We present progress toward creating and entangling states of squeezed light for a simulated-atmosphere tabletop quantum illumination experiment. The purpose of this experiment is to explore theoretical studies previously done by our team.

A new instrument for electron beam characterization has been developed, based on measuring the range of beam electrons in different thicknesses of aluminum, to determine both the current and energy of an electron beam traveling in open air. This instrument is referred to as a ‘plate spectrometer’ as the thickness of the spectrometer is adjusted by adding or removing alu- minum plates. This spectrometer was assembled and then characterized at the Idaho Accelerator Center (IAC) with three different beam energies and with one beam energy at the University of Maryland Radiation Facilities. The plate spectrometer was able to match the median energies and provide a reasonable constraint to the beam distributions seen in the IAC magnetic spectrometer. In a separate experiment, the plate spectrometer was also seen to agree with a dosimetry characterization of the beam at the University of Maryland Radiation Facilities and improved upon the uncertainties of this measurement.

Dielectric materials are foundational to our modern-day communications, defense, and commerce needs. Although dielectric breakdown is a primary cause of failure of these systems, we do not fully understand this process. We analyzed the dielectric breakdown channel propagation dynamics of two distinct types of electrical trees. One type of these electrical trees has not been formally classified. We observed the propagation speed of this electrical tree type to exceed 10 million meters per second. These results identify substantial gaps in the understanding of dielectric breakdown, and filling these gaps is paramount to the design and engineering of dielectric materials that are less susceptible to electrostatic discharge failure.

architecture. The cameras in this system use an object detection algorithm to nd important targets in the scene. The raw data from the camera and the outputs from the detection algorithm are then placed in a transaction on the distributed ledger. Similarly, microwave data is used to detect relevant events and are placed in a transaction. These transactions are then bundled into blocks and broadcast to the rest of the network using the Bitcoin-based MultiChain protocol. We develop five tests to examine the security metrics of our network. We performed the five security metric test using different sized networks from 7 to 39 nodes to determine how the metrics scale with respect to size. We nd that when compared to a centralized architecture our implementation provides a resiliency increase that is expected from a blockchain-based protocol without slowing the system so much that a human operator would notice. Furthermore, our approach is able to detect tampering in real time. Based on these results, we theorize that security networks in general could use a blockchain-based approach in a meaningful way.

voltage variation across the induction cells is shown to be nearly unchanged for end-point energies above 10 MeV.

Los Alamos National Laboratory has developed an incoherent, long-range, sub-centimeter resolution (LIDAR) with which we achieve centimeter-scale reflection holography at extremely long ranges. The system consists of a pulsed laser and photon-counting receiver. This combination yields round-trip time of flight data to illuminate parts of the object of interest. The aggregation of these data for many LIDAR pulses yields a plot with a range on the X axis and reflectance on the Y axis, which we refer to as a range profile. Observing that the range profile is a projection of the reflection map of the object onto the view vector, we collect profiles from a variety of viewing angles and invert these data to form an image. We adapt imaging algorithms from the field of computer aided tomography to suit our application and present results from imaging demonstrations at a 10 km range.

The Nano-satellite Atmospheric Chemistry Hyperspectral Observation System (NACHOS) is a high-throughput (f/2.9), high spectral resolution (~1.3 nm optical resolution, 0.6 nm sampling) Offner-design hyperspectral imager operating in the 300-500 nm spectral region. The 1.5U instrument payload (1U optical system, 0.5U electronics module) is hosted by a 1.5U LANL-designed CubeSat bus to comprise a 3U complete satellite. Spectroscopically similar to NASA's Ozone Monitoring Instrument (OMI), which provides wide-field global mapping of ozone and other gases at coarse spatial resolution, NACHOS fills the complementary niche of targeted measurements at much higher spatial resolution. With 350 across-track spatial pixels and a 15-degree across-track field of view, NACHOS will provide spectral imaging at roughly 0.4 km per pixel from 500 km altitude. NACHOS incorporates highly streamlined gas-retrieval algorithms for rapid onboard processing, alleviating the need to routinely downlink massive hyperspectral data cubes. We will discuss the instrument design, challenges in achieving mechanical robustness to launch vibration in such a compact instrument, the onboard calibration system, and gas-retrieval data downlink strategy. We will also discuss potential science missions, including monitoring of NO2 as an easily detected proxy for anthropogenic fossil-fuel greenhouse gases, monitoring lowlevel SO2 degassing at pre-eruptive volcanoes, H2CO from wildfires, and characterization of aerosols. The long-term vision is for a many-satellite constellation that could provide both high spatial resolution and frequent revisits for selected targets of interest. As an initial technology demonstration of this vision, the NACHOS project is currently slated to launch two CubeSats in early 2022.

Compact readout of a large (5×5×5 cm3) CLYC scintillator was demonstrated with a 8×8 array of 6mm silicon photomultipliers (SiPMs, specifically, a SensL ArrayJ-60035-64P) and an optimized amplification and summing circuit. Read out by the SiPM array, the crystal yielded an energy resolution of 5.5% at 662 keV and a figure of merit of 3.5, equivalent to the performance achieved with a 3-inch Hamamatsu R6233-100 PMT. To reduce channel count and avoid individual amplification of each SiPM in the array, the standard outputs of 16 SiPMs were passively summed then amplified. A current feedback amplifier was used for each channel to provide the required fast response time. The four amplified channels were then passively summed resulting in a single signal channel. A custom laboratory setup, based on the PSD8C ASIC, was used to capture the output and provide time-gated integration for PSD computation. The compact volume, low bias voltage, and reduced mass of the SiPM array readout are desirable for space and national security applications.

Radio frequency aperture synthesis from multiple free-flying collectors is traditionally dependent on highly accurate intra-constellation metrology and shared clocks. We demonstrate that coherent alignment of independent collectors with poor knowledge of relative positioning and clocking can be achieved through computational means in post processing. This allows the synthesis of a coherent sparse array of RF collectors with the time and position knowledge available from a cheap and commercial GPS receiver. This paper extends our previous publication in the 2018 IEEE Aerospace conference with several key advances, including on-GPU execution of the CAF algorithm, on-GPU multi-emitter tracking, and interpolation-based correction adaptation. The alignment algorithm has significantly increased in performance and capability since 2018. The Complex Ambiguity Function (CAF) is used for simultaneous estimation of time difference of arrival (TDOA) and frequency difference of arrival (FDOA) for multiple pairs of received signals. These time, frequency, and phase corrections are applied to the data, bringing them into alignment with each other. Maintaining this alignment over a longer time span is the challenge, addressed through overlapped sequential CAF estimates to estimate the evolving TDOA/FDOA of multiple emitters. Achieving good alignment over millions of samples requires an evolving model of the collection geometry. By breaking a long signal into successive, overlapping frames, we can estimate the signal parameters; however, the computation time is untenable on traditional CPUs. In this paper, we explore the use of heterogeneous architectures to speed up the CAF algorithm and to make it suitable for the alignment of larger signal lengths. We show that the optimized GPU implementation provides a performance improvement of 150x compared to the sequential implementation. We also demonstrate a dynamic load balancing scheme for MPI that can distribute the work across multiple GPU nodes. Using the accelerated code, we demonstrate the signal alignment using CAF with the NOAA satellite full-pass collects using multiple collectors on the ground around the Los Alamos townsite.

Radio frequency aperture synthesis from multiple free-flying collectors is traditionally dependent on highly accurate intra-constellation metrology and shared clocks. We demonstrate that relaxed precision of relative positioning and clocking can be acceptable through computational means in post processing. The work assumes a small cluster of RF collectors that can collect on an emitter at the same time, with position and time accuracy provided by commonly available aerospace GPS units. No cross links or inter-vehicle spacing is assumed. In lieu of accurate timing, correlation searches are performed at the ground station. A key part of the idea is an alignment stage following collection. This is composed of a Cross Ambiguity Function (CAF) search across all possible FDOA/TDOA shifts, and a phase alignment search. These time, frequency and phase corrections are applied to the data, bringing them into alignment with each other. Maintaining this alignment over a longer time span is the challenge, covered here in some detail. This paper covers our work to date. This includes on-orbit results, a simulation model of the coherence-through-computation mechanism, consisting of models of the geolocation process, Doppler correction over time, and transforming input signals to a common time and frequency reference. This paper extends our previous publication in the IEEE Aerospace conference[1] with several key advances, including parallized execution, interpolated TDOA/FDOA tracking, and multi-emitter tracking.