Symposium gives insight into ongoing research project at Chemnitz University of Technology ….
Introductory lectures, and then celebrations at night - the Orientation Phase runs from 7 to 11 October and marks the start of the school year for university students with numerous events and offerings …. Nowadays, Chemnitz University of Technology graduate Vipul Ballupet runs his own business in Chemnitz — find out how this came about in a new video …. ASIS provides a more comprehensive understanding of impedance spectroscopy ….
The courses of the summer school focus on different aspects of Applied …. New students are greeted each year at the beginning of the winter semester in a cherished TU …. Page Navigation. Hoffmann, M. Schreiber The list of the speakers and workshop details are given in this PDF. University News.
Driving dementia research forward. Likewise in a nutshell , classical Monte Carlo calculations consist in proposing a move, then in computing the change of the total system energy, and then accepting or rejecting the move with a probability given by the Metropolis filter. How to compute the forces for molecular dynamics or the energies for Monte Carlo is a science in its own right, whenever the interactions are long-ranged, as for the Coulomb potential.
Maggs, to show how this can be done in practice.
Baus, Physicalia, Issue 6, English Choose a language for shopping. Title: Computational Statistical Physics. The result then is quite a pleasing survey of current topics in computational statistical physics. While good textbooks exist on the general aspects of statistical physics, the numerical methods and the new developments based on large-scale computing are not usually adequately presented. Paez, J.
In what, internally, we call our 'Proof-of-Concept paper', we explicitly show how to set up a highly efficient algorithm to simulate a model of liquid water. We indeed confirm that it is possible to sample the Boltzmann distribution which involves the Boltzmann weight, and therefore the system energy , without computing the energy.
As often, the difference lies in the subtle difference between the concepts of 'sampling' that is, obtaining examples of a certain distribution and of 'computing' for example computing the energy. Technically, we succeed in drawing independent samples with a complexity 'N' log 'N' just like the best PPPM algorithms but, we think, much faster. Now, of course, after the first excitement of our 'confirmation paper', we are all excited by the forthcoming 'benchmark paper', where we will compare not only complexities, but actual running times.
Active matter for example the collective dynamics of flocks of birds, of schools of fish, etc is a very active field of research in statistical physics.
However, active matter cannot really be described by equilibrium statistical theory where the state of what is called the system is fully characterized by two numbers for example the volume and the pressure , and where the statistical weight of each configuration can be attributed an energy E, and a statistical Boltzmann weight exp -beta E which depends on the energy alone.
Many active materials are two-dimensional ranging from sheep on a meadow to bacterial colonies to artificial Janus particles on a glass place. As we are so much interested in regular two-dimensional particle systems that are described by equilibrium statistical physics , we posed the question of whether there was some kind of continuous passage between the two types of models. Teaming up with Juliane U.
Klamser and Sebastian C. Kapfer, we studied this question in detail. Our conclusions were published, in November , in Nature Communications.
The density difference between the coexisting hexatic and liquid is non-monotonous as a function of n. For smaller n, the coexisting liquid shows extremely long orientational correlations, and positional correlations in the hexatic become extremely short. Continue with Past Research Notices.
Here is the schedule of past events. Jump to: navigation , search. Cover of a book I wrote in Here is the book's website.
Direct-sampling algorithm for ideal bosons in a trap see article with M. Adapted for interacting bosons, this algorithm was used in a variety of articles.
Event-chain Monte Carlo algorithm for hard spheres and related systems see article with E. Bernard and D. Wilson, including Python implementation. This fantastic algorithm, about two orders of magnitude faster than local Monte Carlo, was used in our discovery of the first-order liquid-hexatic phase transition in hard disks. The method can be generalized to continuous potentials , and we used it to map out the phase diagrams of soft-disk systems.
Look here for an implementation of the event-chain algorithm.
In recent years statistical physics has made significant progress as a result of advances in numerical techniques. While good textbooks exist on the general. While good textbooks exist on the general aspects of statistical physics, the numerical Computational Statistical Physics: From Billiards to Monte Carlo.
Exact diagonalization algorithm for Dynamical mean field theory see article with M.