Conductance of quantum impurity models from quantum monte carlo
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The conductance of two Anderson impurity models, one with twofold and another with fourfold degeneracy, representing two types of quantum dots, is calculated using a world-line quantum Monte Carlo (QMC) method. Extrapolation of the imaginary time QMC data to zero frequency yields the linear conductance, which is then compared to numerical renormalization-group results in order to assess its accuracy. We find that the method gives excellent results at low temperature (T TK) throughout the mixed-valence and Kondo regimes but it is unreliable for higher temperature. © 2010 The American Physical Society.
Published Version (Please cite this version)10.1103/PhysRevB.82.165447
Publication InfoLiu, DE; Chandrasekharan, S; & Baranger, HU (2010). Conductance of quantum impurity models from quantum monte carlo. Physical Review B - Condensed Matter and Materials Physics, 82(16). pp. 165447. 10.1103/PhysRevB.82.165447. Retrieved from https://hdl.handle.net/10161/4258.
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Professor of Physics
The broad focus of Prof. Baranger's group is quantum open systems at the nanoscale, particularly the generation of correlation between particles in such systems. Fundamental interest in nanophysics-- the physics of small, nanometer scale, bits of solid-- stems from the ability to control and probe systems on length scales larger than atoms but small enough that the averaging inherent in bulk properties has not yet occurred. Using this ability, entirely unanticipated phenomena ca
Professor of Physics
Prof. Chandrasekharan is interested in understanding quantum field theories non-perturbatively from first principles calculations. His research focuses on lattice formulations of these theories with emphasis on strongly correlated fermionic systems of interest in condensed matter, particle and nuclear physics. He develops novel Monte-Carlo algorithms to study these problems. He is particularly excited about solutions to the notoriously difficult <a href="http://en.wikipedia.org/wiki/Numerical_si
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