Patterns and Higher-Order Stability in the Coefficients of the Colored Jones Polynomial. Katie Walsh Hall

Transcription

1 Patterns and Higher-Order Stability in the Coefficients of the Colored Jones Polynomial Katie Walsh Hall

2 The Colored Jones Polynomial The colored Jones polynomial is knot invariant. It assigns to each knot a sequence of polynomials. We want to look at the coefficients of these polynomials. Katie Walsh Hall Patterns and Higher Order Stability 2 / 68

3 The Colored Jones Polynomial The colored Jones polynomial is knot invariant. It assigns to each knot a sequence of polynomials. We want to look at the coefficients of these polynomials. Katie Walsh Hall Patterns and Higher Order Stability 2 / 68

4 The Colored Jones Polynomial The colored Jones polynomial is knot invariant. It assigns to each knot a sequence of polynomials. We want to look at the coefficients of these polynomials. N Highest Terms of the Colored Jones Polynomial of q 2 q + 1 q 1 + q 2 3 q 6 q 5 q 4 + 2q 3 q 2 q + 3 q 1 q q 12 q 11 q 10 +0q 9 + 2q 8 2q 6 + 3q 4 3q q 20 q 19 q 18 +0q 17 +0q q 15 q 14 q q 30 q 29 q 28 +0q 27 +0q 26 +q q q q 42 q 41 q 40 +0q 39 +0q 38 +q 37 +0q q 35 + Katie Walsh Hall Patterns and Higher Order Stability 3 / 68

5 The Colored Jones Polynomial The colored Jones polynomial is knot invariant. It assigns to each knot a sequence of polynomials. We want to look at the coefficients of these polynomials. Katie Walsh Hall Patterns and Higher Order Stability 4 / 68

6 Notes on Normalization The (N + 1) st colored Jones polynomial of a knot K is the Jones polynomial of K decorated with the f (N), the Jones-Wenzl idempotent in TL n. Katie Walsh Hall Patterns and Higher Order Stability 5 / 68

7 Notes on Normalization The (N + 1) st colored Jones polynomial of a knot K is the Jones polynomial of K decorated with the f (N), the Jones-Wenzl idempotent in TL n. Normalized colored Jones polynomial: J N,unknot (q) = 1 Un-normalized colored Jones polynomial: J N,unknot (q) = N 1 = ( 1) N 1 [N] J N,K (q) = J N,K (q) N 1 We use the convention that N = 2 gives the standard Jones polynomial. Katie Walsh Hall Patterns and Higher Order Stability 5 / 68

8 Set-Up Katie Walsh Hall Patterns and Higher Order Stability 6 / 68

9 Set-Up 5 Katie Walsh Hall Patterns and Higher Order Stability 7 / 68

10 The 5 th colored Jones Polynomial for figure 8 knot is: 1 q 20 1 q 19 1 q q 15 1 q 14 1 q 13 1 q 12 1 q q 10 1 q 9 2 q 8 2 q 7 1 q q 5 1 q 4 2 q 3 2 q 2 1 q +7 q 2q2 2q 3 q 4 +6q 5 q 6 2q 7 2q 8 q 9 +5q 10 This has coefficients: q 11 q 12 q 13 q q 15 q 18 q 19 + q 20 {1, 1, 1, 0, 0, 3, 1, 1, 1, 1, 5, 1, 2, 2, 1, 6, 1, 2, 2, 1, 7, 1, 2, 2, 1, 6, 1, 2, 2, 1, 5, 1, 1, 1, 1, 3, 0, 0, 1, 1, 1} Katie Walsh Hall Patterns and Higher Order Stability 8 / 68

11 {1, 1, 1, 0, 0, 3, 1, 1, 1, 1, 5, 1, 2, 2, 1, 6, 1, 2, 2, 1, 7, 1, 2, 2, 1, 6, 1, 2, 2, 1, 5, 1, 1, 1, 1, 3, 0, 0, 1, 1, 1} We can plot these: Figure: Coefficients of the 5 th Colored Jones Polynomial for the Figure Eight Knot Katie Walsh Hall Patterns and Higher Order Stability 9 / 68

12 Figure: Coefficients of the 20 th Colored Jones Polynomial for the Figure Eight Knot Katie Walsh Hall Patterns and Higher Order Stability 10 / 68

13 Figure: Coefficients of the 50 th Colored Jones Polynomial for the Figure Eight Knot Katie Walsh Hall Patterns and Higher Order Stability 11 / 68

14 Figure: Coefficients of the 95 th Colored Jones Polynomial for the Figure Eight Knot Katie Walsh Hall Patterns and Higher Order Stability 12 / 68

15 What is this polynomial? J N,4 1 (q) = = = N 1 n=0 k=1 N 1 n n=0 k=1 N 1 n n=0 k=1 n {N + k}{n k} (q (N+k)/2 q (N+k)/2 )(q (N k)/2 q (N k)/2 ) (q N q k q k + q N ) Katie Walsh Hall Patterns and Higher Order Stability 13 / 68

16 What about other knots? See Mathematica Demo... Katie Walsh Hall Patterns and Higher Order Stability 14 / 68

17 But what about the middle? Katie Walsh Hall Patterns and Higher Order Stability 15 / 68

18 Figure 8 Knot Middle Coefficients Observed Properties The middle coefficient is the constant term. The maximum coefficient is the coefficient of constant term. Some sort of N-periodicity in the middle coefficients. Katie Walsh Hall Patterns and Higher Order Stability 16 / 68

19 Constant Coefficient of the Colored Jones Polynomial of the Figure 8 Knot Constant Coefficient Number of Colors Figure: The Maximum Coefficient of the N Colored Jones Polynomial of the Figure 8 Knot as a function of N. Katie Walsh Hall Patterns and Higher Order Stability 17 / 68

20 Assumption The maximum coefficient takes the form Ae bn where N is the number of colors and A and b depend on the knot. Proposition The colored Jones polynomial of a knot K satisfies log J k (N)(e 2πi/N ) lim lim N N N log m K (N). N If the above assumption holds, then the colored Jones polynomial satisfies log J k (N)(e 2πi/N ) lim b. N N Katie Walsh Hall Patterns and Higher Order Stability 18 / 68

21 Assumption The maximum coefficient takes the form Ae bn where N is the number of colors and A and b depend on the knot. So for knots where the Hyperbolic Volume Conjecture holds we get to following Proposition For knots for which the Hyperbolic Volume conjecture holds vol(s 3 \K) 2π lim N log m K (N). N Now, if we include the above assumption, so that m(k)(n) = Ae bn, we get vol(s 3 \K) 2π b. Katie Walsh Hall Patterns and Higher Order Stability 19 / 68

22 Assumption The maximum coefficient takes the form Ae bn where N is the number of colors and A and b depend on the knot. Assumption The coefficients take the form of a normal distribution times a sine wave of period 2N. Proposition If the colored Jones polynomial of a knot satisfies these two assumptions then log (f N (e 2πi/N )) b = lim. N N If this is a knot for which the Hyperbolic Volume Conjecture holds, b = vol(s 3 \K). 2π Katie Walsh Hall Patterns and Higher Order Stability 20 / 68

23 Further Analysis on the Coefficients of the Figure 8 Knot Katie Walsh Hall Patterns and Higher Order Stability 21 / 68

24 0 semi-(un)normalized colored Jones polynomial:sjn,k (q) = {N}JN,K (q). 0 ±JN,K (q){1} = sjn,k (q) = JN,K (q){n} Katie Walsh Hall Patterns and Higher Order Stability 22 / 68

25 0 semi-(un)normalized colored Jones polynomial:sjn,k (q) = {N}JN,K (q). 0 ±JN,K (q){1} = sjn,k (q) = JN,K (q){n} Figure: The coefficients of the 95 colored semi-(un)normalized Jones polynomial of the figure 8 knot. Katie Walsh Hall Patterns and Higher Order Stability 22 / 68

26 Figure: The middle 3000 coefficients of the sj95,41 (q) Figure: The middle 2000 coefficients of the sj95,41 (q). Katie Walsh Hall Patterns and Higher Order Stability 23 / 68

27 Figure: The middle 1000 coefficients of the sj95,41 (q) Figure: The middle 400 coefficients of the sj95,41 (q). Katie Walsh Hall Patterns and Higher Order Stability 24 / 68

28 Conjecture Let c(q i ) be the coefficient of the q i term of sj N,41 (q). When N is odd, c(q i ) = When N is even, c(q i ) = { ±1 i = ±N/2 or ± 3N/2 0 i < 2N 1/2 and i ±N/2 or ± 3N/2 { ±1 i = ±N or ± 3N/2 0 i < 2N and i ±N or ± 3N/ Figure: The middle Katie Walsh 400 Hallcoefficients Patterns and ofhigher the Order sj 95,41 Stability (q). 25 / 68

29 Head and Tail Stabilty In 2006, Dasbach and Lin conjectured that the first and last coefficients of the colored Jones polynomial stabilize for alternating knots. In 2011, Armond proved this for alternating links and for adequate links, using skein theoretical techniques. The head and tail do not exist for all knots, however. Armond and Dasbach showed that the head and tail does not exist for the (4, 3) torus knot. It was also independently proven by Garoufalidis and Lê. In fact, they proved a stronger version of this stability. Katie Walsh Hall Patterns and Higher Order Stability 26 / 68

30 Definition The head of the Colored Jones Polynomial of a knot K - if it exists - is a polynomial whose first N terms (highest powers of q) have the same coefficients as the first N terms of J N,K. Definition The tail of the Colored Jones Polynomial of a knot K - if it exists - is a polynomial whose last N terms (lowest powers of q) have the same coefficients as the last N terms of J N,K. Katie Walsh Hall Patterns and Higher Order Stability 27 / 68

31 N Highest Terms of the Colored Jones Polynomial of q 2 q + 1 q 1 + q 2 3 q 6 q 5 q 4 + 2q 3 q 2 q + 3 q 1 q q 12 q 11 q 10 +0q 9 + 2q 8 2q 6 + 3q 4 3q q 20 q 19 q 18 +0q 17 +0q q 15 q 14 q q 30 q 29 q 28 +0q 27 +0q 26 +q q q q 42 q 41 q 40 +0q 39 +0q 38 +q 37 +0q q q 56 q 55 q 54 +0q 53 +0q 52 +q 51 +0q 50 +q 49 + Katie Walsh Hall Patterns and Higher Order Stability 28 / 68

32 The Head of the Colored Jones Polynomial of 4 1 J N,4 1 (q) = N 1 n=0 k=1 n q N q k q k + q N The max degree of each summand is Nn so decreasing the n by 1 changes the max degree by N thus only n = N 1 contributes to the head and tail. J N,4 1 (q) reindex:k = N k HT = HT = N 1 k=1 N 1 k=1 N 1 = q N q N q k q k + q N q N q k k=1 1 q k N Katie Walsh Hall N 1 Patterns and Higher Order Stability 29 / 68

33 J N,4 1 (q) HT = N 1 k =1 (1 q k ) Theorem (Euler s Pentagonal Number Theorem) (1 x n ) = n=1 k= ( 1) k x k(3k 1)/2 = 1 x x 2 + x 5 + x 7 x 12 x 15 + A similar arguments shows that the head of twists knots is the same polynomial. Katie Walsh Hall Patterns and Higher Order Stability 30 / 68

34 Theorem (Armond) The head and tail of the colored Jones polynomial exist for alternating and adequate links. Theorem (Armond and Dasbach) The tail and head of the colored Jones polynomial of adequate links only depend on a certain reduced checkerboard graph of a diagram of the link. Katie Walsh Hall Patterns and Higher Order Stability 31 / 68

35 Figure: The Knot 6 2 Katie Walsh Hall Patterns and Higher Order Stability 32 / 68

36 Figure: The Knot 6 2 with a checkerboard coloring Katie Walsh Hall Patterns and Higher Order Stability 33 / 68

37 Figure: The Knot 6 2 with one of its associated graph Katie Walsh Hall Patterns and Higher Order Stability 34 / 68

38 Figure: The Knot 6 2 with the other associated graph Katie Walsh Hall Patterns and Higher Order Stability 35 / 68

39 Knot Knot Diagram White Checkerboard Graph Black Checkerboard Graph Tail Head 3_1 1 h 3 4_1 h 3 h 3 5_1 h 5 1 5_2 h 3 * h 4 6_2 h 3 * h 3 h 4 7_4 h 3 (h 4 ) 2 7_7 (h 3 ) 2 (h 3 ) 3 8_5 h 3??? h b (q) = ( 1) n q bn(n+1)/2 n n Z h b (q) = n Z ɛ(n)q bn(n+1)/2 n Katie Walsh Hall Patterns and Higher Order Stability 36 / 68

40 Definition (Garoufalidis and Lê) A sequence (f n (q)) Z[[q]] is k-stable if there exist Φ j (q) Z((q)) for j = 0,..., k such that k lim f n (q) Φ j (q)q j(n+1) = 0. n q k(n+1) We call Φ k (q) the k-limit of (f n (q)). We say that (f n (q)) is stable if it is k-stable for all k. j=0 For example, a sequence (f n (q)) is 2-stable if ( ( )) lim n q 2(n+1) f n (q) Φ 0 (q) + q (n+1) Φ 1 (q) + q 2(n+1) Φ 2 (q) = 0. Katie Walsh Hall Patterns and Higher Order Stability 37 / 68

41 For the knot 8 5 : Φ 0 = (1 q n ) = ( 1) k q k 2 (3k 1). n=1 k= Φ N = N = N = Katie Walsh Hall Patterns and Higher Order Stability 38 / 68

42 Φ N = N = N = Now, since we know all of Φ 0, we can subtract it from the shifted colored Jones polynomials. Now are coefficients are: Φ N = N = N = Katie Walsh Hall Patterns and Higher Order Stability 39 / 68

43 Φ N = N = N = Shifting these sequences back so that they start with a non-zero term, we can see that they again stabilize. The sequence they stabilize to is Φ 1. Φ N = N = N = Katie Walsh Hall Patterns and Higher Order Stability 40 / 68

44 Φ N = N = N = Subtracting and shifting these sequences back so that they start with a non-zero term, we can see that they again stabilize. The sequence they stabilize to is Φ 2. Φ N = N = N = Katie Walsh Hall Patterns and Higher Order Stability 41 / 68

45 Theorem (Garoufalidis and Lê) For every alternating link K, the sequence f N (q) = ( ˆ J N+1,K (q)) is stable and its associated k-limit Φ K,k (q) can be effectively computed from any reduced alternating diagram D of K. Katie Walsh Hall Patterns and Higher Order Stability 42 / 68

46 A k + 1-stable sequence satisfies: k+1 lim J N+1,K (q) q j(n+1) Φ j (q) = 0. N q (k+1)(n+1) j=0 The first k(n + 1) coefficients of J N+1,K (q) match k j=0 qj(n+1) Φ j for large enough N. This does not guarantee this property from the beginning. Katie Walsh Hall Patterns and Higher Order Stability 43 / 68

47 Order 1st Order Stabilization of Coefficients Which knots stabilize to the same sequence? What do they stablize to? Higher Order adequate links? for alternating links in some cases? Katie Walsh Hall Patterns and Higher Order Stability 44 / 68

48 Corollary Let m be the minimum number of parallel edges in a diagram. In addition to the first N + 1 terms only depending on the overall graph structure, the next (m 1)N terms also depend only on the graph structure. Corollary To find Φ k, we can consider the graph diagram reduced so that multiples edges with multiplicity greater than k are reduced to k multiple edges. Katie Walsh Hall Patterns and Higher Order Stability 45 / 68

49 Order 1st Order Stabilization of Coefficients Which knots stabilize to the same sequence? What do they stablize to? Higher Order adequate links in some cases for alternating links? Katie Walsh Hall Patterns and Higher Order Stability 46 / 68

50 m 1 m 2 m 3 Figure: A knot with its checkerboard graph. Katie Walsh Hall Patterns and Higher Order Stability 47 / 68

51 J N+1,K (q) = m 1 m 2 m 3 = N 3 j i =0 i=1 2ji θ(n, N, 2j i ) m 1 m 2 m3 2 j1 2 j2 2 j3 = N j i =0 i=1 3 γ(n, N, 2j i ) m i 2ji θ(n, N, 2j i ) 2j1 2j2 2j3 = N j i =0 i=1 3 γ(n, N, 2j i ) m i 2ji θ(n, N, 2j i ) Γ N,(j 1,j 2,j 3 ) Katie Walsh Hall Patterns and Higher Order Stability 48 / 68

52 Fusion a b n = = c n c θ(a, b, c) a c a b b (1) = ( 1) n [n + 1] (2) where [n] = {n} {1}, {n} = A2n A 2n and A 4 = a 2 = q. (3) Katie Walsh Hall Patterns and Higher Order Stability 49 / 68

53 Fusion a b = c c θ(a, b, c) a b c a b (4) Assume (a, b, c) is an admissible triple, then let i, j, k be the internal colors, in particular i = (b + c a)/2 j = (a + c b)/2 k = (a + b c)/2. (5) θ(a, b, c) = a b c i+j+k [i + j + k + 1]![i]![j]![k]! = ( 1). (6) [i + j]![j + k]![i + k]! Katie Walsh Hall Patterns and Higher Order Stability 50 / 68

54 J N+1,K (q) = m 1 m 2 m 3 = N 3 j i =0 i=1 2ji θ(n, N, 2j i ) m 1 m 2 m3 2 j1 2 j2 2 j3 = N j i =0 i=1 3 γ(n, N, 2j i ) m i 2ji θ(n, N, 2j i ) 2j1 2j2 2j3 = N j i =0 i=1 3 γ(n, N, 2j i ) m i 2ji θ(n, N, 2j i ) Γ N,(j 1,j 2,j 3 ) Katie Walsh Hall Patterns and Higher Order Stability 51 / 68

55 Twist Coefficients with b a b c = γ(a, b, c) a c (7) γ(a, b, c) = ( 1) a+b c 2 A a+b c+ a2 +b 2 c 2 2. (8) Katie Walsh Hall Patterns and Higher Order Stability 52 / 68

56 J N+1,K (q) = m 1 m 2 m 3 = N 3 j i =0 i=1 2ji θ(n, N, 2j i ) m 1 m 2 m3 2 j1 2 j2 2 j3 = N j i =0 i=1 3 γ(n, N, 2j i ) m i 2ji θ(n, N, 2j i ) 2j1 2j2 2j3 = N j i =0 i=1 3 γ(n, N, 2j i ) m i 2ji θ(n, N, 2j i ) Γ N,(j 1,j 2,j 3 ) Katie Walsh Hall Patterns and Higher Order Stability 53 / 68

57 m-reduced graph Corollary Proof Label edge sets with m or more parallel edges 1 through b. J N+1,K = N j 1,...j k =0 i=1 k γ(n, N, 2j i ) m i (m+1)n = γ(n, N, 2N) b i=1 m i N k j b+1,...,j k =0 i=b+1 γ(n, N, 2j i ) m i 2ji θ(n, N, 2j i ) Γ N,(j 1,...,j k ) k i=1 2ji θ(n, N, 2j i ) Γ N,(N,...,N,j b+1,...,j k Again, since γ(n, N, 2N) only contributes an overall shift, we get the same highest (m + 1)N coefficients regardless of the values of m 1,..., m b and thus knots with the same m + 1-reduced graph structure have the same highest (m + 1)N coefficients. (9) Katie Walsh Hall Patterns and Higher Order Stability 54 / 68

58 J N+1,K (q) = N j i =0 i=1 3 γ(n, N, 2j i ) m i 2ji θ(n, N, 2j i ) Γ N,(j 1,j 2,j 3 ) What terms contribute to the first 2N + 1 coefficients? Katie Walsh Hall Patterns and Higher Order Stability 55 / 68

59 J N+1,K (q) = N j i =0 i=1 3 γ(n, N, 2j i ) m i 2ji θ(n, N, 2j i ) Γ N,(j 1,j 2,j 3 ) What terms contribute to the first 2N + 1 coefficients? either all j i = N or exactly one j i = N 1 and the rest are N Katie Walsh Hall Patterns and Higher Order Stability 55 / 68

60 In the case where each m i is greater than 2, the maximum degree decreases by more than 2N when we decrease j i from N to N 1, thus we only need to deal with the case where each j i = N. Thus we get J N+1,K (q) = 2N+1 = N j i =0 i=1 3 γ(n, N, 2j i ) m i 3 γ(n, N, 2N) m i i=1 = γ(n, N, 2N) m 1+m 2 +m 3 ( = 2N+1 = = ( 1){N}! 3 {N}! 2 ( 1 2q N 1 1 q 1 ) {1} ( 1){N}! ( ). 1 2q N 1 {1} 1 q 1 2ji θ(n, N, 2j i ) Γ N,(j 1,j 2,j 3 ) 2N θ(n, N, 2N) Γ N,(N,N,N) 2N θ(n, N, 2N) ) 3 ( ) ΓN,(N,N,N) Katie Walsh Hall Patterns and Higher Order Stability 56 / 68

61 J N+1,K (q) stabilized head 2N+1 ( ( ) = ( 1) N {N}! 1 + 2q N 1 + q N 1 1 q 1 ) (1 ) q N 1 1 q 1 ) = ( 1) N {N}! (q N 1 + 3q N 1 1 q ( 1 = ( 1) N q N 1 {N}! + 3{N}! ) 1 q 1 = N (1 q i ) + 3 N i=1 (1 q i ) 1 q 1. i=1 Katie Walsh Hall Patterns and Higher Order Stability 57 / 68

62 2N When an m i is 1, we do get a term with j i = N 1. Need to consider the graph Γ(N + 1, N 1, N 1) and its evaluation. N 1 N-1 N-1 N 1 N N 2N N N Katie Walsh Hall Patterns and Higher Order Stability 58 / 68

63 2N 2N N 1 N-1 N-1 N 1 N N 2N N N 1 N-1 1 N-1 N-1 N-1 1 N-1 1 N-1 2N N Γ N,(N 1,N,N) = Γ(N + 1, N 1, N 1)). N Katie Walsh Hall Patterns and Higher Order Stability 59 / 68

64 Theorem (KPWH) Let m be the number edges in the checkerboard graph with m i of 2 or more. The tailneck of knots whose reduced checkboard graph is the triangle graph is: n=1 (1 q n n=1 ) + m (1 qn ), 1 q i.e. the pentagonal numbers plus the m times the partial sum of the pentagonal numbers. Katie Walsh Hall Patterns and Higher Order Stability 60 / 68

65 Oliver Dasbach suggested the following: Redefine the neck and tail neck by subtracting consecutive terms in sequence, shifted so that they have the same minimum degree. This gives us a simpler expression for the higher order stable pieces. Katie Walsh Hall Patterns and Higher Order Stability 61 / 68

66 Oliver Dasbach suggested the following: Redefine the neck and tail neck by subtracting consecutive terms in sequence, shifted so that they have the same minimum degree. Corollary This gives us a simpler expression for the higher order stable pieces. Again, let m be the number edges in the checkerboard graph with m i of 2 or more. Then we have J N,K q J N+1,K N = (1 + m q) (1 q n ). n=1 Katie Walsh Hall Patterns and Higher Order Stability 61 / 68

67 If we want the first 3N + 1 terms, which terms in the sum contribute? Labeling (up to permutation) Increase in min degree from (N, N, N) (N, N, N) 0 (N, N, N 1) at least N + 1 (N, N, N 2) at least 2N + 1 (N, N 1, N 1) at least 2N + 2 (N, N, N 3) at least 3N 1 (N, N 1, N 2) at least 3N + 1 (N 1, N 1, N 1) at least 3N + 3 Katie Walsh Hall Patterns and Higher Order Stability 62 / 68

68 2N The Graph Γ N,(N,N 1,N 1) N N 1 N-1 N-1 1 N N 2N N N 1 N-1 1 N We can absorb the smaller idempotents into the larger ones and combine adjoining ones. N 1 N-1 N-1 N-1 1 N-1 N-1 1 N-1 Katie Walsh Hall Patterns and Higher Order Stability 63 / 68

69 2N We resolve the remaining N idempotents ( but ) only one of the terms is N 2 non-zero. We get a factor of N 1 from each resolution. N-1 1 N-1 N-2 N-2 N-1 N N-1 2N N-1 We can then absorb the remaining N 1 idempotents. N-2 1 N-1 N-1 The evaluation of Γ N,(N,N 1,N 1) = ( N 2 N 1 ) 2 Γ(N, N, N 2). Katie Walsh Hall Patterns and Higher Order Stability 64 / 68

70 Let s look at the next stable sequence for these knots: q (2N+2) (q(ĵ N,K Ĵ N+1,K ) (Ĵ N+1,K Ĵ N+2,K ))/ (1 q i ) i=1 Katie Walsh Hall Patterns and Higher Order Stability 65 / 68

71 Values of (m 1, m 2, m 3 ) T1 T2 : 1 q q2 q 3 q 4 (up to permutation) (1, 1, 1) 1 q (1, 1, 2) 2 q (1, 1, 3 + ) 2 q (1, 2, 2) 3 q (1, 2, 3 + ) 3 q (1, 3 +, 3 + ) 3 q (2, 2, 2) 4 q (2, 2, 3 + ) 4 q (2, 3 +, 3 + ) 4 q (3 +, 3 +, 3 + ) 4 q Katie Walsh Hall Patterns and Higher Order Stability 66 / 68

72 Question What information is contained these coefficients? Katie Walsh Hall Patterns and Higher Order Stability 67 / 68

73 Question What information is contained these coefficients? More questions: Can we prove that these are the stable sequences? Can we get a geometric proof of stability for all knots? What does the stable sequence look like for other families of knots or for even higher stability? Can these sequences help us understand the middle coefficients? Katie Walsh Hall Patterns and Higher Order Stability 67 / 68

74 Any Questions?