Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Cluster detection”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18

Binary-binary interactions and the formation of the PSR B1620-26 triple system in M4

The hierarchical triple system containing the millisecond pulsar PSR B1620-26 in M4 is the first star system ever detected in a globular cluster. Such systems should form in globular clusters as a result of dynamical interactions between binaries. We propose that the triple system containing PSR B1620-26 formed through an exchange interaction between a wide primordial binary and a pre-existing binary millisecond pulsar. This scenario would have the advantage of reconciling the approximately 10(exp 9) yr timing age of the pulsar with the much shorter lifetime of the triple system in the core of M4.

Rasio, Frederic A.↗

Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles

Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/~ge/gedihome.html Supplementary information: http://www.chip.org/~ge/gedihome.html.

Database Management Systems↗

Spatially Resolved Imaging at 350 Micrometers of Cold Dust in Nearby Elliptical Galaxies

Continuum observations at 350 micrometers of seven nearby elliptical galaxies for which CO gas disks have recently been resolved with interferometry mapping are presented. These SHARC II mapping results provide the first clearly resolved far-infrared (FIR)-to-submillimeter continuum emission from cold dust (with temperatures 31 K is approximately greater than T approximately greater than 23 K) of any elliptical galaxy at a distance greater than 40 Mpc. The measured FIR excess shows that the most likely and dominant heating source of this dust is not dilute stellar radiation or cooling flows, but rather star formation that could have been triggered by an accretion or merger event and fueled by dust-rich material that has settled in a dense region cospatial with the central CO gas disks. The dust is detected even in two cluster ellipticals that are deficient in H (sub I), showing that, unlike H (sub I), cold dust and CO in ellipticals can survive in the presence of hot X-ray gas, even in galaxy clusters. No dust cooler than 20 K, either distributed outside the CO disks or cospatial with and heated by the entire dilute stellar optical galaxy (or very extended H (sub I)), is currently evident.

photometry↗

High performance FPGA embedded system for machine learning based tracking and trigger in sPhenix and EIC

We present a comprehensive end-to-end pipeline to classify triggers versus background events in this paper. This pipeline makes online decisions to select signal data and enables the intelligent trigger system for efficient data collection in the Data Acquisition System (DAQ) of the upcoming sPHENIX and future EIC (Electron-Ion Collider) experiments. Starting from the coordinates of pixel hits that are lightened by passing particles in the detector, the pipeline applies three-stage of event processing (hits clustering, track reconstruction, and trigger detection) and labels all processed events with the binary tag of trigger versus background events. The pipeline consists of deterministic algorithms such as clustering pixels to reduce event size, tracking reconstruction to predict candidate edges, and advanced graph neural network-based models for recognizing the entire jet pattern. In particular, we apply the message-passing graph neural network to predict links between hits and reconstruct tracks and a hierarchical pooling algorithm (DiffPool) to make the graph-level trigger detection. We obtain an impressive performance (≥70% accuracy) for trigger detection with only 3200 neuron weights in the end-to-end pipeline. We deploy the end-to-end pipeline into a field-programmable gate array (FPGA) and accelerate the three stages with speedup factors of 1152, 280, and 21, respectively.

Instruments & Instrumentation↗

Predictions for the Detectability of Milky Way Satellite Galaxies and Outer-Halo Star Clusters with the Vera C. Rubin Observatory

We predict the sensitivity of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) to faint, resolved Milky Way satellite galaxies and outer-halo star clusters. We characterize the expected sensitivity using simulated LSST data from the LSST Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2) accessed and analyzed with the Rubin Science Platform as part of the Rubin Early Science Program. We simulate resolved stellar populations of Milky Way satellite galaxies and outer-halo star clusters over a wide range of sizes, luminosities, and heliocentric distances, which are broadly consistent with expectations for the Milky Way satellite system. We inject simulated stars into the DC2 catalog with realistic photometric uncertainties and star/galaxy separation derived from the DC2 data itself. We assess the probability that each simulated system would be detected by LSST using a conventional isochrone matched-filter technique. We find that assuming perfect star/galaxy separation enables the detection of resolved stellar systems with $M_V$ = 0 mag and $r_{1/2}$ = 10 pc with >50% efficiency out to a heliocentric distance of ~250 kpc. Similar detection efficiency is possible with a simple star/galaxy separation criterion based on measured quantities, although the false positive rate is higher due to leakage of background galaxies into the stellar sample. When assuming perfect star/galaxy classification and a model for the galaxy-halo connection fit to current data, we predict that 89 +/- 20 Milky Way satellite galaxies will be detectable with a simple matched-filter algorithm applied to the LSST wide-fast-deep data set. Different assumptions about the performance of star/galaxy classification efficiency can decrease this estimate by ~7%-25%, which emphasizes the importance of high-quality star/galaxy separation for studies of the Milky Way satellite population with LSST.

79 ASTRONOMY AND ASTROPHYSICS↗

Studies of the evolution of the x ray emission of clusters of galaxies

The x ray luminosity function of clusters of galaxies was determined at different cosmic epoches using data from the Einstein Observatory Extended Medium Survey. The sample consisted of 67 x ray selected clusters that were grouped into three redshift shells. Evolution was detected in the x ray properties of clusters. The present volume density of high luminosity clusters was found to be greater than it was in the past. This result is the first convincing evidence for evolution in the x ray properties of clusters. Investigations into the constraints provided by these data on various Cold Dark Matter models are underway.

Henry, J. Patrick↗

Sonora exploratory study for the detection of wheat-leaf rust

The applicability of LANDSAT remote sensing technology to the detection of a wheat-leaf-rust epidemic in Sonora, Mexico, during 1977 was investigated. LANDSAT data acquired during crop years 1975-76 and 1976-77 were clustered, classified, and analyzed in order to detect agricultural changes. Analysis of 1977 data indicates a significant proportion of the identified wheat is stressed (potentially rust-infected). Additional analyses show a significant increase in fallowing during the year, as well as a substantial decrease in reservoir levels in the Sonora agricultural region. Ground observations are required to substantiate these analyses. The possibility exists that heat-rust is not LANDSAT detectable and that the clusters identified as containing stressed signatures represent different varieties of wheat or perhaps nonwheat crops.

Payne, R. W.↗

Decaying neutrinos in galaxy clusters

Davidsen et al. (1991) have argued that the failure to detect UV photons from the dark matter (DM) in cluster A665 excludes the decaying neutrino hypothesis. Sciama et al. (1993) argued that because of high central concentration the DM in that cluster must be baryonic. We study the DM profile in clusters of galaxies simulated using the Harrison-Zel'dovich spectrum of density fluctuations, and an amplitude previously derived from numerical simulations (Melott 1984b; Anninos et al. 1991) and in agreement with microwave background fluctuations (Smoot et al. 1992). We find that with this amplitude normalization cluster neutrino DM densities are comparable to observed cluster DM values. We conclude that given this normalization, the cluster DM should be at least largely composed of neutrinos. The constraint of Davidsen et al. can be somewhat weakened by the presence of baryonic DM; but it cannot be eliminated given our assumptions.

Melott, Adrian L.↗

A joint SZ–X-ray–optical analysis of the dynamical state of 288 massive galaxy clusters

In this work, we use imaging from the first three years of the Dark Energy Survey to characterize the dynamical state of 288 galaxy clusters at 0.1 ≲ z ≲ 0.9 detected in the South Pole Telescope (SPT) Sunyaev–Zeldovich (SZ) effect survey (SPT-SZ). We examine spatial offsets between the position of the brightest cluster galaxy (BCG) and the centre of the gas distribution as traced by the SPT-SZ centroid and by the X-ray centroid/peak position from Chandra and XMM data. We show that the radial distribution of offsets provides no evidence that SPT SZ-selected cluster samples include a higher fraction of mergers than X-ray-selected cluster samples. We use the offsets to classify the dynamical state of the clusters, selecting the 43 most disturbed clusters, with half of those at z ≳ 0.5, a region seldom explored previously. We find that Schechter function fits to the galaxy population in disturbed clusters and relaxed clusters differ at z > 0.55 but not at lower redshifts. Disturbed clusters at z > 0.55 have steeper faint-end slopes and brighter characteristic magnitudes. Within the same redshift range, we find that the BCGs in relaxed clusters tend to be brighter than the BCGs in disturbed samples, while in agreement in the lower redshift bin. Possible explanations includes a higher merger rate, and a more efficient dynamical friction at high redshift. The red-sequence population is less affected by the cluster dynamical state than the general galaxy population.

79 ASTRONOMY AND ASTROPHYSICS↗

Evidence for X-ray emission from superclusters of galaxies determined from Uhuru

X-ray emission from three class 2 clusters of rich clusters of galaxies has been detected. A definition for these objects based in part on Abell's (1961) description is used, and 12 candidate superclusters of distance class 5 and six clusters are found within the area of sky covered by the 4U catalog. The probability that these three X-ray sources accidentally coincide with the superclusters is less than 0.003. Equally low probabilities are found that the X-ray emission is due to either a single luminous cluster or to the combined emission of all members of the supercluster. A possible explanation of these sources is thermal bremsstrahlung emission from a hot tenuous gas pervading the supercluster. The mass of the gas can be as much as 10 times the mass of the galaxies in the supercluster and comparable to the virial mass necessary to bind the supercluster gravitationally. Should such regions of enhanced gas density be found to be associated with all groups of clusters (multiplicity of at least 2), this gas may provide a significant fraction of the mass required to close the universe.

Murray, S. S.↗

The MeerKAT Fornax Survey: II. The rapid removal of H I from dwarf galaxies in the Fornax cluster

We present MeerKAT Fornax Survey atomic hydrogen (H I) observations of the dwarf galaxies located in the central ~2.5 × 4 deg 2 of the Fornax galaxy cluster (R vir ~2°). The H I images presented in this work have a 3σ column density sensitivity between 2.7 and 50 × 10 18 cm –2 over 25 km s –1 for spatial resolution between 4 and 1 kpc. We are able to detect an impressive M HI = 5 × 10 5 M ⊙ 3σ point source with a line width of 50 km s –1 at a distance of 20 Mpc. We detected H I in 17 out of the 304 dwarfs in our field, with 14 out of the 36 late-type dwarfs (LTDs) and three out of the 268 early-type dwarfs (ETDs). The H I-detected LTDs have likely just joined the cluster and are on their first infall as they are located at large clustocentric radii, with comparable MHI and mean stellar surface brightness at fixed luminosity as blue, star-forming LTDs in the field. By contrast, the H I-detected ETDs have likely been in the cluster longer than the LTDs and acquired their H I through a recent merger or accretion from nearby H I. Eight of the H I-detected LTDs host irregular or asymmetric H I emission and disturbed or lopsided stellar emission. There are two clear cases of ram pressure shaping the H I, with the LTDs displaying compressed H I on the side closest to the cluster centre and a one-sided, starless tail pointing away from the cluster centre. The H I-detected dwarfs avoid the most massive potentials (i.e. cluster centre and massive galaxies), consistent with massive galaxies playing an active role in the removal of H I. We created a simple toy model to quantify the timescale of H I stripping in the cluster by reproducing the observed M r' –M HI relation. We find that a M HI = 10 8 M ⊙ dwarf is stripped in ~240 Myr. The model is consistent with our observations, where low-mass LTDs are directly stripped of their H I from a single encounter and more massive LTDs can harbour a disturbed H I morphology due to longer times or multiple encounters being required to fully strip their H I. This is the first time dwarf galaxies with M HI ≲ 1 × 10 6 M ⊙ have been detected and resolved beyond the local group and in a galaxy cluster.

79 ASTRONOMY AND ASTROPHYSICS↗

X-ray archaeology in the Coma cluster

We present images of X-ray emission from hot gas within the Coma cluster of galaxies. These maps, made with the ROSAT satellite, have much higher SNR than any previous X-ray image of a galaxy cluster, and allow cluster structure to be analyzed in unprecedented detail. They show greater structural irregularity than might have been anticipated from earlier observations of Coma. Emission is detected from a number of bright cluster galaxies in addition to the two known previously. In four cases, there is evidence that these galaxies lie at the center of an extended subconcentration within the cluster, possibly the remnant of their associated groups. For at least two galaxies, the images show direct evidence for ongoing disruption of their gaseous atmosphere. The luminosity associated with these galaxies is comparable to that detected around similar ellipticals in much poorer environments. Emission is easily detected to the limit of our field, about 1 deg from the cluster center, and appears to become more regular at large radii. The data show clearly that this archetype of a rich and regular galaxy cluster was, in fact, formed by the merging of several distinct subunits which are not yet fully destroyed.

White, Simon D. M.↗

Detection of Anomalies in Gamma Background Radiation Data with K-Means and Self-Organizing Map Clustering Algorithms (Consortium on Nuclear Security Technologies (CONNECT) Q1 Report)

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. The challenge is that spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.

61 RADIATION PROTECTION AND DOSIMETRY↗

Deep ROSAT HRI observations of the Orion nebula region

We present results from three deep ROSAT high-resolution imager observations of the Orion Nebula star-forming region. The X-ray images contain over 1500 cataloged stars in a roughly 0.8 sq deg region centered on the Trapezium. In all, 389 distinct X-ray sources have been detected, at least two-thirds of which are associated with a single proper-motion cluster member. X-ray emission is detected from stars of all spectral types, from massive O- and B-type components of the Trapezium to the coolest, low-mass pre-main-sequence (PMS) stars. In this paper we focus primarily on X-ray emission from the late-type PMS stars. Of the approximately 100 late-type cluster members with measured spectral types, approximately three-fourths have been detected; we have derived X-ray luminosity upper limits for the remaining stars. We found coronal X-ray emission turns on around spectral type F6, with the upper envelope of activity increasing with deceasing effective temperature. When plotted in an X-ray luminosity versus bolometric luminosity diagram, late-type PMS stars lie below a 'saturation' line corresponding to L(sub x)/L(sub bol) approximately 10(exp -3). For approximately solar-mass PMS stars, we find a median X-ray luminosity approximately 1 x 10(exp 30) ergs/s. The late G, K, and M stars exhibit nearly a two order of magnitude spread in X-ray luminosity and in L(sub x)/L(sub bol) at a given effective temperature. Plots of X-ray activity versus v sin i rotational velocity and rotational period appear to show no clear dependence of activity on rotation. However, because only a small fraction of late-type PMS stars in the Orion Nebula have measured v sin i or P(sub rot) and because of uncertainties in L(sub x) and L(sub x)/L(sub bol), we believe the data are not conclusive on this point. Light curves of the detected X-ray sources have revealed at least 10 strong X-ray flares with characteristic rise times greater than or approximately equal to 1 hr and decay times ranging from approximately 2 to 12 hr. All the flares have X-ray energies in excess of 3 x 10(exp 35) ergs. Many of the X-ray sources associated with late-type cluster members have been observed in more than one ROSAT HRI exposure, allowing us to look for variability on the approximately 1 yr timescale between HRI observations. A statistical analysis of the resulting count rate ratios suggests that at least one-fourth of the late-type cluster stars are significantly variable on this timescale.

Gagne, Marc↗

Robust clustering of the local Milky Way stellar kinematic substructures with Gaia eDR3

Understanding local stellar kinematic substructures in the solar neighbourhood helps build a complete picture of the formation of the Milky Way, as well as an empirical phase space distribution of dark matter that would inform detection experiments. We apply the clustering algorithm HDBSCAN on the Gaia early third data release to identify a list of stable clusters in velocity space and action-angle space by taking into account the measurement uncertainties and studying the stability of the clustering results. We find 1405 (497) stars in 23 (6) robust clusters in velocity space (action-angle space) that are consistently not associated with noise. We discuss the kinematic properties of these structures and study whether many of the small clusters belong to a similar larger cluster based on their chemical abundances. They are attributed to the known structures: the Gaia Sausage-Enceladus, the Helmi Stream, and globular cluster NGC 3201 are found in both spaces, while NGC 104 and the thick disc (Sequoia) are identified in velocity space (action-angle space). Although we do not identify any new structures, we find that the HDBSCAN member selection of already known structures is unstable to input kinematics of the stars when resampled within their uncertainties. We therefore present the stable subset of local kinematic structures, which are consistently identified by the clustering algorithm, and emphasize the need to take into account error propagation during both the manual and automated identification of stellar structures, both for existing ones as well as future discoveries.

79 ASTRONOMY AND ASTROPHYSICS↗

Vapor-cavity-QED system for quantum computation and communication

In this work, we propose performing key operations in quantum computation and communication using room-temperature atoms moving across a grid of high-quality-factor, small-mode-volume cavities. These cavities enable high-cooperativity interactions with single atoms to be achieved with a characteristic timescale much shorter than the atomic transit time, allowing multiple coherent operations to take place. We study scenarios where we can drive a Raman transition to generate photons with specific temporal shapes and to absorb, and hence detect, single photons. The strong atom-cavity interaction can also be used to implement the atom-photon controlled-phase gate, which can then be used to construct photon-photon gates, create photonic cluster states, and perform nondemolition detection of single photons. We provide numerics validating our methods and discuss the implications of our results for several applications.

Austin, Sharoon [National Institute of Standards a↗

Machine-learning identification of the variability of mean velocity and turbulence intensity for wakes generated by onshore wind turbines: Cluster analysis of wind LiDAR measurements

Light detection and ranging (LiDAR) measurements of isolated wakes generated by wind turbines installed at an onshore wind farm are leveraged to characterize the variability of the wake mean velocity and turbulence intensity during typical operations, which encompass a breadth of atmospheric stability regimes and rotor thrust coefficients. The LiDAR measurements are clustered through the k-means algorithm, which enables identifying the most representative realizations of wind turbine wakes while avoiding the imposition of thresholds for the various wind and turbine parameters. Considering the large number of LiDAR samples collected to probe the wake velocity field, the dimensionality of the experimental dataset is reduced by projecting the LiDAR data on an intelligently truncated basis obtained with the proper orthogonal decomposition (POD). The coefficients of only five physics-informed POD modes are then injected in the k-means algorithm for clustering the LiDAR dataset. The analysis of the clustered LiDAR data and the associated supervisory control and data acquisition and meteorological data enables the study of the variability of the wake velocity deficit, wake extent, and wake-added turbulence intensity for different thrust coefficients of the turbine rotor and regimes of atmospheric stability. Furthermore, the cluster analysis of the LiDAR data allows for the identification of systematic off-design operations with a certain yaw misalignment of the turbine rotor with the mean wind direction.

17 WIND ENERGY↗

Detection of large-scale alignment of Lick counts around Abell clusters

The possible tendency of galaxies to be distributed in an aligned fashion, on sheets or filaments, on scales greater than the Abell radius, has been tested by a variety of statistics. The subject remains controversial because the statistical tests have either not been sensitive to the alignment or capable of unambiguously signalling alignment in a general, clumpy distribution of galaxies. The present approach combines ideas of Bingelli (1982) and Fry and Peebles (1980) in an examination of the cross correlation of Lick counts relative to the preferred direction defined by the cluster. This can substantially reduce the noise, and it is suggested on this basis that alignment has been found on large scales for Lick galaxy counts and Abell cluster positions and their angles.

Argyres, P. C.↗