38 centered on te orgn, and for ostve ntegers K let P K () denote te set of lattce vectors n suc tat n=k P. Gven N onts r 1 ;::: ;r N n te unt cell U,

Size: px
Start display at page:

Download "38 centered on te orgn, and for ostve ntegers K let P K () denote te set of lattce vectors n suc tat n=k P. Gven N onts r 1 ;::: ;r N n te unt cell U,"

Transcription

1 37 Aendx D Ewald Summaton D.1 Introducton From macromolecular structure, to aqueous bologcal systems, accurate comutaton of electrostatc and van der Waals nteractons s te most dcult task n comuter modelng. Smulatons of etdes and membranes as well as of ons n aqueous solutons ave rovded clear-cut evdence of artfactual beavor due to te use of cutos. Works done by Yor 1 ave sowed usng current force eld wtout truncaton of Coulombc nteractons do not exbt smlar artfactual beavor. Te general aroac to ts roblem s te Ewald metod. D. Lattce Sums For Inverse Power Of Dstance Consder crystal lattce arwse sums of te tye E n = 1 C n q j q k r n j6=k jk (D.1) were n = 1 for Coulomb nteracton and n = for selded Coulomb nteracton, wle n =6ste London dserson term, or te van der Waals attracton sum. We'll derve te lattce summaton formulas used n our rogram for te case of dserson nteractons as well as for Coulombc nteractons. Tese lattce sums do not n general converge absolutely, so we need to secfy te asymtotc order of summaton, corresondng to te asymtotc sae of te nte crystal made u of te unon of lattce translatons of unt cell U. Let denote te set of all lattce vectors n = n 1 a 1 + n a + n 3 a 3. In order to descrbe te order of summaton n R 3, we ntroduce a closed, bounded regon P,

2 38 centered on te orgn, and for ostve ntegers K let P K () denote te set of lattce vectors n suc tat n=k P. Gven N onts r 1 ;::: ;r N n te unt cell U, and real constants C j, we consder 1 E (r 1 ;::: ;r N )= lm K!1 0 np K () ;j C j jr, r j + nj (D.) were te rme denotes tat terms wt = j and n = 0 are omtted. Let's start wt some denttes for te nverse owers 1=jrj, > 0, were r s any nonzero vector n R 3. Te followng two formulas are used,(x) = 1 1 t x,1 e,t dt = z t x,1 e,t dt 0 0 (D.3) and e,a w = a 1 0 e, u a e,wu du (D.4) were,(x) s te Euler gamma functon. Gven a 3-dmenson vector r, substtute = jrj = r and z = =. For arbtrary ostve number, we ten ave,( ) 1 = t r,1 e,rt dt + t,1 e,rt dt (D.5) 0 In te second term, f we substtute t by s, wt r t = s, we ave 1 t,1 e,rt dt = 1 1 r r s,1 e,s ds (D.6) For te rst term, we wrte r = x + y + z and aly Equaton (D.4) n all tree dmenson; and we ave 0 t,1 e,rt dt = 3 0 t, 5 R3 e, u t e,ur d 3 udt (D.7)

3 39 Integrate over t rst and substtutng t wt s, were u = ts,weave 3 0 t, 5 e, u t dt = 3,3 ( u 1 ),3 s, e,s ds u (D.8) Consder te recrocal unt cell U made u of te onts u n R 3 suc tat, 1 a u 1 and te fact tat R 3 can be decomosed as te unon of te onts sets U + m, over all recrocal vectors m, we ave 1 r = 3,3 m were we ave dened jv + mj f ( )e,(v+m)r d 3 v + g (r) U r (D.9) 1 f (x) = x,3,( ) s, e,s ds x (D.10) and g (x) = 1,( ) s,1 e,s ds x (D.11) also noted lm( 1 r!0 r, g (r) )= 1 r,( ) t,1 dt = 0,( ) (D.1) For v U we wrte v = w 1 a 1 + w a + w 3 a 3 were w k = v a k, k =1;;3. For r U and any lattce vector n = n 1 a 1 + n a + n 3 a 3, suc tat r + n 6= 0,we extend Equaton (D.9); cangng varables n te ntegral over U, we ave 1 jr + nj = 3,3 V m e,mr 1, 1 1, 1 1, 1 ;m;n (w)e,wn d 3 w + g (jr + nj) jr + nj (D.13)

4 40 were wt v = w a ;m;n (w) =f ( jv+mj )e,vr (D.14) Alyng te above formula to Equaton (D.), and usng te fact tat te sum of te Fourer coecents of te smoot, bounded functon ;m;r, m 6= 0 converges to ;m;r (0) = f ( jmj ), we can wrte E (r 1 ;::: ;r N ) = 1 0 n j,,( ) C C j g (jr, r j + nj) jr, r j + nj + 3,3 V m f ( jmj ) j C j e,m(r,r j ) (D.15) were te last term s te correcton term (self-energy) for r =0. D.3 Coulomb Sums D.3.1 Energy, Force, Stress Wen = 1 wc s Coulomb nteracton, we ave f 1 (x) = e,x ; g x 1(x) =erfc(x) (D.16) Ten we can wrte E 1 (r 1 ;::: ;r N ) = 1 0 n j, q q j erfc(jr, r j + nj) jr, r j + nj q + 1 lm K!1 np K () + 1 V U j m6=0 e, m m q q j e, m v S(m)S(,m) e,v(r,r j ) e,vn d 3 v (D.17)

5 41 were S(m) = q e,mr (D.18) s te Coulomb structure factor. Te last term dverges, but wen we aly a secondorder Taylor seres exanson to te functon e, m e,v(r,r j), exandng about v = 0. Te zerot and rst-order terms, wc account for te sngularty n te ntegral, are cancelled by te double summaton over and j for neutral unt cell. Te remander term, wc s of order tree, can be wrtten as J(D) = lm K!1 np K () U (v D) were D = P q r s te unt cell dole moment. v e,vn d 3 v (D.19) Followng te above argument, f we neglect te unt cell dole moment contrbuton (wc deends on te surface boundary of te bulk materal) and relace by =1=, weave E Coulomb = 1 L;;j Q j erfc(a) a + 0 S()S(,), e,b, 1 Q (D.0) were te rme ndcates tat te term at te orgn s excluded, a = jr, r j, R L j ; ~ =~m = H ~,1 ~n (D.1) wt matrx H contans te real sace unt cell vectors n Cartesan coordnates, and b = ; = det H (D.)

6 S() s te structure factor S() =C j q j e,r j (D.3) It was roved tat S()S(,) =C 1 ( q cos( r ) + ) q sn( r ) (D.4) Snce " 1 (r) = 1 1 r r r e,t t 1 dt # =, 1 e, r r r ( r, r r )=,e r (D.5) and S(,)S() r ; ( = C 1 q, sn( r ) q cos( r ) + cos( r ) = C 1 q q sn[ (r, r )] q sn( r ) ) (D.6) Te force on eac atom F ; =, E 1 r ;ala = C 1 erfc(a ) q q (r ;, r ;, R L; ) 3 L; + 4C 1 0 a 3 + e,a a e,b q q sn [ (r, r )] (D.7) were a = j~r, ~r, ~ R L j (D.8)

7 43 Te nternal stress can be calculated as were =, E 1 = 1, L;;j " # erfc(a) Q j + e,a a a 0 = L;;j 0 e,b S()S(,) " erfc(a) Q j + e,a a 3 a a ( 1 ), 1 # (e,b ) (r, r j, R L ) (r, r j, R L ) S()S(,) e,b ", 1+b # (D.9) r =~ H,1 n H s ; =n s (D.30) s ndeendent of H matrx, or, and a = 1 a = 1 a a (s, s j, S L ) G (s, s j, S L ) = 1 a (r, r j, R L ) (r, r j, R L ) (D.31) = 4 (n G,1 n ) G,1 = 4 n n G =,4 n G,1 G,1 n =, (D.3)

8 44 were A,1 =,A,1 B A B A,1 (D.33) was used. 1 =, 1 G G =, 1 G G,1 =, 1 (D.34) D.3. Accuracy Seced Cutos Wt seced tere s stll an nnte number of terms n te sums over te real sace and recrocal sace lattces, and an accuracy crtera s used to secfy lmts on tese sums. Ts s aceved by secfyng a tolerance and carryng out te sums untl te neglected terms ave a total contrbuton smaller tan. For structure otmzaton, te energy based cutos s desred, wle for dynamcs smulaton, te force based cutos s more arorate. We'll look at te two cases searately. Energy Based Cutos Usng a cuto dstance R cut ntroduces an error n te total energy for te real sace sum of E real = 1 L;;j were (R jl, R cut )steste functon. Q j erfc( RjL ) R jl (R jl, R cut ) (D.35) To estmate ts error, we relace te dscrete sum by a contnous ntegral. Den-

9 45 P ng te average nteracton as <q >= q =N, we ave By usng te nequalty E real ' N <q > 1 4R erfc( R R cut R ) dr (D.36) we obtan erfc( R )= t,1 e,t dt 1 R 1 1 R R e,t dt = 1 R e, R (D.37) E real N <q > 1 4 1, e R <q > dr = N erfc( R cut R cut ) (D.38) Usng a cuto H cut n te recrocal sace sum ntroduces an error n te total energy for te recrocal sace sum of E rec = 0 S()S(,) e,b (, H cut) (D.39) Relacng te sum by anntergral and relacng S()S(,) byn <q >,weobtan E rec ' N <q > Force Based Cutos H cut 4 e,( ) d = N <q > erfc( H cut 1 ) (D.40) For te real sace sum, te error ntroduced n force of atom by R cut can be wrtten as jf ;real j = 1 3 L; " erfc(a ) jq jr L + e,a #(R a 3 a L, R cut ) (D.41)

10 46 by usng average nteracton and relacng te sum wt ntegral, we obtan " # erfc(a) jf real j' N<q > 1 4R R 3 R cut a 3 + e,a a dr (D.4) furter usng Equaton (D.37), jf real j ' 4N <q > 1 Rcut 4N <q > 4N <q > = 4N <q > 1 Rcut 1 Rcut erfc(a)+ ae,a da 1 a e,a + ae,a da e,a + Rcut erfc( R cut )+e, ae,a da R cut (D.43) For recrocal sace sum, te error ntroduced n force of atom by R cut s jf ;rec j = 4 0 e,b Q sn ( r ) (, H cut) (D.44) Relacng te sum by ntegral and relacng P Q sn ( r ) by N < q >, we obtan jf rec j ' 4 N <q > 1 e,b 8 3 H cut d = N <q > 1 H cut e,b d = N <q > e, 1 4 H cut (D.45) For a gven, by usng Equaton (D.43) and Equaton (D.45) we can evaluate te cuto dstances R cut and H cut to obtan a gven accuracy Q. Because of te neutralty of te cell under wc Ewald calculaton s carred out, tere wll be a great deal of cancellaton wen we use te average nteracton <q >. Consequently, Equaton (D.43) and Equaton (D.45) overestmate te errors.

11 D.4 Dserson Sums 47 D.4.1 Energy, Force, Stress For = 6, wc s te London dserson nteracton, noted f 6 (x) = 1 3 (1, x )e,x +x 3 erfc(x) (D.46) and g 6 (x) = (1 + x + 1 x4 )e,x (D.47) we can wrte energy sum as E London = 1 C j (a,6 + a,4 +1a, )e,a 6 L;;j ;j C j cos[ (r, r j )] 3 " C j, ;j C 1 erfc(b)+ 1 b 3,1 b were a, b, and are dened n te revous secton. If we assume e,b # (D.48),C j = C C jj (D.49) we ave C j cos[ (r, r j )] =, jc j cos( r ), jc j sn( r ) ;j (D.50)

12 48 Te force on atom s F ; =, E London r ; = 1 8 L C (r, r, R L ) (6a,8 +6a,6 +3a,4 +a, )e,a 0 erfc(b)+( 1 C sn[ (r, r )] 3 b,1 3 b )e,b (D.51) Te stress = 1 8 L;;j C j (6a,8 +6a,6 +3a,4 0 ;j 0 ;j +a, )e,a (r,r,r L ) (r,r,r L ) " # 1 C j cos[ (r, r j )] 3 1 erfc(b)+( b,1 3 b )e,b C j cos[ (r, r j )]3 1 e erfc(b),,b + 3 b 6 3 ;j C j (D.5) D.4. Accuracy Seced Cutos Followng secton of Coulombnteracton, we'll dscuss te energy based accuracy and force based accuracy for London dserson nteracton. Energy Based Cutos Usng a cuto dstance R cut ntroduces an error n te total energy for te real sace sum of E real = 1 B 6 j (a,6 + a,4 + 1 a, )e,a (R Lj, R cut ) L;;j (D.53)

13 49 By usng average nteracton strengt <B j > and relacng te sum wt ntegral, we obtan E real ' N <B j > 1 6 Rcut N <B j > ( Rcut 4 Rcut (a,6 + a,4 + 1 a, )e,a R dr + 1 ) 1 Rcut e,a da = 3 N <B j > ( Rcut 4 Rcut )erfc(r cut ) (D.54) Usng a cuto dstance H cut ntroduces an error n te total energy for te recrocal sace sum of E rec = 3 4 " 0 erfc(b)+ 1 B j cos ( r j ) 3 b,1 e #(,H,b cut ) 3 b j (D.55) Relacng te sum wt ntegral, and relacng P j B j cos ( r j ) wt N <B j >, we obtan E rec ' 3 N <B j > H cut 3 " erfc(b)+ 1 = N <B j > 1 " b 3 5 erfc(b)+ 6 1 Hcut By usng erfc(b) e,b =b, we ave b 3,1 b e,b #d 1 b,b 4 e,b #db (D.56) E rec ' N <B j > = N <B j > Hcut Hcut b e,b db e, 1 4 H cut + erfc( 1 H cut) (D.57)

14 Force Based Cutos 50 Usng a cuto dstance R cut ntroduces an error n te force on atom for te real sace sum of jf ;real j' 1 8 L B r L (6a,8 +6a,6 +3a,4 +a, )e,a (r L, R cut ) (D.58) Relacng te sum wt ntegral and usng te average nteracton <B j >, we ave jf real j ' N<B j > 1 R (6a,8 +6a,6 +3a,4 +a, )e,a dr 8 R cut = N <B j > 1 (6a,6 +6a,4 +3a, +1)e,a da 5 Rcut N <B j > ( ) 5 Rcut 6 Rcut 4 Rcut 1 Rcut e,a da = 3 N<B j > ( )erfc( R cut 5 Rcut 6 Rcut 4 Rcut ) (D.59) Usng a cuto dstance H cut ntroduces an error n te force on atom for te recrocal sace sum of jf ;rec j' " erfc(b)+ 1 B sn ( r ) 3 b,1 e #(,H,b cut ) 3 b (D.60) Relacng te sum wt ntegral and usng P B sn ( r ) ' N<B j >, we obtan jf rec j ' 3 N<B j > 1 erfc(b)+( H cut b,1 3 b )e,b d N<B j > b 3 e,b d H cut = 4N<B j > 1 3 b e,b db 6 1 Hcut = N<B j > 3 H cut e, Hcut + erfc( 1 H cut) (D.61)

15 51 D.5 Partcle-Mes Ewald Sum Snce n cut = 1 H cut, te cost for recrocal sum s roortonal to 4 3 n3 cut N N N for conventon comutaton, were 4 3 n3 cut s te volume n sace, wle N s te cost of structure factor comutaton. For gven accuracy, otmze eta arameter so tat te comutaton cost mnmzed, we can get a scalng of N 3 = NN were te N and N s te cost n real sace sum and recrocal sace sum. It's not ractcal to erform smulaton wt N 1000; 000. To mrove seed, Lee Pedersen et al. roosed te so-called artclemes Ewald (PME) metod,4 wc sannlog N metod for te recrocal sace sum. D.5.1 Teory Te artcle-mes Ewald metod nvolves coosng sucently large tat atom ars for wc r j exceeds a seced cuto are neglgble n te drect sace sum wc reduces te real sace sum to order N. Te recrocal sace sum s ten aroxmated by multdmensonal ecewse-nterolaton. Te aroxmate recrocal energy and forces are exressed as convolutons and tus can be evaluated quckly usng 3D fast fourer transforms (FFTs). Te resultng algortm s of order N ln N. Let's look at te second term n Equaton (D.15) E rec = 3,3 V 0 m f ( jmj ) j C j e,m(r,r j ) (D.6) Dene te recrocal lattce vector m by m = m x a x + m y a y + m z a z wt m x,m y,m z ntegers not all zero, and te structure factor S(m) by ~S(m) = = N j=1 N j=1 q j e mr q j ex (m x s xj + m y s yj + m z s zj ) (D.63)

16 5 were s j ; = x; y; z are te fractonal coordnates of atom j. In order to aroxmate te above dened structure factor (Coulomb, or London), we'll nterolate te comlex exonentals aearng n te above equaton. Gven ostve ntegers K x ; K y ; K z and a ont r n te unt cell, denote ts fractonal coordnates by u x ; u y ; u z,.e., u = K a r, for = x; y; z. Due to erodc boundary condtons, we may assume tat 0 u K. Ten ex(m r) =ex( m xu x K x ) ex( m yu y ) ex( m zu z ) (D.64) K y K z Tere are several ways of nterolatng te above exonental. Lagrangan nterolaton and Cardnal B-slnes are te two wc get te most attenton. Lagrangan wegt functons are contnuous and terefore gve rse to aroxmate unt cell energes wc are contnuous as functons of artcle ostons. But tey are only ecewse derentable, so te aroxmate recrocal energy cannot be derentated to arrve at forces. Te forces and stresses ave to be nterolated as well. Wle by usng te Euler exonental slne wc nterolate exonentals wt te Cardnal B-slnes, we can derentate te energy to get forces and stresses, due to several nce roertes of te Cardnal B-slnes. For any real number u, let M (u) denote te lnear at functon gven by M (u) = 8 < : 1,ju,1j 0u 0 oterwse (D.65) For n greater tan, dene M n (u) byte recurson It can be roven tat M n (u) = u n,1 M n,1(u)+ n,u n,1 M n,1(u,1) (D.66) d du M n(u) =M n,1 (u),m n,1 (u,1) (D.67)

17 53 Clearly, for n >, M n (u) s n, tmes contnously derentable. It's also roved wen n s even we can wrte ex( m K u ) ' b(m ) 1 k=,1 M n (u, k)ex( m K k) (D.68) were agan = x; y; z, and b(m )= ex (n, 1) m K P n, k=0 M n(k +1)ex( m K k) (D.69) Proceedng as above, we can ten aroxmate te structure factor by ~S(m) =b(m x )b(m y )b(m z ) 1 k x;k y;k z=,1 Q(k x ;k y ;k z )ex( m x k x )ex( m y k y )ex( m z k z ) K x K y K z (D.70) were Q(k x ;k y ;k z )= N j=1 q j M n (u j x, k x, n x K x )M n (u j y, k y, n y K y )M n (u j z, k z, n z K z ) n x;n y;n z (D.71) Dene B(m x ;m y ;m z )=jb(m x )j jb(m y )j jb(m z )j (D.7) and F (Q)(m x ;m y ;m z )= 1 k x;k y;k z=,1 Q(k x ;k y ;k z )ex( m x k x )ex( m y k y )ex( m z k z ) K x K y K z (D.73)

18 54 Te aroxmate recrocal energy s now gven by E rec = 3,3 = 1 V 0 m x;m y;m z K x,1 K y,1 K z,1 k x=0 k y=0 f ( jmj )B(m x;m y ;m z )F(Q)(m x ;m y ;m z )F(Q)(,m x ;,m y ;,m z ) k z=0 Q(k x ;k y ;k z )( rec Q)(k x ;k y ;k z ) (D.74) were rec Q s te convoluton of rec and Q, and rec = F 3,3 f ( jmj V )B(m x;m y ;m z ) We ave used te followng roertes of dscrete fourer transform A B = F F,1 (A B) = F F,1 (A)F,1 (B) (D.75) (D.76) F,1 (A)(m x ;m y ;m z )=F(A)(,m x ;,m y ;,m z ) (D.77) m F (A)(m) B(m) = m A(m)F(B)(m) (D.78) Snce rec does not deend on artcle ostons, we get E rec r = K x,1 k x=0 K y,1 k y=0 K z,1 k z=0 Q r (k x ;k y ;k z )( rec Q)(k x ;k y ;k z ) (D.79) Also, snce m r does not deend on te unt cell arameters, we can comute recrocal contrbuton of stress as te followng two terms: 1; = E rec (D.80)

19 55 wc orgnate from and wt ; = 1 = F K x,1 k x=0 K y,1 k y=0 K z,1 k z=0 Q(k x ;k y ;k z )( Q)(k x ;k y ;k z ) 3,3 f ( jmj V m m )B(m x;m y ;m z ) (D.81) (D.8) For te Coulomb case, wc s =1,weave 1 Q rec = F V e, m m B(m x ;m y ;m z ) (D.83) For van der Waals attracton, or London dserson nteracton, we ave = 6, wc gves us L rec = F " 3 3 (1, 6V D.6 References m )e, + 5 m 3 3 # erfc( m ) B(m x ;m y ;m z ) (D.84) 1. D.M. York, T.A. Darden, and L.G. Pedersen, \Te eect of long-range electrostatc nteractons n smulatons of macromolecular crystals: A comarson of te Ewald and truncated lst metods," J. Cem. Pys. 99(10), 1993, U. Essmann, L. Perera, M.L. Berkowtz, T. Darden, H. Lee, and L.G. Pedersen, \A smoot artcle mes Ewald metod," J. Cem. Pys. 103(19), 1995, H.G. Petersen, \Accuracy and ecency of te artcle mes Ewald metod," J. Cem. Pys. 103(9), 1995, T. Darden, D. York, and L. Pedersen, \Partcle mes Ewald: An N log(n)

20 56 metod for Ewald sums n large systems," J. Cem. Pys. 98(1), 1993,

Not-for-Publication Appendix to Optimal Asymptotic Least Aquares Estimation in a Singular Set-up

Not-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 information

Translational Equations of Motion for A Body Translational equations of motion (centroidal) for a body are m r = f.

Translational Equations of Motion for A Body Translational equations of motion (centroidal) for a body are m r = f. Lesson 12: Equatons o Moton Newton s Laws Frst Law: A artcle remans at rest or contnues to move n a straght lne wth constant seed there s no orce actng on t Second Law: The acceleraton o a artcle s roortonal

More information

Solution Set #3

Solution 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 information

Digital PI Controller Equations

Digital PI Controller Equations Ver. 4, 9 th March 7 Dgtal PI Controller Equatons Probably the most common tye of controller n ndustral ower electroncs s the PI (Proortonal - Integral) controller. In feld orented motor control, PI controllers

More information

Shuai Dong. Isaac Newton. Gottfried Leibniz

Shuai Dong. Isaac Newton. Gottfried Leibniz Computatonal pyscs Sua Dong Isaac Newton Gottred Lebnz Numercal calculus poston dervatve ntegral v velocty dervatve ntegral a acceleraton Numercal calculus Numercal derentaton Numercal ntegraton Roots

More information

ORDINARY DIFFERENTIAL EQUATIONS EULER S METHOD

ORDINARY DIFFERENTIAL EQUATIONS EULER S METHOD Numercal Analss or Engneers German Jordanan Unverst ORDINARY DIFFERENTIAL EQUATIONS We wll eplore several metods o solvng rst order ordnar derental equatons (ODEs and we wll sow ow tese metods can be appled

More information

On a nonlinear compactness lemma in L p (0, T ; B).

On 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 information

Stanford University CS254: Computational Complexity Notes 7 Luca Trevisan January 29, Notes for Lecture 7

Stanford 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 information

6. Hamilton s Equations

6. Hamilton s Equations 6. Hamlton s Equatons Mchael Fowler A Dynamcal System s Path n Confguraton Sace and n State Sace The story so far: For a mechancal system wth n degrees of freedom, the satal confguraton at some nstant

More information

On Pfaff s solution of the Pfaff problem

On 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 information

TR/95 February Splines G. H. BEHFOROOZ* & N. PAPAMICHAEL

TR/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 information

, rst we solve te PDE's L ad L ad n g g (x) = ; = ; ; ; n () (x) = () Ten, we nd te uncton (x), te lnearzng eedbac and coordnates transormaton are gve

, rst we solve te PDE's L ad L ad n g g (x) = ; = ; ; ; n () (x) = () Ten, we nd te uncton (x), te lnearzng eedbac and coordnates transormaton are gve Freedom n Coordnates Transormaton or Exact Lnearzaton and ts Applcaton to Transent Beavor Improvement Kenj Fujmoto and Tosaru Suge Dvson o Appled Systems Scence, Kyoto Unversty, Uj, Kyoto, Japan suge@robotuassyoto-uacjp

More information

Algorithms for factoring

Algorithms 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 information

Advanced Topics in Optimization. Piecewise Linear Approximation of a Nonlinear Function

Advanced 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 information

Multivariate Ratio Estimator of the Population Total under Stratified Random Sampling

Multivariate Ratio Estimator of the Population Total under Stratified Random Sampling Open Journal of Statstcs, 0,, 300-304 ttp://dx.do.org/0.436/ojs.0.3036 Publsed Onlne July 0 (ttp://www.scrp.org/journal/ojs) Multvarate Rato Estmator of te Populaton Total under Stratfed Random Samplng

More information

Lesson 16: Basic Control Modes

Lesson 16: Basic Control Modes 0/8/05 Lesson 6: Basc Control Modes ET 438a Automatc Control Systems Technology lesson6et438a.tx Learnng Objectves Ater ths resentaton you wll be able to: Descrbe the common control modes used n analog

More information

Supplementary Material for Spectral Clustering based on the graph p-laplacian

Supplementary Material for Spectral Clustering based on the graph p-laplacian Sulementary Materal for Sectral Clusterng based on the grah -Lalacan Thomas Bühler and Matthas Hen Saarland Unversty, Saarbrücken, Germany {tb,hen}@csun-sbde May 009 Corrected verson, June 00 Abstract

More information

A NOTE ON THE DISCRETE FOURIER RESTRICTION PROBLEM

A NOTE ON THE DISCRETE FOURIER RESTRICTION PROBLEM A NOTE ON THE DISCRETE FOURIER RESTRICTION PROBLEM XUDONG LAI AND YONG DING arxv:171001481v1 [mathap] 4 Oct 017 Abstract In ths aer we establsh a general dscrete Fourer restrcton theorem As an alcaton

More information

Solution for singularly perturbed problems via cubic spline in tension

Solution for singularly perturbed problems via cubic spline in tension ISSN 76-769 England UK Journal of Informaton and Computng Scence Vol. No. 06 pp.6-69 Soluton for sngularly perturbed problems va cubc splne n tenson K. Aruna A. S. V. Rav Kant Flud Dynamcs Dvson Scool

More information

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system Transfer Functons Convenent representaton of a lnear, dynamc model. A transfer functon (TF) relates one nput and one output: x t X s y t system Y s The followng termnology s used: x y nput output forcng

More information

The Finite Element Method: A Short Introduction

The 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 information

A Quadratic Cumulative Production Model for the Material Balance of Abnormally-Pressured Gas Reservoirs F.E. Gonzalez M.S.

A Quadratic Cumulative Production Model for the Material Balance of Abnormally-Pressured Gas Reservoirs F.E. Gonzalez M.S. Natural as Engneerng A Quadratc Cumulatve Producton Model for the Materal Balance of Abnormally-Pressured as Reservors F.E. onale M.S. Thess (2003) T.A. Blasngame, Texas A&M U. Deartment of Petroleum Engneerng

More information

A Quadratic Cumulative Production Model for the Material Balance of Abnormally-Pressured Gas Reservoirs F.E. Gonzalez M.S.

A Quadratic Cumulative Production Model for the Material Balance of Abnormally-Pressured Gas Reservoirs F.E. Gonzalez M.S. Formaton Evaluaton and the Analyss of Reservor Performance A Quadratc Cumulatve Producton Model for the Materal Balance of Abnormally-Pressured as Reservors F.E. onale M.S. Thess (2003) T.A. Blasngame,

More information

One can coose te bass n te 'bg' space V n te form of symmetrzed products of sngle partcle wavefunctons ' p(x) drawn from an ortonormal complete set of

One can coose te bass n te 'bg' space V n te form of symmetrzed products of sngle partcle wavefunctons ' p(x) drawn from an ortonormal complete set of 8.54: Many-body penomena n condensed matter and atomc pyscs Last moded: September 4, 3 Lecture 3. Second Quantzaton, Bosons In ts lecture we dscuss second quantzaton, a formalsm tat s commonly used to

More information

Non-Ideality Through Fugacity and Activity

Non-Ideality Through Fugacity and Activity Non-Idealty Through Fugacty and Actvty S. Patel Deartment of Chemstry and Bochemstry, Unversty of Delaware, Newark, Delaware 19716, USA Corresondng author. E-mal: saatel@udel.edu 1 I. FUGACITY In ths dscusson,

More information

Dr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur

Dr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur Analyss of Varance and Desgn of Exerments-I MODULE II LECTURE - GENERAL LINEAR HYPOTHESIS AND ANALYSIS OF VARIANCE Dr. Shalabh Deartment of Mathematcs and Statstcs Indan Insttute of Technology Kanur 3.

More information

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U)

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U) Econ 413 Exam 13 H ANSWERS Settet er nndelt 9 deloppgaver, A,B,C, som alle anbefales å telle lkt for å gøre det ltt lettere å stå. Svar er gtt . Unfortunately, there s a prntng error n the hnt of

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs hyscs 151 Lecture Canoncal Transformatons (Chater 9) What We Dd Last Tme Drect Condtons Q j Q j = = j, Q, j, Q, Necessary and suffcent j j for Canoncal Transf. = = j Q, Q, j Q, Q, Infntesmal CT

More information

Chapter Runge-Kutta 2nd Order Method for Ordinary Differential Equations

Chapter 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 information

Quasi-Static transient Thermal Stresses in a Robin's thin Rectangular plate with internal moving heat source

Quasi-Static transient Thermal Stresses in a Robin's thin Rectangular plate with internal moving heat source 31-7871 Weely Scence Research Journal Orgnal Artcle Vol-1, Issue-44, May 014 Quas-Statc transent Theral Stresses n a Robn's n Rectangular late w nternal ovng heat source D. T. Solane and M.. Durge ABSTRACT

More information

Chapter 3 Differentiation and Integration

Chapter 3 Differentiation and Integration MEE07 Computer Modelng Technques n Engneerng Chapter Derentaton and Integraton Reerence: An Introducton to Numercal Computatons, nd edton, S. yakowtz and F. zdarovsky, Mawell/Macmllan, 990. Derentaton

More information

APPENDIX A Some Linear Algebra

APPENDIX A Some Linear Algebra APPENDIX A Some Lnear Algebra The collecton of m, n matrces A.1 Matrces a 1,1,..., a 1,n A = a m,1,..., a m,n wth real elements a,j s denoted by R m,n. If n = 1 then A s called a column vector. Smlarly,

More information

Complete Variance Decomposition Methods. Cédric J. Sallaberry

Complete Variance Decomposition Methods. Cédric J. Sallaberry Comlete Varance Decomoston Methods Cédrc J. allaberry enstvty Analyss y y [,,, ] [ y, y,, ] y ny s a vector o uncertan nuts s a vector o results s a comle uncton successon o derent codes, systems o de,

More information

Math1110 (Spring 2009) Prelim 3 - Solutions

Math1110 (Spring 2009) Prelim 3 - Solutions Math 1110 (Sprng 2009) Solutons to Prelm 3 (04/21/2009) 1 Queston 1. (16 ponts) Short answer. Math1110 (Sprng 2009) Prelm 3 - Solutons x a 1 (a) (4 ponts) Please evaluate lm, where a and b are postve numbers.

More information

Evaluating Thermodynamic Properties in LAMMPS

Evaluating Thermodynamic Properties in LAMMPS D. Keffer ME 64 Det. of Materals cence & Engneerng Unversty of ennessee Knoxvlle Evaluatng hermodynamc Proertes n LAMMP Davd Keffer Deartment of Materals cence & Engneerng Unversty of ennessee Knoxvlle

More information

CENTROID (AĞIRLIK MERKEZİ )

CENTROID (AĞIRLIK MERKEZİ ) CENTOD (ĞLK MEKEZİ ) centrod s a geometrcal concept arsng from parallel forces. Tus, onl parallel forces possess a centrod. Centrod s tougt of as te pont were te wole wegt of a pscal od or sstem of partcles

More information

Elliptic problems in domains with edges: anisotropic regularity. and anisotropic nite element meshes. October 12, 1994

Elliptic problems in domains with edges: anisotropic regularity. and anisotropic nite element meshes. October 12, 1994 Elltc roblems n domans wth edges: ansotroc regularty and ansotroc nte element meshes Thomas Ael Serge Ncase y October 2, 994 Abstract. Ths aer s concerned wth the ansotroc sngular behavour of the soluton

More information

Complex Variables. Chapter 18 Integration in the Complex Plane. March 12, 2013 Lecturer: Shih-Yuan Chen

Complex Variables. Chapter 18 Integration in the Complex Plane. March 12, 2013 Lecturer: Shih-Yuan Chen omplex Varables hapter 8 Integraton n the omplex Plane March, Lecturer: Shh-Yuan hen Except where otherwse noted, content s lcensed under a BY-N-SA. TW Lcense. ontents ontour ntegrals auchy-goursat theorem

More information

Confidence intervals for weighted polynomial calibrations

Confidence intervals for weighted polynomial calibrations Confdence ntervals for weghted olynomal calbratons Sergey Maltsev, Amersand Ltd., Moscow, Russa; ur Kalambet, Amersand Internatonal, Inc., Beachwood, OH e-mal: kalambet@amersand-ntl.com htt://www.chromandsec.com

More information

More metrics on cartesian products

More metrics on cartesian products More metrcs on cartesan products If (X, d ) are metrc spaces for 1 n, then n Secton II4 of the lecture notes we defned three metrcs on X whose underlyng topologes are the product topology The purpose of

More information

Open Systems: Chemical Potential and Partial Molar Quantities Chemical Potential

Open Systems: Chemical Potential and Partial Molar Quantities Chemical Potential Open Systems: Chemcal Potental and Partal Molar Quanttes Chemcal Potental For closed systems, we have derved the followng relatonshps: du = TdS pdv dh = TdS + Vdp da = SdT pdv dg = VdP SdT For open systems,

More information

One-sided finite-difference approximations suitable for use with Richardson extrapolation

One-sided finite-difference approximations suitable for use with Richardson extrapolation Journal of Computatonal Physcs 219 (2006) 13 20 Short note One-sded fnte-dfference approxmatons sutable for use wth Rchardson extrapolaton Kumar Rahul, S.N. Bhattacharyya * Department of Mechancal Engneerng,

More information

SINGULARLY PERTURBED BOUNDARY VALUE. We consider the following singularly perturbed boundary value problem

SINGULARLY PERTURBED BOUNDARY VALUE. We consider the following singularly perturbed boundary value problem Cater PARAETRIC QUITIC SPLIE SOLUTIO OR SIGULARLY PERTURBED BOUDARY VALUE PROBLES Introcton We conser te ollong snglarly ertrbe bonary vale roblem " L r r > an ere s a small ostve arameter st

More information

Quantum Mechanics I - Session 4

Quantum Mechanics I - Session 4 Quantum Mechancs I - Sesson 4 Aprl 3, 05 Contents Operators Change of Bass 4 3 Egenvectors and Egenvalues 5 3. Denton....................................... 5 3. Rotaton n D....................................

More information

bounds, but Mao [{4] only dscussed te mean square (te case of p = ) almost sure exponental stablty. Due to te new tecnques developed n ts paper, te re

bounds, but Mao [{4] only dscussed te mean square (te case of p = ) almost sure exponental stablty. Due to te new tecnques developed n ts paper, te re Asymptotc Propertes of Neutral Stocastc Derental Delay Equatons Xuerong Mao Department of Statstcs Modellng Scence Unversty of Stratclyde Glasgow G XH, Scotl, U.K. Abstract: Ts paper dscusses asymptotc

More information

1 (1 + ( )) = 1 8 ( ) = (c) Carrying out the Taylor expansion, in this case, the series truncates at second order:

1 (1 + ( )) = 1 8 ( ) = (c) Carrying out the Taylor expansion, in this case, the series truncates at second order: 68A Solutons to Exercses March 05 (a) Usng a Taylor expanson, and notng that n 0 for all n >, ( + ) ( + ( ) + ) We can t nvert / because there s no Taylor expanson around 0 Lets try to calculate the nverse

More information

Numerical Simulation of One-Dimensional Wave Equation by Non-Polynomial Quintic Spline

Numerical Simulation of One-Dimensional Wave Equation by Non-Polynomial Quintic Spline IOSR Journal of Matematcs (IOSR-JM) e-issn: 78-578, p-issn: 319-765X. Volume 14, Issue 6 Ver. I (Nov - Dec 018), PP 6-30 www.osrournals.org Numercal Smulaton of One-Dmensonal Wave Equaton by Non-Polynomal

More information

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0 MODULE 2 Topcs: Lnear ndependence, bass and dmenson We have seen that f n a set of vectors one vector s a lnear combnaton of the remanng vectors n the set then the span of the set s unchanged f that vector

More information

CENTROID (AĞIRLIK MERKEZİ )

CENTROID (AĞIRLIK MERKEZİ ) CENTOD (ĞLK MEKEZİ ) centrod s a geometrcal concept arsng from parallel forces. Tus, onl parallel forces possess a centrod. Centrod s tougt of as te pont were te wole wegt of a pscal od or sstem of partcles

More information

Non-interacting Spin-1/2 Particles in Non-commuting External Magnetic Fields

Non-interacting Spin-1/2 Particles in Non-commuting External Magnetic Fields EJTP 6, No. 0 009) 43 56 Electronc Journal of Theoretcal Physcs Non-nteractng Spn-1/ Partcles n Non-commutng External Magnetc Felds Kunle Adegoke Physcs Department, Obafem Awolowo Unversty, Ile-Ife, Ngera

More information

Chapter Eight. Review and Summary. Two methods in solid mechanics ---- vectorial methods and energy methods or variational methods

Chapter Eight. Review and Summary. Two methods in solid mechanics ---- vectorial methods and energy methods or variational methods Chapter Eght Energy Method 8. Introducton 8. Stran energy expressons 8.3 Prncpal of statonary potental energy; several degrees of freedom ------ Castglano s frst theorem ---- Examples 8.4 Prncpal of statonary

More information

Digital Signal Processing

Digital Signal Processing Dgtal Sgnal Processng Dscrete-tme System Analyss Manar Mohasen Offce: F8 Emal: manar.subh@ut.ac.r School of IT Engneerng Revew of Precedent Class Contnuous Sgnal The value of the sgnal s avalable over

More information

Dr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur

Dr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur Analyss of Varance and Desgn of Exerments-I MODULE III LECTURE - 2 EXPERIMENTAL DESIGN MODELS Dr. Shalabh Deartment of Mathematcs and Statstcs Indan Insttute of Technology Kanur 2 We consder the models

More information

5 The Laplace Equation in a convex polygon

5 The Laplace Equation in a convex polygon 5 Te Laplace Equaton n a convex polygon Te most mportant ellptc PDEs are te Laplace, te modfed Helmoltz and te Helmoltz equatons. Te Laplace equaton s u xx + u yy =. (5.) Te real and magnary parts of an

More information

Competitive Experimentation and Private Information

Competitive Experimentation and Private Information Compettve Expermentaton an Prvate Informaton Guseppe Moscarn an Francesco Squntan Omtte Analyss not Submtte for Publcaton Dervatons for te Gamma-Exponental Moel Dervaton of expecte azar rates. By Bayes

More information

χ x B E (c) Figure 2.1.1: (a) a material particle in a body, (b) a place in space, (c) a configuration of the body

χ x B E (c) Figure 2.1.1: (a) a material particle in a body, (b) a place in space, (c) a configuration of the body Secton.. Moton.. The Materal Body and Moton hyscal materals n the real world are modeled usng an abstract mathematcal entty called a body. Ths body conssts of an nfnte number of materal partcles. Shown

More information

OPTIMISATION. Introduction Single Variable Unconstrained Optimisation Multivariable Unconstrained Optimisation Linear Programming

OPTIMISATION. Introduction Single Variable Unconstrained Optimisation Multivariable Unconstrained Optimisation Linear Programming OPTIMIATION Introducton ngle Varable Unconstraned Optmsaton Multvarable Unconstraned Optmsaton Lnear Programmng Chapter Optmsaton /. Introducton In an engneerng analss, sometmes etremtes, ether mnmum or

More information

PARTIAL QUOTIENTS AND DISTRIBUTION OF SEQUENCES. Department of Mathematics University of California Riverside, CA

PARTIAL QUOTIENTS AND DISTRIBUTION OF SEQUENCES. Department of Mathematics University of California Riverside, CA PARTIAL QUOTIETS AD DISTRIBUTIO OF SEQUECES 1 Me-Chu Chang Deartment of Mathematcs Unversty of Calforna Rversde, CA 92521 mcc@math.ucr.edu Abstract. In ths aer we establsh average bounds on the artal quotents

More information

Number of cases Number of factors Number of covariates Number of levels of factor i. Value of the dependent variable for case k

Number of cases Number of factors Number of covariates Number of levels of factor i. Value of the dependent variable for case k ANOVA Model and Matrx Computatons Notaton The followng notaton s used throughout ths chapter unless otherwse stated: N F CN Y Z j w W Number of cases Number of factors Number of covarates Number of levels

More information

1 Introducton Nonlnearty crtera of Boolean functons Cryptograpc transformatons sould be nonlnear to be secure aganst varous attacks. For example, te s

1 Introducton Nonlnearty crtera of Boolean functons Cryptograpc transformatons sould be nonlnear to be secure aganst varous attacks. For example, te s KUIS{94{000 Nonlnearty crtera of Boolean functons HIROSE Souc IKEDA Katsuo Tel +81 75 753 5387 Fax +81 75 751 048 E-mal frose, kedag@kus.kyoto-u.ac.jp July 14, 1994 1 Introducton Nonlnearty crtera of Boolean

More information

Lecture Note 3. Eshelby s Inclusion II

Lecture Note 3. Eshelby s Inclusion II ME340B Elastcty of Mcroscopc Structures Stanford Unversty Wnter 004 Lecture Note 3. Eshelby s Incluson II Chrs Wenberger and We Ca c All rghts reserved January 6, 004 Contents 1 Incluson energy n an nfnte

More information

Fuzzy approach to solve multi-objective capacitated transportation problem

Fuzzy approach to solve multi-objective capacitated transportation problem Internatonal Journal of Bonformatcs Research, ISSN: 0975 087, Volume, Issue, 00, -0-4 Fuzzy aroach to solve mult-objectve caactated transortaton roblem Lohgaonkar M. H. and Bajaj V. H.* * Deartment of

More information

The Karush-Kuhn-Tucker. Nuno Vasconcelos ECE Department, UCSD

The Karush-Kuhn-Tucker. Nuno Vasconcelos ECE Department, UCSD e Karus-Kun-ucker condtons and dualt Nuno Vasconcelos ECE Department, UCSD Optmzaton goal: nd mamum or mnmum o a uncton Denton: gven unctons, g, 1,...,k and, 1,...m dened on some doman Ω R n mn w, w Ω

More information

Linear system of the Schrödinger equation Notes on Quantum Mechanics

Linear system of the Schrödinger equation Notes on Quantum Mechanics Lnear sstem of the Schrödnger equaton Notes on Quantum Mechancs htt://quantum.bu.edu/notes/quantummechancs/lnearsstems.df Last udated Wednesda, October 9, 003 :0:08 Corght 003 Dan Dll (dan@bu.edu) Deartment

More information

EP523 Introduction to QFT I

EP523 Introduction to QFT I EP523 Introducton to QFT I Toc 0 INTRODUCTION TO COURSE Deartment of Engneerng Physcs Unversty of Gazante Setember 2011 Sayfa 1 Content Introducton Revew of SR, QM, RQM and EMT Lagrangan Feld Theory An

More information

A Novel Blind Channel Estimation for a 2x2 MIMO System

A Novel Blind Channel Estimation for a 2x2 MIMO System Int. J. Communcatons Network and System Scences 009 5 344-350 do:0.436/jcns.009.5037 Publsed Onlne ugust 009 (tt://www.scrp.org/journal/jcns/). Novel Blnd Cannel Estmaton for a x MIMO System Xa LIU Marek

More information

1 Matrix representations of canonical matrices

1 Matrix representations of canonical matrices 1 Matrx representatons of canoncal matrces 2-d rotaton around the orgn: ( ) cos θ sn θ R 0 = sn θ cos θ 3-d rotaton around the x-axs: R x = 1 0 0 0 cos θ sn θ 0 sn θ cos θ 3-d rotaton around the y-axs:

More information

PHYS 705: Classical Mechanics. Canonical Transformation II

PHYS 705: Classical Mechanics. Canonical Transformation II 1 PHYS 705: Classcal Mechancs Canoncal Transformaton II Example: Harmonc Oscllator f ( x) x m 0 x U( x) x mx x LT U m Defne or L p p mx x x m mx x H px L px p m p x m m H p 1 x m p m 1 m H x p m x m m

More information

Problem 10.1: One-loop structure of QED

Problem 10.1: One-loop structure of QED Problem 10.1: One-loo structure of QED In Secton 10.1 we argued form general rncles that the hoton one-ont and three-ont functons vansh, whle the four-ont functon s fnte. (a Verfy drectly that the one-loo

More information

University of Washington Department of Chemistry Chemistry 452/456 Summer Quarter 2014

University of Washington Department of Chemistry Chemistry 452/456 Summer Quarter 2014 Lecture 16 8/4/14 Unversty o Washngton Department o Chemstry Chemstry 452/456 Summer Quarter 214. Real Vapors and Fugacty Henry s Law accounts or the propertes o extremely dlute soluton. s shown n Fgure

More information

Topology optimization of plate structures subject to initial excitations for minimum dynamic performance index

Topology optimization of plate structures subject to initial excitations for minimum dynamic performance index th World Congress on Structural and Multdsclnary Otmsaton 7 th -2 th, June 25, Sydney Australa oology otmzaton of late structures subject to ntal exctatons for mnmum dynamc erformance ndex Kun Yan, Gengdong

More information

Adaptive Kernel Estimation of the Conditional Quantiles

Adaptive Kernel Estimation of the Conditional Quantiles Internatonal Journal of Statstcs and Probablty; Vol. 5, No. ; 206 ISSN 927-7032 E-ISSN 927-7040 Publsed by Canadan Center of Scence and Educaton Adaptve Kernel Estmaton of te Condtonal Quantles Rad B.

More information

Tensor Analysis. For orthogonal curvilinear coordinates, ˆ ˆ (98) Expanding the derivative, we have, ˆ. h q. . h q h q

Tensor Analysis. For orthogonal curvilinear coordinates, ˆ ˆ (98) Expanding the derivative, we have, ˆ. h q. . h q h q For orthogonal curvlnear coordnates, eˆ grad a a= ( aˆ ˆ e). h q (98) Expandng the dervatve, we have, eˆ aˆ ˆ e a= ˆ ˆ a h e + q q 1 aˆ ˆ ˆ a e = ee ˆˆ ˆ + e. h q h q Now expandng eˆ / q (some of the detals

More information

Solutions to Problem Set 6

Solutions to Problem Set 6 Solutons to Problem Set 6 Problem 6. (Resdue theory) a) Problem 4.7.7 Boas. n ths problem we wll solve ths ntegral: x sn x x + 4x + 5 dx: To solve ths usng the resdue theorem, we study ths complex ntegral:

More information

Comparing two Quantiles: the Burr Type X and Weibull Cases

Comparing two Quantiles: the Burr Type X and Weibull Cases IOSR Journal of Mathematcs (IOSR-JM) e-issn: 78-578, -ISSN: 39-765X. Volume, Issue 5 Ver. VII (Se. - Oct.06), PP 8-40 www.osrjournals.org Comarng two Quantles: the Burr Tye X and Webull Cases Mohammed

More information

PES 1120 Spring 2014, Spendier Lecture 6/Page 1

PES 1120 Spring 2014, Spendier Lecture 6/Page 1 PES 110 Sprng 014, Spender Lecture 6/Page 1 Lecture today: Chapter 1) Electrc feld due to charge dstrbutons -> charged rod -> charged rng We ntroduced the electrc feld, E. I defned t as an nvsble aura

More information

Limit Cycle Bifurcations in a Class of Cubic System near a Nilpotent Center *

Limit Cycle Bifurcations in a Class of Cubic System near a Nilpotent Center * Appled Mateatcs 77-777 ttp://dxdoorg/6/a75 Publsed Onlne July (ttp://wwwscrporg/journal/a) Lt Cycle Bfurcatons n a Class of Cubc Syste near a Nlpotent Center * Jao Jang Departent of Mateatcs Sanga Marte

More information

An efficient algorithm for multivariate Maclaurin Newton transformation

An efficient algorithm for multivariate Maclaurin Newton transformation Annales UMCS Informatca AI VIII, 2 2008) 5 14 DOI: 10.2478/v10065-008-0020-6 An effcent algorthm for multvarate Maclaurn Newton transformaton Joanna Kapusta Insttute of Mathematcs and Computer Scence,

More information

Counting Solutions to Discrete Non-Algebraic Equations Modulo Prime Powers

Counting Solutions to Discrete Non-Algebraic Equations Modulo Prime Powers Rose-Hulman Insttute of Technology Rose-Hulman Scholar Mathematcal Scences Techncal Reorts (MSTR) Mathematcs 5-20-2016 Countng Solutons to Dscrete Non-Algebrac Equatons Modulo Prme Powers Abgal Mann Rose-Hulman

More information

SIO 224. m(r) =(ρ(r),k s (r),µ(r))

SIO 224. m(r) =(ρ(r),k s (r),µ(r)) SIO 224 1. A bref look at resoluton analyss Here s some background for the Masters and Gubbns resoluton paper. Global Earth models are usually found teratvely by assumng a startng model and fndng small

More information

LECTURE 5: FIBRATIONS AND HOMOTOPY FIBERS

LECTURE 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 information

Power-sum problem, Bernoulli Numbers and Bernoulli Polynomials.

Power-sum problem, Bernoulli Numbers and Bernoulli Polynomials. Power-sum roblem, Bernoull Numbers and Bernoull Polynomals. Arady M. Alt Defnton 1 Power um Problem Fnd the sum n : 1... n where, n N or, usng sum notaton, n n n closed form. Recurrence for n Exercse Usng

More information

COMP4630: λ-calculus

COMP4630: 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 information

Bernoulli Numbers and Polynomials

Bernoulli Numbers and Polynomials Bernoull Numbers and Polynomals T. Muthukumar tmk@tk.ac.n 17 Jun 2014 The sum of frst n natural numbers 1, 2, 3,..., n s n n(n + 1 S 1 (n := m = = n2 2 2 + n 2. Ths formula can be derved by notng that

More information

Malaya J. Mat. 2(1)(2014) 49 60

Malaya J. Mat. 2(1)(2014) 49 60 Malaya J. Mat. 2(1)(2014) 49 60 Functonal equaton orgnatng from sum of hgher owers of arthmetc rogresson usng dfference oerator s stable n Banach sace: drect and fxed ont methods M. Arunumar a, and G.

More information

Formulas for the Determinant

Formulas for the Determinant page 224 224 CHAPTER 3 Determnants e t te t e 2t 38 A = e t 2te t e 2t e t te t 2e 2t 39 If 123 A = 345, 456 compute the matrx product A adj(a) What can you conclude about det(a)? For Problems 40 43, use

More information

Numerical Analysis MTH603. dy dt = = (0) , y n+1. We obtain yn. Therefore. and. Copyright Virtual University of Pakistan 1

Numerical Analysis MTH603. dy dt = = (0) , y n+1. We obtain yn. Therefore. and. Copyright Virtual University of Pakistan 1 Numerical Analysis MTH60 PREDICTOR CORRECTOR METHOD Te metods presented so far are called single-step metods, were we ave seen tat te computation of y at t n+ tat is y n+ requires te knowledge of y n only.

More information

Managing Capacity Through Reward Programs. on-line companion page. Byung-Do Kim Seoul National University College of Business Administration

Managing Capacity Through Reward Programs. on-line companion page. Byung-Do Kim Seoul National University College of Business Administration Managng Caacty Through eward Programs on-lne comanon age Byung-Do Km Seoul Natonal Unversty College of Busness Admnstraton Mengze Sh Unversty of Toronto otman School of Management Toronto ON M5S E6 Canada

More information

Departure Process from a M/M/m/ Queue

Departure Process from a M/M/m/ Queue Dearture rocess fro a M/M// Queue Q - (-) Q Q3 Q4 (-) Knowledge of the nature of the dearture rocess fro a queue would be useful as we can then use t to analyze sle cases of queueng networs as shown. The

More information

Finite Element Modelling of truss/cable structures

Finite Element Modelling of truss/cable structures Pet Schreurs Endhoven Unversty of echnology Department of Mechancal Engneerng Materals echnology November 3, 214 Fnte Element Modellng of truss/cable structures 1 Fnte Element Analyss of prestressed structures

More information

Ballot Paths Avoiding Depth Zero Patterns

Ballot Paths Avoiding Depth Zero Patterns Ballot Paths Avodng Depth Zero Patterns Henrch Nederhausen and Shaun Sullvan Florda Atlantc Unversty, Boca Raton, Florda nederha@fauedu, ssull21@fauedu 1 Introducton In a paper by Sapounaks, Tasoulas,

More information

Modelli Clamfim Equazione del Calore Lezione ottobre 2014

Modelli Clamfim Equazione del Calore Lezione ottobre 2014 CLAMFIM Bologna Modell 1 @ Clamfm Equazone del Calore Lezone 17 15 ottobre 2014 professor Danele Rtell danele.rtell@unbo.t 1/24? Convoluton The convoluton of two functons g(t) and f(t) s the functon (g

More information

THE VIBRATIONS OF MOLECULES II THE CARBON DIOXIDE MOLECULE Student Instructions

THE VIBRATIONS OF MOLECULES II THE CARBON DIOXIDE MOLECULE Student Instructions THE VIBRATIONS OF MOLECULES II THE CARBON DIOXIDE MOLECULE Student Instructons by George Hardgrove Chemstry Department St. Olaf College Northfeld, MN 55057 hardgrov@lars.acc.stolaf.edu Copyrght George

More information

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems Numercal Analyss by Dr. Anta Pal Assstant Professor Department of Mathematcs Natonal Insttute of Technology Durgapur Durgapur-713209 emal: anta.bue@gmal.com 1 . Chapter 5 Soluton of System of Lnear Equatons

More information

Numerical Differentiation

Numerical Differentiation Part 5 Capter 19 Numercal Derentaton PowerPonts organzed by Dr. Mcael R. Gustason II, Duke Unversty Revsed by Pro. Jang, CAU All mages copyrgt Te McGraw-Hll Companes, Inc. Permsson requred or reproducton

More information

Georgia Tech PHYS 6124 Mathematical Methods of Physics I

Georgia Tech PHYS 6124 Mathematical Methods of Physics I Georga Tech PHYS 624 Mathematcal Methods of Physcs I Instructor: Predrag Cvtanovć Fall semester 202 Homework Set #7 due October 30 202 == show all your work for maxmum credt == put labels ttle legends

More information

Prof. Dr. I. Nasser Phys 630, T Aug-15 One_dimensional_Ising_Model

Prof. Dr. I. Nasser Phys 630, T Aug-15 One_dimensional_Ising_Model EXACT OE-DIMESIOAL ISIG MODEL The one-dmensonal Isng model conssts of a chan of spns, each spn nteractng only wth ts two nearest neghbors. The smple Isng problem n one dmenson can be solved drectly n several

More information

Chapter 8: Fast Convolution. Keshab K. Parhi

Chapter 8: Fast Convolution. Keshab K. Parhi Cater 8: Fat Convoluton Keab K. Par Cater 8 Fat Convoluton Introducton Cook-Too Algort and Modfed Cook-Too Algort Wnograd Algort and Modfed Wnograd Algort Iterated Convoluton Cyclc Convoluton Degn of Fat

More information

Week 9 Chapter 10 Section 1-5

Week 9 Chapter 10 Section 1-5 Week 9 Chapter 10 Secton 1-5 Rotaton Rgd Object A rgd object s one that s nondeformable The relatve locatons of all partcles makng up the object reman constant All real objects are deformable to some extent,

More information

where the sums are over the partcle labels. In general H = p2 2m + V s(r ) V j = V nt (jr, r j j) (5) where V s s the sngle-partcle potental and V nt

where the sums are over the partcle labels. In general H = p2 2m + V s(r ) V j = V nt (jr, r j j) (5) where V s s the sngle-partcle potental and V nt Physcs 543 Quantum Mechancs II Fall 998 Hartree-Fock and the Self-consstent Feld Varatonal Methods In the dscusson of statonary perturbaton theory, I mentoned brey the dea of varatonal approxmaton schemes.

More information