56,718 research outputs found

    The hard-disk fluid revisited

    Full text link
    The hard-disk model plays a role of touchstone for testing and developing the transport theory. By large scale molecular dynamics simulations of this model, three important autocorrelation functions, and as a result the corresponding transport coefficients, i.e., the diffusion constant, the thermal conductivity and the shear viscosity, are found to deviate significantly from the predictions of the conventional transport theory beyond the dilute limit. To improve the theory, we consider both the kinetic process and the hydrodynamic process in the whole time range, rather than each process in a seperated time scale as the conventional transport theory does. With this consideration, a unified and coherent expression free of any fitting parameters is derived succesfully in the case of the velocity autocorrelation function, and its superiority to the conventional `piecewise' formula is shown. This expression applies to the whole time range and up to moderate densities, and thus bridges the kinetics and hydrodynamics approaches in a self-consistent manner.Comment: 5 pages, 4 figure

    Brownian motion: from kinetics to hydrodynamics

    Full text link
    Brownian motion has served as a pilot of studies in diffusion and other transport phenomena for over a century. The foundation of Brownian motion, laid by Einstein, has generally been accepted to be far from being complete since the late 1960s, because it fails to take important hydrodynamic effects into account. The hydrodynamic effects yield a time dependence of the diffusion coefficient, and this extends the ordinary hydrodynamics. However, the time profile of the diffusion coefficient across the kinetic and hydrodynamic regions is still absent, which prohibits a complete description of Brownian motion in the entire course of time. Here we close this gap. We manage to separate the diffusion process into two parts: a kinetic process governed by the kinetics based on molecular chaos approximation and a hydrodynamics process described by linear hydrodynamics. We find the analytical solution of vortex backflow of hydrodynamic modes triggered by a tagged particle. Coupling it to the kinetic process we obtain explicit expressions of the velocity autocorrelation function and the time profile of diffusion coefficient. This leads to an accurate account of both kinetic and hydrodynamic effects. Our theory is applicable for fluid and Brownian particles, even of irregular-shaped objects, in very general environments ranging from dilute gases to dense liquids. The analytical results are in excellent agreement with numerical experiments.Comment: 8pages,3figure

    Modified Stokes-Einstein Relation for Small Brownian Particles

    Full text link
    The Stokes-Einstein (SE) relation has been widely applied to quantitatively describe the Brownian motion. Notwithstanding, here we show that even for a simple fluid, the SE relation may not be completely applicable. Namely, although the SE relation could be a good approximation for a large enough Brownian particle, we find that it induces significant error for a smaller Brownian particle, and the error increases with the decrease of the Brownian particle's size, till the SE relation fails completely when the size of Brownian particle is comparable with that of a fluid molecule. The cause is rooted in the fact that the kinetic and the hydrodynamic effects depend on the size of the Brownian particle differently. By excluding the kinetic contribution to the diffusion coefficient, we propose a revised Stokes-Einstein relation and show that it expands significantly the applicable range.Comment: 3 figure

    Copy the dynamics using a learning machine

    Full text link
    Is it possible to generally construct a dynamical system to simulate a black system without recovering the equations of motion of the latter? Here we show that this goal can be approached by a learning machine. Trained by a set of input-output responses or a segment of time series of a black system, a learning machine can be served as a copy system to mimic the dynamics of various black systems. It can not only behave as the black system at the parameter set that the training data are made, but also recur the evolution history of the black system. As a result, the learning machine provides an effective way for prediction, and enables one to probe the global dynamics of a black system. These findings have significance for practical systems whose equations of motion cannot be approached accurately. Examples of copying the dynamics of an artificial neural network, the Lorenz system, and a variable star are given. Our idea paves a possible way towards copy a living brain.Comment: 8 pages, 4 figure

    Inferring Global Dynamics of a Black-Box System Using Machine Learning

    Full text link
    We present that, instead of establishing the equations of motion, one can model-freely reveal the dynamical properties of a black-box system using a learning machine. Trained only by a segment of time series of a state variable recorded at present parameters values, the dynamics of the learning machine at different training stages can be mapped to the dynamics of the target system along a particular path in its parameter space, following an appropriate training strategy that monotonously decreases the cost function. This path is important, because along that, the primary dynamical properties of the target system will subsequently emerge, in the simple-to-complex order, matching closely the evolution law of certain self-evolved systems in nature. Why such a path can be reproduced is attributed to our training strategy. This particular function of the learning machine opens up a novel way to probe the global dynamical properties of a black-box system without artificially establish the equations of motion, and as such it might have countless applications. As an example, this method is applied to infer what dynamical stages a variable star has experienced and how it will evolve in future, by using the light curve observed presently.Comment: 17 pages, 8 figure

    The 2-adic valuations of differences of Stirling numbers of the second kind

    Full text link
    Let m,n,km, n, k and cc be positive integers. Let Ξ½2(k)\nu_2(k) be the 2-adic valuation of kk. By S(n,k)S(n,k) we denote the Stirling numbers of the second kind. In this paper, we first establish a convolution identity of the Stirling numbers of the second kind and provide a detailed 2-adic analysis to the Stirling numbers of the second kind. Consequently, we show that if 2≀m≀n2\le m\le n and cc is odd, then Ξ½2(S(c2n+1,2mβˆ’1)βˆ’S(c2n,2mβˆ’1))=n+1\nu_2(S(c2^{n+1},2^m-1)-S(c2^n, 2^m-1))=n+1 except when n=m=2n=m=2 and c=1c=1, in which case Ξ½2(S(8,3)βˆ’S(4,3))=6\nu_2(S(8,3)-S(4,3))=6. This solves a conjecture of Lengyel proposed in 2009.Comment: 20 page

    Divisibility by 2 of Stirling numbers of the second kind and their differences

    Full text link
    Let n,k,an,k,a and cc be positive integers and bb be a nonnegative integer. Let Ξ½2(k)\nu_2(k) and s2(k)s_2(k) be the 2-adic valuation of kk and the sum of binary digits of kk, respectively. Let S(n,k)S(n,k) be the Stirling number of the second kind. It is shown that Ξ½2(S(c2n,b2n+1+a))β‰₯s2(a)βˆ’1,\nu_2(S(c2^n,b2^{n+1}+a))\geq s_2(a)-1, where 0<a<2n+10<a<2^{n+1} and 2∀c2\nmid c. Furthermore, one gets that Ξ½2(S(c2n,(cβˆ’1)2n+a))=s2(a)βˆ’1\nu_2(S(c2^{n},(c-1)2^{n}+a))=s_2(a)-1, where nβ‰₯2n\geq 2, 1≀a≀2n1\leq a\leq 2^n and 2∀c2\nmid c. Finally, it is proved that if 3≀k≀2n3\leq k\leq 2^n and kk is not a power of 2 minus 1, then Ξ½2(S(a2n,k)βˆ’S(b2n,k))=n+Ξ½2(aβˆ’b)βˆ’βŒˆlog⁑2kβŒ‰+s2(k)+Ξ΄(k),\nu_2(S(a2^{n},k)-S(b2^{n},k))=n+\nu_2(a-b)-\lceil\log_2k\rceil +s_2(k)+\delta(k), where Ξ΄(4)=2\delta(4)=2, Ξ΄(k)=1\delta(k)=1 if k>4k>4 is a power of 2, and Ξ΄(k)=0\delta(k)=0 otherwise. This confirms a conjecture of Lengyel raised in 2009 except when kk is a power of 2 minus 1.Comment: 23 pages. To appear in Journal of Number Theor

    The universal Kummer congruences

    Full text link
    Let pp be a prime. In this paper, we present a detailed pp-adic analysis to factorials and double factorials and their congruences. We give good bounds for the pp-adic sizes of the coefficients of the divided universal Bernoulli number B^nn{{\hat B_n}\over n} when nn is divisible by pβˆ’1p-1. Using these we then establish the universal Kummer congruences modulo powers of a prime pp for the divided universal Bernoulli numbers B^nn{{\hat B_n}\over n} when nn is divisible by pβˆ’1p-1.Comment: 20 pages. To appear in Journal of the Australian Mathematical Societ

    The 2-adic valuations of Stirling numbers of the second kind

    Full text link
    In this paper, we investigate the 2-adic valuations of the Stirling numbers S(n,k)S(n, k) of the second kind. We show that v2(S(4i,5))=v2(S(4i+3,5))v_2(S(4i, 5))=v_2(S(4i+3, 5)) if and only if i≑̸7(mod32)i\not\equiv 7\pmod {32}. This confirms a conjecture of Amdeberhan, Manna and Moll raised in 2008. We show also that v2(S(2n+1,k+1))=s2(n)βˆ’1v_2(S(2^n+1, k+1))= s_2(n)-1 for any positive integer nn, where s2(n)s_2(n) is the sum of binary digits of nn. It proves another conjecture of Amdeberhan, Manna and Moll.Comment: 9 pages. To appear in International Journal of Number Theor

    Methods of exploring energy diffusion in lattices with finite temperature

    Full text link
    We discuss two methods for exploring energy diffusion in lattices with finite temperature in this paper. The first one is the energy-kick (EK) method. To apply this method, one adds an external energy kick to a particle in the lattice, and tracks its evolution by evolving the kicked system. The second one is the fluctuation-correlation (FC) method. The formula for calculating the probability density function (PDF) using the canonical ensemble is slightly revised and extended to the microcanonical ensemble. We show that the FC method has advantages over the EK method theoretically and technically. Theoretically, the PDF obtained by the FC method reveals the diffusion processes of the inner energy while the PDF obtained by the EK method represents that of the kick energy. The diffusion processes of the inner energy and the external energy added to the system, i.e., the kick energy, may be different quantitatively and even qualitatively depending on models. To show these facts, we study not only the equilibrium systems but also the stationary nonequilibrium systems. Examples showing that the inner energy and the kick energy may have different diffusion behavior are reported in both cases. The technical advantage enables us to study the long-time diffusion processes and thus avoids the finite-time effect.Comment: 10 pages;7figur
    • …
    corecore