Momentum Broadening of a Fast Parton in a Perturbative Quark-Gluon Plasma

The average transverse momentum transfer per unit path length to a fast parton scattering elastically in a perturbative quark-gluon plasma is related to the radiative energy loss of the parton. We first calculate the momentum transfer coefficient $\hat q$ in terms of a classical Langevin problem and then define it quantum-mechanically through scattering matrix element. After treating the well known case of a quark-gluon plasma in equilibrium we consider an off-equilibrium unstable plasma. As a specific example, we treat the two-stream plasma with unstable modes of longitudinal chromoelectric field. In the presence of the instabilities, $\hat q$ is shown to exponentially grow in time.Comment: Updated version containing an analysis of insufficiencies in previous calculations of momentum broadening in unstable plasma

Orbital angular momentum bistability in a microlaser

Light's orbital angular momentum (OAM) is an unbounded degree of freedom emerging in helical beams that appears very advantageous technologically. Using a chiral microlaser, i.e. an integrated device that allows generating an emission carrying a net OAM, we demonstrate a regime of bistability involving two modes presenting distinct OAM (L = 0 and L = 2). Furthermore, thanks to an engineered spin-orbit coupling of light in the device, these modes also exhibit distinct polarization patterns, i.e. cirular and azimuthal polarizations. Using a dynamical model of rate euqations, we show that this bistability arises from polarization-dependent saturation of the gain medium. Such a bistable regime appears very promising for implementing ultrafast optical switches based on the OAM of light. As well, it paves the way to the exploration of dynamical processes involving phase and polarization vortices

Hard Loop Approach to Anisotropic Systems

Anisotropic systems of quarks and gluons, which at least for sufficiently short space-time intervals can be treated as homogeneous and static, are considered. The gluon polarization tensor of such a system is explicitly computed within the semiclassical kinetic and Hard Loop diagrammatic theories. The equivalence of the two approaches is demonstrated. The quark self energy is computed as well, and finally, the dispersion relations of quarks and gluons in the anisotropic medium are discussed.Comment: 10 pages, revised to appear in Phys. Rev.

The effect of surface character on flows in microchannels

A technique for quantifying velocity profiles of fluids flowing in circular microchannels is presented. The primary purpose of this technique is to provide a robust method for quantifying the effect Of Surface character on the bulk fluid behaviour. A laser-scanning confocal microscope has been used to obtain fluorescent particle images from a 1 micron thick plane along the centreline of hydrophobic and hydrophilic glass capillaries. The velocities of fluorescent particles being carried in pressure-driven laminar flow of a Newtonian fluid have been evaluated at the centreplane of 57.5 micron capillaries using a variation of particle tracking velocimetry (PTV). This work aims to clarify inconsistencies in previously reported [1-12] slip velocities observed in water over hydrophobically modified surfaces at micron and submicron lengthscales. A change in the velocity profile is observed for water flowing in hydrophobic capillaries, although the behaviour appears to be a result of an optical distortion at the fluid-wall interface. This may point to previous suggestions of a thin layer of air adsorbing to the surface. Notwithstanding, the results do not confidently suggest evidence of slip of water on hydrophobic surfaces in microchannels

Renormalized Effective QCD Hamiltonian: Gluonic Sector

Extending previous QCD Hamiltonian studies, we present a new renormalization procedure which generates an effective Hamiltonian for the gluon sector. The formulation is in the Coulomb gauge where the QCD Hamiltonian is renormalizable and the Gribov problem can be resolved. We utilize elements of the Glazek and Wilson regularization method but now introduce a continuous cut-off procedure which eliminates non-local counterterms. The effective Hamiltonian is then derived to second order in the strong coupling constant. The resulting renormalized Hamiltonian provides a realistic starting point for approximate many-body calculations of hadronic properties for systems with explicit gluon degrees of freedom.Comment: 25 pages, no figures, revte

The 2016 Planned Giving Study

Charitable bequests and other planned gifts have historically played a significant role in the funding of higher education institutions. Prominent institutions such as Harvard University, Johns Hopkins University, and the Julliard School have been established as a direct result of bequests, and these gifts continue to have a profound impact today. The field of planned giving has become more sophisticated over time. However, the complexity of various planned giving vehicles and the comparatively long time period required for planned gifts to be formalized make it difficult for researchers to systematically track and examine planned giving behavior. Existing studies, therefore, heavily rely on self-reported survey data or tax returns. This study is one of the first efforts that seek to understand the changing landscape of planned giving and to explore donor life-cycle trajectories at higher education institutions. This whitepaper is the first in what is hoped to be a series of reports based upon data on planned gifts and donors in the field of higher education. The whitepaper discusses findings from five case-study universities located across the U.S. As the study expands the sample to include more universities and colleges in the next phase, this report series will offer richer data and insights into more underexplored, yet important, questions in planned giving

Geostrophic balance preserving interpolation in mesh adaptive shallow-water ocean modelling

The accurate representation of geostrophic balance is an essential requirement for numerical modelling of geophysical flows. Significant effort is often put into the selection of accurate or optimal balance representation by the discretisation of the fundamental equations. The issue of accurate balance representation is particularly challenging when applying dynamic mesh adaptivity, where there is potential for additional imbalance injection when interpolating to new, optimised meshes. In the context of shallow-water modelling, we present a new method for preservation of geostrophic balance when applying dynamic mesh adaptivity. This approach is based upon interpolation of the Helmholtz decomposition of the Coriolis acceleration. We apply this in combination with a discretisation for which states in geostrophic balance are exactly steady solutions of the linearised equations on an f-plane; this method guarantees that a balanced and steady flow on a donor mesh remains balanced and steady after interpolation onto an arbitrary target mesh, to within machine precision. We further demonstrate the utility of this interpolant for states close to geostrophic balance, and show that it prevents pollution of the resulting solutions by imbalanced perturbations introduced by the interpolation

Large-scale exploration of neural relation classification architectures

Experimental performance on the task of relation classification has generally improved using deep neural network architectures. One major drawback of reported studies is that individual models have been evaluated on a very narrow range of datasets, raising questions about the adaptability of the architectures, while making comparisons between approaches difficult. In this work, we present a systematic large-scale analysis of neural relation classification architectures on six benchmark datasets with widely varying characteristics. We propose a novel multi-channel LSTM model combined with a CNN that takes advantage of all currently popular linguistic and architectural features. Our ‘Man for All Seasons’ approach achieves state-of-the-art performance on two datasets. More importantly, in our view, the model allowed us to obtain direct insights into the continued challenges faced by neural language models on this task. Example data and source code are available at: https://github.com/aidantee/ MASS.MR