Introduction to Group Theory Note 2 Theory of Representation
|
|
- Marlene Dean
- 5 years ago
- Views:
Transcription
1 Introducton to Grou Teory Note Teory of Reresentton August 5, 009 Contents Grou Reresentton. De nton of Reresentton Reducble nd Irreducble Reresenttons Untry Reresentton Scur s Lemm 4 Gret Ortogonlty Teorem 6 4 Crcter of Reresentton 7 4. Decomoston of Reducble Reresentton Regulr Reresentton Crcter Tble Product Reresentton (Kronecker roduct) 6 Drect Product Grou Grou Reresentton In yscl lcton, te grou reresentton lys very mortnt role n deducng te consequence of te symmetres of te system. Rougly sekng, reresentton of grou s just some wy to relze te sme grou oerton oter tn te orgnl de nton of te grou. Of rtculr nterest to most ycl lcton s te relzton of grou oerton by te mtrces wose multlcton oerton cn be nturlly ssocted wt grou multlcton.. De nton of Reresentton Gven grou G = fa ; = ng : If for ec A G; tere s n n n mtrx D (A ) suc tt D (A ) D (A j ) = D (A A j ) ten D s forms n-dmensonl reresentton of te grou G. In oter words, te corresondence A D (A ) s omomorsm. Te condton n Eq smly mens tt te mtrces D (A ) stsfy te sme multlcton lw s te grou elments. If ts omomorsm turns out to be n somorsm ( ) ten te reresentton sclled ftful. Note tt mtrce M j cn be vewed s lner oertors M ctng on some vector sce V wt resect to some coce of bss e ; Me = e j M j j One wy to generte suc mtrces for te symmetry of certn geometrc objects s to use te grou nduced trnsformtons, dscussed before. Recll tt ec grou element A wll nduce trnsformton of te coordnte vector ~r; ~r A ~r Ten we cn tke ny functon of ~r; sy ' (~r) nd for ny grou element A de ne new trnsformton P A by
2 P A ' (~r) = ' A ~r Among te trnsformed functons obtned ts wy, P A ' (~r) ; P A ' (~r) ; P An ' (~r) ; we select te lnerly ndeendent set ' (~r) ; ' (~r) '` (~r) :Ten t s cler tt P A ' cn be exressed s lner combnton of ' ; P A ' = ` ' b D b (A ) nd D b (A ) forms reresentton of G: Ts cn be seen s follows. P AA j ' = P A P Aj ' = P A b D b (A j ) = c D cb (A ) D b (A j ) b:c: On te oter nd, b b= P AA j ' = c ' c D (A A j ) c Ts gves D (A A j ) c = D cb (A ) D b (A j ) wc mens tt D (A ) 0 s form reresentton of te grou. Exmle: Grou D ; symmetry of te trngle. As we ve dscussed n te revous cter, coosng coordnte system on te lne, we cn reresent te grou elements by te followng mtrces, A = K = 0 0 Coose f (~r) = f (x; y) = x y ; we get ; B = ; L = ; E = ; M = 0 0 P A f (~r) = f A ~r = x + y x y = 4 4 x y + xy: We now ve new functon g (x; y) = xy: We cn oerte on g (r) to get, P A g (~r) = g A ~r = x + y x y = x y xy = x y (xy) Tus we ve P A (f; g) = (f; g) Te mtrx generted ts wy s te sme s A s gven bove. Smlrly P B f (~r) = f B ~r = x y x + y = 4 4 x y + ( xy) P B g (~r) = g B ~r r + = x y x + y = + x y xy = x y ( x sme s B s gven before. Remrks P B (f; g) = (f; g)
3 . If (A) nd (A) re bot reresentton of te grou, ten t s cler tt (A) = (A) 0 0 (A) lso forms reresentton. We wll denote t s drect sum ; (A) = (A) (A) (block dgonl form) drect sum. If (A) nd (A) re reresenttons of G wt sme dmenson nd tere exsts squre mtrx U suc tt (A ) = U (A ) U for ll A G: ten nd re sd to be equvlent reresenttons. Recll tt f we cnge te bss used to reresent te lner oertors, te corresondng mtrces undergo smlr trnsformton. Snce tey reresent te sme oertors, we consder tem te "sme" reresentton but wt resect to d erent coce of bss.. Reducble nd Irreducble Reresenttons A reresentton D of grou G s clled rreducble f t s de ned on vector sce V (D) wc s no nontrvl nvrnt subsce. Oterwse, t s reducble. In essence ts de nton smly mens tt for reducble reresentton, te lner oertors correondng to te grou elements wll leve some smller vector sce nvrnt. In oter words, ll te grou ctons cn be relzed n some subsce. We need to convert tese sttment nto more rctcl crteron. Suose te reresenton D s reducble on te vector sce V. Ten tere exsts subsce S wc s nvrnt under D. For ny vector v V; we cn decomos t s, v = s + s? were s S nd s? belongs to te comlement S? of S: If we wrte te vector v n te block form, v = ten te reresentton mtrx cn be wrtten s D (A) Av = D (A) v = D (A) s s? For te sce S to be nvrnt under grou oertors mens tt D (A ) = 0;.e. te mtrces D (A ) re ll of te uer trngulr form, D (A D (A ) = ) D (A ) 0 D 4 (A ) D (A) D 4 (A) 8A G s s? ; 8A G A reresentton s comletely reducble f ll te mtrces n te reresenttons D (A ) cn be smultneously brougt nto block dgonl form by te sme smlrty trnsformton U; UD (A ) U D (A = ) 0 ; for ll A 0 D (A ) G.e. D (A ) = 0 n te uer trngulr mtrces gven n Eq. In oter words, te sce comlement to S s lso nvrnt under te grou oerton. Ts wll be te cse f te reresnetton mstrces re untry s stted n te teorem; Teorem: Any untry reducble reresentton s comletely reducble. Proof: For smlcty we ssume tt te vector sce V s equed wt sclr roduct (u; v) : It s esy to see n ts cse we cn coose te comlement sce S? to be erendculr to S;.e. (u; v) = 0; f u S; v S? Recll tt te sclr roduct s nvrnt under te untry trnsformton, 0 = (u; v) = (D (A ) u; D (A ) v) Tus f D (A ) u S; ten D (A ) v S? wc mles tt S? s lso nvrnt under te grou oerton. In yscl lctons, we del mostly wt untry reresenttons nd tey re comletely reducble.
4 . Untry Reresentton Snce untry oertors reserve te sclr roduct of vector sce, reresentton by untry mtrces wll smlfy te nlyss of grou teory. In te relm of nte grous, t turns out tt we cn lwys trnsform te reresentton nto unty one. Ts s te content of te followng teorem. Fundmentl Teorem Every rre of nte grou s equvlent to untry rre (re by untry mtrces) Proof: Let D (A r ) be reresentton of te grou G = fe; A A n g Consder te sum n H = D (A r ) D y (A r ) ten H y = H r= Snce H s ostve semde nte, we cn de ne squre root by De ne new set of mtrces by = H; y = D (A r ) = D (A r ) r = ; ; ; n Snce ts s smlrty trnsformton, D (Ar ) lso forms re wc s equvlent to D (A r ) : demonstrte tt D (A r ) s untry, We wll now D (A r ) D y (A r ) = D (A r ) D y (A r ) = D (A r ) " n # = D (A r A s ) D y (A r A s ) = s= were we ve used te rerrngement teorem. Scur s Lemm n D (As ) D y (A s ) D y (A r ) s= n s 0 = D (A s 0) D y (A s 0) = = One of te most mortnt teorems n te study of te rreducble rerentton s te followng lemm. Scur s Lemm Any mtrx wc commutes wt ll mtrces of rre s multle of dentty mtrx. Proof: Assume 9 M suc tt ten by tkng te ermtn conjugte, we get MD (A r ) = D (A r ) M D y (A r ) M y = M y D y (A r ) As sown bove, we cn tke D (A r ) to be untry, so we cn wrte 8 A r G M y = D (A r ) M y D y (A r ) or M y D (A r ) = D (A r ) M y Ts mens tt M y lso commutes wt ll D s nd so re te combnton M + M y nd M M y ; wc re ermtn. Tus, we only ve to consder te cse were M s ermtn. Strt by dgonlzng M by untry mtrx U; M = UdU y De ne D (Ar ) = U y D (A r ) U; ten we ve d : dgonl d D (A r ) = D (A r ) d or n terms of mtrx elements, d _ D r (A s ) = _ D (A s ) d 4
5 Snce te mtrx d s dgonl, we get (d d ) D (A s ) = 0 =) f d 6= d ; ten D (A s ) = 0 Ts mens f dgonl elements d re ll d erent, ten te o -dgonl elements of D re ll zero. In ts _ cse, D 0 s re ll dgonl nd ence ll reducble. Te only ossble non-zero o -dgonl elements of D cn rse wen some of d 0 _ s re equl. For exmle, f d = d ; ten D cn be non-zero. Tus D wll be n te block dgonl form,.e. d d f d = d d... ten 6 D = 4 d _ D 0 0 D _ Ts s true for every mtrx n te reresentton. Tus ll te mtrces n te reresentton re n te block dgonl form. But D s rreducble wc mens tt not ll mtrces cn be brougt nto block dgonl form. Tus ll d s ve to be equl d = ci: or M = UdU y = duu y = d = ci If te only mtrx tt commutes wt ll te mtrces of reresentton s multle of dentty, ten te reresentton s rre. Proof: construct M = Suose D s reducble, ten we cn trnsform tem nto I 0 0 I D D (A ) = (A ) ten clerly (A ) for ll A G D (A ) M = MD (A ) for ll But M s not multle of dentty (contrdcton). Terefore D must be rreducble. Remrks. Any rre of Abeln grou s dmensonl. Ts s becuse for ny element A; D (A) commutes wt ll D (A ) : Ten Scur s lemm =) D (A) = ci 8A G: But D s rre, so D s to be mtrx.. In ny rre, te dentty element E s lwys reresented by dentty mtrx. Ts follows Scur s lemm.. From D (A) D A = D (E) = I:; we see tt D A = [D (A)] nd for untry reresentton D A = D + (A) : If nd re rres of dmenson l ; nd dmenson l nd ten () f l 6= l M = 0 M (A ) = (A ) M :for ll A G (b) f l = l ; ten eter M = 0 or det M 6= 0 nd res re equvlent. Proof: : Wtout loss of generlty we cn tke l l : Note tt snce Eq s true for ll elements we cn relce A by A ; wc cn be wrtten s Hermtn conjugte of Eq gves M A = D A M M (A ) y = (A ) y M y M y = M y y ; MM y (A ) y = M (A ) y M y = (A ) y MM y 5
6 or MM y (A ) = (A ) MM y 8 (A ) G Ten from Scur s lemm we get MM y = ci;were I s l dmensonl dentty mtrx. Frst consder te cse l = l ; were we get jdet Mj = c` : Ten eter det M 6= 0;wc mles M s non-sngulr nd from Eq (A ) = M (A ) M 8 (A ) G Ts mens (A ) nd (A ) re equvlent. Oterwse f te determnnt s zero, In rtculr, for = det M = 0 =) c = 0 or MM y = 0 =) P jm j = 0 M = 0 for ll : =) M = 0: Next, f l < l ; ten M s retngulr l l ; mtrx : : M = : : {z } l we cn de ne de ne squre mtrx by ddng colums of zeros l M M = 0 8:: N = l z } { [M; 0]gl l l squre mtrx ten M N y y = 0 M nd NN y y = (M; 0) = MM y = ci 0 were I s te l l dentty mtrx. But from constructon we see tt det N = 0; Hence c = 0; =) NN y = 0 or M = 0 dentclly. Gret Ortogonlty Teorem Te most useful teorem for te reresentton of te nte grou s te followng one. Teorem(Gret ortogonlty teorem): Suose G s grou wt n elements,fa ; = ; ; ng ; nd (A ) ; = ; re ll te nequvlent rres of G wt dmenson l : Ten n j (A ) k` (A ) = n k j` l = Proof: De ne M = (A ) A were s n rbtrry l l mtrx. Ten multlyng M by reresentton mtrces, we get (A b ) M = (A b ) (A ) A A b (A b ) = (A b A ) (A b A ) (A b ) = M (A b ) If 6= ; ten M = 0 from Scur s lemm, we get M = r (A ) rs sk A = r Coose rs = rj sl (.e. s zero excet te jl element). Ten we ve j (A ) k` (A ) = 0 (A ) rs ks (A ) = 0 Ts sows tt for d erent rreducble reresenttons, te mtrx elements, fter summng over grou elements, re ortogonl to ec oter. 6
7 = ten we cn wrte M = P (A ) A :Ts mles wc gves, Tke (A ) M = M (A b ) =) M = ci T r (A ) A = cl or nt r = cl ; or c = (T r) n l rs = rj s` ten T r = j` nd (A ) j (A ) k` = n k j` l Ts gves te ortogonlty for d erent mtrx elements wtn gven rreducble reresentton. Geometrc Interretton Imgne comlex n dmensonl vector sce n wc xes (or comonenets) re lbeled by grou elements E; A :A A n (Grou element sce). Consder te vector n ts sce wt comonets mde out of te mtrx element of rreducble reresentton mtrx (A ) j :Ec vector n ts n dmensonl sce s lbeled by ndces, ; : ~D = D (E) ; D (A ) ; D (A n ) (4) Gret ortogonlty teorem sys tt ll tese vectors re? to ec oter. As result l n becuse tere cn be no more tn n mutully? vectors n n-dmenson vector sce. As n exmle, we tke te -dmensonl reresentton we ve work out before, 0 E = ; A = ; B = 0 K = 0 ; L = 0 ; M = Lbel te xses by te groul elements n te order (E; A; B; K; L; M) : Ten we cn construct four 6-dmensonl ectors from tese mtrces, = ( ; = (0 ; ; ; ; ; ; ) ; 0 ; ; ) ; 0 ; ) = (0 ; = ( ; ; ; ; ; ) It s strgtforwrd to ceck tt tese 4 vectors re erendculr to ec oter. Note tt te oter two vectors wc re ortogonl to tese vectors re of te form, D E = ( ; ; ; ; ; ) D A = ( ; ; ; ; ; ) comng from te dentty reresentton nd oter -dmensonl reresentton. 4 Crcter of Reresentton Te mtrces n rre re not unque, becuse we cn generte noter equvlent rre by smlrty trnsformton. However, te trce of mtrx s nvrnt under suc trnsformton, T r SAS = T ra We cn use te trce, or crcter, to crcterze te rre. (A ) T r (A ) = (A ) Useful Proertes 7
8 . If nd re equvlent, ten (A ) = (A ) 8A G. If A nd B re n te sme clss, (A) = (B) Proof: If A nd B re n sme clss =) 9x G suc tt xax = B =) (x) (A) x = (B) Usng we get x = (x) T r (x) (A) (x) = T r (B) Hence s functon of clss, not of ec element. or (A) = (B). Denote = (C ) ; te crcter of t clss. Let n c be te number of clsses n G; nd n te number of grou elements n C : From gret ortogonlty teorem r j (A r ) k` (A r ) = n k jl l we get (A r ) (A r ) = n l = n l r or P n = n Ts s te gret ortogonlty teorem for te crcters. De ne U = n n (C ) ; ten gret ortogonlty teorem mles, n c = U U = Tus, f we consder U s comonents n n c dmensonl vector sce, ~ U = (U U U nc ) ; ten ~ U = ; ; n r (n r : # of nde rres)form n otornorml set of vectors,.e. Ts mles tt n c U U = U U = = n r n c. e. number of rres s smller tn te number of clsses. Ts gretly restrcts te number of ossble rres. 4. Decomoston of Reducble Reresentton For reducble reresentton, we cn wrte D = D.e. D (A ) = (A ) Ten we ve for te trce (A ) (A ) = (A ) + (A ) 8A G Denote by ; = ; n r ; ll te nequvlent untry rre. Ten ny re D cn be decomosed s D = c c : some nteger, # of tme ers In terms of trces, we get (C ) = c (C ) 8
9 were we ndcte tt te trce s functon of clss C :Te coe cent cn be clculted s follows (by usng ortogonty teorem). Multly by n nd sum over n = c n = c n = nc or c = P n n From ts we lso get, n = n c c Ts leds to te followng teorem: Teorem: If te re D wt crcter st es te relton, n = n ten te reresentton D s rreducble. ; = n jc j 4. Regulr Reresentton Gven grou G = fa = E; A A n g :We cn construct te regulr re s follows: Tke ny A G: If AA = A = 0A + 0A + A + 0A 4 +.e. we wrte te roduct "formlly" s lner combnton of grou elements, AA s = n C rs A r = r= n A r D rs (A) ;.e. C rs = D rs (A) s eter 0 or: (5) r=.e. D rs (A) = f AA s = A r or A = A r As = 0 oterwse Note strctly sekng, te sum over grou elments s unde ned. But ere only one grou element sows u n te rgt-nd sde n Eq(5), we do not need to de ne te sum of grou elements. Ten D (A) s form re of G: regulr reresentton wt dmensonl n: Ts cn be seen s follows: A r D rs (AB) = ABA s = A A t D ts (B) = D ts (B) A r D rt (A) r t tr or D rs (AB) = D rt (A) D ts (B) From te de nton of te regulr reresentton D rs (A) = AA s = A r we see tt te dgonl elements re of te form, D rr (A) = ff AA r = A r or A = E Terefore every crcter s zero excet for dentty clss, (reg) (C ) = 0 6= (reg) (C ) = n = (6) From ts we cn work out ow D (reg) reduces to rres. Wrte D (reg) = c 9
10 ten c = n (reg) n = n (reg) = n nl = l Ts mens tt D reg contns te rres s mny tmes s ts dmenson; (reg) = n r l or (reg) For te dentty clss reg = n; = l ; ten we get P l = n n r = = = n Ts severely constrnts te ossble dmensonltes of rres becuse bot n nd l ve to be ntegers. For D, wt n = 6; te only ossble soluton for P l = 6 s l = : l = : l = ; nd ter ermuttons. Te relton n Eq(7) mles tt te vector sce formed by vectors de ned n Eq(4) s dmenson n; te number of elements n te grou. Snce tose vectors n Eq(4) re ortogonl to ec oter, ence lnerly ndeendent, nd tere re n suc vectors, tey must stsfy te comleteness relton, ;; l n D (A k ) (A l ) = kl comleteness relton (8) Te fctor l comes from te normlzton of te vectors n Eq(4). n We now wnt to sow tt n c = n r.e. # of clsses = # of rres. De ne by ddng u ll mtrces corresondng to elements n te sme clss C ; = AC (A) (7) Ten, (A j ) A j = A = A (A j ) (A) A j A j AA j = D Usng we get.e. A j = (A j ) (A j ) = (A j ) commutes wt ll mtrce n te rre. From Scur s lemm, we get Tkng te trce, we get = were s some number n = l or = n l = n were s te crcter of dentty clss. In te comleteness relton n Eq(8), we cn sum A k over grou elements n clss C r nd A l over clss C s to get ;; l n r s = n r rs (9) 0
11 Usng vlue of n Eq(9) we ve n r r = Ts te comleteness relton for te crcters. ; ; : : : (nr) we get s = n n r rs comleteness If we now consder s vector n n r dm sce = n c n r Combne ts wt te result n r n c ; we ve derved before, we get 4. Crcter Tble n r = n c For nte grou, te essentl nformton bout te rreducble reresenttons cn be summrzed n tble wc lsts te crcters of ec rreducble reresentton n terms of te clsses. Ts tble s mny useful lctons. To construct suc tble we cn use te followng useful nformton:. # of columns = # of rows = # of clsses P. l = n. P n = n nd 4. If l = ; s tself re. P j = n n j 5. A = T r A = T r + A = (A) If A nd A re n te sme clss ten (A) s rel. 6. s re =) s lso re so f s re comlex numbers, noter row wll be ter comlex conjugte 7. If l > ; = 0 for t lest one clss. Ts follows from te relton n j j = n nd n = n 8. For yscl symmetry grou, x:y nd z form bss of re. Exmle : D crcter tble E C C 0 x + y ; z A R z; z: A (xz; yz) (x; y) E 0 x y ; xy (R x :R y ) In ts tble, te tycl bss functons u to qudrtc n coordnte system re lsted. Remrk: te bss functons lsted n te usul crcter tble re not necessrly normlzed. In rtculr, te qudrtc functons ve to be ndled crefully. Te dnger s tt f we use te bss functons gven n te crcter tble, we mgt not generte untry mtrces. Usng te trnsformton roertes of te coordnte, we cn lso nfer te trnsformton roertes of ny vectors. For exmle, te usul coordntes ve te trnsformton roerty, ~r = (x; y; z) A E n D Ts mens tt electrc eld of ~ E or mgnetc eld ~ B wll ve sme trnsformton roerty, ~B s ~ E s A E becuse tey ll trnsform te sme wy under te rotton.
12 5 Product Reresentton (Kronecker roduct) Let x be te bss for ;.e. y` be te bss for ;.e. ten te roducts x j y l trnsform s x 0 = P ` x j (A) x 0 y 0 k = j` j= y 0 k = `P j j y` `k `= (A) (A) k` (A) x jy` j` j`;k (A) x j y` were j`;k (A) = j (A) `k (A) Note tt n tese mtrces, row nd column re lbelled by ndces, nsted of one. It s esy to sow tt forms re of te grou. (A) (B) = (A) j;st (B) st;k` j;k` s:t = s:t s (A) D jt (A) sk (B) D t` (B) = k (AB) D j` (AB) = D (AB) k;k` or (A) (B) = (AB) Te bss functons for re x y j Te crcter of ts new re cn be clculted by mkng te row nd colum ndces te sme nd sum over, (A) = j` j`;j` (A) = j` jj (A) `` (A) = (A) (A) (A) = (A) (A) If = ; we cn furter decomose te roduct re by symmetrzton or ntsymmetrzton; D fg k;j` (A) = D [] k;j` (A) = j j (A) k` (A) k` (A) + D ` (A) D ` (A) kj (A) (A) kj (A) Tese mtrces lso form re of G nd te crcters re gven by bss bss (x y k + x k y ) (x y k x k y ) fg (A) = (A) + A ; [] (A) = (A) A Exmle D E: C C 0 R z: z (xz; yz) (x; y) 0 x y ; xy 4 0 = ( ) s 0 = ( ) =
13 6 Drect Product Grou Gven grous G = fe; A A n g ; G = fe; B B m g ; we cn de ne te roduct grou s G G = fa B j ; = n; j = mg wt multlcton lw (A k B`) (A k 0B`0) = (A k A k 0) (B`B`0) It turns out tt rre of G G re just drect roduct of rres of G; nd G : Let (A ) be n rre of G nd (B j ) n rre of G ten te mtrces de ned by wll ve te roerty (A B j ) b;cd (A ) c (B j ) bd (A B j ) (A k B`) b;cd = ef = ef (A B j ) (A k B`) b;ef ef;cd (A ) c (A k ) ec (B j ) bf (B e ) fd = (A A k ) c (B j B`) bd = (A A k: B j B`) b;cd Ts mens tt te mtrce (A B j ) form reresentton of te roduct grou G G : Te crcters cn be clculted, Ten (A B j ) = b (A B j ) = j (A B j ) b;b = b (A ) (B j ) bb = (A ) (B j ) 0 (A j (B j ) A = nm =) s rre. Exmle, G = D = fe; C ; C 0 g ; G = fe; g = ' were : re ecton on te lne of trngle. Drect roduct grou s tend D ' = E; A; B = fe; C ; C 0 ; ; C ; C 0 g Crcter Tble ' E + C C 0 D E AB KLM 0 Crcter Tble E C C 0 C C
p (i.e., the set of all nonnegative real numbers). Similarly, Z will denote the set of all
th Prelmnry E 689 Lecture Notes by B. Yo 0. Prelmnry Notton themtcl Prelmnres It s ssumed tht the reder s fmlr wth the noton of set nd ts elementry oertons, nd wth some bsc logc oertors, e.g. x A : x s
More informationThe Schur-Cohn Algorithm
Modelng, Estmton nd Otml Flterng n Sgnl Processng Mohmed Njm Coyrght 8, ISTE Ltd. Aendx F The Schur-Cohn Algorthm In ths endx, our m s to resent the Schur-Cohn lgorthm [] whch s often used s crteron for
More informationGroup Theory in Physics
Group Theory n Physcs Lng-Fong L (Insttute) Representaton Theory / 4 Theory of Group Representaton In physcal applcaton, group representaton s mportant n deducng the consequence of the symmetres of the
More informationLECTURE 5: FIBRATIONS AND HOMOTOPY FIBERS
LECTURE 5: FIBRATIONS AND HOMOTOPY FIBERS In ts lecture we wll ntroduce two mortant classes of mas of saces, namely te Hurewcz fbratons and te more general Serre fbratons, wc are bot obtaned by mosng certan
More informationProof that if Voting is Perfect in One Dimension, then the First. Eigenvector Extracted from the Double-Centered Transformed
Proof tht f Votng s Perfect n One Dmenson, then the Frst Egenvector Extrcted from the Doule-Centered Trnsformed Agreement Score Mtrx hs the Sme Rn Orderng s the True Dt Keth T Poole Unversty of Houston
More informationNot-for-Publication Appendix to Optimal Asymptotic Least Aquares Estimation in a Singular Set-up
Not-for-Publcaton Aendx to Otmal Asymtotc Least Aquares Estmaton n a Sngular Set-u Antono Dez de los Ros Bank of Canada dezbankofcanada.ca December 214 A Proof of Proostons A.1 Proof of Prooston 1 Ts roof
More informationUNIVERSITY OF IOANNINA DEPARTMENT OF ECONOMICS. M.Sc. in Economics MICROECONOMIC THEORY I. Problem Set II
Mcroeconomc Theory I UNIVERSITY OF IOANNINA DEPARTMENT OF ECONOMICS MSc n Economcs MICROECONOMIC THEORY I Techng: A Lptns (Note: The number of ndctes exercse s dffculty level) ()True or flse? If V( y )
More informationSupplement 4 Permutations, Legendre symbol and quadratic reciprocity
Sulement 4 Permuttions, Legendre symbol nd qudrtic recirocity 1. Permuttions. If S is nite set contining n elements then ermuttion of S is one to one ming of S onto S. Usully S is the set f1; ; :::; ng
More informationTwo Coefficients of the Dyson Product
Two Coeffcents of the Dyson Product rxv:07.460v mth.co 7 Nov 007 Lun Lv, Guoce Xn, nd Yue Zhou 3,,3 Center for Combntorcs, LPMC TJKLC Nnk Unversty, Tnjn 30007, P.R. Chn lvlun@cfc.nnk.edu.cn gn@nnk.edu.cn
More informationCENTROID (AĞIRLIK MERKEZİ )
CENTOD (ĞLK MEKEZİ ) centrod s geometrcl concept rsng from prllel forces. Tus, onl prllel forces possess centrod. Centrod s tougt of s te pont were te wole wegt of pscl od or sstem of prtcles s lumped.
More informationSolution Set #3
5-55-7 Soluton Set #. Te varaton of refractve ndex wt wavelengt for a transarent substance (suc as glass) may be aroxmately reresented by te emrcal equaton due to Caucy: n [] A + were A and are emrcally
More informationChapter Runge-Kutta 2nd Order Method for Ordinary Differential Equations
Cter. Runge-Kutt nd Order Metod or Ordnr Derentl Eutons Ater redng ts cter ou sould be ble to:. understnd te Runge-Kutt nd order metod or ordnr derentl eutons nd ow to use t to solve roblems. Wt s te Runge-Kutt
More informationHAMILTON-JACOBI TREATMENT OF LAGRANGIAN WITH FERMIONIC AND SCALAR FIELD
AMION-JACOBI REAMEN OF AGRANGIAN WI FERMIONIC AND SCAAR FIED W. I. ESRAIM 1, N. I. FARAA Dertment of Physcs, Islmc Unversty of Gz, P.O. Box 18, Gz, Plestne 1 wbrhm 7@hotml.com nfrht@ugz.edu.s Receved November,
More informationReview of linear algebra. Nuno Vasconcelos UCSD
Revew of lner lgebr Nuno Vsconcelos UCSD Vector spces Defnton: vector spce s set H where ddton nd sclr multplcton re defned nd stsf: ) +( + ) (+ )+ 5) λ H 2) + + H 6) 3) H, + 7) λ(λ ) (λλ ) 4) H, - + 8)
More informationDCDM BUSINESS SCHOOL NUMERICAL METHODS (COS 233-8) Solutions to Assignment 3. x f(x)
DCDM BUSINESS SCHOOL NUMEICAL METHODS (COS -8) Solutons to Assgnment Queston Consder the followng dt: 5 f() 8 7 5 () Set up dfference tble through fourth dfferences. (b) Wht s the mnmum degree tht n nterpoltng
More informationSymmetry Labeling of Molecular Energies
Capter 7. Symmetry Labeling of Molecular Energies Notes: Most of te material presented in tis capter is taken from Bunker and Jensen 1998, Cap. 6, and Bunker and Jensen 2005, Cap. 7. 7.1 Hamiltonian Symmetry
More informationPrinciple Component Analysis
Prncple Component Anlyss Jng Go SUNY Bufflo Why Dmensonlty Reducton? We hve too mny dmensons o reson bout or obtn nsghts from o vsulze oo much nose n the dt Need to reduce them to smller set of fctors
More information12 Basic Integration in R
14.102, Mt for Economists Fll 2004 Lecture Notes, 10/14/2004 Tese notes re primrily bsed on tose written by Andrei Bremzen for 14.102 in 2002/3, nd by Mrek Pyci for te MIT Mt Cmp in 2003/4. I ve mde only
More informationLecture Note 4: Numerical differentiation and integration. Xiaoqun Zhang Shanghai Jiao Tong University
Lecture Note 4: Numericl differentition nd integrtion Xioqun Zng Sngi Jio Tong University Lst updted: November, 0 Numericl Anlysis. Numericl differentition.. Introduction Find n pproximtion of f (x 0 ),
More informationQuadrilateral et Hexahedral Pseudo-conform Finite Elements
Qurlterl et Heerl seuo-conform Fnte Elements E. DUBACH R. LUCE J.M. THOMAS Lbortore e Mtémtques Applquées UMR 5 u Frnce GDR MoMs Métoes Numérques pour les Flues. rs écembre 6 Wt s te problem? Loss of conergence
More informationLecture 4: Piecewise Cubic Interpolation
Lecture notes on Vrtonl nd Approxmte Methods n Appled Mthemtcs - A Perce UBC Lecture 4: Pecewse Cubc Interpolton Compled 6 August 7 In ths lecture we consder pecewse cubc nterpolton n whch cubc polynoml
More informationApplied Statistics Qualifier Examination
Appled Sttstcs Qulfer Exmnton Qul_june_8 Fll 8 Instructons: () The exmnton contns 4 Questons. You re to nswer 3 out of 4 of them. () You my use ny books nd clss notes tht you mght fnd helpful n solvng
More informationk and v = v 1 j + u 3 i + v 2
ORTHOGONAL FUNCTIONS AND FOURIER SERIES Orthogonl functions A function cn e considered to e generliztion of vector. Thus the vector concets like the inner roduct nd orthogonlity of vectors cn e extended
More informationThe proof is a straightforward probabilistic extension of Palfrey and Rosenthal (1983). Note that in our case we assume N
PROOFS OF APPDIX A Proo o PROPOSITIO A pure strtey Byesn-s equlbr n te PUprtcpton me wtout lled oters: Te proo s strtorwrd blstc etenson o Plrey nd Rosentl 983 ote tt n our cse we ssume A B : It s esy
More informationMath 324 Advanced Financial Mathematics Spring 2008 Final Exam Solutions May 2, 2008
Mat 324 Advanced Fnancal Matematcs Sprng 28 Fnal Exam Solutons May 2, 28 Ts s an open book take-ome exam. You may work wt textbooks and notes but do not consult any oter person. Sow all of your work and
More informationFINITE NEUTROSOPHIC COMPLEX NUMBERS. W. B. Vasantha Kandasamy Florentin Smarandache
INITE NEUTROSOPHIC COMPLEX NUMBERS W. B. Vsnth Kndsmy lorentn Smrndche ZIP PUBLISHING Oho 11 Ths book cn be ordered from: Zp Publshng 1313 Chespeke Ave. Columbus, Oho 31, USA Toll ree: (61) 85-71 E-ml:
More informationThe Number of Rows which Equal Certain Row
Interntonl Journl of Algebr, Vol 5, 011, no 30, 1481-1488 he Number of Rows whch Equl Certn Row Ahmd Hbl Deprtment of mthemtcs Fcult of Scences Dmscus unverst Dmscus, Sr hblhmd1@gmlcom Abstrct Let be X
More informationOnline Appendix to. Mandating Behavioral Conformity in Social Groups with Conformist Members
Onlne Appendx to Mndtng Behvorl Conformty n Socl Groups wth Conformst Members Peter Grzl Andrze Bnk (Correspondng uthor) Deprtment of Economcs, The Wllms School, Wshngton nd Lee Unversty, Lexngton, 4450
More informationMSC: Primary 11A15, Secondary 11A07, 11E25 Keywords: Reciprocity law; octic residue; congruence; quartic Jacobi symbol
Act Arth 159013, 1-5 Congruences for [/] mo ZHI-Hong Sun School of Mthemtcl Scences, Hun Norml Unverst, Hun, Jngsu 3001, PR Chn E-ml: zhhongsun@hoocom Homege: htt://wwwhtceucn/xsjl/szh Abstrct Let Z be
More informationCOMP4630: λ-calculus
COMP4630: λ-calculus 4. Standardsaton Mcael Norrs Mcael.Norrs@ncta.com.au Canberra Researc Lab., NICTA Semester 2, 2015 Last Tme Confluence Te property tat dvergent evaluatons can rejon one anoter Proof
More informationMath Week 5 concepts and homework, due Friday February 10
Mt 2280-00 Week 5 concepts nd omework, due Fridy Februry 0 Recll tt ll problems re good for seeing if you cn work wit te underlying concepts; tt te underlined problems re to be nded in; nd tt te Fridy
More information4. Eccentric axial loading, cross-section core
. Eccentrc xl lodng, cross-secton core Introducton We re strtng to consder more generl cse when the xl force nd bxl bendng ct smultneousl n the cross-secton of the br. B vrtue of Snt-Vennt s prncple we
More informationStanford University CS254: Computational Complexity Notes 7 Luca Trevisan January 29, Notes for Lecture 7
Stanford Unversty CS54: Computatonal Complexty Notes 7 Luca Trevsan January 9, 014 Notes for Lecture 7 1 Approxmate Countng wt an N oracle We complete te proof of te followng result: Teorem 1 For every
More informationOn a nonlinear compactness lemma in L p (0, T ; B).
On a nonlnear compactness lemma n L p (, T ; B). Emmanuel Matre Laboratore de Matématques et Applcatons Unversté de Haute-Alsace 4, rue des Frères Lumère 6893 Mulouse E.Matre@ua.fr 3t February 22 Abstract
More information7.3 Problem 7.3. ~B(~x) = ~ k ~ E(~x)=! but we also have a reected wave. ~E(~x) = ~ E 2 e i~ k 2 ~x i!t. ~B R (~x) = ~ k R ~ E R (~x)=!
7. Problem 7. We hve two semi-innite slbs of dielectric mteril with nd equl indices of refrction n >, with n ir g (n ) of thickness d between them. Let the surfces be in the x; y lne, with the g being
More informationUSA Mathematical Talent Search Round 1 Solutions Year 25 Academic Year
1/1/5. Alex is trying to oen lock whose code is sequence tht is three letters long, with ech of the letters being one of A, B or C, ossibly reeted. The lock hs three buttons, lbeled A, B nd C. When the
More informationQuadratic Residues. Chapter Quadratic residues
Chter 8 Qudrtic Residues 8. Qudrtic residues Let n>be given ositive integer, nd gcd, n. We sy tht Z n is qudrtic residue mod n if the congruence x mod n is solvble. Otherwise, is clled qudrtic nonresidue
More informationOn Pfaff s solution of the Pfaff problem
Zur Pfaff scen Lösung des Pfaff scen Probles Mat. Ann. 7 (880) 53-530. On Pfaff s soluton of te Pfaff proble By A. MAYER n Lepzg Translated by D. H. Delpenc Te way tat Pfaff adopted for te ntegraton of
More informationEcon 401A Three extra questions John Riley. Homework 3 Due Tuesday, Nov 28
Econ 40 ree etr uestions Jon Riley Homework Due uesdy, Nov 8 Finncil engineering in coconut economy ere re two risky ssets Plnttion s gross stte contingent return of z (60,80) e mrket vlue of tis lnttion
More informationINTEGRAL p-adic HODGE THEORY, TALK 14 (COMPARISON WITH THE DE RHAMWITT COMPLEX)
INTEGRAL -ADIC HODGE THEORY, TALK 4 (COMPARISON WITH THE DE RHAMWITT COMPLEX) JOAQUIN RODRIGUES JACINTO (NOTES BY JAMES NEWTON). Recollectons and statement of theorem Let K be a erfectod eld of characterstc
More informationQuadratic reciprocity
Qudrtic recirocity Frncisc Bozgn Los Angeles Mth Circle Octoer 8, 01 1 Qudrtic Recirocity nd Legendre Symol In the eginning of this lecture, we recll some sic knowledge out modulr rithmetic: Definition
More informationGAUSS ELIMINATION. Consider the following system of algebraic linear equations
Numercl Anlyss for Engneers Germn Jordnn Unversty GAUSS ELIMINATION Consder the followng system of lgebrc lner equtons To solve the bove system usng clsscl methods, equton () s subtrcted from equton ()
More informationRank One Update And the Google Matrix by Al Bernstein Signal Science, LLC
Introducton Rnk One Updte And the Google Mtrx y Al Bernsten Sgnl Scence, LLC www.sgnlscence.net here re two dfferent wys to perform mtrx multplctons. he frst uses dot product formulton nd the second uses
More informationIntegration by Parts for D K
Itertol OPEN ACCESS Jourl Of Moder Egeerg Reserc IJMER Itegrto y Prts for D K Itegrl T K Gr, S Ry 2 Deprtmet of Mtemtcs, Rgutpur College, Rgutpur-72333, Purul, West Begl, Id 2 Deprtmet of Mtemtcs, Ss Bv,
More informationChapter Newton-Raphson Method of Solving a Nonlinear Equation
Chpter.4 Newton-Rphson Method of Solvng Nonlner Equton After redng ths chpter, you should be ble to:. derve the Newton-Rphson method formul,. develop the lgorthm of the Newton-Rphson method,. use the Newton-Rphson
More informationREPRESENTATION THEORY OF PSL 2 (q)
REPRESENTATION THEORY OF PSL (q) YAQIAO LI Following re notes from book [1]. The im is to show the qusirndomness of PSL (q), i.e., the group hs no low dimensionl representtion. 1. Representtion Theory
More informationChapter 2 Introduction to Algebra. Dr. Chih-Peng Li ( 李 )
Chpter Introducton to Algebr Dr. Chh-Peng L 李 Outlne Groups Felds Bnry Feld Arthetc Constructon of Glos Feld Bsc Propertes of Glos Feld Coputtons Usng Glos Feld Arthetc Vector Spces Groups 3 Let G be set
More informationMath 20C Multivariable Calculus Lecture 5 1. Lines and planes. Equations of lines (Vector, parametric, and symmetric eqs.). Equations of lines
Mt 2C Multivrible Clculus Lecture 5 1 Lines nd plnes Slide 1 Equtions of lines (Vector, prmetric, nd symmetric eqs.). Equtions of plnes. Distnce from point to plne. Equtions of lines Slide 2 Definition
More informationTR/95 February Splines G. H. BEHFOROOZ* & N. PAPAMICHAEL
TR/9 February 980 End Condtons for Interpolatory Quntc Splnes by G. H. BEHFOROOZ* & N. PAPAMICHAEL *Present address: Dept of Matematcs Unversty of Tabrz Tabrz Iran. W9609 A B S T R A C T Accurate end condtons
More informationStats & Summary
Stts 443.3 & 85.3 Summr The Woodbur Theorem BCD B C D B D where the verses C C D B, d est. Block Mtrces Let the m mtr m q q m be rttoed to sub-mtrces,,,, Smlrl rtto the m k mtr B B B mk m B B l kl Product
More informationChapter 3 MATRIX. In this chapter: 3.1 MATRIX NOTATION AND TERMINOLOGY
Chpter 3 MTRIX In this chpter: Definition nd terms Specil Mtrices Mtrix Opertion: Trnspose, Equlity, Sum, Difference, Sclr Multipliction, Mtrix Multipliction, Determinnt, Inverse ppliction of Mtrix in
More informationSection 4.7 Inverse Trigonometric Functions
Section 7 Inverse Trigonometric Functions 89 9 Domin: 0, q Rnge: -q, q Zeros t n, n nonnegtive integer 9 Domin: -q, 0 0, q Rnge: -q, q Zeros t, n non-zero integer Note: te gr lso suggests n te end-bevior
More informationLECTURE 10: JACOBI SYMBOL
LECTURE 0: JACOBI SYMBOL The Jcobi symbol We wish to generlise the Legendre symbol to ccomodte comosite moduli Definition Let be n odd ositive integer, nd suose tht s, where the i re rime numbers not necessrily
More informationINTRODUCTION TO COMPLEX NUMBERS
INTRODUCTION TO COMPLEX NUMBERS The numers -4, -3, -, -1, 0, 1,, 3, 4 represent the negtve nd postve rel numers termed ntegers. As one frst lerns n mddle school they cn e thought of s unt dstnce spced
More informationMany-Body Calculations of the Isotope Shift
Mny-Body Clcultons of the Isotope Shft W. R. Johnson Mrch 11, 1 1 Introducton Atomc energy levels re commonly evluted ssumng tht the nucler mss s nfnte. In ths report, we consder correctons to tomc levels
More informationFUNDAMENTALS ON ALGEBRA MATRICES AND DETERMINANTS
Dol Bgyoko (0 FUNDAMENTALS ON ALGEBRA MATRICES AND DETERMINANTS Introducton Expressons of the form P(x o + x + x + + n x n re clled polynomls The coeffcents o,, n re ndependent of x nd the exponents 0,,,
More informationAdvanced Topics in Optimization. Piecewise Linear Approximation of a Nonlinear Function
Advanced Tocs n Otmzaton Pecewse Lnear Aroxmaton of a Nonlnear Functon Otmzaton Methods: M8L Introducton and Objectves Introducton There exsts no general algorthm for nonlnear rogrammng due to ts rregular
More informationPART 1: VECTOR & TENSOR ANALYSIS
PART : VECTOR & TENSOR ANALYSIS wth LINEAR ALGEBRA Obectves Introduce the concepts, theores, nd opertonl mplementton of vectors, nd more generlly tensors, n dvnced engneerng nlyss. The emphss s on geometrc
More informationMath 61CM - Solutions to homework 9
Mth 61CM - Solutions to homework 9 Cédric De Groote November 30 th, 2018 Problem 1: Recll tht the left limit of function f t point c is defined s follows: lim f(x) = l x c if for ny > 0 there exists δ
More informationMechanical resonance theory and applications
Mechncl resonnce theor nd lctons Introducton In nture, resonnce occurs n vrous stutons In hscs, resonnce s the tendenc of sstem to oscllte wth greter mltude t some frequences thn t others htt://enwkedorg/wk/resonnce
More informationChapter 1: Fundamentals
Chpter 1: Fundmentls 1.1 Rel Numbers Types of Rel Numbers: Nturl Numbers: {1, 2, 3,...}; These re the counting numbers. Integers: {... 3, 2, 1, 0, 1, 2, 3,...}; These re ll the nturl numbers, their negtives,
More informationSome Unbiased Classes of Estimators of Finite Population Mean
Itertol Jourl O Mtemtcs Ad ttstcs Iveto (IJMI) E-IN: 3 4767 P-IN: 3-4759 Www.Ijms.Org Volume Issue 09 etember. 04 PP-3-37 ome Ubsed lsses o Estmtors o Fte Poulto Me Prvee Kumr Msr d s Bus. Dertmet o ttstcs,
More informationSUMMER 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 informationChapter 2 Differentiation
Cpter Differentition. Introduction In its initil stges differentition is lrgely mtter of finding limiting vlues, wen te vribles ( δ ) pproces zero, nd to begin tis cpter few emples will be tken. Emple..:
More informationOverview. Regular Languages. Finite Automata. A finite automaton. Startstate : q Acceptstate : q. Transitions
Overvew Regulr Lnguges Andres Krwth & Mlte Helmert Determnstc fnte utomt Regulr lnguges Nondetermnstc fnte utomt Closure oertons Regulr exressons Nonregulr lnguges The umng lemm 2 Fnte Automt A fnte utomton
More informationMath 212-Lecture 9. For a single-variable function z = f(x), the derivative is f (x) = lim h 0
3.4: Partial Derivatives Definition Mat 22-Lecture 9 For a single-variable function z = f(x), te derivative is f (x) = lim 0 f(x+) f(x). For a function z = f(x, y) of two variables, to define te derivatives,
More informationFinite Automata Theory and Formal Languages TMV027/DIT321 LP4 2018
Finite Automt Theory nd Forml Lnguges TMV027/DIT321 LP4 2018 Lecture 10 An Bove April 23rd 2018 Recp: Regulr Lnguges We cn convert between FA nd RE; Hence both FA nd RE ccept/generte regulr lnguges; More
More informationDuke Math Meet
Duke Mth Meet 01-14 Power Round Qudrtic Residues nd Prime Numers For integers nd, we write to indicte tht evenly divides, nd to indicte tht does not divide For exmle, 4 nd 4 Let e rime numer An integer
More informationORDINARY DIFFERENTIAL EQUATIONS
6 ORDINARY DIFFERENTIAL EQUATIONS Introducton Runge-Kutt Metods Mult-step Metods Sstem o Equtons Boundr Vlue Problems Crcterstc Vlue Problems Cpter 6 Ordnr Derentl Equtons / 6. Introducton In mn engneerng
More information( dg. ) 2 dt. + dt. dt j + dh. + dt. r(t) dt. Comparing this equation with the one listed above for the length of see that
Arc Length of Curves in Three Dimensionl Spce If the vector function r(t) f(t) i + g(t) j + h(t) k trces out the curve C s t vries, we cn mesure distnces long C using formul nerly identicl to one tht we
More informationMAT 1275: Introduction to Mathematical Analysis
1 MT 1275: Intrdutin t Mtemtil nlysis Dr Rzenlyum Slving Olique Tringles Lw f Sines Olique tringles tringles tt re nt neessry rigt tringles We re ging t slve tem It mens t find its si elements sides nd
More informationCOMPLEX NUMBER & QUADRATIC EQUATION
MCQ COMPLEX NUMBER & QUADRATIC EQUATION Syllus : Comple numers s ordered prs of rels, Representton of comple numers n the form + nd ther representton n plne, Argnd dgrm, lger of comple numers, modulus
More informationMoment estimates for chaoses generated by symmetric random variables with logarithmically convex tails
Moment estmtes for choses generted by symmetrc rndom vrbles wth logrthmclly convex tls Konrd Kolesko Rf l Lt l Abstrct We derve two-sded estmtes for rndom multlner forms (rndom choses) generted by ndeendent
More informationA note on proper curvature collineations in Bianchi types VI
note on roer curvture collinetions in inci tyes VI nd VII sce-times Gulm Sbbir nd mjd li Fculty o Engineering Sciences GIK Institute o Engineering Sciences nd Tecnology Toi Swbi NWFP Pkistn Emil: sbbir@gikieduk
More informationProblem Set 4: Sketch of Solutions
Problem Set 4: Sketc of Solutons Informaton Economcs (Ec 55) George Georgads Due n class or by e-mal to quel@bu.edu at :30, Monday, December 8 Problem. Screenng A monopolst can produce a good n dfferent
More informationDemand. Demand and Comparative Statics. Graphically. Marshallian Demand. ECON 370: Microeconomic Theory Summer 2004 Rice University Stanley Gilbert
Demnd Demnd nd Comrtve Sttcs ECON 370: Mcroeconomc Theory Summer 004 Rce Unversty Stnley Glbert Usng the tools we hve develoed u to ths ont, we cn now determne demnd for n ndvdul consumer We seek demnd
More informationLectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix
Lectures - Week 4 Matrx norms, Condtonng, Vector Spaces, Lnear Independence, Spannng sets and Bass, Null space and Range of a Matrx Matrx Norms Now we turn to assocatng a number to each matrx. We could
More informationTHE COMBINED SHEPARD ABEL GONCHAROV UNIVARIATE OPERATOR
REVUE D ANALYSE NUMÉRIQUE ET DE THÉORIE DE L APPROXIMATION Tome 32, N o 1, 2003, pp 11 20 THE COMBINED SHEPARD ABEL GONCHAROV UNIVARIATE OPERATOR TEODORA CĂTINAŞ Abstrct We extend the Sheprd opertor by
More informationQUADRATIC RESIDUES MATH 372. FALL INSTRUCTOR: PROFESSOR AITKEN
QUADRATIC RESIDUES MATH 37 FALL 005 INSTRUCTOR: PROFESSOR AITKEN When is n integer sure modulo? When does udrtic eution hve roots modulo? These re the uestions tht will concern us in this hndout 1 The
More informationStrong Gravity and the BKL Conjecture
Introducton Strong Grvty nd the BKL Conecture Dvd Slon Penn Stte October 16, 2007 Dvd Slon Strong Grvty nd the BKL Conecture Introducton Outlne The BKL Conecture Ashtekr Vrbles Ksner Sngulrty 1 Introducton
More informationTheory of Computation Regular Languages. (NTU EE) Regular Languages Fall / 38
Theory of Computtion Regulr Lnguges (NTU EE) Regulr Lnguges Fll 2017 1 / 38 Schemtic of Finite Automt control 0 0 1 0 1 1 1 0 Figure: Schemtic of Finite Automt A finite utomton hs finite set of control
More informationThe Finite Element Method: A Short Introduction
Te Fnte Element Metod: A Sort ntroducton Wat s FEM? Te Fnte Element Metod (FEM) ntroduced by engneers n late 50 s and 60 s s a numercal tecnque for solvng problems wc are descrbed by Ordnary Dfferental
More informationGEOMETRY OF THE CIRCLE TANGENTS & SECANTS
Geometry Of The ircle Tngents & Secnts GEOMETRY OF THE IRLE TNGENTS & SENTS www.mthletics.com.u Tngents TNGENTS nd N Secnts SENTS Tngents nd secnts re lines tht strt outside circle. Tngent touches the
More informationWe partition C into n small arcs by forming a partition of [a, b] by picking s i as follows: a = s 0 < s 1 < < s n = b.
Mth 255 - Vector lculus II Notes 4.2 Pth nd Line Integrls We begin with discussion of pth integrls (the book clls them sclr line integrls). We will do this for function of two vribles, but these ides cn
More informationRemember: Project Proposals are due April 11.
Bonformtcs ecture Notes Announcements Remember: Project Proposls re due Aprl. Clss 22 Aprl 4, 2002 A. Hdden Mrov Models. Defntons Emple - Consder the emple we tled bout n clss lst tme wth the cons. However,
More informationLinear Algebra 1A - solutions of ex.4
Liner Algebr A - solutions of ex.4 For ech of the following, nd the inverse mtrix (mtritz hofkhit if it exists - ( 6 6 A, B (, C 3, D, 4 4 ( E i, F (inverse over C for F. i Also, pick n invertible mtrix
More information1 Review: Volumes of Solids (Stewart )
Lecture : Some Bic Appliction of Te Integrl (Stewrt 6.,6.,.,.) ul Krin eview: Volume of Solid (Stewrt 6.-6.) ecll: we d provided two metod for determining te volume of olid of revolution. Te rt w by dic
More informationKey words. Numerical quadrature, piecewise polynomial, convergence rate, trapezoidal rule, midpoint rule, Simpson s rule, spectral accuracy.
O SPECTRA ACCURACY OF QUADRATURE FORMUAE BASED O PIECEWISE POYOMIA ITERPOATIO A KURGAOV AD S TSYKOV Abstrct It is well-known tt te trpezoidl rule, wile being only second-order ccurte in generl, improves
More informationTopic 6b Finite Difference Approximations
/8/8 Course Instructor Dr. Rymond C. Rump Oice: A 7 Pone: (95) 747 6958 E Mil: rcrump@utep.edu Topic 6b Finite Dierence Approximtions EE 486/5 Computtionl Metods in EE Outline Wt re inite dierence pproximtions?
More informationScientific notation is a way of expressing really big numbers or really small numbers.
Scientific Nottion (Stndrd form) Scientific nottion is wy of expressing relly big numbers or relly smll numbers. It is most often used in scientific clcultions where the nlysis must be very precise. Scientific
More informationFamilies of Solutions to Bernoulli ODEs
In the fmily of solutions to the differentil eqution y ry dx + = it is shown tht vrition of the initil condition y( 0 = cuses horizontl shift in the solution curve y = f ( x, rther thn the verticl shift
More informationMath 497C Sep 17, Curves and Surfaces Fall 2004, PSU
Mth 497C Sep 17, 004 1 Curves nd Surfces Fll 004, PSU Lecture Notes 3 1.8 The generl defnton of curvture; Fox-Mlnor s Theorem Let α: [, b] R n be curve nd P = {t 0,...,t n } be prtton of [, b], then the
More informationVariable time amplitude amplification and quantum algorithms for linear algebra. Andris Ambainis University of Latvia
Vrble tme mpltude mplfcton nd quntum lgorthms for lner lgebr Andrs Ambns Unversty of Ltv Tlk outlne. ew verson of mpltude mplfcton;. Quntum lgorthm for testng f A s sngulr; 3. Quntum lgorthm for solvng
More informationLecture 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 informationFundamental Theorem of Calculus
Funmentl Teorem of Clculus Liming Png 1 Sttement of te Teorem Te funmentl Teorem of Clculus is one of te most importnt teorems in te istory of mtemtics, wic ws first iscovere by Newton n Leibniz inepenently.
More informationPRIMES AND QUADRATIC RECIPROCITY
PRIMES AND QUADRATIC RECIPROCITY ANGELICA WONG Abstrct We discuss number theory with the ultimte gol of understnding udrtic recirocity We begin by discussing Fermt s Little Theorem, the Chinese Reminder
More informationKatholieke Universiteit Leuven Department of Computer Science
Updte Rules for Weghted Non-negtve FH*G Fctorzton Peter Peers Phlp Dutré Report CW 440, Aprl 006 Ktholeke Unverstet Leuven Deprtment of Computer Scence Celestjnenln 00A B-3001 Heverlee (Belgum) Updte Rules
More informationTheory of Computation Regular Languages
Theory of Computtion Regulr Lnguges Bow-Yw Wng Acdemi Sinic Spring 2012 Bow-Yw Wng (Acdemi Sinic) Regulr Lnguges Spring 2012 1 / 38 Schemtic of Finite Automt control 0 0 1 0 1 1 1 0 Figure: Schemtic of
More informationAlgorithms for factoring
CSA E0 235: Crytograhy Arl 9,2015 Instructor: Arta Patra Algorthms for factorng Submtted by: Jay Oza, Nranjan Sngh Introducton Factorsaton of large ntegers has been a wdely studed toc manly because of
More informationSCHOOL OF ENGINEERING & BUILT ENVIRONMENT. Mathematics
SCHOOL OF ENGINEERING & BUIL ENVIRONMEN Mthemtics An Introduction to Mtrices Definition of Mtri Size of Mtri Rows nd Columns of Mtri Mtri Addition Sclr Multipliction of Mtri Mtri Multipliction 7 rnspose
More information