Sökning: "computational physics"
Visar resultat 1 - 5 av 160 uppsatser innehållade orden computational physics.
1. Optical Communication using Nanowires and Molecular Memory Systems
Master-uppsats, Lunds universitet/Fysiska institutionen; Lunds universitet/SynkrotronljusfysikSammanfattning : Neuromorphic computational networks, inspired by biological neural networks, provide a possible way of lowering computational energy cost, while at the same time allowing for much more sophisticated devices capable of real-time inferences and learning. Since simulating artificial neural networks on conventional computers is particularly inefficient, the development of neuromorphic devices is strongly motivated as the reliance on AI-models increases. LÄS MER
2. Brain morphometry in Parkinson’s disease
Master-uppsats,Sammanfattning : Abstract Purpose The purpose of this brain morphometry study was to examine the volumes of different regions of the brain by research participants with Parkinson’s disease. Method To carry out the study, MR (magnetic resonance) images from 956 research participants from the Parkinson’s Progression Markers Initiative (PPMI) were used. LÄS MER
3. Fitting a photospheric prompt emission model to GRB data: The Kompaneets RMS approximation (KRA)
Master-uppsats, KTH/FysikSammanfattning : Gamma-ray bursts (GRBs) are some of the most energetic events in the universe. Shocks occurring below the photosphere are likely radiation mediated shocks (RMSs) and are suspected to shape the spectra. Due to computational costs of simulating RMSs, models had not been fitted to data and a faster model was needed. LÄS MER
4. Exploring time-extended complexity measures in magnetic systems
L3-uppsats, Uppsala universitet/MaterialteoriSammanfattning : Complexity, a fundamental concept in physics, encompasses phenomena spanning atomic to cosmic scales. The natural emergence of complexity can be explained by self-organized criticality. In this work, two complexity measures in magnetic systems are explored. LÄS MER
5. Evaluation of Physics Informed Neural Networks in engineering simple structural analysis problems
Master-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : Neural Networks have found many applications for a long time in Machine Learning in different disciplines, and have especially flourished in the last decade because of the ever-increasing processing power especially from GPUs. Because of their ability to operate as universal function approximators and model nonlinear processes, attempts have been made in recent years to be also used for modeling partial differential equation (PDE) solutions. LÄS MER