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Register a new userTemperature and Friction Accelerated Sampling of Boltzmann-Gibbs Distribution
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This paper is concerned with tuning friction and temperature in Langevin dynamics for fast sampling from the canonical ensemble. We show that near-optimal acceleration is achieved by choosing friction so that the local quadratic approximation of the Hamiltonian is a critical damped oscillator. The system is also over-heated and cooled down to its final temperature. The performances of different cooling schedules are analyzed as functions of total simulation time.
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In this work we present a molecular dynamics simulation of a FFM experiment. The tip-sample interaction is studied by varying the normal force in the tip and the temperature of the surface. The friction force, cA, at zero load and the friction coefficient, $mu$, were obtained. Our results strongly support the idea that the effective contact area, A, decreases with increasing temperature and the friction coefficient presents a clear signature of the premelting process of the surface.
Restricted Boltzmann Machines (RBM) are bi-layer neural networks used for the unsupervised learning of model distributions from data. The bipartite architecture of RBM naturally defines an elegant sampling procedure, called Alternating Gibbs Sampling (AGS), where the configurations of the latent-variable layer are sampled conditional to the data-variable layer, and vice versa. We study here the performance of AGS on several analytically tractable models borrowed from statistical mechanics. We show that standard AGS is not more efficient than classical Metropolis-Hastings (MH) sampling of the effective energy landscape defined on the data layer. However, RBM can identify meaningful representations of training data in their latent space. Furthermore, using these representations and combining Gibbs sampling with the MH algorithm in the latent space can enhance the sampling performance of the RBM when the hidden units encode weakly dependent features of the data. We illustrate our findings on three datasets: Bars and Stripes and MNIST, well known in machine learning, and the so-called Lattice Proteins, introduced in theoretical biology to study the sequence-to-structure mapping in proteins.
In a recent paper, Dunkel and Hilbert [Nature Physics 10, 67-72 (2014)] use an entropy definition due to Gibbs to provide a consistent thermostatistics which forbids negative absolute temperatures. Here we argue that the Gibbs entropy fails to satisfy a basic requirement of thermodynamics, namely that when two bodies are in thermal equilibrium, they should be at the same temperature. The entropy definition due to Boltzmann does meet this test, and moreover in the thermodynamic limit can be shown to satisfy Dunkel and Hilberts consistency criterion. Thus, far from being forbidden, negative temperatures are inevitable, in systems with bounded energy spectra.
The analysis of uniformly longitudinally extended detector is performed and it is shown that the response of such a detector does not differ from the response of the Unruh detector, but the its excitation is caused not by the thermal bath, but by interaction with the fluctuations of the quantum field by virtual quanta.
In this work we propose an extension to the analytical one-dimensional model proposed by E. Gnecco (Phys. Rev. Lett. 84:1172) to describe friction. Our model includes normal forces and the dependence with the angular direction of movement in which the object is dragged over a surface. The presence of the normal force in the model allow us to define judiciously the friction coefficient, instead of introducing it as an {sl a posteriori} concept. We compare the analytical results with molecular dynamics simulations. The simulated model corresponds to a tip sliding over a surface. The tip is simulated as a single particle interacting with a surface through a Lennard-Jones $(6-12)$ potential. The surface is considered as consisting of a regular BCC(001) arrangement of particles interacting with each other through a Lennard-Jones $(6-12)$ potential. We investigate the system under several conditions of velocity, temperature and normal forces. Our analytical results are in very good agreement with those obtained by the simulations and with experimental results from E. Riedo (Phys. Rev. Lett. 91:084502) and Eui-Sung Yoon (Wear 259:1424-1431) as well.
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