Recall Taylor s Theorem for a function f(x) in three dimensions with a displacement δx = (δx, δy, δz): δx + δy + δz + higher order terms. = f. δx +.

Size: px
Start display at page:

Download "Recall Taylor s Theorem for a function f(x) in three dimensions with a displacement δx = (δx, δy, δz): δx + δy + δz + higher order terms. = f. δx +."

Transcription

1 Chpter 1 Vritionl Methos 1.1 Sttionry Vlues of Functions Recll Tylor s Theorem for function f(x) in three imensions with isplcement δx (δx, δy, δz): so tht f(x + δx) f(x) + f f f δx + δy + δz + higher orer terms x y z δf f(x + δx) f(x) f f f δx + δy + x y z δz + f. δx +. In the limit δx 0 we write f f. x. This result is true in ny number n of imensions. At n extremum ( mximum or minimum) f must be sttionry, i.e. the first vrition f must vnish for ll possible irections of x. This cn only hppen if f 0 there. Note tht if we try to fin the extrem of f by solving f 0, we my lso fin other sttionry points of f which re neither mxim nor minim, for instnce sle points. (This is the sme ifficulty s in one imension, where sttionry point my be point of inflection rther thn mximum or minimum.) If we nee to fin the extrem of f in boune region for instnce, within two-imensionl unit squre then not only must we solve f 0 but we must lso compre the resulting vlues of f with those on the bounry of the squre. It is quite possible for the mximum vlue to occur on the bounry without tht point being sttionry one. 1 R. E. Hunt, 2002

2 Constrine sttionry vlues Suppose tht we wish to fin the extrem of f(x) subject to constrint of the form g(x) c, where c is some constnt. In this cse, the first vrition f must still vnish, but now not ll possible irections for x re llowe: only those which lie in the surfce efine by g(x) c. Hence, since f f.x, the vector f must lie perpeniculr to the surfce. But recll tht the norml to surfce of the form g(x) c is in the irection g. Hence f must be prllel to g, i.e., f λ g for some sclr λ. This gives us the metho of Lgrnge s unetermine multiplier: solve the n equtions (f λg) 0 for x together with the single constrint eqution g(x) c. The resulting vlues of x give the sttionry points of f subject to the constrint. Note tht while solving the totl of n+1 equtions it is usully possible to eliminte λ without ever fining its vlue; hence the moniker unetermine. If there re two constrints g(x) c n h(x) k, then we nee multiplier for ech constrint, n we solve (f λg µh) 0 together with the two constrints. strightforwr. The extension to higher numbers of constrints is 1.2 Functionls Let y(x) be function of x in some intervl < x < b, n consier the efinite integrl F ( {y(x)} 2 + y (x)y (x) ) x. F is clerly inepenent of x; inste it epens only on the function y(x). F is simple exmple of functionl, n to show the epenence on y we normlly enote it F [y]. We cn think of functionls s n extension of the concept of function of mny vribles e.g. g(x 1, x 2,..., x n ), function of n vribles to function of n infinite number of vribles, becuse F epens on every single vlue tht y tkes in the rnge < x < b. 2 R. E. Hunt, 2002

3 We shll be concerne in this chpter with functionls of the form F [y] f(x, y, y ) x where f epens only on x n the vlue of y n its first erivtive t x. However, the theory cn be extene to more generl functionls (for exmple, with functions f(x, y, y, y, y,... ) which epen on higher erivtives, or ouble integrls with two inepenent vribles x 1 n x 2 inste of just x). 1.3 Vritionl Principles Functionls re useful becuse mny lws of physics n of physicl chemistry cn be recst s sttements tht some functionl F [y] is minimise. For exmple, hevy chin suspene between two fixe points hngs in equilibrium in such wy tht its totl grvittionl potentil energy (which cn be expresse s functionl) is minimise. A mechnicl system of hevy elstic strings minimises the totl potentil energy, both elstic n grvittionl. Similr principles pply when electric fiels n chrge prticles re present (we inclue the electrosttic potentil energy) n when chemicl rections tke plce (we inclue the chemicl potentil energy). Two funmentl exmples of such vritionl principles re ue to Fermt n Hmilton. Fermt s Principle Consier light ry pssing through meium of vrible refrctive inex µ(r). The pth it tkes between two fixe points A n B is such s to minimise the opticl pth length B A where l is the length of pth element. µ(r) l, Strictly speking, Fermt s principle only pplies in the geometricl optics pproximtion; i.e., when the wvelength of the light is smll compre with the physicl imensions of the opticl system, so tht light my be regre s rys. This is true for telescope, but not for Young s slits: when the geometricl optics pproximtion fils to hol, iffrction occurs. For exmple, consier ir bove hot surfce, sy trmc ro on hot y. The ir is hotter ner the ro n cooler bove, so tht µ is smller closer to the ro surfce. A light ry trvelling from cr to n observer minimises the opticl pth length by stying 3 R. E. Hunt, 2002

4 close to the ro, n so bens ppropritely. The light seems to the observer to come from low ngle, leing to virtul imge (n hence to the mirge effect). Hmilton s Principle of Lest Action Consier mechnicl system with kinetic energy T n potentil energy V which is in some given configurtion t time t 1 n some other configurtion t time t 2. Define the Lgrngin of the system by L T V, n efine the ction to be S t2 t 1 L t ( functionl which epens on the wy the system moves). Hmilton s principle sttes tht the ctul motion of the system is such s to minimise the ction. 1.4 The Clculus of Vritions How o we fin the function y(x) which minimises, or more generlly mkes sttionry, our rchetypl functionl F [y] f(x, y, y ) x, with fixe vlues of y t the en-points (viz. fixe y() n y(b))? We consier chnging y to some nerby function y(x) + δy(x), n clculte the corresponing chnge δf in F (to first orer in δy). Then F is sttionry when δf 0 for ll possible smll vritions δy. Note tht more nturl nottion woul be to write F rther thn δf, since we will consier only the first-orer chnge n ignore terms which re secon orer in δy. However, the nottion δ is tritionl in this context. 4 R. E. Hunt, 2002

5 Now δf F [y + δy] F [y] f(x, y + δy, y + (δy) ) x { f(x, y, y ) + f f δy + y y (δy) f(x, y, y ) x } x [using Tylor expnsion to first orer] { } f f δy + y y (δy) x [ f y δy ] b + { f y δy ( ) } f δy x x y [integrting by prts] { f y ( )} f δy x x y f(x, y, y ) x since δy 0 t x, b (becuse y(x) is fixe there). It is cler tht δf 0 for ll possible smll vritions δy(x) if n only if This is Euler s eqution. ( ) f f x y y. Nottion f/ y looks strnge becuse it mens ifferentite with respect to y, keeping x n y constnt, n it seems impossible for y to chnge if y oes not. But / y n / y in Euler s eqution re just forml erivtives (s though y n y were unconnecte) n in prctice it is esy to o strightforwr orinry prtil ifferentition. Exmple: if f(x, y, y ) x(y 2 y 2 ) then f y 2xy, f y 2xy. Note however tht /x n / x men very ifferent things: / x mens keep y n y constnt wheres /x is so-clle full erivtive, so tht y n y re ifferentite with respect to x s well. 5 R. E. Hunt, 2002

6 but Continuing with the bove exmple, ( ) f 2y, x y Hence Euler s eqution for this exmple is ( ) f x y x (2xy ) 2y + 2xy. 2y + 2xy 2xy or y + 1 x y + y 0 (Bessel s eqution of orer 0, incientlly). Severl Depenent Vribles Wht if, inste of just one epenent vrible y(x), we hve n epenent vribles y 1 (x), y 2 (x),..., y n (x), so tht our functionl is F [y 1,..., y n ] f(x, y 1,..., y n, y 1,..., y n) x? In this cse, Euler s eqution pplies to ech y i (x) inepenently, so tht ( ) f f x y i for i 1,..., n. y i The proof is very similr to before: δf n i1 { f δy f δy n + f y 1 y n y 1 (δy 1 ) + + f } y n (δy n ) x n i1 { f δy i + f } y i y i (δy i ) x { f ( )} f y i x y i δy i x using the sme mnipultions (Tylor expnsion n integrtion by prts). It is now cler tht we cn only hve δf 0 for ll possible vritions of ll the y i (x) if Euler s eqution pplies to ech n every one of the y i t the sme time. 6 R. E. Hunt, 2002

7 1.5 A First Integrl In some cses, it is possible to fin first integrl (i.e., constnt of the motion) of Euler s eqution. Consier f x f f + y x y + y f y (clculting f( x, y(x), y (x) ) using the chin rule). Using Euler s eqution, x f x f ( ) x + f y f + y x y y f x + x ( y f y ) [prouct rule] so tht ( f y f ) f x y x. Hence, if f hs no explicit x -epenence, so tht f/ x 0, we immeitely euce tht f y f y constnt. (Note tht f hs no explicit x-epenence mens tht x oes not itself pper in the expression for f, even though y n y implicitly epen on x; so f y 2 y 2 hs no explicit x-epenence while f x(y 2 y 2 ) oes.) If there re n epenent vribles y 1 (x),..., y n (x), then the first integrl bove is esily generlise to f if f hs no explicit x-epenence. n f y i y i1 i constnt 1.6 Applictions of Euler s Eqution Geoesics A geoesic is the shortest pth on given surfce between two specifie points A n B. We will illustrte the use of Euler s eqution with trivil exmple: geoesics on the Euclien plne. 7 R. E. Hunt, 2002

8 The totl length of pth from (x 1, y 1 ) to (x 2, y 2 ) long the pth y(x) is given by L B A B A l 1 + B A x2 + y 2 ( ) 2 y x2 x 1 + y 2 x. x x 1 Note tht we ssume tht y(x) is single-vlue, i.e., the pth oes not curve bck on itself. We wish to minimise L over ll possible pths y(x) with the en-points hel fixe, so tht y(x 1 ) y 1 n y(x 2 ) y 2 for ll pths. This is precisely our rchetypl vritionl problem with f(x, y, y ) 1 + y 2, n hence f y 0, The Euler eqution is therefore ( ) y 0 x 1 + y 2 f y y 1 + y 2. y 1 + y 2 k, constnt. So y 2 k 2 /(1 k 2 ). It is cler tht k ±1, so y is constnt, m sy. Hence the solutions of Euler s eqution re the functions y mx + c (where m n c re constnts) i.e., stright lines! To fin the prticulr vlues of m n c require in this cse we now substitute in the bounry conitions y(x 1 ) y 1, y(x 2 ) y 2. It is importnt to note two similrities with the technique of minimising function f(x) by solving f 0. Firstly, we hve not shown tht this stright line oes inee prouce minimum of L: we hve shown only tht L is sttionry for this choice, so it might be mximum or even some kin of point of inflection. It is usully esy to confirm tht we hve the correct solution by inspection in this cse it 8 R. E. Hunt, 2002

9 is obviously minimum. (There is no equivlent of the one-imensionl test f (x) > 0 for functionls, or t lest not one which is simple enough to be of ny use.) Seconly, ssuming tht we hve inee foun minimum, we hve shown only tht it is locl minimum, not globl one. Tht is, we hve shown only tht nerby pths hve greter length. Once gin, however, we usully confirm tht we hve the correct solution by inspection. Compre this ifficulty with the equivlent problem for functions, illustrte by the grph below. An lterntive metho of solution for this simple geoesic problem is to note tht f(x, y, y ) 1 + y 2 hs no explicit x-epenence, so we cn use the first integrl: const. f y f y 1 + y 2 y y 1 + y y 2, i.e., y is constnt (s before). The Brchistochrone A be slies own frictionless wire, strting from rest t point A. Wht shpe must the wire hve for the be to rech some lower point B in the shortest time? (A similr evice ws use in some erly clock mechnisms.) Using conservtion of energy, 1 2 mv2 mgy, i.e., v 2gy. Also l v t, so t x2 + y y 2 x. 2gy 2g y 9 R. E. Hunt, 2002

10 The time tken to rech B is therefore T [y] 1 2g xb y 2 y x n we wish to minimise this, subject to y(0) 0, y(x B ) y B. integrn hs no explicit x-epenence, so we use the first integrl 1 + y const. 2 y 1 + y 2 y y y 1 + y 2 y y 2 y 1 + y 2 We note tht the 1 y 1 + y 2. Hence y(1 + y 2 ) c, sy, constnt, so tht c y y or y y y x. c y Substitute y c sin 2 θ; then sin 2 θ x 2c 1 sin 2 sin θ cos θ θ θ 2c sin 2 θ θ c(1 cos 2θ) θ. Using the initil conition tht when y 0 (i.e., θ 0), x 0, we obtin x c(θ 1 sin 2θ), 2 y c sin 2 θ which is n inverte cycloi. The constnt c is foun by pplying the other conition, y y B when x x B. 10 R. E. Hunt, 2002

11 Note tht strictly speking we shoul hve si tht y ± (c y)/y bove. Tking the negtive root inste of the positive one woul hve le to x c(θ 1 2 sin 2θ), y c sin 2 θ, which is exctly the sme curve but prmeterise in the opposite irection. It is rrely worth spening much time worrying bout such intriccies s they invribly le to the sme effective result. Light n Soun Consier light rys trvelling through meium with refrctive inex inversely proportionl to z where z is the height. By Fermt s principle, we must minimise l. z This is exctly the sme vritionl problem s for the Brchistochrone, so we conclue tht light rys will follow the pth of cycloi. More relisticlly, consier soun wves in ir. Soun wves obey principle similr to Fermt s: except t very long wvelengths, they trvel in such wy s to minimise the time tken to trvel from A to B, B A where c is the (vrible) spee of soun (comprble to 1/µ for light). Consier sitution where the bsolute temperture T of the ir is linerly relte to the height z, so tht l c, T αz + T 0 for some temperture T 0 t groun level. Since the spee of soun is proportionl to the squre root of the bsolute temperture, we hve c αz + T 0 Z sy. This les once gin to the Brchistochrone problem (for Z rther thn z), n we conclue tht soun wves follow pths z(x) which re prts of cyclois, scle verticlly by fctor 1/α (check this s n exercise). 1.7 Hmilton s Principle in Mechnicl Problems Hmilton s principle cn be use to solve mny complicte problems in rigi-boy mechnics. Consier mechnicl system whose configurtion cn be escribe by number of so-clle generlise coorintes q 1, q 2,..., q n. Exmples: A prticle with position vector r (x 1, x 2, x 3 ) moving through spce. Here we cn simply let q 1 x 1, q 2 x 2 n q 3 x 3 : there re three generlise coorintes. 11 R. E. Hunt, 2002

12 A penulum swinging in verticl plne: here there is only one generlise coorinte, q 1 θ, the ngle to the verticl. A rigi boy (sy top) spinning on its xis on smooth plne. This requires five generlise coorintes: two to escribe the position of the point of contct on the plne, one for the ngle of the xis to the verticl, one for the rottion of the xis bout the verticl, n one for the rottion of the top bout its own xis. The Lgrngin L T V is function of t, q 1,..., q n n q 1,..., q n, so ( S L t, q1 (t),..., q n (t), q 1 (t),..., q n (t) ) t. This is functionl with n epenent vribles q i (t), so we cn use Euler s eqution (with t plying the role of x, n q i (t) plying the role of y i (x)) for ech of the q i inepenently: ( ) L L t q i q i for ech i. In this context these equtions re known s the Euler Lgrnge equtions. In the cse when L hs no explicit time-epenence, the first integrl (from 1.5) gives us tht L n i1 q i L q i constnt. It is frequently the cse tht T is homogeneous qurtic in the q i, i.e., it is of the form n i1 n ij (q 1,..., q n ) q i q j j1 where the coefficients ij o not epen on ny of the generlise velocities q i or on t, n V lso oes not epen on the velocities or time so tht V V (q 1,..., q n ). Then it cn be shown tht L n i1 q i L q i (T V ) 2T (T + V ), i.e., the totl energy E T + V is conserve when there is no explicit time-epenence. This fils however when the externl forces vry with time or when the potentil is velocity-epenent, e.g., for motion in mgnetic fiel. 12 R. E. Hunt, 2002

13 A Prticle in Conservtive Force Fiel Here L 1 2 m(ẋ2 1 + ẋ ẋ 2 3) V (x 1, x 2, x 3 ); hence the Euler Lgrnge equtions re t (mẋ 1) V x 1, t (mẋ 2) V, x 2 t (mẋ 3) V, x 3 or in vector nottion (mṙ) V, t i.e., F m where F V is the force n r is the ccelertion. Two Intercting Prticles Consier Lgrngin L 1 2 m 1 ṙ m 2 ṙ 2 2 V (r 1 r 2 ), where the only force is conservtive one between two prticles with msses m 1 n m 2 t r 1 n r 2 respectively, n epens only on their (vector) seprtion. We coul use the six Crtesin coorintes of the prticles s generlise coorintes; but inste efine the reltive position vector, n r r 1 r 2, R m 1r 1 + m 2 r 2, M the position vector of the centre of mss, where M m 1 + m 2 is the totl mss. Now ṙ 1 2 Ṙ + m 2 M ṙ 2 n similrly m ) 2 (Ṙ + M ṙ m ) 2. (Ṙ + M ṙ Ṙ 2 + m2 2 M 2 ṙ 2 + 2m 2 M Ṙ. ṙ ṙ 2 2 Ṙ 2 + m2 1 M 2 ṙ 2 2m 1 M Ṙ. ṙ. Let r (x 1, x 2, x 3 ), R (X 1, X 2, X 3 ), n use these s generlise coorintes. Then L 1 2 M Ṙ 2 + m 1m 2 2M ṙ 2 V (r) 1 2 M(Ẋ2 1 + Ẋ2 2 + Ẋ2 3) + m 1m 2 2M (ẋ2 1 + ẋ ẋ 2 3) V (x 1, x 2, x 3 ). The Euler Lgrnge eqution for X i is therefore t (MẊi) 0, 13 R. E. Hunt, 2002

14 i.e., R 0 (the centre of mss moves with constnt velocity); n for x i is ( m1 m ) 2 t M ẋi V, x i i.e., µ r V where µ is the reuce mss m 1 m 2 /(m 1 + m 2 ) (the reltive position vector behves like prticle of mss µ). Note tht the kinetic energy T is homogeneous qurtic in the Ẋi n ẋ i ; tht V oes not epen on the Ẋi n ẋ i ; n tht L hs no explicit t-epenence. We cn euce immeitely tht the totl energy E T + V is conserve. 1.8 The Clculus of Vritions with Constrint In 1.1 we stuie constrine vrition of functions of severl vribles. The extension of this metho to functionls (i.e., functions of n infinite number of vribles) is strightforwr: to fin the sttionry vlues of functionl F [y] subject to G[y] c, we inste fin the sttionry vlues of F [y] λg[y], i.e., fin the function y which solves δ(f λg) 0, n then eliminte λ using G[y] c. 1.9 The Vritionl Principle for Sturm Liouville Equtions We shll show in this section tht the following three problems re equivlent: (i) Fin the eigenvlues λ n eigenfunctions y(x) which solve the Sturm Liouville problem ( ) p(x)y + q(x)y λw(x)y x in < x < b, where neither p nor w vnish in the intervl. (ii) Fin the functions y(x) for which F [y] is sttionry subject to G[y] 1 where G[y] (py 2 + qy 2 ) x wy 2 x. The eigenvlues of the equivlent Sturm Liouville problem in (i) re then given by the vlues of F [y]. 14 R. E. Hunt, 2002

15 (iii) Fin the functions y(x) for which Λ[y] F [y] G[y] is sttionry; the eigenvlues of the equivlent Sturm Liouville problem re then given by the vlues of Λ[y]. Hence Sturm Liouville problems cn be reformulte s vritionl problems. Note the similrity between (iii) n the sttionry property of the eigenvlues of symmetric mtrix (recll tht it is possible to fin the eigenvlues of symmetric mtrix A by fining the sttionry vlues of T A/ T over ll possible vectors ). The two fcts re in fct closely relte. To show tht (ii) is equivlent to (i), consier δ(f λg) δ Using Euler s eqution, F λg is sttionry when i.e., (py 2 + qy 2 λwy 2 ) x. x (2py ) 2qy 2λwy, x (py ) + qy λwy, which is the require Sturm Liouville problem: note tht the Lgrnge multiplier of the vritionl problem is the sme s the eigenvlue of the Sturm Liouville problem. Furthermore, multiplying the Sturm Liouville eqution by y n integrting, we obtin using the constrint. Hence ( y x (py ) + qy 2) x λ λ ( y x (py ) + qy 2) x [ ypy ] b + wy 2 x λg[y] λ (py 2 + qy 2 ) x [integrting by prts] (py 2 + qy 2 ) x F [y], using pproprite bounry conitions. This proves tht the sttionry vlues of F [y] give the eigenvlues. 15 R. E. Hunt, 2002

16 There re two wys of showing tht (ii) is equivlent to (iii). The first, informl wy is to note tht multiplying y by some constnt α sy oes not in fct chnge the vlue of Λ[y]. This implies tht when fining the sttionry vlues of Λ we cn choose to normlise y so tht G[y] 1, in which cse Λ is just equl to F [y]. So fining the sttionry vlues of Λ is equivlent to fining the sttionry vlues of F subject to G 1. The secon, forml wy is to clculte δλ F + δf G + δg F G F + δf G δf G F δg G 2 ( 1 δg G ) F G [using Tylor expnsion for (1 + δg/g) 1 to first orer] (gin to first orer). Hence δλ 0 if n only if δf (F/G) δg; tht is, Λ is sttionry if n only if δf Λ δg 0. But this is just the sme problem s (ii); so fining the sttionry vlues of Λ is the sme s fining the sttionry vlues of F subject to G 1. In the usul cse tht p(x), q(x) n w(x) re ll positive, we hve tht Λ[y] 0. Hence ll the eigenvlues must be non-negtive, n there must be smllest eigenvlue λ 0 ; Λ tkes the vlue λ 0 when y y 0, the corresponing eigenfunction. But wht is the bsolute minimum vlue of Λ over ll functions y(x)? If it were some vlue µ < λ 0, then µ woul be sttionry (minimum) vlue of Λ n woul therefore be n eigenvlue, contricting the sttement tht λ 0 is the smllest eigenvlue. Hence Λ[y] λ 0 for ny function y(x). As n exmple, consier the simple hrmonic oscilltor y + x 2 y λy subject to y 0 s x. This is n importnt exmple s it is goo moel for mny physicl oscillting systems. For instnce, the Schröinger eqution for itomic molecule hs pproximtely this form, where λ is proportionl to the quntum mechnicl energy level E; we woul like to know the groun stte energy, i.e., the eigenfunction with the lowest eigenvlue λ. Here p(x) 1, q(x) x 2 n w(x) 1, so Λ[y] (y 2 + x 2 y 2 ) x. y2 x 16 R. E. Hunt, 2002

17 We cn solve this Sturm Liouville problem exctly: the lowest eigenvlue turns out to be λ 0 1 with corresponing eigenfunction y 0 exp( 1 2 x2 ). But suppose inste tht we in t know this; we cn use the bove fcts bout Λ to try to guess t the vlue of λ 0. Let us use tril function y tril exp( 1 2 αx2 ), where α is positive constnt (in orer to stisfy the bounry conitions). Then Λ[y tril ] (α2 + 1) x2 exp( αx 2 ) x. exp( αx2 ) x We recll tht exp( αx2 ) x π/α n x2 exp( αx 2 ) x 1 2 π/α3 (by integrtion by prts). Hence Λ[y tril ] (α 2 + 1)/2α. We know tht Λ[y tril ], for ny α, cnnot be less thn λ 0. The smllest vlue of (α 2 + 1)/2α is 1, when α 1; we conclue tht λ 0 1, which gives us n upper boun on the lowest eigenvlue. In fct this metho hs given us the exct eigenvlue n eigenfunction; but tht is n ccient cuse by the fct tht this is prticulrly simple exmple! The Ryleigh Ritz Metho The Ryleigh Ritz metho is systemtic wy of estimting the eigenvlues, n in prticulr the lowest eigenvlue, of Sturm Liouville problem. The first step is to reformulte the problem s the vritionl principle tht Λ[y], the Ryleigh quotient, is sttionry. Seconly, using whtever clues re vilble (for exmple, symmetry consiertions or generl theorems such s the groun stte wvefunction hs no noes ) we mke n eucte guess y tril (x) t the true eigenfunction y 0 (x) with lowest eigenvlue λ 0. It is preferble for y tril to contin number of justble prmeters (e.g., α in the exmple bove). We cn now fin Λ[y tril ], which will epen on these justble prmeters. We clculte the minimum vlue Λ min of Λ with respect to ll the justble prmeters; we cn then stte tht the lowest eigenvlue λ 0 Λ min. If the tril function ws resonble guess then Λ min shoul ctully be goo pproximtion to λ 0. If we wish, we cn improve the pproximtion by introucing more justble prmeters. The fct tht Λ[y] is sttionry with respect to vritions in the function y mens tht if y tril is close to the true eigenfunction y 0 (sy within O(ε) of it) then the finl clculte vlue Λ min will be very goo pproximtion to λ 0 (within O(ε 2 ) in fct). If the inclusion 17 R. E. Hunt, 2002

18 of further justble prmeters fils to significntly improve the pproximtion then we cn be resonbly sure tht the pproximtion is goo one. Note tht if the tril function hppens to inclue the exct solution y 0 s specil cse of the justble prmeters, then the Ryleigh Ritz metho will fin both y 0 n λ 0 exctly. This is wht hppene in the exmple bove. An lterntive to clculting Λ[y tril ] n minimising it with respect to the justble prmeters is to clculte F [y tril ] n G[y tril ], n to minimise F subject to G 1. These proceures re equivlent, s we showe t the strt of this section. Higher eigenvlues [non-exminble] Once we hve foun goo pproximtion y 0 tril to y 0, we cn procee to fin pproximtions to the higher eigenvlues λ 1, λ 2,.... Just s λ 0 is the bsolute minimum of Λ[y] over ll possible functions y, so λ 1 is the bsolute minimum of Λ[y] over functions which re constrine to be orthogonl to y 0. (Recll tht y 1 is orthogonl to y 0 in the sense tht wy 0y 1 x 0.) Hence, to estimte λ 1 we procee s before but choose our new tril function y 1 tril in such wy tht it is orthogonl to our previous best pproximtion y 0 tril. This process cn be continue to higher n higher eigenvlues but of course becomes less n less ccurte. 18 R. E. Hunt, 2002

EULER-LAGRANGE EQUATIONS. Contents. 2. Variational formulation 2 3. Constrained systems and d Alembert principle Legendre transform 6

EULER-LAGRANGE EQUATIONS. Contents. 2. Variational formulation 2 3. Constrained systems and d Alembert principle Legendre transform 6 EULER-LAGRANGE EQUATIONS EUGENE LERMAN Contents 1. Clssicl system of N prticles in R 3 1 2. Vritionl formultion 2 3. Constrine systems n Alembert principle. 4 4. Legenre trnsform 6 1. Clssicl system of

More information

Conservation Law. Chapter Goal. 6.2 Theory

Conservation Law. Chapter Goal. 6.2 Theory Chpter 6 Conservtion Lw 6.1 Gol Our long term gol is to unerstn how mthemticl moels re erive. Here, we will stuy how certin quntity chnges with time in given region (sptil omin). We then first erive the

More information

Review of Calculus, cont d

Review of Calculus, cont d Jim Lmbers MAT 460 Fll Semester 2009-10 Lecture 3 Notes These notes correspond to Section 1.1 in the text. Review of Clculus, cont d Riemnn Sums nd the Definite Integrl There re mny cses in which some

More information

LECTURE 3. Orthogonal Functions. n X. It should be noted, however, that the vectors f i need not be orthogonal nor need they have unit length for

LECTURE 3. Orthogonal Functions. n X. It should be noted, however, that the vectors f i need not be orthogonal nor need they have unit length for ECTURE 3 Orthogonl Functions 1. Orthogonl Bses The pproprite setting for our iscussion of orthogonl functions is tht of liner lgebr. So let me recll some relevnt fcts bout nite imensionl vector spces.

More information

Physics 116C Solution of inhomogeneous ordinary differential equations using Green s functions

Physics 116C Solution of inhomogeneous ordinary differential equations using Green s functions Physics 6C Solution of inhomogeneous ordinry differentil equtions using Green s functions Peter Young November 5, 29 Homogeneous Equtions We hve studied, especilly in long HW problem, second order liner

More information

Notes on the Eigenfunction Method for solving differential equations

Notes on the Eigenfunction Method for solving differential equations Notes on the Eigenfunction Metho for solving ifferentil equtions Reminer: Wereconsieringtheinfinite-imensionlHilbertspceL 2 ([, b] of ll squre-integrble functions over the intervl [, b] (ie, b f(x 2

More information

f a L Most reasonable functions are continuous, as seen in the following theorem:

f a L Most reasonable functions are continuous, as seen in the following theorem: Limits Suppose f : R R. To sy lim f(x) = L x mens tht s x gets closer n closer to, then f(x) gets closer n closer to L. This suggests tht the grph of f looks like one of the following three pictures: f

More information

If we have a function f(x) which is well-defined for some a x b, its integral over those two values is defined as

If we have a function f(x) which is well-defined for some a x b, its integral over those two values is defined as Y. D. Chong (26) MH28: Complex Methos for the Sciences 2. Integrls If we hve function f(x) which is well-efine for some x, its integrl over those two vlues is efine s N ( ) f(x) = lim x f(x n ) where x

More information

MEG6007: Advanced Dynamics -Principles and Computational Methods (Fall, 2017) Lecture 4: Euler-Lagrange Equations via Hamilton s Principle

MEG6007: Advanced Dynamics -Principles and Computational Methods (Fall, 2017) Lecture 4: Euler-Lagrange Equations via Hamilton s Principle MEG6007: Avnce Dynmics -Principles n Computtionl Methos (Fll, 2017) Lecture 4: Euler-Lgrnge Equtions vi Hmilton s Principle This lecture covers: Begin with Alembert s Principle. Cst the virtul work emnting

More information

Partial Derivatives. Limits. For a single variable function f (x), the limit lim

Partial Derivatives. Limits. For a single variable function f (x), the limit lim Limits Prtil Derivtives For single vrible function f (x), the limit lim x f (x) exists only if the right-hnd side limit equls to the left-hnd side limit, i.e., lim f (x) = lim f (x). x x + For two vribles

More information

Chapter Five - Eigenvalues, Eigenfunctions, and All That

Chapter Five - Eigenvalues, Eigenfunctions, and All That Chpter Five - Eigenvlues, Eigenfunctions, n All Tht The prtil ifferentil eqution methos escrie in the previous chpter is specil cse of more generl setting in which we hve n eqution of the form L 1 xux,tl

More information

Calculus of Variations

Calculus of Variations Clculus of Vritions Com S 477/577 Notes) Yn-Bin Ji Dec 4, 2017 1 Introduction A functionl ssigns rel number to ech function or curve) in some clss. One might sy tht functionl is function of nother function

More information

Sturm-Liouville Theory

Sturm-Liouville Theory LECTURE 1 Sturm-Liouville Theory In the two preceing lectures I emonstrte the utility of Fourier series in solving PDE/BVPs. As we ll now see, Fourier series re just the tip of the iceerg of the theory

More information

Week 10: Line Integrals

Week 10: Line Integrals Week 10: Line Integrls Introduction In this finl week we return to prmetrised curves nd consider integrtion long such curves. We lredy sw this in Week 2 when we integrted long curve to find its length.

More information

Math 211A Homework. Edward Burkard. = tan (2x + z)

Math 211A Homework. Edward Burkard. = tan (2x + z) Mth A Homework Ewr Burkr Eercises 5-C Eercise 8 Show tht the utonomous system: 5 Plne Autonomous Systems = e sin 3y + sin cos + e z, y = sin ( + 3y, z = tn ( + z hs n unstble criticl point t = y = z =

More information

Best Approximation. Chapter The General Case

Best Approximation. Chapter The General Case Chpter 4 Best Approximtion 4.1 The Generl Cse In the previous chpter, we hve seen how n interpolting polynomil cn be used s n pproximtion to given function. We now wnt to find the best pproximtion to given

More information

Introduction to the Calculus of Variations

Introduction to the Calculus of Variations Introduction to the Clculus of Vritions Jim Fischer Mrch 20, 1999 Abstrct This is self-contined pper which introduces fundmentl problem in the clculus of vritions, the problem of finding extreme vlues

More information

Math 8 Winter 2015 Applications of Integration

Math 8 Winter 2015 Applications of Integration Mth 8 Winter 205 Applictions of Integrtion Here re few importnt pplictions of integrtion. The pplictions you my see on n exm in this course include only the Net Chnge Theorem (which is relly just the Fundmentl

More information

Practice Problems Solution

Practice Problems Solution Prctice Problems Solution Problem Consier D Simple Hrmonic Oscilltor escribe by the Hmiltonin Ĥ ˆp m + mwˆx Recll the rte of chnge of the expecttion of quntum mechnicl opertor t A ī A, H] + h A t. Let

More information

Improper Integrals, and Differential Equations

Improper Integrals, and Differential Equations Improper Integrls, nd Differentil Equtions October 22, 204 5.3 Improper Integrls Previously, we discussed how integrls correspond to res. More specificlly, we sid tht for function f(x), the region creted

More information

5.4, 6.1, 6.2 Handout. As we ve discussed, the integral is in some way the opposite of taking a derivative. The exact relationship

5.4, 6.1, 6.2 Handout. As we ve discussed, the integral is in some way the opposite of taking a derivative. The exact relationship 5.4, 6.1, 6.2 Hnout As we ve iscusse, the integrl is in some wy the opposite of tking erivtive. The exct reltionship is given by the Funmentl Theorem of Clculus: The Funmentl Theorem of Clculus: If f is

More information

4. Calculus of Variations

4. Calculus of Variations 4. Clculus of Vritions Introduction - Typicl Problems The clculus of vritions generlises the theory of mxim nd minim. Exmple (): Shortest distnce between two points. On given surfce (e.g. plne), nd the

More information

Recitation 3: Applications of the Derivative. 1 Higher-Order Derivatives and their Applications

Recitation 3: Applications of the Derivative. 1 Higher-Order Derivatives and their Applications Mth 1c TA: Pdric Brtlett Recittion 3: Applictions of the Derivtive Week 3 Cltech 013 1 Higher-Order Derivtives nd their Applictions Another thing we could wnt to do with the derivtive, motivted by wht

More information

Abstract inner product spaces

Abstract inner product spaces WEEK 4 Abstrct inner product spces Definition An inner product spce is vector spce V over the rel field R equipped with rule for multiplying vectors, such tht the product of two vectors is sclr, nd the

More information

221B Lecture Notes WKB Method

221B Lecture Notes WKB Method Clssicl Limit B Lecture Notes WKB Method Hmilton Jcobi Eqution We strt from the Schrödinger eqution for single prticle in potentil i h t ψ x, t = [ ] h m + V x ψ x, t. We cn rewrite this eqution by using

More information

SUPPLEMENTARY NOTES ON THE CONNECTION FORMULAE FOR THE SEMICLASSICAL APPROXIMATION

SUPPLEMENTARY NOTES ON THE CONNECTION FORMULAE FOR THE SEMICLASSICAL APPROXIMATION Physics 8.06 Apr, 2008 SUPPLEMENTARY NOTES ON THE CONNECTION FORMULAE FOR THE SEMICLASSICAL APPROXIMATION c R. L. Jffe 2002 The WKB connection formuls llow one to continue semiclssicl solutions from n

More information

Homework Assignment 5 Solution Set

Homework Assignment 5 Solution Set Homework Assignment 5 Solution Set PHYCS 44 3 Februry, 4 Problem Griffiths 3.8 The first imge chrge gurntees potentil of zero on the surfce. The secon imge chrge won t chnge the contribution to the potentil

More information

MATH34032: Green s Functions, Integral Equations and the Calculus of Variations 1

MATH34032: Green s Functions, Integral Equations and the Calculus of Variations 1 MATH34032: Green s Functions, Integrl Equtions nd the Clculus of Vritions 1 Section 1 Function spces nd opertors Here we gives some brief detils nd definitions, prticulrly relting to opertors. For further

More information

Figure 1: Double pendulum system

Figure 1: Double pendulum system Lecture 1 Introuction MATH-GA 710.001 Mechnics The purpose of this lecture is to motivte vritionl formultions of clssicl mechnics n to provie brief reminer of the essentil ies n results of the clculus

More information

Exam 2, Mathematics 4701, Section ETY6 6:05 pm 7:40 pm, March 31, 2016, IH-1105 Instructor: Attila Máté 1

Exam 2, Mathematics 4701, Section ETY6 6:05 pm 7:40 pm, March 31, 2016, IH-1105 Instructor: Attila Máté 1 Exm, Mthemtics 471, Section ETY6 6:5 pm 7:4 pm, Mrch 1, 16, IH-115 Instructor: Attil Máté 1 17 copies 1. ) Stte the usul sufficient condition for the fixed-point itertion to converge when solving the eqution

More information

CHM Physical Chemistry I Chapter 1 - Supplementary Material

CHM Physical Chemistry I Chapter 1 - Supplementary Material CHM 3410 - Physicl Chemistry I Chpter 1 - Supplementry Mteril For review of some bsic concepts in mth, see Atkins "Mthemticl Bckground 1 (pp 59-6), nd "Mthemticl Bckground " (pp 109-111). 1. Derivtion

More information

Chapter 2. Constraints, Lagrange s equations

Chapter 2. Constraints, Lagrange s equations Chpter Constrints, Lgrnge s equtions Section Constrints The position of the prticle or system follows certin rules due to constrints: Holonomic constrint: f (r. r,... r n, t) = 0 Constrints tht re not

More information

First midterm topics Second midterm topics End of quarter topics. Math 3B Review. Steve. 18 March 2009

First midterm topics Second midterm topics End of quarter topics. Math 3B Review. Steve. 18 March 2009 Mth 3B Review Steve 18 Mrch 2009 About the finl Fridy Mrch 20, 3pm-6pm, Lkretz 110 No notes, no book, no clcultor Ten questions Five review questions (Chpters 6,7,8) Five new questions (Chpters 9,10) No

More information

lim P(t a,b) = Differentiate (1) and use the definition of the probability current, j = i (

lim P(t a,b) = Differentiate (1) and use the definition of the probability current, j = i ( PHYS851 Quntum Mechnics I, Fll 2009 HOMEWORK ASSIGNMENT 7 1. The continuity eqution: The probbility tht prticle of mss m lies on the intervl [,b] t time t is Pt,b b x ψx,t 2 1 Differentite 1 n use the

More information

4.5 THE FUNDAMENTAL THEOREM OF CALCULUS

4.5 THE FUNDAMENTAL THEOREM OF CALCULUS 4.5 The Funmentl Theorem of Clculus Contemporry Clculus 4.5 THE FUNDAMENTAL THEOREM OF CALCULUS This section contins the most importnt n most use theorem of clculus, THE Funmentl Theorem of Clculus. Discovere

More information

The Wave Equation I. MA 436 Kurt Bryan

The Wave Equation I. MA 436 Kurt Bryan 1 Introduction The Wve Eqution I MA 436 Kurt Bryn Consider string stretching long the x xis, of indeterminte (or even infinite!) length. We wnt to derive n eqution which models the motion of the string

More information

The Regulated and Riemann Integrals

The Regulated and Riemann Integrals Chpter 1 The Regulted nd Riemnn Integrls 1.1 Introduction We will consider severl different pproches to defining the definite integrl f(x) dx of function f(x). These definitions will ll ssign the sme vlue

More information

Basic Derivative Properties

Basic Derivative Properties Bsic Derivtive Properties Let s strt this section by remining ourselves tht the erivtive is the slope of function Wht is the slope of constnt function? c FACT 2 Let f () =c, where c is constnt Then f 0

More information

221A Lecture Notes WKB Method

221A Lecture Notes WKB Method A Lecture Notes WKB Method Hmilton Jcobi Eqution We strt from the Schrödinger eqution for single prticle in potentil i h t ψ x, t = [ ] h m + V x ψ x, t. We cn rewrite this eqution by using ψ x, t = e

More information

Theoretical foundations of Gaussian quadrature

Theoretical foundations of Gaussian quadrature Theoreticl foundtions of Gussin qudrture 1 Inner product vector spce Definition 1. A vector spce (or liner spce) is set V = {u, v, w,...} in which the following two opertions re defined: (A) Addition of

More information

VII. The Integral. 50. Area under a Graph. y = f(x)

VII. The Integral. 50. Area under a Graph. y = f(x) VII. The Integrl In this chpter we efine the integrl of function on some intervl [, b]. The most common interprettion of the integrl is in terms of the re uner the grph of the given function, so tht is

More information

When e = 0 we obtain the case of a circle.

When e = 0 we obtain the case of a circle. 3.4 Conic sections Circles belong to specil clss of cures clle conic sections. Other such cures re the ellipse, prbol, n hyperbol. We will briefly escribe the stnr conics. These re chosen to he simple

More information

1.9 C 2 inner variations

1.9 C 2 inner variations 46 CHAPTER 1. INDIRECT METHODS 1.9 C 2 inner vritions So fr, we hve restricted ttention to liner vritions. These re vritions of the form vx; ǫ = ux + ǫφx where φ is in some liner perturbtion clss P, for

More information

Unit #9 : Definite Integral Properties; Fundamental Theorem of Calculus

Unit #9 : Definite Integral Properties; Fundamental Theorem of Calculus Unit #9 : Definite Integrl Properties; Fundmentl Theorem of Clculus Gols: Identify properties of definite integrls Define odd nd even functions, nd reltionship to integrl vlues Introduce the Fundmentl

More information

x dx does exist, what does the answer look like? What does the answer to

x dx does exist, what does the answer look like? What does the answer to Review Guie or MAT Finl Em Prt II. Mony Decemer th 8:.m. 9:5.m. (or the 8:3.m. clss) :.m. :5.m. (or the :3.m. clss) Prt is worth 5% o your Finl Em gre. NO CALCULATORS re llowe on this portion o the Finl

More information

Properties of Integrals, Indefinite Integrals. Goals: Definition of the Definite Integral Integral Calculations using Antiderivatives

Properties of Integrals, Indefinite Integrals. Goals: Definition of the Definite Integral Integral Calculations using Antiderivatives Block #6: Properties of Integrls, Indefinite Integrls Gols: Definition of the Definite Integrl Integrl Clcultions using Antiderivtives Properties of Integrls The Indefinite Integrl 1 Riemnn Sums - 1 Riemnn

More information

The Basic Functional 2 1

The Basic Functional 2 1 2 The Bsic Functionl 2 1 Chpter 2: THE BASIC FUNCTIONAL TABLE OF CONTENTS Pge 2.1 Introduction..................... 2 3 2.2 The First Vrition.................. 2 3 2.3 The Euler Eqution..................

More information

7.2 The Definite Integral

7.2 The Definite Integral 7.2 The Definite Integrl the definite integrl In the previous section, it ws found tht if function f is continuous nd nonnegtive, then the re under the grph of f on [, b] is given by F (b) F (), where

More information

Indefinite Integral. Chapter Integration - reverse of differentiation

Indefinite Integral. Chapter Integration - reverse of differentiation Chpter Indefinite Integrl Most of the mthemticl opertions hve inverse opertions. The inverse opertion of differentition is clled integrtion. For exmple, describing process t the given moment knowing the

More information

5.3 The Fundamental Theorem of Calculus

5.3 The Fundamental Theorem of Calculus CHAPTER 5. THE DEFINITE INTEGRAL 35 5.3 The Funmentl Theorem of Clculus Emple. Let f(t) t +. () Fin the re of the region below f(t), bove the t-is, n between t n t. (You my wnt to look up the re formul

More information

Introduction. Calculus I. Calculus II: The Area Problem

Introduction. Calculus I. Calculus II: The Area Problem Introuction Clculus I Clculus I h s its theme the slope problem How o we mke sense of the notion of slope for curves when we only know wht the slope of line mens? The nswer, of course, ws the to efine

More information

3.4 Conic sections. In polar coordinates (r, θ) conics are parameterized as. Next we consider the objects resulting from

3.4 Conic sections. In polar coordinates (r, θ) conics are parameterized as. Next we consider the objects resulting from 3.4 Conic sections Net we consier the objects resulting from + by + cy + + ey + f 0. Such type of cures re clle conics, becuse they rise from ifferent slices through cone In polr coorintes r, θ) conics

More information

Name Solutions to Test 3 November 8, 2017

Name Solutions to Test 3 November 8, 2017 Nme Solutions to Test 3 November 8, 07 This test consists of three prts. Plese note tht in prts II nd III, you cn skip one question of those offered. Some possibly useful formuls cn be found below. Brrier

More information

13.4 Work done by Constant Forces

13.4 Work done by Constant Forces 13.4 Work done by Constnt Forces We will begin our discussion of the concept of work by nlyzing the motion of n object in one dimension cted on by constnt forces. Let s consider the following exmple: push

More information

5.3 Nonlinear stability of Rayleigh-Bénard convection

5.3 Nonlinear stability of Rayleigh-Bénard convection 118 5.3 Nonliner stbility of Ryleigh-Bénrd convection In Chpter 1, we sw tht liner stbility only tells us whether system is stble or unstble to infinitesimlly-smll perturbtions, nd tht there re cses in

More information

ARITHMETIC OPERATIONS. The real numbers have the following properties: a b c ab ac

ARITHMETIC OPERATIONS. The real numbers have the following properties: a b c ab ac REVIEW OF ALGEBRA Here we review the bsic rules nd procedures of lgebr tht you need to know in order to be successful in clculus. ARITHMETIC OPERATIONS The rel numbers hve the following properties: b b

More information

Lecture 14: Quadrature

Lecture 14: Quadrature Lecture 14: Qudrture This lecture is concerned with the evlution of integrls fx)dx 1) over finite intervl [, b] The integrnd fx) is ssumed to be rel-vlues nd smooth The pproximtion of n integrl by numericl

More information

Recitation 3: More Applications of the Derivative

Recitation 3: More Applications of the Derivative Mth 1c TA: Pdric Brtlett Recittion 3: More Applictions of the Derivtive Week 3 Cltech 2012 1 Rndom Question Question 1 A grph consists of the following: A set V of vertices. A set E of edges where ech

More information

Introduction. Calculus I. Calculus II: The Area Problem

Introduction. Calculus I. Calculus II: The Area Problem Introuction Clculus I Clculus I h s its theme the slope problem How o we mke sense of the notion of slope for curves when we only know wht the slope of line mens? The nswer, of course, ws the to efine

More information

TIME VARYING MAGNETIC FIELDS AND MAXWELL S EQUATIONS

TIME VARYING MAGNETIC FIELDS AND MAXWELL S EQUATIONS TIME VARYING MAGNETIC FIED AND MAXWE EQUATION Introuction Electrosttic fiels re usull prouce b sttic electric chrges wheres mgnetosttic fiels re ue to motion of electric chrges with uniform velocit (irect

More information

Lecture 1. Functional series. Pointwise and uniform convergence.

Lecture 1. Functional series. Pointwise and uniform convergence. 1 Introduction. Lecture 1. Functionl series. Pointwise nd uniform convergence. In this course we study mongst other things Fourier series. The Fourier series for periodic function f(x) with period 2π is

More information

SUMMER KNOWHOW STUDY AND LEARNING CENTRE

SUMMER KNOWHOW STUDY AND LEARNING CENTRE SUMMER KNOWHOW STUDY AND LEARNING CENTRE Indices & Logrithms 2 Contents Indices.2 Frctionl Indices.4 Logrithms 6 Exponentil equtions. Simplifying Surds 13 Opertions on Surds..16 Scientific Nottion..18

More information

A REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H. Thomas Shores Department of Mathematics University of Nebraska Spring 2007

A REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H. Thomas Shores Department of Mathematics University of Nebraska Spring 2007 A REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H Thoms Shores Deprtment of Mthemtics University of Nebrsk Spring 2007 Contents Rtes of Chnge nd Derivtives 1 Dierentils 4 Are nd Integrls 5 Multivrite Clculus

More information

1.1 Functions. 0.1 Lines. 1.2 Linear Functions. 1.3 Rates of change. 0.2 Fractions. 0.3 Rules of exponents. 1.4 Applications of Functions to Economics

1.1 Functions. 0.1 Lines. 1.2 Linear Functions. 1.3 Rates of change. 0.2 Fractions. 0.3 Rules of exponents. 1.4 Applications of Functions to Economics 0.1 Lines Definition. Here re two forms of the eqution of line: y = mx + b y = m(x x 0 ) + y 0 ( m = slope, b = y-intercept, (x 0, y 0 ) = some given point ) slope-intercept point-slope There re two importnt

More information

Numerical Integration

Numerical Integration Chpter 5 Numericl Integrtion Numericl integrtion is the study of how the numericl vlue of n integrl cn be found. Methods of function pproximtion discussed in Chpter??, i.e., function pproximtion vi the

More information

Goals: Determine how to calculate the area described by a function. Define the definite integral. Explore the relationship between the definite

Goals: Determine how to calculate the area described by a function. Define the definite integral. Explore the relationship between the definite Unit #8 : The Integrl Gols: Determine how to clculte the re described by function. Define the definite integrl. Eplore the reltionship between the definite integrl nd re. Eplore wys to estimte the definite

More information

Classical Mechanics. From Molecular to Con/nuum Physics I WS 11/12 Emiliano Ippoli/ October, 2011

Classical Mechanics. From Molecular to Con/nuum Physics I WS 11/12 Emiliano Ippoli/ October, 2011 Clssicl Mechnics From Moleculr to Con/nuum Physics I WS 11/12 Emilino Ippoli/ October, 2011 Wednesdy, October 12, 2011 Review Mthemtics... Physics Bsic thermodynmics Temperture, idel gs, kinetic gs theory,

More information

20 MATHEMATICS POLYNOMIALS

20 MATHEMATICS POLYNOMIALS 0 MATHEMATICS POLYNOMIALS.1 Introduction In Clss IX, you hve studied polynomils in one vrible nd their degrees. Recll tht if p(x) is polynomil in x, the highest power of x in p(x) is clled the degree of

More information

Lecture XVII. Vector functions, vector and scalar fields Definition 1 A vector-valued function is a map associating vectors to real numbers, that is

Lecture XVII. Vector functions, vector and scalar fields Definition 1 A vector-valued function is a map associating vectors to real numbers, that is Lecture XVII Abstrct We introduce the concepts of vector functions, sclr nd vector fields nd stress their relevnce in pplied sciences. We study curves in three-dimensionl Eucliden spce nd introduce the

More information

Chapters 4 & 5 Integrals & Applications

Chapters 4 & 5 Integrals & Applications Contents Chpters 4 & 5 Integrls & Applictions Motivtion to Chpters 4 & 5 2 Chpter 4 3 Ares nd Distnces 3. VIDEO - Ares Under Functions............................................ 3.2 VIDEO - Applictions

More information

Chapter 5. , r = r 1 r 2 (1) µ = m 1 m 2. r, r 2 = R µ m 2. R(m 1 + m 2 ) + m 2 r = r 1. m 2. r = r 1. R + µ m 1

Chapter 5. , r = r 1 r 2 (1) µ = m 1 m 2. r, r 2 = R µ m 2. R(m 1 + m 2 ) + m 2 r = r 1. m 2. r = r 1. R + µ m 1 Tor Kjellsson Stockholm University Chpter 5 5. Strting with the following informtion: R = m r + m r m + m, r = r r we wnt to derive: µ = m m m + m r = R + µ m r, r = R µ m r 3 = µ m R + r, = µ m R r. 4

More information

Review of basic calculus

Review of basic calculus Review of bsic clculus This brief review reclls some of the most importnt concepts, definitions, nd theorems from bsic clculus. It is not intended to tech bsic clculus from scrtch. If ny of the items below

More information

4.4 Areas, Integrals and Antiderivatives

4.4 Areas, Integrals and Antiderivatives . res, integrls nd ntiderivtives 333. Ares, Integrls nd Antiderivtives This section explores properties of functions defined s res nd exmines some connections mong res, integrls nd ntiderivtives. In order

More information

p(t) dt + i 1 re it ireit dt =

p(t) dt + i 1 re it ireit dt = Note: This mteril is contined in Kreyszig, Chpter 13. Complex integrtion We will define integrls of complex functions long curves in C. (This is bit similr to [relvlued] line integrls P dx + Q dy in R2.)

More information

SPECIALIST MATHEMATICS

SPECIALIST MATHEMATICS Victorin Certificte of Euction 04 SUPERVISOR TO ATTACH PROCESSING LABEL HERE Letter STUDENT NUMBER SPECIALIST MATHEMATICS Written exmintion Friy 7 November 04 Reing time: 9.00 m to 9.5 m (5 minutes) Writing

More information

VI MAGNETIC EFFECTS OF CURRENTS

VI MAGNETIC EFFECTS OF CURRENTS V MAGNETC EFFECTS OF CURRENTS 6.1 Ampère s investigtions t ws Ampère who first estblishe n quntifie the force tht occurs between two currentcrrying conuctors. This is not quite s simple s the Coulomb lw

More information

THE EXISTENCE-UNIQUENESS THEOREM FOR FIRST-ORDER DIFFERENTIAL EQUATIONS.

THE EXISTENCE-UNIQUENESS THEOREM FOR FIRST-ORDER DIFFERENTIAL EQUATIONS. THE EXISTENCE-UNIQUENESS THEOREM FOR FIRST-ORDER DIFFERENTIAL EQUATIONS RADON ROSBOROUGH https://intuitiveexplntionscom/picrd-lindelof-theorem/ This document is proof of the existence-uniqueness theorem

More information

APPENDIX. Precalculus Review D.1. Real Numbers and the Real Number Line

APPENDIX. Precalculus Review D.1. Real Numbers and the Real Number Line APPENDIX D Preclculus Review APPENDIX D.1 Rel Numers n the Rel Numer Line Rel Numers n the Rel Numer Line Orer n Inequlities Asolute Vlue n Distnce Rel Numers n the Rel Numer Line Rel numers cn e represente

More information

Section 6.3 The Fundamental Theorem, Part I

Section 6.3 The Fundamental Theorem, Part I Section 6.3 The Funmentl Theorem, Prt I (3//8) Overview: The Funmentl Theorem of Clculus shows tht ifferentition n integrtion re, in sense, inverse opertions. It is presente in two prts. We previewe Prt

More information

Definition of Continuity: The function f(x) is continuous at x = a if f(a) exists and lim

Definition of Continuity: The function f(x) is continuous at x = a if f(a) exists and lim Mth 9 Course Summry/Study Guide Fll, 2005 [1] Limits Definition of Limit: We sy tht L is the limit of f(x) s x pproches if f(x) gets closer nd closer to L s x gets closer nd closer to. We write lim f(x)

More information

Main topics for the First Midterm

Main topics for the First Midterm Min topics for the First Midterm The Midterm will cover Section 1.8, Chpters 2-3, Sections 4.1-4.8, nd Sections 5.1-5.3 (essentilly ll of the mteril covered in clss). Be sure to know the results of the

More information

AP Calculus BC Review Applications of Integration (Chapter 6) noting that one common instance of a force is weight

AP Calculus BC Review Applications of Integration (Chapter 6) noting that one common instance of a force is weight AP Clculus BC Review Applictions of Integrtion (Chpter Things to Know n Be Able to Do Fin the re between two curves by integrting with respect to x or y Fin volumes by pproximtions with cross sections:

More information

1.3 The Lemma of DuBois-Reymond

1.3 The Lemma of DuBois-Reymond 28 CHAPTER 1. INDIRECT METHODS 1.3 The Lemm of DuBois-Reymond We needed extr regulrity to integrte by prts nd obtin the Euler- Lgrnge eqution. The following result shows tht, t lest sometimes, the extr

More information

Energy Bands Energy Bands and Band Gap. Phys463.nb Phenomenon

Energy Bands Energy Bands and Band Gap. Phys463.nb Phenomenon Phys463.nb 49 7 Energy Bnds Ref: textbook, Chpter 7 Q: Why re there insultors nd conductors? Q: Wht will hppen when n electron moves in crystl? In the previous chpter, we discussed free electron gses,

More information

Homework Problem Set 1 Solutions

Homework Problem Set 1 Solutions Chemistry 460 Dr. Jen M. Stnr Homework Problem Set 1 Solutions 1. Determine the outcomes of operting the following opertors on the functions liste. In these functions, is constnt..) opertor: / ; function:

More information

NUMERICAL INTEGRATION. The inverse process to differentiation in calculus is integration. Mathematically, integration is represented by.

NUMERICAL INTEGRATION. The inverse process to differentiation in calculus is integration. Mathematically, integration is represented by. NUMERICAL INTEGRATION 1 Introduction The inverse process to differentition in clculus is integrtion. Mthemticlly, integrtion is represented by f(x) dx which stnds for the integrl of the function f(x) with

More information

Section 4.8. D v(t j 1 ) t. (4.8.1) j=1

Section 4.8. D v(t j 1 ) t. (4.8.1) j=1 Difference Equtions to Differentil Equtions Section.8 Distnce, Position, nd the Length of Curves Although we motivted the definition of the definite integrl with the notion of re, there re mny pplictions

More information

Overview of Calculus I

Overview of Calculus I Overview of Clculus I Prof. Jim Swift Northern Arizon University There re three key concepts in clculus: The limit, the derivtive, nd the integrl. You need to understnd the definitions of these three things,

More information

Calculus I-II Review Sheet

Calculus I-II Review Sheet Clculus I-II Review Sheet 1 Definitions 1.1 Functions A function is f is incresing on n intervl if x y implies f(x) f(y), nd decresing if x y implies f(x) f(y). It is clled monotonic if it is either incresing

More information

MATH 144: Business Calculus Final Review

MATH 144: Business Calculus Final Review MATH 144: Business Clculus Finl Review 1 Skills 1. Clculte severl limits. 2. Find verticl nd horizontl symptotes for given rtionl function. 3. Clculte derivtive by definition. 4. Clculte severl derivtives

More information

CHAPTER 9 BASIC CONCEPTS OF DIFFERENTIAL AND INTEGRAL CALCULUS

CHAPTER 9 BASIC CONCEPTS OF DIFFERENTIAL AND INTEGRAL CALCULUS CHAPTER 9 BASIC CONCEPTS OF DIFFERENTIAL AND INTEGRAL CALCULUS BASIC CONCEPTS OF DIFFERENTIAL AND INTEGRAL CALCULUS LEARNING OBJECTIVES After stuying this chpter, you will be ble to: Unerstn the bsics

More information

Chapter 0. What is the Lebesgue integral about?

Chapter 0. What is the Lebesgue integral about? Chpter 0. Wht is the Lebesgue integrl bout? The pln is to hve tutoril sheet ech week, most often on Fridy, (to be done during the clss) where you will try to get used to the ides introduced in the previous

More information

Chapter 14. Matrix Representations of Linear Transformations

Chapter 14. Matrix Representations of Linear Transformations Chpter 4 Mtrix Representtions of Liner Trnsformtions When considering the Het Stte Evolution, we found tht we could describe this process using multipliction by mtrix. This ws nice becuse computers cn

More information

PHYS 4390: GENERAL RELATIVITY LECTURE 6: TENSOR CALCULUS

PHYS 4390: GENERAL RELATIVITY LECTURE 6: TENSOR CALCULUS PHYS 4390: GENERAL RELATIVITY LECTURE 6: TENSOR CALCULUS To strt on tensor clculus, we need to define differentition on mnifold.a good question to sk is if the prtil derivtive of tensor tensor on mnifold?

More information

Conservation Law. Chapter Goal. 5.2 Theory

Conservation Law. Chapter Goal. 5.2 Theory Chpter 5 Conservtion Lw 5.1 Gol Our long term gol is to understnd how mny mthemticl models re derived. We study how certin quntity chnges with time in given region (sptil domin). We first derive the very

More information

Jack Simons, Henry Eyring Scientist and Professor Chemistry Department University of Utah

Jack Simons, Henry Eyring Scientist and Professor Chemistry Department University of Utah 1. Born-Oppenheimer pprox.- energy surfces 2. Men-field (Hrtree-Fock) theory- orbitls 3. Pros nd cons of HF- RHF, UHF 4. Beyond HF- why? 5. First, one usully does HF-how? 6. Bsis sets nd nottions 7. MPn,

More information

Vidyalankar S.E. Sem. III [CMPN] Discrete Structures Prelim Question Paper Solution

Vidyalankar S.E. Sem. III [CMPN] Discrete Structures Prelim Question Paper Solution S.E. Sem. III [CMPN] Discrete Structures Prelim Question Pper Solution 1. () (i) Disjoint set wo sets re si to be isjoint if they hve no elements in common. Exmple : A = {0, 4, 7, 9} n B = {3, 17, 15}

More information

Math& 152 Section Integration by Parts

Math& 152 Section Integration by Parts Mth& 5 Section 7. - Integrtion by Prts Integrtion by prts is rule tht trnsforms the integrl of the product of two functions into other (idelly simpler) integrls. Recll from Clculus I tht given two differentible

More information

Solution to HW 4, Ma 1c Prac 2016

Solution to HW 4, Ma 1c Prac 2016 Solution to HW 4 M c Prc 6 Remrk: every function ppering in this homework set is sufficiently nice t lest C following the jrgon from the textbook we cn pply ll kinds of theorems from the textbook without

More information

W. We shall do so one by one, starting with I 1, and we shall do it greedily, trying

W. We shall do so one by one, starting with I 1, and we shall do it greedily, trying Vitli covers 1 Definition. A Vitli cover of set E R is set V of closed intervls with positive length so tht, for every δ > 0 nd every x E, there is some I V with λ(i ) < δ nd x I. 2 Lemm (Vitli covering)

More information