Corrigendum on Generic family with robustly infinitely many sinks

Size: px
Start display at page:

Download "Corrigendum on Generic family with robustly infinitely many sinks"

Transcription

1 Corrigendum on Generic fmily with robustly infinitely mny sinks Pierre Berger ll the min results of [Ber16b] re correct, but this would need substntil vrition of the proof s done in [Ber16]. In this corrigendum we prefer to chnge the topologies considered in ll the sttements of [Ber16b]. lso we generlize nd correct the fundmentl property of prblender. Correction of the sttements For d, r, k 0, nd M, N Riemninn mnifolds, two different spces of C d -fmilies (f ) of C r -mps f C r (M, N) prmetred by R k, cn be defined s follows: C d,r (Rk, M, N) = {(f ) : i j zf (z) exists continuously for ll i d, i+j r nd (, z) R k M} C d,r (Rk, M, N) = {(f ) : i j zf (z) exists continuously for ll j r, i d nd (, z) R k M} We endow these spces with the compct open topology w.r.t. the considered derivtives. We notice tht in the importnt cse r = these two spces re equl. In generl, it holds: C d,d+r C d,r Cd,r. The previous rticle delt with the spce C d,r ; the spce Cd,r should be considered insted of C d,r. Then the whole rticle is correct but the sttement of the fundmentl property of the prblender which needs 1 d < r (the cse d = r does not seem to work). Therefore, the topology involved in the sttement of Theorems, C (nd fcts 4.2, 4.3, 4.4 of its proof) must be corrected to C d,r for ny 1 d < r. Likewise, the topology involved in the sttement of Theorems B must be corrected to C d,r for ny 1 d < r <. This correction removes the cse d = r 2. However the vrition [Ber16] of [Ber16b] gives the cse d = r 1 nd lso d r for the topologies C d,r nd Cd,r. In prticulr the sttements of the min theorems of the rticle under correction re correct. Here is the mistke I mde. The spce C d,r is ctully not stble by composition. For instnce if M = M, there exists (f ) C d,r so tht (f f ) does not belong to C d,r. Tht is why we correct it by the spce C d,r which is stble by composition. I m grteful to S. Crovisier for vluble suggestions on the presenttion of the following section. Correction nd generlizton of the fundmentl property Let us fix k 0, 0 d < r. Given Riemnnin mnifold M, nd C d -fmilies of points (z ) R k, its C d -jet t = 0 is denoted by J0 d(z ) = d j=0 j z j! j. Let J0 d M be the spce of C d -jets of C d -fmilies of points in M t = 0. CNRS-LG, Université Pris 13, USPC. 1

2 We notice tht ny C d,r -fmily (f ) of C r -mps f of M cts cnoniclly J0 d M s the mp: J d 0 (f ) : J d 0 (z ) J d 0 M J d 0 (f (z )) J d 0 M Let us define ctegory of C d -prblenders contining those of [Ber16b, BCP16]. Definition 1. n ffine C d -pr-ifs of R 2 is the dt of finite set of symbols δ, nd polynomils λ δ, Λ δ, p δ, q δ R[X 1,..., X k ] of degrees d, so tht Λ δ (0) < 1/2 < λ δ (0) < 1 nd with () g δ : (x, y) R 2 (Λ δ () x + p δ (), y q δ() ) R 2. λ δ () I e := [ 1, 1], I δ := [p δ Λ δ, p δ + Λ δ ], I δ := [q δ λ δ, q δ + λ δ ] Y e = I e I e Y δ = I δ I e Y δ = I e I δ u Y δ := I δ I e nd s Y δ := I e I δ there exist compct neighborhoods J d 0 R2 of 0 stisfying: (i) for every J d 0 (z ), there exists δ so tht J d 0 ( gδ (z )) is in. (ii) For every smll nd δ, the subsets Y δ () nd Y δ () re included in Y e, with u Y δ () u Y e nd s Y δ () s Y e, moreover they stisfy g δ (Y δ ()) = Y δ (). (iii) for every Z = d i=0 z i i, the vlue z 0 belongs to the interior of Y δ (0) for every δ. Definition 2. Let r d. fmily (f ) of locl diffeomorphisms of R 2 defines nerly ffine C d -prblender if the fmily of its inverse brnches ((g δ ) ) δ is C d,r -perturbtion of (( gδ ) ) δ. Then for smll R k nd δ, with Îδ smll neighborhood of I δ, the imge by g δ of [ 1, 1] Îδ intersects Y e t set Y δ (f ) close to Y δ (). The set Y δ (f ) is bounded by two segments u Y δ (f ) of u Y e, nd two curves s Y δ (f ) close to s Y δ (). The imge by f of Y δ (f ) is denoted by Y δ (f ). It is filled squre close to Y δ (). The set Y δ (f ) is bounded by two segments s Y δ (f ) of s Y e nd two segments u Y δ (f ) close to u Y δ (). We notice tht (i)-(ii)-(iii) re still stisfied by (g δ ) insted of ( g δ ) nd Y δ (f ) insted of Y δ (). Then, for every δ = (δ i ) i 1 Z we define the following locl unstble mnifold: W u loc (δ; f ) := n 1 f n (Y δ n (f )). Exmple 3. In [BCP16], we showed exmple of nerly ffine C d -prblender with Crd = 2. It is precisely for this exmple tht we consider the topology on the inverse brnches rther thn on the dynmics, since the degenerte cse Λ δ = 0 does occur in the limit of renormliztion process. Exmple 4. In [Ber16b], we defined in 2.2, the fmily of mps (f ɛ ) for f U 0 nd ɛ > smll enough. The covering property (i) is shown in section with with = {P J0 2R2 : P (0) [ 1, 1] [ 2/3, 2/3] i P (0) [ 1, 1] [ 2ɛ, 2ɛ]} nd neighborhood of {P J0 2R2 : P (0) [ 1/2, 1/2] [ 1/2, 1/2] i P (0) [ 1/2, 1/2] [ 3 2 ɛ, 3 2 ɛ]}. Let us fix n ffine C d -pr-ifs (( g ) δ R k) δ. Let γ : x [ 1, 1] (x, x 2 ). 2

3 Fundmentl property of the prblender If r > d 1 nd Λ δ (0) < λ δ d (0) for every δ, there exist C d,r -neighborhood V γ of the constnt fmily of functions ( γ) nd C d,r - neighborhood V g of (( g ) δ ) δ so tht for every nerly ffine prblender (f ) with inverse brnches ((g δ ) ) δ V g, every (γ ) V γ hs its imge (Γ = γ ([ 1, 1])) which is C d -prtngent t = 0 to locl unstble mnifold of (f ). We recll tht (Γ ) is C d -prtngent to locl unstble mnifold (W u loc (δ; f )) if there re C d -fmilies of points (C ) in (Γ ) nd (Q ) in (W u loc (δ; f )) so tht: J d 0 (C ) = J d 0 (Q ) nd J d 0 (T C Γ ) = J d 0 (T Q W u loc (δ; f )). To prove the fundmentl property we re going to define sequence of symbols (δ k ) k 1 nd C d -fmily of points (C ) of (Γ ) stisfying the following property: (H 1 ) for every k 1, J d 0 (Gk C ) is in, with G k = g δ k (H 2 ) for every k 1, J d 0 (DGk T C Γ ) is smll. g δ 1, Proof tht (H 1 ) (H 2 ) implies the fundmentl property. By proceeding s in the proof of Thm B. [BCP16], (H 1 ) implies the existence of C d -curve of points (Q ) in (W u loc (δ; f )) so tht: J d 0 (C ) = J d 0 (Q ). Note tht J0 d(gk Q ) is equl to J0 d(gk C ) for every k nd so it is in, for every k 1. s (g ) is C d,d+1 -perturbtion of ( g ), (Wloc u (δ; f )) is C d,d+1 -close to be horizontl, by Prop. 1.6 [Ber16b]. The sme holds for (Wloc u (σk (δ); f )), with σ k (δ) = (δ i+k ) i 1. Hence, with L PR 1 the line tngent to Wloc u (δ; f ) t Q, it holds tht J0 d(l ) is smll, nd J0 d(d Q G k L ) s well. Consequently, by (H 2 ), J d 0 (DGk T C Γ ) is close to J d 0 (D C G k L ) for every k 1. Let us notice tht the ction of T Q G k of DG k on PR 1 is exponentilly expnding t the neighborhood of L. The sme holds for J d 0 (T Q G k ) : it is exponentilly expnding t bll centered t J d 0 (L ) nd which contins J d 0 (T C Γ ). Thus they re equl. The proof of (H 1 ) (H 2 ) is done by constructing by induction on n 0 sequence of symbols δ n 1,..., δ 1 so tht there exists C d -curve (C n ) (Γ ) stisfying: () C n 0 is in the interior of the domin of Gn 0. (b) G n (C n ) is the point of G n (Γ ) with the miniml y-coordinte. (c) J d 0 (Gk (C n )) is in for every n k 0 nd J d 0 (Gn 1 (C n )) is in. We observe tht ny C d -curve (C ) in (Γ ), so tht J d 0 (C ) is cluster vlue of (J d 0 (Cn ) ) n stisfies (H 1 ) by (c). To see tht it stisfies lso (H 2 ), let us bring some mterils. Let κ < 1 nd let η > 0 be smll nd such tht: ( ) 1 > κ exp(η), η + η/(1 κexp(η)) < d(, c ) nd 1 > κ > mx δ Λ δ λ d δ (0)exp(η). 3

4 Let p y : R 2 R be the 2 sd coordinte projection. For ny n 1, nd δ n,..., δ 1, we define the line field: L(δ n δ 1, f ) := ker D(p y g δ n g δ 1 ) nd L(, f ) := ker p y = R {0}. We will define norm on the spce of C d,d -line field fmilies nd show the following below: Lemm 5. For V g sufficiently smll, there exists smll neighborhood V of 0 R k such tht for ll n < 0 nd δ n 1,..., δ 1 d, the C d,d -distnce between the fmilies (L(δ n 1 δ 1, f )) V nd (L(δ n δ 1, f )) V (restricted to the intersection of their definition domins) is t most ηκ n (λ δ n λ δ 1 ). In prticulr (L(δ n δ 1, f )) V is η(1 κ) 1 -C d,d -close to the horizontl line field (L(, f )) V. Proof tht ( b c) implies (H 2 ). By (b), the curve Γ is tngent to L(δ n δ 1, f ) t C n, for every smll. Note lso tht DG k T Γ is equl to L(δ n δ k 1, f ) G k t C n for every n k 1. Thus J d 0 (DGk T Γ ) is equl to J d 0 (L(δ n δ k 1, f ) G k ) t J d 0 (Cn ). By (c), J d 0 (Gk C ) is in the compct set for every k 1. lso J d 0 (L(δ n δ k 1, f )) is η(1 κ) 1 -smll by Lemm 5. Thus J d 0 (DGk T Γ ) is bounded by η(1 κ) 1 dim t J d 0 (Cn ), for every n k 1. Hence (H 2 ) holds true t the cluster vlue J d 0 (C ) of (J d 0 (Cn ) ) n. Proof of the induction hypothesis (-b-c). Let n = 0. Let C 0 be the point which relizes the y- minimum of Γ. s it is C d -close to 0 for V γ smll, its C d -jet J d 0 (C0 ) is in. Hence by (ii), there exists symbol δ 1 so tht G 1 C 0 = g δ 1 C 0 hs its C d -jets t = 0 in. Let n 1. Let us ssume δ n 1,..., δ 1 constructed so tht (C m ) stisfies ( b c) for every n m 0. We put L m := L(δ m δ 1, f ) for every n 1 m 0. For every n 1 m 0, we cn extend (L m ) on Y e so tht nerby = 0, the line fields (L m ) nd (L n 1 ) re η n j=m κ j λ δj λ δ 1 -C d,d -close by Lemm 5. Therefore there is unique point C n 1 () t which L n 1 nd T Γ re equl, this proves (b). Moreover, J0 d(cn 1 ) nd J0 d(cm ) re η n j=m κ j λ δj λ δ 1 -C d,d -close. We will define the norm involved nd we will prove the following below: Lemm 6. For V g sufficiently smll, for every ((g δ ) ) δ V g, for every δ, the following mp is exp(η)/λ δ (0) Lipschitz: Hence J d 0 (Gm 1 (C n 1 J d (g δ ) : J d 0 (z ) J d 0 (g δ z ) J d 0 R 2. )) nd J0 d(gm 1 C m ) is less thn: ηκ m λ δm 1 exp( m 1 η) + η n j=m 1 κ j λ δj λ δm 2 exp( m 1 η) By the first inequlity of ( ) nd since 1 > λ δm 1 (0) 1/2, the bove sum is t most η + η/(1 κexp(η)). 4

5 By the second inequlity of ( ) nd the second prt of (c) t step m, J0 d(gm 1 C n 1 ) is in for every n m 0. This proves the first prt of (c) t step n 1. Note tht for m = n, this proves tht J0 d(gn 1 to the domin of ny g0 δ, hence () is stisfied. Let δ n 2 so tht J d 0 (gδ n 2 is stisfied. ) sends J d 0 (Gn 2 (C n 1 C n 1 )) is in nd so tht G n 1 0 (C n 1 0 ) belongs ) into. Note tht the second prt of (c) Proof of Lemm 6. We only need to prove this proposition for ( g ) since the Lipschitz constnt depends continuously on the C d;d -perturbtion. With J0 d(z ) = d j=0 z j j, nd since z g j 0 δ = 0 for every j 2, it holds: J d ( g δ (z )) = d n=0 i+k 1 + +k j =n ( i j z g δ 0 ) i!j! ( l z kl ) n = d n=0 i+k=n ( i z g δ 0 ) i! z k n Hence J d ( g δ ) is liner mp with upper tringulr mtrix in the bse (z n ) 1 n d nd with digonl equl to z g 0 δ id which is λ 1 δ (0) -Lipschitz. Hence there exists (c i ) i d with c i smll w.r.t. c j whenever i < j, so tht for the norm d j=0 z j j J0 dr2 j d c j z j, the mp J d ( g ) δ is (0)exp(η/2)-Lipschitz. By tking V g smll in function of η, we get the lemm. λ 1 δ To prove Lemm 5, let us order the set {(i, j) : i + j d} by: (i, j) (i, j ) iff i > i or i = i nd j > j ). Proof of Lemm 5. Let δ, nd let L(Ω) be the spce of C d,d -fmilies of line fields (L ) V over set Ω R 2. We notice tht the following mp fix the horizontl line field H : (, z) R {0}. φ: (L ) L(Y δ ) ((D g δ ) 1 L g δ ) L(Y δ ). In the identifiction of PR 1 which ssocites to line its slope, H is the zero section nd the mp (D g δ ) 1 is the multipliction by Λ δ ()λ δ (). Thus the mp φ is liner: φ(l ) = (Λ δ ()λ δ () L g δ ). Note tht Lemm 5 is proved if we show tht φ is exp(3η/4)λ δ (0)λ 1 d δ (0)-contrcting for C d,d - equivlent norm, independent of δ. Then, there exist continuous functions (C i,j i,j ) (i,j )<(i,j) so tht, for every smll (L ) L(Y δ ) : i j zφ(l ) = Λ δ ()λ δ () i j z(l ) g δ ( z g δ ) i + (i,j ) (i,j) C i,j i,j (z, ) i j z (L ) g δ Thus the derivtives [ i j z] i+j d re bounded from bove by n upper tringulr mtrix with digonl coefficients t most Λ δ λ δ ( z g δ ) d. For V sufficiently smll, the ltter is t most exp(η/2) Λ δ (0) λ δ (0) d 1. Hence there exists (c i,j ) i+j d with c i,j smll w.r.t. c i,j whenever (i, j) (i, j ), so tht the mp φ is exp(3η/4) Λ δ (0) λ δ (0) d 1 -contrcting for the norm (L ) = i+j d c i,j i j zl C 0. 5

6 References [BCP16] P. Berger, S. Crovisier, nd P. Pujls. Iterted functions systems, blenders nd prblenders. rxiv: , to pper Proc. FRFIII, [Ber16] P. Berger. Emergence nd non-typiclity of the finiteness of the ttrctors in mny topologies. rxiv, [Ber16b] P. Berger. Generic fmily with robustly infinitely mny sinks. Invent. Mth., 205(1): ,

LINEAR TRANSFORMATIONS AND THEIR REPRESENTING MATRICES

LINEAR TRANSFORMATIONS AND THEIR REPRESENTING MATRICES LINEAR TRANSFORMATIONS AND THEIR REPRESENTING MATRICES DAVID WEBB CONTENTS Liner trnsformtions 2 The representing mtrix of liner trnsformtion 3 3 An ppliction: reflections in the plne 6 4 The lgebr of

More information

Example A rectangular box without lid is to be made from a square cardboard of sides 18 cm by cutting equal squares from each corner and then folding

Example A rectangular box without lid is to be made from a square cardboard of sides 18 cm by cutting equal squares from each corner and then folding 1 Exmple A rectngulr box without lid is to be mde from squre crdbord of sides 18 cm by cutting equl squres from ech corner nd then folding up the sides. 1 Exmple A rectngulr box without lid is to be mde

More information

and thus, they are similar. If k = 3 then the Jordan form of both matrices is

and thus, they are similar. If k = 3 then the Jordan form of both matrices is Homework ssignment 11 Section 7. pp. 249-25 Exercise 1. Let N 1 nd N 2 be nilpotent mtrices over the field F. Prove tht N 1 nd N 2 re similr if nd only if they hve the sme miniml polynomil. Solution: If

More information

Lecture 5. Inner Product

Lecture 5. Inner Product Lecture 5 Inner Product Let us strt with the following problem. Given point P R nd line L R, how cn we find the point on the line closest to P? Answer: Drw line segment from P meeting the line in right

More information

Math 314, Homework Assignment 1. 1. Prove that two nonvertical lines are perpendicular if and only if the product of their slopes is 1.

Math 314, Homework Assignment 1. 1. Prove that two nonvertical lines are perpendicular if and only if the product of their slopes is 1. Mth 4, Homework Assignment. Prove tht two nonverticl lines re perpendiculr if nd only if the product of their slopes is. Proof. Let l nd l e nonverticl lines in R of slopes m nd m, respectively. Suppose

More information

Use Geometry Expressions to create a more complex locus of points. Find evidence for equivalence using Geometry Expressions.

Use Geometry Expressions to create a more complex locus of points. Find evidence for equivalence using Geometry Expressions. Lerning Objectives Loci nd Conics Lesson 3: The Ellipse Level: Preclculus Time required: 120 minutes In this lesson, students will generlize their knowledge of the circle to the ellipse. The prmetric nd

More information

PROF. BOYAN KOSTADINOV NEW YORK CITY COLLEGE OF TECHNOLOGY, CUNY

PROF. BOYAN KOSTADINOV NEW YORK CITY COLLEGE OF TECHNOLOGY, CUNY MAT 0630 INTERNET RESOURCES, REVIEW OF CONCEPTS AND COMMON MISTAKES PROF. BOYAN KOSTADINOV NEW YORK CITY COLLEGE OF TECHNOLOGY, CUNY Contents 1. ACT Compss Prctice Tests 1 2. Common Mistkes 2 3. Distributive

More information

MATH 150 HOMEWORK 4 SOLUTIONS

MATH 150 HOMEWORK 4 SOLUTIONS MATH 150 HOMEWORK 4 SOLUTIONS Section 1.8 Show tht the product of two of the numbers 65 1000 8 2001 + 3 177, 79 1212 9 2399 + 2 2001, nd 24 4493 5 8192 + 7 1777 is nonnegtive. Is your proof constructive

More information

EQUATIONS OF LINES AND PLANES

EQUATIONS OF LINES AND PLANES EQUATIONS OF LINES AND PLANES MATH 195, SECTION 59 (VIPUL NAIK) Corresponding mteril in the ook: Section 12.5. Wht students should definitely get: Prmetric eqution of line given in point-direction nd twopoint

More information

Vectors 2. 1. Recap of vectors

Vectors 2. 1. Recap of vectors Vectors 2. Recp of vectors Vectors re directed line segments - they cn be represented in component form or by direction nd mgnitude. We cn use trigonometry nd Pythgors theorem to switch between the forms

More information

MODULE 3. 0, y = 0 for all y

MODULE 3. 0, y = 0 for all y Topics: Inner products MOULE 3 The inner product of two vectors: The inner product of two vectors x, y V, denoted by x, y is (in generl) complex vlued function which hs the following four properties: i)

More information

Example 27.1 Draw a Venn diagram to show the relationship between counting numbers, whole numbers, integers, and rational numbers.

Example 27.1 Draw a Venn diagram to show the relationship between counting numbers, whole numbers, integers, and rational numbers. 2 Rtionl Numbers Integers such s 5 were importnt when solving the eqution x+5 = 0. In similr wy, frctions re importnt for solving equtions like 2x = 1. Wht bout equtions like 2x + 1 = 0? Equtions of this

More information

4.11 Inner Product Spaces

4.11 Inner Product Spaces 314 CHAPTER 4 Vector Spces 9. A mtrix of the form 0 0 b c 0 d 0 0 e 0 f g 0 h 0 cnnot be invertible. 10. A mtrix of the form bc d e f ghi such tht e bd = 0 cnnot be invertible. 4.11 Inner Product Spces

More information

5.2. LINE INTEGRALS 265. Let us quickly review the kind of integrals we have studied so far before we introduce a new one.

5.2. LINE INTEGRALS 265. Let us quickly review the kind of integrals we have studied so far before we introduce a new one. 5.2. LINE INTEGRALS 265 5.2 Line Integrls 5.2.1 Introduction Let us quickly review the kind of integrls we hve studied so fr before we introduce new one. 1. Definite integrl. Given continuous rel-vlued

More information

2005-06 Second Term MAT2060B 1. Supplementary Notes 3 Interchange of Differentiation and Integration

2005-06 Second Term MAT2060B 1. Supplementary Notes 3 Interchange of Differentiation and Integration Source: http://www.mth.cuhk.edu.hk/~mt26/mt26b/notes/notes3.pdf 25-6 Second Term MAT26B 1 Supplementry Notes 3 Interchnge of Differentition nd Integrtion The theme of this course is bout vrious limiting

More information

Factoring Polynomials

Factoring Polynomials Fctoring Polynomils Some definitions (not necessrily ll for secondry school mthemtics): A polynomil is the sum of one or more terms, in which ech term consists of product of constnt nd one or more vribles

More information

Review guide for the final exam in Math 233

Review guide for the final exam in Math 233 Review guide for the finl exm in Mth 33 1 Bsic mteril. This review includes the reminder of the mteril for mth 33. The finl exm will be cumultive exm with mny of the problems coming from the mteril covered

More information

Polynomial Functions. Polynomial functions in one variable can be written in expanded form as ( )

Polynomial Functions. Polynomial functions in one variable can be written in expanded form as ( ) Polynomil Functions Polynomil functions in one vrible cn be written in expnded form s n n 1 n 2 2 f x = x + x + x + + x + x+ n n 1 n 2 2 1 0 Exmples of polynomils in expnded form re nd 3 8 7 4 = 5 4 +

More information

Physics 43 Homework Set 9 Chapter 40 Key

Physics 43 Homework Set 9 Chapter 40 Key Physics 43 Homework Set 9 Chpter 4 Key. The wve function for n electron tht is confined to x nm is. Find the normliztion constnt. b. Wht is the probbility of finding the electron in. nm-wide region t x

More information

Babylonian Method of Computing the Square Root: Justifications Based on Fuzzy Techniques and on Computational Complexity

Babylonian Method of Computing the Square Root: Justifications Based on Fuzzy Techniques and on Computational Complexity Bbylonin Method of Computing the Squre Root: Justifictions Bsed on Fuzzy Techniques nd on Computtionl Complexity Olg Koshelev Deprtment of Mthemtics Eduction University of Texs t El Pso 500 W. University

More information

Lectures 8 and 9 1 Rectangular waveguides

Lectures 8 and 9 1 Rectangular waveguides 1 Lectures 8 nd 9 1 Rectngulr wveguides y b x z Consider rectngulr wveguide with 0 < x b. There re two types of wves in hollow wveguide with only one conductor; Trnsverse electric wves

More information

Mathematics. Vectors. hsn.uk.net. Higher. Contents. Vectors 128 HSN23100

Mathematics. Vectors. hsn.uk.net. Higher. Contents. Vectors 128 HSN23100 hsn.uk.net Higher Mthemtics UNIT 3 OUTCOME 1 Vectors Contents Vectors 18 1 Vectors nd Sclrs 18 Components 18 3 Mgnitude 130 4 Equl Vectors 131 5 Addition nd Subtrction of Vectors 13 6 Multipliction by

More information

QUADRATURE METHODS. July 19, 2011. Kenneth L. Judd. Hoover Institution

QUADRATURE METHODS. July 19, 2011. Kenneth L. Judd. Hoover Institution QUADRATURE METHODS Kenneth L. Judd Hoover Institution July 19, 2011 1 Integrtion Most integrls cnnot be evluted nlyticlly Integrls frequently rise in economics Expected utility Discounted utility nd profits

More information

CURVES ANDRÉ NEVES. that is, the curve α has finite length. v = p q p q. a i.e., the curve of smallest length connecting p to q is a straight line.

CURVES ANDRÉ NEVES. that is, the curve α has finite length. v = p q p q. a i.e., the curve of smallest length connecting p to q is a straight line. CURVES ANDRÉ NEVES 1. Problems (1) (Ex 1 of 1.3 of Do Crmo) Show tht the tngent line to the curve α(t) (3t, 3t 2, 2t 3 ) mkes constnt ngle with the line z x, y. (2) (Ex 6 of 1.3 of Do Crmo) Let α(t) (e

More information

Unambiguous Recognizable Two-dimensional Languages

Unambiguous Recognizable Two-dimensional Languages Unmbiguous Recognizble Two-dimensionl Lnguges Mrcell Anselmo, Dor Gimmrresi, Mri Mdoni, Antonio Restivo (Univ. of Slerno, Univ. Rom Tor Vergt, Univ. of Ctni, Univ. of Plermo) W2DL, My 26 REC fmily I REC

More information

g(y(a), y(b)) = o, B a y(a)+b b y(b)=c, Boundary Value Problems Lecture Notes to Accompany

g(y(a), y(b)) = o, B a y(a)+b b y(b)=c, Boundary Value Problems Lecture Notes to Accompany Lecture Notes to Accompny Scientific Computing An Introductory Survey Second Edition by Michel T Heth Boundry Vlue Problems Side conditions prescribing solution or derivtive vlues t specified points required

More information

RIGHT TRIANGLES AND THE PYTHAGOREAN TRIPLETS

RIGHT TRIANGLES AND THE PYTHAGOREAN TRIPLETS RIGHT TRIANGLES AND THE PYTHAGOREAN TRIPLETS Known for over 500 yers is the fct tht the sum of the squres of the legs of right tringle equls the squre of the hypotenuse. Tht is +b c. A simple proof is

More information

Binary Representation of Numbers Autar Kaw

Binary Representation of Numbers Autar Kaw Binry Representtion of Numbers Autr Kw After reding this chpter, you should be ble to: 1. convert bse- rel number to its binry representtion,. convert binry number to n equivlent bse- number. In everydy

More information

9.3. The Scalar Product. Introduction. Prerequisites. Learning Outcomes

9.3. The Scalar Product. Introduction. Prerequisites. Learning Outcomes The Sclr Product 9.3 Introduction There re two kinds of multipliction involving vectors. The first is known s the sclr product or dot product. This is so-clled becuse when the sclr product of two vectors

More information

Graphs on Logarithmic and Semilogarithmic Paper

Graphs on Logarithmic and Semilogarithmic Paper 0CH_PHClter_TMSETE_ 3//00 :3 PM Pge Grphs on Logrithmic nd Semilogrithmic Pper OBJECTIVES When ou hve completed this chpter, ou should be ble to: Mke grphs on logrithmic nd semilogrithmic pper. Grph empiricl

More information

Integration by Substitution

Integration by Substitution Integrtion by Substitution Dr. Philippe B. Lvl Kennesw Stte University August, 8 Abstrct This hndout contins mteril on very importnt integrtion method clled integrtion by substitution. Substitution is

More information

Lecture 3 Gaussian Probability Distribution

Lecture 3 Gaussian Probability Distribution Lecture 3 Gussin Probbility Distribution Introduction l Gussin probbility distribution is perhps the most used distribution in ll of science. u lso clled bell shped curve or norml distribution l Unlike

More information

Math 135 Circles and Completing the Square Examples

Math 135 Circles and Completing the Square Examples Mth 135 Circles nd Completing the Squre Exmples A perfect squre is number such tht = b 2 for some rel number b. Some exmples of perfect squres re 4 = 2 2, 16 = 4 2, 169 = 13 2. We wish to hve method for

More information

6.2 Volumes of Revolution: The Disk Method

6.2 Volumes of Revolution: The Disk Method mth ppliction: volumes of revolution, prt ii Volumes of Revolution: The Disk Method One of the simplest pplictions of integrtion (Theorem ) nd the ccumultion process is to determine so-clled volumes of

More information

9 CONTINUOUS DISTRIBUTIONS

9 CONTINUOUS DISTRIBUTIONS 9 CONTINUOUS DISTIBUTIONS A rndom vrible whose vlue my fll nywhere in rnge of vlues is continuous rndom vrible nd will be ssocited with some continuous distribution. Continuous distributions re to discrete

More information

SPECIAL PRODUCTS AND FACTORIZATION

SPECIAL PRODUCTS AND FACTORIZATION MODULE - Specil Products nd Fctoriztion 4 SPECIAL PRODUCTS AND FACTORIZATION In n erlier lesson you hve lernt multipliction of lgebric epressions, prticulrly polynomils. In the study of lgebr, we come

More information

Radius of the Earth - Radii Used in Geodesy James R. Clynch February 2006

Radius of the Earth - Radii Used in Geodesy James R. Clynch February 2006 dius of the Erth - dii Used in Geodesy Jmes. Clynch Februry 006 I. Erth dii Uses There is only one rdius of sphere. The erth is pproximtely sphere nd therefore, for some cses, this pproximtion is dequte.

More information

Operations with Polynomials

Operations with Polynomials 38 Chpter P Prerequisites P.4 Opertions with Polynomils Wht you should lern: Write polynomils in stndrd form nd identify the leding coefficients nd degrees of polynomils Add nd subtrct polynomils Multiply

More information

All pay auctions with certain and uncertain prizes a comment

All pay auctions with certain and uncertain prizes a comment CENTER FOR RESEARC IN ECONOMICS AND MANAGEMENT CREAM Publiction No. 1-2015 All py uctions with certin nd uncertin prizes comment Christin Riis All py uctions with certin nd uncertin prizes comment Christin

More information

The Velocity Factor of an Insulated Two-Wire Transmission Line

The Velocity Factor of an Insulated Two-Wire Transmission Line The Velocity Fctor of n Insulted Two-Wire Trnsmission Line Problem Kirk T. McDonld Joseph Henry Lbortories, Princeton University, Princeton, NJ 08544 Mrch 7, 008 Estimte the velocity fctor F = v/c nd the

More information

Integration. 148 Chapter 7 Integration

Integration. 148 Chapter 7 Integration 48 Chpter 7 Integrtion 7 Integrtion t ech, by supposing tht during ech tenth of second the object is going t constnt speed Since the object initilly hs speed, we gin suppose it mintins this speed, but

More information

4 Approximations. 4.1 Background. D. Levy

4 Approximations. 4.1 Background. D. Levy D. Levy 4 Approximtions 4.1 Bckground In this chpter we re interested in pproximtion problems. Generlly speking, strting from function f(x) we would like to find different function g(x) tht belongs to

More information

PROBLEMS 13 - APPLICATIONS OF DERIVATIVES Page 1

PROBLEMS 13 - APPLICATIONS OF DERIVATIVES Page 1 PROBLEMS - APPLICATIONS OF DERIVATIVES Pge ( ) Wter seeps out of conicl filter t the constnt rte of 5 cc / sec. When the height of wter level in the cone is 5 cm, find the rte t which the height decreses.

More information

Basic Analysis of Autarky and Free Trade Models

Basic Analysis of Autarky and Free Trade Models Bsic Anlysis of Autrky nd Free Trde Models AUTARKY Autrky condition in prticulr commodity mrket refers to sitution in which country does not engge in ny trde in tht commodity with other countries. Consequently

More information

INTERCHANGING TWO LIMITS. Zoran Kadelburg and Milosav M. Marjanović

INTERCHANGING TWO LIMITS. Zoran Kadelburg and Milosav M. Marjanović THE TEACHING OF MATHEMATICS 2005, Vol. VIII, 1, pp. 15 29 INTERCHANGING TWO LIMITS Zorn Kdelburg nd Milosv M. Mrjnović This pper is dedicted to the memory of our illustrious professor of nlysis Slobodn

More information

Rotating DC Motors Part II

Rotating DC Motors Part II Rotting Motors rt II II.1 Motor Equivlent Circuit The next step in our consiertion of motors is to evelop n equivlent circuit which cn be use to better unerstn motor opertion. The rmtures in rel motors

More information

COMPONENTS: COMBINED LOADING

COMPONENTS: COMBINED LOADING LECTURE COMPONENTS: COMBINED LOADING Third Edition A. J. Clrk School of Engineering Deprtment of Civil nd Environmentl Engineering 24 Chpter 8.4 by Dr. Ibrhim A. Asskkf SPRING 2003 ENES 220 Mechnics of

More information

Linear Equations in Two Variables

Linear Equations in Two Variables Liner Equtions in Two Vribles In this chpter, we ll use the geometry of lines to help us solve equtions. Liner equtions in two vribles If, b, ndr re rel numbers (nd if nd b re not both equl to 0) then

More information

. At first sight a! b seems an unwieldy formula but use of the following mnemonic will possibly help. a 1 a 2 a 3 a 1 a 2

. At first sight a! b seems an unwieldy formula but use of the following mnemonic will possibly help. a 1 a 2 a 3 a 1 a 2 7 CHAPTER THREE. Cross Product Given two vectors = (,, nd = (,, in R, the cross product of nd written! is defined to e: " = (!,!,! Note! clled cross is VECTOR (unlike which is sclr. Exmple (,, " (4,5,6

More information

Reasoning to Solve Equations and Inequalities

Reasoning to Solve Equations and Inequalities Lesson4 Resoning to Solve Equtions nd Inequlities In erlier work in this unit, you modeled situtions with severl vriles nd equtions. For exmple, suppose you were given usiness plns for concert showing

More information

Treatment Spring Late Summer Fall 0.10 5.56 3.85 0.61 6.97 3.01 1.91 3.01 2.13 2.99 5.33 2.50 1.06 3.53 6.10 Mean = 1.33 Mean = 4.88 Mean = 3.

Treatment Spring Late Summer Fall 0.10 5.56 3.85 0.61 6.97 3.01 1.91 3.01 2.13 2.99 5.33 2.50 1.06 3.53 6.10 Mean = 1.33 Mean = 4.88 Mean = 3. The nlysis of vrince (ANOVA) Although the t-test is one of the most commonly used sttisticl hypothesis tests, it hs limittions. The mjor limittion is tht the t-test cn be used to compre the mens of only

More information

Or more simply put, when adding or subtracting quantities, their uncertainties add.

Or more simply put, when adding or subtracting quantities, their uncertainties add. Propgtion of Uncertint through Mthemticl Opertions Since the untit of interest in n eperiment is rrel otined mesuring tht untit directl, we must understnd how error propgtes when mthemticl opertions re

More information

How fast can we sort? Sorting. Decision-tree model. Decision-tree for insertion sort Sort a 1, a 2, a 3. CS 3343 -- Spring 2009

How fast can we sort? Sorting. Decision-tree model. Decision-tree for insertion sort Sort a 1, a 2, a 3. CS 3343 -- Spring 2009 CS 4 -- Spring 2009 Sorting Crol Wenk Slides courtesy of Chrles Leiserson with smll chnges by Crol Wenk CS 4 Anlysis of Algorithms 1 How fst cn we sort? All the sorting lgorithms we hve seen so fr re comprison

More information

19. The Fermat-Euler Prime Number Theorem

19. The Fermat-Euler Prime Number Theorem 19. The Fermt-Euler Prime Number Theorem Every prime number of the form 4n 1 cn be written s sum of two squres in only one wy (side from the order of the summnds). This fmous theorem ws discovered bout

More information

Experiment 6: Friction

Experiment 6: Friction Experiment 6: Friction In previous lbs we studied Newton s lws in n idel setting, tht is, one where friction nd ir resistnce were ignored. However, from our everydy experience with motion, we know tht

More information

AREA OF A SURFACE OF REVOLUTION

AREA OF A SURFACE OF REVOLUTION AREA OF A SURFACE OF REVOLUTION h cut r πr h A surfce of revolution is formed when curve is rotted bout line. Such surfce is the lterl boundr of solid of revolution of the tpe discussed in Sections 7.

More information

Regular Sets and Expressions

Regular Sets and Expressions Regulr Sets nd Expressions Finite utomt re importnt in science, mthemtics, nd engineering. Engineers like them ecuse they re super models for circuits (And, since the dvent of VLSI systems sometimes finite

More information

UNIVERSITY OF OSLO FACULTY OF MATHEMATICS AND NATURAL SCIENCES

UNIVERSITY OF OSLO FACULTY OF MATHEMATICS AND NATURAL SCIENCES UNIVERSITY OF OSLO FACULTY OF MATHEMATICS AND NATURAL SCIENCES Solution to exm in: FYS30, Quntum mechnics Dy of exm: Nov. 30. 05 Permitted mteril: Approved clcultor, D.J. Griffiths: Introduction to Quntum

More information

Harvard College. Math 21a: Multivariable Calculus Formula and Theorem Review

Harvard College. Math 21a: Multivariable Calculus Formula and Theorem Review Hrvrd College Mth 21: Multivrible Clculus Formul nd Theorem Review Tommy McWillim, 13 tmcwillim@college.hrvrd.edu December 15, 2009 1 Contents Tble of Contents 4 9 Vectors nd the Geometry of Spce 5 9.1

More information

Drawing Diagrams From Labelled Graphs

Drawing Diagrams From Labelled Graphs Drwing Digrms From Lbelled Grphs Jérôme Thièvre 1 INA, 4, venue de l Europe, 94366 BRY SUR MARNE FRANCE Anne Verroust-Blondet 2 INRIA Rocquencourt, B.P. 105, 78153 LE CHESNAY Cedex FRANCE Mrie-Luce Viud

More information

Distributions. (corresponding to the cumulative distribution function for the discrete case).

Distributions. (corresponding to the cumulative distribution function for the discrete case). Distributions Recll tht n integrble function f : R [,] such tht R f()d = is clled probbility density function (pdf). The distribution function for the pdf is given by F() = (corresponding to the cumultive

More information

Module 2. Analysis of Statically Indeterminate Structures by the Matrix Force Method. Version 2 CE IIT, Kharagpur

Module 2. Analysis of Statically Indeterminate Structures by the Matrix Force Method. Version 2 CE IIT, Kharagpur Module Anlysis of Stticlly Indeterminte Structures by the Mtrix Force Method Version CE IIT, Khrgpur esson 9 The Force Method of Anlysis: Bems (Continued) Version CE IIT, Khrgpur Instructionl Objectives

More information

Homework 3 Solutions

Homework 3 Solutions CS 341: Foundtions of Computer Science II Prof. Mrvin Nkym Homework 3 Solutions 1. Give NFAs with the specified numer of sttes recognizing ech of the following lnguges. In ll cses, the lphet is Σ = {,1}.

More information

A.7.1 Trigonometric interpretation of dot product... 324. A.7.2 Geometric interpretation of dot product... 324

A.7.1 Trigonometric interpretation of dot product... 324. A.7.2 Geometric interpretation of dot product... 324 A P P E N D I X A Vectors CONTENTS A.1 Scling vector................................................ 321 A.2 Unit or Direction vectors...................................... 321 A.3 Vector ddition.................................................

More information

Review Problems for the Final of Math 121, Fall 2014

Review Problems for the Final of Math 121, Fall 2014 Review Problems for the Finl of Mth, Fll The following is collection of vrious types of smple problems covering sections.,.5, nd.7 6.6 of the text which constitute only prt of the common Mth Finl. Since

More information

Scalar and Vector Quantities. A scalar is a quantity having only magnitude (and possibly phase). LECTURE 2a: VECTOR ANALYSIS Vector Algebra

Scalar and Vector Quantities. A scalar is a quantity having only magnitude (and possibly phase). LECTURE 2a: VECTOR ANALYSIS Vector Algebra Sclr nd Vector Quntities : VECTO NLYSIS Vector lgebr sclr is quntit hving onl mgnitude (nd possibl phse). Emples: voltge, current, chrge, energ, temperture vector is quntit hving direction in ddition to

More information

FUNCTIONS AND EQUATIONS. xεs. The simplest way to represent a set is by listing its members. We use the notation

FUNCTIONS AND EQUATIONS. xεs. The simplest way to represent a set is by listing its members. We use the notation FUNCTIONS AND EQUATIONS. SETS AND SUBSETS.. Definition of set. A set is ny collection of objects which re clled its elements. If x is n element of the set S, we sy tht x belongs to S nd write If y does

More information

PHY 140A: Solid State Physics. Solution to Homework #2

PHY 140A: Solid State Physics. Solution to Homework #2 PHY 140A: Solid Stte Physics Solution to Homework # TA: Xun Ji 1 October 14, 006 1 Emil: jixun@physics.ucl.edu Problem #1 Prove tht the reciprocl lttice for the reciprocl lttice is the originl lttice.

More information

1. In the Bohr model, compare the magnitudes of the electron s kinetic and potential energies in orbit. What does this imply?

1. In the Bohr model, compare the magnitudes of the electron s kinetic and potential energies in orbit. What does this imply? Assignment 3: Bohr s model nd lser fundmentls 1. In the Bohr model, compre the mgnitudes of the electron s kinetic nd potentil energies in orit. Wht does this imply? When n electron moves in n orit, the

More information

Online Multicommodity Routing with Time Windows

Online Multicommodity Routing with Time Windows Konrd-Zuse-Zentrum für Informtionstechnik Berlin Tkustrße 7 D-14195 Berlin-Dhlem Germny TOBIAS HARKS 1 STEFAN HEINZ MARC E. PFETSCH TJARK VREDEVELD 2 Online Multicommodity Routing with Time Windows 1 Institute

More information

On the degrees of freedom in GR

On the degrees of freedom in GR On the degrees of freedom in GR István Rácz Wigner RCP Budpest rcz.istvn@wigner.mt.hu University of the Bsque Country Bilbo, 27 My, 2015 István Rácz (Wigner RCP, Budpest) degrees of freedom 27 My, 2015

More information

Pentominoes. Pentominoes. Bruce Baguley Cascade Math Systems, LLC. The pentominoes are a simple-looking set of objects through which some powerful

Pentominoes. Pentominoes. Bruce Baguley Cascade Math Systems, LLC. The pentominoes are a simple-looking set of objects through which some powerful Pentominoes Bruce Bguley Cscde Mth Systems, LLC Astrct. Pentominoes nd their reltives the polyominoes, polycues, nd polyhypercues will e used to explore nd pply vrious importnt mthemticl concepts. In this

More information

Section 7-4 Translation of Axes

Section 7-4 Translation of Axes 62 7 ADDITIONAL TOPICS IN ANALYTIC GEOMETRY Section 7-4 Trnsltion of Aes Trnsltion of Aes Stndrd Equtions of Trnslted Conics Grphing Equtions of the Form A 2 C 2 D E F 0 Finding Equtions of Conics In the

More information

1.00/1.001 Introduction to Computers and Engineering Problem Solving Fall 2011 - Final Exam

1.00/1.001 Introduction to Computers and Engineering Problem Solving Fall 2011 - Final Exam 1./1.1 Introduction to Computers nd Engineering Problem Solving Fll 211 - Finl Exm Nme: MIT Emil: TA: Section: You hve 3 hours to complete this exm. In ll questions, you should ssume tht ll necessry pckges

More information

NOTES ON LINEAR TRANSFORMATIONS

NOTES ON LINEAR TRANSFORMATIONS NOTES ON LINEAR TRANSFORMATIONS Definition 1. Let V and W be vector spaces. A function T : V W is a linear transformation from V to W if the following two properties hold. i T v + v = T v + T v for all

More information

On the Robustness of Most Probable Explanations

On the Robustness of Most Probable Explanations On the Robustness of Most Probble Explntions Hei Chn School of Electricl Engineering nd Computer Science Oregon Stte University Corvllis, OR 97330 chnhe@eecs.oregonstte.edu Adnn Drwiche Computer Science

More information

1. Prove that the empty set is a subset of every set.

1. Prove that the empty set is a subset of every set. 1. Prove that the empty set is a subset of every set. Basic Topology Written by Men-Gen Tsai email: b89902089@ntu.edu.tw Proof: For any element x of the empty set, x is also an element of every set since

More information

2m + V ( ˆX) (1) 2. Consider a particle in one dimensions whose Hamiltonian is given by

2m + V ( ˆX) (1) 2. Consider a particle in one dimensions whose Hamiltonian is given by Teoretisk Fysik KTH Advnced QM SI2380), Exercise 8 12 1. 3 Consider prticle in one dimensions whose Hmiltonin is given by Ĥ = ˆP 2 2m + V ˆX) 1) with [ ˆP, ˆX] = i. By clculting [ ˆX, [ ˆX, Ĥ]] prove tht

More information

Real Analysis and Multivariable Calculus: Graduate Level Problems and Solutions. Igor Yanovsky

Real Analysis and Multivariable Calculus: Graduate Level Problems and Solutions. Igor Yanovsky Rel Anlysis nd Multivrible Clculus: Grdute Level Problems nd Solutions Igor Ynovsky 1 Rel Anlysis nd Multivrible Clculus Igor Ynovsky, 2005 2 Disclimer: This hndbook is intended to ssist grdute students

More information

Karlstad University. Division for Engineering Science, Physics and Mathematics. Yury V. Shestopalov and Yury G. Smirnov. Integral Equations

Karlstad University. Division for Engineering Science, Physics and Mathematics. Yury V. Shestopalov and Yury G. Smirnov. Integral Equations Krlstd University Division for Engineering Science, Physics nd Mthemtics Yury V. Shestoplov nd Yury G. Smirnov Integrl Equtions A compendium Krlstd Contents 1 Prefce 4 Notion nd exmples of integrl equtions

More information

Appendix D: Completing the Square and the Quadratic Formula. In Appendix A, two special cases of expanding brackets were considered:

Appendix D: Completing the Square and the Quadratic Formula. In Appendix A, two special cases of expanding brackets were considered: Appendi D: Completing the Squre nd the Qudrtic Formul Fctoring qudrtic epressions such s: + 6 + 8 ws one of the topics introduced in Appendi C. Fctoring qudrtic epressions is useful skill tht cn help you

More information

15.6. The mean value and the root-mean-square value of a function. Introduction. Prerequisites. Learning Outcomes. Learning Style

15.6. The mean value and the root-mean-square value of a function. Introduction. Prerequisites. Learning Outcomes. Learning Style The men vlue nd the root-men-squre vlue of function 5.6 Introduction Currents nd voltges often vry with time nd engineers my wish to know the verge vlue of such current or voltge over some prticulr time

More information

LECTURE #05. Learning Objectives. How does atomic packing factor change with different atom types? How do you calculate the density of a material?

LECTURE #05. Learning Objectives. How does atomic packing factor change with different atom types? How do you calculate the density of a material? LECTURE #05 Chpter : Pcking Densities nd Coordintion Lerning Objectives es How does tomic pcking fctor chnge with different tom types? How do you clculte the density of mteril? 2 Relevnt Reding for this

More information

Geometry 7-1 Geometric Mean and the Pythagorean Theorem

Geometry 7-1 Geometric Mean and the Pythagorean Theorem Geometry 7-1 Geometric Men nd the Pythgoren Theorem. Geometric Men 1. Def: The geometric men etween two positive numers nd is the positive numer x where: = x. x Ex 1: Find the geometric men etween the

More information

6 Energy Methods And The Energy of Waves MATH 22C

6 Energy Methods And The Energy of Waves MATH 22C 6 Energy Methods And The Energy of Wves MATH 22C. Conservtion of Energy We discuss the principle of conservtion of energy for ODE s, derive the energy ssocited with the hrmonic oscilltor, nd then use this

More information

Module Summary Sheets. C3, Methods for Advanced Mathematics (Version B reference to new book) Topic 2: Natural Logarithms and Exponentials

Module Summary Sheets. C3, Methods for Advanced Mathematics (Version B reference to new book) Topic 2: Natural Logarithms and Exponentials MEI Mthemtics in Ection nd Instry Topic : Proof MEI Structured Mthemtics Mole Summry Sheets C, Methods for Anced Mthemtics (Version B reference to new book) Topic : Nturl Logrithms nd Eponentils Topic

More information

Derivatives and Rates of Change

Derivatives and Rates of Change Section 2.1 Derivtives nd Rtes of Cnge 2010 Kiryl Tsiscnk Derivtives nd Rtes of Cnge Te Tngent Problem EXAMPLE: Grp te prbol y = x 2 nd te tngent line t te point P(1,1). Solution: We ve: DEFINITION: Te

More information

2.016 Hydrodynamics Prof. A.H. Techet

2.016 Hydrodynamics Prof. A.H. Techet .01 Hydrodynics Reding #.01 Hydrodynics Prof. A.H. Techet Added Mss For the cse of unstedy otion of bodies underwter or unstedy flow round objects, we ust consider the dditionl effect (force) resulting

More information

LECTURE #05. Learning Objective. To describe the geometry in and around a unit cell in terms of directions and planes.

LECTURE #05. Learning Objective. To describe the geometry in and around a unit cell in terms of directions and planes. LECTURE #05 Chpter 3: Lttice Positions, Directions nd Plnes Lerning Objective To describe the geometr in nd round unit cell in terms of directions nd plnes. 1 Relevnt Reding for this Lecture... Pges 64-83.

More information

The Definite Integral

The Definite Integral Chpter 4 The Definite Integrl 4. Determining distnce trveled from velocity Motivting Questions In this section, we strive to understnd the ides generted by the following importnt questions: If we know

More information

UNIVERSITY OF NOTTINGHAM. Discussion Papers in Economics STRATEGIC SECOND SOURCING IN A VERTICAL STRUCTURE

UNIVERSITY OF NOTTINGHAM. Discussion Papers in Economics STRATEGIC SECOND SOURCING IN A VERTICAL STRUCTURE UNVERSTY OF NOTTNGHAM Discussion Ppers in Economics Discussion Pper No. 04/15 STRATEGC SECOND SOURCNG N A VERTCAL STRUCTURE By Arijit Mukherjee September 004 DP 04/15 SSN 10-438 UNVERSTY OF NOTTNGHAM Discussion

More information

Section 5-4 Trigonometric Functions

Section 5-4 Trigonometric Functions 5- Trigonometric Functions Section 5- Trigonometric Functions Definition of the Trigonometric Functions Clcultor Evlution of Trigonometric Functions Definition of the Trigonometric Functions Alternte Form

More information

Vectors. The magnitude of a vector is its length, which can be determined by Pythagoras Theorem. The magnitude of a is written as a.

Vectors. The magnitude of a vector is its length, which can be determined by Pythagoras Theorem. The magnitude of a is written as a. Vectors mesurement which onl descries the mgnitude (i.e. size) of the oject is clled sclr quntit, e.g. Glsgow is 11 miles from irdrie. vector is quntit with mgnitude nd direction, e.g. Glsgow is 11 miles

More information

Algebra Review. How well do you remember your algebra?

Algebra Review. How well do you remember your algebra? Algebr Review How well do you remember your lgebr? 1 The Order of Opertions Wht do we men when we write + 4? If we multiply we get 6 nd dding 4 gives 10. But, if we dd + 4 = 7 first, then multiply by then

More information

Applications to Physics and Engineering

Applications to Physics and Engineering Section 7.5 Applictions to Physics nd Engineering Applictions to Physics nd Engineering Work The term work is used in everydy lnguge to men the totl mount of effort required to perform tsk. In physics

More information

www.mathsbox.org.uk e.g. f(x) = x domain x 0 (cannot find the square root of negative values)

www.mathsbox.org.uk e.g. f(x) = x domain x 0 (cannot find the square root of negative values) www.mthsbo.org.uk CORE SUMMARY NOTES Functions A function is rule which genertes ectl ONE OUTPUT for EVERY INPUT. To be defined full the function hs RULE tells ou how to clculte the output from the input

More information

The Riemann Integral. Chapter 1

The Riemann Integral. Chapter 1 Chpter The Riemnn Integrl now of some universities in Englnd where the Lebesgue integrl is tught in the first yer of mthemtics degree insted of the Riemnn integrl, but now of no universities in Englnd

More information

Redistributing the Gains from Trade through Non-linear. Lump-sum Transfers

Redistributing the Gains from Trade through Non-linear. Lump-sum Transfers Redistributing the Gins from Trde through Non-liner Lump-sum Trnsfers Ysukzu Ichino Fculty of Economics, Konn University April 21, 214 Abstrct I exmine lump-sum trnsfer rules to redistribute the gins from

More information

Novel Methods of Generating Self-Invertible Matrix for Hill Cipher Algorithm

Novel Methods of Generating Self-Invertible Matrix for Hill Cipher Algorithm Bibhudendr chry, Girij Snkr Rth, Srt Kumr Ptr, nd Sroj Kumr Pnigrhy Novel Methods of Generting Self-Invertible Mtrix for Hill Cipher lgorithm Bibhudendr chry Deprtment of Electronics & Communiction Engineering

More information

Thinking out of the Box... Problem It s a richer problem than we ever imagined

Thinking out of the Box... Problem It s a richer problem than we ever imagined From the Mthemtics Techer, Vol. 95, No. 8, pges 568-574 Wlter Dodge (not pictured) nd Steve Viktor Thinking out of the Bo... Problem It s richer problem thn we ever imgined The bo problem hs been stndrd

More information