Inertial effects in the fractional translational diffusion of a Brownian particle in a double-well potential

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  • Inertial effects in the fractional translational diffusion of a Brownian particlein a double-well potential

    Yuri P. KalmykovLab. Mathmatiques et Physique des Systmes, Universit de Perpignan, 52, Avenue de Paul Alduy, 66860 Perpignan Cedex, France

    William T. CoffeyDepartment of Electronic and Electrical Engineering, Trinity College, Dublin 2, Ireland

    Sergey V. TitovInstitute of Radio Engineering and Electronics of the Russian Academy of Sciences, Vvedenskii Square 1, Fryazino,

    Moscow Region, 141190, Russian FederationReceived 31 October 2006; published 1 March 2007

    The anomalous translational diffusion including inertial effects of nonlinear Brownian oscillators in a doublewell potential Vx=ax2 /2+bx4 /4 is considered. An exact solution of the fractional Klein-Kramers Fokker-Planck equation is obtained allowing one to calculate via matrix continued fractions the positional autocor-relation function and dynamic susceptibility describing the position response to a small external field. Theresult is a generalization of the solution for the normal Brownian motion in a double well potential to fractionaldynamics giving rise to anomalous diffusion.

    DOI: 10.1103/PhysRevE.75.031101 PACS numbers: 05.40.a, 05.45.Df


    The Brownian motion in a field of force is of fundamentalimportance in problems involving relaxation and resonancephenomena in stochastic systems 1,2. An example is thetranslational diffusion of noninteracting Brownian particlesdue to Einstein 3 with a host of applications in physicschemistry, biology, etc. Einsteins theory relies on the diffu-sion limit of a discrete time random walk. Here the randomwalker or particle makes a jump of a fixed mean squarelength in a fixed time and the inertia is ignored so that thevelocity distribution instantaneously attains its equilibriumvalue. Thus the only random variable is the jump directionleading automatically via the central limit theorem in thelimit of a large sequence of jumps to the Wiener processdescribing the normal Brownian motion. The Einstein theoryof normal diffusion has been generalized to fractional diffu-sion see Refs. 46 for a review in order to describeanomalous relaxation and diffusion processes in disorderedcomplex systems such as amorphous polymers, glass form-ing liquids, etc.. These exhibit temporal nonlocal behaviorarising from energetic disorder causing obstacles or traps si-multaneously slowing down the motion of the walker andintroducing memory effects. Thus in one dimension the dy-namics of the particle are described by a fractional diffusionequation for the distribution function fx , t in configurationspace incorporating both a waiting time probability densityfunction governing the random time intervals between singlemicroscopic jumps of the particles and a jump length prob-ability distribution. The fractional diffusion equation stemsfrom the integral equation for a continuous time randomwalk CTRW introduced by Montroll and Weiss 7,8. In themost general case of the CTRW, the random walker mayjump an arbitrary length in arbitrary time. However, the jumplength and jump time random variables are not statisticallyindependent 79. In other words a given jump length ispenalized by a time cost, and vice versa.

    A simple case of the CTRW arises by assuming that thejump length and jump time random variables are decoupled.Such walks possessing a discrete hierarchy of time scales,without the same probability of occurrence, are known asfractal time random walks 5. They lead in the limit of alarge sequence of jump times and the non inertial limit to thefollowing fractional Fokker-Planck equation in configurationspace for a review see Refs. 5,7


    = 0Dt1K


    xfx,t +


    xVx,t . 1

    Here x specifies the position of the walker at time t,x, kT is the thermal energy, K= /kT is a gener-alized diffusion coefficient, is a generalized viscous dragcoefficient arising from the heat bath and Vx , t denotes theexternal potential. The operator 0Dt

    1 t 0Dt in Eq. 1 is

    given by the convolution the Riemann-Liouville fractionalintegral definition 6

    0Dtfx,t =


    0t fx,tdtt t1

    , 2

    where z is the gamma function. The physical meaning ofthe parameter is the order of the fractional derivative in thefractional differential equation describing the continuumlimit of a random walk with a chaotic set of waiting timesfractal time random walk. Values of in the range01 correspond to subdiffusion phenomena =1 cor-responds to normal diffusion.

    Since inertial effects are ignored the fractional Fokker-Planck equation in configuration space Eq. 1 only describesthe long time low frequency behavior of the ensemble ofparticles. In order to give a physically meaningful descrip-tion of the short time high frequency behavior, inertial ef-fects must be taken into account just as in normal diffusion

    PHYSICAL REVIEW E 75, 031101 2007

    1539-3755/2007/753/0311018 2007 The American Physical Society031101-1

  • 1,10. Inertial effects in the normal Brownian motion areincluded via the Fokker-Planck equation which for a sepa-rable and additive Hamiltonian is known as the Klein-Kramers equation for the distribution function of particlesWx , p , t in phase space x , p 1,10. In order to incorporatethese effects in anomalous translational diffusion, Metzler12 and Metzler and Klafter 13 have proposed a fractionalKlein-Kramers equation FKKE for the distribution functionW=Wx , x , t in phase space


    t= 0Dt

    11 xWx







    + x

    xW +kT




    , 3

    where = x20 /K1 has the meaning of the intertrapping timewaiting time between jumps, K1=kT / m is the diffusioncoefficient for normal diffusion, =1 /m is a friction coeffi-cient arising from the heat bath, and the angular bracketsdenote the equilibrium ensemble average. Equation 3 de-scribes a multiple trapping picture, whereby the tagged par-ticle executes translational Brownian motion. However, theparticle gets successively immobilized in traps whose meandistance apart is = kT /m, where is the mean time be-tween successive trapping events. The time intervals spent inthe traps are governed by the waiting time probability den-sity function wtAt1 01. The entire Klein-Kramers operator in the square brackets of Eq. 3 acts non-locally in time, i.e., drift friction and diffusion terms areunder the time convolution and are thus affected by thememory. However, a model based on a FKKE of the form ofEq. 3 provides a physically unacceptable picture of the be-havior of physical parameters such as the dynamic suscepti-bility in the high frequency limit in particular, it pre-dicts infinite integral absorption 10; see Sec. IV below.The root of this difficulty apparently being that in writing Eq.3, the convective derivative or Liouville term, in the under-lying Klein-Kramers equation, is operated upon by the frac-tional derivative. This problem does not arise in the FKKEproposed by Barkai and Silbey 15, where the fractionalderivative term acts solely on the dissipative part of the nor-mal Klein-Kramers operator see Eq. 3


    t= x








    x+ 0Dt

    11 x

    xW +kT



    x2 .4

    In order to justify a diffusion equation of the form of Eq. 4,Barkai and Silbey 15 consider a Brownian test particlemoving freely in one dimension and colliding elastically atrandom times with particles of the heat bath which are as-sumed to move much more rapidly than the test particle. Thetimes between collision events are assumed to be indepen-dent, identically distributed, random variables, implying thatthe number of collisions in a time interval 0, t is a renewalprocess. This is reasonable, according to Barkai and Silbey,when the bath particles thermalize rapidly and when the mo-tion of the test particle is slow. The FKKEs of Metzler andKlafter and Barkai and Silbey have recently been extended to

    the analogous fractional rotational diffusion models in a pe-riodic potential by Coffey et al. 10,16.

    As an example of application of the FKKE to a particularproblem, we shall now present a solution for the Barkai andSilbey kinetic model of anomalous diffusion of a particle in adouble-well potential, viz.,

    Vx = ax2/2 + bx4/4, 5

    where a and b are constants the Metzler and Klafter modelcan be treated in like manner. The model of normal diffu-sion in the potential given by Eq. 5 is almost invariablyused to describe the noise driven motion in bistable physicaland chemical systems. Examples are such diverse subjects assimple isometrization processes 1721, chemical reactionrate theory 2230, bistable nonlinear oscillators 3133,second order phase transitions 34, nuclear fission and fu-sion 35,36, stochastic resonance 37,38, etc. If the inertialeffects are taken into account, a large number of specializedsolutions exist mostly for particular parameters in the aboveproblem. For example, the normalized position correlationfunction and its spectra for small dumping were treated inRefs. 32,3941. Voigtlaender and Risken 42 calculatedeigenvalues and eigenfunctions of the Kramers Fokker-Planck equation for a Brownian particle in the double-wellpotential 5 and evaluated the Fourier transforms of the po-sition and velocity correlation functions. The method is asfollows. First the distribution function is expanded in Her-mite functions in the velocity and then in Hermite functionsin the position. Next by inserting this distribution functioninto the Fokker-Planck equation they obtain a recursion re-lation for the expansion coefficients. By introducing a suit-able vector and matrix notation this recurrence relation be-comes a tridiagonal vector recurrence relation. Finally, thisvector recurrence relation is solved by matrix continued frac-tions. The matrix continued fraction solution of the problemin question has been further developed in Ref. 43.

    Fractional Klein-Kramers equations can in principle besolved by the same methods as the normal Klein-Kramersequation, e.g., by the method of separation of the variables.The separation procedure yields an equation of Sturm-Liouville type. Anomalous subdiffusion in the harmonic po-tential and double-well potential 5 has been treated by thismethod in Refs. 4446 when inertial effects are ignoredusing an eigenfunction expansion with Mittag-Leffler tempo-ral behavior. This method has recently been extended to theanalogous fractional rotational diffusion models in a periodicpotential by Coffey et al. 10,47. There, the authors havedeveloped effective methods of solution of fractional diffu-sion equations based on ordinary and matrix continued frac-tions as is well known continued fractions are an extremelypowerful tool in the solution of normal diffusion equations1. Here we apply the methods of Coffey et al. 10,43,47to account for inertial effects in fractional translational dif-fusion. The main objective of the present paper is to ascer-tain how these effects in anomalous diffusion in a bistablepotential modify the behavior of the normalized position cor-relation function x0xt0 / x200 and its spectra charac-terizing the anomalous relaxation.




    By introducing the normalized variables as in 43

    y =x

    x201/2 , A =


    , B =bx20




    , = , 6

    the fractional kinetic Eq. 4 becomes


    t+ y









    = 10Dt1

    yyW +



    y2 , 7

    where =2 and Vy=Ay2+By4. For A0 and B0, thepotential Vy has only one minimum. For A0 and B0which is the case of interest, the potential Vy has twominima separated by a maximum at y=0 with the potentialbarrier V=Q=A2 /4B. The new normalization conditiony20=1 implies that the constants A and B are not indepen-dent and are related via 48

    B = BQ =1


    , 8

    where Dvz is Whitakers parabolic cylinder function of or-der v 14. According to Barkai and Silbey 15, Eq. 7 hashitherto been regarded as been valid for subdiffusion in ve-locity space, 01. However, the subdiffusion in velocityspace gives rise to enhanced diffusion in configuration space10,47. Furthermore, if 12, Eq. 7 is also regarded asdescribing enhanced diffusion in velocity space, then the en-hanced diffusion in velocity space gives rise to subdiffusionin configuration space 10,47.

    Just as normal diffusion 42,43, one may seek a generalsolution of Eq. 7 in the form

    Wy, y,t =






    HqyHny , 9

    where Hnz are the orthogonal Hermite polynomials 14,=B1/4 and is a scaling factor with value chosen so as toensure optimum convergence of the continued fractions in-volved as suggested by Voigtlaender and Risken 42 allresults for the observables are independent of . By substi-tuting Eq. 9 into Eq. 7 and noting that 14


    dzHnz = 2nHn1z, Hn+1z = 2zHnz 2nHn1z ,

    we have the fractional differential recurrence relations for thefunctions cn,qt


    dtcn,qt = n10Dt

    1cn,qt + n + 1eqcn+1,q+3t

    + dqcn+1,q+1t + dq1

    + cn+1,q1t + eq3cn+1,q3t

    neqcn1,q+3t + dq+cn1,q+1t+ dq1

    cn1,q1t + eq3cn1,q3t , 10


    dq =

    B1/4q + 123

    3q + 1 22Q 4 , 11

    eq =B1/4q + 1

    23q + 3q + 2q + 1 . 12

    For =1, Eq. 10 coincides with that for normal diffusion42,43.

    Equation 10 can be solved exactly using matrix contin-ued fractions as described in Appendix A. Having deter-mined c0,2q1t, one can then calculate the position correla-tion function Ct= y0yt0 see Appendix B

    Ct =ZB1/4


    c0,2q10c0,2q1t , 13

    its spectrum C=0Cteitdt, and the dynamic suscep-

    tibility = i defined as

    = 0


    dtCtdt = 1 iC . 14

    Here Z is the partition function in configuration space givenby 47

    Z =

    eAy2By4dy = 2B1/4D1/2 2QeQ/2.


    We remark that the dynamic susceptibility characterizesthe ac response of the system to a small perturbation 42.


    In the high damping or noninertial limit, 1, and12, i.e., noninertial subdiffusion in configurationspace, the low-frequency behavior 0 of the suscepti-bility may be evaluated as 47

    1 i2int/ + , 16

    where the relaxation time int is given by

    int = 0

    C1tdt . 17

    For normal diffusion, int corresponds to the correlation orintegral relaxation time the area under the correlation func-tion C1t. Now int for normal diffusion in a double well



  • potential 5 may be expressed in exact closed form, viz.10, Chap. 6,

    int = eQ/2D1/2 2Q

    23/4D3/22 2Q 0

    es Q21 erfs Q2 dss



    where erfz= 20zez

    2dz is the error function 14. The low

    frequency part of the susceptibility spectrum may alsobe approximated by a Cole-Cole-like equation 16,46


    1 + i/R2+ , 19


    R 111/2 20

    is the characteristic frequency, 1 is the smallest nonvanish-ing eigenvalue of the Fokker-Planck equation for normal dif-fusion, and is a parameter accounting for the contributionof the high-frequency modes. In the time domain, such arepresentation is equivalent to assuming that the correlationfunction Ct may be approximated as

    Ct 1 E2 1t/2 + , 21

    where Ez is the Mittag-Leffler function defined as 4,5

    Ez = n=0


    1 + n.

    The behavior of 1 for normal diffusion can be evaluatedwith very high accuracy from the approximate equation10,46

    1 =D3/2 2QD1/2 2Q eQ1 + erfQ0


    es Q2t Q2


    stdsdt1. 22

    In the low temperature limit Q1 11 and int have the

    simple asymptotic behavior 10,46

    1/1 eQ

    42Q1 + 58Q + ,int


    42Q1 + 12Q + . 23Equations 1923 allow one to readily estimate thequalitative behavior of the susceptibility and itscharacteristic frequency R. In particular, R

    42Q /1/2eQ/2 / in the low temperature limitQ1. Noninertial subdiffusion in a double well potentialhas been treated in detail in Ref. 46.


    The imaginary part of the dynamic susceptibilityfor various values of the barrier height Q, friction coefficient

    , and fractional exponent are shown in Figs. 1 and 2.The low-frequency asymptotes Eq. 16 are also shownhere for comparison. Apparently for high damping, 1,the low frequency part of the spectrum may by approximatedby Eq. 19. This low frequency relaxation band is due to theslow overbarrier relaxation of the particles in the double-wellpotential. A very high-frequency band is also visible in Figs.1 and 2 due to the fast inertial oscillations of the particles inthe potential wells. As far as the behavior of the high-frequency band as a function of is concerned, its ampli-tude decreases progressively with increasing , as onewould intuitively expect. For large friction 1 small in-ertial effects, the characteristic frequency of this band can

    FIG. 1. The imaginary part of vs solid lines for thefractional exponent =1.5 and various values of the damping coef-ficient and barrier height Q. The Cole-Cole-like spectra Eq.19 and low frequency asymptotes Eq. 16 are shown by sym-bols and dashed lines, respectively.

    FIG. 2. The same as in Fig. 1 for =0.5.



  • be estimated as W8Q1/2 / 46 for 12. Onthe other hand, for very small friction 1 large inertialeffects, two sharp peaks appear in the high-frequency partof the spectra. These peaks appear at the fundamental andsecond harmonic frequencies of the almost free periodic mo-tion of the particle in the anharmonic potential Vx=ax2 /2+bx4 /4. For Q1, 1, and =1, the character-istic frequency of the high-frequency oscillations L can beestimated from the analytic solution for the position correla-tion function x0xt0 at vanishing damping, 0, asL2Q3/41 32,42,43 detailed discussion of the un-damped case is given in Refs. 32,39,43. Moreover, just asin normal Brownian dynamics, inertial effects cause a rapidfalloff of at high frequencies. The integral absorp-tion defined as 0

    d satisfies the sum rule 11


    d = 0








    42, 24

    which relates the second spectral moments of position auto-correlation functions to their second time derivative at t=0.The sum rule Eq. 24 dictates that the integral absorptionremains finite. We remark, on the other hand, that for amodel based on a FKKE of the form of Eq. 3, this sum ruleis not fulfilled as here 0

    d=. The behavior of and the low-frequency asymptotes Eq. 16 for highdamping is shown in Figs. 3 and 4 for various values of thefractional exponent . Apparently, the agreement betweenthe exact continued fraction calculations and the approximateEq. 16 at low frequencies is very good when 12, i.e.,noninertial subdiffusion in configuration space. As far as thedependence of the characteristic frequency R111/2 Eq. 20 of the low-frequency band on thebarrier height Q and fractional exponent is concerned thefrequency R decreases exponentially eQ/2 as Q israised and 2. This behavior occurs because for normaldiffusion the probability of escape of a particle from one wellto another over the potential barrier exponentially decreaseswith increasing Q.

    The model we have outlined incorporates both relaxationand resonance behavior of a nonlinear Brownian oscillatorand so may simultaneously explain both the anomalous low-frequency relaxation and high frequency resonance spectra.The present calculation also constitutes an example of thesolution of the fractional Klein-Kramers equation for anoma-lous inertial translational diffusion in a double well potentialand is to our knowledge the first example of such a solution.We remark that all the above results are obtained from theBarkai-Silbey fractional form of the Klein-Kramers Eq. 7for the evolution of the probability distribution function in

    phase space. In that equation, the fractional derivative actsonly on the diffusion term. Hence the form of the Liouvilleoperator, or convective derivative is preserved so that Eq. 7has the conventional form of a Boltzmann equation for thesingle particle distribution function. Thus the high frequencybehavior is entirely controlled by the inertia of the system,and does not depend on the anomalous exponent. Althoughsuch a diffusion equation fully incorporates inertial effectsand produces physically meaning results much work remainsto be done in order to provide a rigorous justification forsuch inertial kinetic equations.


    The solution of Eq. 10 can be found by modifying thesolution for normal diffusion 43. We introduce the columnvectors

    C2n1t = c2n2,1tc2n2,3t

    , C2nt = c2n1,0tc2n1,2t

    n 1 .Now, Eq. 10 can be rearranged as the set of matrix three-term recurrence equations for the one-sided Fourier trans-

    forms Cn=0Cnteitdt, viz.,

    FIG. 3. The real and imaginary parts of the dynamicsusceptibility vs solid lines for various values of thefractional exponent =1 normal diffusion, 0.8, and 0.6; the bar-rier height Q=10 and damping coefficient =100. The Cole-Cole-like spectra Eq. 19 and low frequency asymptotes Eq. 16 areshown by symbols and dashed lines, respectively.



  • i + i1n 1Cn QnCn1 Qn


    = n,1C10 , A1

    where Qn+ and Qn

    are the four-diagonal matrices. Their ma-trix elements are given by

    Q2n p,q = 2n 1p,q+2e2p5 + p,q+1d2p3 + p,qd2p1+

    + p,q1e2p1 ,

    Q2n+ p,q = 2np,q+2e2p5 + p,q+1d2p3+ + p,qd2p1

    + p,q1e2p1 ,

    Q2n1 p,q = 2n 2p,q+1e2p2 + p,qd2p1 + p,q1d2p1+

    + p,q2e2p1 ,

    Q2n1+ p,q = 2n 1p,q+1e2p2 + p,qd2p1+ + p,q1d2p1

    + p,q2e2p1 ,

    where dq and eq are defined by Eqs. 11 and 12.

    By invoking the general method 10 for solving the ma-trix recursion Eq. A1, we have the exact solution for thespectrum C1 in terms of a matrix continued fraction, viz.

    C1 = 1C10 , A2

    where the matrix continued fraction 1 is defined by therecurrence equation

    n = i + i1n 1I Qn+n+1Qn+1


    and I is the unit matrix. Having determined C1 whoseelements are c0,2q1, q1, we can evaluate the spectrumof the position correlation function Ct= y0yt definedby Eq. 13 here the initial values c0,2q10 are calculatedfrom Eq. B2 of the Appendix B.

    The exact matrix continued fraction solution Eq. A2we have obtained is easily computed. As far as practicalcalculations of the infinite matrix continued fraction are con-cerned, we approximate it by a matrix continued fraction offinite order by putting n+1=0 at some n=N; simulta-neously, we confine the dimensions of the infinite matricesQn

    , Qn+, and I to a finite value M M. N and M are deter-

    mined so that further increase of N and M does not alter theresults. Both N and M depend mainly on the dimensionlessbarrier Q and damping parameters and must be chosentaking into account the desired degree of accuracy of thecalculation. The final results are independent of the scalingfactor . The advantage of choosing an optimal value of is, however, that the dimensions N and M can be minimized.Both N and M increase with decreasing and increasing Q.


    Equation 13 follows from the definition of the correla-tion function Ct, viz.,

    Ct = y0yt0


    yy0Wy, y,ty0, y0,0

    W0y0, y0dydy0dydy0,

    where y0=y0, W0y0 , y0= /Ze2y0

    2Vy0 is theequilibrium Boltzmann distribution function, andWy , y , t y0 , y0 ,0 is the transition probability, which satis-fies Eq. 7 with the initial condition Wy , y ,0 y0 , y0 ,0=yy0y y0 and is defined as

    Wy, y,ty0, y0,0









    n,mHpy0Hmy0HqyHny2n+m+p+qm!p!n!q! ,


    where Gtq,pn,m are the matrix elements of the system matrix

    Gt defined as

    Gtq,pn,m =

    dydy0dydy0Wy, y,ty0, y0,0




    The coefficients cn,qt can be presented in terms of Gtq,pn,m

    as 42

    FIG. 4. The same as in Fig. 3 for =1 normal diffusion, 1.2,and 1.4; =10 and Q=10.



  • cn,qt = m=0


    Gtq,pn,mcm,p0 .


    c0,qt = p=0


    with the initial conditions

    c0,p0 =1


    xHpxe2x22Qx2+x4/2dx .


    Noting that G0q,pm,n=q,pm,n, we have from Eq. B1

    Wy, y,0y0, y0,0 =









    Taking into account that 1

    fy,y0 = p=0




    1 42exp 42

    1 42yy0 y2 y0



    fy,y0 =


    2y y0 ,

    we have Eq. 13.

    1 H. Risken, The Fokker-Planck Equation, 2nd ed. Springer-Verlag, Berlin, 1989.

    2 R. Mazo, Brownian Motion: Fluctuations, Dynamics and Ap-plications Oxford University Press, Oxford, 2002.

    3 A. Einstein, in Investigations on the Theory of the BrownianMovement, edited by R. H. Frth Methuen, London, 1926.

    4 R. Metzler and J. Klafter, Phys. Rep. 339, 1 2000.5 R. Metzler and J. Klafter, Adv. Chem. Phys. 116, 223 2001.6 B. J. West, M. Bologna, and P. Grigolini, Physics of Fractal

    Operators Springer, New York, 2003.7 E. W. Montroll and M. F. Shlesinger, in Non Equilibrium Phe-

    nomena II from Stochastics to Hydrodynamics, edited by J. L.Lebowitz and E. W. Montroll Elsevier Science Publishers,Amsterdam, 1984.

    8 E. W. Montroll and G. H. Weiss, J. Math. Phys. 6, 167 1965.9 W. Paul and J. Baschnagel, Stochastic Processes from Physics

    to Finance Springer Verlag, Berlin, 1999.10 W. T. Coffey, Yu. P. Kalmykov, and J. T. Waldron, The Lange-

    vin Equation, 2nd ed. World Scientific, Singapore, 2004.11 M. W. Evans, G. J. Evans, W. T. Coffey, and P. Grigolini,

    Molecular Dynamics Wiley Interscience, New York, 1982.12 R. Metzler, Phys. Rev. E 62, 6233 2000.13 R. Metzler and J. Klafter, J. Phys. Chem. B 104, 3851 2000.14 Handbook of Mathematical Functions, edited by M.

    Abramowitz and I. Stegun Dover, New York, 1964.15 E. Barkai and R. S. Silbey, J. Phys. Chem. B 104, 3866

    2000.16 W. T. Coffey, Yu. P. Kalmykov, and S. V. Titov, Phys. Rev. E

    67, 061115 2003.17 D. Chandler, J. Chem. Phys. 68, 2959 1978.18 B. J. Berne, J. L. Skinner, and P. G. Wolynes, J. Chem. Phys.

    73, 4314 1980.19 D. L. Hasha, T. Eguchi, and J. Jonas, J. Chem. Phys. 75, 1571

    1981; J. Am. Chem. Soc. 104, 2290 1982.20 D. K. Garrity and J. L. Skinner, Chem. Phys. Lett. 95, 46

    1983.21 B. Carmeli and A. Nitzan, J. Chem. Phys. 80, 3596 1984.22 H. A. Kramers, Physica Amsterdam 7, 284 1940.23 H. C. Brinkman, Physica Amsterdam 22, 29 1956; 22, 149

    1956.24 C. Blomberg, Physica A 86, 49 1977; 86, 67 1977.25 P. B. Visscher, Phys. Rev. B 14, 347 1976.26 J. L. Skinner and P. G. Wolynes, J. Chem. Phys. 69, 2143

    1978; 72, 4913 1980.27 R. S. Larson and M. D. Kostin, J. Chem. Phys. 69, 4821

    1978; 72, 1392 1980.28 S. C. Northrup and J. T. Hynes, J. Chem. Phys. 69, 5246

    1978; J. Chem. Phys. 69, 5261 1978; R. F. Grote and J. T.Hynes, ibid. 73, 2700 1980; 73, 2715 1980.

    29 M. Mangel, J. Chem. Phys. 72, 6606 1980.30 K. Schulten, Z. Schulten, and A. Szabo, J. Chem. Phys. 74,

    4426 1981.31 M. Bixon and R. Zwanzig, J. Stat. Phys. 3, 245 1971.32 M. I. Dykman, S. M. Soskin, and M. A. Krivoglaz, Physica A

    133, 53 1985.33 P. Hnggi, Phys. Lett. 78A, 304 1980.34 J. A. Krumhansl and J. R. Schriefier, Phys. Rev. B 11, 3535

    1975.35 J. D. Bao and Y. Z. Zhuo, Phys. Rev. C 67, 064606 2003.36 V. M. Kolomietz, S. V. Radionov, and S. Shlomo, Phys. Rev. C

    64, 054302 2001.37 M. I. Dykman, G. P. Golubev, D. G. Luchinsky, P. V. E. Mc-

    Clintock, N. D. Stein, and N. G. Stocks, Phys. Rev. E 49, 19351994.

    38 L. Gammaitoni, P. Hnggi, P. Jung, and F. Marchesoni, Rev.Mod. Phys. 70, 223 1998.



  • 39 Y. Onodera, Prog. Theor. Phys. 44, 1477 1970.40 K. Voigtlaender and H. Risken, J. Stat. Phys. 41, 825 1985.41 M. I. Dykman, R. Mannella, P. V. E. McClintock, F. Moss, and

    S. M. Soskin, Phys. Rev. A 37, 1303 1988.42 K. Voigtlaender and H. Risken, J. Stat. Phys. 40, 397 1985;

    Chem. Phys. Lett. 105, 506 1984.43 Yu. P. Kalmykov, W. T. Coffey, and S. V. Titov, J. Chem. Phys.

    124, 024107 2006.44 R. Metzler, E. Barkai, and J. Klafter, Phys. Rev. Lett. 82, 3563

    1999.45 F. So and K. L. Liu, Physica A 331, 378 2004; C. W. Chow

    and K. L. Liu, ibid. 331, 378 2004.46 Yu. P. Kalmykov, W. T. Coffey, and S. V. Titov, Phys. Rev. E

    74, 011105 2006.47 W. T. Coffey, Yu. P. Kalmykov, and S. V. Titov, Adv. Chem.

    Phys. 133, 285 2006.48 A. Perico, R. Pratolongo, K. F. Freed, R. W. Pastor, and A.

    Szabo, J. Chem. Phys. 98, 564 1993.




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