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DOE OSTI2021

Quantum-Based Molecular Dynamics Simulations Using Tensor Cores

Tensor cores, along with tensor processing units, represent a new form of hardware acceleration specifically designed for deep neural network calculations in artificial intelligence applications. Tensor cores provide extraordinary computational speed and energy efficiency but with the caveat that they were designed for tensor contractions (matrix–matrix multiplications) using only low-precision floating-point operations. Despite this perceived limitation, we demonstrate how tensor cores can be applied with high efficiency to the challenging and numerically sensitive problem of quantum-based Born–Oppenheimer molecular dynamics, which requires highly accurate electronic structure optimizations and conservative force evaluations. The interatomic forces are calculated on-the-fly from an electronic structure that is obtained from a generalized deep neural network, where the computational structure naturally takes advantage of the exceptional processing power of the tensor cores and allows for high performance in excess of 100 Tflops on a single Nvidia A100 GPU. Stable molecular dynamics trajectories are generated using the framework of extended Lagrangian Born–Oppenheimer molecular dynamics, which combines computational efficiency with long-term stability, even when using approximate charge relaxations and force evaluations that are limited in accuracy by the numerically noisy conditions caused by the low-precision tensor core floating-point operations. A canonical ensemble simulation scheme is also presented, where the additional numerical noise in the calculated forces is absorbed into a Langevin-like dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1973

The 100-micron observations of galactic and extragalactic Southern Hemisphere objects

Far-infrared observations of the interstellar medium are reported by a balloon-borne telescope. With the 30-centimeter (12-in.) telescope operating at a wavelength of 100 microns, approximately forty new sources were observed in the galactic plane and in the large Magellanic Cloud. Patterns and some degree of understanding are beginning to emerge from the observations of objects in the far infrared.

Hoffmann, W. F.↗

NASA NTRS2011

ASTRO-H Soft X-Ray Telescope (SXT)

ASTRO-H is an astrophysics satellite dedicated for X-ray spectroscopic study non-dispersively and to carry out survey complementally, which will be borne out of US-Japanese collaborative effort. Among the onboard instruments there are four conically approximated Wolter-I X-ray mirrors, among which two of them are soft X-ray mirrors\ of which the energy range is from a few hundred eV to 15 keY, currently being fabricated in the X-ray Optics Lab at Goddard Space Flight Center. The focal point instruments will be a calorimeter (SXS) and a CCD camera (SXI), respectively. The reflectors of the mirror are made of heat-formed aluminum substrate of the thickness gauged of 152 micron, 229 micron, and 305 micron of the alloy 5052 H-19, followed by epoxy replication on gold-sputtered smooth Pyrex cylindrical mandrels to acquire the X-ray reflective surface. The epoxy layer is 10 micron nominal and surface gold layer of 0.2 micron. Improvements on angular response over the Astro-El/Suzaku mirrors come from error reduction on the figure, the roundness, and the grazing angle/radius mismatching of the reflecting surface, and tighter specs and mechanical strength on supporting structure to reduce the reflector positioning and the assembly errors. In this paper, we report the results of calibration of the engineering model of SXT (EM), and project the quality of the flight mirrors.

Soong, Yang↗

NASA NTRS2012

Development of Fast, Background-Limited Transition-Edge Sensors for the Background-Limited Infrared/Sub-mm Spectrograph (BLISS) for SPICA

We report experimental progress toward demonstrating background-limited arrays of membrane-isolated transition-edge sensors (TESs) for the Background Limited Infrared/Sub-mm Spectrograph (BLISS). BLISS is a space-borne instrument with grating spectrometers for wavelengths lambda=35-435 micron and with R=lambda/delta lambda approximately equals 500. The goals for BLISS TESs are: noise equivalent power (NEP) = 5x10 (sup -20) W/Hz(exp 1/2) and response time tau <30ms. We expect background-limited performance from bilayers TESs with T(sub c) = 65mK and G=15fW/K. However, such TESs cannot be operated at 50mK unless stray power on the devices, or dark power P(sub D), is less than 200aW. We describe criteria for measuring P(sub D) that requires accurate knowledge of TC. Ultimately, we fabricated superconducting thermistors from Ir (T(sub c) >= 135mK) and Mo/Cu proximitized bilayers, where T(sub c) is the thermistor transition temperature. We measured the Ir TES arrays in our 50mK adiabatic demagnetization refrigerator test system, which can measure up to eight 1x32 arrays simultaneously using a time-division multiplexer, as well as our single-pixel test system which can measure down to 15mK. In our previous Ir array measurements our best reported performance was NEP=2.5x10(exp -19) W/Hz(sub 1/2) and Tau approximately equals 5ms for straight-beam TESs. In fact, we expected NEP approximately equals 1.5x10(exp -19)?W/Hz(sup 1/2) for meander beam TESs, but did not achieve this previously due to 1/f noise. Here, we detail improvements toward measuring the expected NEP and demonstrate NEP=(1.3+0.2)x10 (sup -19)W/Hz(exp 1/2) in our single-pixel test system and NEP=(1.6+/-0.3)x10(sup -19)W/Hz(sup 1/2) in our array test system.

infrared spectrometer↗

NASA NTRS2008

Validation of Aura Microwave Limb Sounder HCl Measurements

The Earth Observing System (EOS) Microwave Limb Sounder (MLS) aboard the Aura satellite has provided daily global HCl profiles since August 2004. We provide a characterization of the resolution, random and systematic uncertainties, and known issues for the version 2.2 MLS HCl data. The MLS sampling allows for comparisons with many (~1500 to more than 3000) closely matched profiles from the Halogen Occultation Experiment (HALOE) and Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS). These data sets provide HCl latitudinal distributions that are, overall, very similar to those from (coincident) MLS profiles, although there are some discrepancies in the upper stratosphere between the MLS and HALOE gradients. As found in previous work, MLS and ACE HCl profiles agree very well (within approximately 5%, on average), but the MLS HCl abundances are generally larger (by 10-20%) than HALOE HCl. The bias versus HALOE is unlikely to arise mostly from MLS, as a similar systematic bias (of order 15%) is not observed between average MLS and balloon-borne measurements of HCl, obtained over Fort Sumner, New Mexico, in 2004 and 2005. At the largest pressure (147 hPa) for MLS HCl, a high bias (approximately 0.2 ppbv) is apparent in analyses of low to midlatitude data versus in situ aircraft chemical ionization mass spectrometry (CIMS) HCl measurements from the Aura Validation Experiment (AVE) campaigns in 2004, 2005, and 2006; this bias is also observed in comparisons of MLS and aircraftHCl/O3 correlations. Good agreement between MLS and CIMS HCl is obtained at 100 to 68 hPa. The recommended pressure range for MLS HCl is from 100 to 0.15 hPa.

Earth Observing System (EOS)↗

DOE OSTI2024

Instrumental uncertainties in radiative corrections for the MUSE experiment

The MUSE experiment at the Paul Scherrer Institute is measuring elastic lepton-proton scattering cross sections in a four-momentum transfer range from Q 2 of approximately 0.002–0.08 GeV 2 using positively and negatively charged electrons and muons. The extraction of the Born cross sections from the experimental data requires radiative corrections. Estimates of the instrumental uncertainties in those corrections have been made using the ESEPP event generator. The results depend in particular on the minimum lepton momentum that contributes to the experimental cross section and the fraction of events with hard initial-state radiation that is detected in the MUSE calorimeter and is excluded from the data. Furthermore, these results show that the angular-dependent instrumental uncertainties in radiative corrections to the electron cross section are less than 0.4% and are negligible for the muon cross section.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1977

Phobos and Deimos

Ground-based and spacecraft observations of Phobos and Deimos are reviewed and the satellites' origin is discussed. The crater densities of both bodies are close to the saturation level. The largest impact events may have caused extensive fracturing of their surfaces. The surfaces are at least 1.5 billion years old and may date back to the early history of the solar system. The Martian satellites display large deviations from sphericity. As a result of tidal processes, they are in synchronous rotation. Several independent lines of evidence show that they have regoliths. Despite some provocative arguments, their internal strengths and the nature of their interior are poorly known at present. Photometric measurements suggest that they are made of either carbonaceous chondritic material or a basalt. Sinclair (1972), Born and Duxbury (1975) and Shor (1975) apparently have successfully determined Phobos' secular acceleration. Their value of approximately .001 deg/year/year implies that the interior of Mars has a low specific dissipation factor (about 100), may indicate that a portion of the Martian interior is experiencing partial melting. The low inclination of the satellites' orbits indicates that they were formed as part of the same process that resulted in Mars.

Pollack, J. B.↗

NASA NTRS2000

On the Feasibility of Studying Shortwave Aerosol Radiative Forcing of Climate Using Dual-Wavelength Aerosol Backscatter Lidar

The current low confidence in the estimates of aerosol-induced perturbations of Earth's radiation balance is caused by the highly non-uniform compositional, spatial and temporal distributions of tropospheric aerosols on a global scale owing to their heterogeneous sources and short lifetimes. Nevertheless, recent studies have shown that the inclusion of aerosol effects in climate model calculations can improve agreement with observed spatial and temporal temperature distributions. In light of the short lifetimes of aerosols, determination of their global distribution with space-borne sensors seems to be a necessary approach. Until recently, satellite measurements of tropospheric aerosols have been approximate and did not provide the full set of information required to determine their radiative effects. With the advent of active aerosol remote sensing from space (e.g., PICASSO-CENA), the applicability fo lidar-derived aerosol 180 deg -backscatter data to radiative flux calculations and hence studies of aerosol effects on climate needs to be investigated.

Redemann, Jens↗

NASA NTRS2013

Dynamics and Control of a Disordered System in Space

In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of N grains in orbit, with N greater than 10(exp 3). These grains can be large (Cubesat-size) or small (mm-size), and can be active, i.e., a fully equipped vehicle capable sensing their own position and attitude, and enabled with propulsion means, or entirely passive. The ultimate objective would be to study the behavior of the single grains and of large ensembles of grains in orbit and to identify ways to guide and control the shape of a cloud composed of these grains so that it can perform a useful function in space, for instance, as an element of an optical imaging system for astrophysical applications. This concept, in which the aperture does not need to be continuous and monolithic, would increase the aperture size several times compared to large NASA observatories such as ATLAST, allowing for a true Terrestrial Planet Imager that would be able to resolve exo-planet details and do meaningful spectroscopy on distant world. In the paper, we address the modeling and autonomous operation of a distributed assembly (the cloud) of large numbers of highly miniaturized space-borne elements (the grains). A multi-scale, multi-physics model is proposed of the dynamics of the cloud in orbit, as well as a control law for cloud shape maintenance, and preliminary simulation studies yield an estimate of the computational effort, indicating a scale factor of approximately N(exp 1.4) as a function of the number of grains. A granular spacecraft can be defined as a collection of a large number of space-borne elements (in the 1000s) designed and controlled such that a desirable collective behavior emerges, either from the interactions among neighboring grains, and/or between the grains and the environment. In this paper, each grain is considered to be a highly miniaturized spacecraft which has limited size and mass, hence it has limited actuation, limited propulsive capability, limited power, limited sensing, limited communication, limited computational resources, limited range of motion, limited lifetime, and may be expendable. The modeling and dynamics of clouds of vehicles is more challenging than with conventional vehicles because we are faced with a probabilistic vehicle composed of a large number of physically disconnected vehicles. First, different scales of motion occur simultaneously in a cloud: translations and rotations of the cloud as a whole (macro-dynamics), relative rotation and translation of one cloud member with respect to another (meso-dynamics), and individual cloud member dynamics (micro-dynamics). Second, the control design needs to be tolerant of the system complexity, of the system architecture (centralized vs. decentralized large scale system control) as well as robust to un-modeled dynamics and noise sources. Figure 1, top left, shows the kinematic parameters of a 1000 element cloud in orbit. The motion of the system is described with respect to a local vertical-local horizontal (LV-LH) orbiting reference frame (x,y,z)=F(sub ORF) of origin O(sub ORF) which rotates with mean motion omega and orbital semi-major axis R(sub 0). The orbital geometry at the initial time is defined in terms of its six orbital elements, and the orbital dynamics equation for point O(sub ORF) is propagated forward in time under the influence of the gravitational field of the primary and other external perturbations, described below. The origin of this frame coincides with the initial position of the center of mass of the system, and the coordinate axes are z along the local vertical, x toward the flight direction, and y in the orbit normal direction. The assumptions we used to model the dynamics are as follows: 1) The inertial frame is fixed at Earth's center. 2) The orbiting Frame ORF follows Keplerian orbit. 3) the cloud system dynamics is referred to ORF. 4) the attitude of each grain uses the principal body frame as body fixed frame. 5) the atmosphere is assumed to be rigidly rotating with the Earth. Regarding the grains forming the cloud: 1) each grain is modeled as a rigid body; 2) a simple attitude estimator provides attitude estimates, 3) a simple guidance logic commands the position and attitude of each grain, 4) a simple local feedback controller based on PD control of local states is used to stabilize the attitude of the vehicle. Regarding the cloud: 1) the cloud as a whole is modeled as an equivalent rigid body in orbit, and 2) an associated graph establishes agent connectivity and enables coupling between modes of motion at the micro and macro scales; 3) a simple guidance and estimation logic is modeled to estimate and command the attitude of this equivalent rigid body; 4) a cloud shape maintenance controller is based on the dynamics of a stable virtual truss in the orbiting frame. Regarding the environmental perturbations acting on the cloud: 1) a non-spherical gravity field including JO (Earth's spherical field) zonal component, J2 (Earth's oblateness) and J3 zonal components is implemented; 2) atmospheric drag is modeled with an exponential model; 3) solar pressure is modeled assuming the Sun is inertially fixed; and 4) the Earth's magnetic field is model using an equivalent dipole model. The equations of motion are written in a referential system with respect to the origin of the orbiting frame and the state is propagated forward in time using an incremental predictor-corrector scheme. A representative cloud with varying number of grains is simulated to identify the limitations in computation time as the number of grains grows. We derive a control law to track a desired surface in the ORF (equivalently to maintain a reference cloud shape) by defining an error from a desired surface shape, and designing a control law that is exponentially stable and reduces the tracking error to zero. Figure 1 (top right) shows a comparison of various requirements for simulation of single spacecraft vs. granular spacecraft, indicating the high degree of complexity that needs to be taken into consideration. The ORF components of control force required by one of the grains is, for this particular case, in the micro-Newton range. However, no attempt has been made yet to reconfigure (or re-orient) the cloud configuration internally, for which forces in the milli-Newton level are expected, depending on the time required to do the reconfiguration. Figure 1, bottom, shows the computation time as a function of the number of grains, indicating an order N(exp 1.43) scaling on a 8 Gb, 1067 MHz RAM MacOSX computer with a 3.06 GHz Intel Core 2 Duo processor. With this metric, the same simulation for a system of N=1000 grains would take 5.4 hours, and 146 hours (i.e., 6 days) for a system with N=10,000 grains. Therefore, efficient ways to simulate this complex system, where not only the time scales of natural system dynamics, but also the sampling times of the Guidance, Navigation, and Control are included, remain to be explored. Additional details on the cloud modeling, dynamics, and control will be described in the paper.

simulation↗

NASA NTRS1983

Stratospheric temperature profile from balloon-borne measurements of the 10.4-micron band of CO2

The technique of nonlinear least squares spectral curve fitting has been used to derive the stratospheric vertical temperature profile from balloon-borne measurements of the 10.4 micron band of CO2. The spectral data were obtained at sunset with the approximately 0.02 per cm resolution University of Denver interferometer system from a float altitude of 33.5 km near Alamogordo, New Mexico, on 23 March 1981. The r.m.s. deviation between the retrieved temperature profile and correlative radiosonde measurements is 2.2 K.

Rinsland, C. P.↗

DOE OSTI2021

Combined Mesonet and Tracker

Title: Combined Mesonet and Trackers (UNL Mobile Mesonets) Authors University of Nebraska PI: Adam Houston, UNL Professor (ahouston2@unl.edu) Mailing Address: 126 Bessey Hall P.O. Box 880340 Lincoln, NE 68588-0340 CoMeT Overview The University of Nebraska-Lincoln operates three Combined Mesonet and Tracker (CoMeTs). CoMeTs are Ford Explorers (model years 2015, 2017, and 2019) with forward-mounted suites of meteorological sensors and dual moonroofs, combining the capability of a mobile mesonet to collect near-surface observations with the capability of an unmanned aircraft systems (UAS) tracker vehicle, which enables an observer in the second row of seats to see the aircraft and maintain compliance with Federal Aviation Administration policies on UAS operation. The CoMeTs collect observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155A, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, and vehicle heading using a KVH Industries C-100 fluxgate compass (Barbieri et al. 2019). The HMP155A and 109SS-L thermistor are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). This list of sensors is also included in the CoMeT data file metadata. Manufacturer specifications for these instruments are given in Table 1 of Hanft and Houston (2018). The reported measured quantities are summarized below.CoMeT-3 was funded through an equipment allocation included in the NSF TORUS award (AGS-1824649). Instrument Description The specific sensors included on each CoMeT are summarized in the table at the end of this section. In general each CoMeT collects observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210 barometer with a Gill pressure port, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, position using a Garmin 19x HVS receiver, and vehicle heading using a KVH Industries C-100 fluxgate compass. The HMP155 and 109SS are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). Fast temperature and corrected RH measurements (using sensors housed within the U-tube) have a time constant of 10-12 s based on data collected across a temperature and RH shock during the CLOUD-MAP 2017 calibration/validation tests on June 26, 2017. Vehicle speed was < 10 kts for this test. CoMeT-1 CoMeT-2 CoMeT-3 Slow Temperature Slow RH Vaisala HMP155A-L20-PT Part #: 22280-7 Vaisala HMP155E Part #: E1AA11A0B1A1A0A Vaisala HMP155E Part #: E1AA11A0B1A1A0A Fast temperature Campbell Scientific 109SS-L20-PT Part #: 21448-3 Campbell Scientific 109SS-L12-PW Part #: 21448-109 Campbell Scientific 109SS-L12-PW Part #: 21448-150 Pressure Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Wind RM Young 05103-L20-PT Part #: 18435-310 RM Young 05103-L20-PW Part #: 18435-244 RM Young 05103-L20-PW Part #: 18435-244 GPS Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Compass KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 Logger Campbell Scientific CR6-NA-XT-SW Part #: 28385-9 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Data Collection and Real-Time Processing The reported measured quantities are summarized in the table below. Quantity Units Source Epoch time Seconds GPS Latitude and longitude Degrees GPS Altitude m GPS Pressure hPa PTB210 Temperature (fast) deg C 109SS-L Temperature (slow) deg C HMP155 RH (slow) % HMP155 Vehicle speed m/s GPS Vehicle heading deg C-100 and GPS In addition to the measured variables, several derived variables are calculated. Corrected/fast relative humidity (%) Relative humidity is adjusted to the fast temperature following Richardson et al. (1998) and Houston et al. (2016). Water vapor mixing ratio (g/kg) Dew point temperature (°C) Potential temperature (Kelvin) Virtual potential temperature (Kelvin) Equivalent potential temperature (Kelvin) Regular intercomparisons between all three CoMeTs were performed during TORUS 2019. Comparisons were also conducted between CoMeT-1 and CoMeT-2 during LAPSE-RATE (2018) on 14 July. In these intercomparisons, the vehicles were parked adjacent to each other aligned perpendicular to (and facing into) the wind. To minimize engine heating effects, intercomparisons were only conducted when the wind speed was >10 kts. Data Format Original data files for each deployment are saved as text files and then converted to NetCDF. NetCDF versions have units that are CF compliant and may not match the original units in the txt files. The naming convention for the NetCDF files is as follows: UNL.CoMeT3.{deployment date YYYYMMDD}.{start time of observation collection in UTC HHMM}.L2.{post-processing codes}.cdf example: UNL.CoMeT3.20190627.1931.L2.g1.f1.cdf Post-processing codes are included to track modifications to the raw data. These codes are closely connected to error flags associated with each record. Each letter corresponds to a particular instrument: g: GPS p: Barometer tf: Fast temperature ts: Slow temperature rh: Relative humidity f: Compass w: Wind monitor a: All instruments Each number corresponds to a particular post-processing action described more below. Measured and derived variables are included in the following table. Variable Heading Standard Name Units time Time seconds since 00:00:00, 01-01-1970 Alt Altitude meters lat Latitude degrees north lon Longitude degrees east fast_temp Air Temperature kelvin slow_temp Air Temperature kelvin pressure Air Pressure pascals logger_RH Relative Humidity percent calc_corr_RH Relative Humidity percent wind_speed Wind Speed meters per second wind_dir Wind From Direction degrees vehicle_dir Vehicle Direction degrees dewpoint Dew Point Temperature kelvin mixing_ratio Humidity Mixing Ratio g/g theta Air Potential Temperature kelvin theta_v Virtual Potential Temperature kelvin theta_e Equivalent Potential Temperature Kelvin error_flag The error_flag variable is a string that matches the post-processing codes listed above. All instruments will have an associated code, but will have a “0” if the datum is unchanged from the initial processed value. Error Codes The following table summarizes the error codes for data collected before 2020: Error Code Relevant CoMeT Description g1 1,2,3 Exact correction. GPS position and time reprocessed from raw data g2 1 As far as we can tell this is an exact correction to an error in the GPS time. During the correct time periods the time suddenly went backwards ~250s and stayed at this offset for 750s when it corrected itself. The offset was applied to the “time warp” period. p1 2 Approximate correction. Hole in the pressure tube connecting the pressure port to the barometer. Resulted in erroneously low air pressure measurements when the vehicle was in motion. Derived variables recalculated (dew point temperature [e depends on qv and p], water vapor mixing ratio, potential temperature, virtual potential temperature, equivalent potential temperature) a1 3 Exact correction. Missing data reprocessed from raw data a2 1 Bug fix to bias correction for ts1, ts2, and rh1: water vapor mixing ratio was off by a factor of 10 and virtual potential temperature was wrong because of this. f1 3 No correction, missing data. Fluxgate compass inoperable. Wind speed and direction calculated using GPS-derived vehicle heading instead. rh1 1 Approximate correction. Constant bias of +1.7% removed from relative humidity. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts1 1 Approximate correction. Constant bias of +0.6 K removed from slow temperature. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts2 1 Approximate correction. Constant bias of +1.0 K removed. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) References Bolton, D., 1980: The Computation of Equivalent Potential Temperature. Mon. Wea. Rev., 108, 1046–1053, https://doi.org/10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2. Hanft, W., and A. L. Houston, 2018: An Observational and Modeling Study of Mesoscale Air Masses with High Theta-E. Mon. Wea. Rev., 146, 2503–2524, https://doi.org/10.1175/MWR-D-17-0389.1.Wexler Houston, A. L., R. J. Laurence III, T. W. Nichols, S. Waugh, B. Argrow, and C. L. Ziegler, 2016: Intercomparison of unmanned aircraft-borne and mobile mesonet atmospheric sensors. Journal of Atmospheric and Oceanic Technology. 33, 1569-1582, doi: 10.1175/JTECH-D-15-0178.1. Lowe, P. R., 1977: An Approximating Polynomial for the Computation of Saturation Vapor Pressure. J. Applied Meteorology, 16, 100–103. Richardson, S. J., S. E. Frederickson, F. V. Brock, and J. A. Brotzge, 1998: Combination temperature and relative humidity probes: Avoiding large air temperature errors and associated relative humidity errors. Preprints, 10th Symp. On Meteorological Observations and Instrumentation, Phoenix, AZ, Amer. Meteor. Soc., 278–283. Waugh, S., and S. E. Frederickson, 2010: An improved aspirated temperature system for mobile meteorological observations, especially in severe weather. 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., P5.2. [Available online at https://ams.confex.com/ams/25SLS/techprogram/paper_176205.htm.]

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1979

Spectrum of the cosmic background radiation

Measurements of the emission spectrum of the night sky have been made in the frequency range from 1.7 to 40 kaysers by using a fully calibrated liquid-helium-cooled balloon-borne spectrophotometer. The results show that the spectrum of the cosmic background radiation peaks at 6 kaysers and is approximately that of a 3-K blackbody out to several times that frequency. However, the data show deviations from a simple blackbody curve.

Woody, D. P.↗

NASA NTRS1985

The isotopic composition of helium in the cosmic radiation above 11 gigavolts

The He-3/He-4 abundance ratio above 11 GV has been measured with a balloon-borne experiment that employs the geomagnetic method of isotope separation near earth's equator. Above a kinetic energy of approximately 6 GeV per nucleon, the He-3/He-4 ratio is measured to be 0.24 + or - 0.05 under the assumption that the helium spectrum at earth is a power law in rigidity of the form R to the -2.65th. The implied interstellar mean escape pathlength of about 15 g per sq cm, with this assumption, is considerably greater than values determined from observations of heavier elements. Propagation models more complex than the standard simple leaky box would be required to simultaneously understand the propagation of both the lighter and heavier components of cosmic rays.

Jordan, S. P.↗

NASA NTRS1988

Axions and SN1987A

The effect of free-streaming axion emission on numerical models for the cooling of the newly born neutron star associated with SN1987A is considered. It is found that for an axion mass of greater than approximately 10 to the -3 eV, axion emission shortens the duration of the expected neutrino burst so significantly that it would be inconsistent with the neutrino observations made by the Kamiokande II and Irvine-Michigan-Brookhaven detectors. However, the possibility has not been investigated that axion trapping (which should occur for masses greater than or equal to 0.02 eV) sufficiently reduces axion emission so that axion masses greater than approximately 2 eV would be consistent with the neutrino observations.

Burrows, Adam↗

NASA NTRS2014

Micro-spec: an Integrated Direct-detection Spectrometer for Far-infrared Space Telescopes

The far-infrared and submillimeter portions of the electromagnetic spectrum provide a unique view of the astrophysical processes present in the early universe. Our ability to fully explore this rich spectral region has been limited, however, by the size and cost of the cryogenic spectrometers required to carry out such measurements.Micro-Spec (μ-Spec) is a high-sensitivity, direct-detection spectrometer concept working in the 450-1000 (micrometers) wavelength range which will enable a wide range of flight missions that would otherwise be challenging due tothe large size of current instruments with the required spectral resolution and sensitivity. The spectrometer design utilizes two internal antenna arrays, one for transmitting and one for receiving, superconducting microstrip transmission lines for power division and phase delay, and an array of microwave kinetic inductance detectors (MKIDs) to achieve these goals. The instrument will be integrated on a approximately 10 sq cm silicon chip and can therefore become an important capability under the low background conditions accessible via space and high-altitude borne platforms. In this paper, an optical design methodology for micro-Spec is presented, with particular attention given to its two-dimensional diffractive region, where the light of different wavelengths is focused on the different detectors. The method is based on the maximization of the instrument resolving power and minimization of the RMS phase error on the instrument focal plane. This two-step optimization can generate geometrical configurations given specific requirements on spectrometer size, operating spectral range and performance.Two point designs with resolving power of 260 and 520 and an RMS phase error less than approximately 0.004 radians were developed for initial demonstration and will be the basis of future instruments with resolving power up to about 1200.

Far-infrared↗

NASA NTRS2012

Toward Active X-ray Telescopes II

In the half century since the initial discovery of an astronomical (non-solar) x-ray source, the sensitivity for detection of cosmic x-ray sources has improved by ten orders of magnitude. Largely responsible for this dramatic progress has been the refinement of the (grazing-incidence) focusing x-ray telescope. The future of x-ray astronomy relies upon the development of x-ray telescopes with larger aperture areas (greater than 1 m2) and finer angular resolution (less than 1.). Combined with the special requirements of grazing-incidence optics, the mass and envelope constraints of space-borne telescopes render such advances technologically challenging.requiring precision fabrication, alignment, and assembly of large areas (greater than 100 m2) of lightweight (approximately 1 kg m2 areal density) mirrors. Achieving precise and stable alignment and figure control may entail active (in-space adjustable) x-ray optics. This paper discusses relevant programmatic and technological issues and summarizes progress toward active x-ray telescopes.

O'Dell, Stephen L.↗

NASA NTRS1975

Splash albedo protons between 4 and 315 MeV at high and low geomagnetic latitudes

Results are reported for measurements of the differential energy spectrum of splash-albedo protons at high geomagnetic latitude during three periods of the last solar cycle as well as at low latitude during one of those periods. The measurements were made with a balloon-borne solid-state detector telescope. Splash-albedo protons with energies between 4 and 315 MeV were observed in fluxes of approximately 81, 70, and 48 protons/sq m per sec per sr at high latitude and in fluxes of approximately 37 protons/sq m per sec per sr at low latitude. It is shown that the difference between the first and third high-latitude measurements was due to solar modulation of the cosmic-ray parent nuclei. The albedo spectrum is found to have a similar shape for both latitudes, and it is suggested that the difference in intensity can be explained by different local geomagnetic cutoffs.

Wenzel, K.-P.↗

NASA NTRS1986

The MC and LFC cameras

The characteristics of the shuttle-borne Large Format Camera are listed. The LFC focal plane format was 23 by 46 cm, double the usual size, thereby acquiring approximately double the ground area. Forward motion compensation was employed. With the stable platform (shuttle) it was possible to use the slow exposure, high resolution, Kodak aerial films; 3414 and 3412 black and white, SO-242 color, and SO-131 aerochrome infrared. The camera was designed to maintain stability during varying temperature extremes of space.

Norton, Clarice L.↗