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Full-Text Articles in Physics

Statistical Characteristics Of High-Frequency Gravity Waves Observed By An Airglow Imager At Andes Lidar Observatory, Alan Z. Liu, Bing Cao May 2022

Statistical Characteristics Of High-Frequency Gravity Waves Observed By An Airglow Imager At Andes Lidar Observatory, Alan Z. Liu, Bing Cao

Publications

The long-term statistical characteristics of high-frequency quasi-monochromatic gravity waves are presented using multi-year airglow images observed at Andes Lidar Observatory (ALO, 30.3° S, 70.7° W) in northern Chile. The distribution of primary gravity wave parameters including horizontal wavelength, vertical wavelength, intrinsic wave speed, and intrinsic wave period are obtained and are in the ranges of 20–30 km, 15–25 km, 50–100 m s−1, and 5–10 min, respectively. The duration of persistent gravity wave events captured by the imager approximately follows an exponential distribution with an average duration of 7–9 min. The waves tend to propagate against the local background winds and …


Measuring Localization Confidence For Quantifying Accuracy And Heterogeneity In Single-Molecule Super-Resolution Microscopy, Hesam Mazidi, Tianben Ding, Arye Nehorai, Matthew D. Lew Feb 2020

Measuring Localization Confidence For Quantifying Accuracy And Heterogeneity In Single-Molecule Super-Resolution Microscopy, Hesam Mazidi, Tianben Ding, Arye Nehorai, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

We present a computational method, termed Wasserstein-induced flux (WIF), to robustly quantify the accuracy of individual localizations within a single-molecule localization microscopy (SMLM) dataset without ground- truth knowledge of the sample. WIF relies on the observation that accurate localizations are stable with respect to an arbitrary computational perturbation. Inspired by optimal transport theory, we measure the stability of individual localizations and develop an efficient optimization algorithm to compute WIF. We demonstrate the advantage of WIF in accurately quantifying imaging artifacts in high-density reconstruction of a tubulin network. WIF represents an advance in quantifying systematic errors with unknown and complex distributions, …


An Evolutionary Vaccination Game In The Modified Activity Driven Network By Considering The Closeness, Dun Han, Mei Sun Sep 2015

An Evolutionary Vaccination Game In The Modified Activity Driven Network By Considering The Closeness, Dun Han, Mei Sun

Publications and Research

In this paper, we explore an evolutionary vaccination game in the modified activity driven network by considering the closeness. We set a closeness parameter p which is used to describe the way of connection between two individuals. The simulation results show that the closeness p may have an active role in weakening both the spreading of epidemic and the vaccination. Besides, when vaccination is not allowed, the final recovered density increases with the value of the ratio of the infection rate to the recovery rate λ/μ. However, when vaccination is allowed the final density of recovered individual first increases and …


Spin Glass Reflection Of The Decoding Transition For Quantum Error Correcting Codes, Alexey Kovalev, Leonid P. Pryadko Jan 2015

Spin Glass Reflection Of The Decoding Transition For Quantum Error Correcting Codes, Alexey Kovalev, Leonid P. Pryadko

Department of Physics and Astronomy: Faculty Publications

We study the decoding transition for quantum error correcting codes with the help of a mapping to random-bond Wegner spin models. Families of quantum low density parity-check (LDPC) codes with a finite decoding threshold lead to both known models (e.g., random bond Ising and random plaquette Z2 gauge models) as well as unexplored earlier generally non-local disordered spin models with non-trivial phase diagrams. The decoding transition corresponds to a transition from the ordered phase by proliferation of "post-topological" extended defects which generalize the notion of domain walls to non-local spin models. In recently discovered quantum LDPC code families with …


Modeling A Sensor To Improve Its Efficacy, Nabin K. Malakar, Daniil Gladkov, Kevin H. Knuth May 2013

Modeling A Sensor To Improve Its Efficacy, Nabin K. Malakar, Daniil Gladkov, Kevin H. Knuth

Physics Faculty Scholarship

Robots rely on sensors to provide them with information about their surroundings. However, high-quality sensors can be extremely expensive and cost-prohibitive. Thus many robotic systems must make due with lower-quality sensors. Here we demonstrate via a case study how modeling a sensor can improve its efficacy when employed within a Bayesian inferential framework. As a test bed we employ a robotic arm that is designed to autonomously take its own measurements using an inexpensive LEGO light sensor to estimate the position and radius of a white circle on a black field. The light sensor integrates the light arriving from a …


Implementation Of Uncertainty Propagation In Triton/Keno, Charlotta Sanders, Denis Beller Jan 2008

Implementation Of Uncertainty Propagation In Triton/Keno, Charlotta Sanders, Denis Beller

Reactor Campaign (TRP)

Monte Carlo methods are beginning to be used for three dimensional fuel depletion analyses to compute various quantities of interest, including isotopic compositions of used nuclear fuel. The TRITON control module, available in the SCALE 5.1 code system, can perform three-dimensional (3-D) depletion calculations using either the KENO V.a or KENO-VI Monte Carlo transport codes, as well as the two-dimensional (2-D) NEWT discrete ordinates code. To overcome problems such as spatially nonuniform neutron flux and non-uniform statistical uncertainties in computed reaction rates and to improve the fidelity of calculations using Monte Carlo methods, uncertainty propagation is needed for depletion calculations.


Monaco/Mavric Evaluation For Facility Shielding And Dose Rate Analysis, Charlotta Sanders, Denis Beller Jan 2008

Monaco/Mavric Evaluation For Facility Shielding And Dose Rate Analysis, Charlotta Sanders, Denis Beller

Reactor Campaign (TRP)

The dimensions and the large amount of shielding required for Global Nuclear Energy Partnership (GNEP) facilities, advanced radiation shielding, and dose computation techniques are beyond today’s capabilities and will certainly be required. With the Generation IV Nuclear Energy System Initiative, it will become increasingly important to be able to accurately model advanced Boiling Water Reactor and Pressurized Water Reactor facilities, and to calculate dose rates at all locations within a containment (e.g., resulting from radiations from the reactor as well as the from the primary coolant loop) and adjoining structures (e.g., from the spent fuel pool).

The MAVRIC sequence is …


Implementation Of Uncertainty Propagation In Triton/Keno: To Support The Global Nuclear Energy Partnership, Charlotta Sanders, Denis Beller Oct 2007

Implementation Of Uncertainty Propagation In Triton/Keno: To Support The Global Nuclear Energy Partnership, Charlotta Sanders, Denis Beller

Reactor Campaign (TRP)

Monte Carlo methods are beginning to be used for three-dimensional fuel depletion analyses to compute various quantities of interest, including isotopic compositions of used fuel.1 The TRITON control module, available in the SCALE 5.1 code system, can perform three dimensional (3-D) depletion calculations using either the KENO V.a or KENO-VI Monte Carlo transport codes, as well as the two-dimensional (2- D) NEWT discrete ordinates code. For typical reactor systems, the neutron flux is not spatially uniform. For Monte Carlo simulations, this results in non-uniform statistical uncertainties in the computed reaction rates. For spatial regions where the flux is low, e.g., …


Monaco/Mavric Evaluation For Facility Shielding And Dose Rate Analysis: To Support The Global Nuclear Energy Partnership, Charlotta Sanders, Denis Beller Oct 2007

Monaco/Mavric Evaluation For Facility Shielding And Dose Rate Analysis: To Support The Global Nuclear Energy Partnership, Charlotta Sanders, Denis Beller

Reactor Campaign (TRP)

Monte Carlo methods are used to compute fluxes or dose rates over large areas using mesh tallies. For problems that demand that the uncertainty in each mesh cell be less than some set maximum, computation time is controlled by the cell with the largest uncertainty. This issue becomes quite troublesome in deep-penetration problems, and advanced variance reduction techniques are required to obtain reasonable uncertainties over large areas.

In this project the MAVRIC sequence will be evaluated along with the Monte Carlo engine Monaco to investigate its effectiveness and usefulness in facility shielding and dose rate analyses. A previously MCNP-evaluated cask …


Diffusion And Fractional Diffusion Based Models For Multiple Light Scattering And Image Analysis, Jonathan Blackledge Jan 2007

Diffusion And Fractional Diffusion Based Models For Multiple Light Scattering And Image Analysis, Jonathan Blackledge

Articles

This paper considers a fractional light diffusion model as an approach to characterizing the case when intermediate scattering processes are present, i.e. the scattering regime is neither strong nor weak. In order to introduce the basis for this approach, we revisit the elements of formal scattering theory and the classical diffusion problem in terms of solutions to the inhomogeneous wave and diffusion equations respectively. We then address the significance of these equations in terms of a random walk model for multiple scattering. This leads to the proposition of a fractional diffusion equation for modelling intermediate strength scattering that is based …