2 resultados para Model-based optimization

em CaltechTHESIS


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In the first part of this thesis we search for beyond the Standard Model physics through the search for anomalous production of the Higgs boson using the razor kinematic variables. We search for anomalous Higgs boson production using proton-proton collisions at center of mass energy √s=8 TeV collected by the Compact Muon Solenoid experiment at the Large Hadron Collider corresponding to an integrated luminosity of 19.8 fb-1.

In the second part we present a novel method for using a quantum annealer to train a classifier to recognize events containing a Higgs boson decaying to two photons. We train that classifier using simulated proton-proton collisions at √s=8 TeV producing either a Standard Model Higgs boson decaying to two photons or a non-resonant Standard Model process that produces a two photon final state.

The production mechanisms of the Higgs boson are precisely predicted by the Standard Model based on its association with the mechanism of electroweak symmetry breaking. We measure the yield of Higgs bosons decaying to two photons in kinematic regions predicted to have very little contribution from a Standard Model Higgs boson and search for an excess of events, which would be evidence of either non-standard production or non-standard properties of the Higgs boson. We divide the events into disjoint categories based on kinematic properties and the presence of additional b-quarks produced in the collisions. In each of these disjoint categories, we use the razor kinematic variables to characterize events with topological configurations incompatible with typical configurations found from standard model production of the Higgs boson.

We observe an excess of events with di-photon invariant mass compatible with the Higgs boson mass and localized in a small region of the razor plane. We observe 5 events with a predicted background of 0.54 ± 0.28, which observation has a p-value of 10-3 and a local significance of 3.35σ. This background prediction comes from 0.48 predicted non-resonant background events and 0.07 predicted SM higgs boson events. We proceed to investigate the properties of this excess, finding that it provides a very compelling peak in the di-photon invariant mass distribution and is physically separated in the razor plane from predicted background. Using another method of measuring the background and significance of the excess, we find a 2.5σ deviation from the Standard Model hypothesis over a broader range of the razor plane.

In the second part of the thesis we transform the problem of training a classifier to distinguish events with a Higgs boson decaying to two photons from events with other sources of photon pairs into the Hamiltonian of a spin system, the ground state of which is the best classifier. We then use a quantum annealer to find the ground state of this Hamiltonian and train the classifier. We find that we are able to do this successfully in less than 400 annealing runs for a problem of median difficulty at the largest problem size considered. The networks trained in this manner exhibit good classification performance, competitive with the more complicated machine learning techniques, and are highly resistant to overtraining. We also find that the nature of the training gives access to additional solutions that can be used to improve the classification performance by up to 1.2% in some regions.

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The overarching theme of this thesis is mesoscale optical and optoelectronic design of photovoltaic and photoelectrochemical devices. In a photovoltaic device, light absorption and charge carrier transport are coupled together on the mesoscale, and in a photoelectrochemical device, light absorption, charge carrier transport, catalysis, and solution species transport are all coupled together on the mesoscale. The work discussed herein demonstrates that simulation-based mesoscale optical and optoelectronic modeling can lead to detailed understanding of the operation and performance of these complex mesostructured devices, serve as a powerful tool for device optimization, and efficiently guide device design and experimental fabrication efforts. In-depth studies of two mesoscale wire-based device designs illustrate these principles—(i) an optoelectronic study of a tandem Si|WO3 microwire photoelectrochemical device, and (ii) an optical study of III-V nanowire arrays.

The study of the monolithic, tandem, Si|WO3 microwire photoelectrochemical device begins with development and validation of an optoelectronic model with experiment. This study capitalizes on synergy between experiment and simulation to demonstrate the model’s predictive power for extractable device voltage and light-limited current density. The developed model is then used to understand the limiting factors of the device and optimize its optoelectronic performance. The results of this work reveal that high fidelity modeling can facilitate unequivocal identification of limiting phenomena, such as parasitic absorption via excitation of a surface plasmon-polariton mode, and quick design optimization, achieving over a 300% enhancement in optoelectronic performance over a nominal design for this device architecture, which would be time-consuming and challenging to do via experiment.

The work on III-V nanowire arrays also starts as a collaboration of experiment and simulation aimed at gaining understanding of unprecedented, experimentally observed absorption enhancements in sparse arrays of vertically-oriented GaAs nanowires. To explain this resonant absorption in periodic arrays of high index semiconductor nanowires, a unified framework that combines a leaky waveguide theory perspective and that of photonic crystals supporting Bloch modes is developed in the context of silicon, using both analytic theory and electromagnetic simulations. This detailed theoretical understanding is then applied to a simulation-based optimization of light absorption in sparse arrays of GaAs nanowires. Near-unity absorption in sparse, 5% fill fraction arrays is demonstrated via tapering of nanowires and multiple wire radii in a single array. Finally, experimental efforts are presented towards fabrication of the optimized array geometries. A hybrid self-catalyzed and selective area MOCVD growth method is used to establish morphology control of GaP nanowire arrays. Similarly, morphology and pattern control of nanowires is demonstrated with ICP-RIE of InP. Optical characterization of the InP nanowire arrays gives proof of principle that tapering and multiple wire radii can lead to near-unity absorption in sparse arrays of InP nanowires.