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Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University math.sfsu.edu/beck DGCI 2016 Digital

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Page 1: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Discrete Volume Computations

for Polyhedra

x

y

z

5

20

2

Matthias Beck

San Francisco State University

math.sfsu.edu/beck

DGCI 2016

Digital

Page 2: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

“Science is what we understand well enough to explain to a computer, artis all the rest.”

Donald Knuth

Discrete Volume Computations for Polyhedra Matthias Beck 2

Page 3: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Themes

Discrete-geometricpolynomials

Generatingfunctions

Discrete Fourieranalysis

Combinatorialstructures

Computation(complexity)

(0, 1, 2, 3)

(1, 0, 2, 3)

(1, 0, 3, 2)

(0, 1, 3, 2)

(0, 2, 1, 3)

(2, 0, 1, 3)

(2, 1, 0, 3)

(1, 2, 0, 3)

(0, 2, 3, 1)

(0, 3, 2, 1)

(0, 3, 1, 2)

(3, 0, 1, 2)

(3, 1, 0, 2)

(1, 3, 0, 2)

(1, 3, 2, 0)

(1, 2, 3, 0)

(2, 0, 3, 1)

(2, 3, 0, 1)

(2, 3, 1, 0)

(2, 1, 3, 0)

(3, 2, 0, 1)

(3, 0, 2, 1)

(3, 2, 1, 0)

(3, 1, 2, 0)

Discrete Volume Computations for Polyhedra Matthias Beck 3

Page 4: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

A Sample Problem: Birkhoff–von Neumann Polytope

Bn =

x11 · · · x1n

... ...xn1 . . . xnn

∈ Rn2

≥0 :

∑j xjk = 1 for all 1 ≤ k ≤ n∑k xjk = 1 for all 1 ≤ j ≤ n

Discrete Volume Computations for Polyhedra Matthias Beck 4

Page 5: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Discrete Volumes

Rational polyhedron P ⊂ Rd – solution set of a system of linear equalities& inequalities with integer coefficients

Goal: understand P ∩ Zd . . .

I (list)∑

m∈P∩Zdzm1

1 zm22 · · · z

mdd

I (count)∣∣P ∩ Zd

∣∣

Discrete Volume Computations for Polyhedra Matthias Beck 5

Page 6: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Discrete Volumes

Rational polyhedron P ⊂ Rd – solution set of a system of linear equalities& inequalities with integer coefficients

Goal: understand P ∩ Zd . . .

I (list)∑

m∈P∩Zdzm1

1 zm22 · · · z

mdd

I (count)∣∣P ∩ Zd

∣∣I (volume) vol(P) = lim

t→∞

1

td

∣∣∣∣P ∩ 1

tZd∣∣∣∣

Discrete Volume Computations for Polyhedra Matthias Beck 5

Page 7: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Discrete Volumes

Rational polyhedron P ⊂ Rd – solution set of a system of linear equalities& inequalities with integer coefficients

Goal: understand P ∩ Zd . . .

I (list)∑

m∈P∩Zdzm1

1 zm22 · · · z

mdd

I (count)∣∣P ∩ Zd

∣∣I (volume) vol(P) = lim

t→∞

1

td

∣∣∣∣P ∩ 1

tZd∣∣∣∣

Ehrhart function LP(t) :=

∣∣∣∣P ∩ 1

tZd∣∣∣∣ =

∣∣tP ∩ Zd∣∣ for t ∈ Z>0

Discrete Volume Computations for Polyhedra Matthias Beck 5

Page 8: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Some Motivation

I Linear systems are everywhere, and so polyhedra are everywhere.

Discrete Volume Computations for Polyhedra Matthias Beck 6

Page 9: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Some Motivation

I Linear systems are everywhere, and so polyhedra are everywhere.

I In applications, the volume of the polytope represented by a linearsystem measures some fundamental data of this system (“average”).

Discrete Volume Computations for Polyhedra Matthias Beck 6

Page 10: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Some Motivation

I Linear systems are everywhere, and so polyhedra are everywhere.

I In applications, the volume of the polytope represented by a linearsystem measures some fundamental data of this system (“average”).

I Polytopes are basic geometric objects, yet even for these basic objectsvolume computation is hard and there remain many open problems.

Discrete Volume Computations for Polyhedra Matthias Beck 6

Page 11: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Some Motivation

I Linear systems are everywhere, and so polyhedra are everywhere.

I In applications, the volume of the polytope represented by a linearsystem measures some fundamental data of this system (“average”).

I Polytopes are basic geometric objects, yet even for these basic objectsvolume computation is hard and there remain many open problems.

I Many discrete problems in various mathematical areas are linearproblems, thus they ask for the discrete volume of a polytope indisguise.

Discrete Volume Computations for Polyhedra Matthias Beck 6

Page 12: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

A Warm-Up Ehrhart Function

Lattice polytope P ⊂ Rd – convex hull of finitely points in Zd

For t ∈ Z>0 let LP(t) := #(tP ∩ Zd

)Example:

∆ = conv {(0, 0), (1, 0), (0, 1)}

={

(x, y) ∈ R2≥0 : x+ y ≤ 1

}

Discrete Volume Computations for Polyhedra Matthias Beck 7

Page 13: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

A Warm-Up Ehrhart Function

Lattice polytope P ⊂ Rd – convex hull of finitely points in Zd

For t ∈ Z>0 let LP(t) := #(tP ∩ Zd

)Example:

∆ = conv {(0, 0), (1, 0), (0, 1)}

={

(x, y) ∈ R2≥0 : x+ y ≤ 1

}

L∆(t) =

(t+ 2

2

)= 1

2(t+ 1)(t+ 2)

Discrete Volume Computations for Polyhedra Matthias Beck 7

Page 14: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

A Warm-Up Ehrhart Function

Lattice polytope P ⊂ Rd – convex hull of finitely points in Zd

For t ∈ Z>0 let LP(t) := #(tP ∩ Zd

)Example:

∆ = conv {(0, 0), (1, 0), (0, 1)}

={

(x, y) ∈ R2≥0 : x+ y ≤ 1

}

L∆(t) =

(t+ 2

2

)= 1

2(t+ 1)(t+ 2) ,

a polynomial in t with leading coefficient vol (∆) =1

2

Discrete Volume Computations for Polyhedra Matthias Beck 7

Page 15: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

A Warm-Up Ehrhart Function

Lattice polytope P ⊂ Rd – convex hull of finitely points in Zd

For t ∈ Z>0 let LP(t) := #(tP ∩ Zd

)Example:

∆ = conv {(0, 0), (1, 0), (0, 1)}

={

(x, y) ∈ R2≥0 : x+ y ≤ 1

}

L∆(t) =

(t+ 2

2

)= 1

2(t+ 1)(t+ 2)

comes with the friendly generating function∑t≥0

(t+ 2

2

)zt =

1

(1− z)3

Discrete Volume Computations for Polyhedra Matthias Beck 7

Page 16: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Ehrhart Polynomials

Theorem (Ehrhart 1962) For any lattice polytope P,LP(t) is a polynomial in t of degree dimP withleading coefficient volP and constant term 1.

Equivalently, EhrP(z) := 1 +∑t≥1

LP(t) zt is rational:

EhrP(z) =h(z)

(1− z)dimP+1

where the Ehrhart h-vector h(z) satisfies h(0) = 1 andh(1) = (dimP)! vol(P).

Discrete Volume Computations for Polyhedra Matthias Beck 8

Page 17: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Ehrhart Polynomials

Theorem (Ehrhart 1962) For any lattice polytope P,LP(t) is a polynomial in t of degree dimP withleading coefficient volP and constant term 1.

Equivalently, EhrP(z) := 1 +∑t≥1

LP(t) zt is rational:

EhrP(z) =h(z)

(1− z)dimP+1

where the Ehrhart h-vector h(z) satisfies h(0) = 1 andh(1) = (dimP)! vol(P).

Seeming dichotomy: vol(P) = limt→∞

1

tdimPLP(t) can be computed discretely

via a finite amount of data.

Discrete Volume Computations for Polyhedra Matthias Beck 8

Page 18: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Ehrhart Polynomials

Theorem (Ehrhart 1962) For any lattice polytope P,LP(t) is a polynomial in t of degree d := dimP withleading coefficient volP and constant term 1.

EhrP(z) := 1 +∑t≥1

LP(t) zt =h(z)

(1− z)d+1

Equivalent descriptions of an Ehrhart polynomial:

I LP(t) = cd td + cd−1 t

d−1 + · · ·+ c0

I via roots of LP(t)

I EhrP(z) −→ LP(t) = h0

(t+dd

)+ h1

(t+d−1d

)+ · · ·+ hd

(td

)

Discrete Volume Computations for Polyhedra Matthias Beck 8

Page 19: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Ehrhart Polynomials

Theorem (Ehrhart 1962) For any lattice polytope P,LP(t) is a polynomial in t of degree d := dimP withleading coefficient volP and constant term 1.

EhrP(z) := 1 +∑t≥1

LP(t) zt =h(z)

(1− z)d+1

−→ LP(t) = h0

(t+dd

)+ h1

(t+d−1d

)+ · · ·+ hd

(td

)Theorem (Macdonald 1971) (−1)dLP(−t) enumerates the interior latticepoints in tP. Equivalently,

LP◦(t) = hd(t+d−1d

)+ hd−1

(t+d−2d

)+ · · ·+ h0

(t−1d

)

Discrete Volume Computations for Polyhedra Matthias Beck 9

Page 20: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Ehrhart Polynomials

Theorem (Ehrhart 1962) For any lattice polytope P,LP(t) is a polynomial in t of degree d := dimP withleading coefficient volP and constant term 1.

EhrP(z) := 1 +∑t≥1

LP(t) zt =h(z)

(1− z)d+1

−→ LP◦(t) = hd(t+d−1d

)+ hd−1

(t+d−2d

)+ · · ·+ h0

(t−1d

)Theorem (Stanley 1980) h0, h1, . . . , hd are nonnegative integers.

Discrete Volume Computations for Polyhedra Matthias Beck 9

Page 21: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Ehrhart Polynomials

Theorem (Ehrhart 1962) For any lattice polytope P,LP(t) is a polynomial in t of degree d := dimP withleading coefficient volP and constant term 1.

EhrP(z) := 1 +∑t≥1

LP(t) zt =h(z)

(1− z)d+1

−→ LP◦(t) = hd(t+d−1d

)+ hd−1

(t+d−2d

)+ · · ·+ h0

(t−1d

)Theorem (Stanley 1980) h0, h1, . . . , hd are nonnegative integers.

Corollary If hd+1−k > 0 then kP◦ contains an integer point.

Discrete Volume Computations for Polyhedra Matthias Beck 9

Page 22: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Interlude: Graph Coloring a la Ehrhart

χK2(k) = 2

(k

2

)...

1k +

1k +

1 = x 2x

2K

(Blass–Sagan)

Discrete Volume Computations for Polyhedra Matthias Beck 10

Page 23: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Interlude: Graph Coloring a la Ehrhart

χK2(k) = 2

(k

2

)...

1k +

1k +

1 = x 2x

2K

(Blass–Sagan)Similarly, for any given graphG on n nodes, we can write

χG(k) = a0

(k + n

n

)+ a1

(k + n− 1

n

)+ · · ·+ an

(k

n

)for some (meaningful) nonnegative integers a0, . . . , an

Discrete Volume Computations for Polyhedra Matthias Beck 10

Page 24: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Computational Complexity of Integer-Point Transforms

Rational polyhedron P ⊂ Rd – solution set of a system of linear equalities& inequalities with integer coefficients

−→ σP(z) :=∑

m∈P∩Zdzm1

1 zm22 · · · z

mdd is a rational function in z1, z2, . . . , zd

Lenstra (1983) polynomial-time algorithm to decide whether σP(z) = 0

Barvinok (1994) polynomial-time algorithm to compute σP(z)

Discrete Volume Computations for Polyhedra Matthias Beck 11

Page 25: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Computational Complexity of Integer-Point Transforms

Rational polyhedron P ⊂ Rd – solution set of a system of linear equalities& inequalities with integer coefficients

−→ σP(z) :=∑

m∈P∩Zdzm1

1 zm22 · · · z

mdd is a rational function in z1, z2, . . . , zd

Lenstra (1983) polynomial-time algorithm to decide whether σP(z) = 0

Barvinok (1994) polynomial-time algorithm to compute σP(z)

Example P = [0, 1000]

σ[0,1000](z) = 1 + z + · · ·+ z1000 =1− z1001

1− z

Discrete Volume Computations for Polyhedra Matthias Beck 11

Page 26: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Computational Complexity of Integer-Point Transforms

Rational polyhedron P ⊂ Rd – solution set of a system of linear equalities& inequalities with integer coefficients

−→ σP(z) :=∑

m∈P∩Zdzm1

1 zm22 · · · z

mdd is a rational function in z1, z2, . . . , zd

Lenstra (1983) polynomial-time algorithm to decide whether σP(z) = 0

Barvinok (1994) polynomial-time algorithm to compute σP(z)

Given a polytope P we can compute

EhrP(z) = σcone(P)(1, 1, . . . , 1, z)

where cone(P) := R≥0 (P × {1})

Discrete Volume Computations for Polyhedra Matthias Beck 11

Page 27: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Computational Complexity of Integer-Point Transforms

Rational polyhedron P ⊂ Rd – solution set of a system of linear equalities& inequalities with integer coefficients

−→ σP(z) :=∑

m∈P∩Zdzm1

1 zm22 · · · z

mdd is a rational function in z1, z2, . . . , zd

Lenstra (1983) polynomial-time algorithm to decide whether σP(z) = 0

Barvinok (1994) polynomial-time algorithm to compute σP(z)

Implementations:

De Loera, Koppe et al www.math.ucdavis.edu/∼latte

Verdoolaege freshmeat.net/projects/barvinok

Discrete Volume Computations for Polyhedra Matthias Beck 11

Page 28: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Ehrhart Quasipolynomials

Rational polytope P ⊂ Rd – convex hull of finitely points in Qd

Theorem (Ehrhart 1962) LP(t) is a quasipolynomial in t:

LP(t) = cd(t) td + cd−1(t) td−1 + · · ·+ c0(t)

where c0(t), . . . , cd(t) are periodic functions.

Example L[0,12](t) =1

2t+

3 + (−1)t

4

Discrete Volume Computations for Polyhedra Matthias Beck 12

Page 29: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Ehrhart Quasipolynomials

Rational polytope P ⊂ Rd – convex hull of finitely points in Qd

Theorem (Ehrhart 1962) LP(t) is a quasipolynomial in t:

LP(t) = cd(t) td + cd−1(t) td−1 + · · ·+ c0(t)

where c0(t), . . . , cd(t) are periodic functions. Equivalently,

EhrP(z) := 1 +∑t≥1

LP(t) zt =h(z)

(1− zp)dimP+1

for some (minimal) p ∈ Z>0 (the period of LP(t)).

Example Ehr[0,12](z) =∑t≥0

(1

2t+

3 + (−1)t

4

)zt =

1 + z

(1− z2)2

Discrete Volume Computations for Polyhedra Matthias Beck 12

Page 30: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Interlude: Magic Squares joint withThomas ZaslavskyAndrew Van Herick

Mn(t) – number of n× n squares with distinctentries and row, column, and diagonal sums t

4 9 23 5 78 1 6

Similar to graph coloring, this is a polyhedral

problem with forbidden hyperplanes:

inside-out polytopes

Discrete Volume Computations for Polyhedra Matthias Beck 13

Page 31: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Interlude: Magic Squaresjoint withThomas ZaslavskyAndrew Van Herick

Mn(t) – number of n× n squares with distinctentries and row, column, and diagonal sums t

4 9 23 5 78 1 6

Example

M3(t) =

2t2−32t+1449 = 2

9(t2 − 16t+ 72) if t ≡ 0 mod 182t2−32t+78

9 = 29(t− 3)(t− 13) if t ≡ 3 mod 18

2t2−32t+1209 = 2

9(t− 6)(t− 10) if t ≡ 6 mod 182t2−32t+126

9 = 29(t− 7)(t− 9) if t ≡ 9 mod 18

2t2−32t+969 = 2

9(t− 4)(t− 12) if t ≡ 12 mod 182t2−32t+102

9 = 29(t2 − 16t+ 51) if t ≡ 15 mod 18

0 if t 6≡ 0 mod 3

∑t≥0

M3(t) zt =8z15

(2z3 + 1

)(1− z3) (1− z6) (1− z9)

Discrete Volume Computations for Polyhedra Matthias Beck 13

Page 32: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Fourier–Dedekind Sums joint withSinai Robins

Rational polytope P ⊂ Rd – convex hull of finitely points in Qd

−→ EhrP(z) := 1 +∑t≥1

LP(t) zt =h(z)

(1− zp)dimP+1

Natural ingredients of formulas for Ehrhart quasipolynomials:

sn (c1, . . . , cd; c) :=1

c

c−1∑k=1

e2πi n/c(1− e2πi c1/c

) (1− e2πi c2/c

)· · ·(1− e2πi cd/c

)Examples sn(c1; c) ∼

⌊nc

Discrete Volume Computations for Polyhedra Matthias Beck 14

Page 33: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Fourier–Dedekind Sums joint withSinai Robins

Rational polytope P ⊂ Rd – convex hull of finitely points in Qd

−→ EhrP(z) := 1 +∑t≥1

LP(t) zt =h(z)

(1− zp)dimP+1

Natural ingredients of formulas for Ehrhart quasipolynomials:

sn (c1, . . . , cd; c) :=1

c

c−1∑k=1

e2πi n/c(1− e2πi c1/c

) (1− e2πi c2/c

)· · ·(1− e2πi cd/c

)Examples sn(c1; c) ∼

⌊nc

s0(c1, c2; c) ∼c−1∑k=1

⌊k c1c

⌋2

∼ Dedekind sum

Discrete Volume Computations for Polyhedra Matthias Beck 14

Page 34: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Fourier–Dedekind Sums joint withSinai Robins

sn (c1, . . . , cd; c) :=1

c

c−1∑k=1

e2πi n/c(1− e2πi c1/c

) (1− e2πi c2/c

)· · ·(1− e2πi cd/c

)Fun Facts (Dedekind 1880s, Rademacher 1950s)

I sn(a, 1; b) = sn(a mod b, 1; b)

I sn(a, 1; b) + sn(b, 1; a) = something simple [reciprocity]

Discrete Volume Computations for Polyhedra Matthias Beck 15

Page 35: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Fourier–Dedekind Sums joint withSinai Robins

sn (c1, . . . , cd; c) :=1

c

c−1∑k=1

e2πi n/c(1− e2πi c1/c

) (1− e2πi c2/c

)· · ·(1− e2πi cd/c

)Fun Facts (Dedekind 1880s, Rademacher 1950s)

I sn(a, 1; b) = sn(a mod b, 1; b)

I sn(a, 1; b) + sn(b, 1; a) = something simple [reciprocity]

Corollary sn (c1, c2; c) can be computed in time log max(c1, c2, c).

Discrete Volume Computations for Polyhedra Matthias Beck 15

Page 36: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Fourier–Dedekind Sums joint withSinai Robins

sn (c1, . . . , cd; c) :=1

c

c−1∑k=1

e2πi n/c(1− e2πi c1/c

) (1− e2πi c2/c

)· · ·(1− e2πi cd/c

)Fun Facts (Dedekind 1880s, Rademacher 1950s)

I sn(a, 1; b) = sn(a mod b, 1; b)

I sn(a, 1; b) + sn(b, 1; a) = something simple [reciprocity]

Corollary sn (c1, c2; c) can be computed in time log max(c1, c2, c).

Corollary The Ehrhart quasipolynomial of any rational polygon P can beexpressed in terms of Fourier–Dedekind sums and computed in linear timein the input size of P.

Discrete Volume Computations for Polyhedra Matthias Beck 15

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Dedekind–Carlitz Polynomials joint withChristian HaaseAsia Matthews

Dedekind sum s0(a, 1; b) ∼b−1∑k=1

⌊ka

b

⌋2

∼b−1∑k=1

⌊ka

b

⌋(k − 1)

Dedekind–Carlitz Polynomial c (u, v; a, b) :=

b−1∑k=1

ubkab cvk−1

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Page 38: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Dedekind–Carlitz Polynomials joint withChristian HaaseAsia Matthews

Dedekind sum s0(a, 1; b) ∼b−1∑k=1

⌊ka

b

⌋2

∼b−1∑k=1

⌊ka

b

⌋(k − 1)

Dedekind–Carlitz Polynomial c (u, v; a, b) :=

b−1∑k=1

ubkab cvk−1

Theorem (Carlitz 1975) If a and b are relatively prime,

(v − 1) c (u, v; a, b) + (u− 1) c (v, u; b, a) = ua−1vb−1 − 1

Applying u ∂u twice and v ∂v once gives Dedekind’s reciprocity law.

Discrete Volume Computations for Polyhedra Matthias Beck 16

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Dedekind–Carlitz Polynomials joint withChristian HaaseAsia Matthews

c (u, v; a, b) :=

b−1∑k=1

ubkab cvk−1

Consider the 2-dimensional cone

K := {λ1(0, 1) + λ2(a, b) : λ1, λ2 ≥ 0}

Fun Fact σK(u, v) :=∑

(m,n)∈K∩Z2

umvn =1 + uv c (v, u; b, a)

(1− v) (1− uavb)

Discrete Volume Computations for Polyhedra Matthias Beck 17

Page 40: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Dedekind–Carlitz Polynomials joint withChristian HaaseAsia Matthews

c (u, v; a, b) :=

b−1∑k=1

ubkab cvk−1

Consider the 2-dimensional cone

K := {λ1(0, 1) + λ2(a, b) : λ1, λ2 ≥ 0}

Fun Fact σK(u, v) :=∑

(m,n)∈K∩Z2

umvn =1 + uv c (v, u; b, a)

(1− v) (1− uavb)

I Carlitz reciprocity = two cones adding up to R2≥0

I Complexity anyone?

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Page 41: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

A (Small) Bouquet of Open Problems

I Classify Ehrhart polynomials (or, alternatively, Ehrhart h-vectors)

I Find more inside-out polytopes

I Attack existence problems via (discrete-geometric) polynomials

I Study periods of Ehrhart quasipolynomials

I Study complexity of Fourier–Dedekind sums

I Compute vol(B11)

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Page 42: Discrete Volume Computations for Polyhedramath.sfsu.edu/beck/papers/nantes.pdf · Discrete Volume Computations for Polyhedra x y z 5 20 2 Matthias Beck San Francisco State University

Birkhoff–von Neumann Revisited joint withDennis PixtonJesus De LoeraMike DevelinJulian PfeifleRichard Stanley

For more about roots of

(Ehrhart) polynomials,

see Braun (2008) and

Pfeifle (2010).

Discrete Volume Computations for Polyhedra Matthias Beck 19