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At least 37 records · Page 2

Hail Size Distribution Mapping

A 3-D weather radar visualization software program was developed and implemented as part of an experimental Launch Pad 39 Hail Monitor System. 3DRadPlot, a radar plotting program, is one of several software modules that form building blocks of the hail data processing and analysis system (the complete software processing system under development). The spatial and temporal mapping algorithms were originally developed through research at the University of Central Florida, funded by NASA s Tropical Rainfall Measurement Mission (TRMM), where the goal was to merge National Weather Service (NWS) Next-Generation Weather Radar (NEXRAD) volume reflectivity data with drop size distribution data acquired from a cluster of raindrop disdrometers. In this current work, we adapted these algorithms to process data from a cluster of hail disdrometers positioned around Launch Pads 39A or 39B, along with the corresponding NWS radar data. Radar data from all NWS NEXRAD sites is archived at the National Climatic Data Center (NCDC). That data can be readily accessed at . 3DRadPlot plots Level III reflectivity data at four scan elevations (this software is available at Open Channel Software, ). By using spatial and temporal interpolation/extrapolation based on hydrometeor fall dynamics, we can merge the hail disdrometer array data coupled with local Weather Surveillance Radar-1988, Doppler (WSR-88D) radial velocity and reflectivity data into a 4-D (3-D space and time) picture of hail size distributions. Hail flux maps can then be generated and used for damage prediction and assessment over specific surfaces corresponding to structures within the disdrometer array volume. Immediately following a hail storm, specific damage areas and degree of damage can be identified for inspection crews.

Source record↗

Low Earth Orbit satellite traffic simulator

This paper describes a significant tool for Low Earth Orbit (LEO) capacity analysis, needed to support marketing, economic, and design analysis, known as a Satellite Traffic Simulator (STS). LEO satellites typically use multiple beams to help achieve the desired communication capacity, but the traffic demand in these beams in usually not uniform. Simulations of dynamic, average, and peak expected demand per beam is a very critical part of the marketing, economic, and design analysis necessary to field a viable LEO system. An STS is described in this paper which can simulate voice, data and FAX traffic carried by LEO satellite beams and Earth Station Gateways. It is applicable world-wide for any LEO satellite constellations operating over any regions. For aeronautical applications to LEO satellites. the anticipates aeronautical traffic (Erlangs for each hour of the day to be simulated) is prepared for geographically defined 'area targets' (each major operational region for the respective aircraft), and used as input to the STS. The STS was designed by Constellations Communications Inc. (CCI) and E-Systems for usage in Brazil in accordance with an ESCA/INPE Statement Of Work, and developed by Analytical Graphics Inc. (AGI) to execute on top of its Satellite Tool Kit (STK) commercial software. The STS simulates constellations of LEO satellite orbits, with input of traffic intensity (Erlangs) for each hour of the day generated from area targets (such as Brazilian States). accumulated in custom LEO satellite beams, and then accumulated in Earth Station Gateways. The STS is a very general simulator which can accommodate: many forms of orbital element and Walker Constellation input; simple beams or any user defined custom beams; and any location of Gateways. The paper describes some of these features, including Manual Mode dynamic graphical display of communication links, to illustrate which Gateway links are accessible and which links are not, at each 'step' of the satellite orbit. In the two Performance Modes, either Channel capacity or Grade Of Service (GOS) for objects (Satellite beams, Gateways, and an entire satellite) are computed respectively by standard traffic table capacity lookup and blocking probability equations. GOS can be input, with number of channels calculated, or number of channels can be input, with GOS calculated. Also described are some of the STS Test Procedure approach and results. AGI plans to make the STS features available through their normal commercial STK products. E-Systems is a co-developer, tester, and user of the STS. The Test Procedure for the STS was prepared by E-Systems, as an independent tester for CCI, to support the CCI delivery of the STS to ESCA, for their customer INPE.

Hoelzel, John↗

Small Ion Channel Linking Molecular Simulations and Electrophysiology

Ion channels are pore-forming protein assemblies that mediate the transport of small ions across cell membranes. Otherwise, membrane bilayers would be almost impermeable to ions incapable to traverse the low dielectric constant, hydrophobic membrane core. Ion channels are ubiquitous to all life forms. In humans and other higher organisms they play the central role in conducting nerve impulses, cardiac functions, muscle contraction and apoptosis. On the other extreme of biological complexity, viral ion channels (viroporins) influence many stages of the virus infection cycle either through regulating virus replication, such as entry, assembly and release or modulating the electrochemical balance in the subcellular compartments of host cells. Ion channels were crucial components of protocells. Their emergence facilitated adaptation of nascent life to different environmental conditions. The earliest ion channels must have been much simpler than most of their modern ancestors. Viral channels are among only a few naturally occurring models to study the structure, function and evolution of primordial channels. Experimental studies of these properties are difficult and often unreliable. In principle, computational methods, and molecular dynamics (MD) simulations in particular, can aid in providing information about both the structure and the function of ion channels. However, MD suffers from its own problems, such as inability to access sufficiently long time scales or limited accuracy of force fields. It is, therefore, essential to determine the reliability of MD simulations. We propose to do so on the basis of two criteria. One is channel stability on time scales that extend for several microseconds or longer. The other is the ability to reproduce the measured ionic conductance as a function of applied voltage. If both the stability and the calculated ionic conductance are satisfactory it will greatly increase our confidence that the structure and the function of a channel are described sufficiently accurately. To our knowledge, long time scale stability (approx.10 micro-sec) and the correct electrophysiology have been shown so far for only one channel - the synthetic LS3 hexamer). In this presentation, this approach will be discussed in application to two viral channels - Vpu, encoded by the HIV-1 genome and p7 of hepatitis C.

Pohorille, Andrzej↗

IR dynamics from UV divergences: UV/IR mixing, NCFT, and the hierarchy problem

The persistence of the hierarchy problem points to a violation of effective field theory expectations. A compelling possibility is that this results from a physical breakdown of EFT, which may arise from correlations between ultraviolet (UV) and infrared (IR) physics. To this end, we study noncommutative field theory (NCFT) as a toy model of UV/IR mixing which generates an emergent infrared scale from ultraviolet dynamics. We explore the range of such theories where ultraviolet divergences are transmogrified into infrared scales, focusing particularly on the properties of Yukawa theory, where we identify a new infrared pole accessible in the s-channel of the Lorentzian theory. We further investigate the interplay between UV-finiteness and UV/IR mixing by studying properties of the softly-broken noncommutative Wess-Zumino model as soft terms are varied relative to the cutoff. While the Lorentz violation inherent to noncommutative theories may limit their direct application to the hierarchy problem, these toy models provide general lessons to guide the realization of UV/IR mixing in more realistic theories.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

In situ visualisation of zeolite anisotropic framework flexibility during catalysis

Zeolites exhibit framework flexibility driving their chemical and catalytic properties. Since the zeolitic pores are extremely small, a slight strain generated in the crystal induces compelling changes in shape, connectivity, accessibility, and the framework chemical properties. These modifications affected the adsorption and desorption of reactants/products and the diffusion within the channels during reaction. Using in situ 3D Bragg coherent X-ray diffraction imaging, we unveil the dynamics of the zeolite structure during catalysis, contraction and/or expansion of its framework also known as zeolite framework flexibility. Here, we imaged three-dimensionally a single faujasite zeolite crystal during the ethanol dehydration reaction revealing anisotropic lattice dynamics simultaneously to guest molecules formation. Understanding zeolite flexibility could permit to tune zeolites properties towards potentially higher adsorption and selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deep Reinforcement Learning based Routing in an Air-to-Air Ad-hoc Network

This paper studies the Multiple Sources and Multiple Destinations (MSMD) routing problem in a dynamic Air-to-Air Ad-hoc Network (AAAN). We consider a spectrum limited scenario where multiple links have to share the same frequency channel so that co-channel interference becomes inevitable. As a result, routing decisions and spectrum access are coupled and must be jointly considered. This paper proposes a deep Q-learning based algorithm to find an optimal routing and channel selection strategy that minimizes the end-to-end communication delay. Specifically, under the assumption that only local information is available to every node, the Deep Q-Network (DQN) is trained offline to learn the optimal routing and channel selection strategy. After the trained DQN is implemented in every node, multiple relay nodes can simultaneously determine their next-hop relay and channel selections in real-time. Simulation results demonstrate the efficacy of our proposed algorithm.

AAAN↗

Deep Reinforcement Learning based Routing in an Air-to-Air Ad-hoc Network

This paper studies the Multiple Sources and Multiple Destinations (MSMD) routing problem in a dynamic Air-to-Air Ad-hoc Network (AAAN). We consider a spectrum limited scenario where multiple links have to share the same frequency channel so that co-channel interference becomes inevitable. As a result, routing decisions and spectrum access are coupled and must be jointly considered. This paper proposes a deep Q-learning based algorithm to find an optimal routing and channel selection strategy that minimizes the end-to-end communication delay. Specifically, under the assumption that only local information is available to every node, the Deep Q-Network (DQN) is trained offline to learn the optimal routing and channel selection strategy. After the trained DQN is implemented in every node, multiple relay nodes can simultaneously determine their next-hop relay and channel selections in real-time. Simulation results demonstrate the efficacy of our proposed algorithm.

AAAN↗

Engineering Electrical Conductivity in Stable Zirconium-Based PCN-222 MOFs with Permanent Mesoporosity

Electrically conductive metal–organic frameworks (MOFs) featuring zirconium-based nodes are of great interest for electrochemical and optoelectronic applications due to their exceptional thermal and chemical stability, although the number of such MOFs remains limited. Here in this paper, we demonstrate that electron deficient molecules such as transition metal(IV) bis(dicarbollide) (TM IV (C 2 B 9 H 11 ) 2 ; TM IV CB for short, where TM = Ni, Pd, and Pt) or C 60 , spatially infiltrated in the microporous channels of the zirconium-based porphyrinic MOFs PCN-222 and PCN-222-Zn, generate highly stable and electrically conductive frameworks in which the mesopores remain accessible to other guests. Solid-state density functional theory (DFT) and ab initio molecular dynamics (AIMD) simulations indicate incorporation of Ni IV CB and C 60 in the MOF micropores is energetically and structurally feasible. Interestingly, in contrast to the free species, strong donor–acceptor interactions between the MOF and Ni IV CB restrain it to a single conformation. Calculated electronic structures and charge-hopping conduction probabilities illustrate that efficient charge-transfer (CT) from photoexcited linkers to the guest molecules facilitates charge hopping in the framework, making the MOFs electrically conductive. The donor–acceptor conjugates also enhance exciton dissociation at their heterojunctions, fostering the formation of long-lived electron-trapped states with potential utility for photo- and electrochemical devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Observation of molecular resonant double-core excitation driven by intense X-ray pulses

The ultrashort and intense pulses of X-rays produced at X-ray free electron lasers (XFELs) have enabled unique experiments on the atomic level structure and dynamics of matter, with time-resolved studies permitted in the femto- and attosecond regimes. To fully exploit them, it is paramount to obtain a comprehensive understanding of the complex nonlinear interactions that can occur at such extreme X-ray intensities. Herein, we report on the experimental observation of a resonant double-core excitation scheme in N 2 , where two 1σ core-level electrons are resonantly promoted to unoccupied 1π$^*_g$ molecular orbitals by a single few-femtosecond broad-bandwidth XFEL pulse. The production of these neutral two-site double core hole states is evidenced through their characteristic decay channels, which are observed in good agreement with high-level theoretical calculations. Such multi-core excitation schemes, benefiting from the high interaction cross sections and state- and site-selective nature of resonant X-ray interactions, should be generally accessible in XFEL irradiated molecules, and provide interesting opportunities for chemical analysis and for monitoring ultrafast dynamic processes.

74 ATOMIC AND MOLECULAR PHYSICS↗

Confinement Controls the Bend Instability of Three-Dimensional Active Liquid Crystals

Spontaneous growth of long-wavelength deformations is a defining feature of active liquid crystals. We investigate the effect of confinement on the instability of 3D active liquid crystals in the isotropic phase composed of extensile microtubule bundles and kinesin molecular motors. When shear aligned, such fluids exhibit finite-wavelength self-amplifying bend deformations. By systematically changing the channel size we elucidate how the instability wavelength and its growth rate depend on the channel dimensions. Experimental findings are qualitatively consistent with a minimal hydrodynamic model, where the fastest growing deformation is set by a balance of active driving and elastic relaxation. Furthermore, our results demonstrate that confinement determines the structure and dynamics of active fluids on all experimentally accessible length scales.

59 BASIC BIOLOGICAL SCIENCES↗

Fiber optic probes for laser light scattering: Ground based evaluation for micgrogravity flight experimentation. Integrated coherent imaging fiber optic systems for laser light scattering and other applications

The research work presented in this report has established a new class of backscatter fiber optics probes for remote dynamic light scattering capability over a range of scattering angles from 94 degrees to 175 degrees. The fiber optic probes provide remote access to scattering systems, and can be utilized in either a noninvasive or invasive configuration. The fiber optics create an interference free data channel to inaccessible and harsh environments. Results from several studies of concentrated suspension, microemulsions, and protein systems are presented. The second part of the report describes the development of a new technology of wavefront processing within the optical fiber, that is, integrated fiber optics. Results have been very encouraging and the technology promises to have significant impact on the development of fiber optic sensors in a variety of fields ranging from environmental monitoring to optical recording, from biomedical sensing to photolithography.

Dhadwal, Harbans Singh↗

Space-time generalization of mutual information

The mutual information characterizes correlations between spatially separated regions of a system. Yet, in experiments we often measure dynamical correlations, which involve probing operators that are also separated in time. Here, we introduce a space-time generalization of mutual information which, by construction, satisfies several natural properties of the mutual information and at the same time characterizes correlations across subsystems that are separated in time. In particular, this quantity, that we call the space-time mutual information, bounds all dynamical correlations. We construct this quantity based on the idea of the quantum hypothesis testing. As a by-product, our definition provides a transparent interpretation in terms of an experimentally accessible setup. We draw connections with other notions in quantum information theory, such as quantum channel discrimination. Finally, we study the behavior of the space-time mutual information in several settings and contrast its long-time behavior in many-body localizing and thermalizing systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Communication Demand in the National Airspace - A Federated Learning Approach

Within the national airspace system (NAS), efficient use of spectrum remains a challenge; as UAS and UAM missions evolve, the amount of mission-critical aircraft communications are expected to significantly grow. To accommodate the increased demand, NASA Glenn Research Center is investigating artificial intelligence approaches that could dynamically allocate spectrum; however, these solutions are driven by communication and aviation data items, many of which are not directly available. One such cornerstone data item is communication demand, parameterizing the needs within a sector in terms that may directly inform spectrum allocation, such as channel access duration, bandwidth, and modulation type. This paper considers the complexity of predicting communication demand as a function of NAS behaviors. Unlike prior prediction work in communications, this research must consider how the NAS may be impacted by external factors - such as convective weather and closures - rather than estimating demand from time-series forecasting alone. Much of this research considers a federated learning design to predict communication events in terms of the type of event occurring (sector coordination, conflict resolution, etc.). To do so, an investigation of products from Sherlock Data Warehouse is conducted, identifying the trends, sufficiency, and correlations of each product to identified events. Additionally, a preliminary discussion for inferring associations between these event types and their communication parameters (duration, bandwidth, modulation) is presented. By utilizing federated learning, imbalances in the types of events and data present throughout the NAS can inform local models without impairing global training. Furthermore, the two-stage approach proposed allows for robust and speculative communication modelling, as communication techniques continue to evolve. As a result, this model enables a generalized approach to understanding NAS communications which is able to inform long-term changes to aviation spectrum management.

Nathan Schimpf↗

A Federated Learning Approach to Predicting Communication Demand in the National Airspace

Within the national airspace system (NAS), efficient use of spectrum remains a challenge; as UAS and UAM missions evolve, the amount of mission-critical aircraft communications are expected to significantly grow. To accommodate the increased demand, NASA Glenn Research Center is investigating artificial intelligence approaches that could dynamically allocate spectrum; however, these solutions are driven by communication and aviation data items, many of which are not directly available. One such cornerstone data item is communication demand, parameterizing the needs within a sector in terms that may directly inform spectrum allocation, such as channel access duration, bandwidth, and modulation type. This paper considers the complexity of predicting communication demand as a function of NAS behaviors. Unlike prior prediction work in communications, this research must consider how the NAS may be impacted by external factors - such as convective weather and closures - rather than estimating demand from time-series forecasting alone. Much of this research considers a federated learning design to predict communication events in terms of the type of event occurring (sector coordination, conflict resolution, etc). To do so, an investigation of products from Sherlock Data Warehouse is conducted, identifying the trends, sufficiency, and correlations of each product to identified events. Additionally, a preliminary discussion for inferring associations between these event types and their communication parameters (duration, bandwidth, modulation) is presented. By utilizing federated learning, imbalances in the types of events and data present throughout the NAS can inform local models without impairing global training. Furthermore, the two-stage approach proposed allows for robust and speculative communication modelling, as communication techniques continue to evolve. As a result, this model enables a generalized approach to understanding NAS communications which is able to inform long-term changes to aviation spectrum management.

Nathan Schimpf↗

A Cascaded Random Access Quantum Memory

Dynamic random access memory is critical to classical computing but notably absent in experimental quantum computers. Here we realize an 8-bit cascaded random access quantum memory using superconducting circuits and cavities and showcase the ability to perform arbitrary gate operations on it. In addition to individual error channels such as photon loss, quantum memories can also experience decoherence from many-body self-interaction. We characterize the origin and contributions of many-body infidelity throughout the memory cycle. We find that individual modes can be accessed with $\lesssim 1.5\%$ infidelity per mode and that the entire memory can be accessed in arbitrary order with an error rate below the depolarization threshold of the surface code, paving the way for fault-tolerant quantum memories.

Li, Ziqian [Stanford U., Appl. Phys. Dept.; Stanfo↗

A Synthesis Methodology for Intelligent Memory Interfaces in Accelerator Systems

Domain-specific systems improve the performance of a specific set of applications compared to general-purpose processing systems by deploying custom hardware accelerators. These hardware accelerators are generated using high-level synthesis (HLS) tools. The HLS tools enable a comprehensive design space exploration to optimize the compute performance of the generated accelerators. However, they often ignore the challenges of implementing the accelerators in a system-on-chip, particularly how the accelerators access memory. Our work introduces a buffering system design that improves accelerators' memory accesses by intelligently employing burst transactions to prefetch useful data from external memory to on-chip local buffers. Our design is dynamic, parametric, and transparent to the accelerators generated by HLS tools. We derive the buffering system parameters using appropriate compiler-based analysis passes and memory channel latency constraints. The proposed buffering system design results in, on average, 8.8x performance improvements while lowering memory channel utilization on average by 53.2% for a set of PolyBench kernels.

Limaye, Ankur M. (ORCID:0000000194062584)↗

Exploring the Nucleon Structure via Deep Electroproduction Processes

Understanding the internal structure of the nucleon is a fundamental goal of modern physics, which aims at a comprehensive framework describing the internal dynamics of quarks and gluons. Among other structure functions, Generalized Parton Distributions (GPDs) offer a powerful framework for describing the nucleon dynamics by correlating the longitudinal momentum and the transverse position of its internal partons. Such a correlation provides a three-dimensional picture of the nucleon and enables access to fundamental properties, including the internal pressure distributions and the parton’s angular momentum contribution to the nucleon's total spin, thereby playing a central role in resolving the nucleon spin puzzle. At the Thomas Jefferson National Facility (JLab), polarized electron beam experiments allow for probing GPDs through the measurement of hard exclusive processes. Among the cleanest experimental channels, we find the electro-production of a real photon through the Deeply Virtual Compton Scattering (DVCS) mechanism. The first data-taking period of the CLAS12 program, taking place in 2018, allowed for unique DVCS Beam Spin Asymmetry (BSA) measurements in the phase space covered by a 10.6 GeV polarized electron beam impinging on an unpolarized liquid hydrogen target. Although detecting all final-state particles ensures exclusivity of the process, conservation laws indicate that it is not mandatory. I adopt an approach omitting the direct detection of the recoil proton, providing a simplified yet effective event selection strategy that boosts statistics and gives access to a larger phase space sensitive to the underlying GPD dynamics through BSA and cross section measurements. The Double DVCS (DDVCS) process promises a dedicated mapping of GPDs. Contributing to the electro-production of a lepton pair cross-section, the DDVCS reaction extends DVCS by allowing the final-state photon to be virtual, enriching the kinematic phase space and providing unique access to the internal correlations encoded by GPDs. A feasibility study is conducted to assess the potential of future DDVCS measurements at Jefferson Lab and the future Electron-Ion Collider (EIC). While Jefferson Lab will provide DDVCS measurements in the valence region through the SoLID$\mu$ and $\mu$CLAS12 experimental projects, in the long term, the EIC will provide complementary measurements in the sea region, both accessing unprecedented information about GPDs in a phase space region otherwise inaccessible. Taken together, these investigations demonstrate both the current capabilities and future opportunities for probing GPDs through exclusive processes. The experimental analysis of DVCS at CLAS12 provides precise measurements within an established framework, while the phenomenological study of DDVCS opens the door to richer and more comprehensive explorations with future detectors and facilities.

Alvarado, Juan [Université Paris-Saclay: Gif-sur-Y↗

Dynamic voltage and frequency scaling based on memory channel slack

A processing system scales power to memory and memory channels based on identifying causes of stalls of threads of a wavefront. If the cause is other than an outstanding memory request, the processing system throttles power to the memory to save power. If the stall is due to memory stalls for a subset of the memory channels servicing memory access requests for threads of a wavefront, the processing system adjusts power of the memory channels servicing memory access request for the wavefront based on the subset. By boosting power to the subset of channels, the processing system enables the wavefront to complete processing more quickly, resulting in increased processing speed. Conversely, by throttling power to the remainder of channels, the processing system saves power without affecting processing speed.

Das, Shomit N.↗