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At least 991 records · Page 55

Estimating Terra MODIS Polarization Effect Using Ocean Data

Terra MODIS has been known since pre-launch to have polarization sensitivity, particularly in shortest-wavelength bands 8 and 9. On-orbit reflectance trending of pseudo-invariant sites show a variation in reflectance as a function of band and scan mirror angle of incidence consistent with time-dependent polarization effects from the rotating double-sided scan mirror. The MODIS Characterization Support Team [MCST] estimates the Mueller matrix trending from this variation as observed from a single desert site, but this effect is not included in Collection 6 [C6] calibration. Here we extend the MCSTs current polarization sensitivity monitoring to two ocean sites distributed over latitude to helpestimate the uncertainties in the derived Mueller matrix. The Mueller matrix elements derived for polarization-sensitive Band 8 for a given site are found to be fairly insensitive to surface brdf modeling. The site-to-site variation is a measure of the uncertainty in the Mueller estimation.Results for band 8 show that the polarization correction reduces mirror-side striping by up to 50% and reduces the instrument polarization effect on reflectance time series of an ocean target.

Wald, Andrew E.↗

Measurement of the energy response of the ATLAS calorimeter to charged pions from $W^{\pm }\rightarrow \tau ^{\pm }(\rightarrow \pi ^{\pm }\nu _{\tau })\nu _{\tau }$ events in Run 2 data

The energy response of the ATLAS calorimeter is measured for single charged pions with transverse momentum in the range 10 < p T < 300 GeV. The measurement is performed using 139 fb –1 of LHC proton–proton collision data at √s = 13 TeV taken in Run 2 by the ATLAS detector. Charged pions originating from τ-lepton decays are used to provide a sample of high-p T isolated particles, where the composition is known, to test an energy regime that has not previously been probed by in situ single-particle measurements. The calorimeter response to single-pions is observed to be overestimated by ~2% across a large part of the p T spectrum in the central region and underestimated by ~4% in the endcaps in the ATLAS simulation. The uncertainties in the measurements are ≲1% for 15 < p T < 185 GeV in the central region. To investigate the source of the discrepancies, the width of the distribution of the ratio of calorimeter energy to track momentum, the energies per layer and response in the hadronic calorimeter are also compared between data and simulation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Modeled and observed properties related to the direct aerosol radiative effect of biomass burning aerosol over the southeastern Atlantic

Biomass burning smoke is advected over the southeastern Atlantic Ocean between July and October of each year. This smoke plume overlies and mixes into a region of persistent low marine clouds. Model calculations of climate forcing by this plume vary significantly in both magnitude and sign. NASA EVS-2 (Earth Venture Suborbital-2) ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) had deployments for field campaigns off the west coast of Africa in 3 consecutive years (September 2016, August 2017, and October 2018) with the goal of better characterizing this plume as a function of the monthly evolution by measuring the parameters necessary to calculate the direct aerosol radiative effect. Here, this dataset and satellite retrievals of cloud properties are used to test the representation of the smoke plume and the underlying cloud layer in two regional models (WRF-CAM5 and CNRM-ALADIN) and two global models (GEOS and UM-UKCA). The focus is on the comparisons of those aerosol and cloud properties that are the primary determinants of the direct aerosol radiative effect and on the vertical distribution of the plume and its properties. The representativeness of the observations to monthly averages are tested for each field campaign, with the sampled mean aerosol light extinction generally found to be within 20 % of the monthly mean at plume altitudes. When compared to the observations, in all models, the simulated plume is too vertically diffuse and has smaller vertical gradients, and in two of the models (GEOS and UM-UKCA), the plume core is displaced lower than in the observations. Plume carbon monoxide, black carbon, and organic aerosol masses indicate underestimates in modeled plume concentrations, leading, in general, to underestimates in mid-visible aerosol extinction and optical depth. Biases in mid-visible single scatter albedo are both positive and negative across the models. Observed vertical gradients in single scatter albedo are not captured by the models, but the models do capture the coarse temporal evolution, correctly simulating higher values in October (2018) than in August (2017) and September (2016). Uncertainties in the measured absorption Ångstrom exponent were large but propagate into a negligible (<4 %) uncertainty in integrated solar absorption by the aerosol and, therefore, in the aerosol direct radiative effect. Model biases in cloud fraction, and, therefore, the scene albedo below the plume, vary significantly across the four models. The optical thickness of clouds is, on average, well simulated in the WRF-CAM5 and ALADIN models in the stratocumulus region and is underestimated in the GEOS model; UM-UKCA simulates cloud optical thickness that is significantly too high. Overall, the study demonstrates the utility of repeated, semi-random sampling across multiple years that can give insights into model biases and how these biases affect modeled climate forcing. The combined impact of these aerosol and cloud biases on the direct aerosol radiative effect (DARE) is estimated using a first-order approximation for a subset of five comparison grid boxes. A significant finding is that the observed grid box average aerosol and cloud properties yield a positive (warming) aerosol direct radiative effect for all five grid boxes, whereas DARE using the grid-box-averaged modeled properties ranges from much larger positive values to small, negative values. It is shown quantitatively how model biases can offset each other, so that model improvements that reduce biases in only one property (e.g., single scatter albedo but not cloud fraction) would lead to even greater biases in DARE. Across the models, biases in aerosol extinction and in cloud fraction and optical depth contribute the largest biases in DARE, with aerosol single scatter albedo also making a significant contribution.

54 ENVIRONMENTAL SCIENCES↗

Atacama Cosmology Telescope: Combined kinematic and thermal Sunyaev-Zel’dovich measurements from BOSS CMASS and LOWZ halos

The scattering of cosmic microwave background (CMB) photons off the free-electron gas in galaxies and clusters leaves detectable imprints on high resolution CMB maps: the thermal and kinematic Sunyaev-Zel’dovich effects (tSZ and kSZ respectively). We use combined microwave maps from the Atacama Cosmology Telescope DR5 and Planck in combination with the CMASS (mean redshift $\langle z \rangle$ = 0.55 and host halo mass $\langle M_{vir} \rangle$ = 3 × 10 13 M ⊙ ) and LOWZ ( $\langle z \rangle$ = 0.31 , $\langle M_{vir} \rangle$ = 5 × 10 13 M ⊙ ) galaxy catalogs from the Baryon Oscillation Spectroscopic Survey (BOSS DR10 and DR12), to study the gas associated with these galaxy groups. Using individual reconstructed velocities, we perform a stacking analysis and reject the no-kSZ hypothesis at 6.5σ, the highest significance to date. This directly translates into a measurement of the electron number density profile, and thus of the gas density profile. Despite the limited signal to noise, the measurement shows at high significance that the gas density profile is more extended than the dark matter density profile, for any reasonable baryon abundance (formally > 90 σ for the cosmic baryon abundance). We simultaneously measure the tSZ signal, i.e., the electron thermal pressure profile of the same CMASS objects, and reject the no-tSZ hypothesis at 10σ. We combine tSZ and kSZ measurements to estimate the electron temperature to 20% precision in several aperture bins, and find it comparable to the virial temperature. In a companion paper, we analyze these measurements to constrain the gas thermodynamics and the properties of feedback inside galaxy groups. We present the corresponding LOWZ measurements in this paper, ruling out a null kSZ (tSZ) signal at 2.9 (13.9) σ , and leave their interpretation to future work. This paper and the companion paper demonstrate that current CMB experiments can detect and resolve gas profiles in low mass halos and at high redshifts, which are the most sensitive to feedback in galaxy formation and the most difficult to measure any other way. They will be a crucial input to cosmological hydrodynamical simulations, thus improving our understanding of galaxy formation. These precise gas profiles are already sufficient to reduce the main limiting theoretical systematic in galaxy-galaxy lensing: baryonic uncertainties. Future such measurements will thus unleash the statistical power of weak lensing from the Rubin, Euclid and Roman observatories. Finally, our stacking software ThumbStackis publicly available and directly applicable to future Simons Observatory and CMB-S4 data.

79 ASTRONOMY AND ASTROPHYSICS↗

Atacama Cosmology Telescope: Combined kinematic and thermal Sunyaev-Zel’dovich measurements from BOSS CMASS and LOWZ halos

The scattering of cosmic microwave background (CMB) photons off the free-electron gas in galaxies and clusters leaves detectable imprints on high resolution CMB maps: the thermal and kinematic Sunyaev-Zel’dovich effects (tSZ and kSZ respectively). We use combined microwave maps from the Atacama Cosmology Telescope DR5 and Planck in combination with the CMASS (mean redshifthzi¼0.55and host halo masshMviri¼3×1013M⊙) and LOWZ (hzi¼0.31,hMviri¼5×1013M⊙) galaxy catalogs from the Baryon Oscillation Spectroscopic Survey (BOSS DR10 and DR12), to study the gas associated with these galaxy groups. Using individual reconstructed velocities, we perform a stacking analysis and reject the no-kSZ hypothes is at 6.5σ, the highest significance to date. This directly translates into a measurement of the electron number density profile, and thus of the gas density profile. Despite the limited signal to noise, the measurement shows at high significance that the gas density profile is more extended than the dark matter density profile, for any reasonable baryon abundance (formally>90σfor the cosmic baryon abundance). We simultaneously measure the tSZ signal, i.e., the electron thermal pressure profile of the same CMASS objects, and reject theno-tSZ hypothesis at10σ. We combine tSZ and kSZ measurements to estimate the electron temperature to20% precision in several aperture bins, and find it comparable to the virial temperature. In a companion paper, we analyze these measurements to constrain the gas thermodynamics and the properties of feedback inside galaxy groups. We present the corresponding LOWZ measurements in this paper, ruling out a null kSZ (tSZ)signal at 2.9ð13.9Þσ, and leave their interpretation to future work. This paper and the companion paper demonstrate that current CMB experiments can detect and resolve gas profiles in low mass halos and at high redshifts, which are the most sensitive to feedback in galaxy formation and the most difficult to measure any other way. They will be a crucial input to cosmological hydrodynamical simulations, thus improving our understanding of galaxy formation. These precise gas profiles are already sufficient to reduce the main limiting theoretical systematic in galaxy-galaxy lensing: baryonic uncertainties. Future such measurements will thus unleash the statistical power of weak lensing from the Rubin, Euclid and Roman observatories. Our stacking software Thumb Stack is publicly available and directly applicable to future Simons Observatory andCMB-S4 data.

Emmanuel Schaan↗

The SIMRAND methodology: Theory and application for the simulation of research and development projects

A research and development (R&D) project often involves a number of decisions that must be made concerning which subset of systems or tasks are to be undertaken to achieve the goal of the R&D project. To help in this decision making, SIMRAND (SIMulation of Research ANd Development Projects) is a methodology for the selection of the optimal subset of systems or tasks to be undertaken on an R&D project. Using alternative networks, the SIMRAND methodology models the alternative subsets of systems or tasks under consideration. Each path through an alternative network represents one way of satisfying the project goals. Equations are developed that relate the system or task variables to the measure of reference. Uncertainty is incorporated by treating the variables of the equations probabilistically as random variables, with cumulative distribution functions assessed by technical experts. Analytical techniques of probability theory are used to reduce the complexity of the alternative networks. Cardinal utility functions over the measure of preference are assessed for the decision makers. A run of the SIMRAND Computer I Program combines, in a Monte Carlo simulation model, the network structure, the equations, the cumulative distribution functions, and the utility functions.

Miles, R. F., Jr.↗

Precise measurement method for ionospheric total electron content using signals from GPS satellites

A GPS codeless receiver called GTR-2 was for measuring total electron content (TEC) along the line of sight to the GPS satellite by using the cross correlation amplitude of the received P-code signals carried by L1(1575.42 MHz) and L2(1227.6 MHz). This equipment has the performance of uncertainty in the measurement of TEC of about 2 X 10(exp 16) electrons/sq m when a 10 dBi gain antenna was used. To increase the measurement performance, an upper version of GTR-2 called GTR-3 is planned which uses the phase information of the continuous signals obtained by making a cross correlation or multiplication of the received L1 and L2 P-code signals. By using the difference of these measured phases values, the ionospheric delay with the ambiguities of the periods of L1+L2 and L1-L2 signals can be estimated.

Imae, Michito↗

Intercomparison of sensible and latent heat flux measurements from combined eddy covariance, energy balance, and Bowen ratio methods above a grassland prairie

We present a comparison of four different methods of measuring sensible (H) and latent (LE) heat fluxes for a year over a mixed grass prairie ecosystem in the Nebraska SandHills [eddy covariance (EC), energy balance/Bowen ratio (EBBR), residual energy (RES), modified Bowen ratio (MBR) methods]. Additionally, we developed a set of quality control criteria for each method and present a simplification to the traditional EBBR setup. Using EC as reference, all methods yielded similar estimates of yearly H (regression slopes (m) ~ 2% from unity; H EC > H EBBR , H RES , and H MBR ). For yearly LE, EBBR and RES yielded similar estimates with EC (m ~ 2% from unity; LE EC < LE EBBR and LE RES ), while a larger bias was found from MBR (m ~ 8% from unity; LE EC > LE MBR ). At shorter time scales (~ hourly), moderate scatter was found about linear regression fits for H between EBBR and EC (R 2 = 0.81), with smaller scatter between RES and MBR, and EC (R 2 = 0.91). For LE, smaller scatter was also measured between EC, and EBBR and RES (R 2 = 0.89 and 0.87, respectively), with the larger scatter between EC and MBR (R 2 = 0.65). This suggests methods other than EC may be well suited to longer-term applications (≥ yearly), but have larger uncertainty on individual measurements.

54 ENVIRONMENTAL SCIENCES↗

Benchmarking a Tunable Quantum Neural Network on Trapped-Ion and Superconducting Hardware

We implement a quantum generalization of a neural network on trapped-ion and IBM superconducting quantum computers to classify MNIST images, a common benchmark in computer vision. The network feedforward involves qubit rotations whose angles depend on the results of measurements in the previous layer. The network is trained via simulation, but inference is performed experimentally on quantum hardware. The classical-to-quantum correspondence is controlled by an interpolation parameter, $a$, which is zero in the classical limit. Increasing $a$ introduces quantum uncertainty into the measurements, which is shown to improve network performance at moderate values of the interpolation parameter. We then focus on particular images that fail to be classified by a classical neural network but are detected correctly in the quantum network. For such borderline cases, we observe strong deviations from the simulated behavior. We attribute this to physical noise, which causes the output to fluctuate between nearby minima of the classification energy landscape. Such strong sensitivity to physical noise is absent for clear images. We further benchmark physical noise by inserting additional single-qubit and two-qubit gate pairs into the neural network circuits. Our work provides a springboard toward more complex quantum neural networks on current devices: while the approach is rooted in standard classical machine learning, scaling up such networks may prove classically non-simulable and could offer a route to near-term quantum advantage.

FOS: Physical sciences↗

Computational Study of Surface Tension and Wall Adhesion Effects on an Oil Film Flow Underneath an Air Boundary Layer

The fringe-imaging skin friction (FISF) technique, which was originally developed by D. J. Monson and G. G. Mateer at Ames Research Center and recently extended to 3-D flows, is the most accurate skin friction measurement technique currently available. The principle of this technique is that the skin friction at a point on an aerodynamic surface can be determined by measuring the time-rate-of-change of the thickness of an oil drop placed on the surface under the influence of the external air boundary layer. Lubrication theory is used to relate the oil-patch thickness variation to shear stress. The uncertainty of FISF measurements is estimated to be as low as 4 percent, yet little is known about the effects of surface tension and wall adhesion forces on the measured results. A modified version of the free-surface Navier-Stokes solver RIPPLE, developed at Los Alamos National Laboratories, was used to compute the time development of an oil drop on a surface under a simulated air boundary layer. RIPPLE uses the volume of fluid method to track the surface and the continuum surface force approach to model surface tension and wall adhesion effects. The development of an oil drop, over a time period of approximately 4 seconds, was studied. Under the influence of shear imposed by an air boundary layer, the computed profile of the drop rapidly changes from its initial circular-arc shape to a wedge-like shape. Comparison of the time-varying oil-thickness distributions computed using RIPPLE and also computed using a greatly simplified numerical model of an oil drop equation which does not include surface tension and wall adhesion effects) was used to evaluate the effects of surface tension on FISF measurement results. The effects of surface tension were found to be small but not necessarily negligible in some cases.

Celic, Alan↗

4D beam matrix reconstruction in particle accelerators

Transverse beam parameters in particle accelerators are commonly described using the Twiss parameters, which are experimentally accessible yet inherently limited because they neglect correlations between different transverse coordinates. Such correlations frequently arise from uncompensated cathode magnetic fields or misaligned focusing quadrupoles, affecting beam quality and accelerator performance. To address this limitation, we propose and validate a novel diagnostic method for the complete four-dimensional (4D) transverse beam matrix. Our method involves passing the beam through a beamline comprising both conventional and skew quadrupole magnets, followed by downstream measurements of the resulting two-dimensional (2D) beam profiles. These measurements represent distinct 2D projections of the underlying 4D transverse phase–space distribution. By systematically varying quadrupole strengths, multiple independent projections of the beam phase space are obtained. We reconstruct the original 4D beam matrix from these measured projections using an optimization-based least-square fit, providing fast and robust reconstruction regardless of the specific beamline configuration. Through extensive numerical simulations and realistic particle-tracking studies, we demonstrate the diagnostic’s accuracy, robustness, and capability to achieve reconstruction uncertainties smaller than measurement errors, particularly when employing sufficient numbers of quadrupole scans. This method presents a powerful and flexible approach for comprehensive beam characterization and accelerator tuning.

43 PARTICLE ACCELERATORS↗

Evaluation and Analysis of F-16XL Wind Tunnel Data From Static and Dynamic Tests

A series of wind tunnel tests were conducted in the NASA Langley Research Center as part of an ongoing effort to develop and test mathematical models for aircraft rigid-body aerodynamics in nonlinear unsteady flight regimes. Analysis of measurement accuracy, especially for nonlinear dynamic systems that may exhibit complicated behaviors, is an essential component of this ongoing effort. In this report, tools for harmonic analysis of dynamic data and assessing measurement accuracy are presented. A linear aerodynamic model is assumed that is appropriate for conventional forced-oscillation experiments, although more general models can be used with these tools. Application of the tools to experimental data is demonstrated and results indicate the levels of uncertainty in output measurements that can arise from experimental setup, calibration procedures, mechanical limitations, and input errors.

Kim, Sungwan↗

Evaluation and Analysis of F-16XL Wind Tunnel Data from Dynamic Tests

A series of wind tunnel tests were conducted in the NASA Langley Research Center as part of an ongoing effort to develop and test mathematical models for aircraft rigid-body aerodynamics in nonlinear unsteady flight regimes. Analysis of measurement accuracy, especially for nonlinear dynamic systems that may exhibit complicated behaviors, is an essential component of this ongoing effort. In this paper, tools for harmonic analysis of dynamic data and assessing measurement accuracy are presented. A linear aerodynamic model is assumed that is appropriate for conventional forced-oscillation experiments, although more general models can be used with these tools. Application of the tools to experimental data is demonstrated and results indicate the levels of uncertainty in output measurements that can arise from experimental setup, calibration procedures, mechanical limitations, and input errors.

Kim, Sungwan↗

Electric Field Conjugation in the Presence of Model Uncertainty

The Wide-Field Infrared Survey Telescope (WFIRST) is a 2.4-meter-diameter space telescope NASA program. The payload will include a coronagraph instrument (CGI). The CGI designs under development use deformable mirrors (DM) to create a point spread function (PSF) with a dark region around the obscured star object. Electric field conjugation (EFC) is an iterative nonlinear optimization procedure that uses measurements of the electric field at the image to determine the DM displacements to modify the PSF to create the region of high contrast in the image. EFC requires a numerical model of the coronagraph to calculate the Jacobian of the system, which is used, along with regularization, to solve for the DM displacements for each iteration of the nonlinear optimization. Ideally, the coronagraph is aligned and calibrated, and the calibration data are used in the numerical model for calculating the Jacobian. However, calibration and alignment measurements always contain uncertainty resulting in calibration error. Therefore, the Jacobian calculated from the numerical model is not an exact representation of the physical coronagraph, and the resulting DM solution for an EFC iteration does not have the exact impact on the electric field of the coronagraph as predicted by the EFC. The result is slow convergence, and, as will be shown, drives the use of more restrictive regularization. Using Monte Carlo trials, we investigate the effect of calibration error on EFC convergence and regulatization. Comparison to results from the High Contrast Imaging Testbed Hybrid Lyot Coronagraph are also presented.

Marx, David↗