Exciton-Population Inversion and Terahertz Gain in Resonantly Excited Semiconductors

The build-up of exciton populations in resonantly laser excited semiconductors is studied microscopically. For excitation at the $2s$-exciton resonance, it is shown that polarization with a strict $s$-type radial symmetry can be efficiently converted into an incoherent $p$-type population. As a consequence, inversion between the $2p$ and $1s$ exciton states can be obtained leading to the appearance of significant terahertz gain.Comment: 4 pages, 3 figure

Effects of local event-by-event conservation laws in ultrarelativistic heavy-ion collisions at particlization

Many simulations of relativistic heavy-ion collisions involve the switching from relativistic hydrodynamics to kinetic particle transport. This switching entails the sampling of particles from the distribution of energy, momentum, and conserved currents provided by hydrodynamics. Usually, this sampling ensures the conservation of these quantities only on the average, i.e., the conserved quantities may actually fluctuate among the sampled particle configurations and only their averages over many such configurations agree with their values from hydrodynamics. Here we apply a recently invented method [D. Oliinychenko and V. Koch, Phys. Rev. Lett. 123, 182302 (2019)PRLTAO0031-900710.1103/PhysRevLett.123.182302] to ensure conservation laws for each sampled configuration in spatially compact regions (patches) and study their effects: From the well-known (micro-)canonical suppression of means and variances to little studied (micro-)canonical correlations and higher-order fluctuations. Most of these effects are sensitive to the patch size. Many of them do not disappear even in the thermodynamic limit, when the patch size goes to infinity. The developed method is essential for particlization of stochastic hydrodynamics. It is useful for studying the chiral magnetic effect, small systems, and in general for fluctuation and correlation observables

Event-by-event fluctuations and the QGP

We discuss the physics underlying event-by-event fluctuations in relativistic heavy ion collisions. We will emphasize how the fluctuations of particle ratios can be utilized to explore the properties of the matter created in these collisions. In particular, we will argue that the fluctutions of the ratio of positively over negatively charged particles may serve as a unique signature for the Quark Gluon Plasma.Comment: Proceedings Quark Matter 2001, Stony Brook, NY January 200

Agent Teams and Evolutionary Computation: Optimizing Semi- Parametric Spatial Autoregressive Models

Classical spatial autoregressive models share the same weakness as the classical linear regression models, namely it is not possible to estimate non-linear relationships between the dependent and independent variables. In the case of classical linear regression a semi-parametric approach can be used to address this issue. Therefore an advanced semi- parametric modelling approach for spatial autoregressive models is introduced. Advanced semi-parametric modelling requires determining the best configuration of independent variable vectors, number of spline-knots and their positions. To solve this combinatorial optimization problem an asynchronous multi-agent system based on genetic-algorithms is utilized. Three teams of agents work each on a subset of the problem and cooperate through sharing their most optimal solutions. Through this system more complex relationships between the dependent and independent variables can be derived. These could be better suited for the possibly non-linear real-world problems faced by applied spatial econometricians.

A profile decomposition approach to the L∞/t (L3/ x) Navier–Stokes regularity criterion

In this paper we continue to develop an alternative viewpoint on recent studies of Navier–Stokes regularity in critical spaces, a program which was started in the recent work by Kenig and Koch (Ann Inst H Poincaré Anal Non Linéaire 28(2):159–187, 2011). Specifically, we prove that strong solutions which remain bounded in the space L3(R3) do not become singular in finite time, a known result established by Escauriaza et al. (Uspekhi Mat Nauk 58(2(350)):3–44, 2003) in the context of suitable weak solutions. Here, we use the method of “critical elements” which was recently developed by Kenig and Merle to treat critical dispersive equations. Our main tool is a “profile decomposition” for the Navier–Stokes equations in critical Besov spaces which we develop here. As a byproduct of this tool, assuming a singularity-producing initial datum for Navier–Stokes exists in a critical Lebesgue or Besov space, we show there is one with minimal norm, generalizing a result of Rusin and Sverak (J Funct Anal 260(3):879–891, 2011)

Enabling Micro-level Demand-Side Grid Flexiblity in Resource Constrained Environments

The increased penetration of uncertain and variable renewable energy presents various resource and operational electric grid challenges. Micro-level (household and small commercial) demand-side grid flexibility could be a cost-effective strategy to integrate high penetrations of wind and solar energy, but literature and field deployments exploring the necessary information and communication technologies (ICTs) are scant. This paper presents an exploratory framework for enabling information driven grid flexibility through the Internet of Things (IoT), and a proof-of-concept wireless sensor gateway (FlexBox) to collect the necessary parameters for adequately monitoring and actuating the micro-level demand-side. In the summer of 2015, thirty sensor gateways were deployed in the city of Managua (Nicaragua) to develop a baseline for a near future small-scale demand response pilot implementation. FlexBox field data has begun shedding light on relationships between ambient temperature and load energy consumption, load and building envelope energy efficiency challenges, latency communication network challenges, and opportunities to engage existing demand-side user behavioral patterns. Information driven grid flexibility strategies present great opportunity to develop new technologies, system architectures, and implementation approaches that can easily scale across regions, incomes, and levels of development