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NASA NTRS2000

Non-Systematic Errors of Monthly Oceanic Rainfall Derived From TMI

A major objective of the Tropical Rainfall Measuring Mission (TRMM) is to produce a multi-year time series of monthly rainfall over 50 latitude by 50 longitude boxes with an uncertainty of 1 mm/day for low rain rates and 10% for high rain rates. Based on some simple assumptions about the error structure, we compute the non-systematic errors of monthly oceanic rainfall over the same space/time domain derived from data taken by the Special Sensor Microwave Imager (SSM/I) on board the Defense Meteorological Satellite Program (DMSP) satellites and TRMM Microwave Imager (TMI). The mean rain rates over a two-year period (1998-1999) are calculated to be 3.0, 2.85, 2.94 mm/day for SSM/I onboard the DMSP F-13, F-14 and TMI, respectively. Assuming that the non-systematic errors for each sensor are independent, the errors are calculated to be 22.2%, 22.4% and 19.7% for F-13, F-14 and for TMI, respectively. The non-systematic error for the TMI is smaller than that for either F-13 or F-14 SSM/I at the low rain rates but is comparable at rain rates higher than about 5 mm/day. The TRMM objective of 1 mm/day for non-systematic error is met by TMI for rain rates up to 5-6 mm/day. For higher rain rates, the nonsystematic error is in the 15% range. The goal of a 10% error for high rain rates may be realized by a combination of sensor measurements from multiple satellites, such as that advocated by the Global Precipitation Mission (GPM).

Chiu, Long S.↗

NASA NTRS2003

First Year Wilkinson Microwave Anisotropy Probe(WMAP) Observations: Data Processing Methods and Systematic Errors Limits

We describe the calibration and data processing methods used to generate full-sky maps of the cosmic microwave background (CMB) from the first year of Wilkinson Microwave Anisotropy Probe (WMAP) observations. Detailed limits on residual systematic errors are assigned based largely on analyses of the flight data supplemented, where necessary, with results from ground tests. The data are calibrated in flight using the dipole modulation of the CMB due to the observatory's motion around the Sun. This constitutes a full-beam calibration source. An iterative algorithm simultaneously fits the time-ordered data to obtain calibration parameters and pixelized sky map temperatures. The noise properties are determined by analyzing the time-ordered data with this sky signal estimate subtracted. Based on this, we apply a pre-whitening filter to the time-ordered data to remove a low level of l/f noise. We infer and correct for a small (approx. 1 %) transmission imbalance between the two sky inputs to each differential radiometer, and we subtract a small sidelobe correction from the 23 GHz (K band) map prior to further analysis. No other systematic error corrections are applied to the data. Calibration and baseline artifacts, including the response to environmental perturbations, are negligible. Systematic uncertainties are comparable to statistical uncertainties in the characterization of the beam response. Both are accounted for in the covariance matrix of the window function and are propagated to uncertainties in the final power spectrum. We characterize the combined upper limits to residual systematic uncertainties through the pixel covariance matrix.

Hinshaw, G.↗

NASA NTRS2012

The Effect of Systematic Error in Forced Oscillation Testing

One of the fundamental problems in flight dynamics is the formulation of aerodynamic forces and moments acting on an aircraft in arbitrary motion. Classically, conventional stability derivatives are used for the representation of aerodynamic loads in the aircraft equations of motion. However, for modern aircraft with highly nonlinear and unsteady aerodynamic characteristics undergoing maneuvers at high angle of attack and/or angular rates the conventional stability derivative model is no longer valid. Attempts to formulate aerodynamic model equations with unsteady terms are based on several different wind tunnel techniques: for example, captive, wind tunnel single degree-of-freedom, and wind tunnel free-flying techniques. One of the most common techniques is forced oscillation testing. However, the forced oscillation testing method does not address the systematic and systematic correlation errors from the test apparatus that cause inconsistencies in the measured oscillatory stability derivatives. The primary objective of this study is to identify the possible sources and magnitude of systematic error in representative dynamic test apparatuses. Sensitivities of the longitudinal stability derivatives to systematic errors are computed, using a high fidelity simulation of a forced oscillation test rig, and assessed using both Design of Experiments and Monte Carlo methods.

Williams, Brianne Y.↗

NASA NTRS2012

A Practical Methodology for Quantifying Random and Systematic Components of Unexplained Variance in a Wind Tunnel

This paper documents a check standard wind tunnel test conducted in the Langley 0.3-Meter Transonic Cryogenic Tunnel (0.3M TCT) that was designed and analyzed using the Modern Design of Experiments (MDOE). The test designed to partition the unexplained variance of typical wind tunnel data samples into two constituent components, one attributable to ordinary random error, and one attributable to systematic error induced by covariate effects. Covariate effects in wind tunnel testing are discussed, with examples. The impact of systematic (non-random) unexplained variance on the statistical independence of sequential measurements is reviewed. The corresponding correlation among experimental errors is discussed, as is the impact of such correlation on experimental results generally. The specific experiment documented herein was organized as a formal test for the presence of unexplained variance in representative samples of wind tunnel data, in order to quantify the frequency with which such systematic error was detected, and its magnitude relative to ordinary random error. Levels of systematic and random error reported here are representative of those quantified in other facilities, as cited in the references.

Deloach, Richard↗

NASA NTRS2016

Marginalizing Instrument Systematics in HST WFC3 Transit Light Curves

Hubble Space Telescope (HST) Wide Field Camera 3 (WFC3) infrared observations at 1.1-1.7 microns probe primarily the H2O absorption band at 1.4 microns, and have provided low-resolution transmission spectra for a wide range of exoplanets. We present the application of marginalization based on Gibson to analyze exoplanet transit light curves obtained from HST WFC3 to better determine important transit parameters such as "ramp" probability (R (sub p)) divided by "ramp" total (R (sub asterisk)), which are important for accurate detections of H2O. We approximate the evidence, often referred to as the marginal likelihood, for a grid of systematic models using the Akaike Information Criterion. We then calculate the evidence-based weight assigned to each systematic model and use the information from all tested models to calculate the final marginalized transit parameters for both the band-integrated and spectroscopic light curves to construct the transmission spectrum. We find that a majority of the highest weight models contain a correction for a linear trend in time as well as corrections related to HST orbital phase. We additionally test the dependence on the shift in spectral wavelength position over the course of the observations and find that spectroscopic wavelength shifts delta (sub lambda) times lambda) best describe the associated systematic in the spectroscopic light curves for most targets while fast scan rate observations of bright targets require an additional level of processing to produce a robust transmission spectrum. The use of marginalization allows for transparent interpretation and understanding of the instrument and the impact of each systematic evaluated statistically for each data set, expanding the ability to make true and comprehensive comparisons between exoplanet atmospheres.

Wakeford, H. R.↗

DOE OSTI2022

Systematic quark/gluon identification with ratios of likelihoods

Discriminating between quark- and gluon-initiated jets has long been a central focus of jet substructure, leading to the introduction of numerous observables and calculations to high perturbative accuracy. At the same time, there have been many attempts to fully exploit the jet radiation pattern using tools from statistics and machine learning. We propose a new approach that combines a deep analytic understanding of jet substructure with the optimality promised by machine learning and statistics. After specifying an approximation to the full emission phase space, we show how to construct the optimal observable for a given classification task. This procedure is demonstrated for the case of quark and gluons jets, where we show how to systematically capture sub-eikonal corrections in the splitting functions, and prove that linear combinations of weighted multiplicity is the optimal observable. In addition to providing a new and powerful framework for systematically improving jet substructure observables, we demonstrate the performance of several quark versus gluon jet tagging observables in parton-level Monte Carlo simulations, and find that they perform at or near the level of a deep neural network classifier. Combined with the rapid recent progress in the development of higher order parton showers, we believe that our approach provides a basis for systematically exploiting subleading effects in jet substructure analyses at the Large Hadron Collider (LHC) and beyond.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Cadmium isotope systematics in sedimentary carbonate: Extending the utility of the cadmium isotope palaeo-productivity proxy

The cadmium (Cd) isotope compositions of seven Holocene (<11.7 ka) carbonate sediments, including the bulk carbonate, as well as the > 140 μm (zooplankton), <63 μm and < 20 μm (phytoplankton) fractions, and individual species of foraminifera isolated from the bulk carbonate were obtained for sub-samples processed using the Cd-cleaning and Mg/Ca cleaning methods. The respective Cd isotope systematics of each carbonate archive were then compared with the Cd isotope signature within the ocean using modern seawater data. We show that a constant Cd isotope fractionation factor of -0.25 ± 0.03 ‰ (2SE, n = 4) describes the partitioning of Cd from seawater into the carbonate phase ($Δ^{114}Cd_{CdC O_3 - seawater}$), allowing for accurate reconstructions of the past seawater nutrient regime. The Cd isotope signature of the < 63 µm and < 20 µm (phytoplankton) fractions can display comparable values to those recorded in the modern surface ocean, and can be used to model the magnitude of Cd uptake and utilisation in the past ocean. Individual species of planktic and benthic foraminifera, which inhabit different depths of the water column, can provide a full surface to deep water column reconstruction of the Cd nutrient regime, while infaunal benthic foraminifera can be used to interrogate the Cd isotope systematics of sediment porewaters. Bulk sediment and the > 140 µm (zooplankton) fraction also retain important information relating to the overlying water column Cd isotope systematics and can serve as essential archives for palaeo-productivity reconstructions where the separation of individual components from the bulk sediment is not possible. This new Cd isotope palaeo-productivity toolkit can considerably aid reconstruction efforts and vastly improves the ability to quantify the role of phytoplankton in modulating carbon sequestration through transitions in Earth’s climate evolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Prevalence of Listeria monocytogenes , Salmonella spp., Shiga toxin-producing Escherichia coli , and Campylobacter spp. in raw milk in the United States between 2000 and 2019: A systematic review and meta-analysis

Raw (unpasteurized) milk is available for sale and direct human consumption within some states in the United States (US); it cannot be sold or distributed in interstate commerce. Raw milk may contain pathogenic microorganisms that, when consumed, may cause illness and sometimes may result in death. No comprehensive review for prevalence and levels of the major bacterial pathogens in raw milk in the US exists. The objective of the present research was to systematically review the scientific literature published from 2000 to 2019 to estimate the prevalence and levels of Listeria monocytogenes, Salmonella spp., Shiga toxin-producing Escherichia coli (STEC), and Campylobacter spp. in raw milk in the US. Peer-reviewed studies were retrieved systematically from PubMed®, Embase®, and Web of ScienceTM. The unique complete nonduplicate references were uploaded into the Health Assessment Work Collaborative (HAWC). Based on the selection criteria, twenty studies were included in the systematic review and meta-analysis. Comprehensive Meta-Analysis (CMA) was used for statistical analyses, specifically, random effects meta-analyses were used to synthesize raw bulk tank milk (BTM) and milk filters (MF) data. Data from studies using culture and non–culture-based detection methods were included. Forest plots generated in CMA (Biostat, Englewood, NJ) were used to visualize the results. The average prevalence (event rate) of L. monocytogenes, Salmonella spp., STEC, and Campylobacter spp. in raw BTM in the US was estimated at 4.3% (95% confidence intervals [CIs], 2.8–6.5%), 3.6% (95% CIs, 2.0–6.2%), 4.3% (95% CIs, 2.4–7.4%), and 6.0% (95% CIs, 3.2–10.9%), respectively. Estimated prevalence was generally larger in MF than in BTM. There was not enough data to perform a meta-analysis for the prevalence or levels of pathogens in raw milk from retail establishments or other milk categories.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Systematic characterization of human gut microbiome-secreted molecules by integrated multi-omics

The human gut microbiome produces a complex mixture of biomolecules that interact with human physiology and play essential roles in health and disease. Crosstalk between micro-organisms and host cells is enabled by different direct contacts, but also by the export of molecules through secretion systems and extracellular vesicles. The resulting molecular network, comprised of various biomolecular moieties, has so far eluded systematic study. Here we present a methodological framework, optimized for the extraction of the microbiome-derived, extracellular biomolecular complement, including nucleic acids, (poly)peptides, and metabolites, from flash-frozen stool samples of healthy human individuals. Our method allows simultaneous isolation of individual biomolecular fractions from the same original stool sample, followed by specialized omic analyses. The resulting multi-omics data enable coherent data integration for the systematic characterization of this molecular complex. Our results demonstrate the distinctiveness of the different extracellular biomolecular fractions, both in terms of their taxonomic and functional composition. This highlights the challenge of inferring the extracellular biomolecular complement of the gut microbiome based on single-omic data. The developed methodological framework provides the foundation for systematically investigating mechanistic links between microbiome-secreted molecules, including those that are typically vesicle-associated, and their impact on host physiology in health and disease.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

J-PLUS: Systematic impact of metallicity on photometric calibration with the stellar locus

Here, we present the photometric calibration of the twelve optical passbands for the Javalambre Photometric Local Universe Survey (J-PLUS) second data release (DR2), comprising 1088 pointings of two square degrees, and study the systematic impact of metallicity on the stellar locus technique. The [Fe/H] metallicity from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) for 146 184 high-quality calibration stars, defined with signal-to-noise ratio larger than ten in J-PLUS passbands and larger than three in Gaia parallax, was used to compute the metallicity-dependent stellar locus (ZSL). The initial homogenization of J-PLUS photometry, performed with a unique stellar locus, was refined by including the metallicity effect in colors via the ZSL. The variation of the average metallicity along the Milky Way produces a systematic offset in J-PLUS calibration. This effect is well above 1% for the bluer passbands and amounts 0.07, 0.07, 0.05, 0.03, and 0.02 mag in u, J0378, J0395, J0410, and J0430, respectively. We modeled this effect with the Milky Way location of the J-PLUS pointing, also providing an updated calibration for those observations without LAMOST information. The estimated accuracy in the calibration after including the metallicity effect is at 1% for the bluer J-PLUS passbands and below for the rest. Photometric calibration with the stellar locus technique is prone to significant systematic bias in the Milky Way for passbands bluer than λ = 4500 Å. The calibration method for J-PLUS DR2 reaches 1–2% precision and 1% accuracy for 12 optical filters within an area of 2176 square degrees.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

TDCOSMO VIII. A key test of systematics in the hierarchical method of time-delay cosmography

The largest source of systematic errors in the time-delay cosmography method likely arises from the lens model mass distribution, where an inaccurate choice of model could in principle bias the value of $H$ 0 . A Bayesian hierarchical framework has been proposed which combines lens systems with kinematic data, constraining the mass profile shape at a population level. The framework has been previously validated using a small sample of lensing galaxies drawn from hydro-simulations. The goal of this work is to expand the validation to a more general set of lenses consistent with observed systems, as well as confirm the capacity of the method to combine two lens populations: one which has time delay information and one which lacks time delays and has systematically different image radii. For this purpose, we generated samples of analytic lens mass distributions made of baryons+dark matter and fit the subsequent mock images with standard power-law models. Corresponding kinematics data were also emulated. The hierarchical framework applied to an ensemble of time-delay lenses allowed us to correct the $H$ 0 bias associated with model choice to find $H$ 0 within 1.5σ of the fiducial value. We then combined this set with a sample of corresponding lens systems which have no time delays and have a source at lower $z$, resulting in a systematically smaller image radius relative to their effective radius. The hierarchical framework has successfully accounted for this effect, recovering a value of $H$ 0 which is both more precise (σ ~ 2%) and more accurate (0.7% median offset) than the time-delay set alone. This result confirms that non-time-delay lenses can nonetheless contribute valuable constraining power to the determination of $H$ 0 via their kinematic constraints, assuming they come from the same global population as the time-delay set.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

ELG spectroscopic systematics analysis of the DESI Data Release 1

Dark Energy Spectroscopic Instrument (DESI) uses more than 2.4 million Emission Line Galaxies (ELGs) for 3D large-scale structure (LSS) analyses in its Data Release 1 (DR1). Such large statistics enable thorough research on systematic uncertainties. In this study, we focus on spectroscopic systematics of ELGs. The redshift success rate (f goodz ) is the relative fraction of secure redshifts among all measurements. It depends on observing conditions, thus introduces non-cosmological variations to the LSS. We, therefore, develop the redshift failure weight (w zfail ) and a per-fibre correction (η zfail ) to mitigate these dependences. They have minor influences on the galaxy clustering. For ELGs with a secure redshift, there are two subtypes of systematics: 1) catastrophics (large) that only occur in a few samples; 2) redshift uncertainty (small) that exists for all samples. The catastrophics represent 0.26% of the total DR1 ELGs, composed of the confusion between [O ii] and sky residuals, double objects, total catastrophics and others. We simulate the realistic 0.26% catastrophics of DR1 ELGs, the hypothetical 1% catastrophics, and the truncation of the contaminated 1.31 < z < 1.33 in the A BACUS S UMMIT ELG mocks. Their P ℓ show non-negligible bias from the uncontaminated mocks. But their influences on the redshift space distortions (RSD) parameters are smaller than 0.2σ. The redshift uncertainty of DR1 ELGs is 8.5km s -1 with a Lorentzian profile. The code for implementing the catastrophics and redshift uncertainty on mocks can be found in https://github.com/Jiaxi-Yu/modelling_spectro_sys.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Primordial non-Gaussianity from the completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey – I: Catalogue preparation and systematic mitigation

ABSTRACT We investigate the large-scale clustering of the final spectroscopic sample of quasars from the recently completed extended Baryon Oscillation Spectroscopic Survey (eBOSS). The sample contains 343 708 objects in the redshift range 0.8 < z < 2.2 and 72 667 objects with redshifts 2.2 < z < 3.5, covering an effective area of $4699\, {\rm deg}^{2}$. We develop a neural network-based approach to mitigate spurious fluctuations in the density field caused by spatial variations in the quality of the imaging data used to select targets for follow-up spectroscopy. Simulations are used with the same angular and radial distributions as the real data to estimate covariance matrices, perform error analyses, and assess residual systematic uncertainties. We measure the mean density contrast and cross-correlations of the eBOSS quasars against maps of potential sources of imaging systematics to address algorithm effectiveness, finding that the neural network-based approach outperforms standard linear regression. Stellar density is one of the most important sources of spurious fluctuations, and a new template constructed using data from the Gaia spacecraft provides the best match to the observed quasar clustering. The end-product from this work is a new value-added quasar catalogue with the improved weights to correct for non-linear imaging systematic effects, which will be made public. Our quasar catalogue is used to measure the local-type primordial non-Gaussianity in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Progenitors and explosion properties of supernova remnants hosting central compact objects: II. A global systematic study with a comparison to nucleosynthesis models

ABSTRACT Core-collapse explosions of massive stars leave behind neutron stars, with a known diversity that includes the ‘Central Compact Objects’ (CCOs). Typified by the neutron star discovered near the centre of the Cas A supernova remnant (SNR), CCOs have been observed to shine only in X-rays. To address their supernova progenitors, we perform a systematic study of SNRs that contain a CCO and display X-ray emission from their shock-heated ejecta. We make use of X-ray data primarily using the Chandra X-ray observatory, complemented with XMM–Newton. This study uses a systematic approach to the analysis of each SNR aimed at addressing the supernova progenitor as well as the explosion properties (energy and ambient density). After fitting for the ejecta abundances estimated from a spatially resolved spectroscopic study, we compare the data to six nucleosynthesis models making predictions on supernova ejecta yields in core-collapse explosions. We find that the explosion models commonly used by the astrophysics community do not match the ejecta yields for any of the SNRs, suggesting additional physics, for example multidimensional explosion models or updated progenitor structures, are required. Overall we find low-mass (≤25 solar masses) progenitors among the massive stars population and low-energy explosions (<1051 ergs). We discuss degeneracies in our model fitting, particularly how altering the explosion energy affects the estimate of the progenitor mass. Our systematic study highlights the need for improving on the theoretical models for nucleosynthesis predictions as well as for sensitive, high-resolution spectroscopy observations to be acquired with next generation X-ray missions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Baryon acoustic oscillation theory and modelling systematics for the DESI 2024 results

This paper provides a comprehensive overview of how fitting of baryon acoustic oscillations (BAO) is carried out within the upcoming Dark Energy Spectroscopic Instrument’s (DESI) 2024 results using its DR1 data set, and the associated systematic error budget from theory and modelling of the BAO. We derive new results showing how non-linearities in the clustering of galaxies can cause potential biases in measurements of the isotropic (⁠α iso ⁠) and anisotropic (⁠α ap ) BAO distance scales, and how these can be effectively removed with an appropriate choice of reconstruction algorithm. We then demonstrate how theory leads to a clear choice for how to model the BAO and develop, implement, and validate a new model for the remaining smooth-broad-band (i.e. without BAO) component of the galaxy clustering. Finally, we explore the impact of all remaining modelling choices on the BAO constraints from DESI using a suite of high-precision simulations, arriving at a set of best practices for DESI BAO fits, and an associated theory and modelling systematic error. Overall, our results demonstrate the remarkable robustness of the BAO to all our modelling choices and motivate a combined theory and modelling systematic error contribution to the post-reconstruction DESI BAO measurements of no more than 0.1 per cent (0.2 per cent) for its isotropic (anisotropic) distance measurements. We expect the theory and best practices laid out to here to be applicable to other BAO experiments in the era of DESI and beyond.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Dark matter substructure or source model systematics? A case study of cluster lens Abell S1063

Mapping the small-scale structure of the universe through gravitational lensing is a promising tool for probing the particle nature of dark matter. Curved Arc Basis (CAB) has been proposed as a local lensing formalism in galaxy clusters, with the potential to detect low-mass dark matter substructure. In this work, we analyse the cluster lens Abell S1063 in search of dark matter substructure with the CAB formalism, using multiband imaging data from James Webb Space Telescope ( JWST ). We use two different source modelling methods: shapelets and pixel-based source reconstruction based on Delaunay triangulation. We find that source modelling systematics from shapelets result in a disagreement between CAB parameters measured from different filters. Source modelling with Delaunay significantly alleviates this systematic, as seen in the improvement in agreement across filters. We also find that inadequate complexity in source modelling can result in convincing spurious detections of dark matter substructure from strong gravitational lenses, as seen by our $\Delta \text{BIC} > 20$ measurement of a $M \sim 10^{10}$ ${\rm M}_{\odot }$ subhalo with shapelets, a spurious detection that is not reproduced with Delaunay source modelling. We demonstrate that multiband analysis with different JWST filters is key for disentangling source and lens model systematics from dark matter substructure detections.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Cosmology requirements on supernova photometric redshift systematics for the Rubin LSST and Roman Space Telescope

Some million type Ia supernovae (SN) will be discovered and monitored during upcoming wide area time domain surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). For cosmological use, accurate redshifts are needed among other characteristics; however the vast majority of the SN will not have spectroscopic redshifts, even for their host galaxies, only photometric redshifts. We assess the redshift systematic control necessary for robust cosmology. Based on the photometric vs true redshift relation generated by machine learning applied to a simulation of 500,000 galaxies as observed with LSST quality, we quantify requirements on systematics in the mean relation and in the outlier fraction and deviance so as not to bias dark energy cosmological inference. Certain redshift ranges are particularly sensitive, motivating spectroscopic followup of SN at z ≲ 0.2 and around z ≈ 0.5–0.6 . Including Nancy Grace Roman Space Telescope near infrared bands in the simulation, we reanalyze the constraints, finding improvements at high redshift but little at the low redshifts where systematics lead to strong cosmology bias. We identify a complete spectroscopic survey of SN host galaxies for z≲0.2 as a highly favored element for robust SN cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Statistical and systematic uncertainties in extracting the source properties of neutron star-black hole binaries with gravitational waves

Gravitational waves emitted by neutron star black hole mergers encode key properties of neutron stars - such as their size, maximum mass and spins - and black holes. However, the presence of matter and the high mass ratio makes generating long and accurate waveforms from these systems hard to do with numerical relativity, and not much is known about systematic uncertainties due to waveform modeling. In this work, we simulate gravitational waves from neutron star black hole mergers by hybridizing numerical relativity waveforms produced with the SpEC code with a recent numerical relativity surrogate NRHybSur3dq8Tidal. These signals are analyzed using a range of available waveform families, and statistical and systematic errors are reported. We find that at a network signal-to-noise ratio (SNR) of 30, statistical uncertainties are usually larger than systematic offsets, while at an SNR of 70 the two become comparable. The individual black hole and neutron star masses, as well as the mass ratios, are typically measured very precisely, though not always accurately at high SNR. At a SNR of 30 the neutron star tidal deformability can only be bound from above, while for louder sources it can be measured and constrained away from zero. All neutron stars in our simulations are non-spinning, but in no case we can constrain the neutron star spin to be smaller than ~0.4 (90% credible interval). Waveform families whose late inspiral has been tuned specifically for neutron star black hole signals typically yield the most accurate characterization of the source parameters. Their measurements are in tension with those obtained using waveform families tuned against binary neutron stars, even for mass ratios that could be relevant for both binary neutron stars and neutron star black holes mergers.

79 ASTRONOMY AND ASTROPHYSICS↗