Search for Higgs Boson Production Beyond the Standard Model Using the Razor Kinematic Variables in pp Collisions at √s=8 TeV and Optimization of Higgs Boson Identification Using a Quantum Annealer

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.

Design, Fabrication, and Mechanical Property Analysis of 3D Nanoarchitected Materials

Recent developments in micro- and nanoscale 3D fabrication techniques have enabled the creation of materials with a controllable nanoarchitecture that can have structural features spanning 5 orders of magnitude from tens of nanometers to millimeters. These fabrication methods in conjunction with nanomaterial processing techniques permit a nearly unbounded design space through which new combinations of nanomaterials and architecture can be realized. In the course of this work, we designed, fabricated, and mechanically analyzed a wide range of nanoarchitected materials in the form of nanolattices made from polymer, composite, and hollow ceramic beams. Using a combination of two-photon lithography and atomic layer deposition, we fabricated samples with periodic and hierarchical architectures spanning densities over 4 orders of magnitude from ρ=0.3-300kg/m³ and with features as small as 5nm. Uniaxial compression and cyclic loading tests performed on different nanolattice topologies revealed a range of novel mechanical properties: the constituent nanoceramics used here have size-enhanced strengths that approach the theoretical limit of materials strength; hollow aluminum oxide (Al₂O₃) nanolattices exhibited ductile-like deformation and recovered nearly completely after compression to 50% strain when their wall thicknesses were reduced below 20nm due to the activation of shell buckling; hierarchical nanolattices exhibited enhanced recoverability and a near linear scaling of strength and stiffness with relative density, with E∝ρ^1.04 and σy∝ρ^1.17 for hollow Al₂O₃ samples; periodic rigid and non-rigid nanolattice topologies were tested and showed a nearly uniform scaling of strength and stiffness with relative density, marking a significant deviation from traditional theories on “bending” and “stretching” dominated cellular solids; and the mechanical behavior across all topologies was highly tunable and was observed to strongly correlate with the slenderness λ and the wall thickness-to-radius ratio t/a of the beams. These results demonstrate the potential of nanoarchitected materials to create new highly tunable mechanical metamaterials with previously unattainable properties.