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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Utah FORGE Project 3-2417: DAS Microseismic Event Catalog from the 16A/16B Circulation Test, 2023

This preliminary data archive includes the relocated microseismic event catalog, 1D velocity model, and methods report from DAS acquisition conducted during the Well 16A and 16B circulation test (July 19th and 20th, 2023) at Utah FORGE. The methods report describes all processing steps, including real-time event detection, hierarchical clustering, joint velocity/hypocenter inversion, and relocation. The resulting work is accepted and will be presented at IMAGE 2024. This dataset was acquired by the FOGMORE R&D project (Fiber Optic MOnitoring for Reservoir Evolution), Utah FORGE R&D Project 3-2417.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Galaxy Clusters Selected via the Sunyaev–Zel’dovich Effect in the SPTpol 100-square-degree Survey

In this work, we present a catalog of galaxy cluster candidates detected in 100 square degrees surveyed with the SPTpol receiver on the South Pole Telescope. The catalog contains 89 candidates detected with a signal-to-noise ratio greater than 4.6. The candidates are selected using the Sunyaev–Zel'dovich effect at 95 and 150 GHz. Using both space- and ground-based optical and infrared telescopes, we have confirmed 81 candidates as galaxy clusters. We use these follow-up images and archival images to estimate photometric redshifts for 66 galaxy clusters and spectroscopic observations to obtain redshifts for 13 systems. An additional two galaxy clusters are confirmed using the overdensity of near-infrared galaxies only and are presented without redshifts. We find that 15 candidates (18% of the total sample) are at redshift z ≥ 1.0, with a maximum confirmed redshift of ${z}_{\max }=1.38\pm 0.10$. We expect this catalog to contain every galaxy cluster with ${M}_{500c}\gt 2.6\times {10}^{14}{M}_{\odot }{{h}}_{70}^{-1}$ and z > 0.25 in the survey area. The mass threshold is approximately constant above z = 0.25, and the complete catalog has a median mass of approximately ${M}_{500c}=2.7\times {10}^{14}{M}_{\odot }{{h}}_{70}^{-1}$. Compared to previous SPT works, the increased depth of the millimeter-wave data (11.2 and 6.5 μK-arcmin at 95 and 150 GHz, respectively) makes it possible to find more galaxy clusters at high redshift and lower mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

TEMImageNet training library and AtomSegNet deep-learning models for high-precision atom segmentation, localization, denoising, and deblurring of atomic-resolution images

Abstract Atom segmentation and localization, noise reduction and deblurring of atomic-resolution scanning transmission electron microscopy (STEM) images with high precision and robustness is a challenging task. Although several conventional algorithms, such has thresholding, edge detection and clustering, can achieve reasonable performance in some predefined sceneries, they tend to fail when interferences from the background are strong and unpredictable. Particularly, for atomic-resolution STEM images, so far there is no well-established algorithm that is robust enough to segment or detect all atomic columns when there is large thickness variation in a recorded image. Herein, we report the development of a training library and a deep learning method that can perform robust and precise atom segmentation, localization, denoising, and super-resolution processing of experimental images. Despite using simulated images as training datasets, the deep-learning model can self-adapt to experimental STEM images and shows outstanding performance in atom detection and localization in challenging contrast conditions and the precision consistently outperforms the state-of-the-art two-dimensional Gaussian fit method. Taking a step further, we have deployed our deep-learning models to a desktop app with a graphical user interface and the app is free and open-source. We have also built a TEM ImageNet project website for easy browsing and downloading of the training data.

25 ENERGY STORAGE↗
DOE OSTI2023

Relativistic coupled-cluster calculations of RaOH pertinent to spectroscopic detection and laser cooling

Here a relativistic coupled-cluster study of the low-lying electronic states in the radium monohydroxide molecule (RaOH), a radioactive polyatomic molecule of interest to laser cooling and to the search of new physics beyond the Standard Model, is reported. The level positions of the A 2 Π 1/2 and C 2 Σ states have been computed with an accuracy of around 200 cm –1 to facilitate spectroscopic observation of RaOH using laser induced fluorescence spectroscopy, thereby exploiting the systematic convergence of electron-correlation and basis-set effects in relativistic coupled-cluster calculations. The energy level for the B 2 Δ 3/2 state has also been calculated accurately to conclude that the B 2 Δ 3/2 state lies above the A 2 Π 1/2 state. This confirms X 2 Σ ↔ A 2 Π 1/2 as a promising optical cycling transition for laser cooling RaOH.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Spatial and Kinematic Clustering of Stars in the Galactic Disk

The Galactic disk is expected to be spatially and kinematically clustered on many scales due to both star formation and the Galactic potential. In this work we calculate the spatial and kinematic two-point correlation functions (TPCF) using a sample of 1.7 × 10 6 stars with radial velocities from Gaia DR2. Clustering is detected on spatial scales of 1–300 pc and a velocity scale of 15 km s –1 . After removing bound structures, the data have a power-law index of γ ≈ –1 for 1 pc < Δr < 100 pc and γ ≲ –1.5 for Δr > 100 pc. We interpret these results with the aid of a star-by-star simulation of the Galaxy, in which stars are born in clusters orbiting in a realistic potential that includes spiral arms, a bar, and giant molecular clouds. We find that the simulation largely agrees with the observations at most spatial and kinematic scales. In detail, the TPCF in the simulation is shallower than the data at ≲20 pc scales, and steeper than the data at ≳30 pc. We also find a persistent clustering signal in the kinematic TPCF for the data at large Δv (>5 km s –1 ) that is not present in the simulations. We speculate that this mismatch between observations and simulations may be due to two processes: hierarchical star formation and transient spiral arms. Furthermore, we also predict that the addition of ages and metallicities measured with a precision of 50% and 0.05 dex, respectively, will enhance the clustering signal beyond current measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The SPT-Chandra BCG Spectroscopic Survey. I. Evolution of the Entropy Threshold for ICM Cooling and AGN Feedback in Galaxy Clusters over the Last 10 Gyr

Abstract We present a multiwavelength study of the brightest cluster galaxies (BCGs) in a sample of the 95 most massive galaxy clusters selected from the South Pole Telescope Sunyaev–Zeldovich (SZ) survey. Our sample spans a redshift range of 0.3 < z < 1.7, and is complete with optical spectroscopy from various ground-based observatories, as well as ground and space-based imaging from optical, X-ray, and radio wave bands. At z ∼ 0, previous studies have shown a strong correlation between the presence of a low-entropy cool core and the presence of both star formation and radio-loud active galactic nuclei in the central BCG. We show for the first time that the central entropy threshold for triggering star formation, which is universally seen in nearby systems, persists out to z ∼ 1, with only marginal (∼1 σ ) evidence for evolution in the threshold entropy value itself. In contrast, we do not find a similar high- z analog for an entropy threshold for feedback, but instead measure a strong evolution in the fraction of radio-loud BCGs in high-entropy cores, decreasing with increasing redshift. This could imply that the cooling-feedback loop was not as tight in the past, or that some other fuel source like mergers are fueling the radio sources more often with increasing redshift, making the radio luminosity an increasingly unreliable proxy for radio jet power. We also find that our SZ-based sample is missing a small (∼4%) population of the most luminous radio sources ( ν L ν > 10 42 erg s −1 ), likely due to radio contamination suppressing the SZ signal with which these clusters are detected.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Zwartia hollandica gen. nov., sp. nov., Jezberella montanilacus gen. nov., sp. nov. and Sheuella amnicola gen. nov., comb. nov., representing the environmental GKS98 (betIII) cluster

We present two strains affiliated with the GKS98 cluster. This phylogenetically defined cluster is representing abundant, mainly uncultured freshwater bacteria, which were observed by many cultivation-independent studies on the diversity of bacteria in various freshwater lakes and streams. Bacteria affiliated with the GKS98 cluster were detected by cultivation-independent methods in freshwater systems located in Europe, Asia, Africa and the Americas. The two strains, LF4-65 T (=CCUG 56422 T =DSM 107630 T ) and MWH-P2sevCIIIb T (=CCUG 56420 T =DSM 107629 T ), are aerobic chemoorganotrophs, both with genome sizes of 3.2 Mbp and G+C values of 52.4 and 51.0 mol%, respectively. Phylogenomic analyses based on concatenated amino acid sequences of 120 proteins suggest an affiliation of the two strains with the family Alcaligenaceae and revealed Orrella amnicola and Orrella marina (= Algicoccus marinus ) as being the closest related, previously described species. However, the calculated phylogenomic trees clearly suggest that the current genus Orrella represents a polyphyletic taxon. Based on the branching order in the phylogenomic trees, as well as the revealed phylogenetic distances and chemotaxonomic traits, we propose to establish the new genus Zwartia gen. nov. and the new species Z. hollandica sp. nov. to harbour strain LF4-65 T and the new genus Jezberella gen. nov. and the new species J. montanilacus sp. nov. to harbour strain MWH-P2sevCIIIb T . Furthermore, we propose the reclassification of the species Orrella amnicola in the new genus Sheuella gen. nov. The new genera Zwartia, Jezberella and Sheuella together represent taxonomically the GKS98 cluster.

Microbiology↗
DOE OSTI2020

Implications from Monitoring Gopher Tortoises at Two Spatial Scales

A problem that conservation biologists face is how to monitor species, given both resource limitations and the inherent challenges of assessing long-term demographic processes. We assessed gopher tortoise (Gopherus polyphemus) abundance at a landscape scale and at the scale of 3 local populations within the Conecuh National Forest (CNF).USA between 1991 and 2017. Landscape-level data were collected 26 from line transect distance sampling arranged uniformly across the CNF and collected during a single season (2011); data for local populations were generated from long-term mark-recapture of individuals at three sites selected based on prior knowledge of high density at each. At a landscape scale, we estimated 5,242 (95% CI = 3,538-7,768) tortoises occurred across the approximately 34,000-ha forest, yielding a density of 0.14-0.32 tortoises/ ha. These low densities across the landscape suggest that, on average, management activities across the property have not allowed tortoise populations to retain social structure needed for long-term persistence. The three local populations, however, contained 25-60 individuals and densities of 1.9–6.9 tortoises/ha. Over the study period, populations at two sites were stable and the third experienced significant population growth. Mean annual survival of individuals was 0.89 and invariant across size classes. Altogether, line transect distance sampling is important for assessing landscape-scale abundance of tortoises but may fail to detect local clusters of high-density sites important for population persistence. Our mark-recapture efforts at the local scale revealed that small populations on these high-density sites can exhibit long-term stability or growth even though they do not meet current established criteria for viability. Improved models that incorporate immigration and emigration and better reflect dynamics of peripheral populations would assist in determining how such populations best contribute to species recovery and regional conservation targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Three dimensional cluster analysis for atom probe tomography using Ripley’s K-function and machine learning

The size and structure of spatial molecular and atomic clustering can significantly impact material properties and is therefore important to accurately quantify. Ripley’s K-function (K(r)), a measure of spatial correlation, can be used to perform such quantification when the material system of interest can be represented as a marked point pattern. This work demonstrates how machine learning models based on K (r)-derived metrics can accurately estimate cluster size and intra-cluster density in simulated three dimensional (3D) point patterns containing spherical clusters of varying size; over 90% of model estimates for cluster size and intra-cluster density fall within 11% and 18% error of the true values, respectively. These K (r)-based size and density estimates are then applied to an experimental APT reconstruction to characterize MgZn clusters in a 7000 series aluminum alloy. Here we find that the estimates are more accurate, consistent, and robust to user interaction than estimates from the popular maximum separation algorithm. Using K (r) and machine learning to measure clustering is an accurate and repeatable way to quantify this important material attribute.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Detecting Cage Crossing and Filling Clusters of Magnesium and Carbon Atoms in Zeolite SSZ-13 with Atom Probe Tomography

The conversion of methanol to valuable hydrocarbon molecules is of great commercial interest, as the process serves as a sustainable alternative for the production of, for instance, the base chemicals for plastics. The reaction is catalyzed by zeolite materials. By the introduction of magnesium as a cationic metal, the properties of the zeolite, and thereby the catalytic performance, are changed. With atom probe tomography (APT), nanoscale relations within zeolite materials can be revealed: i.e., crucial information for a fundamental mechanistic understanding. We show that magnesium forms clusters within the cages of zeolite SSZ-13, while the framework elements are homogeneously distributed. These clusters of just a few nanometers were analyzed and visualized in 3-D. Magnesium atoms seem to initially be directed to the aluminum sites, after which they aggregate and fill one or two cages in the zeolite SSZ-13 structure. The presence of magnesium in zeolite SSZ-13 increases the lifetime as well as the propylene selectivity. By using operando UV–vis spectroscopy and X-ray diffraction techniques, we are able to show that these findings are related to the suppression of aromatic intermediate products, while maintaining the formation of polyaromatic compounds. Further nanoscale analysis of the spent catalysts showed indications of magnesium redistribution after catalysis. Unlike zeolite H-SSZ-13, for which only a homogeneous distribution of carbon was found, carbon can be either homogeneously or heterogeneously distributed within zeolite Mg-SSZ-13 crystals as the magnesium decreases the coking rate. Carbon clusters were isolated, visualized, and analyzed and were assumed to be polyaromatic compounds. Small one-cage-filling polyaromatic compounds were identified; furthermore, large-cage-crossing aromatic molecules were found by isolating large coke clusters, demonstrating the unique coking mechanism in zeolite SSZ-13. Short-length-scale evidence for the formation of polyaromatic compounds at acid sites is discovered, as clear nanoscale relations between aluminum and carbon atoms exist.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Symmetry-specific orientational order parameters for complex structures

A comprehensive framework of characterizing complex self-assembled structures with a set of orientational order parameters is presented. It is especially relevant in the context of using anisotropic building blocks with various symmetries. Two classes of tensor order parameters are associated with polyhedral nematic and bond orientational order. For the latter, a variation of classical bond order parameters (BOPs) is introduced, which takes advantage of the symmetry of constituent particles and/or expected crystalline phases. These symmetrized BOPs can be averaged over an entire system or assigned locally to an individual bond. By combining that with the bond percolation procedure, one is able to identify coherent domains within a self-assembled structure. As a demonstration of the proposed framework, we apply it to a simulated hybrid system that combines isotropic and patchy particles with octahedral symmetry. In conclusion, not only does the methodology allow one to identify individual crystalline domains but also it detects coherent clusters of a peculiar compact amorphous structure that is not space-filling and lacks any long-range order.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Atacama Cosmology Telescope: Combined kinematic and thermal Sunyaev-Zel’dovich measurements from BOSS CMASS and LOWZ halos

The scattering of cosmic microwave background (CMB) photons off the free-electron gas in galaxies and clusters leaves detectable imprints on high resolution CMB maps: the thermal and kinematic Sunyaev-Zel’dovich effects (tSZ and kSZ respectively). We use combined microwave maps from the Atacama Cosmology Telescope DR5 and Planck in combination with the CMASS (mean redshift $\langle z \rangle$ = 0.55 and host halo mass $\langle M_{vir} \rangle$ = 3 × 10 13 M ⊙ ) and LOWZ ( $\langle z \rangle$ = 0.31 , $\langle M_{vir} \rangle$ = 5 × 10 13 M ⊙ ) galaxy catalogs from the Baryon Oscillation Spectroscopic Survey (BOSS DR10 and DR12), to study the gas associated with these galaxy groups. Using individual reconstructed velocities, we perform a stacking analysis and reject the no-kSZ hypothesis at 6.5σ, the highest significance to date. This directly translates into a measurement of the electron number density profile, and thus of the gas density profile. Despite the limited signal to noise, the measurement shows at high significance that the gas density profile is more extended than the dark matter density profile, for any reasonable baryon abundance (formally > 90 σ for the cosmic baryon abundance). We simultaneously measure the tSZ signal, i.e., the electron thermal pressure profile of the same CMASS objects, and reject the no-tSZ hypothesis at 10σ. We combine tSZ and kSZ measurements to estimate the electron temperature to 20% precision in several aperture bins, and find it comparable to the virial temperature. In a companion paper, we analyze these measurements to constrain the gas thermodynamics and the properties of feedback inside galaxy groups. We present the corresponding LOWZ measurements in this paper, ruling out a null kSZ (tSZ) signal at 2.9 (13.9) σ , and leave their interpretation to future work. This paper and the companion paper demonstrate that current CMB experiments can detect and resolve gas profiles in low mass halos and at high redshifts, which are the most sensitive to feedback in galaxy formation and the most difficult to measure any other way. They will be a crucial input to cosmological hydrodynamical simulations, thus improving our understanding of galaxy formation. These precise gas profiles are already sufficient to reduce the main limiting theoretical systematic in galaxy-galaxy lensing: baryonic uncertainties. Future such measurements will thus unleash the statistical power of weak lensing from the Rubin, Euclid and Roman observatories. Finally, our stacking software ThumbStackis publicly available and directly applicable to future Simons Observatory and CMB-S4 data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Development of Multimodal Few-Shot Analytics for Electron Micrographs

Recent advances in materials data analytics have provided new avenues for determining process-structure-property (PSP) linkages in a variety of materials. Machine learning techniques including few-shot learning have increased the efficiency of classifying microscopy images for the purposes of material characterization. Attempts at creating a multimodal approach can provide further improvements to current models and help extract more salient features from data. In this vein, raw spectrum data was taken to provide an additional modality to our current pyCHIP classifier. Modifications in segmentation also show potential in improving the accuracy of the pyCHIP classifier. Classifier output was analyzed using network graphs and unsupervised clustering algorithms such as spectral clustering to detect better segmentation methods than the current “chipping” approach. We suggest that the chip selection process can be automated in the future using a combination of these techniques to enable high-throughput analyses.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Probing the pH Effect on Boehmite Particles in Water Using Vacuum Ultraviolet Single-Photon Ionization Mass Spectrometry

Boehmite has been widely used in theoretical research and industry, especially for hazardous material processing. For the liquid-phase treating process, the interfacial properties of boehmite are believed to be affected by pH conditions, which change its physicochemical behavior. However, molecular-level detection on cluster ions is challenging when using bulk approaches. Herein we employ in situ vacuum ultraviolet single-photon ionization mass spectrometry (VUV SPI-MS) coupled with a vacuum-compatible microreactor system for analysis at the liquid–vacuum interface (SALVI) to investigate the solute molecular composition of boehmite under different pH conditions for the first time. The mass spectral results show that more complex clustering of solute molecules exists at the solid–liquid (s–l) interface than conventionally perceived in a “simple” aqueous solution. Besides solute ions, such as boehmite molecules and fragments, the composition and appearance energies of these newly discovered solvated cluster ions are determined by VUV SPI-MS in different pH solutions. We offer new results for the pH-dependent effect of boehmite and provide insights into a more detailed solvation mechanism at the s–l interface. By comparing the key products under different pH conditions, fundamental understanding of boehmite dissolution is revealed to assist the engineering design of waste processing and storage solutions.

SALVI↗
DOE OSTI2022

The Design and Integrated Performance of SPT-3G

Abstract SPT-3G is the third survey receiver operating on the South Pole Telescope dedicated to high-resolution observations of the cosmic microwave background (CMB). Sensitive measurements of the temperature and polarization anisotropies of the CMB provide a powerful data set for constraining cosmology. Additionally, CMB surveys with arcminute-scale resolution are capable of detecting galaxy clusters, millimeter-wave bright galaxies, and a variety of transient phenomena. The SPT-3G instrument provides a significant improvement in mapping speed over its predecessors, SPT-SZ and SPTpol. The broadband optics design of the instrument achieves a 430 mm diameter image plane across observing bands of 95, 150, and 220 GHz, with 1.2′ FWHM beam response at 150 GHz. In the receiver, this image plane is populated with 2690 dual-polarization, trichroic pixels (∼16,000 detectors) read out using a 68× digital frequency-domain multiplexing readout system. In 2018, SPT-3G began a multiyear survey of 1500 deg 2 of the southern sky. We summarize the unique optical, cryogenic, detector, and readout technologies employed in SPT-3G, and we report on the integrated performance of the instrument.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Detecting CAN Masquerade Attacks with Signal Clustering Similarity

Vehicular Controller Area Networks (CANs) are susceptible to cyber attacks of different levels of sophistication. Fabrication attacks are the easiest to administer—an adversary simply sends (extra) frames on a CAN—but also the easiest to detect because they disrupt frame frequency. To overcome time-based detection methods, adversaries must administer masquerade attacks by sending frames in lieu of (and therefore at the expected time of) benign frames but with malicious payloads. Research efforts have proven that CAN attacks, and masquerade attacks in particular, can affect vehicle functionality. Examples include causing unintended acceleration, deactivation of vehicle’s brakes, as well as steering the vehicle. We hypothesize that masquerade attacks modify the nuanced correlations of CAN signal time series and how they cluster together. Therefore, changes in cluster assignments should indicate anomalous behavior. We confirm this hypothesis by leveraging our previously developed capability for reverse engineering CAN signals (i.e., CAN-D [Controller Area Network Decoder]) and focus on advancing the state of the art for detecting masquerade attacks by analyzing time series extracted from raw CAN frames. Specifically, we demonstrate that masquerade attacks can be detected by computing time series clustering similarity using hierarchical clustering on the vehicle’s CAN signals (time series) and comparing the clustering similarity across CAN captures with and without attacks. We test our approach in a previously collected CAN dataset with masquerade attacks (i.e., the ROAD dataset) and develop a forensic tool as a proof of concept to demonstrate the potential of the proposed approach for detecting CAN masquerade attacks.

Moriano Salazar, Pablo↗
DOE OSTI2022

A search for stellar structures around nine outer halo globular clusters in the Milky Way

We use deep imaging from the Dark Energy Camera to explore the peripheral regions of nine globular clusters in the outer halo of the Milky Way. Apart from Whiting 1 and NGC 7492, which are projected against the Sagittarius stream, we see no evidence for adjacent stellar populations to indicate any of these clusters is associated with coherent tidal debris from a destroyed host dwarf. We also find no evidence for tidal tails around any of the clusters in our sample; however, both NGC 1904 and 6981 appear to possess outer envelopes. Here, motivated by a slew of recent Gaia -based discoveries, we compile a sample of clusters with robust detections of extra-tidal structure, and search for correlations with orbital properties. While we observe that clusters with tidal tails are typically on moderately or very eccentric orbits that are highly inclined to the Galactic plane and often retrograde, these are neither necessary nor sufficient conditions for the formation of extra-tidal structure. That many objects with tidal tails appear to be accreted leads us to speculate that this lack of consistency may stem from the inhomogeneous dynamical history of the Milky Way globular cluster system. Finally, we note that clusters with prominent stellar envelopes detected in ground-based imaging (such as NGC 1851 and 7089) are now all known from Gaia to possess long tidal tails – experimental confirmation that the presence of an extended envelope is indicative of tidal erosion.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

DELVE-ing into the Milky Way’s Globular Clusters: Assessing Extratidal Features in NGC 5897, NGC 7492, and Testing Detectability with Deeper Photometry

Extratidal features around globular clusters (GCs) are tracers of their disruption, stellar stream formation, and their host’s gravitational potential. However, these features remain challenging to detect due to their low surface brightness. We conduct a systematic search for such features around 19 GCs in the DECam Local Volume Exploration (DELVE) survey Data Release 2, discovering a new extra-tidal envelope around NGC 5897 and find tentative evidence for an extended envelope surrounding NGC 7492. Through a combination of dynamical modeling and analyzing synthetic stellar populations, we demonstrate these envelopes may have formed through tidal disruption. We use these models to explore the detectability of these features in the upcoming Legacy Survey of Space and Time (LSST), finding that while LSST’s deeper photometry will enhance detection significance, additional methods for foreground removal like proper motions or metallicities may be important for robust stream detection. Our results both add to the sample of globular clusters with extratidal features and provide insights on interpreting similar features in current and upcoming data.

Chiti, A. [Univ. of Chicago, IL (United States); S↗