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At least 793 records · Page 44

Simultaneous quaternion estimation (QUEST) and bias determination

Tests of a new method for the simultaneous estimation of spacecraft attitude and sensor biases, based on a quaternion estimation algorithm minimizing Wahba's loss function are presented. The new method is compared with a conventional batch least-squares differential correction algorithm. The estimates are based on data from strapdown gyros and star trackers, simulated with varying levels of Gaussian noise for both inertially-fixed and Earth-pointing reference attitudes. Both algorithms solve for the spacecraft attitude and the gyro drift rate biases. They converge to the same estimates at the same rate for inertially-fixed attitude, but the new algorithm converges more slowly than the differential correction for Earth-pointing attitude. The slower convergence of the new method for non-zero attitude rates is believed to be due to the use of an inadequate approximation for a partial derivative matrix. The new method requires about twice the computational effort of the differential correction. Improving the approximation for the partial derivative matrix in the new method is expected to improve its convergence at the cost of increased computational effort.

Markley, F. Landis↗

Scientific Impact of MODIS C5 Calibration Degradation and C6+ Improvements

The Collection 6 (C6) MODIS (Moderate Resolution Imaging Spectroradiometer) land and atmosphere data sets are scheduled for release in 2014. C6 contains significant revisions of the calibration approach to account for sensor aging. This analysis documents the presence of systematic temporal trends in the visible and near-infrared (500 m) bands of the Collection 5 (C5) MODIS Terra and, to lesser extent, in MODIS Aqua geophysical data sets. Sensor degradation is largest in the blue band (B3) of the MODIS sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple MODIS C5 products including the dark target algorithm's aerosol optical depth over land and Ångstrom exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface reflectance and vegetation indices, including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). As the C5 production will be maintained for another year in parallel with C6, one objective of this paper is to raise awareness of the calibration-related trends for the broad MODIS user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6C calibration of the MODIS data set which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of MODIS Terra since about 2007, as well as detrending and Terra- Aqua cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the MODIS ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface reflectance (SR) records along with spectral distortions of SR. Using the multiangle implementation of atmospheric correction (MAIAC) algorithm over deserts, we have also developed a detrending and cross-calibration method which removes residual decadal trends on the order of several tenths of 1% of the top-of-atmosphere (TOA) reflectance in the visible and near-infrared MODIS bands B1-B4, and provides a good consistency between the two MODIS sensors. MAIAC analysis over the southern USA shows that the C6C approach removed an additional negative decadal trend of Terra (Delta)NDVI approx.0.01 as compared to Aqua data. This change is particularly important for analysis of vegetation dynamics and trends in the tropics, e.g., Amazon rainforest, where the morning orbit of Terra provides considerably more cloud-free observations compared to the afternoon Aqua measurements.

Terra and Aqua↗

malbacR: A Package for Standardized Implementation of Batch Correction Methods for Omics Data

Mass spectrometry is a powerful tool for identifying and analyzing small molecules, such as metabolites and lipids, in com-plex biological samples. Liquid chromatography and gas chromatography mass spectrometry studies quite commonly in-volve large numbers of samples, which can require significant time for sample preparation and analyses. To accommodate such studies, the samples are commonly split into batches. Inevitably, variations in sample handling, temperature fluctua-tion, imprecise timing, column degradation and other factors result in systematic errors or biases of the measured abundances between the batches. Numerous methods are available via R packages to assist with batch correction for small molecule om-ics data; however, since these methods were developed by different research teams, the algorithms are available in separate R packages, each with different data input and output formats. We introduce the malbacR package which consolidates eleven common batch effect correction methods for small molecule omics data into one place so users can easily implement and compare: pareto scaling, power scaling, range scaling, ComBat, EigenMS, NOMIS, RUV-random, QC-RLSC, WaveI-CA2.0, TIGER, and SERRF. The malbacR package standardizes data input and output formats across these batch correction methods. The package works in conjunction with the pmartR package, allowing users to seamlessly include batch effect cor-rection in a pmartR workflow without needing any additional data manipulation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Attitude determination and parameter estimation using vector observations - Application

This paper presents tests of a new method for the simultaneous estimation of spacecraft attitude and sensor biases, based on a quaternion estimation algorithm minimizing Wahba's loss function. The new method is compared with a conventional batch least-squares differential correction algorithm. The estimates are based on data from strapdown gyros and star trackers, simulated with varying levels of Gaussian noise for both inertially-fixed and earth-pointing attitudes. Both algorithms solve for the spacecraft attitude and the gyro drift rate biases. In the majority of tests performed, the two methods converge to the same estimates in the same number of iterations, but the new algorithm requires about 60 percent more computational effort. Some cases were found in which the new method converges in fewer iterations than the differential correction, and some for which the differential correction requires fewer iterations.

Markley, F. Landis↗

Evaluation of Models and Measurements to Estimate Solar Radiation for 1-Axis Tracking Modules at NREL's SRRL: Preprint

Solar radiation reaching photovoltaic (PV) modules on a 1-axis tracking system can be measured by reference cells or thermopiles. The former is often biased due to the reflection of solar radiation by the glass cover of the PV. The uncertainty can be moderated by applying a correction factor, as a function of solar incident angle and the refractive index of the glass, to the measurement. On the other hand, solar radiation on the inclined PV panels can be computed by transposition models using global horizontal irradiance (GHI) observations from thermopiles. This study examines the models and measurements to estimate solar radiation for 1-axis tracking modules at National Renewable Energy Laboratory’s (NREL’s) Solar Radiation Research Laboratory (SRRL). The 1-minute plane-of-array (POA) irradiances in 2019 are computed using the observed GHIs and a transposition model developed by Perez et al. The POA irradiances are compared with the observation by an IMT reference cell and a Kipp & Zonen CM Pyranometer 22 (CMP22) thermopile. For SRRL’s 1-axis tracking system with the annual solar energy of 2323.9 kWh/m2, the POA irradiance is overestimated by ~70 kWh/m2 using the transposition model. This bias is reduced by more than 50% using the IMT measurements calibrated by a correction factor for a PV surface of antireflection coated glass.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Evaluation of Models and Measurements to Estimate Solar Radiation for 1-Axis Tracking Modules at NREL’s SRRL

Solar radiation reaching photovoltaic (PV) modules on a 1-axis tracking system can be measured by reference cells or thermopiles. The former is often biased due to the reflection of solar radiation by the glass cover of the PV. The uncertainty can be moderated by applying a correction factor, as a function of solar incident angle and the refractive index of the glass, to the measurement. On the other hand, solar radiation on the inclined PV panels can be computed by transposition models using global horizontal irradiance (GHI) observations from thermopiles. This study examines the models and measurements to estimate solar radiation for 1-axis tracking modules at the National Renewable Energy Laboratory’s (NREL’s) Solar Radiation Research Laboratory (SRRL). The 1-minute plane-of-array (POA) irradiances from 2019 are computed using the observed GHIs and a transposition model developed by Perez et al. The POA irradiances are compared with the observation by an IMT reference cell and a Kipp & Zonen CM Pyranometer 22 (CMP22) thermopile. For the SRRL’s 1-axis tracking system with an annual solar energy of 2323.9 kWh/m 2 , the POA irradiance is overestimated by ~70 kWh/m 2 using the transposition model. This bias is reduced by more than 50% using the IMT measurements calibrated by a correction factor for a PV surface of antireflection coated glass.

POA irradiance↗

Advanced Land Imager Assessment System

The Advanced Land Imager Assessment System (ALIAS) supports radiometric and geometric image processing for the Advanced Land Imager (ALI) instrument onboard NASA s Earth Observing-1 (EO-1) satellite. ALIAS consists of two processing subsystems for radiometric and geometric processing of the ALI s multispectral imagery. The radiometric processing subsystem characterizes and corrects, where possible, radiometric qualities including: coherent, impulse; and random noise; signal-to-noise ratios (SNRs); detector operability; gain; bias; saturation levels; striping and banding; and the stability of detector performance. The geometric processing subsystem and analysis capabilities support sensor alignment calibrations, sensor chip assembly (SCA)-to-SCA alignments and band-to-band alignment; and perform geodetic accuracy assessments, modulation transfer function (MTF) characterizations, and image-to-image characterizations. ALIAS also characterizes and corrects band-toband registration, and performs systematic precision and terrain correction of ALI images. This system can geometrically correct, and automatically mosaic, the SCA image strips into a seamless, map-projected image. This system provides a large database, which enables bulk trending for all ALI image data and significant instrument telemetry. Bulk trending consists of two functions: Housekeeping Processing and Bulk Radiometric Processing. The Housekeeping function pulls telemetry and temperature information from the instrument housekeeping files and writes this information to a database for trending. The Bulk Radiometric Processing function writes statistical information from the dark data acquired before and after the Earth imagery and the lamp data to the database for trending. This allows for multi-scene statistical analyses.

Chander, Gyanesh↗

The damage equivalence of electrons, protons, and gamma rays in MOS devices

The results of laboratory tests to determine the radiation damage effects induced on MOS devices from Co-60, electron, and proton radiation are reported. The tests are performed to establish the relationship between the Co-60 gamma rays and the level of damage to the MOS devices in regards to different damages which can be expected with the electron and particle bombardments experienced in space applications. CMOS devices were exposed to the Co-60 gamma rays, 1 MeV electrons, and 1 MeV protons while operating at 3, 10, and 15 V. The test data indicated that the Co-60 source was reliable for an initial evaluation of the electron damages up to 2 MeV charge. A correction factor was devised for transferring the Co-60 measurements to proton damages, independent of bias and transistor types, for any orbit or environment.

Brucker, G. J.↗

Brief Communication: Buoyancy-Induced Differences in Soot Morphology

Reduction or elimination of buoyancy in flames affects the dominant mechanisms driving heat transfer, burning rates and flame shape. The absence of buoyancy produces longer residence times for soot formation, clustering and oxidation. In addition, soot pathlines are strongly affected in microgravity. We recently conducted the first experiments comparing soot morphology in normal and reduced-gravity laminar gas jet diffusion flames. Thermophoretic sampling is a relatively new but well-established technique for studying the morphology of soot primaries and aggregates. Although there have been some questions about biasing that may be induced due to sampling, recent analysis by Rosner et al. showed that the sample is not biased when the system under study is operating in the continuum limit. Furthermore, even if the sampling is preferentially biased to larger aggregates, the size-invariant premise of fractal analysis should produce a correct fractal dimension.

Ku, Jerry C.↗

Transition in Turbine Flows

We have further developed our capabilities to analyze transition in turbine boundary layers from first principles by integrating the nonlinear parabolized stability equations (PSE) with improved initial and boundary conditions. With modified iteration schemes, we are able to proceed deeper into the transition region where skin friction coefficient and heat transfer coefficient significantly increase. Initial and boundary conditions at elevated turbulence levels can be derived by receptivity analysis. Test runs for ERCOFTAC test case T3A at 2.4\% turbulence level provide results in good agreement with the experimental data. The sharper minimum of the skin coefficient also shown by DNS results is likely due to the missing intermittency. The method has been applied to various experimentally studied turbine blades (UTRC, VKI, Zierke, Langston, Hippensteele, and others). The PSE results, though physically reasonable, do not agree as well as expected with the experimental findings. We have, therefore, performed an extensive search for the reasons of the seemingly systematic deviations. A first source of uncertainty has been found in the often insufficient documentation of the experiments (e.g. on blockage by end-wall boundary layers). However, variation of the relevant parameters does not lead to more satisfactory agreement. A second reason has been found in the "standard procedure" which considers a 2D flow at midspan and uses a panel code and subsequent boundary-layer code to obtain the laminar basic flow for the transition analysis. Comparison with the pressure distribution obtained with a 3D design code (RVC3D) shows significant three-dimensionality of the flow (e.g. in the UTRC experiments). The spanwise variation has been neglected in our original PSE code. To overcome this problem, we have developed the PSE/3D for fully 3D boundary layers to account for streamwise and spanwise variations. Since the design code does not provide the boundary-layer flow with sufficient resolution, we have generated the Euler solution and employed a 3D boundary-layer code to obtain the viscous basic flow. Although only the linear stability level of PSE/3D has been implemented so far, the discrepancies with the experiments change but do not disappear. We still find deviations between the computed and experimental variations of C(sub f), and St along the blade for laminar flow. The main reason can be seen by comparing the solution of the boundary-layer code with the viscous results of the design code. The conventional boundary-layer solution exhibits an asymptotic behavior appropriate in external aerodynamics but does not match the steep gradients of the inviscid flow through the passage and consequently provides biased results for C(sub f), and St. An attempt is currently being made to correct this deficiency. Before attempting to perform the transition analysis for the viscous flow provided by the design code, we have analyzed the implementation and "best possible" results. Code and results exhibit flaws that may negatively affect the design and are intolerable for transition analysis. Therefore, we have decided to develop a new code to obtain a reliable basis for stability and transition studies. We expect to report improved results by the time of the meeting.

Herbert, Thorwald↗

Volcanic Signatures in Estimates of Stratospheric Aerosol Size, Distribution Width, Surface Area, and Volume Deduced from Global Satellite-Based Observations

Volcanic signatures in the stratospheric aerosol layer are revealed by two independent techniques which retrieve aerosol information from global satellite-based observations of particulate extinction. Both techniques combine the 4-wavelength Stratospheric Aerosol and Gas Experiment (SAGE) II extinction measurements (0.385 <= lambda <= 1.02 microns) with the 7.96 micron and 12.82 micron extinction measurements from the Cryogenic Limb Array Etalon Spectrometer (CLAES) instrument. The algorithms use the SAGE II/CLAES composite extinction spectra in month-latitude-altitude bins to retrieve values and uncertainties of particle effective radius R(sub eff), surface area S, volume V and size distribution width sigma(sub R). The first technique is a multi-wavelength Look-Up-Table (LUT) algorithm which retrieves values and uncertainties of R(sub eff) by comparing ratios of extinctions from SAGE II and CLAES (e.g., E(sub lambda)/E(sub 1.02) to pre-computed extinction ratios which are based on a range of unimodal lognormal size distributions. The pre-computed ratios are presented as a function of R(sub eff) for a given sigma(sub g); thus the comparisons establish the range of R(sub eff) consistent with the measured spectra for that sigma(sub g). The fact that no solutions are found for certain sigma(sub g) values provides information on the acceptable range of sigma(sub g), which is found to evolve in response to volcanic injections and removal periods. Analogous comparisons using absolute extinction spectra and error bars establish the range of S and V. The second technique is a Parameter Search Technique (PST) which estimates R(sub eff) and sigma(sub g) within a month-latitude-altitude bin by minimizing the chi-squared values obtained by comparing the SAGE II/CLAES extinction spectra and error bars with spectra calculated by varying the lognormal fitting parameters: R(sub eff), sigma(sub g), and the total number of particles N(sub 0). For both techniques, possible biases in retrieved-parameters caused by assuming a unimodal functional form are removed using correction factors computed from representative in situ measurements of bimodal size distributions. Some interesting features revealed by the LUT and PST retrievals include: (1) Increases in S and V (but not R(sub eff)) after the Ruiz and Kelut injections, (2) Increases in S, V, R(sub eff) after Pinatubo, (3) Post-Pinatubo increases in S, V, and R(sub eff) that are more rapid in the tropics than elsewhere, (4) Mid-latitude post-Pinatubo increases in R(sub eff) that lag increases in S and V, (5) S and V returning to pre-Pinatubo values sooner than R(sub eff) does, (6) Sharp increases in sigma(sub g), after Pinatubo and slight increases in sigma(sub g) after Ruiz, Etna, Kelut, Spurr and Rabaul, and (7) Gradual declines in the heights at which R(sub eff), S and V peak after Pinatubo.

Bauman, J. J.↗

Anomalous Heat Budgets in the Interior Pacific Ocean on Seasonal- to -Timescales and Gyre Spacescales

This study quantifies uncertainties in closing the seasonal cycle of diabatic heat storage over the Pacific Ocean from 20 degrees S to 60 degrees N through the synthesis of World Ocean Circulation Experiment (WOCE) products over 7 years from 1993-1999. We utilize WOCE reanalysis products from the following sources: diabatic heat storage (DHS) from the Scripps Institution of Oceanography (SIO); near-surface geostrophic and Ekman currents from the Earth and Space Research (ESR); and air-sea heat fluxes from Comprehensive Ocean-Atmosphere Data Set (COADS), National Centers for Environmental Prediction (NCEP), and European Center for Mid-Range Weather Forecasts (ECMWF). We interpolate these products onto a common grid, allowing the seasonal cycle of DHS to be modeled for comparison with that observed. Everywhere latent heat flux residuals dominate sensible heat flux residuals and shortwave heat flux residuals dominate longwave heat flux residuals, both comparable in magnitude to the residual horizontal heat advection. We find the root-mean-square (RMS) of the differences between observed and model residual DHS tendencies to be less than 15 W per square meters everywhere except in the Kuroshio extension. Comparable COADS and NCEP products perform better than ECMWF products in the extra-tropics, while the NCEP product performs best in the tropics. Radiative and turbulent air-sea heat flux residuals computed from ship-born measurements perform better than those computed from satellite cloud and wind measurements. Since the RMS differences derive largely from biases in measured wind speed and cloud fraction, least-squares minimization is used to correct the residual Ekman heat advection and air-sea heat flux. Minimization reduces RMS differences less than 5 W per square meters except in the Kuroshio extension, suggesting how winds, clouds, and exchange coefficients in the NCEP, ECMWF, and ESR products can be improved.

White, Warren↗

The Salinity Retrieval Algorithms for the NASA Aquarius Version 5 and SMAP Version 3 Releases

The Aquarius end-of-mission (Version 5) salinity data set was released in December 2017. This article gives a comprehensive overview of the main steps of the Level 2 salinity retrieval algorithm. In particular, we will discuss the corrections for wind induced surface roughness, atmospheric oxygen absorption, reflected galactic radiation and side-lobe intrusion from land surfaces. Most of these corrections have undergone major updates from previous versions, which has helped mitigating temporal and zonal biases. Our article also discusses the ocean target calibration for Aquarius Version 5. We show how formal error estimates for the Aquarius retrievals can be obtained by perturbing the input to the algorithm. The performance of the Aquarius Version 5 salinity retrievals is evaluated against salinity measurements from the ARGO network and the HYCOM model. When stratified as function of sea surface temperature or sea surface wind speed, the difference between Aquarius Version 5 and ARGO is within +/-0.1 psu. The estimated global RMS uncertainty for monthly 100 km averages is 0.128 psu for the Aquarius Version 5 retrievals. Finally, we show how the Aquarius Version 5 salinity retrieval algorithm is adapted to retrieve salinity from the Soil-Moisture Active Passion (SMAP) mission.

retrieval algorithm↗

The Salinity Retrieval Algorithms for the NASA Aquarius Version 5 and SMAP Version 3 Releases

The Aquarius end-of-mission (Version 5) salinity data set was released in December 2017. This article gives a comprehensive overview of the main steps of the Level 2 salinity retrieval algorithm. In particular, we will discuss the corrections for wind induced surface roughness, atmospheric oxygen absorption, reflected galactic radiation and side-lobe intrusion from land surfaces. Most of these corrections have undergone major updates from previous versions, which has helped mitigating temporal and zonal biases. Our article also discusses the ocean target calibration for Aquarius Version 5. We show how formal error estimates for the Aquarius retrievals can be obtained by perturbing the input to the algorithm. The performance of the Aquarius Version 5 salinity retrievals is evaluated against salinity measurements from the ARGO network and the HYCOM model. When stratified as function of sea surface temperature or sea surface wind speed, the difference between Aquarius Version 5 and ARGO is within +-0.1 psu. The estimated global RMS uncertainty for monthly 100 km averages is 0.128 psu for the Aquarius Version 5 retrievals. Finally, we show how the Aquarius Version 5 salinity retrieval algorithm is adapted to retrieve salinity from the Soil-Moisture Active Passion (SMAP) mission.

calibration↗

A Computational Study of RNA Tetraloop Thermodynamics, Including Misfolded States

An important characteristic of RNA folding is the adoption of alternative configurations of similar stability, often referred to as misfolded configurations. These configurations are considered to compete with correctly folded configurations, although their rigorous thermodynamic and structural characterization remains elusive. Tetraloop motifs found in large ribozymes are ideal systems for an atomistically detailed computational quantification of folding free energy landscapes and the structural characterization of their constituent free energy basins, including nonnative states. In this work, we studied a group of closely related 10-mer tetraloops using a combined parallel tempering and metadynamics technique that allows a reliable sampling of the free energy landscapes, requiring only knowledge that the stem folds into a canonical A-RNA configuration. Here we isolated and analyzed unfolded, folded, and misfolded populations that correspond to different free energy basins. We identified a distinct misfolded state that has a stability very close to that of the correctly folded state. This misfolded state contains a predominant population that shares the same structural features across all tetraloops studied here and lacks the noncanonical A-G base pair in its loop portion. Further analysis performed with biased trajectories showed that although this competitive misfolded state is not an essential intermediate, it is visited in most of the transitions from unfolded to correctly folded states. Moreover, the tetraloops can transition from this misfolded state to the correctly folded state without requiring extensive unfolding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluation of the Snow Simulations from the Community Land Model, Version 4 (CLM4)

This paper evaluates the simulation of snow by the Community Land Model, version 4 (CLM4), the land model component of the Community Earth System Model, version 1.0.4 (CESM1.0.4). CLM4 was run in an offline mode forced with the corrected land-only replay of the Modern-Era Retrospective Analysis for Research and Applications (MERRA-Land) and the output was evaluated for the period from January 2001 to January 2011 over the Northern Hemisphere poleward of 30 deg N. Simulated snow-cover fraction (SCF), snow depth, and snow water equivalent (SWE) were compared against a set of observations including the Moderate Resolution Imaging Spectroradiometer (MODIS) SCF, the Interactive Multisensor Snow and Ice Mapping System (IMS) snow cover, the Canadian Meteorological Centre (CMC) daily snow analysis products, snow depth from the National Weather Service Cooperative Observer (COOP) program, and Snowpack Telemetry (SNOTEL) SWE observations. CLM4 SCF was converted into snow-cover extent (SCE) to compare with MODIS SCE. It showed good agreement, with a correlation coefficient of 0.91 and an average bias of -1.54 x 10(exp 2) sq km. Overall, CLM4 agreed well with IMS snow cover, with the percentage of correctly modeled snow-no snow being 94%. CLM4 snow depth and SWE agreed reasonably well with the CMC product, with the average bias (RMSE) of snow depth and SWE being 0.044m (0.19 m) and -0.010m (0.04 m), respectively. CLM4 underestimated SNOTEL SWE and COOP snow depth. This study demonstrates the need to improve the CLM4 snow estimates and constitutes a benchmark against which improvement of the model through data assimilation can be measured.

northern hemisphere↗

Toward Accurate Modeling of Galaxy Clustering on Small Scales: Halo Model Extensions and Lingering Tension

This paper represents an effort to provide robust constraints on the galaxy–halo connection and simultaneously test the Planck ΛCDM cosmology using a fully numerical model of small-scale galaxy clustering. We explore two extensions to the standard Halo Occupation Distribution model: assembly bias, whereby halo occupation depends on both halo mass and the larger environment, and velocity bias, whereby galaxy velocities do not perfectly trace the velocity of the dark matter within the halo. Moreover, we incorporate halo mass corrections to account for the impact of baryonic physics on the halo population. We identify an optimal set of clustering measurements to constrain this "decorated" HOD model for both low- and high-luminosity galaxies in SDSS DR7. We find that, for low-luminosity galaxies, a model with both assembly bias and velocity bias provides the best fit to the clustering measurements, with no tension remaining in the fit. In this model, we find evidence for both central and satellite galaxy assembly bias at the 99% and 95% confidence levels, respectively. In addition, we find evidence for satellite galaxy velocity bias at the 99.9% confidence level. For high-luminosity galaxies, we find no evidence for either assembly bias or velocity bias, but our model exhibits significant tension with SDSS measurements. We find that all of these conclusions still stand when we include the effects of baryonic physics on the halo mass function, suggesting that the tension we find for high-luminosity galaxies may be due to a problem with our assumed cosmological model.

79 ASTRONOMY AND ASTROPHYSICS↗

Constraining primordial non-Gaussianity with DESI 2024 LRG and QSO samples

We analyse the large-scale clustering of the Luminous Red Galaxy (LRG) and Quasar (QSO) sample from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI). In particular, we constrain the primordial non-Gaussianity (PNG) parameter f NL loc via the large-scale scale-dependent bias in the power spectrum using 1,631,716 LRGs (0.6 < z < 1.1) and 1,189,129 QSOs (0.8 < z < 3.1). This new measurement takes advantage of the enormous statistical power at large scales of DESI DR1 data, surpassing the latest data release (DR16) of the extended Baryon Oscillation Spectroscopic Survey (eBOSS). For the first time in this kind of analysis, we use a blinding procedure to mitigate the risk of confirmation bias in our results. We improve the model of the radial integral constraint proposing an innovative technique allowing the correction through the window matrix convolution. We also carefully test the mitigation of the dependence of the target selection on the photometry qualities by incorporating an angular integral constraint contribution to the window function, and validate our methodology with the blinded data. Finally, combining the two samples, we measure f NL loc = -3.6 -9.1 +9.0 at 68% confidence, where we assume the universality relation for the LRG sample and a recent merger model for the QSO sample about the response of bias to primordial non-Gaussianity. Adopting the universality relation for the PNG bias in the QSO analysis leads to f NL loc = 3.5 -7.4 +10.7 at 68% confidence. Due to restricted selection in the LRG sample, the inclusion of the LRGs allows for 10% improvement. This measurement is the most precise determination of primordial non-Gaussianity using large-scale structure to date, surpassing the latest result from eBOSS by a factor of 2.3.

79 ASTRONOMY AND ASTROPHYSICS↗