The Secret Life of the ax + b Group

Size: px
Start display at page:

Download "The Secret Life of the ax + b Group"

Transcription

1 The Secret Life of the ax + b Group Linear function x ax + b are prominent if not ubiquitou in high chool mathematic, beginning in, or now before, Algebra I. In particular, they are prime exhibit in any dicuion of function. It i perhap trange, then, that the topic of compoition of linear function doe not receive more attention. Epecially, the aociated group, the affine group of the line, alo known a the ax + b group, along with it group law, i pretty univerally ignored. Thi note will explore ome way in which the ax + b group urface unacknowledged in high chool mathematic, and ome extenion of tandard topic which are uggeted by thi point of view. 1. Tranlation, dilation, and affine tranformation. Conider the function of tranlation by a contant a: T a : x x + a. Here a i any fixed number, and x i a real variable. A main property of function i that they can be compoed. We compute (T b T a )(x) = T b (T a (x)) = T a (x) + b = (x + a) + b = x + (a + b) = x + (b + a) = T b+a (x). (T rancomp) In other word, the compoite of T b and T a i T b+a. The family of tranlation i cloed under compoition, and for tranlation function, compoition mimic addition of real number. We may alo conider function of dilation, aka homogeneou linear function (or what in more modern mathematical parlance would be called imply linear function) D : x x. Here i a fixed non-zero real number, and x again i a real variable. If we compoe dilation, we get another one: (D t D )(x) = D t (D (x)) = td (x) = t(x) = (t)x = D t (x). (Dilcomp) Thu, dilation are another family of function which i cloed under compoition, and for dilation, compoition mimic multiplication of (non-zero number. We may alo compoe a tranlation and a dilation. Thi give a new kind of function, whoe traditional name in high chool algebra i linear function, but which we will try to call affine function, or affine mapping or affine tranformation. Thee are the mapping We can compoe two affine mapping: A,a (x) = T a D (x) = T a (D (x)) = x + a. (A,a A t.b )(x) = A,a (A t,b (x)) = A t,b (x) + a = (tx + b) + a = atx + b + a = A t,a+b (x). Thi how u that the collection of all affine mapping i cloed under compoition, and the compoition of affine tranformation i decribed by the rule (aka group law ) A,a A t,b = A t,a+b. (Affcomp) In thi connection, we note that A 1,0 i the identity map, and therefore that the compoition formula let u check that (A,a ) 1 = A 1. (AffInv) 1, a

2 Application 1: Solve the linear equation x + a = c. (L1) Solution: In term of affine mapping, thi equation ay that A,a (x) = c, o we can find x by inverting A,a : x = (A,a ) 1 (c) = A 1, a (c) = c a = c a. Remark: The equation x + a = c and a = c are often referred to in introductory algebra text a onetep equation, wherea the equation x + b = c i called a two-tep equation, reflecting the fact that we contruct A,a a a compoition of two tranformation, one dilation and one tranlation.. Conjugation and Fixed Point. Since the affine tranformation do not commute with each other, they act on themelve non-trivially by conjugation. Explicitly, we have In particular, A,a A t,b (A.,a ) 1 = A t,a+b A 1, a = A t,a+b ta = A t,()a+b. (Conj1) T a D t T a = A t,()a. (Conj) We are intereted in the fixed point of affine tranformation. Fixed point of tranformation behave in a very imple way under conjugation. Propoition.1: Let Φ and Ψ be tranformation of ome et X. Let F Ψ denote the et of fixed point for Ψ: F Ψ = {x X : Ψ(x) = x}. Then Thi i proved by a imple calculation. F Φ Ψ Φ 1 = Φ(F Ψ ). Of coure, the identity tranformation leave all point fixed. It i eay to check that non-trivial tranlation have no fixed point. Non-trivial dilation have the origin a a unique fixed point: if D (x) = x = x for any x 0, then ( 1)x = 0, whence 1 = 0, or = 1. Combining thi with the formula above for the conjugate of a dilation by a tranlation (or jut by direct computation), we conclude that Propoition.: If 1, the affine tranformation A,a ha the unique fixed point Corollary.3: Auming that 1 t, the affine tranformation A,a and A t.b commute with each other if and only if they have the ame fixed point. Proof: Two tranformation Φ and Ψ commute with each other if and only if the conjugate of Ψ by Φ i Ψ itelf. Applying thi to A,a and A t,b, and uing formula (Conj 1), we ee that A,a and A t,b commute a with each other if and only if (1 t)a + b = b, or (1 t)a = (1 )b, or 1 = b. But the two ide of the lat equation are exactly the fixed point of A,a and of A t,b repectively. Application : Solve the (general one-variable linear) equation a 1. x + a = tx + b. (L) Solution: In term of affine mapping, thi equation ay that A,a (x) = A t,b (x). Proceeding a before, and inverting A,a, we get x = (A,a ) 1 A t,b (x). Since the right hand ide of the equation alo involve x, we have not arrived at a olution. However, we have done omething. We can interpret thi equation a aying that x i a fiixed point for the tranformation (A,a ) 1 A t,b = A t = A t. According to Propoition., thi fixed point i x = b a 1 t = b a t., a + b, b a

3 Remark: Thi reult can of coure be found eaily by manipulation of the original equation. However, equation (L) i known to be coniderably harder for tudent to deal with than equation (L1). Equation (L1) can be olved by backtracking, or undoing the indicated operation in ucceion. In tranformational term, thi mean inverting A,a by firt applying (T a ) 1, and then applying (D ) 1. Thi trategy fail for equation (L); one mut add and ubtract term from both ide of the equation to iolate x on one ide, and one mut conolidate the term in x by uing the Ditributive Rule. The main point of the dicuion above i to point out the way in which equation (L) differ from (L1). Intead of calling for inverting a function, it call for finding a fixed point, a very different kind of problem. 3. Iteration and Difference Equation. It i often of interet to iterate tranformation. From the equation (TranComp) decribing the compoition of two tranlation, it i eay to conclude that for a tranlation T a, we have (T a ) n = T na. (T ranit) It i jut a eay to pa from the formula (Dilcomp) to an expreion for the iteration of a dilation: (D ) n = D n. (DilIt) Uing formula (Affcomp) to find the iteration of a general affine tranformation i not a traightforward. However, if we take adapt formula (Conj) by eting (1 t)a = b, then we can write A b D t (A b ) 1 = A t,b. Since conjugation preerve compoition, thi allow u to generalize formula (DilIt) to conclude that (A t,b ) n = A b (D t ) n (A b ) 1 = A tn, b(n ). (AffIt) Application 3: difference equation) a) Find a general formula for number {x n } defined by the iterative cheme (aka, x n+1 = x n + b. (T rdiff) b) Find a general formula for number {x n } defined by the iterative cheme x n+1 = tx n. (DilDiff) c) Find a general formula for number {x n } defined by the iterative cheme x n+1 = tx n + b. (AffDiff) Solution: Thee difference equation are repectively equivalent to x n+1 = T b (x n ), (T rdiff ) x n+1 = D t (x n ), (DilDiff ) and x n+1 = A t,b ((x n ). (AffDiff ) Conequently, they are olved by x n = (T b ) n (x o ) = x o + nb, x n = (D t ) n (x o ) = t n x o, 3 (T rdiffsoln) (DilDiffSoln)

4 and x n = (A t,b ) n (x o ) = A t n, b(n ) (x o ) = t n x o + b(1 tn ) = t n (x o b 1 t 1 t ) + b 1 t. (AffDiffSoln) Remark: i) Of coure, the third equation (AffDiff) include both of the other, o the correponding olution alo include both of the other. ii) Thee equation receive a fair amount of attention in ome algebra coure, and the difference cheme (TrDiff) i entailed in many pre- or proto-algebraic invetigation of pattern. iii) The olution (TrDiffSoln) and (DilDiffSoln) are relatively eay to come by. However, the general formula (AffDiff) preent more obtacle. Wherea the firt two application clearly are imply refined (ome might ay overly) interpretation of imple mathematic, the olution of (AffDiff) may be a place near where the line cro, and the tranformational olution i in ome way impler than a direct approach, which require the ummation of a geometric erie. Alternatively, thi approach can be thought of a howing that the ummation of a geometric erie, like o much ele in mathematic, i bound up with ymmetry. iv) The three difference cheme can be characterized a follow: a) A equence {x n } atifie an equation of the form (TrDiff) if and only if x n+1 x n = b (contant difference). b) A equence {x n } atifie an equation of the form (DilDiff) if and only if xn+1 x n = t (contant ratio). c) A equence {x n } atifie an equation of the form (AffDiff) if and only if xn+1 xn x n x n 1 = t (contant ratio of difference). 4. Action on Polynomial. So far, we have been looking at the compoition of affine function with themelve. However, we can compoe them with any function from R to R. We can compoe them on the right (precompoition) or on the left (potcompoition). The reult of thee operation how even more dramatically than the group law for the ax b group the difference order make when compoing function. Let P (x) = α n x n + α n 1 x n 1 + α n x n α 1 x + α o be a polynomial of degree n. Then and On the other hand and P T a (x) = α n (x + a) n + α n 1 (x + a) n 1 + α n (x + a) n α 1 (x + a) + α o, P D (x) = α n n x n + α n 1 n 1 x n 1 + α n n x n α 1 x + α o. T a P (x) = α n x n + α n 1 x n 1 + α n x n α 1 x + α o + a, D P (x) = α n x n + α n 1 x n 1 + α n x n α 1 x + α o. Thee formula are all expreed in term of power of x, except for the formula for P T a. We expand thi explicitly for quadratic and cubic polynomial. If Q(x) = α x + α 1 x + α o, then Q T a (x) = α x + (α 1 + α a)x + (α o + α 1 a + α a ). Similarly, for a cubic polynomial, C(x) = α 3 x 3 + α x + α 1 x + α o, then C T a (x) = α 3 x + (α + a)x + (α 1 + α a + a )x + (α 0 + α 1 a + α a + α 3 a 3 ). Given that we can tranform polynomial in thi explicit fahion by pre- and pot-compoing with affine tranformation, it i natural to ak whether we can ue tranformation to implify polynomial and polynomial equation. The anwer i a reounding ye! for quadratic polynomial, and ye alo for cubic. 4

5 A firt tep in implification of P i to eliminate the x n 1 term. Thi can in fact be done for a polynomial of any degree: we take a o = α n 1 nα n. Then we find that the x n 1 term alway vanihe. For a quadratic polynomial, we get Q(x) = Q T ao (x) = α x + (α o + α 1 ( α 1 α ) + α ( α 1 α ) ) = α x + (α o α 1 α + α 1 4α ) = α x + (α o α 1 4α ) = α x + ( 4α oα α 1 4α ), The implet thing to do next to implify Q i to pot-compoe with D 1 α. Thi give D 1 Q(x) = x + ( 4α oα α1 ) = x + γ α o. 4α Finally, if we potcompoe tranlation with γ o = 4αoα α 1, we obtain the monomial x. We record thi 4α reult. Propoition 4.1: Every quadratic polynomial Q i the tranform of Q o = x under precompoition by an appropriate tranlation, and potcompoition by an appropriate affine tranformation: Q = A,a Q o T b, for appropriate a, b and. Preciely, α x + α 1 x + α o = A,a x T b,, where = α, a = α 1 α, and b = α o a = 4α α o α 4α. Application 4: Solve the equation Q(x) = 0 for a given quadratic polynomial Q. Solution: If we have a quadratic equation, Q(x) = 0, then Propoition 3.1 ay that thi i equivalent to A,a Q 0 T b (x) = 0, with a, b and a pecified jut above. Tranforming by A,a 1, thi equation become Q o T a (x) = (A,a ) 1 (0) = a. Since Q o(x) = x, thi mean that T a (x) = ± a. Hence we finally conclude that x = T b (± a ) = b ± a. Remark: If we rewrite thi formula in term of the coefficient α j of Q, it become the quadratic formula. Thu, the quadratic formula may be thought of a a practical reflection of the fact that all quadratic function can be reduced to the implet poible one, Q o = x, by compoing appropriately with affine tranformation. In other word, if we know how to find quare root, we can olve any quadratic equation. Thi i another perpective on the quadratic formula: it reduce the olution of any quadratic equation to the problem of taking quare root. We turn now to cubic polynomial. If we tranlate by a o to eliminate the x term from C, we get and C(x) = C T ao (x) = α 3 x 3 + (α 1 + α ( α ) + ( α ) )x + (α o + α 1 ( α ) + α ( α ) + α 3 ( α ) 3 ) 5

6 = α 3 x 3 + (α 1 1 α )x + (α o α 1α + 3 α 3 7 α 3 α3 ) = β 3 x 3 + β 1 x + β o. If it hould happen that at thi point we have β 1 = 0, then we can proceed a we did with the quadratic, and olve c(x) = 0 by taking a cube root. From now on, we will aume that we are not in thi relatively imple cae, and that both β 1 and β 3 are non-zero. Thu we have two term involving x, the term x andx 3. We can adjut both of them by the ame calar via potcompoition with a dilation. Precompoition with a dilation adjut them by different power of the dilation factor. It turn out that we can adjut their ratio by any poitive factor. It turn out to be convenient to make β 1 three time the magnitude of β 3 Specifically, let u et = ± β 1 3β 3 1, where the ign i the ign of β 3, o that β 3 3 > 0. We then compute Q D (x) = β 3 3 x 3 + β 1 x + β o = 1 β 1 3 (x 3 ± 3x) + β 3 3β 3 1 o. Thi formula implie an analog of Propoition 3.1. Propoition 4.: Every cubic polynomial C i the tranform by pre- and potcompoition by affine tranform of one of three pecific cubic polynomial C ɛ (x) = x 3 + ɛ3x, where ɛ i equal to 1, 0, or -1: C(x) = A t,b C ɛ A,a, for appropriate affine tranformation A t,b and A,a. Preciely, α 3 x 3 + α x + α 1 x + α o = T,a (x 3 + ɛx) T t,b, where 3 t = α 3 δ, b = α 1 = α 3δ, = α 3 3 3δ t 3 = 9α3 In thee formula, ɛ = gn(3α 1 α 3 α ), and δ = 3α 1 α 3 α. Application 5: Solve the cubic equation C(x) = 0., a = α o + α3 9α 1 α α 3 7α3. Solution: Propoition 3. provide a reduction of thi problem to the problem of olving C ɛ (x) = y. More pecifically, if C i a in Propoition 3., then the equation C(x) = 0 i equivalent to A t,b C ɛ A,a (x) = 0, which i equivalent to C ɛ A,a (x) = A 1 t,b (0) = b t. If we can invert C ɛ, then we can turn thi equation to A,a (x) = C 1 ɛ ( b t ), or x = A 1,a(Cɛ 1 ( b t ) = 1 (C 1 ɛ ( b t ) a). If ɛ = 0, then computing Cɛ 1 amount to taking a cube root. Otherwie, there i no tandard notation which decribe c 1 ɛ. If ɛ = 1, then C ɛ i trictly monotone, and o i globally invertible a a function on R. Approximate value can be computed for Cɛ 1 (y) by mean of a computational cheme baed on the Newton-Raphon method. If ɛ = 1, then C ɛ i not globally invertible. For value of y between - and, there are three poible root x of C 1 (x) = y. One will be in the interval ( 1, 1), one will be greater than 1, and one will be le than -1. Iterative cheme to compute thee root preciely are fairly eay to contruct. Thi would be an approach to olving cubic equation parallel to the quadratic formula for quadratic. It i not nearly a elegant, becaue of the need for cae, but it i neverthele effective. 5. One parameter ubgroup. We hope the reader will agree that the application ketched above of the ax + b group in chool mathematic are intereting, and in fact, connect the ax + b group with key part (with the exception of normal form of cubic) of the high chool curriculum. However, the connection we will now dicu are in 6

7 ome ene more fundamental. They give inight into the nature of the function commonly tudied in high chool, and help to explain why we tudy thee particular function. The tranformation A,a depend on two parameter, the and the a. We are intereted in knowing the one-parameter ubgroup, the ubgroup which can be parametrized by a ingle variable. Formally, we call a et φ t of tranformation a one-parameter group if the φ t have multiplication law which mirror addition of number. That i a one-parameter group i a collection of tranformation φ uch that φ r φ = φ r+. OneP ar We hould alo require that φ depend continuouly on. We note that, a defined, a one-parameter group i not imply a collection of tranformation, it come with a parametrization φ. Thi mean that if we recale the group by ending c for ome contant c, then we will get the ame et of tranformation, but labeled by different numbe. We remark that uch recaling are the only way we can change parametrization, ubject to the conditiion (1P ). For if φ γ() i another parametrization of the T which give a one-parameter group, that i, which atifie (1P ), then γ() = c for ome contant c. To ee thi, we note that the group law implie that φ γ(r+) = φ γ(r) φ γ() = φ γ(r)+γ(). Auming that the φ are all ditinct, thi implie that γ( + t) = γ(r) + γ(). It i well-known, and we will not reheare the argument here, that the only continuou olution to thi functional equation are γ() = c for ome contant c. In the cae the parametrization of φ i not unique, the argument i lightly more elaborate. One mut analyze the poibilitie for redundancy. We will alo not do thi here. The one-to-one cae i the only one that will affect u here. An important fact about a one-parameter group i that all the operator in it necearily commute. Thi follow directly from the definition: the group law in a one-parameter group i modeled on the group law of R under addition, and thi i of coure commutative. Thi fact allow u almot immediately to determine the one-parameter ubgroup of the ax + b group; for we have een that if two (non-identity) tranformation commute, they are either both tranlation, or they have the ame fixed point (Corollary.3). Thi together with Propoition., the equation (Conj) of, and the dicuion above of reparametrization implie the following reult. Propoition 5.1: ax + b group are Up the conjugation and reparametrization, the one-parameter ubgroup of the T and D e 6. Function invariant under ymmetrie of both axe. We ak the following quetion: uppoe that we have a one-parameter group of affine tranformation acting on each axi: x φ r (x), and y ψ (y). What function Φ, if any, are compatible with thee action, in the ene that Φ(φ r (x)) = ψ r (Φ(x))? (Inv) We can think about the equation (Inv) in the following way. The graph of Φ i the curve coniting of the point [ ] x : x R Φ(x) in the carteian plane. We can combine the one-parameter group φ and ψ to get a one-parameter group of (affine) tranformation of the plane: [ x (φ ψ) r ( y ] ) = [ ] φr (x). (φ ψ) ψ r (y) The compatibility condition (Inv) imply amount to aking that the graph of Φ be tranformed into itelf by all tranformation (φ ψ) r, i.e., by the one-parameter group φ ψ. 7

8 What function are ingled out by the condition (Inv)? Evidently, thi depend on the one-parameter group φ and ψ. We know that, up to conjugation, there are two type of one parameter group, tranlation and dilation. Thi give u four cae to conider: We will conider thee cae in ucceion. TT) Both φ and ψ are group of tranlation. TD) The group φ conit of tranlation and the group ψ conit of dilation. DT) The group φ conit of dilation and the group ψ conit of tranlation. DD) Both group φ and ψ conit of dilation. Cae TT. Suppoe that φ (x) = x + a and ψ (y) = y + b. Then the condition (Inv) amount to Φ(x + a) = Φ(x) + b. Setting x = 0 and = t a, thi can be rewritten a Φ(t) = Φ(0) + b at. In other word, Φ i itelf jut an affine function (aka linear function, in the language of K-1), with dilation factor (aka lope) equal to the ratio b a of the caling of the x-tranlation group and the y-tranlation group. Cae TD. Suppoe again that φ (x) = x + a, but that now ψ x (y) = e b y. Then the condition (Inv) become Φ(x + a) = e b Φ(x). Again etting x = 0 and = t a, we find that Φ(t) = e b a t Φ(0). Thu in thi cae, Φ i a multiple of (or equivalently, a horizontal tranlation of) an exponential function. Cae DT. Here we revere the role of dilation and tranlation from the previou cae. We et φ (x) = e a x and ψ (y) = y + bt. Then the condition (Inv) read Φ(e a x) = Φ(x) + b. If we et x = 1 and e a = t, o that = ln(t) a, then we get the equation Φ(t) = Φ(1) + b a ln(t). Thu, Φ i an affine tranform of the natural logarithm function. The factor a b can be aborbed into the logarithm by uing a different bae, and the contant could alo be aborbed by tranlation Φ. Cae DD. Here both φ and ψ involve dilation: φ (x) = e a x, and ψ (y) = e b y. The compatibility condition (Inv) now read Φ(e a x) = e b Φ(x). Again etting x = 1 and e a = t, we ee that Φ(t) = e b Φ(1)) = (e a ) b a Φ(1) = t b a Φ(1). Thu, in thi cae, Φ i a multiple of a power function. In ummary, we ee that the baic function elementary function - linear function (aka affine or firt order function), exponential and logarithm function, and power function - which occupy o much attention in algebra/precalculu are ingled out by ymmetry conideration, pecifically, ymmetry with repect to affine tranformation. The other function which receive ubtantial attention in the late high chool curriculum are trigonometric function. Thee, epecially ine and coine, are alo deeply involved with ymmetry, pecifically with rotational ymmetry. Characteritic functional equation While it i debatable whether the above conideration need to be part of the high chool curriculum, I would argue that teacher hould undertand thee idea. Furthermore, there i another apect of thee idea which not only teacher hould be aware of, but hould be trongly conidered for incluion in normal precalculu coure. Thi i the matter of functional equation which are atified by, and which characterize, thee baic function. We will reprie the cae-by-cae dicuion above to bring out thee equation. Cae TT. Here the (Inv) relation i Φ(x + a) = Φ(x) + b. If we et a = x, then b = Φ(x ) Φ(0). Thu another wa of tating the relation (Inv) i Φ(x + x ) = Φ(x) + Φ(x ) Φ(0). (AffChar) We ee then that the function Φ = Φ Φ(0) which i the homogeneou linear function (aka, linear function) with the ame lope a Φ atifie the functional equation Φ(x + x ) = Φ(x) + Φ(x ). (LinChar)) A we have remarked, the equation (LinChar) characterize the function x cx: they are the only (continuou) function which atify (LinChar). Similarly the function x cx + d are characterized by the equation (AffChar). Indeed, a we have hown, Φ atifie (AffChar) if and only if Φ = Φ = Φ(0) atifie (LinChar). 8

9 Cae TD. The (Inv) relation i Φ(x + a) = e b Φ(x). Setting a = x, we have that e b = Φ(x ) Φ(0). Thu, in thi cae, Φ atifie the functional equation The correponding equation for the normalized function Φ = Φ(x + x ) = Φx)Φ(x ). (ExpM ultchar) Φ(0) Φ Φ(0) i Φ(x + x ) = Φ(x) Φ(x ). (ExpChar) Thi label capture the eential feature of the exponential function- that it convert addition into multiplication. A it label ugget, it characterize exponential function: any (continuou) function atifying it ha the form x c x for ome poitive number c (the bae of the exponent). Similarly, and by a reduction imilar to the one in cae TT, the equation (ExpMultChar) characterize multiple of exponential function. Cae DT. We will be omewhat briefer with the lat two cae. The (Inv) relation here i eentially the revere of the lat ituation: Φ(e a x) = Φ(x) + b. If we et e a = x, then b = Φ(x ) Φ(1), o we get the functional equation Φ(xx ) = Φ(x) + Φ(x ) Φ(1). (LogMultChar) The aociated normalized function i Φ = Φ Φ(1). It atifie the functional equation Φ(xx ) = Φ(x) + Φ(x ). (LogChar). Again the equation (LogCare) characterize logarithm function, and the equation (LogMultChar) characterize multiple of logarithm function. Cae DD. Finally, for the cae DD, the functional equation derived in the manner of the one above i The aociated homogeneou functional equation i Φ(xx ) = Φ(x)Φ(x ). (M ultp owerchar) Φ(1) Φ(xx ) = Φ(x) Φ(x ). (P owerchar) Again the only continuou olution to equation PowerChar are the exponential function. The equation (MultPowerChar) alo allow multiple of exponential function. We remark that, in the language of group theory, equation (PowerChar) i jut the functional equation for homomorphim from the multiplicative group of R to itelf. Thu, all the function that are invariant under one-parameter affine group which preerve the axe in the plane are characterized by imple functional equation. Thee equation are omewhat analogou to thoe characterizing the olution to the affine difference equation analyzed in 4. 9

Lecture 17: Analytic Functions and Integrals (See Chapter 14 in Boas)

Lecture 17: Analytic Functions and Integrals (See Chapter 14 in Boas) Lecture 7: Analytic Function and Integral (See Chapter 4 in Boa) Thi i a good point to take a brief detour and expand on our previou dicuion of complex variable and complex function of complex variable.

More information

Social Studies 201 Notes for November 14, 2003

Social Studies 201 Notes for November 14, 2003 1 Social Studie 201 Note for November 14, 2003 Etimation of a mean, mall ample ize Section 8.4, p. 501. When a reearcher ha only a mall ample ize available, the central limit theorem doe not apply to the

More information

7.2 INVERSE TRANSFORMS AND TRANSFORMS OF DERIVATIVES 281

7.2 INVERSE TRANSFORMS AND TRANSFORMS OF DERIVATIVES 281 72 INVERSE TRANSFORMS AND TRANSFORMS OF DERIVATIVES 28 and i 2 Show how Euler formula (page 33) can then be ued to deduce the reult a ( a) 2 b 2 {e at co bt} {e at in bt} b ( a) 2 b 2 5 Under what condition

More information

IEOR 3106: Fall 2013, Professor Whitt Topics for Discussion: Tuesday, November 19 Alternating Renewal Processes and The Renewal Equation

IEOR 3106: Fall 2013, Professor Whitt Topics for Discussion: Tuesday, November 19 Alternating Renewal Processes and The Renewal Equation IEOR 316: Fall 213, Profeor Whitt Topic for Dicuion: Tueday, November 19 Alternating Renewal Procee and The Renewal Equation 1 Alternating Renewal Procee An alternating renewal proce alternate between

More information

Nonlinear Single-Particle Dynamics in High Energy Accelerators

Nonlinear Single-Particle Dynamics in High Energy Accelerators Nonlinear Single-Particle Dynamic in High Energy Accelerator Part 6: Canonical Perturbation Theory Nonlinear Single-Particle Dynamic in High Energy Accelerator Thi coure conit of eight lecture: 1. Introduction

More information

DIFFERENTIAL EQUATIONS

DIFFERENTIAL EQUATIONS DIFFERENTIAL EQUATIONS Laplace Tranform Paul Dawkin Table of Content Preface... Laplace Tranform... Introduction... The Definition... 5 Laplace Tranform... 9 Invere Laplace Tranform... Step Function...4

More information

Laplace Transformation

Laplace Transformation Univerity of Technology Electromechanical Department Energy Branch Advance Mathematic Laplace Tranformation nd Cla Lecture 6 Page of 7 Laplace Tranformation Definition Suppoe that f(t) i a piecewie continuou

More information

Lecture 8: Period Finding: Simon s Problem over Z N

Lecture 8: Period Finding: Simon s Problem over Z N Quantum Computation (CMU 8-859BB, Fall 205) Lecture 8: Period Finding: Simon Problem over Z October 5, 205 Lecturer: John Wright Scribe: icola Rech Problem A mentioned previouly, period finding i a rephraing

More information

Social Studies 201 Notes for March 18, 2005

Social Studies 201 Notes for March 18, 2005 1 Social Studie 201 Note for March 18, 2005 Etimation of a mean, mall ample ize Section 8.4, p. 501. When a reearcher ha only a mall ample ize available, the central limit theorem doe not apply to the

More information

Chapter 4. The Laplace Transform Method

Chapter 4. The Laplace Transform Method Chapter 4. The Laplace Tranform Method The Laplace Tranform i a tranformation, meaning that it change a function into a new function. Actually, it i a linear tranformation, becaue it convert a linear combination

More information

Bogoliubov Transformation in Classical Mechanics

Bogoliubov Transformation in Classical Mechanics Bogoliubov Tranformation in Claical Mechanic Canonical Tranformation Suppoe we have a et of complex canonical variable, {a j }, and would like to conider another et of variable, {b }, b b ({a j }). How

More information

Dimensional Analysis A Tool for Guiding Mathematical Calculations

Dimensional Analysis A Tool for Guiding Mathematical Calculations Dimenional Analyi A Tool for Guiding Mathematical Calculation Dougla A. Kerr Iue 1 February 6, 2010 ABSTRACT AND INTRODUCTION In converting quantitie from one unit to another, we may know the applicable

More information

SOLUTIONS TO ALGEBRAIC GEOMETRY AND ARITHMETIC CURVES BY QING LIU. I will collect my solutions to some of the exercises in this book in this document.

SOLUTIONS TO ALGEBRAIC GEOMETRY AND ARITHMETIC CURVES BY QING LIU. I will collect my solutions to some of the exercises in this book in this document. SOLUTIONS TO ALGEBRAIC GEOMETRY AND ARITHMETIC CURVES BY QING LIU CİHAN BAHRAN I will collect my olution to ome of the exercie in thi book in thi document. Section 2.1 1. Let A = k[[t ]] be the ring of

More information

DIFFERENTIAL EQUATIONS Laplace Transforms. Paul Dawkins

DIFFERENTIAL EQUATIONS Laplace Transforms. Paul Dawkins DIFFERENTIAL EQUATIONS Laplace Tranform Paul Dawkin Table of Content Preface... Laplace Tranform... Introduction... The Definition... 5 Laplace Tranform... 9 Invere Laplace Tranform... Step Function...

More information

An Inequality for Nonnegative Matrices and the Inverse Eigenvalue Problem

An Inequality for Nonnegative Matrices and the Inverse Eigenvalue Problem An Inequality for Nonnegative Matrice and the Invere Eigenvalue Problem Robert Ream Program in Mathematical Science The Univerity of Texa at Dalla Box 83688, Richardon, Texa 7583-688 Abtract We preent

More information

Lecture 21. The Lovasz splitting-off lemma Topics in Combinatorial Optimization April 29th, 2004

Lecture 21. The Lovasz splitting-off lemma Topics in Combinatorial Optimization April 29th, 2004 18.997 Topic in Combinatorial Optimization April 29th, 2004 Lecture 21 Lecturer: Michel X. Goeman Scribe: Mohammad Mahdian 1 The Lovaz plitting-off lemma Lovaz plitting-off lemma tate the following. Theorem

More information

Problem Set 8 Solutions

Problem Set 8 Solutions Deign and Analyi of Algorithm April 29, 2015 Maachuett Intitute of Technology 6.046J/18.410J Prof. Erik Demaine, Srini Devada, and Nancy Lynch Problem Set 8 Solution Problem Set 8 Solution Thi problem

More information

Control Systems Analysis and Design by the Root-Locus Method

Control Systems Analysis and Design by the Root-Locus Method 6 Control Sytem Analyi and Deign by the Root-Locu Method 6 1 INTRODUCTION The baic characteritic of the tranient repone of a cloed-loop ytem i cloely related to the location of the cloed-loop pole. If

More information

MATEMATIK Datum: Tid: eftermiddag. A.Heintz Telefonvakt: Anders Martinsson Tel.:

MATEMATIK Datum: Tid: eftermiddag. A.Heintz Telefonvakt: Anders Martinsson Tel.: MATEMATIK Datum: 20-08-25 Tid: eftermiddag GU, Chalmer Hjälpmedel: inga A.Heintz Telefonvakt: Ander Martinon Tel.: 073-07926. Löningar till tenta i ODE och matematik modellering, MMG5, MVE6. Define what

More information

The Laplace Transform (Intro)

The Laplace Transform (Intro) 4 The Laplace Tranform (Intro) The Laplace tranform i a mathematical tool baed on integration that ha a number of application It particular, it can implify the olving of many differential equation We will

More information

Math Skills. Scientific Notation. Uncertainty in Measurements. Appendix A5 SKILLS HANDBOOK

Math Skills. Scientific Notation. Uncertainty in Measurements. Appendix A5 SKILLS HANDBOOK ppendix 5 Scientific Notation It i difficult to work with very large or very mall number when they are written in common decimal notation. Uually it i poible to accommodate uch number by changing the SI

More information

Convex Hulls of Curves Sam Burton

Convex Hulls of Curves Sam Burton Convex Hull of Curve Sam Burton 1 Introduction Thi paper will primarily be concerned with determining the face of convex hull of curve of the form C = {(t, t a, t b ) t [ 1, 1]}, a < b N in R 3. We hall

More information

Practice Problems - Week #7 Laplace - Step Functions, DE Solutions Solutions

Practice Problems - Week #7 Laplace - Step Functions, DE Solutions Solutions For Quetion -6, rewrite the piecewie function uing tep function, ketch their graph, and find F () = Lf(t). 0 0 < t < 2. f(t) = (t 2 4) 2 < t In tep-function form, f(t) = u 2 (t 2 4) The graph i the olid

More information

Linear Motion, Speed & Velocity

Linear Motion, Speed & Velocity Add Important Linear Motion, Speed & Velocity Page: 136 Linear Motion, Speed & Velocity NGSS Standard: N/A MA Curriculum Framework (006): 1.1, 1. AP Phyic 1 Learning Objective: 3.A.1.1, 3.A.1.3 Knowledge/Undertanding

More information

Lecture 9: Shor s Algorithm

Lecture 9: Shor s Algorithm Quantum Computation (CMU 8-859BB, Fall 05) Lecture 9: Shor Algorithm October 7, 05 Lecturer: Ryan O Donnell Scribe: Sidhanth Mohanty Overview Let u recall the period finding problem that wa et up a a function

More information

into a discrete time function. Recall that the table of Laplace/z-transforms is constructed by (i) selecting to get

into a discrete time function. Recall that the table of Laplace/z-transforms is constructed by (i) selecting to get Lecture 25 Introduction to Some Matlab c2d Code in Relation to Sampled Sytem here are many way to convert a continuou time function, { h( t) ; t [0, )} into a dicrete time function { h ( k) ; k {0,,, }}

More information

MAE140 Linear Circuits Fall 2012 Final, December 13th

MAE140 Linear Circuits Fall 2012 Final, December 13th MAE40 Linear Circuit Fall 202 Final, December 3th Intruction. Thi exam i open book. You may ue whatever written material you chooe, including your cla note and textbook. You may ue a hand calculator with

More information

THE THERMOELASTIC SQUARE

THE THERMOELASTIC SQUARE HE HERMOELASIC SQUARE A mnemonic for remembering thermodynamic identitie he tate of a material i the collection of variable uch a tre, train, temperature, entropy. A variable i a tate variable if it integral

More information

Reading assignment: In this chapter we will cover Sections Definition and the Laplace transform of simple functions

Reading assignment: In this chapter we will cover Sections Definition and the Laplace transform of simple functions Chapter 4 Laplace Tranform 4 Introduction Reading aignment: In thi chapter we will cover Section 4 45 4 Definition and the Laplace tranform of imple function Given f, a function of time, with value f(t

More information

The machines in the exercise work as follows:

The machines in the exercise work as follows: Tik-79.148 Spring 2001 Introduction to Theoretical Computer Science Tutorial 9 Solution to Demontration Exercie 4. Contructing a complex Turing machine can be very laboriou. With the help of machine chema

More information

THE SPLITTING SUBSPACE CONJECTURE

THE SPLITTING SUBSPACE CONJECTURE THE SPLITTING SUBSPAE ONJETURE ERI HEN AND DENNIS TSENG Abtract We anwer a uetion by Niederreiter concerning the enumeration of a cla of ubpace of finite dimenional vector pace over finite field by proving

More information

Vector-Space Methods and Kirchhoff Graphs for Reaction Networks

Vector-Space Methods and Kirchhoff Graphs for Reaction Networks Vector-Space Method and Kirchhoff Graph for Reaction Network Joeph D. Fehribach Fuel Cell Center WPI Mathematical Science and Chemical Engineering 00 Intitute Rd. Worceter, MA 0609-2247 Thi article preent

More information

Pikeville Independent Schools [ALGEBRA 1 CURRICULUM MAP ]

Pikeville Independent Schools [ALGEBRA 1 CURRICULUM MAP ] Pikeville Independent School [ALGEBRA 1 CURRICULUM MAP 20162017] Augut X X X 11 12 15 16 17 18 19 22 23 24 25 26 12 37 8 12 29 30 31 13 15 September 1 2 X 6 7 8 9 16 17 18 21 PreAlgebra Review Algebra

More information

TMA4125 Matematikk 4N Spring 2016

TMA4125 Matematikk 4N Spring 2016 Norwegian Univerity of Science and Technology Department of Mathematical Science TMA45 Matematikk 4N Spring 6 Solution to problem et 6 In general, unle ele i noted, if f i a function, then F = L(f denote

More information

Moment of Inertia of an Equilateral Triangle with Pivot at one Vertex

Moment of Inertia of an Equilateral Triangle with Pivot at one Vertex oment of nertia of an Equilateral Triangle with Pivot at one Vertex There are two wa (at leat) to derive the expreion f an equilateral triangle that i rotated about one vertex, and ll how ou both here.

More information

The Laplace Transform , Haynes Miller and Jeremy Orloff

The Laplace Transform , Haynes Miller and Jeremy Orloff The Laplace Tranform 8.3, Hayne Miller and Jeremy Orloff Laplace tranform baic: introduction An operator take a function a input and output another function. A tranform doe the ame thing with the added

More information

By Xiaoquan Wen and Matthew Stephens University of Michigan and University of Chicago

By Xiaoquan Wen and Matthew Stephens University of Michigan and University of Chicago Submitted to the Annal of Applied Statitic SUPPLEMENTARY APPENDIX TO BAYESIAN METHODS FOR GENETIC ASSOCIATION ANALYSIS WITH HETEROGENEOUS SUBGROUPS: FROM META-ANALYSES TO GENE-ENVIRONMENT INTERACTIONS

More information

Singular perturbation theory

Singular perturbation theory Singular perturbation theory Marc R. Rouel June 21, 2004 1 Introduction When we apply the teady-tate approximation (SSA) in chemical kinetic, we typically argue that ome of the intermediate are highly

More information

Symmetric Determinantal Representation of Formulas and Weakly Skew Circuits

Symmetric Determinantal Representation of Formulas and Weakly Skew Circuits Contemporary Mathematic Symmetric Determinantal Repreentation of Formula and Weakly Skew Circuit Bruno Grenet, Erich L. Kaltofen, Pacal Koiran, and Natacha Portier Abtract. We deploy algebraic complexity

More information

where F (x) (called the Similarity Factor (SF)) denotes the function

where F (x) (called the Similarity Factor (SF)) denotes the function italian journal of pure and applied mathematic n. 33 014 15 34) 15 GENERALIZED EXPONENTIAL OPERATORS AND DIFFERENCE EQUATIONS Mohammad Aif 1 Anju Gupta Department of Mathematic Kalindi College Univerity

More information

Fair Game Review. Chapter 7 A B C D E Name Date. Complete the number sentence with <, >, or =

Fair Game Review. Chapter 7 A B C D E Name Date. Complete the number sentence with <, >, or = Name Date Chapter 7 Fair Game Review Complete the number entence with , or =. 1. 3.4 3.45 2. 6.01 6.1 3. 3.50 3.5 4. 0.84 0.91 Find three decimal that make the number entence true. 5. 5.2 6. 2.65 >

More information

CHAPTER 8 OBSERVER BASED REDUCED ORDER CONTROLLER DESIGN FOR LARGE SCALE LINEAR DISCRETE-TIME CONTROL SYSTEMS

CHAPTER 8 OBSERVER BASED REDUCED ORDER CONTROLLER DESIGN FOR LARGE SCALE LINEAR DISCRETE-TIME CONTROL SYSTEMS CHAPTER 8 OBSERVER BASED REDUCED ORDER CONTROLLER DESIGN FOR LARGE SCALE LINEAR DISCRETE-TIME CONTROL SYSTEMS 8.1 INTRODUCTION 8.2 REDUCED ORDER MODEL DESIGN FOR LINEAR DISCRETE-TIME CONTROL SYSTEMS 8.3

More information

Solving Radical Equations

Solving Radical Equations 10. Solving Radical Equation Eential Quetion How can you olve an equation that contain quare root? Analyzing a Free-Falling Object MODELING WITH MATHEMATICS To be proficient in math, you need to routinely

More information

EE 508 Lecture 16. Filter Transformations. Lowpass to Bandpass Lowpass to Highpass Lowpass to Band-reject

EE 508 Lecture 16. Filter Transformations. Lowpass to Bandpass Lowpass to Highpass Lowpass to Band-reject EE 508 Lecture 6 Filter Tranformation Lowpa to Bandpa Lowpa to Highpa Lowpa to Band-reject Review from Lat Time Theorem: If the perimeter variation and contact reitance are neglected, the tandard deviation

More information

p. (The electron is a point particle with radius r = 0.)

p. (The electron is a point particle with radius r = 0.) - pin ½ Recall that in the H-atom olution, we howed that the fact that the wavefunction Ψ(r) i ingle-valued require that the angular momentum quantum nbr be integer: l = 0,,.. However, operator algebra

More information

Computers and Mathematics with Applications. Sharp algebraic periodicity conditions for linear higher order

Computers and Mathematics with Applications. Sharp algebraic periodicity conditions for linear higher order Computer and Mathematic with Application 64 (2012) 2262 2274 Content lit available at SciVere ScienceDirect Computer and Mathematic with Application journal homepage: wwweleviercom/locate/camwa Sharp algebraic

More information

USPAS Course on Recirculated and Energy Recovered Linear Accelerators

USPAS Course on Recirculated and Energy Recovered Linear Accelerators USPAS Coure on Recirculated and Energy Recovered Linear Accelerator G. A. Krafft and L. Merminga Jefferon Lab I. Bazarov Cornell Lecture 6 7 March 005 Lecture Outline. Invariant Ellipe Generated by a Unimodular

More information

HELICAL TUBES TOUCHING ONE ANOTHER OR THEMSELVES

HELICAL TUBES TOUCHING ONE ANOTHER OR THEMSELVES 15 TH INTERNATIONAL CONFERENCE ON GEOMETRY AND GRAPHICS 0 ISGG 1-5 AUGUST, 0, MONTREAL, CANADA HELICAL TUBES TOUCHING ONE ANOTHER OR THEMSELVES Peter MAYRHOFER and Dominic WALTER The Univerity of Innbruck,

More information

Reading assignment: In this chapter we will cover Sections Definition and the Laplace transform of simple functions

Reading assignment: In this chapter we will cover Sections Definition and the Laplace transform of simple functions Chapter 4 Laplace Tranform 4 Introduction Reading aignment: In thi chapter we will cover Section 4 45 4 Definition and the Laplace tranform of imple function Given f, a function of time, with value f(t

More information

OPTIMAL STOPPING FOR SHEPP S URN WITH RISK AVERSION

OPTIMAL STOPPING FOR SHEPP S URN WITH RISK AVERSION OPTIMAL STOPPING FOR SHEPP S URN WITH RISK AVERSION ROBERT CHEN 1, ILIE GRIGORESCU 1 AND MIN KANG 2 Abtract. An (m, p) urn contain m ball of value 1 and p ball of value +1. A player tart with fortune k

More information

UNIT 15 RELIABILITY EVALUATION OF k-out-of-n AND STANDBY SYSTEMS

UNIT 15 RELIABILITY EVALUATION OF k-out-of-n AND STANDBY SYSTEMS UNIT 1 RELIABILITY EVALUATION OF k-out-of-n AND STANDBY SYSTEMS Structure 1.1 Introduction Objective 1.2 Redundancy 1.3 Reliability of k-out-of-n Sytem 1.4 Reliability of Standby Sytem 1. Summary 1.6 Solution/Anwer

More information

Automatic Control Systems. Part III: Root Locus Technique

Automatic Control Systems. Part III: Root Locus Technique www.pdhcenter.com PDH Coure E40 www.pdhonline.org Automatic Control Sytem Part III: Root Locu Technique By Shih-Min Hu, Ph.D., P.E. Page of 30 www.pdhcenter.com PDH Coure E40 www.pdhonline.org VI. Root

More information

Fermi Distribution Function. n(e) T = 0 T > 0 E F

Fermi Distribution Function. n(e) T = 0 T > 0 E F LECTURE 3 Maxwell{Boltzmann, Fermi, and Boe Statitic Suppoe we have a ga of N identical point particle in a box ofvolume V. When we ay \ga", we mean that the particle are not interacting with one another.

More information

Chapter 5 Consistency, Zero Stability, and the Dahlquist Equivalence Theorem

Chapter 5 Consistency, Zero Stability, and the Dahlquist Equivalence Theorem Chapter 5 Conitency, Zero Stability, and the Dahlquit Equivalence Theorem In Chapter 2 we dicued convergence of numerical method and gave an experimental method for finding the rate of convergence (aka,

More information

ON THE APPROXIMATION ERROR IN HIGH DIMENSIONAL MODEL REPRESENTATION. Xiaoqun Wang

ON THE APPROXIMATION ERROR IN HIGH DIMENSIONAL MODEL REPRESENTATION. Xiaoqun Wang Proceeding of the 2008 Winter Simulation Conference S. J. Maon, R. R. Hill, L. Mönch, O. Roe, T. Jefferon, J. W. Fowler ed. ON THE APPROXIMATION ERROR IN HIGH DIMENSIONAL MODEL REPRESENTATION Xiaoqun Wang

More information

Correction for Simple System Example and Notes on Laplace Transforms / Deviation Variables ECHE 550 Fall 2002

Correction for Simple System Example and Notes on Laplace Transforms / Deviation Variables ECHE 550 Fall 2002 Correction for Simple Sytem Example and Note on Laplace Tranform / Deviation Variable ECHE 55 Fall 22 Conider a tank draining from an initial height of h o at time t =. With no flow into the tank (F in

More information

DYNAMIC MODELS FOR CONTROLLER DESIGN

DYNAMIC MODELS FOR CONTROLLER DESIGN DYNAMIC MODELS FOR CONTROLLER DESIGN M.T. Tham (996,999) Dept. of Chemical and Proce Engineering Newcatle upon Tyne, NE 7RU, UK.. INTRODUCTION The problem of deigning a good control ytem i baically that

More information

Question 1 Equivalent Circuits

Question 1 Equivalent Circuits MAE 40 inear ircuit Fall 2007 Final Intruction ) Thi exam i open book You may ue whatever written material you chooe, including your cla note and textbook You may ue a hand calculator with no communication

More information

Physics 741 Graduate Quantum Mechanics 1 Solutions to Final Exam, Fall 2014

Physics 741 Graduate Quantum Mechanics 1 Solutions to Final Exam, Fall 2014 Phyic 7 Graduate Quantum Mechanic Solution to inal Eam all 0 Each quetion i worth 5 point with point for each part marked eparately Some poibly ueful formula appear at the end of the tet In four dimenion

More information

Symmetry Lecture 9. 1 Gellmann-Nishijima relation

Symmetry Lecture 9. 1 Gellmann-Nishijima relation Symmetry Lecture 9 1 Gellmann-Nihijima relation In the lat lecture we found that the Gell-mann and Nihijima relation related Baryon number, charge, and the third component of iopin. Q = [(1/2)B + T 3 ]

More information

The Laplace Transform

The Laplace Transform Chapter 7 The Laplace Tranform 85 In thi chapter we will explore a method for olving linear differential equation with contant coefficient that i widely ued in electrical engineering. It involve the tranformation

More information

NCAAPMT Calculus Challenge Challenge #3 Due: October 26, 2011

NCAAPMT Calculus Challenge Challenge #3 Due: October 26, 2011 NCAAPMT Calculu Challenge 011 01 Challenge #3 Due: October 6, 011 A Model of Traffic Flow Everyone ha at ome time been on a multi-lane highway and encountered road contruction that required the traffic

More information

Feedback Control Systems (FCS)

Feedback Control Systems (FCS) Feedback Control Sytem (FCS) Lecture19-20 Routh-Herwitz Stability Criterion Dr. Imtiaz Huain email: imtiaz.huain@faculty.muet.edu.pk URL :http://imtiazhuainkalwar.weebly.com/ Stability of Higher Order

More information

Preemptive scheduling on a small number of hierarchical machines

Preemptive scheduling on a small number of hierarchical machines Available online at www.ciencedirect.com Information and Computation 06 (008) 60 619 www.elevier.com/locate/ic Preemptive cheduling on a mall number of hierarchical machine György Dóa a, Leah Eptein b,

More information

arxiv: v2 [math.nt] 30 Apr 2015

arxiv: v2 [math.nt] 30 Apr 2015 A THEOREM FOR DISTINCT ZEROS OF L-FUNCTIONS École Normale Supérieure arxiv:54.6556v [math.nt] 3 Apr 5 943 Cachan November 9, 7 Abtract In thi paper, we etablih a imple criterion for two L-function L and

More information

ON THE DETERMINATION OF NUMBERS BY THEIR SUMS OF A FIXED ORDER J. L. SELFRIDGE AND E. G. STRAUS

ON THE DETERMINATION OF NUMBERS BY THEIR SUMS OF A FIXED ORDER J. L. SELFRIDGE AND E. G. STRAUS ON THE DETERMINATION OF NUMBERS BY THEIR SUMS OF A FIXED ORDER J. L. SELFRIDGE AND E. G. STRAUS 1. Introduction. We wih to treat the following problem (uggeted by a problem of L. Moer [2]): Let {x} = {x

More information

Avoiding Forbidden Submatrices by Row Deletions

Avoiding Forbidden Submatrices by Row Deletions Avoiding Forbidden Submatrice by Row Deletion Sebatian Wernicke, Jochen Alber, Jen Gramm, Jiong Guo, and Rolf Niedermeier Wilhelm-Schickard-Intitut für Informatik, niverität Tübingen, Sand 13, D-72076

More information

Multicolor Sunflowers

Multicolor Sunflowers Multicolor Sunflower Dhruv Mubayi Lujia Wang October 19, 2017 Abtract A unflower i a collection of ditinct et uch that the interection of any two of them i the ame a the common interection C of all of

More information

NULL HELIX AND k-type NULL SLANT HELICES IN E 4 1

NULL HELIX AND k-type NULL SLANT HELICES IN E 4 1 REVISTA DE LA UNIÓN MATEMÁTICA ARGENTINA Vol. 57, No. 1, 2016, Page 71 83 Publihed online: March 3, 2016 NULL HELIX AND k-type NULL SLANT HELICES IN E 4 1 JINHUA QIAN AND YOUNG HO KIM Abtract. We tudy

More information

Homework #7 Solution. Solutions: ΔP L Δω. Fig. 1

Homework #7 Solution. Solutions: ΔP L Δω. Fig. 1 Homework #7 Solution Aignment:. through.6 Bergen & Vittal. M Solution: Modified Equation.6 becaue gen. peed not fed back * M (.0rad / MW ec)(00mw) rad /ec peed ( ) (60) 9.55r. p. m. 3600 ( 9.55) 3590.45r.

More information

The continuous time random walk (CTRW) was introduced by Montroll and Weiss 1.

The continuous time random walk (CTRW) was introduced by Montroll and Weiss 1. 1 I. CONTINUOUS TIME RANDOM WALK The continuou time random walk (CTRW) wa introduced by Montroll and Wei 1. Unlike dicrete time random walk treated o far, in the CTRW the number of jump n made by the walker

More information

Beta Burr XII OR Five Parameter Beta Lomax Distribution: Remarks and Characterizations

Beta Burr XII OR Five Parameter Beta Lomax Distribution: Remarks and Characterizations Marquette Univerity e-publication@marquette Mathematic, Statitic and Computer Science Faculty Reearch and Publication Mathematic, Statitic and Computer Science, Department of 6-1-2014 Beta Burr XII OR

More information

SOME RESULTS ON INFINITE POWER TOWERS

SOME RESULTS ON INFINITE POWER TOWERS NNTDM 16 2010) 3, 18-24 SOME RESULTS ON INFINITE POWER TOWERS Mladen Vailev - Miana 5, V. Hugo Str., Sofia 1124, Bulgaria E-mail:miana@abv.bg Abtract To my friend Kratyu Gumnerov In the paper the infinite

More information

Solving Differential Equations by the Laplace Transform and by Numerical Methods

Solving Differential Equations by the Laplace Transform and by Numerical Methods 36CH_PHCalter_TechMath_95099 3//007 :8 PM Page Solving Differential Equation by the Laplace Tranform and by Numerical Method OBJECTIVES When you have completed thi chapter, you hould be able to: Find the

More information

Lie series An old concept going back to Sophus Lie, but already used by Newton and made rigorous by Cauchy. Widely exploited, e.g.

Lie series An old concept going back to Sophus Lie, but already used by Newton and made rigorous by Cauchy. Widely exploited, e.g. ÄÁ Ë ÊÁ Ë Æ ÄÁ ÌÊ ÆË ÇÊÅË Lie erie An old concept going back to Sophu Lie, but already ued by Newton and made rigorou by Cauchy Widely exploited, eg, in differential geometry Ued a a method for numerical

More information

Introduction to Laplace Transform Techniques in Circuit Analysis

Introduction to Laplace Transform Techniques in Circuit Analysis Unit 6 Introduction to Laplace Tranform Technique in Circuit Analyi In thi unit we conider the application of Laplace Tranform to circuit analyi. A relevant dicuion of the one-ided Laplace tranform i found

More information

RaneNote BESSEL FILTER CROSSOVER

RaneNote BESSEL FILTER CROSSOVER RaneNote BESSEL FILTER CROSSOVER A Beel Filter Croover, and It Relation to Other Croover Beel Function Phae Shift Group Delay Beel, 3dB Down Introduction One of the way that a croover may be contructed

More information

A BATCH-ARRIVAL QUEUE WITH MULTIPLE SERVERS AND FUZZY PARAMETERS: PARAMETRIC PROGRAMMING APPROACH

A BATCH-ARRIVAL QUEUE WITH MULTIPLE SERVERS AND FUZZY PARAMETERS: PARAMETRIC PROGRAMMING APPROACH Mathematical and Computational Application Vol. 11 No. pp. 181-191 006. Aociation for Scientific Reearch A BATCH-ARRIVA QEE WITH MTIPE SERVERS AND FZZY PARAMETERS: PARAMETRIC PROGRAMMING APPROACH Jau-Chuan

More information

Alternate Dispersion Measures in Replicated Factorial Experiments

Alternate Dispersion Measures in Replicated Factorial Experiments Alternate Diperion Meaure in Replicated Factorial Experiment Neal A. Mackertich The Raytheon Company, Sudbury MA 02421 Jame C. Benneyan Northeatern Univerity, Boton MA 02115 Peter D. Krau The Raytheon

More information

SERIES COMPENSATION: VOLTAGE COMPENSATION USING DVR (Lectures 41-48)

SERIES COMPENSATION: VOLTAGE COMPENSATION USING DVR (Lectures 41-48) Chapter 5 SERIES COMPENSATION: VOLTAGE COMPENSATION USING DVR (Lecture 41-48) 5.1 Introduction Power ytem hould enure good quality of electric power upply, which mean voltage and current waveform hould

More information

Online Appendix for Managerial Attention and Worker Performance by Marina Halac and Andrea Prat

Online Appendix for Managerial Attention and Worker Performance by Marina Halac and Andrea Prat Online Appendix for Managerial Attention and Worker Performance by Marina Halac and Andrea Prat Thi Online Appendix contain the proof of our reult for the undicounted limit dicued in Section 2 of the paper,

More information

Comparing Means: t-tests for Two Independent Samples

Comparing Means: t-tests for Two Independent Samples Comparing ean: t-tet for Two Independent Sample Independent-eaure Deign t-tet for Two Independent Sample Allow reearcher to evaluate the mean difference between two population uing data from two eparate

More information

Unbounded solutions of second order discrete BVPs on infinite intervals

Unbounded solutions of second order discrete BVPs on infinite intervals Available online at www.tjna.com J. Nonlinear Sci. Appl. 9 206), 357 369 Reearch Article Unbounded olution of econd order dicrete BVP on infinite interval Hairong Lian a,, Jingwu Li a, Ravi P Agarwal b

More information

Physics 443 Homework 2 Solutions

Physics 443 Homework 2 Solutions Phyic 3 Homework Solution Problem 1 a Under the tranformation φx φ x λ a φλx Lagrangian Lx 1 µφx ρφx tranform a Lx 1 µ λ a φλx ρλ a φλx 1 λ +a 1 µφ λx ρλ a φλx. Moreover, note that action S d xlx i invariant

More information

Suggested Answers To Exercises. estimates variability in a sampling distribution of random means. About 68% of means fall

Suggested Answers To Exercises. estimates variability in a sampling distribution of random means. About 68% of means fall Beyond Significance Teting ( nd Edition), Rex B. Kline Suggeted Anwer To Exercie Chapter. The tatitic meaure variability among core at the cae level. In a normal ditribution, about 68% of the core fall

More information

Constant Force: Projectile Motion

Constant Force: Projectile Motion Contant Force: Projectile Motion Abtract In thi lab, you will launch an object with a pecific initial velocity (magnitude and direction) and determine the angle at which the range i a maximum. Other tak,

More information

The statistical properties of the primordial fluctuations

The statistical properties of the primordial fluctuations The tatitical propertie of the primordial fluctuation Lecturer: Prof. Paolo Creminelli Trancriber: Alexander Chen July 5, 0 Content Lecture Lecture 4 3 Lecture 3 6 Primordial Fluctuation Lecture Lecture

More information

Standard Guide for Conducting Ruggedness Tests 1

Standard Guide for Conducting Ruggedness Tests 1 Deignation: E 69 89 (Reapproved 996) Standard Guide for Conducting Ruggedne Tet AMERICA SOCIETY FOR TESTIG AD MATERIALS 00 Barr Harbor Dr., Wet Conhohocken, PA 948 Reprinted from the Annual Book of ASTM

More information

Codes Correcting Two Deletions

Codes Correcting Two Deletions 1 Code Correcting Two Deletion Ryan Gabry and Frederic Sala Spawar Sytem Center Univerity of California, Lo Angele ryan.gabry@navy.mil fredala@ucla.edu Abtract In thi work, we invetigate the problem of

More information

NON-LINEAR SYSTEM CONTROL

NON-LINEAR SYSTEM CONTROL Non-linear Proce Control NON-LINEAR SYSTEM CONTROL. Introduction In practice, all phyical procee exhibit ome non-linear behaviour. Furthermore, when a proce how trong non-linear behaviour, a linear model

More information

Lecture 4 Topic 3: General linear models (GLMs), the fundamentals of the analysis of variance (ANOVA), and completely randomized designs (CRDs)

Lecture 4 Topic 3: General linear models (GLMs), the fundamentals of the analysis of variance (ANOVA), and completely randomized designs (CRDs) Lecture 4 Topic 3: General linear model (GLM), the fundamental of the analyi of variance (ANOVA), and completely randomized deign (CRD) The general linear model One population: An obervation i explained

More information

Assignment for Mathematics for Economists Fall 2016

Assignment for Mathematics for Economists Fall 2016 Due date: Mon. Nov. 1. Reading: CSZ, Ch. 5, Ch. 8.1 Aignment for Mathematic for Economit Fall 016 We now turn to finihing our coverage of concavity/convexity. There are two part: Jenen inequality for concave/convex

More information

arxiv: v1 [math.ac] 30 Nov 2012

arxiv: v1 [math.ac] 30 Nov 2012 ON MODULAR INVARIANTS OF A VECTOR AND A COVECTOR YIN CHEN arxiv:73v [mathac 3 Nov Abtract Let S L (F q be the pecial linear group over a finite field F q, V be the -dimenional natural repreentation of

More information

Inquisitive Semantics and Implicature

Inquisitive Semantics and Implicature Utrecht Univerity Bachelor Thei (7.5 EC) Inquiitive Semantic and Implicature Author: Minke Brandenburg Student no. 3821838 Supervior: Dr. R. Iemhoff Augut 2014 ii Content 1 Introduction 1 2 Inquiitive

More information

DMA Departamento de Matemática e Aplicações Universidade do Minho

DMA Departamento de Matemática e Aplicações Universidade do Minho Univeridade do Minho DMA Departamento de Matemática e Aplicaçõe Univeridade do Minho Campu de Gualtar 470-057 Braga Portugal www.math.uminho.pt Univeridade do Minho Ecola de Ciência Departamento de Matemática

More information

Clustering Methods without Given Number of Clusters

Clustering Methods without Given Number of Clusters Clutering Method without Given Number of Cluter Peng Xu, Fei Liu Introduction A we now, mean method i a very effective algorithm of clutering. It mot powerful feature i the calability and implicity. However,

More information

Name: Solutions Exam 3

Name: Solutions Exam 3 Intruction. Anwer each of the quetion on your own paper. Put your name on each page of your paper. Be ure to how your work o that partial credit can be adequately aeed. Credit will not be given for anwer

More information

Math 273 Solutions to Review Problems for Exam 1

Math 273 Solutions to Review Problems for Exam 1 Math 7 Solution to Review Problem for Exam True or Fale? Circle ONE anwer for each Hint: For effective tudy, explain why if true and give a counterexample if fale (a) T or F : If a b and b c, then a c

More information

List coloring hypergraphs

List coloring hypergraphs Lit coloring hypergraph Penny Haxell Jacque Vertraete Department of Combinatoric and Optimization Univerity of Waterloo Waterloo, Ontario, Canada pehaxell@uwaterloo.ca Department of Mathematic Univerity

More information

Riemann s Functional Equation is Not a Valid Function and Its Implication on the Riemann Hypothesis. Armando M. Evangelista Jr.

Riemann s Functional Equation is Not a Valid Function and Its Implication on the Riemann Hypothesis. Armando M. Evangelista Jr. Riemann Functional Equation i Not a Valid Function and It Implication on the Riemann Hypothei By Armando M. Evangelita Jr. armando78973@gmail.com On Augut 28, 28 ABSTRACT Riemann functional equation wa

More information