Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
- Publication
- Publication Type
Articles 1 - 5 of 5
Full-Text Articles in Quantum Physics
Noncontextuality Inequalities From Antidistinguishability, Matthew S. Leifer, Cristhiano Duarte
Noncontextuality Inequalities From Antidistinguishability, Matthew S. Leifer, Cristhiano Duarte
Mathematics, Physics, and Computer Science Faculty Articles and Research
Noncontextuality inequalities are usually derived from the distinguishability properties of quantum states, i.e., their orthogonality. Here, we show that antidistinguishability can also be used to derive noncontextuality inequalities. The Yu-Oh 13-ray noncontextuality inequality can be rederived and generalized as an instance of our antidistinguishability method. For some sets of states, the antidistinguishability method gives tighter bounds on noncontextual models than just considering orthogonality, and the Hadamard states provide an example of this. We also derive noncontextuality inequalities based on mutually unbiased bases and symmetric informationally complete positive operator-valued measures. Antidistinguishability based inequalities were initially discovered as overlap bounds for the …
Magnetic Forces In The Absence Of A Classical Magnetic Field, Ismael L. Paiva, Yakir Aharonov, Jeff Tollaksen, Mordecai Waegell
Magnetic Forces In The Absence Of A Classical Magnetic Field, Ismael L. Paiva, Yakir Aharonov, Jeff Tollaksen, Mordecai Waegell
Mathematics, Physics, and Computer Science Faculty Articles and Research
It is shown that, in some cases, the effect of discrete distributions of flux lines in quantum mechanics can be associated with the effect of continuous distributions of magnetic fields with special symmetries. In particular, flux lines with an arbitrary value of magnetic flux can be used to create energetic barriers, which can be used to confine quantum systems in specially designed configurations. This generalizes a previous work where such energy barriers arose from flux lines with half-integer fluxons. Furthermore, it is shown how the Landau levels can be obtained from a two-dimensional grid of flux lines. These results suggest …
Density Functional Theory Study Of Two-Dimensional Boron Nitride Films, Pradip R. Niraula
Density Functional Theory Study Of Two-Dimensional Boron Nitride Films, Pradip R. Niraula
Dissertations, Theses, and Capstone Projects
Since graphene was isolated in 2004, the number of two-dimensional (2D) materials and their scientific relevance have grown exponentially. Besides graphene, one of the most important and technolocially promizing 2D materials that has emerged in recent years is hexagonal boron nitride, in its monolayer or multilayer form. In my thesis work, I used density functional theory (DFT) calculations to investigate the properties of boron nitride films. In particular, I first studied the properties (i.e. formation energy, defect states, and structure) of point charged defects in monolayer and bilayer hexagonal boron nitride, and subsequently, I focused on the linear and nonlinear …
Dual-Axis Solar Tracker, Bryan Kennedy
Dual-Axis Solar Tracker, Bryan Kennedy
All Undergraduate Projects
Renewable energies, and fuels that are not fossil fuel-based, are one of the prolific topics of debate in modern society. With climate change now becoming a primary focus for scientists and innovators of today, one of the areas for the largest amount of potential and growth is that of the capturing and utilization of Solar Energy. This method involves using a mechanical system to track the progression of the sun as it traverses the sky throughout the day. A dual-axis solar tracker such as the one designed and built for this project, can follow the sun both azimuthally and in …
Recent Developments In The Pyscf Program Package, Qiming Sun, Xing Zhang, Samragni Banerjee, Peng Bao, Marc Barbry, Nick S. Blunt, Nikolay A. Bogdanov, George H. Booth, Jia Chen, Zhi-Hao Cui, Janus J. Eriksen, Yang Gao, Sheng Gun, Jan Hermann, Matthew R. Hermes, Kevin Koh, Peter Koval, Susi Lehtola, Zhendong Li, Junzi Liu, Narbe Mardirossian, James D. Mcclain, Mario Motta, Bastien Mussard, Hung Q. Pham, Artem Pulkin, Wirawan Purwanto, Paul J. Robinson, Enrico Ronca, Elvira R. Sayfutyarova, Maximillian Scheurer, Henry F. Schurkus, James E.T. Smith, Chong Sun, Shi-Ning Sun, Shiv Upadhyay, Lucas K. Wagner, Xiao Wang, Alec White, James Daniel Whitfield, Mark J. Williamson, Sebastian Wouters, Jun Yang, Jason M. Yu, Tianyu Zhu, Timothy C. Berkelbach, Sandeep Sharma, Alexander Yu Sokolov, Garnet Kin-Lic Chan
Recent Developments In The Pyscf Program Package, Qiming Sun, Xing Zhang, Samragni Banerjee, Peng Bao, Marc Barbry, Nick S. Blunt, Nikolay A. Bogdanov, George H. Booth, Jia Chen, Zhi-Hao Cui, Janus J. Eriksen, Yang Gao, Sheng Gun, Jan Hermann, Matthew R. Hermes, Kevin Koh, Peter Koval, Susi Lehtola, Zhendong Li, Junzi Liu, Narbe Mardirossian, James D. Mcclain, Mario Motta, Bastien Mussard, Hung Q. Pham, Artem Pulkin, Wirawan Purwanto, Paul J. Robinson, Enrico Ronca, Elvira R. Sayfutyarova, Maximillian Scheurer, Henry F. Schurkus, James E.T. Smith, Chong Sun, Shi-Ning Sun, Shiv Upadhyay, Lucas K. Wagner, Xiao Wang, Alec White, James Daniel Whitfield, Mark J. Williamson, Sebastian Wouters, Jun Yang, Jason M. Yu, Tianyu Zhu, Timothy C. Berkelbach, Sandeep Sharma, Alexander Yu Sokolov, Garnet Kin-Lic Chan
University Administration Publications
PySCF is a Python-based general-purpose electronic structure platform that supports first-principles simulations of molecules and solids as well as accelerates the development of new methodology and complex computational workflows. This paper explains the design and philosophy behind PySCF that enables it to meet these twin objectives. With several case studies, we show how users can easily implement their own methods using PySCF as a development environment. We then summarize the capabilities of PySCF for molecular and solid-state simulations. Finally, we describe the growing ecosystem of projects that use PySCF across the domains of quantum chemistry, materials science, machine learning, and …