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Register a new userGalWeight: A New and Effective Weighting Technique for Determining Galaxy Cluster and Group Membership
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We introduce GalWeight, a new technique for assigning galaxy cluster membership. This technique is specifically designed to simultaneously maximize the number of bona fide cluster members while minimizing the number of contaminating interlopers. The GalWeight technique can be applied to both massive galaxy clusters and poor galaxy groups. Moreover, it is effective in identifying members in both the virial and infall regions with high efficiency. We apply the GalWeight technique to MDPL2 & Bolshoi N-body simulations, and find that it is $> 98%$ accurate in correctly assigning cluster membership. We show that GalWeight compares very favorably against four well-known existing cluster membership techniques (shifting gapper, den Hartog, caustic, SIM). We also apply the GalWeight technique to a sample of twelve Abell clusters (including the Coma cluster) using observations from the Sloan Digital Sky Survey. We end by discussing GalWeights potential for other astrophysical applications.
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We introduce a new effective strategy to assign group and cluster membership probabilities $P_{mem}$ to galaxies using photometric redshift information. Large dynamical ranges both in halo mass and cosmic time are considered. The method takes the magnitude distribution of both cluster and field galaxies as well as the radial distribution of galaxies in clusters into account using a non-parametric formalism and relies on Bayesian inference to take photometric redshift uncertainties into account. We successfully test the method against 1,208 galaxy clusters within redshifts $z=0.05-2.58$ and masses $10^{13.29-14.80}~M_odot$ drawn from wide field simulated galaxy mock catalogs developed for the Euclid mission. Median purity $(55^{+17}_{-15})%$ and completeness $(95^{+5}_{-10})%$ are reached for galaxies brighter than 0.25$L_ast$ within $r_{200}$ of each simulated halo and for a statistical photometric redshift accuracy $sigma((z_s-z_p)/(1+z_s))=0.03$. The mean values $p=56%$ and $c=93%$ have sub-percent uncertainties. Accurate photometric redshifts ($sigma((z_s-z_p)/(1+z_s))lesssim0.05$) and robust estimates for the cluster redshift and the center coordinates are required. The method is applied to derive accurate richness estimates. A statistical comparison between the true ($N_{rm true}$) vs estimated richness ($lambda=sum P_{mem}$) yields on average to unbiased results, $Log(lambda/N_{rm true})=-0.0051pm0.15$. The scatter around the mean of the logarithmic difference between $lambda$ and the halo mass is 0.10~dex, for massive halos $gtrsim10^{14.5}~M_odot$. Our estimates could be useful to calibrate independent cluster mass estimates from weak lensing, SZ, and X-ray studies. Our method can be applied to any list of galaxy clusters or groups in both present and forthcoming surveys such as SDSS, CFHTLS, DES, LSST, and Euclid.
Keck/LRIS multi-object spectroscopy has been carried out on 140 of some of the lowest and highest surface brightness faint (19 < R < 22) dwarf galaxy candidates in the core region of the Coma Cluster. These spectra are used to measure redshifts and establish membership for these faint dwarf populations. The primary goal of the low surface brightness sample is to test our ability to use morphological and surface brightness criteria to distinguish between Coma Cluster members and background galaxies using high resolution HST/ACS images. Candidates were rated as expected members, uncertain, or expected background. From 93 spectra, 51 dwarf galaxy members and 20 background galaxies are identified. Our morphological membership estimation success rate is ~100% for objects expected to be members and better than ~90% for galaxies expected to be in the background. We confirm that low surface brightness is a very good indicator of cluster membership. High surface brightness galaxies are almost always background with confusion arising only from the cases of the rare compact elliptical galaxies. The more problematic cases occur at intermediate surface brightness. Many of these galaxies are given uncertain membership ratings, and these were found to be members about half of the time. Including color information will improve membership determination but will fail for some of the same objects that are already mis-identified when using only surface brightness and morphology criteria. Compact elliptical galaxies with B-V colors ~0.2 magnitudes redward of the red sequence in particular require spectroscopic follow-up. In a sample of 47 high surface brightness, UCD candidates, 19 objects have redshifts which place them in the Coma Cluster. Redshift measurements are presented and the use of indirect means for establishing cluster membership is discussed.
We present a new quantitative technique that determines the times and durations of substorm expansion and recovery phases and possible growth phases based on percentiles of the rate of change of auroral electrojet indices. By being able to prescribe different percentile values, we can determine the onset and duration of substorm phases for smaller or larger variations of the auroral index or indeed any auroral zone ground-based magnetometer data. We apply this technique to the SuperMAG AL (SML) index and compare our expansion phase onset times with previous lists of substorm onsets. We find that more than 50% of events in previous lists occur within 20 min of our identified onsets. We also present a comparison of superposed epoch analyses of SML based on our onsets identified by our technique and existing onset lists and find that the general characteristics of the substorm bay are comparable. By prescribing user-defined thresholds, this automated, quantitative technique represents an improvement over any visual identification of substorm onsets or indeed any fixed threshold method.
This paper proposes a group membership verification protocol preventing the curious but honest server from reconstructing the enrolled signatures and inferring the identity of querying clients. The protocol quantizes the signatures into discrete embeddings, making reconstruction difficult. It also aggregates multiple embeddings into representative values, impeding identification. Theoretical and experimental results show the trade-off between the security and the error rates.
Context. Groups form the most abundant class of galaxy systems. They act as the principal drivers of galaxy evolution and can be used as tracers of the large-scale structure and the underlying cosmology. However, the detection of galaxy groups from galaxy redshift survey data is hampered by several observational limitations. Aims. We improve the widely used friends-of-friends (FoF) group finding algorithm with membership refinement procedures and apply the method to a combined dataset of galaxies in the local Universe. A major aim of the refinement is to detect subgroups within the FoF groups, enabling a more reliable suppression of the fingers-of-God effect. Methods. The FoF algorithm is often suspected of leaving subsystems of groups and clusters undetected. We used a galaxy sample built of the 2MRS, CF2, and 2M++ survey data comprising nearly 80000 galaxies within the local volume of 430 Mpc radius to detect FoF groups. We conducted a multimodality check on the detected groups in search for subgroups. We furthermore refined group membership using the group virial radius and escape velocity to expose unbound galaxies. We used the virial theorem to estimate group masses. Results. The analysis results in a catalogue of 6282 galaxy groups in the 2MRS sample with two or more members, together with their mass estimates. About half of the initial FoF groups with ten or more members were split into smaller systems with the multimodality check. An interesting comparison to our detected groups is provided by another group catalogue that is based on similar data but a completely different methodology. Two thirds of the groups are identical or very similar. Differences mostly concern the smallest and largest of these other groups, the former sometimes missing and the latter being divided into subsystems in our catalogue.
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