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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Prediction of thyroid C-cell carcinogenicity after chronic administration of GLP1-R agonists in rodents

Increased incidence of C-cell carcinogenicity has been observed for glucagon-like-protein-1 receptor (GLP-1r) agonists in rodents. It is suggested that the duration of exposure is an indicator of carcinogenic potential in rodents of the different products on the market. Furthermore, the role of GLP-1-related mechanisms in the induction of C-cell carcinogenicity has gained increased attention by regulatory agencies. This study proposes an integrative pharmacokinetic/pharmacodynamic (PKPD) framework to identify explanatory factors and characterize differences in carcinogenic potential of the GLP-1r agonist products. PK models for four products (exenatide QW (once weekly), exenatide BID (twice daily), liraglutide and lixisenatide) were developed using nonlinear mixed effects modelling. Predicted exposure was subsequently linked to GLP-1r stimulation using in vitro GLP-1r potency data. A logistic regression model was then applied to exenatide QW and liraglutide data to assess the relationship between GLP-1r stimulation and thyroid C-cell hyperplasia incidence as pre-neoplastic predictor of a carcinogenic response. The model showed a significant association between predicted GLP-1r stimulation and C-cell hyperplasia after 2 years of treatment. The predictive performance of the model was evaluated using lixisenatide, for which hyperplasia data were accurately described during the validation step. The use of a model-based approach provided insight into the relationship between C-cell hyperplasia and GLP-1r stimulation for all four products, which is not possible with traditional data analysis methods. It can be concluded that both pharmacokinetics (exposure) and pharmacodynamics (potency for GLP-1r) factors determine C-cell hyperplasia incidence in rodents. Our work highlights the pharmacological basis for GLP-1r agonist-induced C-cell carcinogenicity. The concept is promising for application to other drug classes. - Highlights: • An integrative PKPD model is applied to study GLP-1r agonist carcinogenicity. • C-cell carcinogenicity is impacted by both pharmacokinetics and pharmacodynamics. • The relation of GLP-1r stimulation and C-cell hyperplasia appears drug-independent. • Understanding carcinogenic risk needs a pharmacological basis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Physical Interpretation of Early Battery Life Prediction Models

Early battery life prediction models are most useful for R&D if they help us understand the early changes in battery electrochemical response that correspond with long-term degradation and failure. Linear regression models such as Fused lasso and Partial Least Squares can fit coefficients directly to high-dimensional electrochemical data like capacity-voltage and ΔV–state-of-charge, i.e., Q(V) and ΔV(SOC) curves, learning coefficients that can be physically interpreted. We leverage the ISU-ILCC battery aging data set to learn high-dimensional coefficients for early battery life prediction from traditional slow-rate capacity check data, demonstrating learning on Q(V), d Q· d V −1 , and ΔV(SOC) curves. A thorough study on the dependence of coefficient values on train/test size and data preprocessing methods is made, demonstrating the reliability of high-dimensional regression approaches unless very small amounts of data are used for model training. For this data set, coefficients from Q(V) and d Q· d V −1 models highlight changes in electrode stoichiometry due to lithium loss, while ΔV(SOC) coefficients highlight changes in positive electrode diffusivity due to particle cracking as well as electrode stoichiometry shifts. By directly interpreting the coefficients of a regression model, we make physical insights into battery degradation mechanisms without requiring the assumptions of traditional battery data analysis methods.

25 ENERGY STORAGE↗
NASA NTRS2002

Induced Moment Effects of Formation Flight Using Two F/A-18 Aircraft

Previous investigations into formation flight have shown the possibility for significant fuel savings through drag reduction. Using two F/A-18 aircraft, NASA Dryden Flight Research Center has investigated flying aircraft in autonomous formation. Positioning the trailing airplane for best drag reduction requires investigation of the wingtip vortex effects induced by the leading airplane. A full accounting of the vortex effect on the trailing airplane is desired to validate vortex-effect prediction methods and provide a database for the design of a formation flight autopilot. A recent flight phase has mapped the complete wingtip vortex effects at two flight conditions with the trailing airplane at varying distances behind the leading one. Force and moment data at Mach 0.56 and an altitude of 25,000 ft and Mach 0.86 and an altitude of 36,000 ft have been obtained with 20, 55, 110, and 190 ft of longitudinal distance between the aircraft. The moments induced by the vortex on the trailing airplane were well within the pilot's ability to control. This report discusses the data analysis methods and vortex-induced effects on moments and side force. An assessment of the impact of the nonlinear vortex effects on the design of a formation autopilot is offered.

Hansen, Jennifer L.↗
NASA NTRS1993

Determining XV-15 aeroelastic modes from flight data with frequency-domain methods

The XV-15 tilt-rotor wing has six major aeroelastic modes that are close in frequency. To precisely excite individual modes during flight test, dual flaperon exciters with automatic frequency-sweep controls were installed. The resulting structural data were analyzed in the frequency domain (Fourier transformed). All spectral data were computed using chirp z-transforms. Modal frequencies and damping were determined by fitting curves to frequency-response magnitude and phase data. The results given in this report are for the XV-15 with its original metal rotor blades. Also, frequency and damping values are compared with theoretical predictions made using two different programs, CAMRAD and ASAP. The frequency-domain data-analysis method proved to be very reliable and adequate for tracking aeroelastic modes during flight-envelope expansion. This approach required less flight-test time and yielded mode estimations that were more repeatable, compared with the exponential-decay method previously used.

Acree, C. W., Jr.↗
DOE OSTI2019

Positron annihilation lifetime spectroscopy using fast scintillators and digital electronics

Positron Annihilation Lifetime Spectroscopy (PALS) is a non-destructive radiological technique widely used in material science studies. PALS typically relies on an analog coincidence measurement setup and allows the estimate of the positron lifetime in a material sample under investigation. The positron trapping at vacancies in the material results in an increased positron lifetime. In this work, we have developed and optimized a PALS experimental setup using organic scintillators, fast digitizers, and advanced pulse processing algorithms. We tested three pairs of different organic scintillators: EJ-309 liquid, EJ-276 newly developed plastic, and BC- 418 plastic, and optimized the data processing parameters for each pair separately. Our high-throughput data analysis method is based on single-pulse interpolation and a constant fraction discrimination (CFD) algorithm. The setup based on the BC-418 detector achieved the best time resolution of 198.3 ± 0.8 ps. We used such optimized setup to analyze two single-crystal quartz samples and found lifetimes of 161 ± 4 ps, 343 ± 12 ps and 1.34 ± 0.05 ns, in good agreement with the characteristic time constants of this material. The proposed experimental set up achieves a time resolution comparable to the minimum positron lifetime in quartz, which makes it possible to accurately characterize material vacancies by discriminating between the lifetimes of either the spin singlet or triplet states of positronium. The optimized data processing algorithms are relevant to all the applications where fast timing is important, such as nuclear medicine and radiation imaging

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Final Report on the Viability of Acoustic Techniques for Density and Mass Flow in Enrichment Plants

The primary purpose of this research is to study the viability of acoustic signatures and sensors that could support accurate, noninvasive, and unattended measurement of uranium hexafluoride (UF6) gas density and mass flow rate in situations representative of gaseous centrifuge enrichment plants (GCEP) under safeguards by the International Atomic Energy Agency. The measurement method under development can be readily retrofitted to the exterior of piping in existing systems, potentially facilitating acceptance by facility operators. The findings from the demonstration of a preliminary prototype design and first-generation analysis algorithms in this project will inform the safeguards community as to whether continued acoustic instrument and methods development are warranted. This project conducted two types of measurements, depending on the flow conditions of the gas. For static measurements, the focus is on understanding the acoustic properties at low pressure for non-flowing UF6. For flow measurements, the focus is on understanding the performance of the acoustic system in a simulation of a GCEP pipe using a surrogate gas under fully developed flow conditions. Testing with flowing UF6 was not considered because the cost of building a flowing UF6 system with flow similar to a GCEP was considerably greater than allocated project resources. This document summarizes the results of research conducted over the course of the project. Based on the results to date, the approach is seen to be promising with non-invasive acoustic measurements shown to be possible at the desired pressures. The project has demonstrated • 5% uncertainty of the UF6 gas density for static measurements at pressures relevant to GCEP operations over a 5-minute measurement window with a clear path forward to achieving considerably lower uncertainties over a two-hour period, • Measurements of flowing surrogate gases at pressures relevant to GCEP operations. However, additional research remains to be done to further develop the measurement approach and transition the technology for field use. These development needs include: • Understand the impact of flowing gas on gas density measurements, • Adding sensors and improving the measurement procedure, • Augmenting the data analysis methods by leveraging machine learning approaches, • Reevaluating uncertainty requirements for density and mass flow given observed Online Enrichment Monitor (OLEM) measurement uncertainties, • Designing a robust instrumentation package for field-testing, and • Evaluating measurement results to understand the potential impact on mass balance calculations within GCEP facilities.

42 ENGINEERING↗
DOE OSTI2022

Accelerating astronomical and cosmological inference with preconditioned Monte Carlo

ABSTRACT We introduce preconditioned Monte Carlo (PMC), a novel Monte Carlo method for Bayesian inference that facilitates efficient sampling of probability distributions with non-trivial geometry. PMC utilizes a Normalizing Flow (NF) in order to decorrelate the parameters of the distribution and then proceeds by sampling from the preconditioned target distribution using an adaptive Sequential Monte Carlo (SMC) scheme. The results produced by PMC include samples from the posterior distribution and an estimate of the model evidence that can be used for parameter inference and model comparison, respectively. The aforementioned framework has been thoroughly tested in a variety of challenging target distributions achieving state-of-the-art sampling performance. In the cases of primordial feature analysis and gravitational wave inference, PMC is approximately 50 and 25 times faster, respectively, than nested sampling (NS). We found that in higher dimensional applications, the acceleration is even greater. Finally, PMC is directly parallelisable, manifesting linear scaling up to thousands of CPUs.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2001

Applications of the Hilbert-Huang Transform

A new method, the Hilbert-Huang Transform, has been developed for analyzing nonlinear and nonstationary data. The key part of the method is the Empirical Mode Decomposition with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An M is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies'as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum. With this technique we can examine the detailed dynamics characteristics of a nonlinear system through the instantaneous frequency rather than harmonics. Thus it constitutes a new view of the nonlinear dynamics. Examples of classic nonlinear equations and other nonlinear and nonstationary data sets will be used as examples to illustrate the advantage of the application of this new data analysis method.

Huang, Norden E.↗
DOE OSTI2018

X-ray Emission Spectroscopy as an in Situ Diagnostic Tool for X-ray Crystallography of Metalloproteins Using an X-ray Free-Electron Laser

Serial femtosecond crystallography (SFX) using the ultrashort X-ray pulses from a X-ray free-electron laser (XFEL) provides a new way of collecting structural data at room temperature that allows for following the reaction in real time after initiation. XFEL experiments are conducted in a shot-by-shot mode as the sample is destroyed and replenished after each X-ray pulse, and therefore, monitoring and controlling the data quality by using in situ diagnostic tools is critical. To study metalloenzymes, we developed the use of simultaneous collection of X-ray diffraction of crystals along with X-ray emission spectroscopy (XES) data that is used as a diagnostic tool for crystallography, by monitoring the chemical state of the metal catalytic center. We have optimized data analysis methods and sample delivery techniques for fast and active feedback to ensure the quality of each batch of samples and the turnover of the catalytic reaction caused by reaction triggering methods. Here, we describe this active in situ feedback system using Photosystem II as an example that catalyzes the oxidation of H2O to O2at the Mn4CaO5active site. We used the first moments of the Mn Kβ1,3emission spectra, which are sensitive to the oxidation state of Mn, as the primary diagnostics. This approach is applicable to different metalloproteins to determine the integrity of samples and follow changes in the chemical states of the reaction that can be initiated by light or activated by substrates and offers a metric for determining the diffraction images that are used for the final data sets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

BEYONDPLANCK III. Commander3

We describe the computational infrastructure for end-to-end Bayesian cosmic microwave background (CMB) analysis implemented by the BeyondPlanck Collaboration. The code is called Commander3. It provides a statistically consistent framework for global analysis of CMB and microwave observations and may be useful for a wide range of legacy, current, and future experiments. The paper has three main goals. Firstly, we provide a high-level overview of the existing code base, aiming to guide readers who wish to extend and adapt the code according to their own needs or re-implement it from scratch in a different programming language. Secondly, we discuss some critical computational challenges that arise within any global CMB analysis framework, for instance in-memory compression of time-ordered data, fast Fourier transform optimization, and parallelization and load-balancing. Thirdly, we quantify the CPU and RAM requirements for the current BEYONDPLANCK analysis, finding that a total of 1.5 TB of RAM is required for efficient analysis and that the total cost of a full Gibbs sample for LFI is 170 CPU-hrs, including both low-level processing and high-level component separation, which is well within the capabilities of current low-cost computing facilities. The existing code base is made publicly available under a GNU General Public Library (GPL) license.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Laser Ablation-Aerosol Mass Spectrometry-Chemical Ionization Mass Spectrometry for Ambient Surface Imaging

Mass spectrometry imaging is becoming an increasingly common analytical technique due to its ability to provide spatially resolved chemical information. In this paper, we report a novel imaging approach combining laser ablation with two mass spectrometric techniques, aerosol mass spectrometry and chemical ionization mass spectrometry, separately and in parallel. Both mass spectrometric methods provide the fast response, rapid data acquisition, low detection limits, and high-resolution peak separation desirable for imaging complex samples. Additionally, the two techniques provide complementary information with aerosol mass spectrometry providing near universal detection of all aerosol molecules and chemical ionization mass spectrometry with a heated inlet providing molecular-level detail of both gases and aerosols. The two techniques operate with atmospheric pressure interfaces and require no matrix addition for ionization, allowing for samples to be investigated in their native state under ambient pressure conditions. We demonstrate the ability of laser ablation-aerosol mass spectrometry-chemical ionization mass spectrometry (LA-AMS-CIMS) to create 2D images of both standard compounds and complex mixtures. Finally, the results suggest that LA-AMS-CIMS, particularly when combined with advanced data analysis methods, could have broad applications in mass spectrometry imaging applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Likelihood non-Gaussianity in large-scale structure analyses

The standard present-day large-scale structure (LSS) analyses make a major assumption in their Bayesian parameter inference – that the likelihood has a Gaussian form. For summary statistics currently used in LSS, this assumption, even if the underlying density field is Gaussian, cannot be correct in detail. We investigate the impact of this assumption on two recent LSS analyses: the Beutler et al. power spectrum multipole ($P_ℓ$) analysis and the Sinha et al. group multiplicity function ($ζ$) analysis. Using non-parametric divergence estimators on mock catalogues originally constructed for covariance matrix estimation, we identify significant non-Gaussianity in both the $P_ℓ$ and $ζ$ likelihoods. We then use Gaussian mixture density estimation and independent component analysis on the same mocks to construct likelihood estimates that approximate the true likelihood better than the Gaussian pseudo-likelihood. Using these likelihood estimates, we accurately estimate the true posterior probability distribution of the Beutler et al. and Sinha et al. parameters. Likelihood non-Gaussianity shifts the fσ8 constraint by -0.44σ, but otherwise does not significantly impact the overall parameter constraints of Beutler et al. For the $ζ$ analysis, using the pseudo-likelihood significantly underestimates the uncertainties and biases the constraints of the Sinha et al. halo occupation parameters. For log $M_1$ and α, the posteriors are shifted by +0.43σ and -0.51σ and broadened by 42 per cent and 66 per cent, respectively. The divergence and likelihood estimation methods we present provide a straightforward framework for quantifying the impact of likelihood non-Gaussianity and deriving more accurate parameter constraints.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Comparing gas composition from fast pyrolysis of live foliage measured in bench-scale and fire-scale experiments

Background: Fire models have used pyrolysis data from oxidising and non-oxidising environments for flaming combustion. In wildland fires pyrolysis, flaming and smouldering combustion typically occur in an oxidising environment (the atmosphere). Aims: Using compositional data analysis methods, determine if the composition of pyrolysis gases measured in non-oxidising and ambient (oxidising) atmospheric conditions were similar. Methods: Permanent gases and tars were measured in a fuel-rich (non-oxidising) environment in a flat flame burner (FFB). Permanent and light hydrocarbon gases were measured for the same fuels heated by a fire flame in ambient atmospheric conditions (oxidising environment). Log-ratio balances of the measured gases common to both environments (CO, CO 2 , CH 4 , H 2 , C 6 H 6 O (phenol), and other gases) were examined by principal components analysis (PCA), canonical discriminant analysis (CDA) and permutational multivariate analysis of variance (PERMANOVA). Key results: Mean composition changed between the non-oxidising and ambient atmosphere samples. PCA showed that flat flame burner (FFB) samples were tightly clustered and distinct from the ambient atmosphere samples. CDA found that the difference between environments was defined by the CO-CO 2 log-ratio balance. PERMANOVA and pairwise comparisons found FFB samples differed from the ambient atmosphere samples which did not differ from each other. Conclusion: Relative composition of these pyrolysis gases differed between the oxidising and non-oxidising environments. This comparison was one of the first comparisons made between bench-scale and field scale pyrolysis measurements using compositional data analysis. Implications: These results indicate the need for more fundamental research on the early time-dependent pyrolysis of vegetation in the presence of oxygen.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

A steep slope and small scatter for the high-mass end of the L–σ relation at z ~ 0.55

We measure the intrinsic relation between velocity dispersion (σ) and luminosity (L) for massive, luminous red galaxies at redshift z ~ 0.55. Here, we achieve unprecedented precision by using a sample of 600 000 galaxies with spectra from the Baryon Oscillation Spectroscopic Survey of the third Sloan Digital Sky Survey (SDSS-III), covering a range of stellar masses M* ≳ 10 11 M ⊙ . We deconvolve the effects of photometric errors, limited spectroscopic signal-to-noise ratio, and red–blue galaxy confusion using a novel hierarchical Bayesian formalism that is generally applicable to any combination of photometric and spectroscopic observables. For an L–σ relation of the form L ∝ σ β , we find β = 7.8 ± 1.1 for σ corrected to the effective radius, and a very small intrinsic scatter of s = 0.047 ± 0.004 in log10σ at fixed L. No significant redshift evolution is found for these parameters. The evolution of the zero-point within the redshift range considered is consistent with the passive evolution of a galaxy population that formed at redshift z = 2–3, assuming single stellar populations. An analysis of previously reported results seems to indicate that the passively evolved high-mass L–σ relation at z ~ 0.55 is consistent with the one measured at z = 0.1. Finally, our results, in combination with those presented in the LF work of Montero-Dorta et al., provide a detailed description of the high-mass end of the red sequence (RS) at z ~ 0.55. This characterization, in the light of previous literature, suggest that the high-mass RS distribution corresponds to the ‘core’ elliptical population.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2019

Comparison of Neutral Outgassing of Comet 67P/Churyumov-Gerasimenko Inbound and Outbound Beyond 3 Au From ROSINA/DFMS

Context. Pre-equinox measurements of comet 67P/Churyumov-Gerasimenko with the mass spectrometer ROSINA/DFMS on board the Rosetta spacecraft revealed a strongly heterogeneous coma. The abundances of major and various minor volatile species were found to depend on the latitude and longitude of the nadir point of the spacecraft. The observed time variability of coma species remained consistent for about three months up to equinox. The chemical variability could be generally interpreted in terms of surface temperature and seasonal effects superposed on some kind of chemical heterogeneity of the nucleus. Aims. We compare here pre-equinox (inbound) ROSINA/DFMS measurements from 2014 to measurements taken after the outbound equinox in 2016, both at heliocentric distances larger than 3 AU. For a direct comparison we limit our observations to the southern hemisphere. Methods. We report the similarities and differences in the concentrations and time variability of neutral species under similar insolation conditions (heliocentric distance and season) pre- and post-equinox, and interpret them in light of the previously published observations. In addition, we extend both the pre- and post-equinox analysis by comparing species concentrations with a mixture of CO2 and H2O. Results. Our results show significant changes in the abundances of neutral species in the coma from pre- to post-equinox that are indicative of seasonally driven nucleus heterogeneity. Conclusions. The observed pre- and post-equinox patterns can generally be explained by the strong erosion in the southern hemisphere that moves volatile-rich layers near the surface.

comets↗
DOE OSTI2023

The cosmic web around the Coma cluster from constrained cosmological simulations

Galaxy clusters in the Universe occupy the important position of nodes of the cosmic web. They are connected among them by filaments, elongated structures composed of dark matter, galaxies, and gas. The connection of galaxy clusters to filaments is important, as it is related to the process of matter accretion onto the former. For this reason, investigating the connections to the cosmic web of massive clusters, especially well-known ones for which a lot of information is available, is a hot topic in astrophysics. In a previous work, we performed an analysis of the filament connections of the Coma cluster of galaxies, as detected from the observed galaxy distribution. In this work we resort to a numerical simulation whose initial conditions are constrained to reproduce the local Universe, including the region of the Coma cluster to interpret our observations in an evolutionary context. We detect the filaments connected to the simulated Coma cluster and perform an accurate comparison with the cosmic web configuration we detect in observations. We perform an analysis of the halos’ spatial and velocity distributions close to the filaments in the cluster outskirts. We conclude that, although not significantly larger than the average, the flux of accreting matter on the simulated Coma cluster is significantly more collimated close to the filaments with respect to the general isotropic accretion flux. This paper is the first example of such a result and the first installment in a series of publications which will explore the build-up of the Coma cluster system in connection to the filaments of the cosmic web as a function of redshift.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Are light curve classification metrics good proxies for SN Ia cosmological constraining power?

Context. When selecting a light curve classifier for use as part of a photometric supernova Ia (SN Ia) cosmological analysis, it is common to make decisions based on metrics of classification performance, such as the contamination within the photometrically classified SN Ia sample, rather than a measure of cosmological constraining power. If the former is an appropriate proxy for the latter, this practice would eliminate the computational expense of a full cosmology forecast in the analysis pipeline design process. Aims. This study tests the assumption that light curve classification metrics are an appropriate proxy for cosmology metrics. Methods. We emulated photometric SN Ia cosmology light curve samples with controlled contamination rates of individual contaminant classes and evaluated each of them under a set of classification metrics. We then derived cosmological parameter constraints from all samples under two common analysis approaches and quantified the impact of contamination by each contaminant class on the resulting cosmological parameter estimates. Results. We observe that cosmology metrics are sensitive to both the contamination rate and the class of the contaminating population, whereas the classification metrics are shown to be insensitive to the latter. Conclusions. Based on these findings, we discourage any exclusive reliance on light curve classification-based metrics for analysis design decisions, which (counterintuitively) include but are not limited to the classifier choice. Instead, we recommend optimising science analysis pipeline design choices using a metric of the information gained about the physical parameters of interest.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Joint inference of multiplicative and additive systematics in galaxy density fluctuations and clustering measurements

Galaxy clustering measurements are a key probe of the matter density field in the Universe. With the era of precision cosmology upon us, surveys rely on precise measurements of the clustering signal for meaningful cosmological analysis. However, the presence of systematic contaminants can bias the observed galaxy number density, and thereby bias the galaxy two-point statistics. As the statistical uncertainties get smaller, correcting for these systematic contaminants becomes increasingly important for unbiased cosmological analysis. We present and validate a new method for understanding and mitigating both additive and multiplicative systematics in galaxy clustering measurements (two-point function) by joint inference of contaminants in the galaxy overdensity field (one-point function) using a maximum-likelihood estimator (MLE). We test this methodology with Kilo-Degree Survey-like mock galaxy catalogues and synthetic systematic template maps. We estimate the cosmological impact of such mitigation by quantifying uncertainties and possible biases in the inferred relationship between the observed and the true galaxy clustering signal. Our method robustly corrects the clustering signal to the sub-percent level and reduces numerous additive and multiplicative systematics from 1.5σ to less than 0.1σ for the scenarios we tested. In addition, we provide an empirical approach to identifying the functional form (additive, multiplicative, or other) by which specific systematics contaminate the galaxy number density. Even though this approach is tested and geared towards systematics contaminating the galaxy number density, the methods can be extended to systematics mitigation for other two-point correlation measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗