Self-Averaging Scaling Limits of Two-Frequency Wigner Distribution for Random Paraxial Waves

Two-frequency Wigner distribution is introduced to capture the asymptotic behavior of the space-frequency correlation of paraxial waves in the radiative transfer limits. The scaling limits give rises to deterministic transport-like equations. Depending on the ratio of the wavelength to the correlation length the limiting equation is either a Boltzmann-like integral equation or a Fokker-Planck-like differential equation in the phase space. The solutions to these equations have a probabilistic representation which can be simulated by Monte Carlo method. When the medium fluctuates more rapidly in the longitudinal direction, the corresponding Fokker-Planck-like equation can be solved exactly.Comment: typos correcte

Modeling AlGaN p-i-n photodiodes

Ternary AlGaN alloys with a band gap of 3.4 to 6.2 eV are very promising for photodetectors in the UV wavelength range. Using the COMSOL MULTIPHYSICS software based on AlGaN, a p-i-n photodiode model was developed, including its I–V characteristic, spectral sensitivity of the received radiation, absorption coefficient as a function of the aluminum fraction and the depletion layer thickness. To calculate the process of interaction of a semiconductor with EM radiation, we used a model based on the use of an element of the transition matrix through the carrier lifetime during spontaneous recombination. In this case, the peak sensitivity of the photodiode is from 0.08 to 0.18 A/W at wavelengths of 0.2–0.33 µm. This is in line with experimental results taken from the relevant literature.Ternary AlGaN alloys with a band gap of 3.4 to 6.2 eV are very promising for photodetectors in the UV wavelength range. Using the COMSOL MULTIPHYSICS software based on AlGaN, a p-i-n photodiode model was developed, including its I–V characteristic, spectral sensitivity of the received radiation, absorption coefficient as a function of the aluminum fraction and the depletion layer thickness. To calculate the process of interaction of a semiconductor with EM radiation, we used a model based on the use of an element of the transition matrix through the carrier lifetime during spontaneous recombination. In this case, the peak sensitivity of the photodiode is from 0.08 to 0.18 A/W at wavelengths of 0.2–0.33 µm. This is in line with experimental results taken from the relevant literature

CONVERGENCE OF AMERICAN OPTION VALUES FROM DISCRETE- TO CONTINUOUS-TIME FINANCIAL MODELS 1

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75553/1/j.1467-9965.1994.tb00059.x.pd

A comparison of 3D particle, fluid and hybrid simulations for negative streamers

In the high field region at the head of a discharge streamer, the electron energy distribution develops a long tail. In negative streamers, these electrons can run away and contribute to energetic processes such as terrestrial gamma-ray and electron flashes. Moreover, electron density fluctuations can accelerate streamer branching. To track energies and locations of single electrons in relevant regions, we have developed a 3D hybrid model that couples a particle model in the region of high fields and low electron densities with a fluid model in the rest of the domain. Here we validate our 3D hybrid model on a 3D (super-)particle model for negative streamers in overvolted gaps, and we show that it almost reaches the computational efficiency of a 3D fluid model. We also show that the extended fluid model approximates the particle and the hybrid model well until stochastic fluctuations become important, while the classical fluid model underestimates velocities and ionization densities. We compare density fluctuations and the onset of branching between the models, and we compare the front velocities with an analytical approximation

Optimal treatment allocations in space and time for on-line control of an emerging infectious disease

A key component in controlling the spread of an epidemic is deciding where, whenand to whom to apply an intervention.We develop a framework for using data to informthese decisionsin realtime.We formalize a treatment allocation strategy as a sequence of functions, oneper treatment period, that map up-to-date information on the spread of an infectious diseaseto a subset of locations where treatment should be allocated. An optimal allocation strategyoptimizes some cumulative outcome, e.g. the number of uninfected locations, the geographicfootprint of the disease or the cost of the epidemic. Estimation of an optimal allocation strategyfor an emerging infectious disease is challenging because spatial proximity induces interferencebetween locations, the number of possible allocations is exponential in the number oflocations, and because disease dynamics and intervention effectiveness are unknown at outbreak.We derive a Bayesian on-line estimator of the optimal allocation strategy that combinessimulation–optimization with Thompson sampling.The estimator proposed performs favourablyin simulation experiments. This work is motivated by and illustrated using data on the spread ofwhite nose syndrome, which is a highly fatal infectious disease devastating bat populations inNorth America

Quadratic optimal functional quantization of stochastic processes and numerical applications

In this paper, we present an overview of the recent developments of functional quantization of stochastic processes, with an emphasis on the quadratic case. Functional quantization is a way to approximate a process, viewed as a Hilbert-valued random variable, using a nearest neighbour projection on a finite codebook. A special emphasis is made on the computational aspects and the numerical applications, in particular the pricing of some path-dependent European options.Comment: 41 page

A systematic review of oil tanker truck disasters: Identifying prevention targets

Introduction: Oil tanker truck disasters have been reported worldwide; however, the circumstances, causes, and health effects of these disasters have not been described. To address this gap, we performed a systematic review using PRISMA criteria to better understand this public health problem and identify prevention targets. Methods: The academic and lay literatures were systematically searched for terms related to oil tanker truck disasters. Reports about civilian oil tanker truck disasters that occurred from 1997–2017 were included. Details about the disasters were summarized, including circumstances, identifiable causes, and health effects. Results: The search yielded 4713 Nexis Uni articles, 199 Google results, and one PubMed article; 951 records met inclusion criteria, describing 224 oil tanker truck explosions or fires. At least 2909 people died as a result of these disasters, and 3038 additional people were hospitalized. Almost all deaths (94%) occurred in low- and low-middle-income countries (LMIC). This may largely be due to scooping – the practice of collecting spilled oil from disabled tanker trucks for use or resale. Using the Haddon matrix, potential targets for future disaster prevention were identified. Conclusions: These data highlight the circumstances, causes, and health burden related to oil tanker truck disasters. Most began as collisions or rollovers, but nearly half of the fatalities involved scooping. The findings suggest opportunities to promote road safety, improve scene safety and security protocols used by drivers and first responders, and promote public understanding of the dangers of scooping to prevent mass casualty disasters from disabled tanker trucks, particularly in LMIC

A Quantum Langevin Formulation of Risk-Sensitive Optimal Control

In this paper we formulate a risk-sensitive optimal control problem for continuously monitored open quantum systems modelled by quantum Langevin equations. The optimal controller is expressed in terms of a modified conditional state, which we call a risk-sensitive state, that represents measurement knowledge tempered by the control purpose. One of the two components of the optimal controller is dynamic, a filter that computes the risk-sensitive state. The second component is an optimal control feedback function that is found by solving the dynamic programming equation. The optimal controller can be implemented using classical electronics. The ideas are illustrated using an example of feedback control of a two-level atom

Gate complexity using dynamic programming

The relationship between efficient quantum gate synthesis and control theory has been a topic of recent interest in the quantum computing literature. Motivated by this work, we describe how the dynamic programming technique from optimal control may be used in principle to determine gate complexity and for the optimal synthesis of quantum circuits. We illustrate the dynamic programming methodology using a simple example on the Lie group SU(2)