a X b LT ( g ) ◮ h = f − a X b g f weakly reduces to h mod G if there exists { g 1 , . . . , g r } ⊂ G , a 1 X b 1 , . . . , a r X b r such that ◮ LT ( f ) = � a j X b j LT ( g j ) ◮ h = f − � a j X b j g j Definition (strong and weak Gröbner basis) I ⊂ A ideal, a strong Gröbner basis of I is a finite set G ⊂ I such that ◮ ∀ f ∈ I , f strongly reduces to 0 mod G A weak Gröbner basis of I is a finite set G ⊂ I such that ◮ � LT ( f ) : f ∈ I � = � LT ( g ) : g ∈ G � or equivalently ◮ ∀ f ∈ I , f weakly reduces to 0 mod G 9

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