An analysis of the bright O star in the globular cluster M3
Von Zeipel 1128 O star spectrum analysis, discussing mass, He/H ratio, metal abundances, etc
Strom, K. M.↗
SEARCH · Engineering Papers
Results for “Cluster Analysis”
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.
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Cosmology from large-scale galaxy clustering and galaxy–galaxy lensing with Dark Energy Survey Science Verification data
We present cosmological constraints from the Dark Energy Survey (DES) using a combined analysis of angular clustering of red galaxies and their cross-correlation with weak gravitational lensing of background galaxies. We use a 139 square degree contiguous patch of DES data from the Science Verification (SV) period of observations. Using large scale measurements, we constrain the matter density of the Universe as $\Omega_m = 0.31 \pm 0.09$ and the clustering amplitude of the matter power spectrum as $\sigma_8 = 0.74 +\pm 0.13$ after marginalizing over seven nuisance parameters and three additional cosmological parameters. This translates into $S_8$ = $\sigma_8(\Omega_m/0.3)^{0.16} = 0.74 \pm 0.12$ for our fiducial lens redshift bin at 0.35 < z < 0.5, while $S_8 = 0.78 \pm 0.09$ using two bins over the range 0.2 < z < 0.5. We study the robustness of the results under changes in the data vectors, modelling and systematics treatment, including photometric redshift and shear calibration uncertainties, and find consistency in the derived cosmological parameters. We show that our results are consistent with previous cosmological analyses from DES and other data sets and conclude with a joint analysis of DES angular clustering and galaxy-galaxy lensing with Planck CMB data, Baryon Accoustic Oscillations and Supernova type Ia measurements.
79 ASTRONOMY AND ASTROPHYSICS↗
Properties of the open cluster Tombaugh 1 from high-resolution spectroscopy and uvbyCaHβ photometry
Open clusters can be the key to deepening our knowledge on various issues involving the structure and evolution of the Galactic disk and details of stellar evolution because a cluster’s properties are applicable to all its members. However, the number of open clusters with detailed analysis from high-resolution spectroscopy or precision photometry imposes severe limitations on studies of these objects. To expand the number of open clusters with well-defined chemical abundances and fundamental parameters, we investigate the poorly studied, anticenter open cluster Tombaugh 1. Using precision uvbyCaHβ photometry and high-resolution spectroscopy, we derive the cluster’s reddening, obtain photometric metallicity estimates, and, for the first time, present a detailed abundance analysis of 10 potential cluster stars (nine clump stars and one Cepheid). Using the radial position from the cluster center and multiple color indices, we have isolated a sample of unevolved, probable single-star members of Tombaugh 1. From 51 stars, the cluster reddening is found to be E(b−y) = 0.221 ± 0.006 or E(B−V) = 0.303 ± 0.008, where the errors refer to the internal standard errors of the mean. The weighted photometric metallicity from m{sub 1} and hk is [Fe/H] = −0.10 ± 0.02, while a match to the Victoria-Regina Strömgren isochrones leads to an age of 0.95 ± 0.10 Gyr and an apparent modulus of (m−M) = 13.10 ± 0.10. Radial velocities identify six giants as probable cluster members, and the elemental abundances of Fe, Na, Mg, Al, Si, Ca, Ti, Cr, Ni, Y, Ba, Ce, and Nd have been derived for both the cluster and the field stars. Tombaugh 1 appears to be a typical inner thin disk, intermediate-age open cluster of slightly subsolar metallicity, located just beyond the solar circle, with solar elemental abundance ratios except for the heavy s-process elements, which are a factor of two above solar. Its metallicity is consistent with a steep metallicity gradient in the galactocentric region between 9.5 and 12 kpc. Our study also shows that Cepheid XZ CMa is not a member of Tombaugh 1 and reveals that this Cepheid presents signs of barium enrichment, making it a probable binary star.
79 ASTRONOMY AND ASTROPHYSICS↗
The Open Cluster Chemical Abundances and Mapping Survey. VI. Galactic Chemical Gradient Analysis from APOGEE DR17
The goal of the Open Cluster Chemical Abundances and Mapping (OCCAM) survey is to constrain key Galactic dynamic and chemical evolution parameters by the construction and analysis of a large, comprehensive, uniform data set of infrared spectra for stars in hundreds of open clusters. This sixth contribution from the OCCAM survey presents analysis of SDSS/APOGEE Data Release 17 (DR17) results for a sample of stars in 150 open clusters, 94 of which we designate to be "high-quality" based on the appearance of their color–magnitude diagram. We find the APOGEE DR17-derived [Fe/H] values to be in good agreement with those from previous high-resolution spectroscopic open cluster abundance studies. Using a subset of the high-quality sample, the Galactic abundance gradients were measured for 16 chemical elements, including [Fe/H], for both Galactocentric radius ($R$ GC ) and guiding center radius ($R$ guide ). We find an overall Galactic [Fe/H] versus RGC gradient of -0.073 ± 0.002 dex kpc -1 over the range of 6 > $R$ GC < 11.5 kpc, and a similar gradient is found for [Fe/H] versus $R$ guide . Significant Galactic abundance gradients are also noted for O, Mg, S, Ca, Mn, Na, Al, K, and Ce. Our large sample additionally allows us to explore the evolution of the gradients in four age bins for the remaining 15 elements.
79 ASTRONOMY AND ASTROPHYSICS↗
Disentangling Structures in the Cluster of Galaxies Abell 133
A dynamical analysis of the structure of the cluster of galaxies Abell 133 will be presented using multi-wavelength data combined from multiple space and earth based observations. New and familiar statistical clustering techniques are used in combination in an attempt to gain a fully consistent picture of this interesting nearby cluster of galaxies. The type of analysis presented should be typical of cluster studies in the future, especially those to come from the surveys like the Sloan Digital Sky Survey and the 2DF.
Way, Michael J.↗
Metabololipidomic profiling of functional immunoresolvent clusters and eicosanoids in mammalian tissues
Highlights: • New methods for metabololipidomics of specialized proresolving mediators (SPM) and classic eicosanoids. • Illustration from human blood coagulation. • Illustration from solid tumor. • Regulation of SPM biosynthesis by adenosine and adenosine deaminase. Metabolomics enables a systems approach to interrogate the bioactive mediators, their pathways and further metabolites involved in the physiology and pathophysiology of human and animal tissues. New metabololipidomic approaches with mass spectrometry presented in this brief review can now be utilized for the identification and profiling of lipid mediator networks that control inflammation-resolution in human blood and healthy and diseased solid tissues. Coagulation of blood is a protective response that prevents excessive bleeding on injury of blood vessels. Here, we review novel approaches to understand the relationship(s) between coagulation and resolution of inflammation and infection. To determine whether coagulation is involved in host-protective actions by lipid mediators, we used a metabololipidomic-based profiling approach with human whole blood (WB) during coagulation. We identified recently temporal clusters of endogenously produced pro-thrombotic and proinflammatory lipid mediators (eicosanoids), as well as specialized proresolving mediators (SPMs) in this vital process. In addition to the classic eicosanoids (prostaglandins, thromboxanes and leukotrienes), a specific SPM cluster was identified that consists of resolvin E1 (RvE1), RvD1, RvD5, lipoxin B{sub 4}, and maresin 1, each of which present at bioactive concentrations (0.1–1 nM). The removal of adenosine from coagulating blood samples significantly enhances SPM amounts and unleashes the biosynthesis of RvD3, RvD4, and RvD6 evident following rapid snap freezing with centrifugation before extraction and LC-MS-MS. The classic cyclooxygenase inhibitors, celecoxib and indomethacin, that block thromboxanes and prostanoids do not block production of the clot-driven SPM cluster. Unbiased mass cytometry analysis demonstrated that the SPM cluster produced in human blood targets leukocytes at the single-cell level, directly activating extracellular signaling in human neutrophils and monocytes. Human whole blood treated with the components of this SPM cluster enhanced both phagocytosis and killing of Escherichia coli by leukocytes. Thus, we identified a pro-resolving lipid mediator circuit and specific SPM cluster that promotes host defense. This new lipid mediator (LM)-SPM metabololipidomic approach now provides accessible metabolomic profiles in healthy and diseased human tissues, including cancer, for precision and personalized medicine.
60 APPLIED LIFE SCIENCES↗
Quantum Materials at the Nanoscale - Final Report
The central aim of the Quantum Materials at the Nanoscale (QMN) cluster was to understand and control collective behavior involving the interplay of spins, orbitals, and charges, which governs many scientifically interesting and technologically important phenomena in numerous complex materials. Because these phenomena involve various competing interactions, and influence properties on many different length and energy scales in complex materials, tackling this important area of study motivated a collaborative effort that combined the diverse capabilities of QMN cluster experimentalists, the essential theoretical analysis provided by QMN cluster theorists, and the outstanding facilities and staff of the FSMRL. During the funding period 2007-2014, the DOE cluster grant for the Quantum Materials at the Nanoscale (QMN) cluster supported, at various times, 15 different faculty members (14 in Physics and 1 in Materials Science and Engineering), 7 postdoctoral research associates, and 57 physics and materials science PhD students. 41 of these PhD students have since graduated and have gone on to a variety of advanced technical positions at universities, industries, and national labs: 25 obtained postdoctoral positions at universities (14), industrial labs (2 at IBM), DOE national facilities (3 at Argonne National Laboratory, 1 at Brookhaven National Lab, 1 at Lawrence Berkeley National Lab, and 1 at Sandia National Lab), and other federal facilities (2 at NIST); 13 took various industrial positions, including positions at Intel (5), Quantum Design (1), Lasque Industries (1), Amazon (1), Bloomberg (1), and J.P. Morgan (1). Thus, the QMN grant provided the essential support for training a large number of technically advanced personnel who have now entered key national facilities, industries, and institutions. Additionally, during the period 2007-2015, the QMN cluster produced 159 publications (see pages 14-23), including 23 papers published in Physical Review Letters; 16 papers in Nature, Nature Physics, Nature Materials, or Nature Communications; 4 papers in Science, and 8 papers in Applied Physics Letters. In this report, we provide some key highlights of the collaborative projects in which the QMN cluster members have been involved since 2007.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Metatranscriptomic Analyses of Diel Metabolic Functions During a Microcystis Bloom in Western Lake Erie (United States)
This study examined diel shifts in metabolic functions of Microcystis spp. during a 48-h Lagrangian survey of a toxin-producing cyanobacterial bloom in western Lake Erie in the aftermath of the 2014 Toledo Water Crisis. Transcripts mapped to the genomes of recently sequenced lower Great Lakes Microcystis isolates showed distinct patterns of gene expression between samples collected across day (10:00 h, 16:00 h) and night (22:00 h, 04:00 h). Daytime transcripts were enriched in functions related to Photosystem II (e.g., psbA), nitrogen and phosphate acquisition, cell division (ftsHZ), heat shock response (dnaK, groEL), and uptake of inorganic carbon (rbc, bicA). Genes transcribed during nighttime included those involved in phycobilisome protein synthesis and Photosystem I core subunits. Hierarchical clustering and principal component analysis (PCA) showed a tightly clustered group of nighttime expressed genes, whereas daytime transcripts were separated from each other over the 48-h duration. Lack of uniform clustering within the daytime transcripts suggested that the partitioning of gene expression in Microcystis is dependent on both circadian regulation and physicochemical changes within the environment.
59 BASIC BIOLOGICAL SCIENCES↗
SITCOMTN-161: PSF assessment in the field of Abell 360 and shapeHSM shear profile using LSSTComCam data
The Rubin LSSTComCam on-sky campaign performed at the end of 2024 provided observations of the Abell 360 galaxy cluster; these data allow a preliminary study of cluster weak lensing analysis using Rubin Data Preview 1 (DP1) data. Among all the steps required for such analyses, accurate modeling of the PSF is essential. This work uses several diagnostics, mostly based on the residuals between the second moments of stars and the PSF model, to characterize the accuracy of the PSF modeling in the A360 field. We find the level of the residuals to be sufficiently low not to hinder the measurement of the tangential shear profile around A360. With a simple source selection process, we demonstrate that outputs of the LSST Science Pipelines can be used to detect the tangential shear profile in Abell 360 at the 3.6σ level, and our analysis indicates that contamination from PSF modeling systematics is negligible.
Dell'Antonio, Ian [Brown University]↗
The redshift evolution of the mean temperature, pressure, and entropy profiles in 80 SPT-selected galaxy clusters
We present the results of an X-ray analysis of 80 galaxy clusters selected in the 2500 deg{sup 2} South Pole Telescope survey and observed with the Chandra X-ray Observatory. We divide the full sample into subsamples of ∼20 clusters based on redshift and central density, performing a joint X-ray spectral fit to all clusters in a subsample simultaneously, assuming self-similarity of the temperature profile. This approach allows us to constrain the shape of the temperature profile over 0 < r < 1.5R {sub 500}, which would be impossible on a per-cluster basis, since the observations of individual clusters have, on average, 2000 X-ray counts. The results presented here represent the first constraints on the evolution of the average temperature profile from z = 0 to z = 1.2. We find that high-z (0.6 < z < 1.2) clusters are slightly (∼30%) cooler both in the inner (r < 0.1R {sub 500}) and outer (r > R {sub 500}) regions than their low-z (0.3 < z < 0.6) counterparts. Combining the average temperature profile with measured gas density profiles from our earlier work, we infer the average pressure and entropy profiles for each subsample. Confirming earlier results from this data set, we find an absence of strong cool cores at high z, manifested in this analysis as a significantly lower observed pressure in the central 0.1R {sub 500} of the high-z cool-core subset of clusters compared to the low-z cool-core subset. Overall, our observed pressure profiles agree well with earlier lower-redshift measurements, suggesting minimal redshift evolution in the pressure profile outside of the core. We find no measurable redshift evolution in the entropy profile at r ≲ 0.7R {sub 500}—this may reflect a long-standing balance between cooling and feedback over long timescales and large physical scales. We observe a slight flattening of the entropy profile at r ≳ R {sub 500} in our high-z subsample. This flattening is consistent with a temperature bias due to the enhanced (∼3×) rate at which group-mass (∼2 keV) halos, which would go undetected at our survey depth, are accreting onto the cluster at z ∼ 1. This work demonstrates a powerful method for inferring spatially resolved cluster properties in the case where individual cluster signal-to-noise is low, but the number of observed clusters is high.
79 ASTRONOMY AND ASTROPHYSICS↗
Whole-Genome SNP Analysis Identifies Putative Mycobacterium bovis Transmission Clusters in Livestock and Wildlife in Catalonia, Spain
The high-resolution WGS analyses of MTBC strains have provided useful insight for determining sources of infection for animal tuberculosis. In Spain, tuberculosis in livestock is caused by Mycobacterium bovis and Mycobacterium caprae, where wildlife reservoirs play an important role. We analyzed a set of 125 M. bovis isolates obtained from livestock and wildlife from Catalonia to investigate strain diversity and identify possible sources and/or causes of infection. Whole-genome SNP profiles were used for phylogenetic reconstruction and pairwise SNP distance analysis. Additionally, SNPs were investigated to identify virulence and antimicrobial resistance factors to investigate clade-specific associations. Putative transmission clusters (≤12 SNPs) were identified, and associated epidemiological metadata were used to determine possible explanatory factors for transmission. M. bovis distribution was heterogeneous, with 7 major clades and 21 putative transmission clusters. In order of importance, the explanatory factors associated were proximity and neighborhood, residual infection, livestock-wildlife interaction, shared pasture, and movement. Genes related to lipid transport and metabolism showed the highest number of SNPs. All isolates were pyrazinamide resistant, and five were additionally resistant to isoniazid, but no clade-specific associations could be determined. Our findings highlight the importance of high-resolution molecular surveillance to monitor bovine tuberculosis dynamics in a low-prevalence setting.
59 BASIC BIOLOGICAL SCIENCES↗
BD-CATS-IO
Modern cosmology and plasma physics codes are now capable of simulating trillions of particles on petascale systems. Each timestep output from such simulations is on the order of 10s of TBs. Summarizing and visualizing raw particle data is challenging, and scientists often focus on density structures, whether in the real 3D space, or a high-dimensional phase space. In this work, code was developed for reading 10s of terabytes of data and for writing the resultant cluster IDs for each particle. This code will be part of a highly scalable version of the clustering algorithm DBSCAN, and apply it to the largest datasets produced by state-of-the-art codes. The overall function of BD-CATS (Big Data Clustering at Trillion Particles Scale) is to perform end-to-end analysis: loading the data, dynamic partitioning, computing kdtrees, performing clustering analysis, and storing the results. BD-CATS-IO provides the functionality of loading the data and storing the results.
Byna, Surendra↗
Unsupervised Clustering of Microseismic Events and Focal Mechanism Analysis at the CO 2 Injection Site in Decatur, Illinois
Characterization of induced microseismicity at a carbon dioxide (CO 2 ) storage site is critical for preserving reservoir integrity and mitigating seismic hazards. We apply a multilevel machine learning (ML) approach that combines the nonnegative matrix factorization and hidden Markov model to extract spectral representations of microseismic events and cluster them to identify seismic patterns at the Illinois Basin-Decatur Project. Unlike traditional waveform correlation methods, this approach leverages spectral characteristics of first arrivals to improve event classification and detect previously undetected planes of weakness. By integrating ML-based clustering with focal mechanism analysis, we resolve small-scale fault structures that are below the detection limits of conventional seismic imaging. Our findings reveal temporal bursts of microseismicity associated with brittle failure, providing insights into the spatio-temporal evolution of fault reactivation during CO 2 injection. This approach enhances seismic monitoring capabilities at CO 2 injection sites by improving fault characterization beyond the resolution of standard geophysical surveys.
Willis, Rachel Marie [Sandia National Laboratories↗
Deep structural clustering for single-cell RNA-seq data jointly through autoencoder and graph neural network
Abstract Single-cell RNA sequencing (scRNA-seq) permits researchers to study the complex mechanisms of cell heterogeneity and diversity. Unsupervised clustering is of central importance for the analysis of the scRNA-seq data, as it can be used to identify putative cell types. However, due to noise impacts, high dimensionality and pervasive dropout events, clustering analysis of scRNA-seq data remains a computational challenge. Here, we propose a new deep structural clustering method for scRNA-seq data, named scDSC, which integrate the structural information into deep clustering of single cells. The proposed scDSC consists of a Zero-Inflated Negative Binomial (ZINB) model-based autoencoder, a graph neural network (GNN) module and a mutual-supervised module. To learn the data representation from the sparse and zero-inflated scRNA-seq data, we add a ZINB model to the basic autoencoder. The GNN module is introduced to capture the structural information among cells. By joining the ZINB-based autoencoder with the GNN module, the model transfers the data representation learned by autoencoder to the corresponding GNN layer. Furthermore, we adopt a mutual supervised strategy to unify these two different deep neural architectures and to guide the clustering task. Extensive experimental results on six real scRNA-seq datasets demonstrate that scDSC outperforms state-of-the-art methods in terms of clustering accuracy and scalability. Our method scDSC is implemented in Python using the Pytorch machine-learning library, and it is freely available at https://github.com/DHUDBlab/scDSC.
Gan, Yanglan↗
Characterization of DESI fiber assignment incompleteness effect on 2-point clustering and mitigation methods for DR1 analysis
We present an in-depth analysis of the fiber assignment incompleteness in the Dark EnergySpectroscopic Instrument (DESI) Data Release 1 (DR1). This incompleteness is caused by therestricted mobility of the robotic fiber positioner in the DESI focal plane, which limits thenumber of galaxies that can be observed at the same time, especially at small angular separations.As a result, the observed clustering amplitude is suppressed in a scale-dependent manner, which,if not addressed, can severely impact the inference of cosmological parameters. We discuss themethods adopted for simulating fiber assignment on mocks and data. In particular, we introducethe fast fiber assignment (FFA) emulator, which was employed to obtain the power spectrumcovariance adopted for the DR1 full-shape analysis. We present the mitigation techniques,organised in two classes: measurement stage and model stage. We then use high fidelity mocks as areference to quantify both the accuracy of the FFA emulator and the effectiveness of the differentmeasurement-stage mitigation techniques. This complements the studies conducted in a parallelpaper for the model-stage techniques, namely the θ-cut approach. We find that pairwiseinverse probability (PIP) weights with angular upweighting recover the “true” clustering in allthe cases considered, in both Fourier and configuration space. Notably, we present the first everpower spectrum measurement with PIP weights from real data.
79 ASTRONOMY AND ASTROPHYSICS↗
Characterization of DESI fiber assignment incompleteness effect on 2-point clustering and mitigation methods for DR1 analysis
We present an in-depth analysis of the fiber assignment incompleteness in the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1). This incompleteness is caused by the restricted mobility of the robotic fiber positioner in the DESI focal plane, which limits the number of galaxies that can be observed at the same time, especially at small angular separations. As a result, the observed clustering amplitude is suppressed in a scale-dependent manner, which, if not addressed, can severely impact the inference of cosmological parameters. We discuss the methods adopted for simulating fiber assignment on mocks and data. In particular, we introduce the fast fiber assignment (FFA) emulator, which was employed to obtain the power spectrum covariance adopted for the DR1 full-shape analysis. We present the mitigation techniques, organised in two classes: measurement stage and model stage. We then use high fidelity mocks as a reference to quantify both the accuracy of the FFA emulator and the effectiveness of the different measurement-stage mitigation techniques. This complements the studies conducted in a parallel paper for the model-stage techniques, namely the θ-cut approach. We find that pairwise inverse probability (PIP) weights with angular upweighting recover the “true” clustering in all the cases considered, in both Fourier and configuration space. Notably, we present the first ever power spectrum measurement with PIP weights from real data.
cosmological simulations↗
Copacabana: a probabilistic membership assignment method for galaxy clusters
Cosmological analyses using galaxy clusters in optical/near-infrared photometric surveys require robust characterization of their galaxy content. Precisely determining which galaxies belong to a cluster is crucial. In this paper, we present the COlor Probabilistic Assignment of Clusters And BAyesiaN Analysis (Copacabana) algorithm. Copacabana computes membership probabilities for all galaxies within an aperture centred on the cluster using photometric redshifts, colours, and projected radial probability density functions. We use simulations to validate Copacabana and we show that it achieves up to 89 per cent membership accuracy with a mild dependence on photometric redshift uncertainties and choice of aperture size. We find that the precision of the photometric redshifts has the largest impact on the determination of the membership probabilities followed by the choice of the cluster aperture size. We also quantify how much these uncertainties in the membership probabilities affect the stellar mass–cluster mass scaling relation, a relation that directly impacts cosmology. Using the sum of the stellar masses weighted by membership probabilities (μ * ) as the observable, we find that Copacabana can reach an accuracy of 0.06 dex in the measurement of the scaling relation at low redshift for a Legacy Survey of Space and Time type survey. These results indicate the potential of Copacabana and μ * to be used in cosmological analyses of optically selected clusters in the future.
79 ASTRONOMY AND ASTROPHYSICS↗
High Mass Analysis with a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer: From Inorganic Salt Clusters to Antibody Conjugates and Beyond
Analysis of proteins and complexes under native mass spectrometric (MS) and solution conditions was typically performed using time-of-flight (ToF) analyzers, due to their routine high m/z transmission and detection capabilities. However, over recent years, the ability of Orbitrap-based mass spectrometers to transmit and detect a range of high molecular weight species is well documented. Herein, we describe how a 15 Tesla Fourier transform ion cyclotron resonance mass spectrometer (15 T FT-ICR MS) is more than capable of analyzing a wide range of ions in the high m/z scale (>5000), in both positive and negative instrument polarities, ranging from the inorganic cesium iodide salt clusters; a humanized IgG1k monoclonal antibody (mAb; 148.2 kDa); an IgG1-mertansine drug conjugate (148.5 kDa, drug-to-antibody ratio; DAR 2.26); an IgG1-siRNA conjugate (159.1 kDa; ribonucleic acid to antibody ratio; RAR 1); the membrane protein aquaporin-Z (97.2 kDa) liberated from a C8E4 detergent micelle; the empty MSP1D1-nanodisc (142.5 kDa) and the tetradecameric chaperone protein complex GroEL (806.2 kDa; GroEL dimer at 1.6 MDa). We also investigate different regions of the FT-ICR MS that impact ion transmission and desolvation. Finally, we demonstrate how the transmission of these species and resultant spectra are highly consistent with those previously generated on both quadrupole-ToF (Q-ToF) and Orbitrap instrumentation. This article serves as an impactful example of how FT-ICR mass analyzers are competitive to Q-ToFs and Orbitraps for high mass detection at high m/z.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗