• 検索結果がありません。

March2017 SylvieCorteelArthurNunge 2-speciesexclusionprocessesandcombinatorialalgebras

N/A
N/A
Protected

Academic year: 2022

シェア "March2017 SylvieCorteelArthurNunge 2-speciesexclusionprocessesandcombinatorialalgebras"

Copied!
75
0
0

読み込み中.... (全文を見る)

全文

(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

関連したドキュメント

Nambu, Three-Triplet Model with Double SU(3) Symmetry, Physical Review, vol.. [Yu]H.Yukawa, On the interaction of elementary

modeling tool has been developed that comprises simple eddy viscosity concept without any

We also prove interface tightness for a long range swapping voter model, which has a mixture of long range voter model and exclusion process dynamics.. 1 Introduction and

Fig.  1  Measurement devices used and experimental procedure a hygro-thermometer Model CTH-1100; b Group I, simple moisture exclusion using cotton rolls; c Group II,

Boothroyd, “A Simple two-dimensional model for IGFET operation in the saturation region,” IEEE Transaction on Electron Devices, vol.. Al., “Threshold voltage

In the standard model of elementary particle physics, the elementary particles in the three generations (up-down, strange-charmed, top-bottom) of elementary particles correpond

The path difference in the asymmetric reflection appears to be “ d ( sin α + sin β ) ”, because the reflection point O’ on the second lattice plane is located right below

In this research, synchronization phenomena observed from simple chaotic circuits with asymmetric coupling by nonlinear mutual inductors are investigated2.