Non-Markovian Effects on the Brownian Motion of a Free Particle

Size: px
Start display at page:

Download "Non-Markovian Effects on the Brownian Motion of a Free Particle"

Transcription

1 Non-Markovian Effecs on he Brownian Moion of a Free Paricle A. O. Bolivar Insiuo Mário Schönberg de Física-Maemáica-Filosofia, Ceilândia, Caixa Posal 7316, DF , Brazil bolivar@cbpf.br Absrac Non-Markovian effecs upon he Brownian movemen of a free paricle in he presence as well as in he absence of inerial force are invesigaed wihin he framework of Fokker Planck equaions (Rayleigh and Smoluchowski equaions). More specifically, i is prediced ha non-markovian feaures can enhance he values of he mean square displacemen and momenum, hereby assuring he mahemaical propery of differeniabiliy of he hese physically observable quaniies. Keywords: Brownian Moion; Smoluchowski equaion; Ornsein Uhlenbeck process; Fokker Planck equaion; non-markov effecs 1

2 1 Inroducion The Brownian moion of a paricle wih mass m and posiion X = X() may be described by he Langevin equaion [1] m d2 X d 2 = dv(x) dx dx + L, (1) d where he inerial force md 2 X/d 2 offses a se of hree sors of forces: a conservaive force derived from an exernal poenial V(X); a linearly velociydependen dissipaive force, dx/d, accouns for sopping he paricle s moion; and a sochasic force L, dubbed Langevin s force, responsible for acivaing he paricle s movemen. The damping consan exhibis dimensions of mass per ime. As far as a free paricle is concerned, he Langevin equaion (1) may be wrien in erms of he linear momenum P = P = mdx/d as dp d = P + L. (2) m On he oher hand, in he absence of inerial force, i.e., md 2 X/d 2 = 0, he free Brownian paricle is described by he sochasic differenial equaion dx d = 1 L. (3) In he Gaussian approximaion i is assumed ha he Langevin force L presen in (1 3) has he following saisical properies [2] L() = 0, (4) L L( ) = Dδ, (5) where D is a consan and he average value is evaluaed from he probabiliy disribuion funcion associaed wih he environmenal random funcion L. Equaion (4) characerizes he irregulariy feaure of he Langevin force and Eq. (5) means ha he ineracion beween he agged paricle and a generic environmen is deemed o be Markovian in he sense ha he auocorrelaion funcion (5) is dela-correlaed (whie noise). For hermal open sysems characerized by he emperaure T and he Bolzmann consan k B, he Ornsein-Uhlenbeck process (2), along wih (4) and (5), leads o he mean square momenum [3] P = mk B T 1 e 2 m, (6) 2

3 whereas he Fokker Planck equaion (he so-called diffusion equaion) generaed by he sochasic differenial equaion (3) wih he saisical properies (4) and (5) yields he Einsein s mean square displacemen [4] X = 2k B T. (7) Boh Markovian resuls (6) and (7) are non-differeniable funcions a = 0. Hence, i has been claimed ha physically here is no force applied o a free Brownian paricle in he presence of inerial forces, as well as no velociy in he absence of inerial forces [5,6]. This fac suggess ha he concep of rajecory of a free Brownian paricle seems o be an elusive feaure in he Markovian regime. The purpose of he presen paper is o show how non-markovian effecs upon a free Brownian paricle are responsible for he differeniabiliy propery of he mean square displacemen (6) and momenum (7), hereby predicing an increase of he values of hese physically observable quaniies. Our paper discusses he Brownian moion of a free paricle reckoning wih wo physical siuaions described by Fokker Planck equaions: In Sec. 2 he case of a Brownian paricle in he presence of inerial forces (Ornsein Uhlenbeck sochasic process) described by he non-markovian Rayleigh equaion is examined, whereas in Sec. 3 we solve our non-markovian Smoluchowki equaion describing a free Brownian paricle in he absence of inerial effecs. Concluding remarks are presened in Sec. 4. In addiion, wo appendices are included. 3

4 2 Brownian Moion in he Presence of Inerial Force A paricle wih mass m, posiion X = X() immersed in a generic environmen (e.g., a non-hermal fluid) undergoes a jiering movemen dubbed Brownian moion. The moion of his agged paricle may be mahemaically described by he sochasic differenial equaion (1) (he so-called Langevin equaion) in he form m d2 X d 2 = dv(x) dx dx + bψ, (8) d wih he Langevin force given by L = bψ, where he parameer b conrols he environmenal influence (flucuaions) upon he Brownian paricle. Because he erm bψ in (8) has dimensions of velociy, i.e., [leng ime 1 ], we can readily check ha b may be expressed in dimensions of [leng ime 1/2 ] and he funcion Ψ in dimensions of [ime 1/2 ]. From he mahemaical viewpoin he quaniies X = X and Ψ = Ψ in he Langevin equaion (8) are inerpreed as random variables belonging o he Kolmogorov probabiliy space [7] in he sense ha here exiss a probabiliy disribuion funcion, F XΨ x, ψ,, associaed wih he sochasic sysem {X, Ψ}, expressed in erms of he possible values x = {x i } and ψ = {ψ i }, wih i 1, disribued abou he sharp values q and φ of X and Ψ, respecively. In addiion, he average values of X and Ψ are expressed as + X = xf XΨ x, ψ, dxdψ, (9) + Ψ = ψf XΨ x, ψ, dxdψ. (10) For a free Brownian paricle he Langevin equaion (8) may be expressed in erms of he concep of linear momenum P = P = mdx/d as Noicing ha dp d = P + bψ. (11) m lim ε 0 +ε Ψ d = 0, (12) wih 4

5 Ψ() = + ψf Ψ ψ, dψ, he Fokker Planck equaion generaed by (11) in he Gaussian approximaion reads (see Appendix A) g p, = p p b Ψ m g p, + D p 2 g p, p 2 (13) in erms of he probabiliy disribuion funcion g p,, he mean value of Ψ and he diffusion coefficien 1 Ψ = lim ε 0 ε +ε Ψ d, (14) D p = E (15) where he funcion E, given by E = b2 2 b2 I() = 2 lim 1 ε 0 ε +ε Ψ Ψ d d, (16) has dimensions of energy, i.e., [mass leng 2 ime 2 ]. Hence we call E he diffusion energy responsible for he Brownian moion of he paricle dipped in a generic environmen. An ousanding feaure underlying he diffusion energy concep (16), which fulfils he validiy condiion 0 < E <, (17) is ha i conveys in andem flucuaion and dissipaion phenomena hrough he funcion I() and he fricion consan, respecively. We can hen sae ha (16) ses up a general flucuaion dissipaion relaionship underlying all open sysems described by he Langevin equaion (11) and is corresponding Fokker Planck equaion (13). Boh cases E = 0 and E = are no concerned, for hey may violae he validiy condiion of he flucuaion dissipaion relaion (17). The former case may lead o dissipaion wihou flucuaion, whils he laer one may give rise o flucuaion wihou dissipaion. 5

6 From he physical poin of view he pivoal issue inheren in heory of Brownian moion is o deermine he ranspor coefficien, ha is, he imedependen diffusion coefficien (15). A = 0 he answer o his quesion seems o be fairly sraighforward, for he diffusion energy is null, i.e., E 0 = D 0 = 0, meaning ha here is no diffusive moion, D 0 = 0, associaed wih he iniial condiion g p, = 0 = δ p o our Fokker Planck equaion (13). On he oher hand, a he long-ime regime,, we assume ha he seady diffusion energy can be idenified wih he hermal energy, k B T, a hermodynamic equilibrium, i.e., b2 lim E = 2 = k BT, (18) wih he dimensionless funcion I in (15) having he asympoic behavior lim I = 1. (19) The physical significance of condiion (19) has o do wih he fac ha environmenal flucuaions decay o Markovian correlaions, i.e., I displays a local (shor) range behavior in he seady regime. By conras, non-markovian effecs show up a he range 0 < <. The correlaional funcion I in (16) fulfilling condiion (19) can be buil up as (see Appendix B) I = 1 e c, (20) where he correlaion ime c accouns for non-markovian effecs upon he Brownian paricle. I is worh underscoring ha he ideniy (18) expresses he principle of energy conservaion, for he diffusion energy E = b 2 /2 comes from he Markovian Brownian dynamics (Langevin and Fokker Planck equaions a he seady regime), whereas he hermal energy k B T is a physical quaniy semming from he environmen a hermodynamic equilibrium (equaion of sae for perfec gases: PV = Nk B T, where N is he number of paricles wihin he volume V under he pressure P and emperaure T; he consan k B denoes he Bolzmann consan and displays dimensions of energy per emperaure). As a consequence of he conservaion of energy (18), from (15) a he hermal equilibrium we can readily derive he Ornsein Uhlenbeck diffusion consan as D p = k B T, (21) and he parameer b urns ou o be of hermal naure, i.e., b = ± 2k B T. (22) 6

7 Using (22), (20), (16), and (15) our Fokker Planck equaion (13) reads g p, = p p m 2k B T Ψ g p, + k B T 1 e c 2 g p, p 2. (23) or g p, = m p p g p, + k B T 1 e c 2 g p, p 2, (24) in erms of he hermal posiion p = p m 2k B T Ψ. (25) According o (23) a paricle immersed in a hea bah undergoes a Brownian moion owing o he diffusion energy semming from he hermal reservoir, k B T, muliplied by he correlaional effecs presen in he funcion I = 1 e / c. In general, he non-equilibrium hermal energy E = k B T 1 e / c is differen from he equilibrium hermal energy, k B T. They equal only a he seady regime (18). In his hermal equilibrium sae he sochasic process is called normal diffusion, whereas in he non-equilibrium hermal regime characerized by 0 < I < 1 he Brownian moion is said o be subdiffusive. I is worh poining ou ha he diffusion consan (21) has been derived wihou specifying ab iniio he form of he auocorrelaion funcion of he Langevin force, L( )L( ) = 2k B T Ψ Ψ = 2D p Ψ Ψ, as well as is average value, i.e., L() = ± 2k B T Ψ() = ± 2D p Ψ(). The crucial poin is he long ime behavior (19). This means ha he arbirariness as o he form of he saisical properies of he Langevin force L() leaves room o incorporae non-markovian and averaging effecs ino he sudy of Brownian moion hrough he funcions I and Ψ in he Fokker Planck equaion (23). So, saring from he iniial condiion g p, = 0 = δ(p ) a non-equilibrium soluion o (23) reads g p, = 1 4πℲ e 4Ⅎ, (26) p 2 where 7

8 Ⅎ = mk BT 2 1 e 2 m 2 c 2 c m e c. (27) The probabiliy disribuion funcion (26), which is expressed in erms of he evoluion ime, he relaxaion ime r = m/, and he correlaion ime c, gives rise o P = 0, (28) P 2 = 2Ⅎ = mk B T 1 e 2 m 2 c 2 c m e c. (29) Making use of (29) he mean mechanical energy associaed wih he free Brownian paricle is given by which reduces o E() = P 2 2m = k BT 2 1 e 2 m 2 c 2 c m e c (30) E() = k BT 2 1 e 2 m (31) in he Markovian limi. The mean square momenum, P () = P 2 P 2, reads P () = P = mk B T 1 e 2 m 2 c 2 c m e c, (32) meaning ha he average value of Ψ in Eq. (25) has no influence upon he physically observable quaniy (32). I is readily o check ha he quaniy d P d =0 = 22 k B T c 2 c m m 2 c 2mk B T c (33) does no diverge provided ha 0 < c < m/2, hereby implying ha non- Markovian effecs are responsible for enhancing he mean square momenum (32). Ye in he Markovian limi we find from (32) he resul P = mk B T 1 e 2 m (34) ha is non-differeniable a = 0. Non-Markovian effecs in (32) herefore accoun for he exisence of he concep of force acing upon a free Brownian paricle in he presence of inerial force, since 0 < c < m/2. 8

9 A he equilibrium regime, from (30) he energy equipariion is readily obained as E( ) = k BT 2, (35) while from he non-equilibrium soluion (26) we derive he Maxwell Bolzmann probabiliy disribuion funcion a hermal equilibrium g p = 1 2πmk B T e 2mk B T (36) p 2 for he hermal momenum (25). 3 Brownian Moion in he Absence of Inerial Force Now we sar from he Langevin equaion (8) in he Smoluchowski limi (he large fricion case) P m + bψ dp d, (37) such ha inerial effecs in (8) can be negligible, i.e., md 2 X/d 2 = 0. So he Brownian moion is approximaed by he sochasic differenial equaion dx d = 1 dv(x) + bψ, (38) dx which gives rise o he following Fokker Planck equaion on configuraion space in he Gaussian approximaion (see Appendix A) f x, = x 1 dv x dx + b Ψ f x, + D x() 2 f x, x 2, (39) where he ime-dependen diffusion coefficien is given by D x = E, (40) wih he diffusion energy E being given by (16). Averaging effecs of he random velociy, b Ψ, upon he drif coefficien bring abou he ime-dependen effecive velociy v eff x, = 1 dv x dx + b Ψ. (41) For hermal sysems a hermodynamic equilibrium in which (18) is valid, he diffusion consan (40) becomes he Einsein relaion 9

10 D x = k BT. (42) Accordingly, he non-markovian Fokker Planck equaion (39) in he presence of hermal flucuaions reads f x, = x 1 dv x dx 2k B T Ψ f x, + k BT I 2 f x, x 2. (43) For Ψ = 0 and I = 1, he Fokker Planck equaion (43) yields he equaion of moion f x, = 1 x dv(x) dx f x, + k BT 2 f x, x 2, (44) early found ou by Smoluchowski [8] and widely invesigaed in he lieraure [9 14]. The Smoluchowski equaion (44) is defined for Markovian correlaions and no averaging effecs in conras o our Fokker Planck equaion (43) which akes ino accoun non-markovian effecs in view of he ime-dependen funcion I as well as averaging effecs presen in he drif coefficien. Again, our accoun of he Einsein Langevin sochasic approach presened above has poined ou ha he main upsho of Einsein he Founding Faher of Brownian moion heory ress on he fac ha his diffusion coefficien (42) is a consequence of he conservaion of energy (43) for hermal open sysems a hermodynamic equilibrium. I is worh recalling ha he Einsein relaion (42) has been aained wihou specifying ab iniio he form of he auocorrelaion funcion of he Langevin force, L()L( ) = 2 2 k BT Ψ Ψ = 2 2 D x Ψ Ψ, as well as is average value, i.e., L() = ± 2 k BT Ψ() = ± 2D x Ψ(). 10

11 3.1 Non-Markovian Brownian Moion of a Free Paricle As far as he non-inerial Brownian moion of a free paricle is concerned, our non- Markovian Smoluchowski equaion (43) wih (20) a poin x reads f x, = 2k B T Ψ f x, x + k BT 1 e c 2 f x, x 2. (45) Saring from he deerminisic iniial condiion f x, = 0 = δ x, (46) characerized by E 0 = 0 and Ψ 0 = 0, we obain he following ime-soluion o (45) f x, = 4πA e 4A, (47) x 2 in erms of he hermal posiion and he funcion x = x 2k B T Ψ d, (48) A = k B T I d = k B T + c e c. (49) Besides reducing o (46) a = 0 (along wih c = 0), soluion (47) yields and X = 0, (50) X 2 = 2k BT + c e c, (51) where he sochasic posiion X = X corresponding o (48) is given by X = X 2k B T Ψ d. Accordingly, he mean square displacemen, X = X 2 X 2, reads X = X = 2k B T + c e c. (52) 11

12 We noice ha averaging effecs are unobservable, for hey do have no influence upon he physically measurable quaniy (52), albei hey can bring abou a shif in he posiion (48). By conras, non-markovian effecs accoun for enhancing he mean square displacemen (52) of a free Brownian paricle. by For very shor imes c, quaniy (52) reduces o a consan value given X = 2k B T c (53) which is differeniable, i.e., d X/d = 0. On he oher hand, in he Markovian limi, c 0, quaniy (52 reduces o he Einsein s renowned upsho X = 2k B T. (54) ha is non-differeniable a = 0, i.e., d X() d =0 = k B T 2 =0. (55) Hence, i is claimed ha here is no concep of velociy of a Brownian paricle in he srong fricion regime [5,6]. In fac, he physically embarrassing oucome (55) is a consequence of neglecing non-markovian feaures in (52). 12

13 4 Concluding Remarks In his paper we have examined he Brownian moion of a free paricle immersed in a hermal reservoir reckoning wih non-markovian effecs. In Sec. 2 we have shown ha he mean square momenum (32) is a differeniable funcion in he presence of inerial force provided ha non-markovian effecs increase he value of (32). In he absence of inerial force in Sec. 3 i has been prediced ha non- Markovian effecs enhance he mean square displacemen (52), hereby assuring he mahemaical propery of differeniabiliy of his physically observable quaniy. I is worh poin ou ha our chief resuls have been obained wihou making use of he generalized Langevin equaion m d2 X d 2 = dv(x) dx β( ) 0 dx( ) d + L d pu forward by Mori [15] on he basis of a close relaionship beween memory effecs ingrained in he fricion kernel β and non-markovian effecs (colored noise) showing up in he auocorrelaion funcion L L( ), given by L L( ) = D β. By conras, our approach has prediced ha non-markovian effecs independen of memory effecs can be physically measured for a free Brownian paricle immersed in a hea bah by means of he mean square displacemen in he absence of inerial force as well as he mean square momenum in he presence of he inerial force. Surprisingly, his feaure sanding ou in he Einsein Langevin framework has been overlooked in he cenenary lieraure abou Brownian moion [1 20]. 13

14 Appendix A: Generalized Fokker Planck Equaions Le us consider he sochasic differenial equaion dz d = 1 dv(z) + aψ. (A1) dz For Z = P, V(P) = 2 P 2 /2m, and a = b Eq. (A1) reduces o he Langevin sochasic equaion (11), whereas for Z = X, V = V(X), and a = b we obain he Langevin equaion (44). Equaion (A1) gives rise o he Kolmogorov equaion [7,11,17,18] f z, = Kf z,, A2 where he Kolmogorovian operaor K acs upon he probabiliy disribuion funcion f z, according o Kf z, = k=1 1 k k! k z k A k z, f z,, A3 he coefficiens A k z, being given by A k z, = lim ε 0 Z k ε, (A4) where he average values, Z k, are o be calculaed abou he sharp values z from he probabiliy disribuion funcion F ZΨ z, ψ, = δ z z F Ψ ψ,. (A5) According o he Pawula heorem [18], if he coefficiens A k z, in (A4) are finie for every k and if A k z, = 0 for some even k, hen A k z, = 0 for all k 3, hereby assuring he posiiviy of he probabiliy densiy funcion f(z, ). So, if z 2 z 3 1 ~0 such ha z 2 z 4 1 = 0, i follows hen ha A k z, = 0, k 3, where z 2 = z + ε and z 1 = z. Accordingly, he Kolmogorov equaion (A2) can be approximaed by he Fokker Planck equaion f z, 2 = z A 1 z, f z, z 2 A 2 z, f z,, A6 where he drif coefficien is given by A 1 z, = lim ε 0 Z ε = 1 dv + a Ψ() dz (A7) and he diffusion coefficien reads 14

15 Z 2 A 2 z, = lim ε 0 ε = a 2 1 lim ε 0 ε +ε Ψ Ψ d d, (A8) wih lim ε 0 1 ε +ε Ψ( ) d = Ψ() (A9) and lim ε 0 +ε Ψ d = 0. (A10) To evaluae he coefficiens (A7) and (A8) we have used (A1) in he form Z = Z + ε Z = ε dv dz + a +ε Ψ d. (A11) For z= p, V(p) = 2 p 2 /2m, and a = b he Fokker Planck equaion (A6) reduces o he Rayleigh equaion (13), whereas for z= x, V = V(X), and a = b (A6) leads o he Smoluchowski equaion (45). 15

16 Appendix B: The Time-dependen Diffusion Energy The ime-dependen diffusion energy E = E I (B1) in he Fokker Planck equaions (13) and (45) presens he correlaional funcion 1 I = lim ε 0 ε +ε Ψ Ψ d d. (B2) given by On he condiion ha he auocorrelaion funcion, Ψ( )Ψ( ), can be Ψ( )Ψ( ) = 1 e + 2 c δ, (B3) where c is he correlaion ime of Ψ() a imes and, i follows ha (B2) becomes I = 1 e c, (B4) reducing o I = 1 in he seady regime. The auocorrelaion funcion (B3) defines a colored noise which in he Markovian limi, c 0, changes ino he so-called whie noise Ψ( )Ψ( ) = δ, (B6) meaning ha he sochasic funcion Ψ() is dela-correlaed [16,19]. I has been argued ha he Markov propery (B6) is a highly idealized feaure [19], because he physical ineracion beween he Brownian paricle and he hermal bah always comes abou for a finie correlaion ime. By he same oken, a decade ago van Kampen has laconically saed: Non-Markov is he rule, Markov is he excepion 20]. Hence, our auo-correlaion funcion (B3) seems o be a more realisic feaure of he Langevin force. 16

17 References 1. Langevin, P.: Sur la héorie du mouvemen brownien, C. R. Acad. Sci. (Paris) 146, (1908) 2. Wang, M. C., Uhlenbeck, G. E.: On he heory of he Brownian moion II, Rev. Mod. Phys. 17, (1945) 3. Ornsein, L. S.: On he Brownian moion, Proc. Roy. Acad. Amserdam 21, (1919); Uhlenbeck, G. E., Ornsein, L. S.: On he heory of he Brownian moion, Phys. Rev. 36, (1930) 4. Einsein, A., Über die von der molekularkineishen Theorie der Wärme gefordee Bewegung von in ruhenden Flüssigkeien suspendieren Teilchen, Ann. Phys. 17, (1905) 5. Doob, J. L., The Brownian moion and sochasic equaions, Ann. Mah. 43, (1942) 6. Coffey, W. T., Kalmykov, Y. P., Waldron, J. T.: The Langevin Equaion: wih Applicaions o Sochasic Problems in Physics, Chemisry and Elecrical Engineering, 2nd edn.. World Scienific, Singapore (2004) 7. Kolmogorov, A.: Über die analyischen Mehoden in der Wahrscheinlichkeisrechnung, Mah. Ann. 104, (1931) 8. Smoluchowski, M. von: Über Brown sche molekular Bewegung uner Einwirkung äussere Kräfe und deren Zusammenhang mi der verallgemeineren Difusionsgleichung, Ann. Phys. 48, (1915) 9. Chandrasekhar, S.: Sochasic problems in physics and asronomy, Rev. Mod. Phys. 15, 1 89 (1943) 10. Kampen, N. G. van: Sochasic Processes in Physics and Chemisry, 3rd edn. Elsevier, Amserdam (2007) 11. Risken, H.: The Fokker Planck Equaion: Mehods of Soluion and Applicaions, 2nd ed. Springer, Berlin (1989) 12. Gardiner, C. W.: Handbook of Sochasic Mehods: for Physics, Chemisry, and he Naural Sciences, 3rd ed. Springer, Berlin (2004) 13. Mazo, R. M.: Brownian Moion: Flucuaions, Dynamics and Applicaions. Oxford Universiy Press, New York (2002) 17

18 14. Nelson, E.: Dynamical heories of Brownian moion. Princeon Universiy Press (1967) 15. Mori, H.: Transpor, collecive moion, and Brownian moion, Progr. Theor. Phys. 33, Luczka, J.: Non-Markovian sochasic processes: Colored noise. Chaos 15, (2005) 17. Sraonovich, R. L.: Topics in he Theory of Random Noise, Vol. 1. Gordon and Breach, New York (1963) 18. Pawula, F.: Approximaion of he linear Bolzmann equaion by he Fokker Planck equaion, Phys. Rev. 162, (1967) 19. Hänggi, P., Jung, P.: Colored noise in dynamical sysems. Adv. Chem. Phys. 89, (1995) 20. van Kampen, N. G.: Remarks on non-markov processes, Braz. J. Phys. 28 (2) (1998). 18

Major Concepts. Brownian Motion & More. Chemical Kinetics Master equation & Detailed Balance Relaxation rate & Inverse Phenomenological Rate

Major Concepts. Brownian Motion & More. Chemical Kinetics Master equation & Detailed Balance Relaxation rate & Inverse Phenomenological Rate Major Conceps Brownian Moion & More Langevin Equaion Model for a agged subsysem in a solven Harmonic bah wih emperaure, T Fricion & Correlaed forces (FDR) Markovian/Ohmic vs. Memory Fokker-Planck Equaion

More information

Physics 127b: Statistical Mechanics. Fokker-Planck Equation. Time Evolution

Physics 127b: Statistical Mechanics. Fokker-Planck Equation. Time Evolution Physics 7b: Saisical Mechanics Fokker-Planck Equaion The Langevin equaion approach o he evoluion of he velociy disribuion for he Brownian paricle migh leave you uncomforable. A more formal reamen of his

More information

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle Chaper 2 Newonian Mechanics Single Paricle In his Chaper we will review wha Newon s laws of mechanics ell us abou he moion of a single paricle. Newon s laws are only valid in suiable reference frames,

More information

THE MYSTERY OF STOCHASTIC MECHANICS. Edward Nelson Department of Mathematics Princeton University

THE MYSTERY OF STOCHASTIC MECHANICS. Edward Nelson Department of Mathematics Princeton University THE MYSTERY OF STOCHASTIC MECHANICS Edward Nelson Deparmen of Mahemaics Princeon Universiy 1 Classical Hamilon-Jacobi heory N paricles of various masses on a Euclidean space. Incorporae he masses in he

More information

ψ(t) = V x (0)V x (t)

ψ(t) = V x (0)V x (t) .93 Home Work Se No. (Professor Sow-Hsin Chen Spring Term 5. Due March 7, 5. This problem concerns calculaions of analyical expressions for he self-inermediae scaering funcion (ISF of he es paricle in

More information

Lecture 14. The term Brownian motion derives its name from the botanist Robert Brown whom, in 1828, made careful

Lecture 14. The term Brownian motion derives its name from the botanist Robert Brown whom, in 1828, made careful Lecure 4. Brownian moion. Einsein-Smoluhowski heory of he Brownian moion. Langevin heory of he Brownian moion Approach o equilibrium: Foker-Planck equaion. The flucuaion-dissipaion heorem. The erm Brownian

More information

Stochastic Processes. A. Bassi. RMP 85, April-June Appendix

Stochastic Processes. A. Bassi. RMP 85, April-June Appendix Sochasic Processes A. Bassi RMP 85, April-June 213 - Appendix The bes known example of a sochasic process is Brownian moion : random moion of small paricles suspended in a liquid, under he influence of

More information

where the coordinate X (t) describes the system motion. X has its origin at the system static equilibrium position (SEP).

where the coordinate X (t) describes the system motion. X has its origin at the system static equilibrium position (SEP). Appendix A: Conservaion of Mechanical Energy = Conservaion of Linear Momenum Consider he moion of a nd order mechanical sysem comprised of he fundamenal mechanical elemens: ineria or mass (M), siffness

More information

The expectation value of the field operator.

The expectation value of the field operator. The expecaion value of he field operaor. Dan Solomon Universiy of Illinois Chicago, IL dsolom@uic.edu June, 04 Absrac. Much of he mahemaical developmen of quanum field heory has been in suppor of deermining

More information

Some Basic Information about M-S-D Systems

Some Basic Information about M-S-D Systems Some Basic Informaion abou M-S-D Sysems 1 Inroducion We wan o give some summary of he facs concerning unforced (homogeneous) and forced (non-homogeneous) models for linear oscillaors governed by second-order,

More information

GEM4 Summer School OpenCourseWare

GEM4 Summer School OpenCourseWare GEM4 Summer School OpenCourseWare hp://gem4.educommons.ne/ hp://www.gem4.org/ Lecure: Thermal Forces and Brownian Moion by Ju Li. Given Augus 11, 2006 during he GEM4 session a MIT in Cambridge, MA. Please

More information

Brownian motion of molecules: the classical theory

Brownian motion of molecules: the classical theory Ann. Univ. Sofia, Fac. Chem. 88 (1) (1995) 57 66 [arxiv 1005.1490] rownian moion of molecules: he classical heory Roumen Tsekov Deparmen of Physical Chemisry, Universiy of Sofia, 1164 Sofia, ulgaria A

More information

An Introduction to Malliavin calculus and its applications

An Introduction to Malliavin calculus and its applications An Inroducion o Malliavin calculus and is applicaions Lecure 5: Smoohness of he densiy and Hörmander s heorem David Nualar Deparmen of Mahemaics Kansas Universiy Universiy of Wyoming Summer School 214

More information

7 The Itô/Stratonovich dilemma

7 The Itô/Stratonovich dilemma 7 The Iô/Sraonovich dilemma The dilemma: wha does he idealizaion of dela-funcion-correlaed noise mean? ẋ = f(x) + g(x)η() η()η( ) = κδ( ). (1) Previously, we argued by a limiing procedure: aking noise

More information

Structural Dynamics and Earthquake Engineering

Structural Dynamics and Earthquake Engineering Srucural Dynamics and Earhquae Engineering Course 1 Inroducion. Single degree of freedom sysems: Equaions of moion, problem saemen, soluion mehods. Course noes are available for download a hp://www.c.up.ro/users/aurelsraan/

More information

Nature Neuroscience: doi: /nn Supplementary Figure 1. Spike-count autocorrelations in time.

Nature Neuroscience: doi: /nn Supplementary Figure 1. Spike-count autocorrelations in time. Supplemenary Figure 1 Spike-coun auocorrelaions in ime. Normalized auocorrelaion marices are shown for each area in a daase. The marix shows he mean correlaion of he spike coun in each ime bin wih he spike

More information

2.3 SCHRÖDINGER AND HEISENBERG REPRESENTATIONS

2.3 SCHRÖDINGER AND HEISENBERG REPRESENTATIONS Andrei Tokmakoff, MIT Deparmen of Chemisry, 2/22/2007 2-17 2.3 SCHRÖDINGER AND HEISENBERG REPRESENTATIONS The mahemaical formulaion of he dynamics of a quanum sysem is no unique. So far we have described

More information

Lecture #31, 32: The Ornstein-Uhlenbeck Process as a Model of Volatility

Lecture #31, 32: The Ornstein-Uhlenbeck Process as a Model of Volatility Saisics 441 (Fall 214) November 19, 21, 214 Prof Michael Kozdron Lecure #31, 32: The Ornsein-Uhlenbeck Process as a Model of Volailiy The Ornsein-Uhlenbeck process is a di usion process ha was inroduced

More information

Electrical Circuits. 1. Circuit Laws. Tools Used in Lab 13 Series Circuits Damped Vibrations: Energy Van der Pol Circuit

Electrical Circuits. 1. Circuit Laws. Tools Used in Lab 13 Series Circuits Damped Vibrations: Energy Van der Pol Circuit V() R L C 513 Elecrical Circuis Tools Used in Lab 13 Series Circuis Damped Vibraions: Energy Van der Pol Circui A series circui wih an inducor, resisor, and capacior can be represened by Lq + Rq + 1, a

More information

Failure of the work-hamiltonian connection for free energy calculations. Abstract

Failure of the work-hamiltonian connection for free energy calculations. Abstract Failure of he work-hamilonian connecion for free energy calculaions Jose M. G. Vilar 1 and J. Miguel Rubi 1 Compuaional Biology Program, Memorial Sloan-Keering Cancer Cener, 175 York Avenue, New York,

More information

arxiv:cond-mat/ May 2002

arxiv:cond-mat/ May 2002 -- uadrupolar Glass Sae in para-hydrogen and orho-deuerium under pressure. T.I.Schelkacheva. arxiv:cond-ma/5538 6 May Insiue for High Pressure Physics, Russian Academy of Sciences, Troisk 49, Moscow Region,

More information

R t. C t P t. + u t. C t = αp t + βr t + v t. + β + w t

R t. C t P t. + u t. C t = αp t + βr t + v t. + β + w t Exercise 7 C P = α + β R P + u C = αp + βr + v (a) (b) C R = α P R + β + w (c) Assumpions abou he disurbances u, v, w : Classical assumions on he disurbance of one of he equaions, eg. on (b): E(v v s P,

More information

Dynamic Analysis of Damped Driven Pendulum using Laplace Transform Method

Dynamic Analysis of Damped Driven Pendulum using Laplace Transform Method , ISSN 0974-570X (Online), ISSN 0974-578 (Prin), Vol. 6; Issue No. 3; Year 05, Copyrigh 05 by CESER PUBLICATIONS Dynamic Analysis of Damped Driven Pendulum using Laplace Transform Mehod M.C. Agarana and

More information

14 Autoregressive Moving Average Models

14 Autoregressive Moving Average Models 14 Auoregressive Moving Average Models In his chaper an imporan parameric family of saionary ime series is inroduced, he family of he auoregressive moving average, or ARMA, processes. For a large class

More information

Elements of Stochastic Processes Lecture II Hamid R. Rabiee

Elements of Stochastic Processes Lecture II Hamid R. Rabiee Sochasic Processes Elemens of Sochasic Processes Lecure II Hamid R. Rabiee Overview Reading Assignmen Chaper 9 of exbook Furher Resources MIT Open Course Ware S. Karlin and H. M. Taylor, A Firs Course

More information

On a Fractional Stochastic Landau-Ginzburg Equation

On a Fractional Stochastic Landau-Ginzburg Equation Applied Mahemaical Sciences, Vol. 4, 1, no. 7, 317-35 On a Fracional Sochasic Landau-Ginzburg Equaion Nguyen Tien Dung Deparmen of Mahemaics, FPT Universiy 15B Pham Hung Sree, Hanoi, Vienam dungn@fp.edu.vn

More information

CHAPTER 2 Signals And Spectra

CHAPTER 2 Signals And Spectra CHAPER Signals And Specra Properies of Signals and Noise In communicaion sysems he received waveform is usually caegorized ino he desired par conaining he informaion, and he undesired par. he desired par

More information

2. Nonlinear Conservation Law Equations

2. Nonlinear Conservation Law Equations . Nonlinear Conservaion Law Equaions One of he clear lessons learned over recen years in sudying nonlinear parial differenial equaions is ha i is generally no wise o ry o aack a general class of nonlinear

More information

Stochastic Model for Cancer Cell Growth through Single Forward Mutation

Stochastic Model for Cancer Cell Growth through Single Forward Mutation Journal of Modern Applied Saisical Mehods Volume 16 Issue 1 Aricle 31 5-1-2017 Sochasic Model for Cancer Cell Growh hrough Single Forward Muaion Jayabharahiraj Jayabalan Pondicherry Universiy, jayabharahi8@gmail.com

More information

Ordinary Differential Equations

Ordinary Differential Equations Lecure 22 Ordinary Differenial Equaions Course Coordinaor: Dr. Suresh A. Karha, Associae Professor, Deparmen of Civil Engineering, IIT Guwahai. In naure, mos of he phenomena ha can be mahemaically described

More information

A Note on Fractional Electrodynamics. Abstract

A Note on Fractional Electrodynamics. Abstract Commun Nonlinear Sci Numer Simula 8 (3 589 593 A Noe on Fracional lecrodynamics Hosein Nasrolahpour Absrac We invesigae he ime evoluion o he racional elecromagneic waves by using he ime racional Maxwell's

More information

Class Meeting # 10: Introduction to the Wave Equation

Class Meeting # 10: Introduction to the Wave Equation MATH 8.5 COURSE NOTES - CLASS MEETING # 0 8.5 Inroducion o PDEs, Fall 0 Professor: Jared Speck Class Meeing # 0: Inroducion o he Wave Equaion. Wha is he wave equaion? The sandard wave equaion for a funcion

More information

Diffusion & Viscosity: Navier-Stokes Equation

Diffusion & Viscosity: Navier-Stokes Equation 4/5/018 Diffusion & Viscosiy: Navier-Sokes Equaion 1 4/5/018 Diffusion Equaion Imagine a quaniy C(x,) represening a local propery in a fluid, eg. - hermal energy densiy - concenraion of a polluan - densiy

More information

1. VELOCITY AND ACCELERATION

1. VELOCITY AND ACCELERATION 1. VELOCITY AND ACCELERATION 1.1 Kinemaics Equaions s = u + 1 a and s = v 1 a s = 1 (u + v) v = u + as 1. Displacemen-Time Graph Gradien = speed 1.3 Velociy-Time Graph Gradien = acceleraion Area under

More information

Excel-Based Solution Method For The Optimal Policy Of The Hadley And Whittin s Exact Model With Arma Demand

Excel-Based Solution Method For The Optimal Policy Of The Hadley And Whittin s Exact Model With Arma Demand Excel-Based Soluion Mehod For The Opimal Policy Of The Hadley And Whiin s Exac Model Wih Arma Demand Kal Nami School of Business and Economics Winson Salem Sae Universiy Winson Salem, NC 27110 Phone: (336)750-2338

More information

Cash Flow Valuation Mode Lin Discrete Time

Cash Flow Valuation Mode Lin Discrete Time IOSR Journal of Mahemaics (IOSR-JM) e-issn: 2278-5728,p-ISSN: 2319-765X, 6, Issue 6 (May. - Jun. 2013), PP 35-41 Cash Flow Valuaion Mode Lin Discree Time Olayiwola. M. A. and Oni, N. O. Deparmen of Mahemaics

More information

Undetermined coefficients for local fractional differential equations

Undetermined coefficients for local fractional differential equations Available online a www.isr-publicaions.com/jmcs J. Mah. Compuer Sci. 16 (2016), 140 146 Research Aricle Undeermined coefficiens for local fracional differenial equaions Roshdi Khalil a,, Mohammed Al Horani

More information

23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes

23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes Represening Periodic Funcions by Fourier Series 3. Inroducion In his Secion we show how a periodic funcion can be expressed as a series of sines and cosines. We begin by obaining some sandard inegrals

More information

Langevin-Vladimirsky approach to Brownian motion with memory

Langevin-Vladimirsky approach to Brownian motion with memory The Open-Access Journal for he asic Principles of Diffusion Theory, Experimen and Applicaion Langevin-Vladimirsky approach o rownian moion wih memory Jana Tohova, Vladimir Lisy Deparmen of Physics, Technical

More information

The Maxwell Equations, the Lorentz Field and the Electromagnetic Nanofield with Regard to the Question of Relativity

The Maxwell Equations, the Lorentz Field and the Electromagnetic Nanofield with Regard to the Question of Relativity The Maxwell Equaions, he Lorenz Field and he Elecromagneic Nanofield wih Regard o he Quesion of Relaiviy Daniele Sasso * Absrac We discuss he Elecromagneic Theory in some main respecs and specifically

More information

Sub Module 2.6. Measurement of transient temperature

Sub Module 2.6. Measurement of transient temperature Mechanical Measuremens Prof. S.P.Venkaeshan Sub Module 2.6 Measuremen of ransien emperaure Many processes of engineering relevance involve variaions wih respec o ime. The sysem properies like emperaure,

More information

Differential Equations

Differential Equations Mah 21 (Fall 29) Differenial Equaions Soluion #3 1. Find he paricular soluion of he following differenial equaion by variaion of parameer (a) y + y = csc (b) 2 y + y y = ln, > Soluion: (a) The corresponding

More information

THE EFFECT OF SUCTION AND INJECTION ON UNSTEADY COUETTE FLOW WITH VARIABLE PROPERTIES

THE EFFECT OF SUCTION AND INJECTION ON UNSTEADY COUETTE FLOW WITH VARIABLE PROPERTIES Kragujevac J. Sci. 3 () 7-4. UDC 53.5:536. 4 THE EFFECT OF SUCTION AND INJECTION ON UNSTEADY COUETTE FLOW WITH VARIABLE PROPERTIES Hazem A. Aia Dep. of Mahemaics, College of Science,King Saud Universiy

More information

5.2. The Natural Logarithm. Solution

5.2. The Natural Logarithm. Solution 5.2 The Naural Logarihm The number e is an irraional number, similar in naure o π. Is non-erminaing, non-repeaing value is e 2.718 281 828 59. Like π, e also occurs frequenly in naural phenomena. In fac,

More information

CH.5. BALANCE PRINCIPLES. Continuum Mechanics Course (MMC) - ETSECCPB - UPC

CH.5. BALANCE PRINCIPLES. Continuum Mechanics Course (MMC) - ETSECCPB - UPC CH.5. BALANCE PRINCIPLES Coninuum Mechanics Course (MMC) - ETSECCPB - UPC Overview Balance Principles Convecive Flux or Flux by Mass Transpor Local and Maerial Derivaive of a olume Inegral Conservaion

More information

HEAT CONDUCTION IN TECHNOLOGICAL PROCESSES

HEAT CONDUCTION IN TECHNOLOGICAL PROCESSES Journal of Engineering Physics and Thermophysics, Vol. 84, No. 6, November, HEAT CONDUCTION IN TECHNOLOGICAL PROCESSES PROPAGATION OF HEAT IN THE SPACE AROUND A CYLINDRICAL SURFACE AS A NON-MARKOVIAN RANDOM

More information

Chapter 15: Phenomena. Chapter 15 Chemical Kinetics. Reaction Rates. Reaction Rates R P. Reaction Rates. Rate Laws

Chapter 15: Phenomena. Chapter 15 Chemical Kinetics. Reaction Rates. Reaction Rates R P. Reaction Rates. Rate Laws Chaper 5: Phenomena Phenomena: The reacion (aq) + B(aq) C(aq) was sudied a wo differen emperaures (98 K and 35 K). For each emperaure he reacion was sared by puing differen concenraions of he 3 species

More information

Lecture 4 Kinetics of a particle Part 3: Impulse and Momentum

Lecture 4 Kinetics of a particle Part 3: Impulse and Momentum MEE Engineering Mechanics II Lecure 4 Lecure 4 Kineics of a paricle Par 3: Impulse and Momenum Linear impulse and momenum Saring from he equaion of moion for a paricle of mass m which is subjeced o an

More information

dt = C exp (3 ln t 4 ). t 4 W = C exp ( ln(4 t) 3) = C(4 t) 3.

dt = C exp (3 ln t 4 ). t 4 W = C exp ( ln(4 t) 3) = C(4 t) 3. Mah Rahman Exam Review Soluions () Consider he IVP: ( 4)y 3y + 4y = ; y(3) = 0, y (3) =. (a) Please deermine he longes inerval for which he IVP is guaraneed o have a unique soluion. Soluion: The disconinuiies

More information

CONTRIBUTION TO IMPULSIVE EQUATIONS

CONTRIBUTION TO IMPULSIVE EQUATIONS European Scienific Journal Sepember 214 /SPECIAL/ ediion Vol.3 ISSN: 1857 7881 (Prin) e - ISSN 1857-7431 CONTRIBUTION TO IMPULSIVE EQUATIONS Berrabah Faima Zohra, MA Universiy of sidi bel abbes/ Algeria

More information

( ) = b n ( t) n " (2.111) or a system with many states to be considered, solving these equations isn t. = k U I ( t,t 0 )! ( t 0 ) (2.

( ) = b n ( t) n  (2.111) or a system with many states to be considered, solving these equations isn t. = k U I ( t,t 0 )! ( t 0 ) (2. Andrei Tokmakoff, MIT Deparmen of Chemisry, 3/14/007-6.4 PERTURBATION THEORY Given a Hamilonian H = H 0 + V where we know he eigenkes for H 0 : H 0 n = E n n, we can calculae he evoluion of he wavefuncion

More information

Vehicle Arrival Models : Headway

Vehicle Arrival Models : Headway Chaper 12 Vehicle Arrival Models : Headway 12.1 Inroducion Modelling arrival of vehicle a secion of road is an imporan sep in raffic flow modelling. I has imporan applicaion in raffic flow simulaion where

More information

( ) = Q 0. ( ) R = R dq. ( t) = I t

( ) = Q 0. ( ) R = R dq. ( t) = I t ircuis onceps The addiion of a simple capacior o a circui of resisors allows wo relaed phenomena o occur The observaion ha he ime-dependence of a complex waveform is alered by he circui is referred o as

More information

Second quantization and gauge invariance.

Second quantization and gauge invariance. 1 Second quanizaion and gauge invariance. Dan Solomon Rauland-Borg Corporaion Moun Prospec, IL Email: dsolom@uic.edu June, 1. Absrac. I is well known ha he single paricle Dirac equaion is gauge invarian.

More information

STRUCTURAL CHANGE IN TIME SERIES OF THE EXCHANGE RATES BETWEEN YEN-DOLLAR AND YEN-EURO IN

STRUCTURAL CHANGE IN TIME SERIES OF THE EXCHANGE RATES BETWEEN YEN-DOLLAR AND YEN-EURO IN Inernaional Journal of Applied Economerics and Quaniaive Sudies. Vol.1-3(004) STRUCTURAL CHANGE IN TIME SERIES OF THE EXCHANGE RATES BETWEEN YEN-DOLLAR AND YEN-EURO IN 001-004 OBARA, Takashi * Absrac The

More information

Module 3: The Damped Oscillator-II Lecture 3: The Damped Oscillator-II

Module 3: The Damped Oscillator-II Lecture 3: The Damped Oscillator-II Module 3: The Damped Oscillaor-II Lecure 3: The Damped Oscillaor-II 3. Over-damped Oscillaions. This refers o he siuaion where β > ω (3.) The wo roos are and α = β + α 2 = β β 2 ω 2 = (3.2) β 2 ω 2 = 2

More information

Golden ratio autocorrelation function and the exponential decay

Golden ratio autocorrelation function and the exponential decay Fluc. Noise Le. 4 (5) 553 [arxiv 4.45] Golden raio auocorrelaion funcion and he exponenial decay Roumen Tsekov Deparmen of Physical Chemisry, Universiy of Sofia, 64 Sofia, Bulgaria An auocorrelaion funcion

More information

t 2 B F x,t n dsdt t u x,t dxdt

t 2 B F x,t n dsdt t u x,t dxdt Evoluion Equaions For 0, fixed, le U U0, where U denoes a bounded open se in R n.suppose ha U is filled wih a maerial in which a conaminan is being ranspored by various means including diffusion and convecion.

More information

Symmetry and Numerical Solutions for Systems of Non-linear Reaction Diffusion Equations

Symmetry and Numerical Solutions for Systems of Non-linear Reaction Diffusion Equations Symmery and Numerical Soluions for Sysems of Non-linear Reacion Diffusion Equaions Sanjeev Kumar* and Ravendra Singh Deparmen of Mahemaics, (Dr. B. R. Ambedkar niversiy, Agra), I. B. S. Khandari, Agra-8

More information

The Optimal Stopping Time for Selling an Asset When It Is Uncertain Whether the Price Process Is Increasing or Decreasing When the Horizon Is Infinite

The Optimal Stopping Time for Selling an Asset When It Is Uncertain Whether the Price Process Is Increasing or Decreasing When the Horizon Is Infinite American Journal of Operaions Research, 08, 8, 8-9 hp://wwwscirporg/journal/ajor ISSN Online: 60-8849 ISSN Prin: 60-8830 The Opimal Sopping Time for Selling an Asse When I Is Uncerain Wheher he Price Process

More information

Electrical and current self-induction

Electrical and current self-induction Elecrical and curren self-inducion F. F. Mende hp://fmnauka.narod.ru/works.hml mende_fedor@mail.ru Absrac The aricle considers he self-inducance of reacive elemens. Elecrical self-inducion To he laws of

More information

The Contradiction within Equations of Motion with Constant Acceleration

The Contradiction within Equations of Motion with Constant Acceleration The Conradicion wihin Equaions of Moion wih Consan Acceleraion Louai Hassan Elzein Basheir (Daed: July 7, 0 This paper is prepared o demonsrae he violaion of rules of mahemaics in he algebraic derivaion

More information

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still.

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still. Lecure - Kinemaics in One Dimension Displacemen, Velociy and Acceleraion Everyhing in he world is moving. Nohing says sill. Moion occurs a all scales of he universe, saring from he moion of elecrons in

More information

Chapter 3 Boundary Value Problem

Chapter 3 Boundary Value Problem Chaper 3 Boundary Value Problem A boundary value problem (BVP) is a problem, ypically an ODE or a PDE, which has values assigned on he physical boundary of he domain in which he problem is specified. Le

More information

Energy representation for nonequilibrium Brownian-like systems: Steady states and fluctuation relations

Energy representation for nonequilibrium Brownian-like systems: Steady states and fluctuation relations Energy represenaion for nonequilibrium Brownian-like sysems: Seady saes and flucuaion relaions Bohdan I. Lev 1, * and Alexei D. Kiselev 2,1, 1 M.M. Bogolyubov Insiue for Theoreical Physics, The NAS of

More information

Summary of shear rate kinematics (part 1)

Summary of shear rate kinematics (part 1) InroToMaFuncions.pdf 4 CM465 To proceed o beer-designed consiuive equaions, we need o know more abou maerial behavior, i.e. we need more maerial funcions o predic, and we need measuremens of hese maerial

More information

Bias in Conditional and Unconditional Fixed Effects Logit Estimation: a Correction * Tom Coupé

Bias in Conditional and Unconditional Fixed Effects Logit Estimation: a Correction * Tom Coupé Bias in Condiional and Uncondiional Fixed Effecs Logi Esimaion: a Correcion * Tom Coupé Economics Educaion and Research Consorium, Naional Universiy of Kyiv Mohyla Academy Address: Vul Voloska 10, 04070

More information

Chapter 2. First Order Scalar Equations

Chapter 2. First Order Scalar Equations Chaper. Firs Order Scalar Equaions We sar our sudy of differenial equaions in he same way he pioneers in his field did. We show paricular echniques o solve paricular ypes of firs order differenial equaions.

More information

Online Appendix to Solution Methods for Models with Rare Disasters

Online Appendix to Solution Methods for Models with Rare Disasters Online Appendix o Soluion Mehods for Models wih Rare Disasers Jesús Fernández-Villaverde and Oren Levinal In his Online Appendix, we presen he Euler condiions of he model, we develop he pricing Calvo block,

More information

Homework 10 (Stats 620, Winter 2017) Due Tuesday April 18, in class Questions are derived from problems in Stochastic Processes by S. Ross.

Homework 10 (Stats 620, Winter 2017) Due Tuesday April 18, in class Questions are derived from problems in Stochastic Processes by S. Ross. Homework (Sas 6, Winer 7 Due Tuesday April 8, in class Quesions are derived from problems in Sochasic Processes by S. Ross.. A sochasic process {X(, } is said o be saionary if X(,..., X( n has he same

More information

Most Probable Phase Portraits of Stochastic Differential Equations and Its Numerical Simulation

Most Probable Phase Portraits of Stochastic Differential Equations and Its Numerical Simulation Mos Probable Phase Porrais of Sochasic Differenial Equaions and Is Numerical Simulaion Bing Yang, Zhu Zeng and Ling Wang 3 School of Mahemaics and Saisics, Huazhong Universiy of Science and Technology,

More information

Linear Response Theory: The connection between QFT and experiments

Linear Response Theory: The connection between QFT and experiments Phys540.nb 39 3 Linear Response Theory: The connecion beween QFT and experimens 3.1. Basic conceps and ideas Q: How do we measure he conduciviy of a meal? A: we firs inroduce a weak elecric field E, and

More information

School and Workshop on Market Microstructure: Design, Efficiency and Statistical Regularities March 2011

School and Workshop on Market Microstructure: Design, Efficiency and Statistical Regularities March 2011 2229-12 School and Workshop on Marke Microsrucure: Design, Efficiency and Saisical Regulariies 21-25 March 2011 Some mahemaical properies of order book models Frederic ABERGEL Ecole Cenrale Paris Grande

More information

Non-equilibrium Green functions I

Non-equilibrium Green functions I Non-equilibrium Green funcions I Joachim Keller Lieraure: H. Haug, A.-P. Jauho, Quanum Kineics in Transpor and Opics of Semiconducors J. Rammer, H. Smih, Quanum field-heoreical mehod in ranspor heory of

More information

The motions of the celt on a horizontal plane with viscous friction

The motions of the celt on a horizontal plane with viscous friction The h Join Inernaional Conference on Mulibody Sysem Dynamics June 8, 18, Lisboa, Porugal The moions of he cel on a horizonal plane wih viscous fricion Maria A. Munisyna 1 1 Moscow Insiue of Physics and

More information

Echocardiography Project and Finite Fourier Series

Echocardiography Project and Finite Fourier Series Echocardiography Projec and Finie Fourier Series 1 U M An echocardiagram is a plo of how a porion of he hear moves as he funcion of ime over he one or more hearbea cycles If he hearbea repeas iself every

More information

Thermal Forces and Brownian Motion

Thermal Forces and Brownian Motion Theral Forces and Brownian Moion Ju Li GEM4 Suer School 006 Cell and Molecular Mechanics in BioMedicine Augus 7 18, 006, MIT, Cabridge, MA, USA Ouline Meaning of he Cenral Lii Theore Diffusion vs Langevin

More information

Lecture 9: Advanced DFT concepts: The Exchange-correlation functional and time-dependent DFT

Lecture 9: Advanced DFT concepts: The Exchange-correlation functional and time-dependent DFT Lecure 9: Advanced DFT conceps: The Exchange-correlaion funcional and ime-dependen DFT Marie Curie Tuorial Series: Modeling Biomolecules December 6-11, 2004 Mark Tuckerman Dep. of Chemisry and Couran Insiue

More information

Plasma Astrophysics Chapter 3: Kinetic Theory. Yosuke Mizuno Institute of Astronomy National Tsing-Hua University

Plasma Astrophysics Chapter 3: Kinetic Theory. Yosuke Mizuno Institute of Astronomy National Tsing-Hua University Plasma Asrophysics Chaper 3: Kineic Theory Yosuke Mizuno Insiue o Asronomy Naional Tsing-Hua Universiy Kineic Theory Single paricle descripion: enuous plasma wih srong exernal ields, imporan or gaining

More information

4.6 One Dimensional Kinematics and Integration

4.6 One Dimensional Kinematics and Integration 4.6 One Dimensional Kinemaics and Inegraion When he acceleraion a( of an objec is a non-consan funcion of ime, we would like o deermine he ime dependence of he posiion funcion x( and he x -componen of

More information

Bifurcation Analysis of a Stage-Structured Prey-Predator System with Discrete and Continuous Delays

Bifurcation Analysis of a Stage-Structured Prey-Predator System with Discrete and Continuous Delays Applied Mahemaics 4 59-64 hp://dx.doi.org/.46/am..4744 Published Online July (hp://www.scirp.org/ournal/am) Bifurcaion Analysis of a Sage-Srucured Prey-Predaor Sysem wih Discree and Coninuous Delays Shunyi

More information

Elementary Differential Equations and Boundary Value Problems

Elementary Differential Equations and Boundary Value Problems Elemenar Differenial Equaions and Boundar Value Problems Boce. & DiPrima 9 h Ediion Chaper 1: Inroducion 1006003 คณ ตศาสตร ว ศวกรรม 3 สาขาว ชาว ศวกรรมคอมพ วเตอร ป การศ กษา 1/2555 ผศ.ดร.อร ญญา ผศ.ดร.สมศ

More information

Vanishing Viscosity Method. There are another instructive and perhaps more natural discontinuous solutions of the conservation law

Vanishing Viscosity Method. There are another instructive and perhaps more natural discontinuous solutions of the conservation law Vanishing Viscosiy Mehod. There are anoher insrucive and perhaps more naural disconinuous soluions of he conservaion law (1 u +(q(u x 0, he so called vanishing viscosiy mehod. This mehod consiss in viewing

More information

Fractional Modified Special Relativity

Fractional Modified Special Relativity Absrac: Fracional Modified Special Relaiviy Hosein Nasrolahpour Deparmen of Physics, Faculy of Basic Sciences, Universiy of Mazandaran, P. O. Box 47416-95447, Babolsar, IRAN Hadaf Insiue of Higher Educaion,

More information

Module 2 F c i k c s la l w a s o s f dif di fusi s o i n

Module 2 F c i k c s la l w a s o s f dif di fusi s o i n Module Fick s laws of diffusion Fick s laws of diffusion and hin film soluion Adolf Fick (1855) proposed: d J α d d d J (mole/m s) flu (m /s) diffusion coefficien and (mole/m 3 ) concenraion of ions, aoms

More information

Math Week 14 April 16-20: sections first order systems of linear differential equations; 7.4 mass-spring systems.

Math Week 14 April 16-20: sections first order systems of linear differential equations; 7.4 mass-spring systems. Mah 2250-004 Week 4 April 6-20 secions 7.-7.3 firs order sysems of linear differenial equaions; 7.4 mass-spring sysems. Mon Apr 6 7.-7.2 Sysems of differenial equaions (7.), and he vecor Calculus we need

More information

Reading from Young & Freedman: For this topic, read sections 25.4 & 25.5, the introduction to chapter 26 and sections 26.1 to 26.2 & 26.4.

Reading from Young & Freedman: For this topic, read sections 25.4 & 25.5, the introduction to chapter 26 and sections 26.1 to 26.2 & 26.4. PHY1 Elecriciy Topic 7 (Lecures 1 & 11) Elecric Circuis n his opic, we will cover: 1) Elecromoive Force (EMF) ) Series and parallel resisor combinaions 3) Kirchhoff s rules for circuis 4) Time dependence

More information

Stability and Bifurcation in a Neural Network Model with Two Delays

Stability and Bifurcation in a Neural Network Model with Two Delays Inernaional Mahemaical Forum, Vol. 6, 11, no. 35, 175-1731 Sabiliy and Bifurcaion in a Neural Nework Model wih Two Delays GuangPing Hu and XiaoLing Li School of Mahemaics and Physics, Nanjing Universiy

More information

Unsteady Mass- Transfer Models

Unsteady Mass- Transfer Models See T&K Chaper 9 Unseady Mass- Transfer Models ChEn 6603 Wednesday, April 4, Ouline Conex for he discussion Soluion for ransien binary diffusion wih consan c, N. Soluion for mulicomponen diffusion wih

More information

Diebold, Chapter 7. Francis X. Diebold, Elements of Forecasting, 4th Edition (Mason, Ohio: Cengage Learning, 2006). Chapter 7. Characterizing Cycles

Diebold, Chapter 7. Francis X. Diebold, Elements of Forecasting, 4th Edition (Mason, Ohio: Cengage Learning, 2006). Chapter 7. Characterizing Cycles Diebold, Chaper 7 Francis X. Diebold, Elemens of Forecasing, 4h Ediion (Mason, Ohio: Cengage Learning, 006). Chaper 7. Characerizing Cycles Afer compleing his reading you should be able o: Define covariance

More information

Open loop vs Closed Loop. Example: Open Loop. Example: Feedforward Control. Advanced Control I

Open loop vs Closed Loop. Example: Open Loop. Example: Feedforward Control. Advanced Control I Open loop vs Closed Loop Advanced I Moor Command Movemen Overview Open Loop vs Closed Loop Some examples Useful Open Loop lers Dynamical sysems CPG (biologically inspired ), Force Fields Feedback conrol

More information

arxiv:math/ v1 [math.pr] 27 Jul 2006

arxiv:math/ v1 [math.pr] 27 Jul 2006 Sochasic Sokes drif wih ineria arxiv:mah/6777v1 [mah.pr] 27 Jul 26 By Kalvis M. Jansons Deparmen of Mahemaics, Universiy College London, Gower Sree, London WC1E 6BT, UK We consider boh he effec of paricle

More information

SZG Macro 2011 Lecture 3: Dynamic Programming. SZG macro 2011 lecture 3 1

SZG Macro 2011 Lecture 3: Dynamic Programming. SZG macro 2011 lecture 3 1 SZG Macro 2011 Lecure 3: Dynamic Programming SZG macro 2011 lecure 3 1 Background Our previous discussion of opimal consumpion over ime and of opimal capial accumulaion sugges sudying he general decision

More information

STOCHASTIC PROCESSES AND RANDOM FIELDS. K. Grill Institut für Statistik und Wahrscheinlichkeitstheorie, TU Wien, Austria

STOCHASTIC PROCESSES AND RANDOM FIELDS. K. Grill Institut für Statistik und Wahrscheinlichkeitstheorie, TU Wien, Austria STOCHASTIC PROCESSES AND RANDOM FIELDS K. Grill Insiu für Saisik und Wahrscheinlichkeisheorie, TU Wien, Ausria Keywords: Sochasic process, mean value funcion, covariance funcion, correlaion heory, Gaussian

More information

Week 1 Lecture 2 Problems 2, 5. What if something oscillates with no obvious spring? What is ω? (problem set problem)

Week 1 Lecture 2 Problems 2, 5. What if something oscillates with no obvious spring? What is ω? (problem set problem) Week 1 Lecure Problems, 5 Wha if somehing oscillaes wih no obvious spring? Wha is ω? (problem se problem) Sar wih Try and ge o SHM form E. Full beer can in lake, oscillaing F = m & = ge rearrange: F =

More information

Final Spring 2007

Final Spring 2007 .615 Final Spring 7 Overview The purpose of he final exam is o calculae he MHD β limi in a high-bea oroidal okamak agains he dangerous n = 1 exernal ballooning-kink mode. Effecively, his corresponds o

More information

Representation of Stochastic Process by Means of Stochastic Integrals

Representation of Stochastic Process by Means of Stochastic Integrals Inernaional Journal of Mahemaics Research. ISSN 0976-5840 Volume 5, Number 4 (2013), pp. 385-397 Inernaional Research Publicaion House hp://www.irphouse.com Represenaion of Sochasic Process by Means of

More information

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Simulaion-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Week Descripion Reading Maerial 2 Compuer Simulaion of Dynamic Models Finie Difference, coninuous saes, discree ime Simple Mehods Euler Trapezoid

More information

Navneet Saini, Mayank Goyal, Vishal Bansal (2013); Term Project AML310; Indian Institute of Technology Delhi

Navneet Saini, Mayank Goyal, Vishal Bansal (2013); Term Project AML310; Indian Institute of Technology Delhi Creep in Viscoelasic Subsances Numerical mehods o calculae he coefficiens of he Prony equaion using creep es daa and Herediary Inegrals Mehod Navnee Saini, Mayank Goyal, Vishal Bansal (23); Term Projec

More information

Correlated anomalous diffusion: Random walk and Langevin equation

Correlated anomalous diffusion: Random walk and Langevin equation JOURNAL OF MATHEMATICAL PHYSICS 51, 3332 21 Correlaed anomalous diffusion: Random walk and Langevin equaion Kiyoshi Sogo, 1,a Yoshiaki Kishikawa, 1 Shuhei Ohnishi, 2 Takenori Yamamoo, 2 Susumu Fujiwara,

More information