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WS 3: Computer Algebra and Polynomials/ 1

RICAM Special Semester on

Applications of Algebra and Number Theory Johann Radon Institute (RICAM), Nov 28, 2013

Computer Algebra, Ramanujan Congruences, and Polynomials

Peter Paule

(joint work with Cristian-Silviu Radu)

Johannes Kepler University Linz

Research Institute for Symbolic Computation (RISC)

(2)

WS 3: Computer Algebra and Polynomials/Introduction 2

Introduction

(3)

WS 3: Computer Algebra and Polynomials/Introduction 3

1 1 2 3 5

7 11 15 22 30

42 56 77 101 135

176 231 297 385 490

627 792 1002 1255 1575

1958 2436 3010 3718 4565

5604 6842 8349 10143 12310

14883 17977 21637 26015 31185 37338 44583 53174 63261 75175 89134 105558 124754 147273 173525 204226 239943 281589 329931 386155 451276 526823 614154 715220 831820 966467 1121505 1300156 1505499 1741630 2012558 2323520 2679689 3087735 3554345 4087968 4697205 5392783 6185689 7089500 8118264 9289091 10619863 12132164 13848650

(4)

WS 3: Computer Algebra and Polynomials/Introduction 4

Theorem

LetS be a compact Riemann surface and z a meromorphic function onS having npoles (incl. multiplicity). Let f be any other meromorphic function onS. Then there exist rational functionsck(x)∈C(x) such that

fn+c1(z)fn−1+· · ·+cn−1(z)f+cn(z) = 0.

(5)

WS 3: Computer Algebra and Polynomials/Introduction 5

Theorem

LetS be a compact Riemann surface and z a meromorphic function onS having npoles (incl. multiplicity). Let f be any other meromorphic function onS. Then there exist rational functionsck(x)∈C(x) such that

fn+c1(z)fn−1+· · ·+cn−1(z)f+cn(z) = 0.

Moreover, if

PoleSet(z)⊆PoleSet(f), then theck(x)are polynomials; i.e., ck(x)∈C[x].

(6)

WS 3: Computer Algebra and Polynomials/Partition Numbers 6

Partition Numbers

(7)

WS 3: Computer Algebra and Polynomials/Partition Numbers 7

Example: p(4) = 5: 4, 3 + 1, 2 + 2, 2 + 1 + 1, 1 + 1 + 1 + 1.

Theorem

(p(n))n≥0 is not holonomic.

Proof. The generating function is

X

n=0

p(n)qn =

Y

n=1

(1−qn)−1

= (1 +q1+q1+1+q1+1+1+. . .)

× (1 +q2+q2+2+q2+2+2+. . .)

× etc.

= . . .+q1+1+1q2+2· · ·+. . .

This implies non-holonomicity, because holonomic functions have only finitely many singularities.

(8)

WS 3: Computer Algebra and Polynomials/Partition Numbers 7

Example: p(4) = 5: 4, 3 + 1, 2 + 2, 2 + 1 + 1, 1 + 1 + 1 + 1.

Theorem

(p(n))n≥0 is not holonomic.

Proof. The generating function is

X

n=0

p(n)qn =

Y

n=1

(1−qn)−1

= (1 +q1+q1+1+q1+1+1+. . .)

× (1 +q2+q2+2+q2+2+2+. . .)

× etc.

= . . .+q1+1+1q2+2· · ·+. . .

This implies non-holonomicity, because holonomic functions have only finitely many singularities.

(9)

WS 3: Computer Algebra and Polynomials/Partition Numbers 8

Growth ofp(n)

Example [MacMahon 1916]:

p(200) = 3,972,999,029,388

Theorem

p(n)∼ 1 4n√

3exp π r2n

3

!

as n→ ∞.

(10)

WS 3: Computer Algebra and Polynomials/Partition Numbers 8

Growth ofp(n)

Example [MacMahon 1916]:

p(200) = 3,972,999,029,388

Theorem

p(n)∼ 1 4n√

3exp π r2n

3

!

as n→ ∞.

(11)

WS 3: Computer Algebra and Polynomials/Partition Numbers 9

Back to our table

I 34 of the 80 entries are even; 46 are odd.

I 4,996 of the first 10,000 entries are even; 5,004 are odd. Does this pattern continue?

(12)

WS 3: Computer Algebra and Polynomials/Partition Numbers 9

Back to our table

I 34 of the 80 entries are even; 46 are odd.

I 4,996 of the first 10,000 entries are even; 5,004 are odd.

Does this pattern continue?

(13)

WS 3: Computer Algebra and Polynomials/Partition Numbers 9

Back to our table

I 34 of the 80 entries are even; 46 are odd.

I 4,996 of the first 10,000 entries are even; 5,004 are odd.

Does this pattern continue?

(14)

WS 3: Computer Algebra and Polynomials/Partition Numbers 10

DEEPER INSIGHT: The Subbarao Conjecture (1966)

I Ono [1996]: Given integers 0≤B < A:

p(An+B)≡0 (mod 2) for infinitely manyn.

I Radu [2012]: Given integers 0≤B < A:

p(An+B)6≡0 (mod 2) for infinitely manyn.

Remark. Radu’s algorithmic insight enabled him to invoke a result by Deligne and Rapoport [1979]. The same applies to his proof [2012] of a conjecture of Ahlgren and Ono [2002].

(15)

WS 3: Computer Algebra and Polynomials/Partition Numbers 10

DEEPER INSIGHT: The Subbarao Conjecture (1966)

I Ono [1996]: Given integers 0≤B < A:

p(An+B)≡0 (mod 2) for infinitely manyn.

I Radu [2012]: Given integers0≤B < A:

p(An+B)6≡0 (mod 2) for infinitely manyn.

Remark. Radu’s algorithmic insight enabled him to invoke a result by Deligne and Rapoport [1979]. The same applies to his proof [2012] of a conjecture of Ahlgren and Ono [2002].

(16)

WS 3: Computer Algebra and Polynomials/Partition Numbers 10

DEEPER INSIGHT: The Subbarao Conjecture (1966)

I Ono [1996]: Given integers 0≤B < A:

p(An+B)≡0 (mod 2) for infinitely manyn.

I Radu [2012]: Given integers0≤B < A:

p(An+B)6≡0 (mod 2) for infinitely manyn.

Remark. Radu’s algorithmic insight enabled him to invoke a result by Deligne and Rapoport [1979]. The same applies to his proof [2012] of a conjecture of Ahlgren and Ono [2002].

(17)

WS 3: Computer Algebra and Polynomials/Partition Numbers 11

Ahlgren and Ono determined:

I 3,313, 3,325, and 3,362 of the first 10,000 entries are congruent respectively to 0, 1, and 2 modulo 3.

BUT:

I 3,611 (many more than the expected one-fifth) of the first 10,000 values of p(n) are divisible by 5.

WHY? Let’s look again at our table:

(18)

WS 3: Computer Algebra and Polynomials/Partition Numbers 11

Ahlgren and Ono determined:

I 3,313, 3,325, and 3,362 of the first 10,000 entries are congruent respectively to 0, 1, and 2 modulo 3.

BUT:

I 3,611 (many more than the expected one-fifth) of the first 10,000 values of p(n) are divisible by 5.

WHY? Let’s look again at our table:

(19)

WS 3: Computer Algebra and Polynomials/Partition Numbers 11

Ahlgren and Ono determined:

I 3,313, 3,325, and 3,362 of the first 10,000 entries are congruent respectively to 0, 1, and 2 modulo 3.

BUT:

I 3,611 (many more than the expected one-fifth) of the first 10,000 values of p(n) are divisible by 5.

WHY? Let’s look again at our table:

(20)

WS 3: Computer Algebra and Polynomials/Partition Numbers 12

1 1 2 3 5

7 11 15 22 30

42 56 77 101 135

176 231 297 385 490

627 792 1002 1255 1575

1958 2436 3010 3718 4565

5604 6842 8349 10143 12310

14883 17977 21637 26015 31185 37338 44583 53174 63261 75175 89134 105558 124754 147273 173525 204226 239943 281589 329931 386155 451276 526823 614154 715220 831820 966467 1121505 1300156 1505499 1741630 2012558 2323520 2679689 3087735 3554345 4087968 4697205 5392783 6185689 7089500 8118264 9289091 10619863 12132164 13848650

(21)

WS 3: Computer Algebra and Polynomials/Partition Congruences and Combinatorics 13

Partition Congruences and Combinatorics

(22)

WS 3: Computer Algebra and Polynomials/Partition Congruences and Combinatorics 14

I There is a combinatorial explanation for the divisibility of p(5n+ 4) by 5 (Dyson’s rank statistics). But concerning further connections between combinatorics and modular forms, not too much is known so far.

As an example, we present a recent combinatorial construction of modular forms which involves Dedekind’s eta function:

η(τ) :=q241

Y

n=1

(1−qn) (q =e2πiτ).

(23)

WS 3: Computer Algebra and Polynomials/Partition Congruences and Combinatorics 15

Partition Diamonds

c a1

AAA U c

a2

- ac3

AA AA

AA - U

ac4

- ac5

AA AA

AA - U

ac6

. . . . ac7

. . . .a2kc1

AA AA

AA - U

a2kc2

-

a2k+1c AUAA a2kc

ca2k+2

Ak-elongated partition diamond of length 1

c a1

AAA U c

a2

. . . . ac3

. . . . c a2k

AAA a2k+1c

U c a2k+2 c

AAA U c a2k+3

. . . . a2k+4c

. . . . c a4k+1

AAA a4k+2c

U c

a4k+3 . . . . c AAA U c

. . . . c

. . . . c a(2k+1)n−1

AAA a(2k+1)nc

U ca(2k+1)n+1

Ak-elongated partition diamond of lengthn

1

(24)

WS 3: Computer Algebra and Polynomials/Partition Congruences and Combinatorics 16

Generating function:

hn,k(q) = Qn−1

j=0(1 +q(2k+1)j+2)(1 +q(2k+1)j+4)· · ·(1 +q(2k+1)j+2k) Q(2k+1)n+1

j=1 (1−qj)

This generating function is beautiful indeed, but George Andrews wanted more!

From: George E Andrews<[email protected]> Date: Jan 2005

To: [email protected], [email protected] Subject: I had a brainstorm

(25)

WS 3: Computer Algebra and Polynomials/Partition Congruences and Combinatorics 16

Generating function:

hn,k(q) = Qn−1

j=0(1 +q(2k+1)j+2)(1 +q(2k+1)j+4)· · ·(1 +q(2k+1)j+2k) Q(2k+1)n+1

j=1 (1−qj)

This generating function is beautiful indeed, but George Andrews wanted more!

From: George E Andrews<[email protected]>

Date: Jan 2005

To: [email protected], [email protected] Subject: I had a brainstorm

(26)

WS 3: Computer Algebra and Polynomials/Partition Congruences and Combinatorics 17

Dear Axel and Peter,

I have had a BRAINSTORM! (I can almost see the smile on Peter’s face ...) To begin with let me draw your attention to Thm.2 in PAXI and Cor.2.1 in PAVIII ... However, THIS IS JUST THE BEGINNING.

Namely, I always had a slight disappointment in both the earlier results because the generating function ... was not a modular form. However, I now know how to produce the appropriate directed graph to provide ... a generating function that is not only a modular form but, in fact, a product of instances of Dedekind’s eta-function.

(27)

WS 3: Computer Algebra and Polynomials/Partition Congruences and Combinatorics 18

Recall the generating function:

hn,k(q) = Qn−1

j=0(1 +q(2k+1)j+2)(1 +q(2k+1)j+4)· · ·(1 +q(2k+1)j+2k) Q(2k+1)n+1

j=1 (1−qj) The result of Andrews’ brainstorm: delete the source:

hn,k(q) = Qn−1

j=0(1 +q(2k+1)j+1)(1 +q(2k+1)j+3)· · ·(1 +q(2k+1)j+2k−1) Q(2k+1)n

j=1 (1−qj) andglue the diamonds together:

(28)

WS 3: Computer Algebra and Polynomials/Partition Congruences and Combinatorics 18

Recall the generating function:

hn,k(q) = Qn−1

j=0(1 +q(2k+1)j+2)(1 +q(2k+1)j+4)· · ·(1 +q(2k+1)j+2k) Q(2k+1)n+1

j=1 (1−qj) The result of Andrews’ brainstorm: delete the source:

hn,k(q) = Qn−1

j=0(1 +q(2k+1)j+1)(1 +q(2k+1)j+3)· · ·(1 +q(2k+1)j+2k−1) Q(2k+1)n

j=1 (1−qj) andglue the diamonds together:

(29)

WS 3: Computer Algebra and Polynomials/Partition Congruences and Combinatorics 19

X

n=0

k(n)qn:=hn,k(q)hn,k(q)

=

Y

n=1

(1−q2n)(1−q(2k+1)n) (1−qn)3(1−q(4k+2)n)

=q(k+1)/12η(2τ)η((2k+ 1)τ) η(τ)3η((4k+ 2)τ)

c b(2k+1)n+1

AAAc b(2k+1)n−1

. . . . b(2k+1)nc

. . . .c AAA c

c

K

K

. . . c AAA

c. . . .

c. . . . K

bc7

AA AA

AA

bc6

K

bc5

K bc4

AA AA

AA

bc3

bc2

b2k+2

b2k+1

b2k

c a1

AAA U c

a2

. . . . ac3

. . . .c a2k

AAA a2k+1c

U c

a2k+2 . . . c

AAA U c

. . . . c

. . . .c a(2k+1)n−1

AAA a(2k+1)nc

U c a(2k+1)n+1

A brokenk-diamond of length 2n

1

(30)

WS 3: Computer Algebra and Polynomials/Partition Congruences and Combinatorics 19

X

n=0

k(n)qn:=hn,k(q)hn,k(q)

=

Y

n=1

(1−q2n)(1−q(2k+1)n) (1−qn)3(1−q(4k+2)n)

=q(k+1)/12η(2τ)η((2k+ 1)τ) η(τ)3η((4k+ 2)τ)

c b(2k+1)n+1

AAAc b(2k+1)n−1

. . . . b(2k+1)nc

. . . .c AAA c

c

K

K

. . . c AAA

c. . . .

c. . . . K

bc7

AA AA

AA

bc6

K

b5c

K b4c

AA AA

AA

bc3

bc2

b2k+2

b2k+1

b2k

c a1

AAA U c

a2

. . . . ac3

. . . .c a2k

AAA a2k+1c

U c

a2k+2 . . . c

AAA U c

. . . . c

. . . .c a(2k+1)n−1

AAA a(2k+1)nc

U c a(2k+1)n+1

A brokenk-diamond of length 2n

1

(31)

WS 3: Computer Algebra and Polynomials/Partition Congruences and Combinatorics 20

Numerous Congruences for∆k(n) Example [Sellers & Radu, 2012]

X

n=0

2(3n+ 1)qn≡2q

Y

n=1

(1−q10n)4

(1−q5n)2 (mod 3)

This implies for alln≥0:

2(15n+ 1) ≡ 0 (mod 3),

2(27n+ 16) ≡ 0 (mod 3),

2(147n+ 58) ≡ 0 (mod 3), etc.

Note. More people became interested in such congruences, e.g., S.H. Chan, W.Y.C. Chen, S. Cui, A.R.B. Fan, S.S. Fu, N. Gu, M.D. Hirschhorn, M. Jameson, E. Mortenson, X. Xiong, R.T. Yu.

(32)

WS 3: Computer Algebra and Polynomials/Partition Congruences and Combinatorics 20

Numerous Congruences for∆k(n) Example [Sellers & Radu, 2012]

X

n=0

2(3n+ 1)qn≡2q

Y

n=1

(1−q10n)4

(1−q5n)2 (mod 3)

This implies for alln≥0:

2(15n+ 1) ≡ 0 (mod 3),

2(27n+ 16) ≡ 0 (mod 3),

2(147n+ 58) ≡ 0 (mod 3), etc.

Note. More people became interested in such congruences, e.g., S.H. Chan, W.Y.C. Chen, S. Cui, A.R.B. Fan, S.S. Fu, N. Gu, M.D. Hirschhorn, M. Jameson, E. Mortenson, X. Xiong, R.T. Yu.

(33)

WS 3: Computer Algebra and Polynomials/Partition Congruences and Combinatorics 20

Numerous Congruences for∆k(n) Example [Sellers & Radu, 2012]

X

n=0

2(3n+ 1)qn≡2q

Y

n=1

(1−q10n)4

(1−q5n)2 (mod 3)

This implies for alln≥0:

2(15n+ 1) ≡ 0 (mod 3),

2(27n+ 16) ≡ 0 (mod 3),

2(147n+ 58) ≡ 0 (mod 3), etc.

Note. More people became interested in such congruences, e.g., S.H. Chan, W.Y.C. Chen, S. Cui, A.R.B. Fan, S.S. Fu, N. Gu, M.D. Hirschhorn, M. Jameson, E. Mortenson, X. Xiong, R.T. Yu.

(34)

WS 3: Computer Algebra and Polynomials/Ramanujan’s Congruences 21

Ramanujan’s Congruences

(35)

WS 3: Computer Algebra and Polynomials/Ramanujan’s Congruences 22

Ramanujan’s Congruences

p(5n+ 4) ≡ 0 (mod 5), p(7n+ 5) ≡ 0 (mod 7), p(11n+ 6) ≡ 0 (mod 11)

(36)

WS 3: Computer Algebra and Polynomials/Ramanujan’s Congruences 22

Ramanujan’s Congruences

p(5n+ 4) ≡ 0 (mod 5), p(52n+ 24) ≡ 0 (mod 52), p(53n+ 99) ≡ 0 (mod 53),

etc.

(37)

WS 3: Computer Algebra and Polynomials/Ramanujan’s Congruences 23

Ramanujan’s Conjecture (1919)

For`∈ {5,7,11} andα∈ {1,2,3, . . .}:

p(`αn+µα,`)≡0 (mod `α), whereµα,`∈ {0, . . . , `α−1} is uniquely defined by

24µα,`≡1 (mod`α).

(38)

WS 3: Computer Algebra and Polynomials/Ramanujan’s Congruences 24

A Bit of History

I Ramanujan [1917-1919]: proof sketches for `= 5 and `= 7;

see Berndt and Ono [1999].

I Watson [1938]: `= 5 and`= 7 (corrected version)

I Atkin [1967]: `= 11

I Gordon [1983]:

p(11αn+µα,11)≡0 (mod 11α+), where is a fixed non-positive integer to be determined. Following Gordon’s proof one can easily determine = 0.

(39)

WS 3: Computer Algebra and Polynomials/Ramanujan’s Congruences 24

A Bit of History

I Ramanujan [1917-1919]: proof sketches for `= 5 and `= 7;

see Berndt and Ono [1999].

I Watson [1938]: `= 5 and`= 7 (corrected version)

I Atkin [1967]: `= 11

I Gordon [1983]:

p(11αn+µα,11)≡0 (mod 11α+), where is a fixed non-positive integer to be determined. Following Gordon’s proof one can easily determine = 0.

(40)

WS 3: Computer Algebra and Polynomials/Ramanujan’s Congruences 24

A Bit of History

I Ramanujan [1917-1919]: proof sketches for `= 5 and `= 7;

see Berndt and Ono [1999].

I Watson [1938]: `= 5 and`= 7 (corrected version)

I Atkin [1967]: `= 11

I Gordon [1983]:

p(11αn+µα,11)≡0 (mod 11α+), where is a fixed non-positive integer to be determined. Following Gordon’s proof one can easily determine = 0.

(41)

WS 3: Computer Algebra and Polynomials/Ramanujan’s Congruences 24

A Bit of History

I Ramanujan [1917-1919]: proof sketches for `= 5 and `= 7;

see Berndt and Ono [1999].

I Watson [1938]: `= 5 and`= 7 (corrected version)

I Atkin [1967]: `= 11

I Gordon [1983]:

p(11αn+µα,11)≡0 (mod 11α+), where is a fixed non-positive integer to be determined.

Following Gordon’s proof one can easily determine = 0.

(42)

WS 3: Computer Algebra and Polynomials/Ramanujan’s Congruences 25

Our proof for ` = 11 and ` = 5, 7:

I In his generalization of Watson’s method, Gordon needs to compute thestructure constants of a certain algebra.

Although this is not needed in the case`= 5,7.

I For `= 11we succeeded to do without structure constants, (i.e., we stay with the module structure), so the ingredients here are the same as in the original proof of Watson.

I This way we obtain a unified frameworkfor all three cases

`= 5,7,11.

I The price to pay: our approach is more expensive computationally.

(43)

WS 3: Computer Algebra and Polynomials/Ramanujan’s Congruences 25

Our proof for ` = 11 and ` = 5, 7:

I In his generalization of Watson’s method, Gordon needs to compute thestructure constants of a certain algebra.

Although this is not needed in the case`= 5,7.

I For `= 11we succeeded to do without structure constants, (i.e., we stay with the module structure), so the ingredients here are the same as in the original proof of Watson.

I This way we obtain a unified frameworkfor all three cases

`= 5,7,11.

I The price to pay: our approach is more expensive computationally.

(44)

WS 3: Computer Algebra and Polynomials/Ramanujan’s Congruences 25

Our proof for ` = 11 and ` = 5, 7:

I In his generalization of Watson’s method, Gordon needs to compute thestructure constants of a certain algebra.

Although this is not needed in the case`= 5,7.

I For `= 11we succeeded to do without structure constants, (i.e., we stay with the module structure), so the ingredients here are the same as in the original proof of Watson.

I This way we obtain a unified frameworkfor all three cases

`= 5,7,11.

I The price to pay: our approach is more expensive computationally.

(45)

WS 3: Computer Algebra and Polynomials/Ramanujan’s Congruences 25

Our proof for ` = 11 and ` = 5, 7:

I In his generalization of Watson’s method, Gordon needs to compute thestructure constants of a certain algebra.

Although this is not needed in the case`= 5,7.

I For `= 11we succeeded to do without structure constants, (i.e., we stay with the module structure), so the ingredients here are the same as in the original proof of Watson.

I This way we obtain a unified frameworkfor all three cases

`= 5,7,11.

I The price to pay: our approach is more expensive computationally.

(46)

WS 3: Computer Algebra and Polynomials/The Modular Function Setting 26

The Modular Function Setting

(47)

WS 3: Computer Algebra and Polynomials/The Modular Function Setting 27

Basic Notions

The level`congruence subgroup Γ0(`):=

a c b d

∈SL2(Z):c≡0 (mod `)

acts onH :=H∪Q∪ {i∞}(extended upper half plane) via a

c b d

(τ)7→ aτ+b cτ+d.

This induces an action on functionsf :H→C∪ {i∞}by (f|γ)(τ) :=faτ+b

cτ +d

where γ = a

c b d

.

(48)

WS 3: Computer Algebra and Polynomials/The Modular Function Setting 27

Basic Notions

The level`congruence subgroup Γ0(`):=

a c b d

∈SL2(Z):c≡0 (mod `)

acts onH :=H∪Q∪ {i∞}(extended upper half plane) via a

c b d

(τ)7→ aτ+b cτ+d.

This induces an action on functionsf :H→C∪ {i∞}by (f|γ)(τ) :=faτ+b

cτ +d

where γ = a

c b d

.

(49)

WS 3: Computer Algebra and Polynomials/The Modular Function Setting 28

Compact Riemann Surfaces X0(`)

X0(`) := orbit space of the action ofΓ0(`) onH

= {[τ] :τ ∈H}

Note.

aτ+b cτ +d −→ a

c when τ −→i∞.

and a

0 =i∞. Set of cusps: For anyprime `,

{[x]∈X0(`):x∈Q∪ {i∞}}={[0],[i∞]}.

(50)

WS 3: Computer Algebra and Polynomials/The Modular Function Setting 28

Compact Riemann Surfaces X0(`)

X0(`) := orbit space of the action ofΓ0(`) onH

= {[τ] :τ ∈H}

Note.

aτ+b cτ +d −→ a

c when τ −→i∞.

and a

0 =i∞.

Set of cusps: For anyprime `,

{[x]∈X0(`):x∈Q∪ {i∞}}={[0],[i∞]}.

(51)

WS 3: Computer Algebra and Polynomials/The Modular Function Setting 28

Compact Riemann Surfaces X0(`)

X0(`) := orbit space of the action ofΓ0(`) onH

= {[τ] :τ ∈H}

Note.

aτ+b cτ +d −→ a

c when τ −→i∞.

and a

0 =i∞.

Set of cusps: For anyprime `,

{[x]∈X0(`):x∈Q∪ {i∞}}={[0],[i∞]}.

(52)

WS 3: Computer Algebra and Polynomials/The Modular Function Setting 29

Modular Functions (MF)on Compact Riemann Surfaces X0(`) f :H→C∪ {i∞}induces a MFf:X0(`)→C∪ {i∞} if

I f is holomorphic onH;

I f is constant on the orbits[τ],τ ∈H;

I f is meromorphic at points inQ∪ {i∞}.

(53)

WS 3: Computer Algebra and Polynomials/The Modular Function Setting 29

Modular Functions (MF)on Compact Riemann Surfaces X0(`) f :H→C∪ {i∞}induces a MFf:X0(`)→C∪ {i∞} if

I f is holomorphic onH;

I f is constant on the orbits[τ],τ ∈H;

I f is meromorphic at points inQ∪ {i∞}.

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WS 3: Computer Algebra and Polynomials/The Modular Function Setting 30

Fourier expansions off at cusps [a/c]∈X0(`)

Forτ ∈neighborhood(i∞):

f

aτ +b cτ+d

) = (f|γ)(τ) = X

n≥ord[a/c](f)

a[a/c](n)q[a/c]n .

whereγ =

ab cd

∈SL2(Z),q[a/c]= e2πiτgcd(c

2,`)

` .

Note. If[a/c] = [a/0] = [i∞]thenq[a/c]=q.

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WS 3: Computer Algebra and Polynomials/The Modular Function Setting 30

Fourier expansions off at cusps [a/c]∈X0(`)

Forτ ∈neighborhood(i∞):

f

aτ +b cτ+d

) = (f|γ)(τ) = X

n≥ord[a/c](f)

a[a/c](n)q[a/c]n .

whereγ =

ab cd

∈SL2(Z),q[a/c]= e2πiτgcd(c

2,`)

` .

Note. If[a/c] = [a/0] = [i∞]thenq[a/c]=q.

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WS 3: Computer Algebra and Polynomials/The Modular Function Setting 31

Back to Ramanujan’s congruences L2β−1,` := q

Y

n=1

(1−q`n)

X

n=0

p(`2β−1n+µ2β−1,`)qn, and

L2β,` :=q

Y

n=1

(1−qn)

X

n=0

p(`n+µ2β,`)qn.

We consider these series asFourier expansions at[i∞]of modular functionsf:X0(`)→C∪ {i∞} from a suitablesubring R(`).

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WS 3: Computer Algebra and Polynomials/The Modular Function Setting 32

The RingsR(5), R(7), andR(11) Recall η(τ) =q241

Y

n=1

(1−qn) (q=e2πiτ).

From the literature it is well known that we can take

R(5)=Z[z5], R(7)=Z[z7], and

R(11)=hJ0, J1, . . . , J4iZ[z11] where

z5 := η6(5τ)

η6(τ) , z7 := η4(7τ)

η4(τ) , z11:= η12(11τ) η12(τ) ,

and with theJk such thatord[i∞](Jk) =k as in Atkin (1967).

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WS 3: Computer Algebra and Polynomials/The Modular Function Setting 32

The RingsR(5), R(7), andR(11) Recall η(τ) =q241

Y

n=1

(1−qn) (q=e2πiτ).

From the literature it is well known that we can take

R(5)=Z[z5], R(7)=Z[z7], and

R(11)=hJ0, J1, . . . , J4iZ[z11] where

z5 := η6(5τ)

η6(τ) , z7:= η4(7τ)

η4(τ) , z11:= η12(11τ) η12(τ) ,

and with theJk such thatord[i∞](Jk) =k as in Atkin (1967).

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WS 3: Computer Algebra and Polynomials/The Modular Function Setting 33

TheU-operator

U`(f):=X

n

ằn)qn

wheref([τ]) =P

năn)qn is the Fourier expansion off at[i∞].

Definition. For prime `, U`(1)(f):=U`

η(`2τ) η(τ) f

and U`(2)(f):=U`(f).

Lemmạ

f ∈R(`) ⇒ U`(i)(f)∈R(`).

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WS 3: Computer Algebra and Polynomials/The Modular Function Setting 33

TheU-operator

U`(f):=X

n

ằn)qn

wheref([τ]) =P

năn)qn is the Fourier expansion off at[i∞].

Definition. For prime `, U`(1)(f):=U`

η(`2τ) η(τ) f

and U`(2)(f):=U`(f).

Lemmạ

f ∈R(`) ⇒ U`(i)(f)∈R(`).

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WS 3: Computer Algebra and Polynomials/The Modular Function Setting 33

TheU-operator

U`(f):=X

n

ằn)qn

wheref([τ]) =P

năn)qn is the Fourier expansion off at[i∞].

Definition. For prime `, U`(1)(f):=U`

η(`2τ) η(τ) f

and U`(2)(f):=U`(f).

Lemmạ

f ∈R(`) ⇒ U`(i)(f)∈R(`).

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WS 3: Computer Algebra and Polynomials/The Modular Function Setting 34

Recursive representation of Lα,` in R(`)

Lemma. For `∈ {5,7,11},

Lα,`∈R(`);

theLα,` satisfy a recursion in R(`) as follows:

L0,`= 1,

L2β−1,`=U`(1)(L2β−2,`) andL2β,` =U`(2)(L2β−1,`).

This recursion is used in the induction proof of our “Main Theorem”:

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WS 3: Computer Algebra and Polynomials/The Modular Function Setting 35

Main Theorem

For suitably definedsubsetsXs,` ofR(`) we have:

Theorem. For`∈ {5,7,11}and all positive integersβ there existfβ,` ∈X1,` ifβ is odd, andfβ,` ∈X2,` if β is even, such that

Lβ,`=`βfβ,` for `= 5,11, and

Lβ,` =`dβ+12 efβ,` for `= 7.

Note. Ramanujan’s congruences are obtained as an immediate corollary.

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WS 3: Computer Algebra and Polynomials/The Modular Function Setting 36

TheR(`)-subsets Xs,` (`= 11: Atkin) Set

A`:= 12

gcd(`−1,12)

`

`+ 1 and z`:=η` η

gcd(`−1,12)24

.

Definition. For `∈ {5,7,11} ands= 1,2:

Xs,` :=

(n

`−1

X

i=0

Ji,`

X

j=0

ai(j)`dA`` (`j+ξi(s,`))ez`j : a0(0) = 0 and

with ai(j)∈Znonzero for only finitely many j )

The integer exponentsξi(s,`) are defined as follows:

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WS 3: Computer Algebra and Polynomials/The Modular Function Setting 37

The Exponentsξi(s,`)

Definition. For `∈ {5,7,11} ands= 1,2define

ξ(s,`) :{0, . . . , n`−1} →Z, i7→ξi(s,`)

by

(1,11)0 , . . . , ξ4(1,11)) := (−5,−1,1,2,6), (ξ(2,11)0 , . . . , ξ4(2,11)) := (−4,0,2,3,7);

and

ξ0(1,7):=−7and ξ0(2,7) :=−10;

and

ξ0(1,5):=−6and ξ0(2,5) :=−5.

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WS 3: Computer Algebra and Polynomials/The Modular Function Setting 38

Main Tool: The Fundamental Lemma

Fundamental Lemma. Let `∈ {5,7,11}. For any analytic w:H→Candj∈Z:

U`(wzj`) =−

d`−1

X

i=0

a(`)i (z`)U`(wzj+i−d` `).

Settingwto the generators of the moduleR(`), we obtain the U`(i) actions on all the module elements — provided

we know the2·d`·n` (2·5·1,2·7·1,2·55·5) initial actions.

This action then serves to expressLβ,` in terms of the generators which reveal the divisibilty properties of these elements.

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WS 3: Computer Algebra and Polynomials/Proof of the Main Theorem 39

Proof of the Main Theorem

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WS 3: Computer Algebra and Polynomials/Proof of the Main Theorem 40

The Fundamental Polynomial for any prime ` ≥ 5

The main ingredient in our induction proof is

Theorem. For any prime`≥5there exists a monic irreducible polynomialF`(X, Y)∈Q[Y][X]of degreed` := gcd(`−1,12)`(`−1) in X (andY) such that

F`(z`(τ), z`(`τ)) = 0.

Recall that

z`(τ) =η(`τ) η(τ)

gcd(`−1,12)24

.

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WS 3: Computer Algebra and Polynomials/Proof of the Main Theorem 41

Proving the Existence of the Fundamental Polynomial

Proof.

The proof uses a variant of a classical fact from Riemann surfaces;

namely, that on a compact Riemann surface two meromorphic functions are connected by an algebraic relation.

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WS 3: Computer Algebra and Polynomials/Proof of the Main Theorem 42

The Fundamental Polynomial for ` ∈ {5, 7, 11}

Theorem. For`∈ {5,7,11}the fundamental polynomial F`(X, Y) =Xd`+

d`−1

X

i=0

a(`)i (Y)Xi

has coefficient polynomialsa(`)i (Y)∈Q[Y]of the form

a(`)i (Y)=

d`

X

j=dd``−ie

s`(i, j)`dA`` (`j+i−d`)eYj

withs`(i, j)∈Z (determined using computer algebra).

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WS 3: Computer Algebra and Polynomials/Proof of the Main Theorem 43

Corollary: The Fundamental Lemma

Fundamental Lemma. Let `∈ {5,7,11}. For any w:H→C andj∈Z:

U`(wzj`) =−

d`−1

X

i=0

a(`)i (z`)U`(wzj+i−d` `).

Proof.

ApplyingU` to wzj−d` `F`(z`(τ), z`(`τ)) = 0gives the desired result.

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WS 3: Computer Algebra and Polynomials/Proof of the Main Theorem 43

Corollary: The Fundamental Lemma

Fundamental Lemma. Let `∈ {5,7,11}. For any w:H→C andj∈Z:

U`(wzj`) =−

d`−1

X

i=0

a(`)i (z`)U`(wzj+i−d` `).

Proof.

ApplyingU` to wzj−d` `F`(z`(τ), z`(`τ)) = 0gives the desired result.

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