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Prologue: Prologue: Theorem of Cayley Bacharach Chasles What is a - - PowerPoint PPT Presentation

Prologue: Prologue: Theorem of Cayley Bacharach Chasles What is a point? Jrgen Richter-Gebert, TU Munich Article at ADG 2010 ADG=Automated Deduction in Geometry Whats the Point? Ramans suggestion From Micheluccis paper From Complex


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Prologue:

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Theorem of Cayley Bacharach Chasles Prologue:

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What is a point?

Jürgen Richter-Gebert, TU Munich

Ramans suggestion

What‘s the Point?

Article at ADG 2010

ADG=Automated Deduction in Geometry

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From Micheluccis paper From Complex matroids: Below, Krummeck, JRG

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From Micheluccis paper

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A first example

Consider all circles through a point 0 Call them „lines“ two Points ≠0 uniquely determine a line two lines have (usually)

  • ne intersection ≠0

Pappos‘s Theorem holds (kind of)

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One way to think about it

Line at ∞ is contracted to a point

after rotation

Affine version of Pappos‘s Theorem

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Second way to think about it

a·(x2 + y2) + b·xz + c·xz + d·z2

→ (a, b, c, d)

  x0 y0 z0  

* B B @ a b c d 1 C C A , B B @ x2

0 + y2

x0z0 y0z0 z2 1 C C A + = 0 4ad − b2 − c2 < 0 4ad − b2 − c2 < 0

two-dimensional projective subspace in RP3

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Second way to think about it

a·(x2 + y2) + b·xz + c·xz + d·z2

→ (a, b, c, d)

* B B @ a b c d 1 C C A , B B @ x2

0 + y2

x0z0 y0z0 z2 1 C C A + = 0 4ad − b2 − c2 < 0 4ad − b2 − c2 < 0

two-dimensional projective subspace in RP3

  x0 y0 z0  

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Connecting the spaces

  x y z   7!     x2 + y2 xz yz z2    

Line at infinity is contracted to a single point

  x y   7!     1    

* B B @ a b c d 1 C C A , B B @ x2

0 + y2

x0z0 y0z0 z2 1 C C A + = 0

(a, b, c, d)

representing „lines“ mapping the points

Φ : RP2 → RP3

with

Point 0 is singular

by

dehomogenized picture Blow up situation in 0 by distinguishing line directions This makes the space a projective plane

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Circles as conics

ax2 + by2 + cz2 + dxy + exz + fyz = 0

J =   1 −i   I =   1 i  

Circles are conics through

I2 =         1 −1 i         J2 =         1 −1 −i         I2 + J2 ∼         1 −1         I2 − J2 ∼         1        

RP5

in

(a, b, c, d, e, f)

Φ : RP2 → RP5

Φ(p) := p2

a = b d = 0

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I J

linear conditions

2 directions to go:

general linear conditions higher degree curves both

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Degree 3 curves

Cubic through 7 points Two more points fix the cubic (in general)

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Degree 3 curves

Cubic through 7 points Two more points fix the cubic (in general) Problem: too many intersections

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Conics with three general linear constraints

ax2 + by2 + cz2 + dxy + exz + fyz = 0

allow arbitrary linear constraints on

(a, b, c, d, e, f)

ax2 + by2 + cz2 = 0

d = 0, e = 0, f = 0

Simple example Four intersections!!

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Conics of the form ax2 + by2 + cz2 = 0

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Symmetric „shadow points“ All quadrants are identical Idea: form equivalence classes of points

Conics of the form ax2 + by2 + cz2 = 0

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A B

Linear pencils of curves

C A, B, C

RP5

„planes“ in through 3 points (constraints)

C = λA + µB

Intersections of

B

and

A

are also on

C = λA + µB C = λA + µB

this implies

c1 ∨ c2 ∨ c3 ∨ Φ(p) ∨ Φ(q) = 0

p and q are equivalent if p q

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Interesting contstraints

equivalent points related by inversion

c1 =         1 −1         c2 =         1         c3 =         1 −1        

x2 + y2 + z2 + exz + fyz = 0

| {z }

circles perpendicular to unit circle

  • ne „half“ is the hyperbolic plane
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Circle inversion interpreted in

  x y 1   7!   x y x2 + y2  

RP5

all 5x5 minors vanish, check it :-) constraints and mapped points

        1 1 x2 x2 −1 y2 y2 −1 1 x4 + y4 + 2x2y2 1 xy xy x x3 + xy2 y x2y + y3        

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Incidence theorems hold (for many reasons)

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Interesting contstraints

equivalent points related by inversion

c1 =         1 −1         c2 =         1         c3 =         1 −1        

x2 + y2 + z2 + exz + fyz = 0

| {z }

circles perpendicular to unit circle

  • ne orbit: hyperbolic plane
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Interesting contstraints

equivalent points related by projective double cover

c1 =         1 −1         c2 =         1        

| {z }

circles through antipodals of unit circle

  • ne „half“ is the projective plane

c3 =         1 1        

x2 + y2 − z2 + exz + fyz = 0

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Incidence theorems hold (for many reasons)

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degree 3 curves

B A λA+μB Again: these are equivalent points

c1 ∨ . . . ∨ c7 ∨ Φ(p) ∨ Φ(q) = 0

Cubic through 7 points Two more points fix the cubic (in general) Problem: Too many intersections

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degree 3 curves

B A λA+μB Interesting problem: How to calculeate the equivalent point?

c1 ∨ . . . ∨ c7 ∨ Φ(p) ∨ Φ(q) = 0

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c1 ∨ . . . ∨ c7 ∨ Φ(p) ∨ Φ(q) = 0

Interesting problem: How to calculeate the equivalent point?

//these are the points pts=[A,B,C,D,E,F,G,H]; //Defining a function that gives the cubic parameters pars(p):=( p.x^3, p.x^2*p.y, p.x*p.y^2, p.y^3, p.x^2, p.x*p.y, p.y^2, p.x, p.y, 1 ); //Setup a matrix consisting of all rows being the cubic parameters of the eight points mat=transpose(apply(pts,pars(#))); //We now need a point whose cubic parameters are linearly dependent //with the rows of this matrix //In Other words the exterior product of the cubic parameters of the point we search for //With all the other cubic parameters must vanish //This gives all together 10 cubic equations //Fortunately they are highly dependent, so already two of them span define the set of solutions //Here are the parameters of two of these equtions (one of them without a x^3 coefficient the other without y^3) a1=0; b1=-det(mat_(3,4,5,6,7,8,9,10)); c1=det(mat_(2,4,5,6,7,8,9,10)); d1=-det(mat_(2,3,5,6,7,8,9,10)); e1=det(mat_(2,3,4,6,7,8,9,10)); f1=-det(mat_(2,3,4,5,7,8,9,10)); g1=det(mat_(2,3,4,5,6,8,9,10)); h1=-det(mat_(2,3,4,5,6,7,9,10)); i1=det(mat_(2,3,4,5,6,7,8,10)); j1=-det(mat_(2,3,4,5,6,7,8,9)); a2=det(mat_(2,3,5,6,7,8,9,10)); b2=-det(mat_(1,3,5,6,7,8,9,10)); c2=det(mat_(1,2,5,6,7,8,9,10)); d2=0; e2=-det(mat_(1,2,3,6,7,8,9,10)); f2=det(mat_(1,2,3,5,7,8,9,10)); g2=-det(mat_(1,2,3,5,6,8,9,10)); h2=det(mat_(1,2,3,5,6,7,9,10)); i2=-det(mat_(1,2,3,5,6,7,8,10)); j2=det(mat_(1,2,3,5,6,7,8,9)); //Now comes the tricky part we must solve this system of two cubic equations. //We already know eight solutions (the eight old points) So in principle it must be possibly //by factoring out the known solutions. // //Here comes the recipe: // --> Use Mathematica to calculate the resultant of these two general cubic equations w.r.t. x and y // --> Since we already know a lot about the solution, // we only need the highest and the lowest coefficient of these resultants // --> as a matter of fact the highest coefficients of the two resultants are identical for the above parameters // Here are these coefficients (Calculated by Mathematica and already applying a1=0, and d2=0; // The highest coefficient zz= a2*b1*b2*c1*c2*d1 - a2^2*c1^2*c2*d1 - a2*b1^2*c2^2*d1 - a2*b1*b2^2*d1^2 + a2^2*b2*c1*d1^2 + 2*a2^2*b1*c2*d1^2 - a2^3*d1^3; // The lowest of one resultant yy= a2*e1*e2*h1*h2*j1 - a2^2*h1^2*h2*j1 - a2*e1^2*h2^2*j1 - a2*e1*e2^2*j1^2 + a2^2*e2*h1*j1^2 + 2*a2^2*e1*h2*j1^2 - a2^3*j1^3 - a2*e1*e2*h1^2*j2 + a2^2*h1^3*j2 + a2*e1^2*h1*h2*j2 + 2*a2*e1^2*e2*j1*j2 - 3*a2^2*e1*h1*j1*j2 - a2*e1^3*j2^2; // The lowest of the other resultant xx= -(d1*g2^2*i1*i2*j1) + d1*g1*g2*i2^2*j1 - d1^2*i2^3*j1 + d1*g2^3*j1^2 + d1*g2^2*i1^2*j2 - d1*g1*g2*i1*i2*j2 + d1^2*i1*i2^2*j2 - 2*d1*g1*g2^2*j1*j2 + 3*d1^2*g2*i2*j1*j2 + d1*g1^2*g2*j2^2 - 2*d1^2*g2*i1*j2^2 - d1^2*g1*i2*j2^2 + d1^3*j2^3; // Assuming the normalizing the highest terms to 1 one gets as lowest terms xx/zz and yy/zz // These two terms are the products of the x, (resp. y) coordinates of all zeros of the system. // So we only have to divide by the known solutions. Et viola: x=xx/zz/(product(pts,#.x));
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//these are the points pts=[A,B,C,D,E,F,G,H]; //Defining a function that gives the cubic parameters pars(p):=( p.x^3, p.x^2*p.y, p.x*p.y^2, p.y^3, p.x^2, p.x*p.y, p.y^2, p.x, p.y, 1 ); //Setup a matrix consisting of all rows being the cubic parameters of the eight points mat=transpose(apply(pts,pars(#))); //We now need a point whose cubic parameters are linearly dependent //with the rows of this matrix //In Other words the exterior product of the cubic parameters of the point we search for //With all the other cubic parameters must vanish //This gives all together 10 cubic equations //Fortunately they are highly dependent, so already two of them span define the set of solutions //Here are the parameters of two of these equtions (one of them without a x^3 coefficient the other without y^3) a1=0; b1=-det(mat_(3,4,5,6,7,8,9,10)); c1=det(mat_(2,4,5,6,7,8,9,10)); d1=-det(mat_(2,3,5,6,7,8,9,10)); e1=det(mat_(2,3,4,6,7,8,9,10)); f1=-det(mat_(2,3,4,5,7,8,9,10)); g1=det(mat_(2,3,4,5,6,8,9,10)); h1=-det(mat_(2,3,4,5,6,7,9,10)); i1=det(mat_(2,3,4,5,6,7,8,10)); j1=-det(mat_(2,3,4,5,6,7,8,9)); a2=det(mat_(2,3,5,6,7,8,9,10)); b2=-det(mat_(1,3,5,6,7,8,9,10)); c2=det(mat_(1,2,5,6,7,8,9,10)); d2=0; e2=-det(mat_(1,2,3,6,7,8,9,10));

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a2=det(mat_(2,3,5,6,7,8,9,10)); b2=-det(mat_(1,3,5,6,7,8,9,10)); c2=det(mat_(1,2,5,6,7,8,9,10)); d2=0; e2=-det(mat_(1,2,3,6,7,8,9,10)); f2=det(mat_(1,2,3,5,7,8,9,10)); g2=-det(mat_(1,2,3,5,6,8,9,10)); h2=det(mat_(1,2,3,5,6,7,9,10)); i2=-det(mat_(1,2,3,5,6,7,8,10)); j2=det(mat_(1,2,3,5,6,7,8,9)); //Now comes the tricky part we must solve this system of two cubic equations. //We already know eight solutions (the eight old points) So in principle it must be possibly //by factoring out the known solutions. // //Here comes the recipe: // --> Use Mathematica to calculate the resultant of these two general cubic equations w.r.t. x and y // --> Since we already know a lot about the solution, // we only need the highest and the lowest coefficient of these resultants // --> as a matter of fact the highest coefficients of the two resultants are identical for the above parameters // Here are these coefficients (Calculated by Mathematica and already applying a1=0, and d2=0; // The highest coefficient zz= a2*b1*b2*c1*c2*d1 - a2^2*c1^2*c2*d1 - a2*b1^2*c2^2*d1 - a2*b1*b2^2*d1^2 + a2^2*b2*c1*d1^2 + 2*a2^2*b1*c2*d1^2 - a2^3*d1^3; // The lowest of one resultant yy= a2*e1*e2*h1*h2*j1 - a2^2*h1^2*h2*j1 - a2*e1^2*h2^2*j1 - a2*e1*e2^2*j1^2 + a2^2*e2*h1*j1^2 + 2*a2^2*e1*h2*j1^2 - a2^3*j1^3 - a2*e1*e2*h1^2*j2 + a2^2*h1^3*j2 + a2*e1^2*h1*h2*j2 + 2*a2*e1^2*e2*j1*j2 - 3*a2^2*e1*h1*j1*j2 - a2*e1^3*j2^2; // The lowest of the other resultant xx= -(d1*g2^2*i1*i2*j1) + d1*g1*g2*i2^2*j1 - d1^2*i2^3*j1 + d1*g2^3*j1^2 + d1*g2^2*i1^2*j2 - d1*g1*g2*i1*i2*j2 + d1^2*i1*i2^2*j2 - 2*d1*g1*g2^2*j1*j2 + 3*d1^2*g2*i2*j1*j2 + d1*g1^2*g2*j2^2 - 2*d1^2*g2*i1*j2^2 - d1^2*g1*i2*j2^2 + d1^3*j2^3; // Assuming the normalizing the highest terms to 1 one gets as lowest terms xx/zz and yy/zz // These two terms are the products of the x, (resp. y) coordinates of all zeros of the system. // So we only have to divide by the known solutions. Et viola: x=xx/zz/(product(pts,#.x));

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Arthur Cayley

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(123456)·{....}·{....} · 6 + (123457)·{....}·{....} · 7 + (123458)·{....}·{....} · 8 = 9

Grading: 8,8,8,8,8,9,9,9

{...}·1 + {...}·2 + {...}·3 + {...}·4 + {...}·5 + {...}·6 + {...}·7 + {...}·8

Question: is 8,8,8,8,8,8,8,8 possible

– [123][647][857][473][428][178][123][573][526][176]

+ [123][647][857][478][128][173][423][573][526][176] + [123][647][857][473][428][178][576][126][173][523] + [123][657][847][573][528][178][123][473][426][176] – [123][657][847][578][128][173][523][473][426][176] – [123][657][847][573][528][178][476][126][173][423]

{....} =

Cayley decifered

(123457) = [123][453][426][156] – [456][126][153][423]

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{...}·1 + {...}·2 + {...}·3 + {...}·4 + {...}·5 + {...}·6 + {...}·7 + {...}·8

X

π∈S8

sign(π) [. . .][. . .][. . .][. . .][. . .][. . .] . . . [. . .] | {z }

27 brackets, grading 88888887

·π(8)

Brutally symmetric Ansatz

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X

π∈S8

sign(π) [. . .][. . .][. . .][. . .][. . .][. . .] . . . [. . .] | {z }

27 brackets, grading 88888887

·π(8)

[8, 1, 2] · [ , , ] · [ , , ] [8, 2, 3] · [ , , ] · [ , , ] [8, 3, 4] · [ , , ] · [ , , ] [8, 4, 5] · [ , , ] · [ , , ] [8, 5, 6] · [ , , ] · [ , , ] [8, 6, 7] · [ , , ] · [ , , ] [8, 7, 1] · [ , , ] · [ , , ] · 8

Brutally symmetric Ansatz

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X

π∈S8

sign(π) [. . .][. . .][. . .][. . .][. . .][. . .] . . . [. . .] | {z }

27 brackets, grading 88888887

·π(8)

[8, 1, 2] · [1, 2, 4] · [ , , ] [8, 2, 3] · [2, 3, 5] · [ , , ] [8, 3, 4] · [3, 4, 6] · [ , , ] [8, 4, 5] · [4, 5, 7] · [ , , ] [8, 5, 6] · [5, 6, 1] · [ , , ] [8, 6, 7] · [6, 7, 2] · [ , , ] [8, 7, 1] · [7, 1, 3] · [ , , ] · 8

Brutally symmetric Ansatz

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X

π∈S8

sign(π) [. . .][. . .][. . .][. . .][. . .][. . .] . . . [. . .] | {z }

27 brackets, grading 88888887

·π(8)

[8, 1, 2] · [1, 2, 4] · [1, 2, 6] [8, 2, 3] · [2, 3, 5] · [2, 3, 7] [8, 3, 4] · [3, 4, 6] · [3, 4, 1] [8, 4, 5] · [4, 5, 7] · [4, 5, 2] [8, 5, 6] · [5, 6, 1] · [5, 6, 3] [8, 6, 7] · [6, 7, 2] · [6, 7, 4] [8, 7, 1] · [7, 1, 3] · [7, 1, 5] · 8

Brutally symmetric Ansatz

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Back to conics

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RP5 RP2

Veronese (dim 2) 5–2 constraints span (dim 5–2)

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RP2 RP5

Veronese (dim 2) 5–2 constraints span (dim 5–2)

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RP2 RP5

Veronese (dim 2) 5–2 constraints span (dim 5–2)

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Φ(   x y z  ) =         x2 y2 z2 xy xz yz         ∂Φ ∂x =         2x y x         ∂Φ ∂y =         2y x z         ∂Φ ∂z =         2z x y        

Calculating the mirror lines

det ⇣ c1, c2, c3, ∂Φ

∂x , ∂Φ ∂y , ∂Φ ∂z

⌘ = 0

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show some pictures

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Questions

Interplay real complex Topology of underlying spaces Fast visualization Iterate the process

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Thanks for your attention

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