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Articles 1 - 11 of 11
Full-Text Articles in Physics
Quantum Error Detection Without Using Ancilla Qubits, Nicolas Guerrero
Quantum Error Detection Without Using Ancilla Qubits, Nicolas Guerrero
Theses and Dissertations
Quantum computers are beset by errors from a variety of sources. Although quantum error correction and detection codes have been developed since the 1990s, these codes require mid-circuit measurements in order to operate. In order to avoid these measurements we have developed a new error detection code that only requires state collapses at the end of the circuit, which we call no ancilla error detection (NAED). We investigate some of the mathematics behind NAED such as which codes can detect which errors. We then run NAED on three separate types of circuits: Greenberger–Horne–Zeilinger circuits, phase dependent circuits, and a quantum …
Error Detection In Quantum Algorithms, Simeon R. Hanks
Error Detection In Quantum Algorithms, Simeon R. Hanks
Theses and Dissertations
Quantum computers need to be able to control highly entangled quantum states in the presence of environmental perturbations that lead to errors in calculations. Progress in superconducting qubits has enabled the development of computers capable of running small quantum circuits. The current era of Noise Intermediate Scale Quantum computing has a high error rate. To alleviate this error rate we apply an encoding scheme that allows us to remove results with known errors improving the quality of our results. The encoding uses multiple qubits as a single logical qubit and balances the natural tendency of state-of-the-art quantum computers to decohere …
Physics-Constrained Hyperspectral Data Exploitation Across Diverse Atmospheric Scenarios, Nicholas M. Westing
Physics-Constrained Hyperspectral Data Exploitation Across Diverse Atmospheric Scenarios, Nicholas M. Westing
Theses and Dissertations
Hyperspectral target detection promises new operational advantages, with increasing instrument spectral resolution and robust material discrimination. Resolving surface materials requires a fast and accurate accounting of atmospheric effects to increase detection accuracy while minimizing false alarms. This dissertation investigates deep learning methods constrained by the processes governing radiative transfer to efficiently perform atmospheric compensation on data collected by long-wave infrared (LWIR) hyperspectral sensors. These compensation methods depend on generative modeling techniques and permutation invariant neural network architectures to predict LWIR spectral radiometric quantities. The compensation algorithms developed in this work were examined from the perspective of target detection performance using …
Global Gradient-Based Phase Unwrapping Algorithm For Increased Performance In Wavefront Sensing, Bryan R. Bartelt
Global Gradient-Based Phase Unwrapping Algorithm For Increased Performance In Wavefront Sensing, Bryan R. Bartelt
Theses and Dissertations
As the reliance on satellite data for military and commercial use increases, more effort must be exerted to protect our space-based assets. In order to help increase our space domain awareness (SDA), new approaches to ground-based space surveillance via wavefront sensing must be adopted. Improving phase-unwrapping algorithms in order to assist in phase retrieval methods is one way of increasing the performance in current adaptive optics (AO) systems. This thesis proposes a new phase-unwrapping algorithm that uses a global, gradient-based technique to more rapidly identify and correct for areas of phase wrapping during particular phase retrieval methods. This is beneficial …
Techniques For Improved Space Object Detection Performance From Ground-Based Telescope Systems Using Long And Short Exposure Images, David J. Becker
Techniques For Improved Space Object Detection Performance From Ground-Based Telescope Systems Using Long And Short Exposure Images, David J. Becker
Theses and Dissertations
Space object detection is of great importance in the highly dependent yet competitive and congested space domain. Detection algorithms employed play a crucial role in fulfilling the detection component in the space situational awareness mission to detect, track, characterize and catalog unknown space objects. Many current space detection algorithms use a matched filter or a spatial correlator on long exposure data to make a detection decision at a single pixel point of a spatial image based on the assumption that the data follows a Gaussian distribution. This research focuses on improving current space object detection algorithms and developing new algorithms …
Automating Mobile Device File Format Analysis, Richard A. Dill
Automating Mobile Device File Format Analysis, Richard A. Dill
Theses and Dissertations
Forensic tools assist examiners in extracting evidence from application files from mobile devices. If the file format for the file of interest is known, this process is straightforward, otherwise it requires the examiner to manually reverse engineer the data structures resident in the file. This research presents the Automated Data Structure Slayer (ADSS), which automates the process to reverse engineer unknown file for- mats of Android applications. After statically parsing and preparing an application, ADSS dynamically runs it, injecting hooks at selected methods to uncover the data structures used to store and process data before writing to media. The resultant …
Efficient Phase Retrieval For Off-Axis Point Spread Functions, Salome Esteban Carrasco
Efficient Phase Retrieval For Off-Axis Point Spread Functions, Salome Esteban Carrasco
Theses and Dissertations
A novel pairing of phase retrieval tools allows for efficient estimation of pupil phase in optical systems from images of point spread functions (PSFs). The phase retrieval algorithm uses correlation of modeled phase in the focal plane to decouple aberrations that are difficult to identify in complex PSFs. The use of a phase kernel that departs from the Fresnel approximation for off-axis PSFs is a more accurate representation of wavefront phase in finite conjugate imaging. The combination of the approximation and phase correlation algorithm can be more efficient and accurate than generic algorithms.
Estimating Anthropometric Marker Locations From 3-D Ladar Point Clouds, Matthew J. Maier
Estimating Anthropometric Marker Locations From 3-D Ladar Point Clouds, Matthew J. Maier
Theses and Dissertations
An area of interest for improving the identification portion of the system is in extracting anthropometric markers from a Laser Detection and Ranging (LADAR) point cloud. Analyzing anthropometrics markers is a common means of studying how a human moves and has been shown to provide good results in determining certain demographic information about the subject. This research examines a marker extraction method utilizing principal component analysis (PCA), self-organizing maps (SOM), alpha hulls, and basic anthropometric knowledge. The performance of the extraction algorithm is tested by performing gender classification with the calculated markers.
Time Dependent Channel Packet Calculation Of Two Nucleon Scattering Matrix Elements, Brian S. Davis
Time Dependent Channel Packet Calculation Of Two Nucleon Scattering Matrix Elements, Brian S. Davis
Theses and Dissertations
A new approach to calculating nucleon-nucleon scattering matrix elements using a proven atomic time-dependent wave packet technique is investigated. Wave packets containing centripetal barrier information are prepared in close proximity to nuclear well. This is accomplished by first using an analytic equation to determine the wave packets in a suitable intermediate asymptotic state where the centripetal barrier is negligible. Then, the split operator technique is used to propagate the wave packets back to their original positions under the full Hamiltonian. Here, one wave packet is held stationary while the other is allowed to evolve and explore the nuclear well. Scattering …
Type Ii Quantum Computing Algorithm For Computational Fluid Dynamics, James A. Scoville
Type Ii Quantum Computing Algorithm For Computational Fluid Dynamics, James A. Scoville
Theses and Dissertations
An algorithm is presented to simulate fluid dynamics on a three qubit type II quantum computer: a lattice of small quantum computers that communicate classical information. The algorithm presented is called a three qubit factorized quantum lattice gas algorithm. It is modeled after classical lattice gas algorithms which move virtual particles along an imaginary lattice and change the particles’ momentums using collision rules when they meet at a lattice node. Instead of moving particles, the quantum algorithm presented here moves probabilities, which interact via a unitary collision operator. Probabilities are determined using ensemble measurement and are moved with classical communications …
Handwritten Word Recognition Based On Fourier Coefficients, Gary F. Shartle
Handwritten Word Recognition Based On Fourier Coefficients, Gary F. Shartle
Theses and Dissertations
A machine which can read unconstrained words remains an unsolved problem. For example, automatic entry o handwritten documents into a computer is yet to be accomplished. Most systems attempt to segment letters o a word and read words one character at a time. Segmenting a handwritten word is very difficult and often, the confidence of the results is low. Another method which avoids segmentation altogether is to treat each word as a whole. This research investigates the use of Fourier Transform coefficients, computed from the whole word, for the recognition of handwritten words. To test this concept, the particular pattern …