Constructing Auxiliary Dynamics for Nonequilibrium Stationary States by Variance Minimization

We present a strategy to construct guiding distribution functions (GDFs) based on variance minimization. Auxiliary dynamics via GDFs mitigates the exponential growth of variance as a function of bias in Monte Carlo estimators of large deviation functions. The variance minimization technique exploits the exact properties of eigenstates of the tilted operator that defines the biased dynamics in the nonequilibrium system. We demonstrate our techniques in two classes of problems. In the continuum, we show that GDFs can be optimized to study the interacting driven diffusive systems where the efficiency is systematically improved by incorporating higher correlations into the GDF. On the lattice, we use a correlator product state ansatz to study the 1D weakly asymmetric simple exclusion process. We show that with modest resources, we can capture the features of the susceptibility in large systems that mark the phase transition from uniform transport to a traveling wave state. Our work extends the repertoire of tools available to study nonequilibrium properties in realistic systems

Local Entanglement and quantum phase transition in spin models

Due to the phase interference of electromagnetic wave, one can recover the total image of one object from a small piece of holograph, which records the interference pattern of two laser light reflected from it. Similarly, the quantum superposition principle allows us to derive the global phase diagram of quantum spin models by investigating a proper local measurement. In the present paper, we study the two-site entanglement in the antifferomagnetic spin models with both spin-1/2 and 1. We show that its behaviors reveal some important information on the global properties and the quantum phase transition of these systems.Comment: 6 pages, 7 figure

Saturation effects in forward-forward dijet production in p+Pb collisions

We study saturation effects in the production of forward dijets in proton-lead collisions at the Large Hadron Collider, using the framework of High Energy Factorization. Such configurations, with both jets produced in the forward direction, probe the gluon density of the lead nucleus at small longitudinal momentum fraction, and also limit the phase space for emissions of additional jets. We find significant suppression of the forward dijet azimuthal correlations in proton-lead versus proton-proton collisions, which we attribute to stronger saturation of the gluon density in the nucleus than in the proton. In order to minimize model dependence of our predictions, we use two different extensions of the Balitsky-Kovchegov equation for evolution of the gluon density with sub-leading corrections.Comment: 13 pages, 4 figures; v2: added figure 4, several clarifying sentences and a reference; version accepted by PR

Simulation of fermionic lattice models in two dimensions with Projected Entangled-Pair States: Next-nearest neighbor Hamiltonians

In a recent contribution [Phys. Rev. B 81, 165104 (2010)] fermionic Projected Entangled-Pair States (PEPS) were used to approximate the ground state of free and interacting spinless fermion models, as well as the $t$-$J$ model. This paper revisits these three models in the presence of an additional next-nearest hopping amplitude in the Hamiltonian. First we explain how to account for next-nearest neighbor Hamiltonian terms in the context of fermionic PEPS algorithms based on simulating time evolution. Then we present benchmark calculations for the three models of fermions, and compare our results against analytical, mean-field, and variational Monte Carlo results, respectively. Consistent with previous computations restricted to nearest-neighbor Hamiltonians, we systematically obtain more accurate (or better converged) results for gapped phases than for gapless ones.Comment: 10 pages, 11 figures, minor change