4,029 research outputs found
On equilibration and coarsening in the quantum O(N) model at infinite
The quantum O(N) model in the infinite limit is a paradigm for
symmetry-breaking. Qualitatively, its phase diagram is an excellent guide to
the equilibrium physics for more realistic values of in varying spatial
dimensions (). Here we investigate the physics of this model out of
equilibrium, specifically its response to global quenches starting in the
disordered phase. If the model were to exhibit equilibration, the late time
state could be inferred from the finite temperature phase diagram. In the
infinite limit, we show that not only does the model not lead to
equilibration on account of an infinite number of conserved quantities, it also
does \emph{not} relax to a generalized Gibbs ensemble consistent with these
conserved quantities. Nevertheless, we \emph{still} find that the late time
states following quenches bear strong signatures of the equilibrium phase
diagram. Notably, we find that the model exhibits coarsening to a
non-equilibrium critical state only in dimensions , that is, if the
equilibrium phase diagram contains an ordered phase at non-zero temperatures.Comment: 11 pages, 9 figure
Unstructured Object Recognition using Morphological Learning
A technique of object recognition which can detect absence or presence of objects of interest without making explicit use of their underlying geometric structure is deemed suitable for many practical applications. In this work, a method of recognising unstructured objects has been presented, wherein several gray patterns are input as examples to a morphological rule-based learning algorithm. The output of the algorithm are the corresponding gray structuring elements capable of recognising patterns in query images. The learning is carried out offline before recognition of the queries. The technique has been tested to identify fuel pellet surface imperfections. Robustness wrt intensity, orientation, and shape variations of the query patterns is built into the method. Moreover, simplicity of the recognition process leading to reduced computational time makes the method attractive to solve many practical problems
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