PPT-Stochastic Particle Acceleration in High Energy Astrophysical Sources

Siming Liu University of Glasgow Collaborators Vahe Petrosian Yanwei Jiang Stanford University Zhonghui Fan Yunnan University Oct 2008 Krakow Poland Outline I Observations Distribution. N is the process noise or disturbance at time are IID with 0 is independent of with 0 Linear Quadratic Stochastic Control 52 brPage 3br Control policies statefeedback control 0 N called the control policy at time roughly speaking we choo Acceleration Mechanisms. 1. Acceleration Mechanisms. There is clear observational evidence that hadrons and electrons are accelerated to extreme energies by astrophysical objects. direct evidence: charged cosmic rays. Gradient Descent Methods. Jakub . Kone. čný. . (joint work with Peter . Richt. árik. ). University of Edinburgh. Introduction. Large scale problem setting. Problems are often structured. Frequently arising in machine learning. Part I: Multistage problems. Anupam. Gupta. Carnegie Mellon University. stochastic optimization. Question: . How to model uncertainty in the inputs?. data may not yet be available. obtaining exact data is difficult/expensive/time-consuming. (Fermi acceleration at shock: most standard, nice powerlaw, few free parameters). main . signatures to . be determined: . E. min . , . E. max. [. Ã. timescale . t. acc. (E. ) ], . spectral slope . Stochastic Calculus: Introduction . Although . stochastic . and ordinary calculus share many common properties, there are fundamental differences. The probabilistic nature of stochastic processes distinguishes them from the deterministic functions associated with ordinary calculus. Since stochastic differential equations so frequently involve Brownian motion, second order terms in the Taylor series expansion of functions become important, in contrast to ordinary calculus where they can be ignored. . Monte Carlo Tree Search. Minimax. search fails for games with deep trees, large branching factor, and no simple heuristics. Go: branching factor . 361 (19x19 board). Monte Carlo Tree Search. Instead . Galerkin. Methods and Software. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.. Processes:. An Overview. Math 182 2. nd. . sem. ay 2016-2017. Stochastic Process. Suppose. we have an index set . . We usually call this “time”. where . is a stochastic or random process . Describe the speedometer on a car that is entering a highway, drives for 25 miles and then exits the highway.. Consider the two situations below. When a shuttle bus approaches a stop, the driver begins to apply the brakes to slow down 5.0 s before actually reaching the stop. The speed changes from 9.0 m/s to 0 m/s over time.. What is acceleration?. If you’re traveling in a car at a constant speed of 50 mph, are you accelerating?. No, you’re not. . Acceleration is the rate of change of velocity. . Acceleration. In order for acceleration to occur, velocity MUST be . . Spring 2018. Introductions. Overview of Particle . Accelerators. Todd Satogata (Jefferson . Lab and ODU) . / . satogata@jlab.org. http://www.toddsatogata.net/. 2018-ODU-AP. Happy Birthday to Nina Dobrev, Dave Matthews, Jimmy Page, Joan Baez, and Vladimir Steklov!. based on the course by. Joël . Le . Duff. Many Thanks!. CAS on Advanced Level Accelerator Physics Course . Trondheim, 18-29 August 2013. Summary of the 2 lectures:. Acceleration methods. Accelerating. John Rundle . Econophysics. PHYS 250. Stochastic Processes. https://. en.wikipedia.org. /wiki/. Stochastic_process. In probability theory and related fields, a stochastic or random process is a mathematical object usually defined as a collection of random variables..