arXiv subjects

Eric Jones

Publications and source records attributed to Eric Jones.

10 recordsLinked to original sources

arXiv2023

Spacecraft Coatings Optimizing LiDAR Debris Tracking and Light Pollution Impacts

Space safety and astronomy are at odds. The problem posed by space debris and derelict satellites in the low Earth orbit is an existential threat to all space operations. These dangerous objects in space are more easily tracked with ground-based LiDAR if they are highly reflective, especially in the near-infrared (NIR) range. At the same time, reflective objects in orbit are the bane of ground-based astronomers, causing light pollution and marring images with bright streaks. How can this tension be resolved? The hypothesis tested is that a near-infrared-transparent (NIRT) coating which is opaque in the visible light range and transparent in the NIR range is a promising candidate for use in satellite construction. This experiment tests whether typical spacecraft surfaces such as anodized aluminum or multi-layer insulation (MLI) with a NIRT coating applied will absorb visible light and reflect NIR. The findings confirm the efficacy of the NIRT coating for this purpose, reducing visible light reflection by 47% (+/-3%) and increasing reflection in the NIR by 7% (+/-2%). This promising novel NIRT coating may help provide a path forward to resolve the tension between astronomy and the space industry.

astro-ph.IM↗

arXiv2023

High Repetition-Rate Pulse Shaping of a Spectrally Broadened Yb Femtosecond Laser

We demonstrate compression and shaping of few cycle pulses from a high average power Ytterbium laser system. The pulses from a commercial 20 W, 100 kHz Yb laser system are spectrally broadened in two-stages using gas-filled, stretched hollow-core fibers and then compressed and shaped in an acousto-optic modulator-based pulse-shaper. The pulse-shaper allows for compression, characterization, and shaping all in one system, producing ~10 fs pulses with 50 uJ of energy

physics.optics↗

arXiv2023

Superstaq: Deep Optimization of Quantum Programs

We describe Superstaq, a quantum software platform that optimizes the execution of quantum programs by tailoring to underlying hardware primitives. For benchmarks such as the Bernstein-Vazirani algorithm and the Qubit Coupled Cluster chemistry method, we find that deep optimization can improve program execution performance by at least 10x compared to prevailing state-of-the-art compilers. To highlight the versatility of our approach, we present results from several hardware platforms: superconducting qubits (AQT @ LBNL, IBM Quantum, Rigetti), trapped ions (QSCOUT), and neutral atoms (Infleqtion). Across all platforms, we demonstrate new levels of performance and new capabilities that are enabled by deeper integration between quantum programs and the device physics of hardware.

quant-ph↗

arXiv2020

Momentum exchange in the electron double-slit experiment

We provide support for the claim that momentum is conserved for individual events in the electron double slit experiment. The natural consequence is that a physical mechanism is responsible for this momentum exchange, but that even if the fundamental mechanism is known for electron crystal diffraction and the Kapitza-Dirac effect, it is unknown for electron diffraction from nano-fabricated double slits. Work towards a proposed explanation in terms of particle trajectories affected by a vacuum field is discussed. The contentious use of trajectories is discussed within the context of oil droplet analogues of double slit diffraction.

quant-ph↗

arXiv2020

On Hybrid Quantum and Classical Computing Algorithms for Mixed-Integer Programming

Quantum computing is emerging as a new computing resource that could be superior to conventional computing for certain classes of optimization problems. However, in principle, most existing approaches to quantum optimization are intended to solve unconstrained binary programming problems, while mixed-integer linear programming is of most interest in practice. We attempt to bridge the gap between the capability of quantum computing and real-world applications by developing a new approach for mixed-integer programming. The approach applies Benders decomposition to decompose the mixed-integer programming into binary programming and linear programming sub-problems, which are solved by a noisy intermediate-scale quantum processor and conventional processor, respectively. The algorithm is provably able to reach the optimal solution of the original mixed-integer programming problem. The algorithm is tested on a D-Wave 2000Q quantum processing unit and is shown to be effective for small-scaled test cases. We also test the algorithm on a mixed-integer programming inspired by power system applications. Many insights are drawn from the numerical results for both the capabilities and limitations of the proposed algorithm.

math.OC↗

arXiv2019

SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python

SciPy is an open source scientific computing library for the Python programming language. SciPy 1.0 was released in late 2017, about 16 years after the original version 0.1 release. SciPy has become a de facto standard for leveraging scientific algorithms in the Python programming language, with more than 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories, and millions of downloads per year. This includes usage of SciPy in almost half of all machine learning projects on GitHub, and usage by high profile projects including LIGO gravitational wave analysis and creation of the first-ever image of a black hole (M87). The library includes functionality spanning clustering, Fourier transforms, integration, interpolation, file I/O, linear algebra, image processing, orthogonal distance regression, minimization algorithms, signal processing, sparse matrix handling, computational geometry, and statistics. In this work, we provide an overview of the capabilities and development practices of the SciPy library and highlight some recent technical developments.

cs.MS↗

arXiv2017

Polymorphism in elemental silicon: Probabilistic interpretation of the realizability of metastable structures

With few systems of technological interest having been studied as extensively as elemental silicon, there currently exists a wide disparity between the number of predicted low-energy silicon polymorphs and those, which have been experimentally realized as metastable at ambient conditions. We put forward an explanation for this disparity wherein the likelihood of formation of a given polymorph under near-equilibrium conditions can be estimated on the basis of mean field isothermal-isobaric (N, p, T) ensemble statistics. The probability that a polymorph will be experimentally realized is shown to depend upon both the hypervolume of that structure's potential energy basin of attraction and a Boltzmann factor weight containing the polymorph's potential enthalpy per particle. Both attributes are calculated using density functional theory relaxations of randomly generated initial structures. We find that the metastable polymorphism displayed by silicon can be accounted for using this framework to the exclusion of a very large number of other low-energy structures.

cond-mat.mtrl-sci↗

arXiv2016

A Modified SEIR Model for the Spread of Ebola in Western Africa and Metrics for Resource Allocation

A modified, deterministic SEIR model is developed for the 2014 Ebola epidemic occurring in the West African nations of Guinea, Liberia, and Sierra Leone. The model describes the dynamical interaction of susceptible and infected populations, while accounting for the effects of hospitalization and the spread of disease through interactions with deceased, but infectious, individuals. Using data from the World Health Organization (WHO), parameters within the model are fit to recent estimates of infected and deceased cases from each nation. The model is then analyzed using these parameter values. Finally, several metrics are proposed to determine which of these nations is in greatest need of additional resources to combat the spread of infection. These include local and global sensitivity metrics of both the infected population and the basic reproduction number with respect to rates of hospitalization and proper burial.

q-bio.PE↗

arXiv2015

Path integrals and the double slit

Basic explanations of the double slit diffraction phenomenon include a description of waves that emanate from two slits and interfere. The locations of the interference minima and maxima are determined by the phase difference of the waves. An optical wave, which has a wavelength ${\lambda}$ and propagates a distance $L$, accumulates a phase of $2{\pi}L{/}{\lambda}$. A matter wave, also having wavelength ${\lambda}$ and propagating the same distance $L$, accumulates a phase of ${\pi}L{/}{\lambda}$, which is a factor of two different from the optical case. Nevertheless, the phase difference, ${\Delta}{\phi}$, for interfering matter waves that propagate distances that differ by ${\Delta}L$, is approximately $2{\pi}{\Delta}L{/}{\lambda}$, which is the same value computed in the optical case. The difference between the matter and optical case hinders conceptual explanations of diffraction from two slits based on the matter-optics analogy. In the following article we provide a path integral description for matter waves with a focus on conceptual explanation. A thought experiment is provided to illustrate the validity range of the approximation ${\Delta}{\phi}{\approx}2{\pi}{\Delta}L{/}{\lambda}$.

quant-ph↗

arXiv2013

Analysis and Simulation of the Three-Component Model of HIV Dynamics

Mathematical modeling of biological systems is crucial to effectively and efficiently developing treatments for medical conditions that plague humanity. Often, systems of ordinary differential equations are a traditional tool used to describe the spread of disease within the body. We consider the dynamics of the Human Immunodeficiency Virus (HIV) in vivo during the initial stage of infection. In particular, we examine the well-known three-component model and prove the existence, uniqueness, and boundedness of solutions. Furthermore, we prove that solutions remain biologically meaningful, i.e., are positivity preserving, and perform a thorough, local stability analysis for the equilibrium states of the system. Finally, we incorporate random coefficients within the model and obtain numerical results to predict the probability of infection given the transmission of the virus to a new individual.

math.CA↗