Publications

This study presents methods for engineering the electrocapillary behavior of fluoropolymer surfaces through the use of surfactants and an external insulating liquid. By the scaling of the appropriate surface energies, electrocapillary behavior is obtained at a record low voltage, with contact angle changes in excess of 100[degrees] at 4 V. A consistent description of electrocapillary saturation is presented, identifying three separate regimes: breakdown, thermodynamic instability, and relaxation. Methods for identifying and mitigating some of the saturation behaviors are discussed. Finally, the parameters influencing the observed voltage of zero charge are summarized.

Three algorithms based on geostationary visible and infrared (IR) observations, are used to identify convective cells that do (or may) present a hazard to aviation over the oceans. The algorithms were developed at the Naval Research Laboratory (NRL), National Center for Atmospheric Research (NCAR), and Aviation Weather Center (AWC). The performance of the algorithms in detecting potentially hazardous cells is determined through verification based upon data from National Aeronautical and Space Administration (NASA) Tropical Rainfall Measuring Mission (TRMM) satellite observations of lightning and radar reflectivity, which provide internal information about the convective cells. The probability of detection of hazardous cells using the satellite algorithms can exceed 90% when lightning is used as a criterion for hazard, but the false alarm ratio with all three algorithms is consistently large (~40%), thereby exaggerating the presence of hazardous conditions. This shortcoming results in part from limitations resulting from the algorithms' dependence upon visible and IR observations, and can be traced to the widespread prevalence of deep cumulonimbi with weak updrafts but without lightning, whose origin is attributed to pronounced departures from non-dilute ascent.

Algorithm implementation efficiency is key to delivering high-performance computing capabilities to demanding, high throughput DoD signal and image processing applications and simulations. Significant progress has been made in compiler optimization of serial programs, but many applications require parallel processing, which brings with it the difficult task of determining efficient mappings of algorithms to multiprocessor computers. The pMapper infrastructure addresses the problem of performance optimization of multistage MATLAB applications on parallel architectures. pMapper is an automatic performance tuning library written as a layer on top of pMatlab. pMatlab is a parallel Matlab toolbox that provides MATLAB users with global array semantics. While pMatlab abstracts the message-passing interface, the responsibility of generating maps for numerical arrays still falls on the user. A processor map for a numerical array is defined as an assignment of blocks of data to processing elements. Choosing the best mapping for a set of numerical arrays in a program is a nontrivial task that requires significant knowledge of programming languages, parallel computing, and processor architecture. pMapper automates the task of map generation, increasing the ease of programming and productivity. In addition to automating the mapping of parallel Matlab programs, pMapper could be used as a mapping tool for embedded systems. This paper addresses the design details of the pMapper infrastructure and presents preliminary results.

We demonstrate Mach-Zehnder-type interferometry in a superconducting flux qubit. The qubit is a tunable artificial atom, the ground and excited states of which exhibit an avoided crossing. Strongly driving the qubit with harmonic excitation sweeps it through the avoided crossing two times per period. Because the induced Landau-Zener transitions act as coherent beamsplitters, the accumulated phase between transitions, which varies with microwave amplitude, results in quantum interference fringes for n = 1 to 20 photon transitions. The generalization of optical Mach-Zehnder interferometry, performed in qubit phase space, provides an alternative means to manipulate and characterize the qubit in the strongly driven regime.

III-N materials currently enjoy a predominant role in the formation of solid-state light emitters for [lamda]

An entry level overview of state-of-the-art CMOS detector technology is presented. Operating principles and system architecture are explained in comparison to the well-established CCD technology, followed by a discussion of important benefits of modern CMOS-based detector arrays. A number of unique CMOS features including different shutter modes and scanning concepts are described. In addition, sub-field stitching is presented as a technique for producing very large imagers. After a brief introduction to the concept of monolithic CMOS sensors, hybrid detectors technology is introduced. A comparison of noise reduction methods for CMOS hybrids is presented. The final sections review CMOS fabrication processes for monolithic and vertically integrated image sensors.

A taxonomy that uses twenty-two attributes to characterize C-program overflows was used to construct 291 small C-program test cases that can be used to diagnostically determine the basic capabilities of static and dynamic analysis buffer overflow detection tools. Attributes in the taxonomy include the buffer location (e.g. stack, heap, data region, BSS, shared memory); scope difference between buffer allocation and access; index, pointer, and alias complexity when addressing buffer elements; complexity of the control flow and loop structure surrounding the overflow; type of container the buffer is within (e.g. structure, union, array); whether the overflow is caused by a signed/unsigned type error; the overflow magnitude and direction; and whether the overflow is discrete or continuous. As an example, the 291 test cases were used to measure the detection, false alarm, and confusion rates of five static analysis tools. They reveal specific strengths and limitations of tools and suggest directions for improvements.

Range-velocity (RV) ambiguity is a source of data quality degradation common to all weather radars. Various methods have been developed in recent years to combat this problem. For example, for the new NEXRAD Open Radar Data Acquisition (ORDA) system, the primary focus for range-overlay separation has been on phase-code transmission and processing techniques. There are, however, conditions under which the phase-code method fails to separate range-overlaid signals, e.g., when the overlaid power ratio is too high or the Doppler spectra are too wide. Phase-code processing also has no intrinsic capacity for velocity dealiasing. To address these issues, Lincoln Laboratory developed an alternative RV ambiguity mitigation scheme using multiple pulse-repetition interval (multi-PRI) transmission and processing. The range-dealiasing performance of the multi-PRI approach complements the capability of the phase-code technique. It can succeed when phase-code processing fails, and where it fails, phase-code processing succeeds (e.g., when an overlaid patch of signal is continuous and extensive in the radial direction). Multi-PRI also provides velocity dealiasing. However, because the multi-PRI algorithm was constructed for the Terminal Doppler Weather Radar (TDWR) with its primary mission of short-range coverage around airports, only the capability of first-trip protection was explicitly developed. This report extends the multi-PRI technique to the recovery of Doppler data from other trips, out to the long-range surveillance limit of NEXRAD. Simulated and real weather radar data are used to demonstrate the capabilities and limitations of the technique.

This paper discusses inter-related studies and development activities that address the significant challenges of implementing Air Traffic Management initiatives in airspace impacted by thunderstorms. We briefly describe current thrusts that will improve the quality and precision of thunderstorm forecasts, work in progress to convert these forecasts into estimates of future airspace capacity, and an initiative to develop a robust ATM optimization model based on future capacity estimates with associated uncertainty bounds. We conclude with a discussion of the thunderstorm ATM problem in the context of future advanced airspace management concepts.

A radar data quality control (QC) system is being developed for the real-time, continuously updateable NOWCAST system at the Naval Research Laboratory (NRL-NOWCAST) in Monterey, California. NRL has developed its own new radar QC algorithms, and is also working with the MIT Lincoln Laboratory (MIT LL), the National Center for Atmospheric Research (NCAR), the National Severe Storms Laboratory and the Cooperative Institute for Mesoscale Meteorological Studies at the University of Oklahoma (NSSL-OU) to obtain, adapt, integrate, test and install various types of recently-developed radar QC algorithms for use with NRL-NOWCAST. These algorithms work with volume scans of full-resolution Doppler radar data. Radar data QC can be divided into two categories: echo classification (EC) and calibration. New EC algorithms have recently demonstrated substantial success at separating the radar echoes of precipitation from other echo types, such as noise, normal propagation (NP) and anomalous propagation (AP) ground clutter, sea clutter, insects/clear-air, birds, second-trip echoes, and constant power function (CPF) artifacts. Radar data calibration methods assess the accuracy of both the data values and data coordinates. One calibration issue is aliased radial velocity data from precipitation and insect/clear-air returns, which if correctly de-aliased, afford the opportunity to estimate winds. Another calibration issue of concern to NRL is the processing of radar data from mobile platforms, such as US Navy ships. This processing requires corrections to the radial velocity data and the data-coordinates for the motion of the platform, as well as corrections for the altitude of the data coordinates due to the AP of the radar beam that frequently occurs within surface and evaporation ducts of the marine atmosphere. The goal of this work is to test the performance of the most current and promising radar data QC algorithms on archived data sets, both from ground- and sea-based radars, in order to determine the optimal combination for future real-time use within NRL-NOWCAST. NRL-NOWCAST currently ingests full-resolution Doppler radar data from both the Weather Surveillance Radar-1988 Doppler (WSR-88D) network and the US Department of Defense (DoD) Supplemental Weather Radar (SWR) at the Naval Air Station (NAS) in Fallon, NV. Various products are then created from these data for NRL-NOWCAST display. The radar data are also ingested into the COAMPS-0S (R) (Geiszler et al. 2004) data assimilation system at NRL. Figure 1 shows a flow chart that summarizes the processing stages and uses of radar data at NRL. Figure 2 shows an example of the NRL-NOWCAST demonstration site currently set up at Fallon, where the specific products displayed are only a few from a large list that may be chosen by the forecasters at the NAS. This paper presents a brief overview of the concepts behind the various EC and radial velocity de-aliasing algorithms under consideration. Test results from an NRL algorithm-testing platform will also be presented along with some previously published test results from the authors. Additional test results from the platform will be presented at the conference. Methods to address data-value and data coordinate calibration problems associated with Doppler radars onboard US Navy ships are currently being studied; a discussion on future work in this area will be outlined.