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Articles 1 - 4 of 4
Full-Text Articles in Quantum Physics
Modeling Excited State Processes In Molecular Aggregates By Constructing An Adaptive Basis For The Hierarchy Of Pure States, Leonel Varvelo
Modeling Excited State Processes In Molecular Aggregates By Constructing An Adaptive Basis For The Hierarchy Of Pure States, Leonel Varvelo
Chemistry Theses and Dissertations
Simulating excitation energy transfer (EET) in molecular materials is of crucial importance for the development of and understanding of materials such as organic photovoltaics and photosynthetic systems and further development of novel materials. The Hierarchy of Pure States (HOPS) is an exact framework for the time evolution of an open quantum system in which a hierarchy of stochastic wave functions are propagated in time. The adaptive HOPS (adHOPS) method achieves size-invariant scaling with the number of simulated molecules for sufficiently large aggregates by using an adaptive basis that moves with the excitation through the material. To demonstrate the power of …
Classification Of Pixel Tracks To Improve Track Reconstruction From Proton-Proton Collisions, Kebur Fantahun, Jobin Joseph, Halle Purdom, Nibhrat Lohia
Classification Of Pixel Tracks To Improve Track Reconstruction From Proton-Proton Collisions, Kebur Fantahun, Jobin Joseph, Halle Purdom, Nibhrat Lohia
SMU Data Science Review
In this paper, machine learning techniques are used to reconstruct particle collision pathways. CERN (Conseil européen pour la recherche nucléaire) uses a massive underground particle collider, called the Large Hadron Collider or LHC, to produce particle collisions at extremely high speeds. There are several layers of detectors in the collider that track the pathways of particles as they collide. The data produced from collisions contains an extraneous amount of background noise, i.e., decays from known particle collisions produce fake signal. Particularly, in the first layer of the detector, the pixel tracker, there is an overwhelming amount of background noise that …
Comparisons Of Performance Between Quantum And Classical Machine Learning, Christopher Havenstein, Damarcus Thomas, Swami Chandrasekaran
Comparisons Of Performance Between Quantum And Classical Machine Learning, Christopher Havenstein, Damarcus Thomas, Swami Chandrasekaran
SMU Data Science Review
In this paper, we present a performance comparison of machine learning algorithms executed on traditional and quantum computers. Quantum computing has potential of achieving incredible results for certain types of problems, and we explore if it can be applied to machine learning. First, we identified quantum machine learning algorithms with reproducible code and had classical machine learning counterparts. Then, we found relevant data sets with which we tested the comparable quantum and classical machine learning algorithm's performance. We evaluated performance with algorithm execution time and accuracy. We found that quantum variational support vector machines in some cases had higher accuracy …
Investigation Of The Effects Of Harmful Radiation On Type-Ii Strained Layer Superlattice Focal Plane Arrays Operated In The Long Wave Infrared, Patrick Fumo
Electrical Engineering Theses and Dissertations
In-situ exposure of InAs/InAsSb strained layer superlattice focal plane arrays to gamma-rays revealed the possibility of a detector capable of imaging through a total ionizing dose event. Two long wave infrared focal plane arrays were exposed to a Co60 source at dose rates of 60 Rads/s and 70 Rads/s in incremental steps up to a total accumulated dose of 30 kRads. The first device showed no degradation in dark current density with accumulated dose while the second device tested showed a small increase up to 1 kRad and minimal increases with subsequent dose steps. The primary imaging defect in …