Global survey of star clusters in the Milky Way: III. 139 new open clusters at high Galactic latitudes

Context. An earlier analysis of the Milky Way Star Cluster (MWSC) catalogue revealed an apparent lack of old (t � 1 Gyr) open clusters in the solar neighbourhood (d � 1 kpc). Aims. To fill this gap we undertook a search for hitherto unknown star clusters, assuming that the missing old clusters reside at high Galactic latitudes | b | > 20°. Methods. We were looking for stellar density enhancements using a star count algorithm on the 2MASS point source catalogue. To increase the contrast between potential clusters and the field, we applied filters in colour-magnitude space according to typical colour-magnitude diagrams of nearby old open clusters. The subsequent comparison with lists of known objects allowed us to select thus far unknown cluster candidates. For verification they were processed with the standard pipeline used within the MWSC survey for computing cluster membership probabilities and for determining structural, kinematic, and astrophysical parameters. Results. In total we discovered 782 density enhancements, 524 of which were classified as real objects. Among them 139 are new open clusters with ages 8.3 < log (t [yr]) < 9.7, distances d< 3 kpc, and distances from the Galactic plane 0.3 <Z< 1 kpc. This new sample has increased the total number of known high latitude open clusters by about 150%. Nevertheless, we still observe a lack of older nearby clusters up to 1 kpc from the Sun. This volume is expected to still contain about 60 unknown clusters that probably escaped our detection algorithm, which fails to detect sparse overdensities with large angular size

A Deep Halpha Survey of Galaxies in the Two Nearby Clusters Abell1367 and Coma: The Halpha Luminosity Functions

We present a deep wide field Halpha imaging survey of the central regions of the two nearby clusters of galaxies Coma and Abell1367, taken with the WFC at the INT2.5m telescope. We determine for the first time the Schechter parameters of the Halpha luminosity function (LF) of cluster galaxies. The Halpha LFs of Abell1367 and Coma are compared with each other and with that of Virgo, estimated using the B band LF by Sandage et al. (1985) and a L(Halpha) vs M_B relation. Typical parameters of phi^* ~ 10^0.00+-0.07 Mpc^-3, L^* ~ 10^41.25+- 0.05 erg sec^-1 and alpha ~ -0.70+-0.10 are found for the three clusters. The best fitting parameters of the cluster LFs differ from those found for field galaxies, showing flatter slopes and lower scaling luminosities L^*. Since, however, our Halpha survey is significantly deeper than those of field galaxies, this result must be confirmed on similarly deep measurements of field galaxies. By computing the total SFR per unit volume of cluster galaxies, and taking into account the cluster density in the local Universe, we estimate that the contribution of clusters like Coma and Abell1367 is approximately 0.25% of the SFR per unit volume of the local Universe.Comment: 19 pages, 11 figures, accepted for publication in A&

The volume and Chern-Simons invariant of a Dehn-filled manifold

학위논문 (박사)-- 서울대학교 대학원 : 자연과학대학 수리과학부, 2019. 2. 박종일.Based on the work of Neumann, Zickert gave a simplicial formula for computing the volume and Chern-Simons invariant of a boundary-parabolic \psl-representation of a compact 3-manifold with non-empty boundary. Main aim of this thesis is to introduce a notion of deformed Ptolemy assignments (or varieties) and generalize the formula of Zickert to a representation of a Dehn-filled manifold. We also generalize the potential function of Cho and Murakami by applying our formula to an octahedral decomposition of a link complement in the 3-sphere. Also, motivated from the work of Hikami and Inoue, we clarify the relation between Ptolemy assignments and cluster variables when a link is given in a braid position. The last work is a joint work with Jinseok Cho and Christian Zickert.1 Introduction 1 1.1 Deformed Ptolemy assignments . . . . . . . . . . . . . . . . . . . 1 1.1.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2 Potential functions . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.3 Cluster variables . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2 Preliminaries 12 2.1 Cocycles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.2 Obstruction classes . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3 Ptolemy varieties 16 3.1 Formulas of Neumann . . . . . . . . . . . . . . . . . . . . . . . . 16 3.2 Deformed Ptolemy varieties . . . . . . . . . . . . . . . . . . . . . 19 3.2.1 Isomorphisms . . . . . . . . . . . . . . . . . . . . . . . . . 23 3.2.2 Pseudo-developing maps . . . . . . . . . . . . . . . . . . . 27 3.3 Flattenings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 3.3.1 Main theorem . . . . . . . . . . . . . . . . . . . . . . . . . 36 4 Potential functions 43 4.1 Generalized potential functions . . . . . . . . . . . . . . . . . . . 43 4.1.1 Proof of Theorem 4.1.1 . . . . . . . . . . . . . . . . . . . 45 4.2 Relation with a Ptolemy assignment . . . . . . . . . . . . . . . . 50 4.2.1 Proof of Theorem 4.2.1 . . . . . . . . . . . . . . . . . . . 54 4.3 Complex volume formula . . . . . . . . . . . . . . . . . . . . . . . 57 4.3.1 Proof of Theorem 4.3.1 . . . . . . . . . . . . . . . . . . . 59 5 Cluster variables 70 5.1 The Hikami-Inoue cluster variables . . . . . . . . . . . . . . . . . 70 5.1.1 The octahedral decomposition . . . . . . . . . . . . . . . 70 5.1.2 The Hikami-Inoue cluster variables . . . . . . . . . . . . . 71 5.1.3 The obstruction cocycle . . . . . . . . . . . . . . . . . . . 74 5.1.4 Proof of Theorem 1.3.2 . . . . . . . . . . . . . . . . . . . 75 5.2 The existence of a non-degenerate solution . . . . . . . . . . . . . 79 5.2.1 Proof of Proposition 5.2.1 . . . . . . . . . . . . . . . . . . 81 5.2.2 Explicit computation from a representation . . . . . . . . 83Docto

High performance data analysis via coordinated caches

With the second run period of the LHC, high energy physics collaborations will have to face increasing computing infrastructural needs. Opportunistic resources are expected to absorb many computationally expensive tasks, such as Monte Carlo event simulation. This leaves dedicated HEP infrastructure with an increased load of analysis tasks that in turn will need to process an increased volume of data. In addition to storage capacities, a key factor for future computing infrastructure is therefore input bandwidth available per core. Modern data analysis infrastructure relies on one of two paradigms: data is kept on dedicated storage and accessed via network or distributed over all compute nodes and accessed locally. Dedicated storage allows data volume to grow independently of processing capacities, whereas local access allows processing capacities to scale linearly. However, with the growing data volume and processing requirements, HEP will require both of these features. For enabling adequate user analyses in the future, the KIT CMS group is merging both paradigms: popular data is spread over a local disk layer on compute nodes, while any data is available from an arbitrarily sized background storage. This concept is implemented as a pool of distributed caches, which are loosely coordinated by a central service. A Tier 3 prototype cluster is currently being set up for performant user analyses of both local and remote data