2 n intervals in the attractor of the tent map

Size: px
Start display at page:

Download "2 n intervals in the attractor of the tent map"

Transcription

1 2 n intervals in the attractor of the tent map Peter Barendse revised December 2010 Abstract In this paper we give a elementary proof explaining the phenomenon of band-splitting, first explained in [2, 1] and seen most notably in the attractors of certain one-parameter, unimodal maps such as the tent map on the unit interval. We show that there are parameters values, ɛ 0 > ɛ 1 > ɛ 2 such that for any n N, if the parameter is in the interval [1 + ɛ n+1, 1 + ɛ n ), then the attractor consists of exactly 2 n disjoint closed intervals and 2 n isolated points. For the tent map, this parameter is the slope of the tent map. The proof consists of an analytic argument to show that the endpoints of these intervals, which are the iterates of the critical point 1/2, are found in a certain order, then a simple linear mapping argument. 1 Introduction This paper concerns a particular pattern of bifurcations found in the dynamics of many iterated maps, including unimodal maps on the unit interval, perhaps the simplest example being the tent map: { f 1+ɛ (x) = where ɛ << 1. (1 + ɛ)x if x 1/2 (1 + ɛ)(1 x) if x > 1/2 Given any map f : X X, the orbit of a point x X is the sequence is {x, f(x), f 2 (x),...} of successive iterates of x by f. A map is called unimodal if it has only one critical point, c. The orbit of this point we will call the critical sequence, C(f) = c 0 = c, c 1 = f(c), c 2 = f 2 (c),.... The kneading sequence K(f) = k 0, k 1,... is given by k n = sgn(f n (c) 1 2 ) (1 if f n (c) > 1 2, 1 if f n (c) < 1 2, 0 if f n (c) = 1 2 ). These sequences keep track of the successive folds of the unit interval. In a unimodal map they tell nearly all there is to know 1

2 about the dynamics, since the only other action is a varying degree of stretching/compression along the interval. In the case of the tent map f 1+ɛ, each iteration folds the unit interval once at the critical point 1 2, then stretches (by a constant linear factor 1 + ɛ), bringing it back into itself. An attractor is the minimal set Y X toward which every orbit in its basin of attraction (an open set containing Y ) eventually goes. More concretely, In this paper we are interested in the attractor of the entire unit interval., which is that certain maps exhibit what has been called a infinite band-splitting sequence of bifurcations as the parameter approaches a certain value [2, 1]. This following will be the basis for an induction argument to show the main theorem. Theorem 1.1. For any continuous unimodal map of the unit interval into itself such that the critical point c is a maximum and f(x) > x for all x < c, the attractor of the unit interval is contained in [c 2, c 1 ] Proof. Since c is a maximum, the attractor must lie in [0, c 1 ]. Since f is increasing for all x < c, every such point must eventually fall into [c 0, c 1 ]. Since f has only one critical point, which is a maximum, the minimum value f takes on any interval must be an endpoint of that interval. Therefore [c 0, c 1 ] is mapped onto [c 2, c 1 ], and [c 2, c 1 ] is mapped into [c 2, c 1 ], since c 1 is greater than the unique fixed point p of f, and so c 2 < p, so c 2 < c 3. Typically, band-splitting occurs in the attractor when the critical sequence satisfies a particular ordering relationship in which the first 2 n iterates of c are split into pairs by the next 2 n iterates: Let x <> y <> <> z mean that x > y > > z or x < y < < z, and [x <> y] to mean the interval [x, y] or [y, x]. We say a sequence of real numbers satisfies the condition O n if: (1) c 2 < c 1 (2) for every i n, c 2 i 1 <> c 2 i 1 +2 i <> c 2 i+1 <> c 0 <> c 2 i (2) for every i n, c 2i +1 < c 2 i+1 +1 O n is a sufficient condition for band-splitting to occur up to the point of having 2 n bands: Theorem 1.2. If f is a continuous unimodal map on the unit interval, and C(f) satisfies O n, then k 2 n[c k <> c k+2 n] is closed under f. If, 2

3 in addition, sup{(f (x)) n 1 : x [b, a]} < c 1+2 n 1 +2 n c 1+2 n c 1+2 n 1 +2 n c 1+2 n c 1+2 n+1 c 1+2 n 1 +2 n, then the attractor of the unit interval is contained in k 2 n[c k <> c k+2 n]. Proof. The proof proceeds by induction on n. We have already shown the case n = 0 in the previous theorem. Now suppose the theorem holds for all i < n, and f satisfies O n.in other words, assuming that every orbit eventually falls into the 2 n 1 intervals, {[c k <> c k+2 n 1] : 1 k 2 n 1 }, we wish to show using O n that every orbit eventually falls into the 2 n intervals, {[c k <> c k+2 n] : k 2 n }. First note that (2) and (3) of O n imply that c 1 > c 1+2 n+1 > c 1+2 n > c 1+2 n 1 +2 n > c 1+2 n 1. Since f is monotonic on each of the other 2 n 1 1 intervals, we have recursively that for every k < 2 n 1, c k <> c k+2 n <> c k+2 n 1 +2 n <> c k+2 n 1. So the ordering of the iterates is such that each interval [c k <> c k+2 n 1] is therefore broken into three subintervals: [c k <> c k+2 n], [c k+2 n <> c k+2 n 1 +2 n], and [c k+2 n 1 +2 n <> c k+2n 1] so that the leftand right-subintervals (which are disjoint) contain the attractor, after the band-splitting has occurred. We first show that these outer subintervals are closed under f. We then show that orbits in the middle subintervals eventually leave for the outer intervals. First the left- an right-subintervals, {[c k <> c k+2 n] : 1 k 2 n }. Since only [c 2 n <> c 2 n+1] contains the critical point, f is monotonic the other 2 n 1 intervals, so f([c 1 <> c 2n +1]) = [c 1 <> c 2n +1], f([c 2 <> c 2n +2]) = [c 3 <> c 2n +3],. f([c 2 n 1 <> c 2 n+1 1]) = [c 2 n <> c 2 n+1]. Finally, since c 2 n+1 +1 [c 1 <> c 2 n +1] and c 0 [c 2 n O n, <> c 2 n+1] by f([c 2 n <> c 2 n+1]) = [c 1 <> c 2 n +1], completing the cycle. Note that this last map is done with a fold. Without this fold band-splitting could not occur on a continuous map. The middle intervals, [c k+2 n <> c k+2 n 1 +2 n] for k 2n 1, also map into each other, by monotonicity: 3

4 f([c 1+2 n <> c 1+2 n 1 +2 n]) = [c 2+2 n <> c 2+2 n 1 +2 n], f([c 2+2 n <> c 2+2 n 1 +2 n]) = [c 3+2 n <> c 3+2 n 1 +2 n],. f([c 2 n n <> c 2 n n 1 +2 n]) = [c 2 n 1 +2 n <> c 2 n+1] However, the last interval does not: f([c 2 n 1 +2 n <> c 2 n+1]) = [c 1+2 n+1 <> c 1+2 n 1 +2 n] [c 1+2 n <> c 1+2 n 1 +2 n]. Since c 2 n+1 +1 [c 1 <> c 2 n +1], part of the middle interval escapes to the outer pair of intervals with each iteration of f 2n 1. To show that every orbit in the middle interval eventually leaves, so that the attractor is contained by the 2 n+1 outer intervals and our induction is complete, we must take a closer look. Denote c 1+2 n 1 +2 n by a, c 1+2 n by b, and c 2n 1 1+2n+1 by c. Then f maps [b, a] onto [b, c] (or [a, b] onto [c, b], which is essentially the same) by sending a to b and b to c. Let s = a c, and λ = sup{(f (x)) n 1 : x [b, a]}. Then (at least) [b, b + s λ ] escapes after the first application of f 2n 1, [a s λ, a] after the second, etc., since we know a segment is 2 taken off alternating ends of [b, a] by each application of f 2n 1, and if less were taken off, then by the mean value theorem, some point would have to have (f (x)) n 1 > λ (or undefined), contrary to our assumptions. The total length removed is therefore at least n=1 s λ = s n 1 1/λ So, all orbits eventually fall into the outer pair of intervals if the total length s 1 1/λ > a b, i.e., if λ < c a. For the tent map, λ = 1 + ɛ, and the intervals [b, b s s λ ], [a + λ ], 2 etc. are exactly the pieces taken out by successive applications of f 2n 1. Equivalently, since the stretching factor is constant for the tent map, λ =, all orbits leave the middle interval [a, b] iff b c < b c c a, i.e., iff ɛ < c a 1. This is a critical value of ɛ where band-splitting occurs. If, ɛ = c a 1, then the total length removed is equal to a b, but since it is being taken from both sides, orbits all leave that middle interval except one: a s n=1 λ = b+ s 2n n=1 λ. This point is periodic of period 2 n 1, 2n 1 since it must map to a similar point in each of the other 2 n 1 other 4

5 middle intervals. In the next section we see exactly how the tent map satisfies O n, for any given n. 2 A deep analysis of the critical sequence of the tent map In this section we gain a full understanding of critical sequence of the tent map, f 1+ɛ, and similar unimodal maps. In particular we will see how the critical sequence of the tent map satisfies O n for all ɛ < some ɛ n, and the exact ordering of the iterates (resloving every <> into < or >). We do this by looking at the critical sequence in the limit as ɛ 0. What we do, in effect, is create a new dynamical system on a space of polynomials (or infinite sequences if we wish). While this system may not be realized in the actual tent map (for any parameter value), the important characteristics of the behavior of the tent map limits on those of this new system. Definition 2.1. Let {P n, n N} be the limiting sequence of polynomials in ɛ given by the n th iterate of 1 2 : P n = lim ɛ 0 f n 1+ɛ( 1 2 ). Note that P n has degree n, and that the constant term is always 1 2. The first sixteen P n are listed in Appendix A. Definition 2.2. Define a linear ordering by P n P n if lim ɛ 0 sgn(p n P n ) = 1. The coefficient of ɛ i in P n we denote Ci n, and the smallest power of ɛ (other than ɛ 0 ) whose coefficient is not zero we denote min(n). Note that for every n, there is some ν so that f1+ɛ( n 1 2 ) = P n for all ɛ < ν, and, for every n and n, if P n P n, then there is some ν so that f1+ɛ( n 1 2 ) < f 1+ɛ( n 1 2 ) for all ɛ < ν. When ɛ is sufficiently small, analysis shows that P n > 1 2 iff the sign of the least nonzero coefficient, Cmin(n) n, is positive. Thus P n can be computed by P n 1 using the relationship C n+1 i = sgn(c n min(n) )(Cn i + C n i 1). (1) 5

6 We first show that the P n satisfy a certain algebraic property, which we will use to deduce the ordering of the critical sequence. Lemma 2.3. For every i the sequence of coefficients Ci 1, C2 i,... is cyclic of length 2 i. Furthermore, min(2 i ) = i + 1, and Ci+1 2i > 0 (and therefore P 2 i ) iff i even. 1 2 Proof. We proceed by induction on i. It is easy to check that C n 1 = 1 2 if n is odd and C n 1 = 0 if n is even. Therefore C n 1 is cyclic of length 2, and min(2) = 2 and C 2 2 < 0. It is also easy to check that min(4) = 3 and C 4 3 > 0. Assume Ci n is cyclic of length 2i, for all i < N, and min(2 N ) = N+1, and CN+1 2N > 0 iff N is even. Since C2N N = C0 N (both are 0), and because CN n is only affected by the coefficients Cn i, for i < N, which are all cyclic of length 2 N, it follows that C 2N +1 N = CN 1, +2 C2N N = CN 2,.... So CN n is cyclic of length 2N also. Notice also that for all n < 2 N+1, the coefficients C0 n,... CN+1 n are not all 0. This is because for all n < 2 N+1, n = 2 k + 2 k+1 s for some k N and some s N (as can be easily shown by induction on N). So, by the previous paragraph and the inductive assumption, Ck+1 n = C2k k+1 = C2k min(2 k ) 0. We now show that min(2 N+1 ) = N + 2, and CN+2 2N+1 we first show that CN+1 2N+1 = 0. < 0. To do this, Using the basic relationship among coefficients, we have, for any n N: C 0 n+1 = 0, C 1 n+1 = sgn(c 0 min(0) )(C0 n + 0), C 2 n+1 = sgn(c 1 min(1) )(C1 n sgn(c 0 min(0) )(C0 n + 0)),. C 2n n+1 = sgn(c 2n 1 1 min(2 n 1) )(C2n n sgn(c 2n 2 min(2 n 2) ) (C1 n sgn(c 0 min(0) )(C0 n+ 0)) ) now let S = C 2n n+1 > 0. Then: C 2n +1 n+1 = sgn(c2n min(2 n ) )(C2n n + S), C 2n +2 n+1 = sgn(c2n min(2 n +1) )(C2n n sgn(c 2n min(2 n ) )(C2n n + S)),. C 2n +2 n n+1 = sgn(c 2n +2 n 1 +2 n 1 min(2 n +2 n 1) )(C2n n sgn(c 2n +2 n 2 min(2 n +2 n 2) ) +1 (C2n n 6

7 sgn(c 2n min(2 n ) )(C2n n + S)) ) Rearranging and simplifying, C 2n +2 n n+1 = sgn(c 2n +2 n 1 +2 n 1 min(2 n +2 n 1) )(C2n n sgn(c 2n +2 n 2 min(2 n +2 n 2) ) +1 (C2n n sgn(c 2n min(2 n ) )(C2n n )) ) + ( 1) 2n S 2 n+1 1 i=2 n sgn(ci min(i) ) Using the cyclicity of coefficients, and the fact that the coefficients C n 0,... C n n+1 are not all 0, so that sgn(c i min(i) ) = sgn(ci min(i) ) for 1 i < 2 n. C 2n +2 n n+1 = sgn(c 2n +2 n 1 +2 n 1 min(2 n +2 n 1) )(C2n n sgn(c 2n +2 n 2 min(2 n +2 n 2) ) +1 (C2n n sgn(c 2n min(2 n ) )(C2n n )) ) + S 2 n i=1 sgn(ci min(i) ) Since the first term is identical to S, we have, for all n N, C 2n+1 n+1 = S + S 2 n i=1 sgn(c i min(i) ) (2) But for all n < N, we assumed C 2n+1 n+1 = 0, so 2 n i=1 sgn(ci min(i) ) = 1. By repeated use of this fact, we get: 2 N i=1 sgn(ci min(i) ) = sgn(c 2N min(2 N ) )( 2 N 1 i=2 N 1 sgn(ci min(i) )) ( i=2 sgn(ci min(i) ))sgn(c1 min(1) ) = sgn(c 2N min(2 N ) )( 1)N 1 Therefore, CN+1 2N+1 = S+S 2 N i=1 sgn(ci min(i) ) = S+Ssgn(C2N min(2 N ) )( 1)N 1, and since we assumed Cmin(2 2N N ) = C2N N+1 > 0 iff N is even, sgn(c2n min(2 N ) )( 1)N 1 = 1, for either N even or odd. So CN+1 2N+1 = 0. Finally, since C 2N+1 1 N+1 and C 2N+1 1 N+2 have the same sign, CN+2 2N+1 = sgn(c 2N+1 1 )(C2N+1 1 min(2 N+1 1) N+2 + C 2N+1 1 N+1 ) < 0 iff N is even. We now use this lemma to deduce the ordering of the critical sequence: Theorem 2.4. For every n, there is some ɛ n > 0 such that the critical sequence C(f 1+ɛ ) satisfies O n wherever 0 < ɛ < ɛ n. 7

8 Proof. We show that {P n, n N} satisfies O n with the ordering. Since O n involves only finitely many order relations, and each is satisfied whenever ɛ is less than some positive value, we can take the minimum of these values for ɛ n to conclude that {c n, n N} satisfies O n wherever 0 < ɛ < ɛ n. Again we proceed by induction on n. Clearly P P 4 P 3 P 1, so O 0 holds. Now suppose the theorem holds for all n up to some even N. Since we assume O N 1 holds, we have by Theorem 1.2 in the previous section that the attractor is contained in k 2 N 1[P k P k+2 N 1], and these intervals map one into the other, in a cycle. We also know the last of these intervals is [P 2 N 1, P 2 N ], by the lemma. So P 2 N +2 N 1 and P 2 N+1 are in the interval [P 2 N 1, P 2N ], since they are the images of P 2 N by 2 N 1 k applications of f 1+ɛ, for some k N. We must only show that P 2 N +2 N 1 P 2 N By the lemma, Cmin(2 2N 1 N 1 ) = C2N 1 N < 0. Since the coefficients Ci 1, C2 i,... are cyclic of length 2i, for every i N, they are all also cyclic of length 2 N. Therefore, C 2N 1 i = C 2N +2 N 1 i C 2N +2 N 1 min(2 N +2 N 1 ) = C2N +2 N 1 N < 0. So P 2N +2 N for any i N. So Also by the lemma, Cmin(2 2N+1 N+1 ) = C2N+1 N+1 < 0, but since this coefficient is of greater degree, lim ɛ 0 sgn(p 2 N+1 P 2N +2 N 1) = +2 N 1 sgn( C2N N > 0, so P 2N +2 N 1 P 2 N+1. In the case N is odd, replace every by, and vice versa. Question 2.5. Can O n be achieved with a different ordering of intervals? Acknowledgements The author would like to thank James Burgmeier, Jeff Dinitz, and Jianke Yang for their encouragement and guidance, as well as Ivan Zaigrallin for pointing out the possibility of the isolated points. 8

9 3 Appendix: the first sixteen iterates of 1 2, as polynomials in ɛ Figure 1: the first 16 P n References [1] H. Shigematsu, H. Mori, T. Yoshida, and H. Okamoto. Analytic study of power spectra of the tent maps near band-splitting transitions. Journal of Statistical Physics, 30: , /BF [2] T. Yoshida, H. Mori, and H. Shigematsu. Analytic study of chaos of the tent map: Band structures, power spectra, and critical behaviors. Journal of Statistical Physics, 31: , /BF

Discrete dynamics on the real line

Discrete dynamics on the real line Chapter 2 Discrete dynamics on the real line We consider the discrete time dynamical system x n+1 = f(x n ) for a continuous map f : R R. Definitions The forward orbit of x 0 is: O + (x 0 ) = {x 0, f(x

More information

CHAOTIC UNIMODAL AND BIMODAL MAPS

CHAOTIC UNIMODAL AND BIMODAL MAPS CHAOTIC UNIMODAL AND BIMODAL MAPS FRED SHULTZ Abstract. We describe up to conjugacy all unimodal and bimodal maps that are chaotic, by giving necessary and sufficient conditions for unimodal and bimodal

More information

Math 354 Transition graphs and subshifts November 26, 2014

Math 354 Transition graphs and subshifts November 26, 2014 Math 54 Transition graphs and subshifts November 6, 04. Transition graphs Let I be a closed interval in the real line. Suppose F : I I is function. Let I 0, I,..., I N be N closed subintervals in I with

More information

PERIODIC POINTS OF THE FAMILY OF TENT MAPS

PERIODIC POINTS OF THE FAMILY OF TENT MAPS PERIODIC POINTS OF THE FAMILY OF TENT MAPS ROBERTO HASFURA-B. AND PHILLIP LYNCH 1. INTRODUCTION. Of interest in this article is the dynamical behavior of the one-parameter family of maps T (x) = (1/2 x

More information

MAT1000 ASSIGNMENT 1. a k 3 k. x =

MAT1000 ASSIGNMENT 1. a k 3 k. x = MAT1000 ASSIGNMENT 1 VITALY KUZNETSOV Question 1 (Exercise 2 on page 37). Tne Cantor set C can also be described in terms of ternary expansions. (a) Every number in [0, 1] has a ternary expansion x = a

More information

Finding numerically Newhouse sinks near a homoclinic tangency and investigation of their chaotic transients. Takayuki Yamaguchi

Finding numerically Newhouse sinks near a homoclinic tangency and investigation of their chaotic transients. Takayuki Yamaguchi Hokkaido Mathematical Journal Vol. 44 (2015) p. 277 312 Finding numerically Newhouse sinks near a homoclinic tangency and investigation of their chaotic transients Takayuki Yamaguchi (Received March 13,

More information

... it may happen that small differences in the initial conditions produce very great ones in the final phenomena. Henri Poincaré

... it may happen that small differences in the initial conditions produce very great ones in the final phenomena. Henri Poincaré Chapter 2 Dynamical Systems... it may happen that small differences in the initial conditions produce very great ones in the final phenomena. Henri Poincaré One of the exciting new fields to arise out

More information

TOPOLOGICAL EQUIVALENCE OF REAL BINARY FORMS

TOPOLOGICAL EQUIVALENCE OF REAL BINARY FORMS proceedings of the american mathematical society Volume 112, Number 4. August 1991 TOPOLOGICAL EQUIVALENCE OF REAL BINARY FORMS DAVID WEINBERG AND DAVE WITTE (Communicated by Frederick R. Cohen) Abstract.

More information

Real Variables: Solutions to Homework 3

Real Variables: Solutions to Homework 3 Real Variables: Solutions to Homework 3 September 3, 011 Exercise 0.1. Chapter 3, # : Show that the cantor set C consists of all x such that x has some triadic expansion for which every is either 0 or.

More information

Sufficient conditions for a period incrementing big bang bifurcation in one-dimensional maps.

Sufficient conditions for a period incrementing big bang bifurcation in one-dimensional maps. Sufficient conditions for a period incrementing big bang bifurcation in one-dimensional maps. V. Avrutin, A. Granados and M. Schanz Abstract Typically, big bang bifurcation occur for one (or higher)-dimensional

More information

Jim Lambers MAT 460 Fall Semester Lecture 2 Notes

Jim Lambers MAT 460 Fall Semester Lecture 2 Notes Jim Lambers MAT 460 Fall Semester 2009-10 Lecture 2 Notes These notes correspond to Section 1.1 in the text. Review of Calculus Among the mathematical problems that can be solved using techniques from

More information

Math 320: Real Analysis MWF 1pm, Campion Hall 302 Homework 8 Solutions Please write neatly, and in complete sentences when possible.

Math 320: Real Analysis MWF 1pm, Campion Hall 302 Homework 8 Solutions Please write neatly, and in complete sentences when possible. Math 320: Real Analysis MWF pm, Campion Hall 302 Homework 8 Solutions Please write neatly, and in complete sentences when possible. Do the following problems from the book: 4.3.5, 4.3.7, 4.3.8, 4.3.9,

More information

2 Problem Set 2 Graphical Analysis

2 Problem Set 2 Graphical Analysis 2 PROBLEM SET 2 GRAPHICAL ANALYSIS 2 Problem Set 2 Graphical Analysis 1. Use graphical analysis to describe all orbits of the functions below. Also draw their phase portraits. (a) F(x) = 2x There is only

More information

Sydney University Mathematical Society Problems Competition Solutions.

Sydney University Mathematical Society Problems Competition Solutions. Sydney University Mathematical Society Problems Competition 005 Solutions 1 Suppose that we look at the set X n of strings of 0 s and 1 s of length n Given a string ɛ = (ɛ 1,, ɛ n ) X n, we are allowed

More information

SUBCONTINUA OF FIBONACCI-LIKE INVERSE LIMIT SPACES.

SUBCONTINUA OF FIBONACCI-LIKE INVERSE LIMIT SPACES. SUBCONTINUA OF FIBONACCI-LIKE INVERSE LIMIT SPACES. H. BRUIN Abstract. We study the subcontinua of inverse limit spaces of Fibonacci-like unimodal maps. Under certain combinatorial constraints no other

More information

Fractals and Dimension

Fractals and Dimension Chapter 7 Fractals and Dimension Dimension We say that a smooth curve has dimension 1, a plane has dimension 2 and so on, but it is not so obvious at first what dimension we should ascribe to the Sierpinski

More information

Chapter 4. Measure Theory. 1. Measure Spaces

Chapter 4. Measure Theory. 1. Measure Spaces Chapter 4. Measure Theory 1. Measure Spaces Let X be a nonempty set. A collection S of subsets of X is said to be an algebra on X if S has the following properties: 1. X S; 2. if A S, then A c S; 3. if

More information

Symbolic dynamics for Lozi maps

Symbolic dynamics for Lozi maps Symbolic dynamics for Lozi maps M. Misiurewicz, S. Štimac Abstract We study the family of the Lozi maps L a,b : R 2 R 2, L a,b (x, y) = (1+y a x, bx), and their strange attractors Λ a,b. We introduce the

More information

Signed Measures. Chapter Basic Properties of Signed Measures. 4.2 Jordan and Hahn Decompositions

Signed Measures. Chapter Basic Properties of Signed Measures. 4.2 Jordan and Hahn Decompositions Chapter 4 Signed Measures Up until now our measures have always assumed values that were greater than or equal to 0. In this chapter we will extend our definition to allow for both positive negative values.

More information

Dynamical Systems 2, MA 761

Dynamical Systems 2, MA 761 Dynamical Systems 2, MA 761 Topological Dynamics This material is based upon work supported by the National Science Foundation under Grant No. 9970363 1 Periodic Points 1 The main objects studied in the

More information

Induction, sequences, limits and continuity

Induction, sequences, limits and continuity Induction, sequences, limits and continuity Material covered: eclass notes on induction, Chapter 11, Section 1 and Chapter 2, Sections 2.2-2.5 Induction Principle of mathematical induction: Let P(n) be

More information

CH 2: Limits and Derivatives

CH 2: Limits and Derivatives 2 The tangent and velocity problems CH 2: Limits and Derivatives the tangent line to a curve at a point P, is the line that has the same slope as the curve at that point P, ie the slope of the tangent

More information

Set, functions and Euclidean space. Seungjin Han

Set, functions and Euclidean space. Seungjin Han Set, functions and Euclidean space Seungjin Han September, 2018 1 Some Basics LOGIC A is necessary for B : If B holds, then A holds. B A A B is the contraposition of B A. A is sufficient for B: If A holds,

More information

Solutions to Homework Assignment 2

Solutions to Homework Assignment 2 Solutions to Homework Assignment Real Analysis I February, 03 Notes: (a) Be aware that there maybe some typos in the solutions. If you find any, please let me know. (b) As is usual in proofs, most problems

More information

We are going to discuss what it means for a sequence to converge in three stages: First, we define what it means for a sequence to converge to zero

We are going to discuss what it means for a sequence to converge in three stages: First, we define what it means for a sequence to converge to zero Chapter Limits of Sequences Calculus Student: lim s n = 0 means the s n are getting closer and closer to zero but never gets there. Instructor: ARGHHHHH! Exercise. Think of a better response for the instructor.

More information

Lebesgue Measure on R n

Lebesgue Measure on R n CHAPTER 2 Lebesgue Measure on R n Our goal is to construct a notion of the volume, or Lebesgue measure, of rather general subsets of R n that reduces to the usual volume of elementary geometrical sets

More information

Lecture3 The logistic family.

Lecture3 The logistic family. Lecture3 The logistic family. 1 The logistic family. The scenario for 0 < µ 1. The scenario for 1 < µ 3. Period doubling bifurcations in the logistic family. 2 The period doubling bifurcation. The logistic

More information

Counting Kneading Sequences. Vorrapan Chandee & Tian Tian Qiu

Counting Kneading Sequences. Vorrapan Chandee & Tian Tian Qiu CORNE UNIVERSITY MATHEMATICS DEPARTMENT SENIOR THESIS Counting Kneading Sequences A THESIS PRESENTED IN PARTIA FUFIMENT OF CRITERIA FOR HONORS IN MATHEMATICS Vorrapan Chandee & Tian Tian Qiu May 2004 BACHEOR

More information

Unbounded Regions of Infinitely Logconcave Sequences

Unbounded Regions of Infinitely Logconcave Sequences The University of San Francisco USF Scholarship: a digital repository @ Gleeson Library Geschke Center Mathematics College of Arts and Sciences 007 Unbounded Regions of Infinitely Logconcave Sequences

More information

Definitions & Theorems

Definitions & Theorems Definitions & Theorems Math 147, Fall 2009 December 19, 2010 Contents 1 Logic 2 1.1 Sets.................................................. 2 1.2 The Peano axioms..........................................

More information

Multi-coloring and Mycielski s construction

Multi-coloring and Mycielski s construction Multi-coloring and Mycielski s construction Tim Meagher Fall 2010 Abstract We consider a number of related results taken from two papers one by W. Lin [1], and the other D. C. Fisher[2]. These articles

More information

Lozi-like maps. M. Misiurewicz and S. Štimac. May 13, 2017

Lozi-like maps. M. Misiurewicz and S. Štimac. May 13, 2017 Lozi-like maps M. Misiurewicz and S. Štimac May 13, 017 Abstract We define a broad class of piecewise smooth plane homeomorphisms which have properties similar to the properties of Lozi maps, including

More information

PERIODS IMPLYING ALMOST ALL PERIODS FOR TREE MAPS. A. M. Blokh. Department of Mathematics, Wesleyan University Middletown, CT , USA

PERIODS IMPLYING ALMOST ALL PERIODS FOR TREE MAPS. A. M. Blokh. Department of Mathematics, Wesleyan University Middletown, CT , USA PERIODS IMPLYING ALMOST ALL PERIODS FOR TREE MAPS A. M. Blokh Department of Mathematics, Wesleyan University Middletown, CT 06459-0128, USA August 1991, revised May 1992 Abstract. Let X be a compact tree,

More information

Chapter 3. Gumowski-Mira Map. 3.1 Introduction

Chapter 3. Gumowski-Mira Map. 3.1 Introduction Chapter 3 Gumowski-Mira Map 3.1 Introduction Non linear recurrence relations model many real world systems and help in analysing their possible asymptotic behaviour as the parameters are varied [17]. Here

More information

The Lebesgue Integral

The Lebesgue Integral The Lebesgue Integral Having completed our study of Lebesgue measure, we are now ready to consider the Lebesgue integral. Before diving into the details of its construction, though, we would like to give

More information

Measures. 1 Introduction. These preliminary lecture notes are partly based on textbooks by Athreya and Lahiri, Capinski and Kopp, and Folland.

Measures. 1 Introduction. These preliminary lecture notes are partly based on textbooks by Athreya and Lahiri, Capinski and Kopp, and Folland. Measures These preliminary lecture notes are partly based on textbooks by Athreya and Lahiri, Capinski and Kopp, and Folland. 1 Introduction Our motivation for studying measure theory is to lay a foundation

More information

UNIVERSITY OF TORONTO Faculty of Arts and Science DECEMBER 2011 EXAMINATIONS. MAT335H1F Solutions Chaos, Fractals and Dynamics Examiner: D.

UNIVERSITY OF TORONTO Faculty of Arts and Science DECEMBER 2011 EXAMINATIONS. MAT335H1F Solutions Chaos, Fractals and Dynamics Examiner: D. General Comments: UNIVERSITY OF TORONTO Faculty of Arts and Science DECEMBER 2011 EXAMINATIONS MAT335H1F Solutions Chaos, Fractals and Dynamics Examiner: D. Burbulla Duration - 3 hours Examination Aids:

More information

CSCE 750 Final Exam Answer Key Wednesday December 7, 2005

CSCE 750 Final Exam Answer Key Wednesday December 7, 2005 CSCE 750 Final Exam Answer Key Wednesday December 7, 2005 Do all problems. Put your answers on blank paper or in a test booklet. There are 00 points total in the exam. You have 80 minutes. Please note

More information

Problem set 1, Real Analysis I, Spring, 2015.

Problem set 1, Real Analysis I, Spring, 2015. Problem set 1, Real Analysis I, Spring, 015. (1) Let f n : D R be a sequence of functions with domain D R n. Recall that f n f uniformly if and only if for all ɛ > 0, there is an N = N(ɛ) so that if n

More information

Laver Tables A Direct Approach

Laver Tables A Direct Approach Laver Tables A Direct Approach Aurel Tell Adler June 6, 016 Contents 1 Introduction 3 Introduction to Laver Tables 4.1 Basic Definitions............................... 4. Simple Facts.................................

More information

Convergence in shape of Steiner symmetrized line segments. Arthur Korneychuk

Convergence in shape of Steiner symmetrized line segments. Arthur Korneychuk Convergence in shape of Steiner symmetrized line segments by Arthur Korneychuk A thesis submitted in conformity with the requirements for the degree of Master of Science Graduate Department of Mathematics

More information

ADMISSIBILITY OF KNEADING SEQUENCES AND STRUCTURE OF HUBBARD TREES FOR QUADRATIC POLYNOMIALS

ADMISSIBILITY OF KNEADING SEQUENCES AND STRUCTURE OF HUBBARD TREES FOR QUADRATIC POLYNOMIALS ADMISSIBILITY OF KNEADING SEQUENCES AND STRUCTURE OF HUBBARD TREES FOR QUADRATIC POLYNOMIALS HENK BRUIN AND DIERK SCHLEICHER Abstract. Hubbard trees are invariant trees connecting the points of the critical

More information

3.4 Using the First Derivative to Test Critical Numbers (4.3)

3.4 Using the First Derivative to Test Critical Numbers (4.3) 118 CHAPTER 3. APPLICATIONS OF THE DERIVATIVE 3.4 Using the First Derivative to Test Critical Numbers (4.3) 3.4.1 Theory: The rst derivative is a very important tool when studying a function. It is important

More information

ADDING MACHINES, ENDPOINTS, AND INVERSE LIMIT SPACES. 1. Introduction

ADDING MACHINES, ENDPOINTS, AND INVERSE LIMIT SPACES. 1. Introduction ADDING MACHINES, ENDPOINTS, AND INVERSE LIMIT SPACES LORI ALVIN AND KAREN BRUCKS Abstract. Let f be a unimodal map in the logistic or symmetric tent family whose restriction to the omega limit set of the

More information

TOEPLITZ KNEADING SEQUENCES AND ADDING MACHINES

TOEPLITZ KNEADING SEQUENCES AND ADDING MACHINES TOEPLITZ KNEADING SEQUENCES AND ADDING MACHINES LORI ALVIN Department of Mathematics and Statistics University of West Florida 11000 University Parkway Pensacola, FL 32514, USA Abstract. In this paper

More information

Defining the Integral

Defining the Integral Defining the Integral In these notes we provide a careful definition of the Lebesgue integral and we prove each of the three main convergence theorems. For the duration of these notes, let (, M, µ) be

More information

Math 172 HW 1 Solutions

Math 172 HW 1 Solutions Math 172 HW 1 Solutions Joey Zou April 15, 2017 Problem 1: Prove that the Cantor set C constructed in the text is totally disconnected and perfect. In other words, given two distinct points x, y C, there

More information

Lebesgue Integration: A non-rigorous introduction. What is wrong with Riemann integration?

Lebesgue Integration: A non-rigorous introduction. What is wrong with Riemann integration? Lebesgue Integration: A non-rigorous introduction What is wrong with Riemann integration? xample. Let f(x) = { 0 for x Q 1 for x / Q. The upper integral is 1, while the lower integral is 0. Yet, the function

More information

Some Results Concerning Uniqueness of Triangle Sequences

Some Results Concerning Uniqueness of Triangle Sequences Some Results Concerning Uniqueness of Triangle Sequences T. Cheslack-Postava A. Diesl M. Lepinski A. Schuyler August 12 1999 Abstract In this paper we will begin by reviewing the triangle iteration. We

More information

V. Graph Sketching and Max-Min Problems

V. Graph Sketching and Max-Min Problems V. Graph Sketching and Max-Min Problems The signs of the first and second derivatives of a function tell us something about the shape of its graph. In this chapter we learn how to find that information.

More information

MATH41011/MATH61011: FOURIER SERIES AND LEBESGUE INTEGRATION. Extra Reading Material for Level 4 and Level 6

MATH41011/MATH61011: FOURIER SERIES AND LEBESGUE INTEGRATION. Extra Reading Material for Level 4 and Level 6 MATH41011/MATH61011: FOURIER SERIES AND LEBESGUE INTEGRATION Extra Reading Material for Level 4 and Level 6 Part A: Construction of Lebesgue Measure The first part the extra material consists of the construction

More information

MTH 241: Business and Social Sciences Calculus

MTH 241: Business and Social Sciences Calculus MTH 241: Business and Social Sciences Calculus F. Patricia Medina Department of Mathematics. Oregon State University January 28, 2015 Section 2.1 Increasing and decreasing Definition 1 A function is increasing

More information

CONSTRAINED PERCOLATION ON Z 2

CONSTRAINED PERCOLATION ON Z 2 CONSTRAINED PERCOLATION ON Z 2 ZHONGYANG LI Abstract. We study a constrained percolation process on Z 2, and prove the almost sure nonexistence of infinite clusters and contours for a large class of probability

More information

Part 2 Continuous functions and their properties

Part 2 Continuous functions and their properties Part 2 Continuous functions and their properties 2.1 Definition Definition A function f is continuous at a R if, and only if, that is lim f (x) = f (a), x a ε > 0, δ > 0, x, x a < δ f (x) f (a) < ε. Notice

More information

Lecture2 The implicit function theorem. Bifurcations.

Lecture2 The implicit function theorem. Bifurcations. Lecture2 The implicit function theorem. Bifurcations. 1 Review:Newton s method. The existence theorem - the assumptions. Basins of attraction. 2 The implicit function theorem. 3 Bifurcations of iterations.

More information

MAT335H1F Lec0101 Burbulla

MAT335H1F Lec0101 Burbulla Fall 2011 Q 2 (x) = x 2 2 Q 2 has two repelling fixed points, p = 1 and p + = 2. Moreover, if I = [ p +, p + ] = [ 2, 2], it is easy to check that p I and Q 2 : I I. So for any seed x 0 I, the orbit of

More information

Measure and integration

Measure and integration Chapter 5 Measure and integration In calculus you have learned how to calculate the size of different kinds of sets: the length of a curve, the area of a region or a surface, the volume or mass of a solid.

More information

2017, James Sethna, all rights reserved. This exercise was developed in collaboration with Christopher Myers.

2017, James Sethna, all rights reserved. This exercise was developed in collaboration with Christopher Myers. Invariant measures (Sethna, "Entropy, Order Parameters, and Complexity", ex. 4.3) 2017, James Sethna, all rights reserved. This exercise was developed in collaboration with Christopher Myers. Liouville's

More information

Measures and Measure Spaces

Measures and Measure Spaces Chapter 2 Measures and Measure Spaces In summarizing the flaws of the Riemann integral we can focus on two main points: 1) Many nice functions are not Riemann integrable. 2) The Riemann integral does not

More information

MTH4100 Calculus I. Bill Jackson School of Mathematical Sciences QMUL. Week 9, Semester 1, 2013

MTH4100 Calculus I. Bill Jackson School of Mathematical Sciences QMUL. Week 9, Semester 1, 2013 MTH4100 School of Mathematical Sciences QMUL Week 9, Semester 1, 2013 Concavity Concavity In the literature concave up is often referred to as convex, and concave down is simply called concave. The second

More information

INTRODUCTION TO REAL ANALYSIS II MATH 4332 BLECHER NOTES

INTRODUCTION TO REAL ANALYSIS II MATH 4332 BLECHER NOTES INTRODUCTION TO REAL ANALYSIS II MATH 4332 BLECHER NOTES You will be expected to reread and digest these typed notes after class, line by line, trying to follow why the line is true, for example how it

More information

Chapter 1 The Real Numbers

Chapter 1 The Real Numbers Chapter 1 The Real Numbers In a beginning course in calculus, the emphasis is on introducing the techniques of the subject;i.e., differentiation and integration and their applications. An advanced calculus

More information

An uncountably categorical theory whose only computably presentable model is saturated

An uncountably categorical theory whose only computably presentable model is saturated An uncountably categorical theory whose only computably presentable model is saturated Denis R. Hirschfeldt Department of Mathematics University of Chicago, USA Bakhadyr Khoussainov Department of Computer

More information

PROPER FORCING REMASTERED

PROPER FORCING REMASTERED PROPER FORCING REMASTERED BOBAN VELIČKOVIĆ AND GIORGIO VENTURI Abstract. We present the method introduced by Neeman of generalized side conditions with two types of models. We then discuss some applications:

More information

Lebesgue measure and integration

Lebesgue measure and integration Chapter 4 Lebesgue measure and integration If you look back at what you have learned in your earlier mathematics courses, you will definitely recall a lot about area and volume from the simple formulas

More information

1 The Local-to-Global Lemma

1 The Local-to-Global Lemma Point-Set Topology Connectedness: Lecture 2 1 The Local-to-Global Lemma In the world of advanced mathematics, we are often interested in comparing the local properties of a space to its global properties.

More information

Continuity. Chapter 4

Continuity. Chapter 4 Chapter 4 Continuity Throughout this chapter D is a nonempty subset of the real numbers. We recall the definition of a function. Definition 4.1. A function from D into R, denoted f : D R, is a subset of

More information

Standard forms for writing numbers

Standard forms for writing numbers Standard forms for writing numbers In order to relate the abstract mathematical descriptions of familiar number systems to the everyday descriptions of numbers by decimal expansions and similar means,

More information

Ergodic Theory of Interval Exchange Transformations

Ergodic Theory of Interval Exchange Transformations Ergodic Theory of Interval Exchange Transformations October 29, 2017 An interval exchange transformation on d intervals is a bijection T : [0, 1) [0, 1) given by cutting up [0, 1) into d subintervals and

More information

Multiple attractors in Newton's method

Multiple attractors in Newton's method Ergod. Th. & Dynam. Sys. (1986), 6, 561-569 Printed in Great Britain Multiple attractors in Newton's method MIKE HURLEY Department of Mathematics and Statistics, Case Western Reserve University, Cleveland,

More information

Absolute and Local Extrema. Critical Points In the proof of Rolle s Theorem, we actually demonstrated the following

Absolute and Local Extrema. Critical Points In the proof of Rolle s Theorem, we actually demonstrated the following Absolute and Local Extrema Definition 1 (Absolute Maximum). A function f has an absolute maximum at c S if f(x) f(c) x S. We call f(c) the absolute maximum of f on S. Definition 2 (Local Maximum). A function

More information

PM functions, their characteristic intervals and iterative roots

PM functions, their characteristic intervals and iterative roots ANNALES POLONICI MATHEMATICI LXV.2(1997) PM functions, their characteristic intervals and iterative roots by Weinian Zhang (Chengdu) Abstract. The concept of characteristic interval for piecewise monotone

More information

Functional Equations

Functional Equations Functional Equations Henry Liu, 22 December 2004 henryliu@memphis.edu Introduction This is a brief set of notes on functional equations. It is one of the harder and less popular areas among Olympiad problems,

More information

Lecture 1: Period Three Implies Chaos

Lecture 1: Period Three Implies Chaos Math 7h Professor: Padraic Bartlett Lecture 1: Period Three Implies Chaos Week 1 UCSB 2014 (Source materials: Period three implies chaos, by Li and Yorke, and From Intermediate Value Theorem To Chaos,

More information

X. Numerical Methods

X. Numerical Methods X. Numerical Methods. Taylor Approximation Suppose that f is a function defined in a neighborhood of a point c, and suppose that f has derivatives of all orders near c. In section 5 of chapter 9 we introduced

More information

Definitions. Notations. Injective, Surjective and Bijective. Divides. Cartesian Product. Relations. Equivalence Relations

Definitions. Notations. Injective, Surjective and Bijective. Divides. Cartesian Product. Relations. Equivalence Relations Page 1 Definitions Tuesday, May 8, 2018 12:23 AM Notations " " means "equals, by definition" the set of all real numbers the set of integers Denote a function from a set to a set by Denote the image of

More information

Chapter 3: Root Finding. September 26, 2005

Chapter 3: Root Finding. September 26, 2005 Chapter 3: Root Finding September 26, 2005 Outline 1 Root Finding 2 3.1 The Bisection Method 3 3.2 Newton s Method: Derivation and Examples 4 3.3 How To Stop Newton s Method 5 3.4 Application: Division

More information

Metric Spaces and Topology

Metric Spaces and Topology Chapter 2 Metric Spaces and Topology From an engineering perspective, the most important way to construct a topology on a set is to define the topology in terms of a metric on the set. This approach underlies

More information

Definitions, Theorems and Exercises. Abstract Algebra Math 332. Ethan D. Bloch

Definitions, Theorems and Exercises. Abstract Algebra Math 332. Ethan D. Bloch Definitions, Theorems and Exercises Abstract Algebra Math 332 Ethan D. Bloch December 26, 2013 ii Contents 1 Binary Operations 3 1.1 Binary Operations............................... 4 1.2 Isomorphic Binary

More information

The Sine Map. Jory Griffin. May 1, 2013

The Sine Map. Jory Griffin. May 1, 2013 The Sine Map Jory Griffin May, 23 Introduction Unimodal maps on the unit interval are among the most studied dynamical systems. Perhaps the two most frequently mentioned are the logistic map and the tent

More information

CHAOTIC BEHAVIOR IN A FORECAST MODEL

CHAOTIC BEHAVIOR IN A FORECAST MODEL CHAOTIC BEHAVIOR IN A FORECAST MODEL MICHAEL BOYLE AND MARK TOMFORDE Abstract. We examine a certain interval map, called the weather map, that has been used by previous authors as a toy model for weather

More information

Hilbert s theorem 90, Dirichlet s unit theorem and Diophantine equations

Hilbert s theorem 90, Dirichlet s unit theorem and Diophantine equations Hilbert s theorem 90, Dirichlet s unit theorem and Diophantine equations B. Sury Stat-Math Unit Indian Statistical Institute 8th Mile Mysore Road Bangalore - 560 059 India. sury@isibang.ac.in Introduction

More information

HIGHER EUCLIDEAN DOMAINS

HIGHER EUCLIDEAN DOMAINS HIGHER EUCLIDEAN DOMAINS CHRIS J. CONIDIS Abstract. Samuel and others asked for a Euclidean domain with Euclidean rank strictly greater than ω, the smallest infinite ordinal. Via a limited technique Hiblot

More information

v n+1 = v T + (v 0 - v T )exp(-[n +1]/ N )

v n+1 = v T + (v 0 - v T )exp(-[n +1]/ N ) Notes on Dynamical Systems (continued) 2. Maps The surprisingly complicated behavior of the physical pendulum, and many other physical systems as well, can be more readily understood by examining their

More information

Real Analysis Chapter 1 Solutions Jonathan Conder

Real Analysis Chapter 1 Solutions Jonathan Conder 3. (a) Let M be an infinite σ-algebra of subsets of some set X. There exists a countably infinite subcollection C M, and we may choose C to be closed under taking complements (adding in missing complements

More information

+ 2x sin x. f(b i ) f(a i ) < ɛ. i=1. i=1

+ 2x sin x. f(b i ) f(a i ) < ɛ. i=1. i=1 Appendix To understand weak derivatives and distributional derivatives in the simplest context of functions of a single variable, we describe without proof some results from real analysis (see [7] and

More information

Chapter 11 - Sequences and Series

Chapter 11 - Sequences and Series Calculus and Analytic Geometry II Chapter - Sequences and Series. Sequences Definition. A sequence is a list of numbers written in a definite order, We call a n the general term of the sequence. {a, a

More information

The PRIMES 2014 problem set

The PRIMES 2014 problem set Dear PRIMES applicant! The PRIMES 24 problem set This is the PRIMES 24 problem set. Please send us your solutions as part of your PRIMES application by December, 24. For complete rules, see http://web.mit.edu/primes/apply.shtml

More information

. As the binomial coefficients are integers we have that. 2 n(n 1).

. As the binomial coefficients are integers we have that. 2 n(n 1). Math 580 Homework. 1. Divisibility. Definition 1. Let a, b be integers with a 0. Then b divides b iff there is an integer k such that b = ka. In the case we write a b. In this case we also say a is a factor

More information

UNCOUNTABLE ω-limit SETS WITH ISOLATED POINTS

UNCOUNTABLE ω-limit SETS WITH ISOLATED POINTS UNCOUNTABLE ω-limit SETS WITH ISOLATED POINTS CHRIS GOOD, BRIAN RAINES, AND ROLF SUABEDISSEN Abstract. We give two examples of tent maps with uncountable (as it happens, post-critical) ω-limit sets, which

More information

Lecture 9 - Increasing and Decreasing Functions, Extrema, and the First Derivative Test

Lecture 9 - Increasing and Decreasing Functions, Extrema, and the First Derivative Test Lecture 9 - Increasing and Decreasing Functions, Extrema, and the First Derivative Test 9.1 Increasing and Decreasing Functions One of our goals is to be able to solve max/min problems, especially economics

More information

An elementary approach to dynamics and bifurcations of skew tent maps

An elementary approach to dynamics and bifurcations of skew tent maps An elementary approach to dynamics and bifurcations of skew tent maps Torsten Lindström School of Pure and Applied Natural Sciences University of Kalmar SE-39 82 KALMAR, SWEDEN Hans Thunberg KTH Mathematics,

More information

LECTURE 10: REVIEW OF POWER SERIES. 1. Motivation

LECTURE 10: REVIEW OF POWER SERIES. 1. Motivation LECTURE 10: REVIEW OF POWER SERIES By definition, a power series centered at x 0 is a series of the form where a 0, a 1,... and x 0 are constants. For convenience, we shall mostly be concerned with the

More information

CPSC 518 Introduction to Computer Algebra Asymptotically Fast Integer Multiplication

CPSC 518 Introduction to Computer Algebra Asymptotically Fast Integer Multiplication CPSC 518 Introduction to Computer Algebra Asymptotically Fast Integer Multiplication 1 Introduction We have now seen that the Fast Fourier Transform can be applied to perform polynomial multiplication

More information

The Geometry of Cubic Maps

The Geometry of Cubic Maps The Geometry of Cubic Maps John Milnor Stony Brook University (www.math.sunysb.edu) work with Araceli Bonifant and Jan Kiwi Conformal Dynamics and Hyperbolic Geometry CUNY Graduate Center, October 23,

More information

Math LM (24543) Lectures 02

Math LM (24543) Lectures 02 Math 32300 LM (24543) Lectures 02 Ethan Akin Office: NAC 6/287 Phone: 650-5136 Email: ethanakin@earthlink.net Spring, 2018 Contents Continuity, Ross Chapter 3 Uniform Continuity and Compactness Connectedness

More information

Footnotes to Linear Algebra (MA 540 fall 2013), T. Goodwillie, Bases

Footnotes to Linear Algebra (MA 540 fall 2013), T. Goodwillie, Bases Footnotes to Linear Algebra (MA 540 fall 2013), T. Goodwillie, Bases November 18, 2013 1 Spanning and linear independence I will outline a slightly different approach to the material in Chapter 2 of Axler

More information

R1: Sets A set is a collection of objects sets are written using set brackets each object in onset is called an element or member

R1: Sets A set is a collection of objects sets are written using set brackets each object in onset is called an element or member Chapter R Review of basic concepts * R1: Sets A set is a collection of objects sets are written using set brackets each object in onset is called an element or member Ex: Write the set of counting numbers

More information

The primitive root theorem

The primitive root theorem The primitive root theorem Mar Steinberger First recall that if R is a ring, then a R is a unit if there exists b R with ab = ba = 1. The collection of all units in R is denoted R and forms a group under

More information

Synchronization, Chaos, and the Dynamics of Coupled Oscillators. Supplemental 1. Winter Zachary Adams Undergraduate in Mathematics and Biology

Synchronization, Chaos, and the Dynamics of Coupled Oscillators. Supplemental 1. Winter Zachary Adams Undergraduate in Mathematics and Biology Synchronization, Chaos, and the Dynamics of Coupled Oscillators Supplemental 1 Winter 2017 Zachary Adams Undergraduate in Mathematics and Biology Outline: The shift map is discussed, and a rigorous proof

More information