Essays about: "fundamentala värden"

Showing result 1 - 5 of 8 essays containing the words fundamentala värden.

  1. 1. Exploring New Physics Through Collider and Gravitational Wave Measurements with Artificial Neural Networks: the Case Study of QCD-like Technicolor

    University essay from Lunds universitet/Fysiska institutionen; Lunds universitet/Teoretisk partikelfysik - Geonomgår omorganisation

    Author : Ashar Ahmed Kamal; [2023]
    Keywords : Artificial Neural Networks; ANN; Beyond the Standard Model; BSM; parameter space scan; Physics and Astronomy;

    Abstract : With physicists actively exploring Beyond the Standard Model (BSM) theories that may fill in the gaps of the Standard Model (SM), a fundamental question arises: which parameters hold physical significance? In this thesis, we present our initial progress towards the development of a model-independent artificial intelligence framework designed for conducting parameter space scans in BSM scenarios. Our framework incorporates several publicly available high-energy physics packages, namely SPheno, HiggsBounds, HiggsSignals, and CosmoTransitions. READ MORE

  2. 2. Photophysics of the polymer acceptor PF5-Y5 in organic photovoltaics : A first principles theory based study

    University essay from Karlstads universitet/Institutionen för ingenjörsvetenskap och fysik (from 2013)

    Author : Anton Almén; [2022]
    Keywords : PF5-Y5; Non-fullerene-acceptor; NFA; polymer; fundamental; optical; gap; oxidation; reduction; exciton; binding; energy; oligomer; length; PF5-Y5; Non-fullerene-acceptor; NFA; polymer; fundamentalt; optiskt; gap; oxidation; reduktion; exciton; binding; energi; oligomerlängd;

    Abstract : Non-fullerene Acceptors (NFAs) have gathered a great deal of interest for use inorganic photovoltaics (OPVs) due to recent breakthroughs in their power conversion efficiency and other advantages they offer over their Fullerene-based counterparts. In this work, a new promising non-fullerene polymer acceptor, PF5-Y5, have been studied using density functional theory and time-dependent density functional theory; and the effects that oligomer length, geometry relaxation and exchange-correlation interaction has on the exciton binding energies (the difference between optical and fundamental energy gaps) have been investigated. READ MORE

  3. 3. Measuring the impact of noise on quantum Fourier transforms

    University essay from KTH/Datavetenskap

    Author : Arami Alfarhani; Elias Gustafsson; [2022]
    Keywords : ;

    Abstract : The field of quantum computing has progressed quickly during recent years, but errors caused by quantum noise still remain as a major issue that prevents accurate computations from being performed on quantum computers. In this study, we measure the impact that these errors have on one of the most fundamental quantum operations, the quantum Fourier transform. READ MORE

  4. 4. Parametric Study of Separation in Outlet Diffuser of Rocket Nozzle Cooling Channel Rig : The Effect of Heat Flux and Angle of Outlet Diffuser for Rectangular-to-Circular Cross Section Transitions

    University essay from KTH/Farkostteknik och Solidmekanik; KTH/Kraft- och värmeteknologi

    Author : Hector Älfvåg; [2021]
    Keywords : ;

    Abstract : The use of natural gas with high methane content as rocket fuel has gained substantial industrial attention over the past number of years. Several actors including SpaceX and Blue Origin are developing natural gas powered rocket engines. READ MORE

  5. 5. Using Neural Networks to Probe the Parameter Space of a 3HDM with a U(1) times Z2 Flavor Symmetry

    University essay from Lunds universitet/Teoretisk partikelfysik - Geonomgår omorganisation

    Author : Ludvig Siwe; [2020]
    Keywords : Three Higgs Doublet Model; 3HDM; Machine Learning; Neural Network; Genetic Algorithm; Physics and Astronomy;

    Abstract : Probing the physical regions in large parameter spaces of typical Standard Model (SM) extensions can be a very difficult computational task. In this thesis project, a new framework has been developed that utilises well-known Machine Learning (ML) techniques in the form of neural networks trained by a genetic algorithm. READ MORE