Andrew Butler
We describe a canonical decomposition of the cohomology of the Dani-Mainkar metabelian Lie algebras associated with graphs. As applications, we obtain explicit formulas for the third cohomology of any Dani-Mainkar Lie algebra and for the…
Development of methods to control the directional and spectral characteristics of thermal radiation from metallic surfaces is a critical factor enabling many important thermal management applications. In this paper, we study the thermal…
We present SCQPTH: a differentiable first-order splitting method for convex quadratic programs. The SCQPTH framework is based on the alternating direction method of multipliers (ADMM) and the software implementation is motivated by the…
Prediction models are typically optimized independently from decision optimization. A smart predict then optimize (SPO) framework optimizes prediction models to minimize downstream decision regret. In this paper we present dboost, the first…
Hexagonal boron nitride (hBN) has emerged as a promising ultrathin host of single photon emitters (SPEs) with favorable quantum properties at room temperature, making it a highly desirable element for integrated quantum photonic networks.…
Parity-Time (PT) symmetric optical structures exhibit several unique and interesting characteristics with the most popular being exceptional points. While the emerging concept of PT-symmetry has been extensively investigated in bulky…
Prediction models are traditionally optimized independently from their use in the asset allocation decision-making process. We address this shortcoming and present a framework for integrating regression prediction models in a mean-variance…
Mean-variance optimization (MVO) is known to be sensitive to estimation error in its inputs. Norm penalization of MVO programs is a regularization technique that can mitigate the adverse effects of estimation error. We augment the standard…
Controlling the spectral and angular response of infrared (IR) radiation is a challenging task of paramount importance to various emerging photonic applications. Here, we overcome these problems by proposing and analyzing a new design of a…
Passive radiative cooling is currently the frontier technology in renewable-energy research. In terms of extraterrestrial applications, radiative cooling is a critical component to the thermal management system of a spacecraft, where the…
Plasmonic nanopatch antennas that incorporate dielectric gaps hundreds of picometers to several nanometers thick have drawn increasing attention over the past decade because they confine electromagnetic fields to grossly sub-diffraction…
Recent advances in neural-network architecture allow for seamless integration of convex optimization problems as differentiable layers in an end-to-end trainable neural network. Integrating medium and large scale quadratic programs into a…
We studied a sample of 274 radio and X-ray selected quasars (XQSOs) detected in the COSMOS and XXL-S radio surveys at 3 GHz and 2.1 GHz, respectively. This sample was identified by adopting a conservative threshold in X-ray luminosity, Lx…
The evolution of the comoving kinetic luminosity densities ($\Omega_{\rm{kin}}$) of the radio loud (RL) high-excitation radio galaxies (RL HERGs) and the low-excitation radio galaxies (LERGs) in the XXL-S field is presented. The wide area…
The classification of the host galaxies of the radio sources in the 25 deg$^2$ ultimate XMM extragalactic survey south field (XXL-S) is presented. XXL-S was surveyed at 2.1 GHz with the Australia Telescope Compact Array (ATCA) and is thus…
The 2.1 GHz radio source catalogue of the 25 deg$^2$ ultimate XMM extragalactic survey south (XXL-S) field, observed with the Australia Telescope Compact Array (ATCA), is presented. The final radio mosaic achieved a resolution of…
In this paper we present the optical, near-infrared (NIR) and X-ray identifications of the 6287 radio sources detected in the 2.1 GHz deep radio survey down to a median rms of ~ 41microJy/beam obtained with the Australia Telescope Compact…
Gaussian Process (GP) models are popular statistical surrogates used for emulating computationally expensive computer simulators. The quality of a GP model fit can be assessed by a goodness of fit measure based on optimized likelihood.…