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At least 469 records · Page 26

White paper on light sterile neutrino searches and related phenomenology

This white paper provides a comprehensive review of our present understanding of experimental neutrino anomalies that remain unresolved, charting the progress achieved over the last decade at the experimental and phenomenological level, and sets the stage for future programmatic prospects in addressing those anomalies. It is purposed to serve as a guiding and motivational "encyclopedic" reference, with emphasis on needs and options for future exploration that may lead to the ultimate resolution of the anomalies. We see the main experimental, analysis, and theory-driven thrusts that will be essential to achieving this goal being: 1) Cover all anomaly sectors -- given the unresolved nature of all four canonical anomalies, it is imperative to support all pillars of a diverse experimental portfolio, source, reactor, decay-at-rest, decay-in-flight, and other methods/sources, to provide complementary probes of and increased precision for new physics explanations; 2) Pursue diverse signatures -- it is imperative that experiments make design and analysis choices that maximize sensitivity to as broad an array of these potential new physics signatures as possible; 3) Deepen theoretical engagement -- priority in the theory community should be placed on development of standard and beyond standard models relevant to all four short-baseline anomalies and the development of tools for efficient tests of these models with existing and future experimental datasets; 4) Openly share data -- Fluid communication between the experimental and theory communities will be required, which implies that both experimental data releases and theoretical calculations should be publicly available; and 5) Apply robust analysis techniques -- Appropriate statistical treatment is crucial to assess the compatibility of data sets within the context of any given model.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Particle image velocimetry (PIV) uncertainty quantification using moment of correlation (MC) plane

Here, we present a new uncertainty estimation method for particle image velocimetry (PIV), that uses the correlation plane as a model for the probability density function (PDF) of displacements and calculates the second order moment of the correlation (MC). The cross-correlation between particle image patterns is the summation of all particle matches convolved with the apparent particle image diameter. MC uses this property to estimate the PIV uncertainty from the shape of the cross-correlation plane. In this new approach, the generalized cross-correlation (GCC) plane corresponding to a PIV measurement is obtained by removing the particle image diameter contribution. The GCC primary peak represents a discretization of the displacement PDF, from which the standard uncertainty is obtained by convolving the GCC plane with a Gaussian function. Then a Gaussian least-squares-fit is applied to the peak region, accounting for the stretching and rotation of the peak, due to the local velocity gradients and the effect of the convolved Gaussian. The MC method was tested with simulated image sets and the predicted uncertainties show good sensitivity to the error sources and agreement with the expected RMS error. Subsequently, the method was demonstrated in three PIV challenge cases and two experimental datasets and was compared with the published image matching (IM) and correlation statistics (CS) techniques. Results show that the MC method has a better response to spatial variation in RMS error and the predicted uncertainty is in good agreement with the expected standard uncertainty. The uncertainty prediction was also explored as a function of PIV interrogation window size. Overall, the MC method performance establishes itself as a valid uncertainty estimation tool for planar PIV.

47 OTHER INSTRUMENTATION↗

Calibrating the BHB star distance scale and the halo kinematic distance to the Galactic Centre

ABSTRACT We report the first determination of the distance to the Galactic Centre based on the kinematics of halo objects. We apply the statistical-parallax technique to the sample of ∼2500 blue horizontal branch (BHB) stars compiled by Xue et al. to simultaneously constrain the correction factor to the photometric distances of BHB stars as reported by those authors and the distance to the Galactic Centre to find R = 8.2 ± 0.6 kpc. We also find that the average velocity of our BHB star sample in the direction of Galactic rotation, V0 = −240 ± 4 km s−1, is greater by about 20 km s−1 in absolute value than the corresponding velocity for halo RR Lyrae type stars (V0 = −222 ± 4 km s−1) in the Galactocentric distance interval from 6 to 18 kpc, whereas the total (σV) and radial (σr) velocity dispersion of the BHB sample are smaller by about 40–45 km s−1 than the corresponding parameters of the velocity dispersion ellipsoid of halo RR Lyrae type variables. The velocity dispersion tensor of halo BHB stars proved to be markedly less anisotropic than the corresponding tensor for RR Lyrae type variables: the corresponding anisotropy parameter values are equal to βBHB = 0.51 ± 0.02 and βRR = 0.71 ± 0.03, respectively.

Utkin, Nikita D.↗

Characterizing the magnetic fields of nearby molecular clouds using submillimeter polarization observations

Of all the factors that influence star formation, magnetic fields are perhaps the least well understood. The goal of this paper is to characterize the 3D magnetic field properties of nearby molecular clouds through various methods of statistically analysing maps of polarized dust emission. Our study focuses on nine clouds, with data taken from the Planck Sky Survey as well as data from the Balloon-borne Large Aperture Submillimeter Telescope for Polarimetry observations of Vela C. We compare the distributions of polarization fraction (p), dispersion in polarization angles ($\mathcal {S}$), and hydrogen column density (N H ) for each of our targeted clouds. To broaden the scope of our analysis, we compare the distributions of our clouds’ polarization observables with measurements from synthetic polarization maps generated from numerical simulations. We also use the distribution of polarization fraction measurements to estimate the inclination angle of each cloud’s cloud-scale magnetic field. We obtain a range of inclination angles associated with our clouds, varying from 16° to 69°. We establish inverse correlations between p and both $\mathcal {S}$ and NH in almost every cloud, but we are unable to establish a statistically robust $\mathcal {S}$ versus NH trend. By comparing the results of these different statistical analysis techniques, we are able to propose a more comprehensive view of each cloud’s 3D magnetic field properties. These detailed cloud analyses will be useful in the continued studies of cloud-scale magnetic fields and the ways in which they affect star formation within these molecular clouds.

79 ASTRONOMY AND ASTROPHYSICS↗

AutoEnRichness: A hybrid empirical and analytical approach for estimating the richness of galaxy clusters

ABSTRACT We introduce AutoEnRichness, a hybrid approach that combines empirical and analytical strategies to determine the richness of galaxy clusters (in the redshift range of 0.1 ≤ z ≤ 0.35) using photometry data from the Sloan Digital Sky Survey Data Release 16, where cluster richness can be used as a proxy for cluster mass. In order to reliably estimate cluster richness, it is vital that the background subtraction is as accurate as possible when distinguishing cluster and field galaxies to mitigate severe contamination. AutoEnRichness is comprised of a multistage machine learning algorithm that performs background subtraction of interloping field galaxies along the cluster line of sight and a conventional luminosity distribution fitting approach that estimates cluster richness based only on the number of galaxies within a magnitude range and search area. In this proof-of-concept study, we obtain a balanced accuracy of 83.20 per cent when distinguishing between cluster and field galaxies as well as a median absolute percentage error of 33.50 per cent between our estimated cluster richnesses and known cluster richnesses within r200. In the future, we aim for AutoEnRichness to be applied on upcoming large-scale optical surveys, such as the Legacy Survey of Space and Time and Euclid, to estimate the richness of a large sample of galaxy groups and clusters from across the halo mass function. This would advance our overall understanding of galaxy evolution within overdense environments as well as enable cosmological parameters to be further constrained.

79 ASTRONOMY AND ASTROPHYSICS↗

Automatic detection of low surface brightness galaxies from Sloan Digital Sky Survey images

ABSTRACT Low surface brightness (LSB) galaxies are galaxies with central surface brightness fainter than the night sky. Due to the faint nature of LSB galaxies and the comparable sky background, it is difficult to search LSB galaxies automatically and efficiently from large sky survey. In this study, we established the low surface brightness galaxies autodetect (LSBG-AD) model, which is a data-driven model for end-to-end detection of LSB galaxies from Sloan Digital Sky Survey (SDSS) images. Object-detection techniques based on deep learning are applied to the SDSS field images to identify LSB galaxies and estimate their coordinates at the same time. Applying LSBG-AD to 1120 SDSS images, we detected 1197 LSB galaxy candidates, of which 1081 samples are already known and 116 samples are newly found candidates. The B-band central surface brightness of the candidates searched by the model ranges from 22 to 24 mag arcsec−2, quite consistent with the surface brightness distribution of the standard sample. A total of 96.46 per cent of LSB galaxy candidates have an axial ratio (b/a) greater than 0.3, and 92.04 per cent of them have $fracDev\_r$ < 0.4, which is also consistent with the standard sample. The results show that the LSBG-AD model learns the features of LSB galaxies of the training samples well, and can be used to search LSB galaxies without using photometric parameters. Next, this method will be used to develop efficient algorithms to detect LSB galaxies from massive images of the next-generation observatories.

79 ASTRONOMY AND ASTROPHYSICS↗

AGNs in post-mergers from the ultraviolet near infrared optical northern survey

The kinematic disturbances associated with major galaxy mergers are known to produce gas inflows, which in turn may trigger accretion onto the supermassive black holes (SMBH) of the participant galaxies. While this effect has been studied in galaxy pairs, the frequency of active galactic nuclei (AGNs) in fully coalesced post-merger systems is poorly constrained due to the limited size or impurity of extant post-merger samples. Previously, we combined convolutional neural network (CNN) predictions with visual classifications to identify a highly pure sample of 699 post-mergers in deep r-band imaging. In the work presented here, we quantify the frequency of AGNs in this sample using three metrics: optical emission lines, mid-infrared (mid-IR) colour, and radio detection of low-excitation radio galaxies (LERGs). We also compare the frequency of AGNs in post-mergers to that in a sample of spectroscopically identified galaxy pairs. We find that AGNs identified by narrow-line optical emission and mid-IR colour have an increased incidence rate in post-mergers, with excesses of ~4 over mass- and redshift-matched controls. The optical and mid-IR AGN excesses in post-mergers exceed the values found for galaxy pairs, indicating that AGN activity in mergers peaks after coalescence. Conversely, we recover no significant excess of LERGs in post-mergers or pairs. Finally, we find that the [O III ] luminosity (a proxy for SMBH accretion rate) in post-mergers that host an optical AGN is ~0.3 dex higher on average than in non-interacting galaxies with an optical AGN, suggesting that mergers generate higher accretion rates than secular triggering mechanisms.

79 ASTRONOMY AND ASTROPHYSICS↗

The satellite population around luminous red galaxies in the 25 deg2 DESI Legacy Imaging Surveys Early Data Release

ABSTRACT Luminous red galaxies, or LRGs, are representative of the most massive galaxies and were originally selected in the Sloan Digital Sky Survey as good tracers of large-scale structure. They are dominated by by uniformly old stellar populations, have low star formation rates, early type morphologies, and little cold gas. Despite having old stellar populations and little in situ star formation, studies have shown that they have grown their stellar mass since z = 1, implying that they grow predominantly via the accretion of satellites. Tests of this picture have been limited because of the lack of deep imaging data sets that both covers a large enough area of the sky to contain substantial numbers of LRGs and that also is deep enough to detect faint satellites. We use the 25 deg2 Early Data Release (EDR) of the DESI Legacy Imaging Surveys to characterize the satellite galaxy population of LRGs out to z = 0.65. The DESI Legacy Imaging Surveys are comprised of grz imaging to 2–2.5 mag deeper than SDSS and with better image quality. We use a new statistical background technique to identify excess populations of putative satellite galaxies around 1823 LRGs at 0.2 < z < 0.65. In three redshift and luminosity bins we measure the numbers of satellite galaxies and their r−z colour distribution down to rest-frame g-band luminosity limits at least 3.6 times fainter than L*. In addition, we develop a forward modeling technique and apply it to constrain the mean number of satellites in each of our redshift and luminosity bins. Finally, we use these estimates to determine the amount of stellar mass growth in LRGs down to the local Universe.

Astronomy & Astrophysics↗

What drives the variance of galaxy spectra?

We present a study aimed at understanding the physical phenomena underlying the formation and evolution of galaxies following a data-driven analysis of spectroscopic data based on the variance in a carefully selected sample. We apply principal component analysis (PCA) independently to three subsets of continuum-subtracted optical spectra, segregated into their nebular emission activity as quiescent, star-forming, and active galactic nuclei (AGNs). We emphasize that the variance of the input data in this work only relates to the absorption lines in the photospheres of the stellar populations. The sample is taken from the Sloan Digital Sky Survey (SDSS) in the stellar velocity dispersion range 100–150 km s −1 , to minimize the ‘blurring’ effect of the stellar motion. We restrict the analysis to the first three principal components (PCs) and find that PCA segregates the three types with the highest variance mapping SSP-equivalent age, along with an inextricable degeneracy with metallicity, even when all three PCs are included. Spectral fitting shows that stellar age dominates PC1, whereas PC2 and PC3 have a mixed dependence of age and metallicity. The trends support – independently of any model fitting – the hypothesis of an evolutionary sequence from star formation to AGN to quiescence. As a further test of the consistency of the analysis, we apply the same methodology in different spectral windows, finding similar trends, but the variance is maximal in the blue wavelength range, roughly around the 4000 Å break.

79 ASTRONOMY AND ASTROPHYSICS↗

redMaGiC: Selecting luminous red galaxies from the DES Science Verification data

Here, we introduce redMaGiC, an automated algorithm for selecting luminous red galaxies (LRGs). The algorithm was specifically developed to minimize photometric redshift uncertainties in photometric large-scale structure studies. redMaGiC achieves this by self-training the colour cuts necessary to produce a luminosity-thresholded LRG sample of constant comoving density. We demonstrate that redMaGiC photo-zs are very nearly as accurate as the best machine learning-based methods, yet they require minimal spectroscopic training, do not suffer from extrapolation biases, and are very nearly Gaussian. We apply our algorithm to Dark Energy Survey (DES) Science Verification (SV) data to produce a redMaGiC catalogue sampling the redshift range z ϵ [0.2, 0.8]. Our fiducial sample has a comoving space density of 10 –3 (h –1 Mpc) –3 , and a median photo-z bias (zspec – zphoto) and scatter (σz/(1 + z)) of 0.005 and 0.017, respectively. The corresponding 5σ outlier fraction is 1.4 per cent. We also test our algorithm with Sloan Digital Sky Survey Data Release 8 and Stripe 82 data, and discuss how spectroscopic training can be used to control photo-z biases at the 0.1 per cent level.

79 ASTRONOMY AND ASTROPHYSICS↗

The nature and energetics of AGN-driven perturbations in the hot gas in the Perseus Cluster

In this paper, cores of relaxed galaxy clusters are often disturbed by AGN. Their Chandra observations revealed a wealth of structures induced by shocks, subsonic gas motions, bubbles of relativistic plasma, etc. In this paper, we determine the nature and energy content of gas fluctuations in the Perseus core by probing statistical properties of emissivity fluctuations imprinted in the soft- and hard-band X-ray images. About 80 per cent of the total variance of perturbations on ~8–70 kpc scales in the core have an isobaric nature, i.e. are consistent with subsonic displacements of the gas in pressure equilibrium with the ambient medium. The observed variance translates to the ratio of energy in perturbations to thermal energy of ~13 per cent. In the region dominated by weak ‘ripples’, about half of the total variance is associated with isobaric perturbations on scales of a few tens of kpc. If these isobaric perturbations are induced by buoyantly rising bubbles, then these results suggest that most of the AGN-injected energy should first go into bubbles rather than into shocks. Using simulations of a shock propagating through the Perseus atmosphere, we found that models reproducing the observed features of a central shock have more than 50 per cent of the AGN-injected energy associated with the bubble enthalpy and only about 20 per cent is carried away with the shock. Such energy partition is consistent with the AGN-feedback model, mediated by bubbles of relativistic plasma, and supports the importance of turbulence in the cooling–heating balance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Models of the strongly lensed quasar DES J0408-5354

We present gravitational lens models of the multiply imaged quasar DES J0408-5354, recently discovered in the Dark Energy Survey (DES) footprint, with the aim of interpreting its remarkable quad-like configuration. We first model the DES single-epoch $grizY$ images as a superposition of a lens galaxy and four point-like objects, obtaining spectral energy distributions (SEDs) and relative positions for the objects. Three of the point sources (A,B,D) have SEDs compatible with the discovery quasar spectra, while the faintest point-like image (G2/C) shows significant reddening and a `grey' dimming of $\approx0.8$mag. In order to understand the lens configuration, we fit different models to the relative positions of A,B,D. Models with just a single deflector predict a fourth image at the location of G2/C but considerably brighter and bluer. The addition of a small satellite galaxy ($R_{\rm E}\approx0.2$") in the lens plane near the position of G2/C suppresses the flux of the fourth image and can explain both the reddening and grey dimming. All models predict a main deflector with Einstein radius between $1.7"$ and $2.0",$ velocity dispersion $267-280$km/s and enclosed mass $\approx 6\times10^{11}M_{\odot},$ even though higher resolution imaging data are needed to break residual degeneracies in model parameters. The longest time-delay (B-A) is estimated as $\approx 85$ (resp. $\approx125$) days by models with (resp. without) a perturber near G2/C. The configuration and predicted time-delays of J0408-5354 make it an excellent target for follow-up aimed at understanding the source quasar host galaxy and substructure in the lens, and measuring cosmological parameters. We also discuss some lessons learnt from J0408-5354 on lensed quasar finding strategies, due to its chromaticity and morphology.

79 ASTRONOMY AND ASTROPHYSICS↗

Galaxy–Galaxy lensing in HSC: Validation tests and the impact of heterogeneous spectroscopic training sets

Although photometric redshifts (photo-z’s) are crucial ingredients for current and upcoming large-scale surveys, the high-quality spectroscopic redshifts currently available to train, validate, and test them are substantially non-representative in both magnitude and colour. We investigate the nature and structure of this bias by tracking how objects from a heterogeneous training sample contribute to photo-z predictions as a function of magnitude and colour, and illustrate that the underlying redshift distribution at fixed colour can evolve strongly as a function of magnitude. We then test the robustness of the galaxy–galaxy lensing signal in 120 deg 2 of HSC–SSP DR1 data to spectroscopic completeness and photo-z biases, and find that their impacts are sub-dominant to current statistical uncertainties. Our methodology provides a framework to investigate how spectroscopic incompleteness can impact photo-z-based weak lensing predictions in future surveys such as LSST and WFIRST .

79 ASTRONOMY AND ASTROPHYSICS↗

Hypothesis testing of scientific Monte Carlo calculations

The steadily increasing size of scientific Monte Carlo simulations and the desire for robust, correct, and reproducible results necessitates rigorous testing procedures for scientific simulations in order to detect numerical problems and programming bugs. However, the testing paradigms developed for deterministic algorithms have proven to be ill suited for stochastic algorithms. In this paper we demonstrate explicitly how the technique of statistical hypothesis testing, which is in wide use in other fields of science, can be used to devise automatic and reliable tests for Monte Carlo methods, and we show that these tests are able to detect some of the common problems encountered in stochastic scientific simulations. We argue that hypothesis testing should become part of the standard testing toolkit for scientific simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Intermittent dynamics in externally driven ferroelastics and strain glasses

The interplay of elastic anisotropy and disorder dictates many of the properties of ferroic materials, specifically martensites. Here we use a phase-field model for ferroelastic athermal materials to study their response to an increasing external stress that couples to the strain order parameter. We show that these systems evolve through avalanches and study the avalanche-size distribution for ferroelastic systems (large anisotropy and/or small disorder) and for the strain glass (small anisotropy and/or large disorder) using various statistical analysis techniques, including the maximum likelihood method. The model predicts that in the former case the distribution is subcritical or power law (in agreement with experimental observations), whereas in the latter case it becomes supercritical. Finally, our results are consistent with experiments on martensitic materials, and we predict specific avalanche behavior that can be tested and used as an alternative means to characterize strain glasses.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SU-D-202-03: Statistical Segmentation On Quantitative CT for Assessing Spatial Tumor Response During Radiation Therapy Delivery

Purpose: Develop a method to segment regions of interest (ROIs) in tumor with statistically similar Hounsfield unit (HU) values and/or HU changes during chemoradiation therapy (CRT) delivery, to assess spatial tumor treatment response based on daily CTs during CRT delivery. Methods: Generate a three region map of ROIs with differential HUs, by sampling neighboring voxels around a selected voxel and comparing to the mean of the entire ROI using a t-test. The cumulative distribution function, P, is calculated from the t-test. The P value is assigned to be the value at the selected voxel, and this is repeated over all voxels in the initial ROI. Three regions are defined as: (1-P) < 0.00001 (mid region), and 0.00001 < (1-P) (mean greater than baseline and mean lower than baseline). The test is then expanded to compare daily CT sets acquired during routine CT-guided RT delivery using a CT-on-rails. The first fraction CT is used as the baseline for comparison. We tested 15 pancreatic head tumor cases undergoing CRT, to identify the ROIs and changes corresponding to normal, fibrotic, and tumor tissue. The obtained ROIs were compared with MRI-ADC maps acquired pre- and post-CRT. Results: The ROIs in 13 out of 15 patients’ first fraction CTs and pre-CRT MRIs matched the general region and slices covered, as well as in 6 out of the 9 patients with post-CRT MRIs. The high HU region designated by the t-test was seen to correlate with the tumor region in MR, and these ROIs are positioned within the same region over the course of treatment. In patients with poorly delineated tumors in MR, the t-test was inconclusive. Conclusion: The proposed statistical segmentation technique shows the potential to identify regions in tumor with differential HUs and HU changes during CRT delivery for patients with pancreas head cancer.

60 APPLIED LIFE SCIENCES↗

Machine learning-based analysis of COVID-19 pandemic impact on US research networks

Here in this study we explore how fallout from the changing public health policy around COVID-19 has changed how researchers access and process their science experiments. Using a combination of techniques from statistical analysis and machine learning, we conduct a retrospective analysis of historical network data for a period around the stay-at-home orders that took place in March 2020. Our analysis takes data from the entire ESnet infrastructure to explore DOE high-performance computing (HPC) resources at OLCF, ALCF, and NERSC, as well as User sites such as PNNL and JLAB. We look at detecting and quantifying changes in site activity using a combination of t-Distributed Stochastic Neighbor Embedding (t-SNE) and decision tree analysis. Our findings bring insights into the working patterns and impact on data volume movements, particularly during late-night hours and weekends.

97 MATHEMATICS AND COMPUTING↗

Reply to “What Is the Maximum Entropy Principle? Comments on ‘Statistical Theory on the Functional Form of Cloud Particle Size Distributions’”

We welcome the opportunity to correct the misunderstandings and misinterpretations contained in Yano’s comment that led him to incorrectly state that Wu and McFarquhar misunderstood the maximum entropy (MaxEnt) principle. As correctly stated by Yano, the principle itself does not suffer from the problem of a lack of invariance. But, as restated in this reply and in Wu and McFarquhar, the commonly used Shannon–Gibbs entropy does suffer from a lack of invariance for coordinate transform when applied in continuous cases, and this problem is resolved by the use of the relative entropy. Further, it is restated that the Wu and McFarquhar derivation of the PSD form using MaxEnt is more general than the formulation by Yano and allows more constraints with any functional relations to be applied. The derivation of Yano is nothing new but the representation of PSDs in other variables.

54 ENVIRONMENTAL SCIENCES↗