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(1)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

2-species exclusion processes and combinatorial algebras

Sylvie Corteel Arthur Nunge

IRIF, LIGM

March 2017

(2)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Non commutative symmetric functions

The algebra of noncommutative symmetric functionsSymis an algebra generalizing the symmetric functions. Its component of degreenhas dimention 2n−1. One can index its bases by compositions.

A composition of sizenis a sequence of integersI= (i1,i2, . . . ,ir) of sumn. Complete basis (analog ofhλ)

For alln, define

Sn= X

1≤j1≤j2≤···≤jn

aj1aj2· · ·ajn.

For any compositionI= (i1,i2, . . . ,ir),

SI=Si1Si2· · ·Sir.

For example,S2(a1,a2,a3) =a21+a1a2+a1a3+a22+a2a3+a23.

(3)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Non commutative symmetric functions

The algebra of noncommutative symmetric functionsSymis an algebra generalizing the symmetric functions. Its component of degreenhas dimention 2n−1. One can index its bases by compositions.

A composition of sizenis a sequence of integersI= (i1,i2, . . . ,ir) of sumn.

Complete basis (analog ofhλ) For alln, define

Sn= X

1≤j1≤j2≤···≤jn

aj1aj2· · ·ajn.

For any compositionI= (i1,i2, . . . ,ir),

SI=Si1Si2· · ·Sir.

For example,S2(a1,a2,a3) =a21+a1a2+a1a3+a22+a2a3+a23.

(4)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Non commutative symmetric functions

The algebra of noncommutative symmetric functionsSymis an algebra generalizing the symmetric functions. Its component of degreenhas dimention 2n−1. One can index its bases by compositions.

A composition of sizenis a sequence of integersI= (i1,i2, . . . ,ir) of sumn.

Complete basis (analog ofhλ) For alln, define

Sn= X

1≤j1≤j2≤···≤jn

aj1aj2· · ·ajn.

For any compositionI= (i1,i2, . . . ,ir),

SI=Si1Si2· · ·Sir.

For example,S2(a1,a2,a3) =a21+a1a2+a1a3+a22+a2a3+a23.

(5)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Non commutative symmetric functions

The algebra of noncommutative symmetric functionsSymis an algebra generalizing the symmetric functions. Its component of degreenhas dimention 2n−1. One can index its bases by compositions.

A composition of sizenis a sequence of integersI= (i1,i2, . . . ,ir) of sumn.

Complete basis (analog ofhλ) For alln, define

Sn= X

1≤j1≤j2≤···≤jn

aj1aj2· · ·ajn.

For any compositionI= (i1,i2, . . . ,ir),

SI=Si1Si2· · ·Sir.

For example,S2(a1,a2,a3) =a21+a1a2+a1a3+a22+a2a3+a23.

(6)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Non commutative symmetric functions

The algebra of noncommutative symmetric functionsSymis an algebra generalizing the symmetric functions. Its component of degreenhas dimention 2n−1. One can index its bases by compositions.

A composition of sizenis a sequence of integersI= (i1,i2, . . . ,ir) of sumn.

Complete basis (analog ofhλ) For alln, define

Sn= X

1≤j1≤j2≤···≤jn

aj1aj2· · ·ajn.

For any compositionI= (i1,i2, . . . ,ir),

SI=Si1Si2· · ·Sir.

For example,S2(a1,a2,a3) =a21+a1a2+a1a3+a22+a2a3+a23.

(7)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Ribbon basis

RI=X

JI

(−1)l(J)−l(I)SJ.

For example,R221=S221−S41−S23+S5.

Polynomial realization

RI = X

Des(w)=I

w. For example,R221(a1,a2) =a1a2a1a2a1+a2a2a1a2a1.

(8)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Ribbon basis

RI=X

JI

(−1)l(J)−l(I)SJ.

For example,R221=S221−S41−S23+S5. Polynomial realization

RI = X

Des(w)=I

w. For example,R221(a1,a2) =a1a2a1a2a1+a2a2a1a2a1.

(9)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Tevlin’s bases

In 2007 L. Tevlin defined the monomial (MI) and fundamental (LI) that are analog of the monomial basis and elementary basis ofSym. They both have binomial structure coefficients.

Transition matrices

The transition matrices between the ribbon basis and the fundamental basis of size 3 and 4 are:

M3=

1 . . .

. 2 1 .

. . 1 .

. . . 1

M4=

1 . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . 2 1 .

. . . 1 .

. . . 1

(10)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Tevlin’s bases

In 2007 L. Tevlin defined the monomial (MI) and fundamental (LI) that are analog of the monomial basis and elementary basis ofSym. They both have binomial structure coefficients.

Transition matrices

The transition matrices between the ribbon basis and the fundamental basis of size 3 and 4 are:

M3=

1 . . .

. 2 1 .

. . 1 .

. . . 1

M4=

1 . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . 2 1 .

. . . 1 .

. . . 1

(11)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ= 25783641

soRec(25783641) = .

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ= 25783641, GC(σ) = .

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

(12)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ=25783641, the recoils are{1}

soRec(25783641) = .

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ= 25783641, GC(σ) = .

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

(13)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ=25783641, the recoils are{1}

soRec(25783641) = .

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ= 25783641, GC(σ) = .

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

(14)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ= 25783641, the recoils are{1}

soRec(25783641) = .

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ= 25783641, GC(σ) = .

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

(15)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ= 25783641, the recoils are{1,4}

soRec(25783641) = .

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ= 25783641, GC(σ) = .

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

(16)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ= 25783641, the recoils are{1,4}

soRec(25783641) = .

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ= 25783641, GC(σ) = .

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

(17)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ= 25783641, the recoils are{1,4,6}

soRec(25783641) = .

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ= 25783641, GC(σ) = .

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

(18)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ= 25783641, the recoils are{1,4,6}

soRec(25783641) = .

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ= 25783641, GC(σ) = .

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

(19)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ= 25783641, the recoils are{1,4,6}soRec(25783641) =1.

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ= 25783641, GC(σ) = .

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

(20)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ= 25783641, the recoils are{1,4,6}soRec(25783641) = 13.

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ= 25783641, GC(σ) = .

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

(21)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ= 25783641, the recoils are{1,4,6}soRec(25783641) = 132.

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ= 25783641, GC(σ) = .

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

(22)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ= 25783641, the recoils are{1,4,6}soRec(25783641) = 1322.

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ= 25783641, GC(σ) = .

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

(23)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ= 25783641, the recoils are{1,4,6}soRec(25783641) = 132.

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ= 25783641, GC(σ) = .

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

(24)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ= 25783641, the recoils are{1,4,6}soRec(25783641) = 132.

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ=25783641, GC(σ) = .

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

(25)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ= 25783641, the recoils are{1,4,6}soRec(25783641) = 132.

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ= 25783641, GC(σ) = .

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

(26)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ= 25783641, the recoils are{1,4,6}soRec(25783641) = 132.

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ= 25783641, GC(σ) =3.

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

(27)

Introduction Combinatorics of the 2-ASEP Generalization ofSym Conclusion and perspectives

Statistics on permutations

Rec(σ) is the composition associated with the values of recoils (i.e., the valuesksuch thatk+ 1 is on the left).

Forσ= 25783641, the recoils are{1,4,6}soRec(25783641) = 132.

GC(σ) is the composition associated with the values of descents (i.e., the valuesk=σi such thatσi > σi+1) minus one.

Forσ= 25783641, GC(σ) = 3.

Combinatorial interpretation (F. Hivert, J.-C. Novelli, L. Tevlin, J.-Y. Thibon, 2009)

1 . . . . . . .

. 3 2 . 1 1 . .

. . 2 . 1 . . .

. . 1 3 . 2 1 .

. . . . 1 . . .

. . . . . 2 1 .

. . . . . . 1 .

. . . . . . . 1

GC\Rec 4 31 22 211 13 121 112 1111

4 1234

31 1243,41231423 13423412 2341 2413

22 13243124 2314

211 3142 1432,43124132 24314231 3241

13 2134

121 21434213 3421

112 3214

1111 4321

参照

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A lemma of considerable generality is proved from which one can obtain inequali- ties of Popoviciu’s type involving norms in a Banach space and Gram determinants.. Key words

On the other hand, from physical arguments, it is expected that asymptotically in time the concentration approach certain values of the minimizers of the function f appearing in

Here we continue this line of research and study a quasistatic frictionless contact problem for an electro-viscoelastic material, in the framework of the MTCM, when the foundation

de la CAL, Using stochastic processes for studying Bernstein-type operators, Proceedings of the Second International Conference in Functional Analysis and Approximation The-