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NASA NTRS2021

Pluto’s Sputnik Planitia: Composition of geological units from infrared spectroscopy

We have compared spectroscopic data of Sputnik Planitia on Pluto, as acquired by New Horizons’ Linear Etalon Imaging Spectral Array (LEISA) instrument, to the geomorphology as mapped by White et al. (2017) using visible and panchromatic imaging acquired by the LOng-Range Reconnaissance Imager (LORRI) and the Multi-spectral Visible Imaging Camera (MVIC). We have focused on 13 of the geologic units identified by White et al. (2017), which include the plains and mountain units contained within the Sputnik basin. We divided the map of Sputnik Planitia into 15 provinces, each containing one or more geologic units, and we use LEISA to calculate the average spectra of the units inside the 15 provinces. Hapke-based modeling was then applied to the average spectra of the units to infer their surface composition, and to determine if the composition resulting from the modeling of LEISA spectra reflects the geomorphologic analyses of LORRI data, and if areas classified as being the same geologically, but which are geographically separated, share a similar composition. We investigated the spatial distribution of the most abundant ices on Pluto’s surface - CH4, N2, CO, H2O, and a non-ice component presumed to be a macromolecular carbon-rich material, termed a tholin, that imparts a positive spectral slope in the visible spectral region and a negative spectral slope longward of ~1.1 μm. Because the exact nature of the non-ice component is still debated and because the negative spectral slope of the available tholins in the near infrared does not perfectly match the Pluto data, for spectral modeling purposes we reference it generically as the negative spectral slope endmember (NSS endmember). We created maps of variations in the integrated band depth (from LEISA data) and areal mass fraction (from the modeling) of the components. The analysis of correlations between the occurrences of the endmembers in the geologic units led to the observation of an anomalous suppression of the strong CH4 absorption bands in units with compositions that are dominated by H2O ice and the NSS endmember. Exploring the mutual variation of the CH4 and N2 integrated band depths with the abundance of crystalline H2O and NSS endmember revealed that the NSS endmember is primarily responsible for the suppression of CH4 absorptions in mountainous units located along the western edge of Sputnik Planitia. Our spectroscopic analyses have provided additional insight into the geological processes that have shaped Sputnik Planitia. A general increase in volatile abundance from the north to the south of Sputnik Planitia is observed. Such an increase first observed and interpreted by Protopapa et al., 2017 and later confirmed by climate modeling (Bertrand et al., 2018) is expressed geomorphologically in the form of preferential deposition of N2 ice in the upland and mountainous regions bordering the plains of southern Sputnik Planitia. Relatively high amounts of pure CH4 are seen at the southern Tenzing Montes, which are a natural site for CH4 deposition owing to their great elevation and the lower insolation they are presently receiving. The NSS endmember correlates the existence of tholins within certain units, mostly those coating the low-latitude mountain ranges that are co-latitudinal with the tholin-covered Cthulhu Macula. The spectral analysis has also revealed compositional differences between the handful of occurrences of northern non-cellular plains and the surrounding cellular plains, all of which are located within the portion of Sputnik Planitia that is presently experiencing net sublimation of volatiles, and which do not therefore exhibit a surface layer of bright, freshly-deposited N2 ice. The compositional differences between the cellular and non-cellular plains here hint at the effectiveness of convection in entraining and trapping tholins within the body of the cellular plains, while preventing the spread of such tholins to abutting non-cellular plains.

Pluto's Sputnik Planitia↗
NASA NTRS1993

Do the spectral energy distributions of GK Tauri and HK Tauri indicate the presence of planetary companions?

The interpretation of the spectral dips of three objects (DF Tau, GK Tau, and HK Tau) for which lunar occultation data are available is discussed. Arguments against an alternate interpretation of the spectral dips (the 'disk-shell' model) are presented, and lunar occultation data are used to constrain the properties of the inferred orbiting companions. In the case of DF Tau, the occultation data indicate a stellar mass companion whose orbital radius is consistent with the present inferred gap location. For GK Tau and HK Tau, no such companions are visible, which suggests that the companions responsible for the inferred gaps are substellar. In either case, the estimated gap width is not consistent with a single orbiting body, but is consistent with a group of planets or planetesimals.

Marsh, Kenneth A.↗
DOE OSTI2022

QuantumNAT: quantum noise-aware training with noise injection, quantization and normalization

Parameterized Quantum Circuits (PQC) are promising towards quantum advantage on near-term quantum hardware. However, due to the large quantum noises (errors), the performance of PQC models has a severe degradation on real quantum devices. Take Quantum Neural Network (QNN) as an example, the accuracy gap between noise-free simulation and noisy results on IBMQ-Yorktown for MNIST-4 classification is over 60%. Existing noise mitigation methods are general ones without leveraging unique characteristics of PQC; on the other hand, existing PQC work does not consider noise effect. To this end, we present QuantumNAT, a PQC-specific framework to perform noise-aware optimizations in both training and inference stages to improve robustness. We experimentally observe that the effect of quantum noise to PQC measurement outcome is a linear map from noise-free outcome with a scaling and a shift factor. Motivated by that, we propose post-measurement normalization to mitigate the feature distribution differences between noise-free and noisy scenarios. Furthermore, to improve the robustness against noise, we propose noise injection to the training process by inserting quantum error gates to PQC according to realistic noise models of quantum hardware. Lastly, post-measurement quantization is introduced to quantize the measurement outcomes to discrete values, achieving the denoising effect. Extensive experiments on 8 classification tasks using 6 quantum devices demonstrate that QuantumNAT improves accuracy by up to 43%, and achieves over 94% 2-class, 80% 4-class, and 34% 10-class classification accuracy measured on real quantum computers. The code for construction and noise-aware training of PQC is available in the TorchQuantum library.

Wang, Hanrui↗
NASA NTRS1981

Calculation of atmospheric loss from microwave radiometric noise temperature measurements

Microwave propagation loss in the atmosphere can be inferred from microwave radiometric noise temperature measurements. The relevant equations are given and a derivation and calculation is made assuming various physical models. Comparison is made with the commonly used lumped element atmospheric model (isothermal and uniform loss) and the model with linear temperature and exponential loss distributions. The results are useful for estimating the integral inversion differences due to the model selection. This indicates that the commonly used lumped element atmospheric model is a very good approximation with judicious choice of the effective physical temperature. For the worst case comparison, the lumped element model agrees with the variable parameter model within 0.2 dB up to a propagation loss of 3 dB.

Stelzried, C.↗
NASA NTRS1992

A Backscatter Moessbauer Spectrometer (BaMS) for use on Mars

The use of Moessbauer spectroscopy for in situ analysis on the surface of Mars was proposed and the design and implementation of a backscatter Moessbauer spectrometer (BaMS) instrument suitable for planetary missions to the surfaces of Mars (MESUR), the Moon (Artemis and lunar outpost), asteroids, or other solid solar system objects is discussed. The BaMS instrument is designed to be capable of analysis of a sample for the mineralogy of its iron-bearing phases without any sample preparation. A requirement of lander missions to Mars is instrumentation for in situ mineralogical analyses. Such analyses provide data needed for primary characterization as to the type of surface materials present and by inference the processes that formed and subsequently modified them. For purposes of providing diagnostic information about naturally occurring materials, the element iron is particularly important because it is abundant and multivalent (primarily 0, +2, and +3 oxidation states). Knowledge of the oxidation state of iron and its distribution among iron-bearing mineralogies tightly constrains the types of materials present. The pivotal role of iron was already recognized in 1978 by COMPLEX, who recommended development of flight instruments that would identify mineralogy and the oxidation state of iron in planetary surface materials. The near-term U.S. strategy for the exploration of Mars is the MESUR (Mars Environmental SURvey) program, which entails emplacement of a network of small, long-lived surface landers. For the Moon, BaMS was recommended as part of a three-instrument landed payload for the Artemis missions, targeted for 1997. BaMS would prospect for ilmenite, an oxygen resource material, and provide data to assess the maturity of lunar soil. Because instrumental characteristics are low mass, low volume, and low power consumption, BaMS is suitable for implementation on even small landers and rovers, as are being envisioned in MESUR and Artemis concepts. In addition to providing highly diagnostic data, a BaMS analyzer is inherently simple and, as is highly desirable for remote operation, no sample preparation is required.

Agresti, D. G.↗
NASA NTRS1994

LET spectra of fragmented 600-MeV/A iron beam on aluminum and polyethylene: A preliminary analysis

An iron beam experiment recently conducted at the Lawrence Berkeley Laboratory Bevalac by Benton et al. provides an opportunity for verifying the new Green's function computer code (GRNTRN) and assessing the related nuclear database. The iron beam with 600 MeV/A at extraction traversed a series of beam transport elements, lead foil, and several triggering devices before impacting the target. Of these, only the 2.24 g/sq cm lead foil and target are considered in the transport analysis with an assumed (inferred from calibration) beam energy of 557 MeV/A. A thin layer of CR-39 plastic nuclear track detector (PNTD) was placed in front of the target to monitor the incident flux and a stack of four PNTD's placed behind to measure the linear energy transfer (LET) distribution of the transported beam. Test data are analyzed for three separate targets: 2 g/sq cm aluminum, 5-cm polyethylene, and 8-cm polyethylene. The two-layer GRNTRN results were mapped into the detector response function for comparison with the measured LET spectra. Reasonable agreement is obtained. Future research and analysis can be improved by using a more accurate isotope set or including other important media which significantly alter the beam. The assumption that the fragmentation cross sections are too small for aluminum is inconclusive because the production of fragments by 2 g/sq cm aluminum can be more significantly affected by the fragment contribution originating from the media in front of the target than that currently considered in the analysis.

Shinn, Judy L.↗
NASA NTRS1999

Jupiter's Deep Flowing Thermocline

The observed banded wind structure of Jupiter and Saturn remains an outstanding problem in planetary fluid dynamics. Both planets exhibit super-rotational equatorial jets (exceeding the underlying rotation of the magnetic fields tied to their deep fluid interiors), with speeds of some 100 and 400m/s, respectively, and counter-flowing lots at higher latitudes;. Recent analyses of the 1995 Galileo probe measurements, Hubble Telescope observations of the 1994 Shoemaker-Levy9 comet crash, and Earth-based infrared mapping provide evidence for a variably stratified, deeply seated flow layer. A now conceptual model for the jovian current system is proposed, in some ways resembling the oceanic thermocline, assuming a mixed distribution of potential vorticity atop a tropospheric wind layer of latitudinally variable stratification. A simple analytic version of the model links the strength, shape, and direction of the alternating zonal currents on Jupiter and Saturn to a single parameter equivalent to the internal deformation scale for an inferred deep stable region.

Allison, Michael↗
NASA NTRS2003

Gamma-Ray Bursts and Cosmology

The unrivalled, extreme luminosities of gamma-ray bursts (GRBs) make them the favored beacons for sampling the high redshift Universe. To employ GRBs to study the cosmic terrain -- e.g., star and galaxy formation history -- GRB luminosities must be calibrated, and the luminosity function versus redshift must be measured or inferred. Several nascent relationships between gamma-ray temporal or spectral indicators and luminosity or total energy have been reported. These measures promise to further our understanding of GRBs once the connections between the luminosity indicators and GRB jets and emission mechanisms are better elucidated. The current distribution of 33 redshifts determined from host galaxies and afterglows peaks near z $\sim$ 1, whereas for the full BATSE sample of long bursts, the lag-luminosity relation predicts a broad peak z $\sim$ 1--4 with a tail to z $\sim$ 20, in rough agreement with theoretical models based on star formation considerations. For some GRB subclasses and apparently related phenomena -- short bursts, long-lag bursts, and X-ray flashes -- the present information on their redshift distributions is sparse or entirely lacking, and progress is expected in Swift era when prompt alerts become numerous.

Norris, Jay P.↗
NASA NTRS2005

Star Formation Rates in Cooling Flow Clusters: A UV Pilot Study with Archival XMM-Newton Optical Monitor Data

We have analyzed XMM-Newton Optical Monitor (OM) UV (180-400 nm) data for a sample of 33 galaxies. 30 are cluster member galaxies, and nine of these are central cluster galaxies (CCGs) in cooling flow clusters having mass deposition rates which span a range of 8 - 525 solar mass per year. By comparing the ratio of UV to 2MASS J band fluxes, we find a significant UV excess in many, but not all, cooling flow CCGs, a finding consistent with the outcome of previous studies based on optical imaging data (McNamara & O Connell 1989; Cardiel, Gorgas, & Aragon-Salamanca 1998; Crawford et al. 1999). This UV excess is a direct indication of the presence of young massive stars, and therefore recent star formation, in these galaxies. Using the Starburst99 spectral energy distribution (SED) model of continuous star formation over a 900 Myr period, we derive star formation rates of 0.2 - 219 solar mass per year for the cooling flow sample. For 2/3 of this sample it is possible to equate Chandra/XMM cooling flow mass deposition rates with UV inferred star formation rates, for a combination of starburst lifetime and IMF slope. This is a pilot study of the well populated XMM UV cluster archive and a more extensive follow up study is currently underway.

Hicks, A. K.↗
NASA NTRS2012

Titan's Stratospheric Condensibles at High Northern Latitudes During Northern Winter

The Infrared Interferometer Spectrometer (IRIS) instrument on board Voyager 1 caught the first glimpse of an unidentified particulate feature in Titan's stratosphere that spectrally peaks at 221 per centimeter. Until recently, this feature that we have termed 'the haystack,' has been seen persistently at high northern latitudes with the Composite Infrared Spectrometer (CIRS) instrument onboard Cassini, The strength of the haystack emission feature diminishes rapidly with season, becoming drastically reduced at high northern latitudes, as Titan transitions from northern winter into spring, In contrast to IRIS whose shortest wavenumber was 200 per centimeter, CIRS extends down to 10 per centimeter, thus revealing an entirely unexplored spectral region in which nitrile ices have numerous broad lattice vibration features, Unlike the haystack, which is only found at high northern latitudes during northern winter/early northern spring, this geometrically thin nitrile cloud pervades Titan's lower stratosphere, spectrally peaking at 160 per centimeter, and is almost global in extent spanning latitudes 85 N to 600 S, The inference of nitrile ices are consistent with the highly restricted altitude ranges over which these features are observed, and appear to be dominated by a mixture of HCN and HC3N, The narrow range in altitude over which the nitrile ices extend is unlike the haystack, whose vertical distribution is significantly broader, spanning roughly 70 kilometers in altitude in Titan's lower stratosphere, The nitrile clouds that CIRS observes are located in a dynamically stable region of Titan's atmosphere, whereas CH4 clouds, which ordinarily form in the troposphere, form in a more dynamically unstable region, where convective cloud systems tend to occur. In the unusual situation where Titan's tropopause cools significantly from the HASI 70.5K temperature minimum, CH4 should condense in Titan's lower stratosphere, just like the aforementioned nitrile clouds, although in significantly larger abundances. We will present the spectral and vertical distribution of Titan's stratospheric particulates during northern winter on Titan. The drastically changing abundance of the haystack over a small latitude range will be highlighted, specifically comparing the IRIS and CIRS epochs, Finally, we will discuss the situation in which CH4 condenses in Titan's lower stratosphere, forming an unexpected quasi steady-state stratospheric Ice cloud.

Anderson, Carrie↗
DOE OSTI2022

Estimating Cosmological Constraints from Galaxy Cluster Abundance using Simulation-Based Inference

Inferring the values and uncertainties of cosmological parameters in a cosmology model is of paramount importance for modern cosmic observations. In this paper, we use the simulation-based inference (SBI) approach to estimate cosmological constraints from a simplified galaxy cluster observation analysis. Using data generated from the Quijote simulation suite and analytical models, we train a machine learning algorithm to learn the probability function between cosmological parameters and the possible galaxy cluster observables. The posterior distribution of the cosmological parameters at a given observation is then obtained by sampling the predictions from the trained algorithm. Our results show that the SBI method can successfully recover the truth values of the cosmological parameters within the 2σ limit for this simplified galaxy cluster analysis, and acquires similar posterior constraints obtained with a likelihood-based Markov Chain Monte Carlo method, the current state-of the-art method used in similar cosmological studies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1995

Constraints on the formation history of the elliptical galaxy NGC 3923 from the colors of its globular clusters

We present a study of the colors of globular clusters associated with the elliptical galaxy NGC 3923. Our final sample consists of Wasington system C and T(sub 1) photometry for 143 globular cluster candidates with an expected contamination of no more than 10%. We find that the color distribution of the NGC 3923 globular cluster system (GCS) is broad and appears to have at least two peaks. A mixture modeling analysis of the color distribution indicates that a two-component model is favored over a single-component one at a high level of confidence (greater than 99%). This evidence for more than one population in the GCS of NGC 3923 is similar to that previously noted for the four other elliptical galaxies for which similar data have been published. Furthermore, we find that the NGC 3923 GCS is redder than the GCSs of previously studed elliptical galaxies of similar luminosity. The median metallicity inferred from our (C-(T(sub 1)))(sub 0) colors is (Fe/H)(sub med) = -0.56, with an uncertainty of 0.14 dex arising from all sources of uncertainty in the mean color. This is more metal rich than the median metallicity found for the GCS of M87 using the same method, (Fe/H)(sub med) = -0.94. Since M87 is more luminous than NGC 3923, this result points to significant scatter about any trend of higher GCS metallicity with increasing galaxy luminosity. We also show that there is a color gradient in the NGC 3923 GCS corresponding to about -0.5 dex in Delta(Fe/H)/Delta(log r). We conclude that the shape of the color distribution of individual GCSs and the variation in mean color among the GCSs of ellipticals are difficult to understand if elliptical galaxies are formed in a single protogalactic collapse. Models in which ellipticals and their globular clusters are formed in more than one event, such as a merger scenario, are more successful in accounting for these observations.

Zepf, Stephen E.↗
NASA NTRS1988

Tropopause adjustment to tropical cyclones as inferred from satellite ozone observations

Data from the Total Ozone Mapping Spectrometer on the Nimbus-7 are used to map the climatological total ozone within and around tropical cyclones. A tropical cyclone numerical model is used to interpret total ozone patterns. The total ozone maps are used to diagnose storm intensity and to differentiate between intesifying and weakening tropical cyclones. The tropical cyclone intensity versus total ozone anomaly distribution is examined and examples of mapping the total ozone of tropical cyclones in the period 1979-1982 are presented.

Rodgers, Edward B.↗
DOE OSTI2025

A segmented approach to modeling building height: Delineating high-rise and low-rise buildings for enhanced height estimation

Understanding building height is imperative to the overall study of energy efficiency, population distribution, urban morphologies, emergency response, among others. Currently, existing approaches for modeling building height at scale are hindered by two pervasive issues. First, there is no consistent approach to quantify what a high-rise building is at a macro scale, leaving researchers unable to accurately compare results across geographies and domains. Second, high-rise buildings represent a small fraction of the built environment, implying data imbalance challenges that negatively affect current approaches. This is a problem of practical relevance since information on high-rise buildings is important for studies on urban heat islands, population dynamics, and pollution dispersion. Here, we introduce a novel approach to map building height which first identifies two distinct distributions within the built environment, with one being composed of low-rise buildings and one composed of high-rise buildings. We then develop an ensemble scheme where discrete specialist models are trained for each subset of low-rise buildings and high-rise buildings to infer building height from morphology features. For experiments mapping heights of 4.85 million buildings in Japan, we show an increase of 34 % in accuracy within 3m error when compared to the current state-of-the-art when modeling high-rise buildings, which based on KNN experimentation we define as any building > 12m . Our findings show that such an ensemble framework outperforms the current state-of-the-art approaches, which is especially relevant in relation to inferring height for high-rise buildings, a prominent issue of existing approaches for mapping the built environment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Exploring the Use of Non‐Invasive Drone‐Based Ground‐Penetrating Radar (GPR) to Characterize Biogenic Gas Dynamics in Subtropical Peat Soils

Peat soils are a critical component of the global carbon cycle as natural producers of biogenic greenhouse gases (e.g., methane and carbon dioxide) that accumulate within the soil and are released to the atmosphere. Previous studies have showed the ability of ground-based minimally-invasive geophysical methods such as ground-penetrating radar (GPR) to characterize carbon dynamics in peat soils. However, ground-based GPR is limited by scale of measurement and soil disturbance potentially altering gas releases during deployment. Here, we explore the potential of drone-based GPR for identification of hot spots and hot moments of gas accumulation and release in subtropical soils. Here, we collected drone-based GPR data sets across two grids (∼17,500 m 2 ) in the Everglades during January (dry season), September, and November (wet season) of 2023 to characterize peat thickness and seasonal variability of gas content. Results show that drone-based GPR is effective and efficient for: (a) capturing the temporal variation of in situ biogenic gas content in peat soils with changes between 1% and 25 % volumetric gas content over repeatable grids; (b) inferring a total peat thickness between 0.8 and 1.2 m; and (c) estimating flux releases of 63 and 135 mg CH 4 m −2 day −1 for specific locations and periods that are strikingly consistent with our coincident gas trap measurements. This work also indicates that (a) spatial distribution of gas content in the Everglades is strongly controlled by landscape morphology such as ridges and sloughs and (b) the temporal variation of gas content is seasonal with increased gas production during the wet season.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Forecasting constraints on the mean free path of ionizing photons at z ≥ 5.4 from the Lyman-α forest flux autocorrelation function

ABSTRACT Fluctuations in Lyman-α (Ly α) forest transmission towards high-z quasars are partially sourced from spatial fluctuations in the ultraviolet background, the level of which are set by the mean free path of ionizing photons (λmfp). The autocorrelation function of Ly α forest flux characterizes the strength and scale of transmission fluctuations and, as we show, is thus sensitive to λmfp. Recent measurements at z ∼ 6 suggest a rapid evolution of λmfp at z > 5.0 which would leave a signature in the evolution of the autocorrelation function. For this forecast, we model mock Ly α forest data with properties similar to the XQR-30 extended data set at 5.4 ≤ z ≤ 6.0. At each z, we investigate 100 mock data sets and an ideal case where mock data matches model values of the autocorrelation function. For ideal data with λmfp = 9.0 cMpc at z = 6.0, we recover $\lambda _{\text{mfp}}=12^{+6}_{-3}$ cMpc. This precision is comparable to direct measurements of λmfp from the stacking of quasar spectra beyond the Lyman limit. Hypothetical high-resolution data leads to a $\sim 40~{{\ \rm per\ cent}}$ reduction in the error bars over all z. The distribution of mock values of the autocorrelation function in this work is highly non-Gaussian for high-z, which should caution work with other statistics of the high-z Ly α forest against making this assumption. We use a rigorous statistical method to pass an inference test, however future work on non-Gaussian methods will enable higher precision measurements.

Astronomy & Astrophysics↗
DOE OSTI2021

Combining Electromagnetic and Gravitational-Wave Constraints on Neutron-Star Masses and Radii

In this work, we perform a joint Bayesian inference of neutron-star mass and radius constraints based on GW170817, observations of quiescent low-mass x-ray binaries (QLMXBs), photospheric radius expansion x-ray bursting sources, and x-ray timing observations of J0030+0451. With this dataset, the form of the prior distribution still has an impact on the posterior mass-radius curves and equation of state (EOS), but this impact is smaller than recently obtained when considering QLMXBs alone. We analyze the consistency of the electromagnetic data by including an “intrinsic scattering” contribution to the uncertainties, and find only a slight broadening of the posteriors. This suggests that the gravitational-wave and electromagnetic observations of neutron-star structure are providing a consistent picture of the neutron-star mass-radius curve and the EOS.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The DESI-Lensing Mock Challenge: large-scale cosmological analysis of 3x2-pt statistics

The current generation of large galaxy surveys will test the cosmological model by combining multiple types of observational probes. Realising the statistical promise of these new datasets requires rigorous attention to all aspects of analysis including cosmological measurements, modelling, covariance and parameter likelihood. In this paper we present the results of an end-to-end simulation study designed to test the analysis pipeline for the combination of the Dark Energy Spectroscopic Instrument (DESI) Year 1 galaxy redshift dataset and separate weak gravitational lensing information from the Kilo-Degree Survey, Dark Energy Survey and Hyper-Suprime-Cam Survey. Our analysis employs the 3x2-pt correlation functions including cosmic shear and galaxy-galaxy lensing, together with the projected correlation function of the spectroscopic DESI lenses. We build realistic simulations of these datasets including galaxy halo occupation distributions, photometric redshift errors, weights, multiplicative shear calibration biases and magnification. We calculate the analytical covariance of these correlation functions including the Gaussian, noise and super-sample contributions, and show that our covariance determination agrees with estimates based on the ensemble of simulations. We use a Bayesian inference platform to demonstrate that we can recover the fiducial cosmological parameters of the simulation within the statistical error margin of the experiment, investigating the sensitivity to scale cuts. This study is the first in a sequence of papers in which we present and validate the large-scale 3x2-pt cosmological analysis of DESI-Y1.

79 ASTRONOMY AND ASTROPHYSICS↗