Physics Commons^™

A Model For Massless Gravitons In Radiation And Matter Dominated Universes, Ioannis Haranas, Eli Cavan, Ioannis Gkigkitzis

Physics and Computer Science Faculty Publications

A massless model of the graviton is explored by considering the minimum amount of information they can carry. The total entropy of the universe is calculated and compared to estimates from Super Massive Black holes and massive models of the graviton. The running cosmological constant is calculated using the entropy relation previously computed and compared to its experimentally accepted value. Both results are quantified considering radiation and matter dominated universes.

Making Artificial Cips Data With A Generative Adversarial Neural Network, Austin Hedges

Fall Showcase for Research and Creative Inquiry

Polar mesospheric clouds (PMCs) have been studied for thirteen years by NASA's Aeronomy of Ice in the Mesosphere (AIM) satellite. The Cloud Imaging and Particle Size (CIPS) instrument onboard AIM has taken many images of PMCs over this time. Such a large number of images makes CIPS data ideal for training neural networks which require large datasets. CIPS images were used to train a Generative Adversarial Network (GAN) to train towards being able to generate purely artificial CIPS-like images.

Modified Newtonian Dynamics Effects In A Region Dominated By Dark Matter And A Cosmological Constant Λ, Ioannis Haranas, Kristin Cobbett, Ioannis Gkigkitzis, Athanasios Alexiou, Eli Cavan

Physics and Computer Science Faculty Publications

We study the motion of a secondary celestial body under the influence of a corrected gravitational potential in a modified Newtonian dynamics scenario. Furthermore we look within the Milky-way where the first correction to the potential results from a modified Poisson equation, and includes two mew terms one of which is of the form ln(r/r_max) and the other is associated with the cosmological constant lambda L added to the Newtonian potential. The regions of influence of the two potentials are associated with regions of interested bounded by the conditions for the Newtonian potential, the logarithmic …

Finite-Time State Estimation For An Inverted Pendulum Under Input-Multiplicative Uncertainty, Sergey V. Drakunov, William Mackunis, Anu Kossery Jayaprakash, Krishna Bhavithavya Kidambi, Mahmut Reyhanoglu

Publications

A sliding mode observer is presented, which is rigorously proven to achieve finite-time state estimation of a dual-parallel underactuated (i.e., single-input multi-output) cart inverted pendulum system in the presence of parametric uncertainty. A salient feature of the proposed sliding mode observer design is that a rigorous analysis is provided, which proves finite-time estimation of the complete system state in the presence of input-multiplicative parametric uncertainty. The performance of the proposed observer design is demonstrated through numerical case studies using both sliding mode control (SMC)- and linear quadratic regulator (LQR)-based closed-loop control systems. The main contribution presented here is the rigorous …

Machine Learning Corrected Quantum Dynamics Calculations, A. Jasinski, J. Montaner, R. C. Forrey, B. H. Yang, P. C. Stancil, Naduvalath Balakrishnan, J. Dai, A. Vargas-Hernandez, R. V. Krems

Chemistry and Biochemistry Faculty Research

Quantum scattering calculations for all but low-dimensional systems at low energies must rely on approximations. All approximations introduce errors. The impact of these errors is often difficult to assess because they depend on the Hamiltonian parameters and the particular observable under study. Here, we illustrate a general, system- and approximation-independent, approach to improve the accuracy of quantum dynamics approximations. The method is based on a Bayesian machine learning (BML) algorithm that is trained by a small number of exact results and a large number of approximate calculations, resulting in ML models that can generalize exact quantum results to different dynamical …

A Physics-Based Machine Learning Study Of The Behavior Of Interstitial Helium In Single Crystal W–Mo Binary Alloys, Adib J. Samin

Faculty Publications

In this work, the behavior of dilute interstitial helium in W–Mo binary alloys was explored through the application of a first principles-informed neural network (NN) in order to study the early stages of helium-induced damage and inform the design of next generation materials for fusion reactors. The neural network (NN) was trained using a database of 120 density functional theory (DFT) calculations on the alloy. The DFT database of computed solution energies showed a linear dependence on the composition of the first nearest neighbor metallic shell. This NN was then employed in a kinetic Monte Carlo simulation, which took into …

Volume 12, Haleigh James, Hannah Meyls, Hope Irvin, Megan E. Hlavaty, Samara L. Gall, Austin J. Funk, Karyn Keane, Sarah Ghali, Antonio Harvey, Andrew Jones, Rachel Hazelwood, Madison Schmitz, Marija Venta, Haley Tebo, Jeremiah Gilmer, Bridget Dunn, Benjamin Sullivan, Mckenzie Johnson

Incite: The Journal of Undergraduate Scholarship

Introduction, Dr. Roger A. Byrne, Dean

From the Editor, Dr. Larissa "Kat" Tracy

From the Designers, Rachel English, Rachel Hanson

Immortality in the Mortal World: Otherworldly Intervention in "Lanval" and "The Wife of Bath's Tale" by Haleigh James

Analysis of Phenolic Compounds in Moroccan Olive Oils by HPLC by Hannah Meyls

Art by Hope Irvin

The Effects of Cell Phone Use on Gameplay Enjoyment and Frustration by Megan E. Hlavaty, Samara L. Gall, and Austin J. Funk

Care, No Matter What: Planned Parenthood's Use of Organizational Rhetoric to Expand its Reputation by Karyn Keane

Analysis of Petroleum Products for …

Quantum Computing And Quantum Algorithms, Daniel Serban

Senior Honors Theses

The field of quantum computing and quantum algorithms is studied from the ground up. Qubits and their quantum-mechanical properties are discussed, followed by how they are transformed by quantum gates. From there, quantum algorithms are explored as well as the use of high-level quantum programming languages to implement them. One quantum algorithm is selected to be implemented in the Qiskit quantum programming language. The validity and success of the resulting computation is proven with matrix multiplication of the qubits and quantum gates involved.

Defect-Free Plastic Deformation Through Dimensionality Reduction And Self-Annihilation Of Topological Defects In Crystalline Solids, Yipeng Gao, Yongfeng Zhang, Larry K. Aagesen, Jianguo Yu, Min Long, Yunzhi Wang

Computer Science Faculty Publications and Presentations

As a signature of symmetry-breaking processes, the generation and annihilation of topological defects (domain walls, strings, etc.) are of great interest in condensed matter physics and cosmology. Here we propose a distinctive self-organization process through phase transitions, in which all the generated topological defects are dimensionality reduced and self-annihilated. In crystalline solids, such a unique mechanism allows a perfect single crystal after plastic deformation, which originates from the coupling of different types of broken symmetries.

Dynamics And Stability Of The Two Body Problem With Yukawa Correction, Eli Cavan, Ioannis Haranas, Ioannis Gkigkitzis

Physics and Computer Science Faculty Publications

We explore the dynamics and stability of the two body problem by modifying the Newtonian potential with the Yukawa potential. This model may be considered a theory of modified gravity; where the interaction is not simply the kepler solution for large distance. The stability is investigated by deriving the Jacobian of the linearized matrix equation and evaluating the eigenvalues of the various equilibrium points calculated during the analysis. The subcases of a purely Yukawa and purely Newtonian potential are also explored.

Agenda, Shubha Tewari

Science and Engineering Saturday Seminars

Abstracts for six Science and Engineering Saturday Seminars.

Arduino Microcontrollers In The Classroom: Teaching How To Phrase Effective Science Questions And How To Answer Them With Original Data, Tony Dinsmore

Science and Engineering Saturday Seminars

Arduino microcontrollers in the classroom: teaching how to phrase effective science questions and how to answer them with original data. Prof. Tony Dinsmore, UMass Physics This workshop will develop course modules that address a challenge in the science curriculum: how do we teach basic problem-solving and curiosity-based research skills in a classroom setting? The standard science curriculum teaches concepts and theory quite well but leaves rather little opportunity for students to take the lead in designing and implementing their own investigations. The workshop will use the Arduino, an inexpensive microcontroller that is simple to set up. A huge range of …

Svat4: A Computer Program For Visualization And Analysis Of Crystal Structures, Xingzhong Li

Nebraska Center for Materials and Nanoscience: Faculty Publications

SVAT4 is a computer program for interactive visualization of three-dimensional crystal structures, including chemical bonds and magnetic moments. A wide range of functions, e.g. revealing atomic layers and polyhedral clusters, are available for further structural analysis. Atomic sizes, colors, appearance, view directions and view modes (orthographic or perspective views) are adjustable. Customized work for the visualization and analysis can be saved and then reloaded. SVAT4 provides a template to simplify the process of preparation of a new data file. SVAT4 can generate high-quality images for publication and animations for presentations. The usability of SVAT4 is broadened by a software suite …

Analytic Threads - Annual Newsletters 2014-2020, Messiah University

Educator Scholarship & Departmental Newsletters

Faculty and student updates. Analytic Threads is the annual newsletter of the Department of Computing, Mathematics and Physics at Messiah University. It is sent annually to alumni and is also available electronically at the website messiah.edu/cmp

Need For Simplicity And Everything Is A Matter Of Degree: How Zadeh's Philosophy Is Related To Kolmogorov Complexity, Quantum Physics, And Deep Learning, Vladik Kreinovich, Olga Kosheleva, Andres Ortiz-Muñoz

Departmental Technical Reports (CS)

Many people remember Lofti Zadeh's mantra -- that everything is a matter of degree. This was one of the main principles behind fuzzy logic. What is somewhat less remembered is that Zadeh also used another important principle -- that there is a need for simplicity. In this paper, we show that together, these two principles can generate the main ideas behind such various subjects as Kolmogorov complexity, quantum physics, and deep learning. We also show that these principles can help provide a better understanding of an important notion of space-time causality.

Nis2 As A Broadband Saturable Absorber For Ultrafast Pulse Lasers, Pengfei Wang, Han Zhang, Yu Yin, Qiuyun Ouyang, Yujin Chen, Elfed Lewis, Gerald Farrell, Masaki Tokurakawa, Sulaiman Wadi Harun, Cong Wang, Shi Li

Articles

Nickel disulfide (NiS2) has recently been found to possess strong nonlinear saturable absorption properties. This feature is highly attractive for nonlinear photonics applications. Ultrafast pulse generation is successfully demonstrated in this article for both Ytterbium- and Erbium-doped fibre lasers using micro-fibre deposited nickel disulfide (NiS2) as a saturable absorber (SA). The fabricated SA device has a modulation depth of 23% at 1.06 μm and 30.8% at 1.55 μm. Stable dissipative soliton operation was achieved at 1064.5 nm with a pulse duration of 11.7 ps and another stable conventional soliton pulse train was also obtained at 1560.2 nm with a pulse …

Special Section Guest Editorial: Machine Learning In Optics, Jonathan Howe, Travis Axtell, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

This guest editorial summarizes the Special Section on Machine Learning in Optics.