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At least 109 records · Page 6

Linear systematics mitigation in galaxy clustering in the Dark Energy Survey Year 1 Data

ABSTRACT We implement a linear model for mitigating the effect of observing conditions and other sources of contamination in galaxy clustering analyses. Our treatment improves upon the fiducial systematics treatment of the Dark Energy Survey (DES) Year 1 (Y1) cosmology analysis in four crucial ways. Specifically, our treatment (1) does not require decisions as to which observable systematics are significant and which are not, allowing for the possibility of multiple maps adding coherently to give rise to significant bias even if no single map leads to a significant bias by itself, (2) characterizes both the statistical and systematic uncertainty in our mitigation procedure, allowing us to propagate said uncertainties into the reported cosmological constraints, (3) explicitly exploits the full spatial structure of the galaxy density field to differentiate between cosmology-sourced and systematics-sourced fluctuations within the galaxy density field, and (4) is fully automated, and can therefore be trivially applied to any data set. The updated correlation function for the DES Y1 redMaGiC catalogue minimally impacts the cosmological posteriors from that analysis. Encouragingly, our analysis does improve the goodness-of-fit statistic of the DES Y1 3 × 2pt data set (Δχ2 = −6.5 with no additional parameters). This improvement is due in nearly equal parts to both the change in the correlation function and the added statistical and systematic uncertainties associated with our method. We expect the difference in mitigation techniques to become more important in future work as the size of cosmological data sets grows.

79 ASTRONOMY AND ASTROPHYSICS↗

Limits of special material detectability fundamental to idealized dual-energy radiographic systems

Analysis of dual-energy radiographic approaches to the detection of “special” material, i.e. contraband, in otherwise innocuous scenes, such as maritime cargo containers encountered at ports of entry, reveals fundamental limitations of data obtained along a single line-of-sight. The basic equations that describe idealized systems are presented and analyzed so as to identify challenges that are only exacerbated by scatter, noise, and measurement uncertainty. In the mono-energetic limit, the instrumentation and measurement methods reduce to a system of linear equations that are simple to treat: it is observed that there exists a threshold for the minimum amount of high-Z material that can be detected unambiguously (without the risk of false positive or false negative indications), even when the background materials are of finite and of well-known variety. The threshold depends on the quality of prior information about the cargo and the selection of probing energies, and can therefore be minimized by good system design practices and measurement procedures, but persists as a general challenge to security operations. In discussion of this result, it is noted that techniques incorporating other prior information, such as the geometry of cargo and potential contraband, along with data from 2D imaging, have far greater potential. For instance, a simple data analysis method capable of differentiating high-Z spheres from those of more common material is presented. This simple example demonstrates that, although simple line-of-sight transmission radiography may suffer fundamental limitations, there remains good cause to be optimistic about the potential for image analysis in radiographic material identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Could a neuroscientist understand a microprocessor?

There is a popular belief in neuroscience that we are primarily data limited, and that producing large, multimodal, and complex datasets will, with the help of advanced data analysis algorithms, lead to fundamental insights into the way the brain processes information. These datasets do not yet exist, and if they did we would have no way of evaluating whether or not the algorithmically-generated insights were sufficient or even correct. To address this, here we take a classical microprocessor as a model organism, and use our ability to perform arbitrary experiments on it to see if popular data analysis methods from neuroscience can elucidate the way it processes information. Microprocessors are among those artificial information processing systems that are both complex and that we understand at all levels, from the overall logical flow, via logical gates, to the dynamics of transistors. We show that the approaches reveal interesting structure in the data but do not meaningfully describe the hierarchy of information processing in the microprocessor. This suggests current analytic approaches in neuroscience may fall short of producing meaningful understanding of neural systems, regardless of the amount of data. Furthermore, we argue for scientists using complex non-linear dynamical systems with known ground truth, such as the microprocessor as a validation platform for time-series and structure discovery methods.

60 APPLIED LIFE SCIENCES↗

On the relaxation behaviors of slow and classical glitches: Observational biases and their opposite recovery trends

We study the pulsar timing properties and the data analysis methods of glitch recoveries. In some cases one first fits the times of arrival (TOAs) to obtain the 'time-averaged' frequency ν and its first derivative ν-dot , and then fits models to them. However, our simulations show that ν and ν-dot obtained in this way are systematically biased unless the time intervals between the nearby data points of TOAs are smaller than about 10{sup 4} s, which is much shorter than typical observation intervals. Alternatively, glitch parameters can be obtained by fitting the phases directly with relatively smaller biases, but the initial recovery time scale is usually chosen by eye, which may introduce a strong bias. We also construct a phenomenological model by assuming a pulsar spin-down law of ν-dot ν{sup −3}=−H{sub 0}G(t) with G(t) = 1 + κe {sup –t/τ} for a glitch recovery, where H {sub 0} is a constant and κ and τ are the glitch parameters to be found. This model can reproduce the observed data of slow glitches from B1822–09 and the giant classical glitch of B2334+61, with κ < 0 or κ > 0, respectively. We then use this model to simulate TOA data and test several fitting procedures for a glitch recovery. The best procedure is (1) to use a very high order polynomial (e.g., to 50th order) to precisely describe the phase, (2) obtain ν(t) and ν-dot (t) from the polynomial, then (3) obtain the glitch parameters from ν(t) or ν-dot (t). Finally, the uncertainty in the starting time t {sub 0} of a classical glitch causes uncertainties in some glitch parameters, but less so for a slow glitch, t {sub 0}, of which can be determined from data.

79 ASTRONOMY AND ASTROPHYSICS↗

Detection of a faint fast-moving near-Earth asteroid using the synthetic tracking technique

We report a detection of a faint near-Earth asteroid (NEA) using our synthetic tracking technique and the CHIMERA instrument on the Palomar 200 inch telescope. With an apparent magnitude of 23 (H = 29, assuming detection at 20 lunar distances), the asteroid was moving at 6.°32 day{sup –1} and was detected at a signal-to-noise ratio (S/N) of 15 using 30 s of data taken at a 16.7 Hz frame rate. The detection was confirmed by a second observation 77 minutes later at the same S/N. Because of its high proper motion, the NEA moved 7 arcsec over the 30 s of observation. Synthetic tracking avoided image degradation due to trailing loss that affects conventional techniques relying on 30 s exposures; the trailing loss would have degraded the surface brightness of the NEA image on the CCD down to an approximate magnitude of 25 making the object undetectable. This detection was a result of our 12 hr blind search conducted on the Palomar 200 inch telescope over two nights, scanning twice over six (5.°3 × 0.°046) fields. Detecting only one asteroid is consistent with Harris's estimates for the distribution of the asteroid population, which was used to predict a detection of 1.2 NEAs in the H-magnitude range 28-31 for the two nights. The experimental design, data analysis methods, and algorithms are presented. We also demonstrate milliarcsecond-level astrometry using observations of two known bright asteroids on the same system with synthetic tracking. We conclude by discussing strategies for scheduling observations to detect and characterize small and fast-moving NEAs using the new technique.

79 ASTRONOMY AND ASTROPHYSICS↗

Next-generation wargames

Over the past century, and particularly since the outset of the Cold War, wargames (interactive simulations used to evaluate aspects of tactics, operations, and strategy) have become an integral means for militaries and policy-makers to evaluate how strategic decisions are made related to nuclear weapons strategy and international security. Furthermore, these methods have also been applied beyond the military realm, to examine phenomena as varied as elections, government policy, international trade, and supply-chain mechanics. Today, a renewed focus on wargaming combined with access to sophisticated and inexpensive drag-and-drop digital game development frameworks and new cloud computing architectures have democratized the ability to enable massive multiplayer gaming experiences. With the integration of simulation tools and experimental methods from a variety of social science disciplines, a science-based experimental gaming approach has the potential to transform the insights generated from gaming by creating human-derived, large-n datasets for replicable, quantitative analysis. In the following, we outline challenges associated with contemporary simulation and wargaming tools, investigate where scholars have searched for game data, and explore the utility of new experimental gaming and data analysis methods in both policy-making and academic settings.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Interlaboratory Reproducibility of Contour Method Data in a High Strength Aluminum Alloy

The contour method for residual stress measurement has seen significant development, but an experimental reproducibility study utilizing physical samples has not been published. A double-blind reproducibly study is reported, having scope beginning with EDM cutting and ending with residual stress calculation. A reinforced I-beam sample geometry is identified for its unique residual stress profile when extracted from residual stress bearing quenched aluminum bar (7050-T74). Contour measurements are prescribed on a midplane of symmetry with dimensions 24.0 mm by 50.0 mm. Fourteen identically prepared samples are fabricated from a single long bar with well characterized and uniform residual stress. Five samples throughout the bar are identified for planning measurements to validate sample uniformity and overall suitability of the residual stress field. The planning measurements employ a range of techniques: contour method, neutron diffraction, and hole-drilling. Eight samples are distributed to an international group of participants to execute their standard measurement practice. A double-blind process is followed to provide anonymity. Results are provided by eight participants: six being self-similar and two being quite different, the latter set aside as outliers. An average residual stress field is established from non-outlying results and the spatial distribution of reproducibility standard deviation is determined. The average stress field ranges from -60 to 70 MPa and the reproducibility standard deviation averages 8.1 MPa on the measurement plane. The average reproducibility standard deviation is about 3 × larger for points within 1.0 mm of plane boundaries (17.6 MPa) than for the remaining points (6.1 MPa). Reproducibility standard deviation (among different labs) for contour method residual stress measurement is found to be very similar to repeatability standard deviation (in a single lab) reported in prior work. The reproducibility observed here, for the entire measurement process, is also similar to that found in a prior reproducibility study limited to contour method data analysis.

36 MATERIALS SCIENCE↗

First hydrogen operation of NIO1: Characterization of the source plasma by means of an optical emission spectroscopy diagnostic

NIO1 (Negative Ion Optimization 1) is a compact and flexible radio frequency H{sup −} ion source, developed by Consorzio RFX and INFN-LNL. The aim of the experimentation on NIO1 is the optimization of both the production of negative ions and their extraction and beam optics. In the initial phase of its commissioning, NIO1 was operated with nitrogen, but now the source is regularly operated also with hydrogen. To evaluate the source performances, an optical emission spectroscopy diagnostic was installed. The system includes a low resolution spectrometer in the spectral range of 300-850 nm and a high resolution (50 pm) one, to study, respectively, the atomic and the molecular emissions in the visible range. The spectroscopic data have been interpreted also by means of a collisional-radiative model developed at IPP Garching. Besides the diagnostic hardware and the data analysis methods, the paper presents the first plasma measurements across a transition to the full H mode, in a hydrogen discharge. The characteristic signatures of this transition in the plasma parameters are described, in particular, the sudden increase of the light emitted from the plasma above a certain power threshold.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Electric Motor Thermal Management R&D. Annual Report

With the push to reduce component volumes, lower costs, and reduce weight without sacrificing performance or reliability, the challenges associated with thermal management increase for power electronics and electric motors. Thermal management for electric motors will become more important as the automotive industry continues the transition to more electrically dominant vehicle propulsion systems. The transition to more electrically dominant propulsion systems leads to higher-power duty cycles for electric drive systems. Thermal constraints place significant limitations on how electric motors ultimately perform, and as thermal management improves, there will be a direct trade-off between motor performance, efficiency, cost, and the sizing of electric motors to operate within the thermal constraints. The goal of this research project is to support broad industry demand for data, analysis methods, and experimental techniques to improve and better understand motor thermal management. Work in FY15 focused on two areas related to motor thermal management: passive thermal performance and active convective cooling. Passive thermal performance emphasized the thermal impact of materials and thermal interfaces among materials within an assembled motor. The research tasks supported the publication of test methods and data for thermal contact resistances and direction-dependent thermal conductivity within an electric motor. Active convective cooling focused on measuring convective heat-transfer coefficients using automatic transmission fluid (ATF). Data for average convective heat transfer coefficients for direct impingement of ATF jets was published. Also, experimental hardware for mapping local-scale and stator-scale convective heat transfer coefficients for ATF jet impingement were developed.

30 DIRECT ENERGY CONVERSION↗

Scattering Calorimeter FY24 Deliverable Report

A simulation-based method has been developed to prototype new detector designs for nuclear data measurements utilizing neutron scattering. This method uses representative physics inputs for signal and background generation, full detector resolution smearing benchmarked by experimental data, and a neutron beam timing simulation to produce analyzable output like a physical measurement. A test case has been studied using a hybrid time-of-flight calorimeter detector for scattering cross-section measurements on 239 Pu with 1-5 MeV incident monoenergetic neutrons. Data analysis methods have been developed to perform event-level particle reconstruction and reaction channel discrimination. This analysis has been used to estimate the capability of the test detector to perform simultaneous scattering and fission cross section measurements, as well as its ability to provide neutron spectra and particle angular information.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Task 1. Monitoring real time materials degradation. NRC extended In-situ and real-time Monitoring

The overall objective of this project was to perform a scoping study to identify, in concert with the nuclear industry, those sensors and techniques that have the most promising commercial viability and fill a critical inspection or monitoring need. Candidates to be considered include sensors to monitor real-time material degradation, characterize residual stress, monitor and inspect component fabrication, assess radionuclide and associated chemical species concentrations in ground water and soil, characterize fuel properties, and monitor severe accident conditions. Under Task 1—Monitoring Real-Time Materials Degradation—scoping studies were conducted to assess the feasibility of potential inspection and monitoring technologies (i.e., a combination of sensors, advanced signal processing techniques, and data analysis methods) that could be utilized in LWR and/or advanced reactor applications for continuous monitoring of degradation in-situ. The goal was to identify those techniques that appear to be the most promising, i.e., those that are closest to being both technically and commercially viable and that the nuclear industry is most likely to pursue. Current limitations and associated issues that must be overcome before commercial application of certain techniques have also been addressed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Performance of internal covariance estimators for cosmic shear correlation functions

Data re-sampling methods such as the delete-one jackknife are a common tool for estimating the covariance of large scale structure probes. In this paper we investigate the concepts of internal covariance estimation in the context of cosmic shear two-point statistics. We demonstrate how to use log-normal simulations of the convergence field and the corresponding shear field to carry out realistic tests of internal covariance estimators and find that most estimators such as jackknife or sub-sample covariance can reach a satisfactory compromise between bias and variance of the estimated covariance. In a forecast for the complete, 5-year DES survey we show that internally estimated covariance matrices can provide a large fraction of the true uncertainties on cosmological parameters in a 2D cosmic shear analysis. The volume inside contours of constant likelihood in the $\Omega_m$-$\sigma_8$ plane as measured with internally estimated covariance matrices is on average $\gtrsim 85\%$ of the volume derived from the true covariance matrix. The uncertainty on the parameter combination $\Sigma_8 \sim \sigma_8 \Omega_m^{0.5}$ derived from internally estimated covariances is $\sim 90\%$ of the true uncertainty.

79 ASTRONOMY AND ASTROPHYSICS↗

XANES and EXAFS of dilute solutions of transition metals at XFELs

This work has demonstrated that X-ray absorption spectroscopy (XAS), both Mn XANES and EXAFS, of solutions with millimolar concentrations of metal is possible using the femtosecond X-ray pulses from XFELs. Mn XAS data were collected using two different sample delivery methods, a Rayleigh jet and a drop-on-demand setup, with varying concentrations of Mn. Here, a new method for normalization of XAS spectra based on solvent scattering that is compatible with data collection from a highly variable pulsed source is described. The measured XANES and EXAFS spectra of such dilute solution samples are in good agreement with data collected at synchrotron sources using traditional scanning protocols. The procedures described here will enable XFEL-based XAS on dilute biological samples, especially metalloproteins, with low sample consumption. Details of the experimental setup and data analysis methods used in this XANES and EXAFS study are presented. This method will also benefit XAS performed at high-repetition-rate XFELs such as the European XFEL, LCLS-II and LCLS-II-HE.

Chatterjee, Ruchira (ORCID:000000020865061X)↗

A composite likelihood approach for inference under photometric redshift uncertainty

ABSTRACT Obtaining accurately calibrated redshift distributions of photometric samples is one of the great challenges in photometric surveys like LSST, Euclid, HSC, KiDS, and DES. We present an inference methodology that combines the redshift information from the galaxy photometry with constraints from two-point functions, utilizing cross-correlations with spatially overlapping spectroscopic samples, and illustrate the approach on CosmoDC2 simulations. Our likelihood framework is designed to integrate directly into a typical large-scale structure and weak lensing analysis based on two-point functions. We discuss efficient and accurate inference techniques that allow us to scale the method to the large samples of galaxies to be expected in LSST. We consider statistical challenges like the parametrization of redshift systematics, discuss and evaluate techniques to regularize the sample redshift distributions, and investigate techniques that can help to detect and calibrate sources of systematic error using posterior predictive checks. We evaluate and forecast photometric redshift performance using data from the CosmoDC2 simulations, within which we mimic a DESI-like spectroscopic calibration sample for cross-correlations. Using a combination of spatial cross-correlations and photometry, we show that we can provide calibration of the mean of the sample redshift distribution to an accuracy of at least 0.002(1 + z), consistent with the LSST-Y1 science requirements for weak lensing and large-scale structure probes.

(cosmology:) large-scale structure of Universe↗

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↗

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↗

Development of a Rubber-Based Product Using a Mixture Experiment: A Challenging Case Study

Many products used in daily life are made by blending two or more components. The properties of such products typically depend on the relative proportions of the components. Experimental design, modeling, and data analysis methods for mixture experiments provide for efficiently determining the component proportions that will yield a product with desired properties. This article presents a case study of the work performed to develop a new rubber formulation for an o-ring (a circular gasket) with requirements specified on 10 product properties. Each step of the study is discussed, including: 1) identifying the objective of the study and requirements for properties of the o-ring, 2) selecting the components to vary and specifying the component constraints, 3) constructing a mixture experiment design, 4) measuring the responses and assessing the data, 5) developing property-composition models, 6) selecting the new product formulation, and 7) confirming the selected formulation in manufacturing. The case study includes some challenging and new aspects, which are discussed in the article.

Full-cubic mixture model↗

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 ↗