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Articles 1 - 3 of 3
Full-Text Articles in Condensed Matter Physics
A Study Of Neural Networks For The Quantum Many-Body Problem, Liam B. Schramm
A Study Of Neural Networks For The Quantum Many-Body Problem, Liam B. Schramm
Senior Projects Spring 2018
One of the fundamental problems in analytically approaching the quantum many-body problem is that the amount of information needed to describe a quantum state. As the number of particles in a system grows, the amount of information needed for a full description of the system increases exponentially. A great deal of work then has gone into finding efficient approximate representations of these systems. Among the most popular techniques are Tensor Networks and Quantum Monte Carlo methods. However, one new method with a number of promising theoretical guarantees is the Neural Quantum State. This method is an adaptation of the Restricted …
Photovoltaics: An Investigation Into The Origins Of Efficiency On All Scales, Jeremy Alexander Bannister
Photovoltaics: An Investigation Into The Origins Of Efficiency On All Scales, Jeremy Alexander Bannister
Senior Projects Spring 2016
This project is comprised of a set of parallel investigations, which share the common mo- tivation of increasing the efficiency of photovoltaics. First, the reader is introduced to core concepts of photovoltaic energy conversion via a semi-classical description of the phys- ical system. Second, a key player in photovoltaic efficiency calculations, the exciton, is discussed in greater quantum mechanical detail. The reader will be taken through a nu- merical derivation of the low-energy exciton states in various geometries, including a line segment, a circle and a sphere. These numerical calculations are done using Mathematica, a computer program which, due to …
Muscle: A Simulation Toolkit Modeling Low Energy Muon Beam Transport In Crystals, Nazmus Saquib
Muscle: A Simulation Toolkit Modeling Low Energy Muon Beam Transport In Crystals, Nazmus Saquib
Senior Projects Spring 2011
The project involves the development of MUSCLE (MUonS Cascade at Low Energy), a collection of programs written in C++ and Mathematica to numerically simulate the passage of low energy muon beams through crystals. Monte Carlo methods employing binary collision approximation calculations and appropriate molecular dynamics algorithms are implemented to construct the trajectories and determine the spatial distribution of stopped muons in single crystals. Channeling of muon particles along certain crystal planes are also found. Binary collision approximation and molecular dynamics algorithms are compared and the possible effect of channeling is discussed.