1. Algorithmic Problems for Curves on Surfaces Daniel Štefankovič University of Rochester

2. ● Simple curves on surfaces * representing surfaces, simple curves in surfaces * algorithmic questions, history ● TOOL: (Quadratic) word equations ● Regular structures in drawings (?) ● Using word equations (Dehn twist, geometric intersection numbers,...) ● What I would like... outline

3. How to represent surfaces?

4. Combinatorial description of a surface 1. (pseudo) triangulation bunch of triangles + description of how to glue them a b c

5. Combinatorial description of a surface 2. pair-of-pants decomposition bunch of pair-of-pants + description of how to glue them (cannnot be used to represent: ball with  2 holes, torus)

6. Combinatorial description of a surface 3. polygonal schema 2n-gon + pairing of the edges = a a b b

7. Simple curves on surfaces closed curve  homeomorphic image of circle S 1 simple closed curve =  is injective (no self-intersections) (free) homotopy equivalent simple closed curves

8. How to represent simple curves in surfaces (up to homotopy)? Ideally the representation is “unique” (each curve has a unique representation) (properly embedded arc)

9. Combinatorial description of a (homotopy type of) a simple curve in a surface 1.intersection sequence with a triangulation a b c

10. Combinatorial description of a (homotopy type of) a simple curve in a surface 1.intersection sequence with a triangulation a b c bc -1 bc -1 ba -1 almost unique if triangulation points on  S

11. Combinatorial description of a (homotopy type of) a simple curve in a surface 2. normal coordinates (w.r.t. a triangulation)  a)=1  b)=3  c)=2 (Kneser ’29) unique if triangulation points on  S

12. Combinatorial description of a (homotopy type of) a simple curve in a surface 2. normal coordinates (w.r.t. a triangulation)  a)=100  b)=300  c)=200 a very concise representation! (compressed)

13. Combinatorial description of a (homotopy type of) a simple curve in a surface 3. weighted train track 5 10 3 13 10 5

14. Combinatorial description of a (homotopy type of) a simple curve in a surface 4. Dehn-Thurston coordinates ● number of intersections ● “twisting number” for each “circle” unique (important for surfaces without boundary)

15. ● Simple curves on surfaces * representing surfaces, simple curves in surfaces * algorithmic questions, history ● TOOL: (Quadratic) word equations ● Regular structures in drawings (?) ● Using word equations (Dehn twist, geometric intersection numbers,...) ● What I would like... outline

16. Algorithmic problems - History Contractibility (Dehn 1912) can shrink curve to point? Transformability (Dehn 1912) are two curves homotopy equivalent? Schipper ’92; Dey ’94; Schipper, Dey ’95 Dey-Guha ’99 (linear-time algorithm) Simple representative (Poincaré 1895) can avoid self-intersections? Reinhart ’62; Ziechang ’65; Chillingworth ’69 Birman, Series ’84

17. Geometric intersection number minimal number of intersections of two curves Reinhart ’62; Cohen,Lustig ’87; Lustig ’87; Hamidi-Tehrani ’97 Computing Dehn-twists “wrap” curve along curve Penner ’84; Hamidi-Tehrani, Chen ’96; Hamidi-Tehrani ’01 polynomial only in explicit representations polynomial in compressed representations, but only for fixed set of curves Algorithmic problems - History

18. Algorithmic problems – will show Geometric intersection number minimal number of intersections of two curves Reinhart ’62; Cohen,Lustig ’87; Lustig ’87; Hamidi-Tehrani ’97, Schaefer-Sedgewick-Š ’08 Computing Dehn-twists “wrap” curve along curve Penner ’84; Hamidi-Tehrani, Chen ’96; Hamidi-Tehrani ’01, Schaefer-Sedgewick-Š ’08 polynomial in explicit compressed representations polynomial in compressed representations, for fixed set of curves any pair of curves

19. ● Simple curves on surfaces * representing surfaces, simple curves in surfaces * algorithmic questions, history ● TOOL: (Quadratic) word equations ● Regular structures in drawings (?) ● Using word equations (Dehn twist, geometric intersection numbers,...) ● What I would like... outline

20. Word equations xabx =yxy x,y – variables a,b - constants

21. xabx =yxy x,y – variables a,b - constants a solution: x=ab y=ab Word equations

22. Word equations with given lengths x,y – variables a,b - constants xayxb = axbxy additional constraints: |x|=4, |y|=1

23. Word equations with given lengths x,y – variables a,b - constants xayxb = axbxy additional constraints: |x|=4, |y|=1 a solution: x=aaaa y=b

24. Word equations word equations word equations with given lengths

25. Word equations word equations - NP-hard word equations with given lengths Plandowski, Rytter ’98 – polynomial time algorithm Diekert, Robson ’98 – linear time for quadratic eqns decidability – Makanin 1977 PSPACE – Plandowski 1999 (quadratic = each variable occurs  2 times) In NP ???

26. Word equations word equations - NP-hard word equations with given lengths Plandowski, Rytter ’98 – polynomial time algorithm Diekert, Robson ’98 – linear time for quadratic eqns decidability – Makanin 1977 PSPACE – Plandowski 1999 (quadratic = each variable occurs  2 times) In NP ??? exponential upper bound on the length of a minimal solution MISSING: OPEN:

27. ● Simple curves on surfaces * representing surfaces, simple curves in surfaces * algorithmic questions, history ● TOOL: (Quadratic) word equations ● Regular structures in drawings (?) ● Using word equations (Dehn twist, geometric intersection numbers,...) ● What I would like... outline

28. Shortcut number  (g,k) k curves on surface of genus g intersecting another curve   (the curves do not intersect)

29. Shortcut number  (g,k) k curves on surface of genus g intersecting another curve   1 4 1 4 1 3 8 6

30. Shortcut number  (g,k) k curves on surface of genus g intersecting another curve    1 4 1 4 1 3 8 6

31. Shortcut number  (g,k) k curves on surface of genus g intersecting another curve  smallest n such that  n intersections  reduced drawing

32. Shortcut number  (g,1)  2 4 1 3 2 4 1 3 2

33. Shortcut number  (1,2)  6 4 6 6 1 1 3 3 5 5 2 2 4

34. Conjecture:  g,k)  C k Experimentally: ,2)  7 ,3)  31 (?) Known [Schaefer, Š ‘2000]:  (0,k)  2 k

35. Directed shortcut number  d (g,k) k curves on surface of genus g intersecting another curve    1 4 1 4 1 3 8 6 BAD

36. Directed shortcut number  d (g,k)  d (0,2) = 20 upper bound must depend on g,k finite? Experimentally:

37. Directed shortcut number  d (g,k) finite? quadratic word equation  drawing problem bound on  d ( ,  )  upper bound on word eq. x=yz z=wB x=Aw y=AB x y z w A B A B interesting?

38. Spirals spiral of depth 1 (spanning arcs, 3 intersections)     interesting for word equations

39. Unfortunately: Example with no spirals [Schaefer, Sedgwick, Š ’07]

40. Spirals and folds spiral of depth 1 (spanning arcs, 3 intersections)   fold of width 3 Pach-Tóth’01: In the plane (with puncures) either a large spiral or a large fold must exist.

41. Unfortunately: Example with no spirals, no folds [Schaefer, Sedgwick, Š ’07]

42. Embedding on torus

43. ● Simple curves on surfaces * representing surfaces, simple curves in surfaces * algorithmic questions, history ● TOOL: (Quadratic) word equations ● Regular structures in drawings (?) ● Using word equations (Dehn twist, geometric intersection numbers,...) ● What I would like... outline

44. Geometric intersection number minimum number of intersections achievable by continuous deformations.  

45. Geometric intersection number minimum number of intersections achievable by continuous deformations. i( ,  )=2  

46. EXAMPLE: Geometric intersection numbers are well understood on the torus (3,5) (2,-1) 3 5 2 -1 det = -13

47. Recap: 1) how to represent them? 2) what/how to compute? 1.intersection sequence with a triangulation 2. normal coordinates (w.r.t. a triangulation) bc -1 bc -1 ba -1  a)=1  b)=3  c)=2 geometric intersection number

48. STEP1: Moving between the representations 1.intersection sequence with a triangulation 2. normal coordinates (w.r.t. a triangulation) bc -1 bc -1 ba -1  a)=1  b)=3  c)=2 Can we move between these two representations efficiently?  a)=1+2 100  b)=1+3.2 100  c)=2 101

49. compressed = straight line program (SLP) X 0  a X 1  b X 2  X 1 X 1 X 3  X 0 X 2 X 4  X 2 X 1 X 5  X 4 X 3 Theorem (SSS’08): normal coordinates  compressed intersection sequence in time O(  log  (e)) compressed intersection sequence  normal coordinates in time O(|T|.SLP-length(S)) X 5 = bbbabb

50. compressed = straight line program (SLP) X 0  a X 1  b X 2  X 1 X 1 X 3  X 0 X 2 X 4  X 2 X 1 X 5  X 4 X 3 X 5 = bbbabb Plandowski, Rytter ’98 – polynomial time algorithm Diekert, Robson ’98 – linear time for quadratic eqns OUTPUT OF: CAN DO (in poly-time): ● count the number of occurrences of a symbol ● check equaltity of strings given by two SLP’s (Miyazaki, Shinohara, Takeda’02 – O(n 4 )) ● get SLP for f(w) where f is a substitution  * and w is given by SLP

51. Simulating curve using quadratic word equations X y z u v u=xy... v=u |u|=|v|=  (u)... Diekert-Robson number of components w z |x|=(|z|+|u|-|w|)/2

52. Moving between the representations 1.intersection sequence with a triangulation 2. normal coordinates (w.r.t. a triangulation) bc -1 bc -1 ba -1  a)=1  b)=3  c)=2 Theorem: normal coordinates  compressed intersection sequence in time O(  log  (e)) “Proof”: X y z u v u=xy... av=ua |u|=|v|=|  T|   (u)

53. Dehn twist of  along   

54.  D()D()

55.   D()D()

56. Geometric intersection numbers n¢ i( ,  )i( ,  ) -i( ,  )  i( ,D n  (  ))  n¢ i( ,  )i( ,  )+i( ,  ) i( ,D n  (  ))/i( ,  ) ! i( , 

57. Computing Dehn-Twists (outline) 1. normal coordinates ! word equations with given lengths 2. solution = compressed intersection sequence with triangulation 3. sequences ! (non-reduced) word for Dehn-twist (substitution in SLPs) 4. Reduce the word ! normal coordinates (only for surfaces with  S  0)

58. ● Simple curves on surfaces * representing surfaces, simple curves in surfaces * algorithmic questions, history ● TOOL: (Quadratic) word equations ● Regular structures in drawings (?) ● Using word equations (Dehn twist, geometric intersection numbers,...) ● What I would like... outline

59. PROBLEM #1: Minimal weight representative 2. normal coordinates (w.r.t. a triangulation)  a)=1  b)=3  c)=2 unique if triangulation points on  S

60. PROBLEM #1: Minimal weight representative INPUT: triangulation + gluing normal coordinates of  edge weights OUTPUT:  ’  minimizing   ’(e) eTeT

61. PROBLEM #2: Moving between representations 4. Dehn-Thurston coordinates (Dehn ’38, W.Thurston ’76) unique representation for closed surfaces! PROBLEM normal coordinates  Dehn-Thurston coordinates in polynomial time? linear time?

62. PROBLEM #3: Word equations PROBLEM: are word equations in NP? are quadratic word equations in NP? NP-hard decidability – Makanin 1977 PSPACE – Plandowski 1999

63. PROBLEM #4: Computing Dehn-Twists faster? 1. normal coordinates ! word equations with given lengths 2. solution = compressed intersection sequence with triangulation 3. sequences ! (non-reduced) word for Dehn-twist (substitution in SLPs) 4. Reduce the word ! normal coordinates O(n 3 ) randomized, O(n 9 ) deterministic

64. PROBLEM #5: Realizing geometric intersection #? our algorithm is very indirect can compress drawing realizing geometric intersection #? can find the drawing?