Phase Diagram and Commensurate-Incommensurate Transitions in the Phase Field Crystal Model with an External Pinning Potential

We study the phase diagram and the commensurate-incommensurate transitions in a phase field model of a two-dimensional crystal lattice in the presence of an external pinning potential. The model allows for both elastic and plastic deformations and provides a continuum description of lattice systems, such as for adsorbed atomic layers or two-dimensional vortex lattices. Analytically, a mode expansion analysis is used to determine the ground states and the commensurate-incommensurate transitions in the model as a function of the strength of the pinning potential and the lattice mismatch parameter. Numerical minimization of the corresponding free energy shows good agreement with the analytical predictions and provides details on the topological defects in the transition region. We find that for small mismatch the transition is of first-order, and it remains so for the largest values of mismatch studied here. Our results are consistent with results of simulations for atomistic models of adsorbed overlayers

Cotunneling Transport and Quantum Phase Transitions in Coupled Josephson-Junction Chains with Charge Frustration

We investigate the quantum phase transitions in two capacitively coupled chains of ultra-small Josephson-junctions, with emphasis on the external charge effects. The particle-hole symmetry of the system is broken by the gate voltage applied to each superconducting island, and the resulting induced charge introduces frustration to the system. Near the maximal-frustration line, where the system is transformed into a spin-1/2 Heisenberg antiferromagnetic chain, cotunneling of the particles along the two chains is shown to play a major role in the transport and to drive a quantum phase transition out of the charge-density wave insulator, as the Josephson-coupling energy is increased. We also argue briefly that slightly off the symmetry line, the universality class of the transition remains the same as that right on the line, still being driven by the particle-hole pairs.Comment: Final version accepted to Phys. Rev. Lett. (Longer version is available from http://ctp.snu.ac.kr/~choims/

The Electron Scattering Region in Seyfert Nuclei

The electron scattering region (ESR) is one of important ingredients in Seyfert nuclei because it makes possible to observe the hidden broad line region (hereafter HBLR) in some type 2 Seyfert nuclei (hereafter S2s). However, little is known about its physical and geometrical properties. Using the number ratio of S2s with and without HBLR, we investigate statistically where the ESR is in Seyfert nuclei. Our analysis suggests that the ESR is located at radius between $\sim$ 0.01 pc and $\sim$ 0.1 pc from the central engine. We also discuss a possible origin of the ESR briefly.Comment: 5 pages and 1 figure. The Astrophysical Journal (Letters), in pres

Anomalous Sliding Friction and Peak Effect near the Flux Lattice Melting Transition

Recent experiments have revealed a giant "peak effect" in ultrapure high $T_c$ superconductors. Moreover, the new data show that the peak effect coincides exactly with the melting transition of the underlying flux lattice. In this work, we show using dynamical scaling arguments that the friction due to the pinning centers acting on the flux lattice develops a singularity near a continuous phase transition and can diverge for many systems. The magnitude of the nonlinear sliding friction of the flux lattice scales with this atomistic friction. Thus, the nonlinear conductance should diverge for a true continuous transition in the flux lattice or peak at a weakly first order transition or for systems of finite size.Comment: 4 pages, to appear in Phys. Rev.

Machine learning to identify ICL and BCG in simulated galaxy clusters

Nowadays, Machine Learning techniques offer fast and efficient solutions for classification problems that would require intensive computational resources via traditional methods. We examine the use of a supervised Random Forest to classify stars in simulated galaxy clusters after subtracting the member galaxies. These dynamically different components are interpreted as the individual properties of the stars in the Brightest Cluster Galaxy (BCG) and IntraCluster Light (ICL). We employ matched stellar catalogues (built from the different dynamical properties of BCG and ICL) of 29 simulated clusters from the DIANOGA set to train and test the classifier. The input features are cluster mass, normalized particle cluster-centric distance, and rest-frame velocity. The model is found to correctly identify most of the stars, while the larger errors are exhibited at the BCG outskirts, where the differences between the physical properties of the two components are less obvious. We investigate the robustness of the classifier to numerical resolution, redshift dependence (up to z = 1), and included astrophysical models. We claim that our classifier provides consistent results in simulations for z 0.1 R-200) is significantly affected by uncertainties in the classification process. In conclusion, this work suggests the importance of employing Machine Learning to speed up a computationally expensive classification in simulations

Sliding Phases in XY-Models, Crystals, and Cationic Lipid-DNA Complexes

We predict the existence of a totally new class of phases in weakly coupled, three-dimensional stacks of two-dimensional (2D) XY-models. These ``sliding phases'' behave essentially like decoupled, independent 2D XY-models with precisely zero free energy cost associated with rotating spins in one layer relative to those in neighboring layers. As a result, the two-point spin correlation function decays algebraically with in-plane separation. Our results, which contradict past studies because we include higher-gradient couplings between layers, also apply to crystals and may explain recently observed behavior in cationic lipid-DNA complexes.Comment: 4 pages of double column text in REVTEX format and 1 postscript figur