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At least 91 records · Page 5

Blinding multiprobe cosmological experiments

ABSTRACT The goal of blinding is to hide an experiment’s critical results – here the inferred cosmological parameters – until all decisions affecting its analysis have been finalized. This is especially important in the current era of precision cosmology, when the results of any new experiment are closely scrutinized for consistency or tension with previous results. In analyses that combine multiple observational probes, like the combination of galaxy clustering and weak lensing in the Dark Energy Survey (DES), it is challenging to blind the results while retaining the ability to check for (in)consistency between different parts of the data. We propose a simple new blinding transformation, which works by modifying the summary statistics that are input to parameter estimation, such as two-point correlation functions. The transformation shifts the measured statistics to new values that are consistent with (blindly) shifted cosmological parameters while preserving internal (in)consistency. We apply the blinding transformation to simulated data for the projected DES Year 3 galaxy clustering and weak lensing analysis, demonstrating that practical blinding is achieved without significant perturbation of internal-consistency checks, as measured here by degradation of the χ2 between the data and best-fitting model. Our blinding method’s performance is expected to improve as experiments evolve to higher precision and accuracy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Wayne—A Simulator for HST WFC3 IR Grism Spectroscopy

Wayne is an algorithm that simulates Hubble Space Telescope Wide Field Camera 3 (WFC3) grism spectroscopic frames, including sources of noise and systematics. It can simulate both staring and spatial scan modes, and observations such as the transit and the eclipse of an exoplanet. Unlike many other instrument simulators, the focus of Wayne is on creating frames with realistic systematics in order to test the effectiveness of different data analysis methods in a variety of different scenarios. This approach is critical for method validation and optimizing observing strategies. In this paper we describe the implementation of Wayne for WFC3 in the near-infrared channel with the G102 and G141 grisms. We compare the simulations to real data obtained for the exoplanet HD 209458b, to verify the accuracy of the simulation. The software is now available as open source at https://github.com/ucl-exoplanets/wayne.

79 ASTRONOMY AND ASTROPHYSICS↗

The Microbial Detection Array for Detection of Emerging Viruses in Clinical Samples - A Useful Panmicrobial Diagnostic Tool

Emerging viruses are usually endemic to tropical and sub-tropical regions of the world, but increased global travel, climate change and changes in lifestyle are believed to contribute to the spread of these viruses into new regions. Many of these viruses cause similar disease symptoms as other emerging viruses or common infections, making these unexpected pathogens difficult to diagnose. Broad-spectrum pathogen detection microarrays containing probes for all sequenced viruses and bacteria can provide rapid identification of viruses, guiding decisions about treatment and appropriate case management. We report a modified Whole Transcriptome Amplification (WTA) method that increases unbiased amplification, particular of RNA viruses. Using this modified WTA method, we tested the specificity and sensitivity of the Lawrence Livermore Microbial Detection Array (LLMDA) against a wide range of emerging viruses present in both nonclinical and clinical samples using two different microarray data analysis methods.

59 BASIC BIOLOGICAL SCIENCES↗

Modelling stellar activity with Gaussian process regression networks

ABSTRACT Stellar photospheric activity is known to limit the detection and characterization of extrasolar planets. In particular, the study of Earth-like planets around Sun-like stars requires data analysis methods that can accurately model the stellar activity phenomena affecting radial velocity (RV) measurements. Gaussian Process Regression Networks (GPRNs) offer a principled approach to the analysis of simultaneous time series, combining the structural properties of Bayesian neural networks with the non-parametric flexibility of Gaussian Processes. Using HARPS-N solar spectroscopic observations encompassing three years, we demonstrate that this framework is capable of jointly modelling RV data and traditional stellar activity indicators. Although we consider only the simplest GPRN configuration, we are able to describe the behaviour of solar RV data at least as accurately as previously published methods. We confirm the correlation between the RV and stellar activity time series reaches a maximum at separations of a few days, and find evidence of non-stationary behaviour in the time series, associated with an approaching solar activity minimum.

Camacho, J. D. (ORCID:0000000151215560)↗

BeyondPlanck: VII. Bayesian estimation of gain and absolute calibration for cosmic microwave background experiments

We present a Bayesian calibration algorithm for cosmic microwave background (CMB) observations as implemented within the global end-to-end BEYONDPLANCK framework and applied to the Planck Low Frequency Instrument (LFI) data. Following the most recent Planck analysis, we decomposed the full time-dependent gain into a sum of three nearly orthogonal components: one absolute calibration term, common to all detectors, one time-independent term that can vary between detectors, and one time-dependent component that was allowed to vary between one-hour pointing periods. Each term was then sampled conditionally on all other parameters in the global signal model through Gibbs sampling. The absolute calibration is sampled using only the orbital dipole as a reference source, while the two relative gain components were sampled using the full sky signal, including the orbital and Solar CMB dipoles, CMB fluctuations, and foreground contributions. We discuss various aspects of the data that influence gain estimation, including the dipole-polarization quadrupole degeneracy and processing masks. Comparing our solution to previous pipelines, we find good agreement in general, with relative deviations of -0.67% (-0.84%) for 30 GHz, 0.12% (-0.04%) for 44 GHz and -0.03% (-0.64%) for 70 GHz, compared to Planck PR4 and Planck 2018, respectively. We note that the BEYONDPLANCK calibration was performed globally, which results in better inter-frequency consistency than previous estimates. Additionally, WMAP observations were used actively in the BEYONDPLANCK analysis, which both breaks internal degeneracies in the Planck data set and results in an overall better agreement with WMAP. Finally, we used a Wiener filtering approach to smoothing the gain estimates. We show that this method avoids artifacts in the correlated noise maps as a result of oversmoothing the gain solution, which is difficult to avoid with methods like boxcar smoothing, as Wiener filtering by construction maintains a balance between data fidelity and prior knowledge. Although our presentation and algorithm are currently oriented toward LFI processing, the general procedure is fully generalizable to other experiments, as long as the Solar dipole signal is available to be used for calibration.

79 ASTRONOMY AND ASTROPHYSICS↗

Trident: A Universal Tool for Generating Synthetic Absorption Spectra from Astrophysical Simulations

Hydrodynamical simulations are increasingly able to accurately model physical systems on stellar, galactic, and cosmological scales; however, the utility of these simulations is often limited by our ability to directly compare them with the data sets produced by observers: spectra, photometry, etc. To address this problem, we have created trident, a Python-based open-source tool for post-processing hydrodynamical simulations to produce synthetic absorption spectra and related data. trident can (i) create absorption-line spectra for any trajectory through a simulated data set mimicking both background quasar and down-the-barrel configurations; (ii) reproduce the spectral characteristics of common instruments like the Cosmic Origins Spectrograph; (iii) operate across the ultraviolet, optical, and infrared using customizable absorption-line lists; (iv) trace simulated physical structures directly to spectral features; (v) approximate the presence of ion species absent from the simulation outputs; (vi) generate column density maps for any ion; and (vii) provide support for all major astrophysical hydrodynamical codes. trident was originally developed to aid in the interpretation of observations of the circumgalactic medium and intergalactic medium, but it remains a general tool applicable in other contexts.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantitative radiography for determining density fluctuations in HED experiments

We have developed a method to extract density fluctuation measurements from x-ray radiographs of high-energy density (HED) instability growth and turbulence experiments. We use this information to calculate density fluctuation statistics for constraining the performance of turbulent mix models in HED systems. The density calculation combines image filtering, removal of systemic effects such as backlighter variation, calculation of transmission across multiple materials, and use of tracer materials to generate an approximate single-material density field. From the density map, we calculate both average density and a variance-like moment b (density-specific-volume covariance), which we compare to our models. We infer both quantities from a single image, which is significantly more information than the historic single scalar mix width measurements. We also develop a method of analyzing simulation outputs that incorporate both the density fluctuation metric from a turbulence model and the bulk material maps from the hydrodynamic code. This analysis helps address the question of how to initialize the simulations for best comparison to data from systems with large separations of scale in the mixing perturbation initial condition. We find that our data analysis method yields 1D average density and b curves with similar morphology and amplitudes as those from preliminary simulation comparisons.

47 OTHER INSTRUMENTATION↗

Thresholding Analysis and Feature Extraction from 3D Ground Penetrating Radar Data for Noninvasive Assessment of Peanut Yield

This study explores the efficacy of utilizing a novel ground penetrating radar (GPR) acquisition platform and data analysis methods to quantify peanut yield for breeding selection, agronomic research, and producer management and harvest applications. Sixty plots comprising different peanut market types were scanned with a multichannel, air-launched GPR antenna. Image thresholding analysis was performed on 3D GPR data from four of the channels to extract features that were correlated to peanut yield with the objective of developing a noninvasive high-throughput peanut phenotyping and yield-monitoring methodology. Plot-level GPR data were summarized using mean, standard deviation, sum, and the number of nonzero values (counts) below or above different percentile threshold values. Best results were obtained for data below the percentile threshold for mean, standard deviation and sum. Data both below and above the percentile threshold generated good correlations for count. Correlating individual GPR features to yield generated correlations of up to 39% explained variability, while combining GPR features in multiple linear regression models generated up to 51% explained variability. The correlations increased when regression models were developed separately for each peanut type. This research demonstrates that a systematic search of thresholding range, analysis window size, and data summary statistics is necessary for successful application of this type of analysis. The results also establish that thresholding analysis of GPR data is an appropriate methodology for noninvasive assessment of peanut yield, which could be further developed for high-throughput phenotyping and yield-monitoring, adding a new sensor and new capabilities to the growing set of digital agriculture technologies.

54 ENVIRONMENTAL SCIENCES↗

Probabilistic Cosmological Mass Mapping from Weak Lensing Shear

We infer gravitational lensing shear and convergence fields from galaxy ellipticity catalogs under a spatial process prior for the lensing potential. We demonstrate the performance of our algorithm with simulated Gaussian-distributed cosmological lensing shear maps and a reconstruction of the mass distribution of the merging galaxy cluster Abell 781 using galaxy ellipticities measured with the Deep Lens Survey. Given interim posterior samples of lensing shear or convergence fields on the sky, we describe an algorithm to infer cosmological parameters via lens field marginalization. In the most general formulation of our algorithm we make no assumptions about weak shear or Gaussian-distributed shape noise or shears. Because we require solutions and matrix determinants of a linear system of dimension that scales with the number of galaxies, we expect our algorithm to require parallel high-performance computing resources for application to ongoing wide field lensing surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Shell structure of {sup 107,109}Ag nuclei and spin–parities nuclei in which the 1{sub g9/2} orbit is being filled

Occupation numbers and energies of proton and neutron orbits in the isotopes {sup 107}Ag and {sup 109}Ag were obtained on the basis of data on nucleon-stripping and nucleon-pickup reactions. A special data-analysis method reducing systematic and statistical uncertainties was applied in relevant calculations. It is shown that, in this region, the spin–parity of nuclei is determined by shells, pairing, and polarization. The schemes of proton and neutron (sub)orbits were constructed. These schemes explain the ground-state spin–parities of N, Z = 39–49 nuclei.

74 ATOMIC AND MOLECULAR PHYSICS↗

Picometer-Precision Atomic Position Tracking through Electron Microscopy

The modern aberration-corrected scanning electron microscopes have successfully achieved direct visualization of atomic columns with sub-angstrom resolution. With this significant progress, advanced image quantification and analysis is still at its early stages. In this work, we present the complete pathway for the metrology of atomic resolution STEM images. This includes: 1) tips for acquiring high-quality STEM images; 2) denoising and drift-correction for enhancing measurement accuracy; 3) obtaining initial atom positions; 4) indexing the atoms based on unit cell vectors; 4) quantifying the atom column positions with either 2D-gaussian single peak fitting or 5) multi-peak fitting routines for slightly overlapping atomic columns; 6) quantification of lattice distortion/strain within the crystal structures or at the defects/interfaces where the lattice periodicity is disrupted, and 7) some common methods to visualize and present the analysis. Furthermore, a simple self-developed free MATLAB app (EASY-STEM) with a graphical user interface (GUI) will be introduced that can help with the analysis of STEM images without the need for writing dedicated analysis code or software. The advanced data analysis methods presented here can be applied for the local quantification of defect relaxations, local structural distortions, local phase transformations, and non-centrosymmetry in a wide range of materials.

47 OTHER INSTRUMENTATION↗

Infrared spectroscopic method for uranium isotopic analysis

A high performance infrared (HPIR) system was developed and demonstrated for the infrared absorption analysis of {sup 235}U and {sup 238}U isotopes in uranium hexafluoride gas samples. Sweeping the quantum cascade laser light source over the spectral range and sampling via a high-rate analog-to-digital converter provided 0.0005 cm-1 spectral resolution, which allowed for high-precision measurements of the isotopic peak shift. A data analysis method was developed using principal component analysis to predict the isotope weight % content of {sup 235}U. The HPIR precision, accuracy, and error were evaluated for a wide range of isotopic ratio samples (0.287 – 93.7 weight % {sup 235}U), and the results were compared to the International Target Values (ITVS) set forth by the International Atomic Energy Agency (IAEA) for non-destructive and destructive analytical techniques. The method meets or surpasses the IAEA ITVs for non-destructive analysis of samples with isotopic content of depleted to highly enriched. The results also demonstrated the capability of the HPIR system to correctly predict the {sup 235}U weight % content of a mislabeled sample whose isotopic distribution was validated by mass spectroscopic measurements. The HPIR measurement is nondestructive and, thus, allows for confirmatory analyses of the exact sample at a designated IAEA lab if higher-resolution or a certified analysis is needed. (author)

07 ISOTOPE AND RADIATION SOURCES↗

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↗