The AstroStat Slog » sunspots http://hea-www.harvard.edu/AstroStat/slog Weaving together Astronomy+Statistics+Computer Science+Engineering+Intrumentation, far beyond the growing borders Fri, 09 Sep 2011 17:05:33 +0000 en-US hourly 1 http://wordpress.org/?v=3.4 [ArXiv] 5th week, Apr. 2008 http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-5th-week-apr-2008/ http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-5th-week-apr-2008/#comments Mon, 05 May 2008 07:08:42 +0000 hlee http://hea-www.harvard.edu/AstroStat/slog/?p=281 Since I learned Hubble’s tuning fork[1] for the first time, I wanted to do classification (semi-supervised learning seems more suitable) galaxies based on their features (colors and spectra), instead of labor intensive human eye classification. Ironically, at that time I didn’t know there is a field of computer science called machine learning nor statistics which do such studies. Upon switching to statistics with a hope of understanding statistical packages implemented in IRAF and IDL, and learning better the contents of Numerical Recipes and Bevington’s book, the ignorance was not the enemy, but the accessibility of data was.

I’m glad to see this week presented a paper that I had dreamed of many years ago in addition to other interesting papers. Nowadays, I’m more and more realizing that astronomical machine learning is not simple as what we see from machine learning and statistical computation literature, which typically adopted data sets from the data repository whose characteristics are well known over the many years (for example, the famous iris data; there are toy data sets and mock catalogs, no shortage of data sets of public characteristics). As the long list of authors indicates, machine learning on astronomical massive data sets are never meant to be a little girl’s dream. With a bit of my sentiment, I offer the list of this week:

  • [astro-ph:0804.4068] S. Pires et al.
    FASTLens (FAst STatistics for weak Lensing) : Fast method for Weak Lensing Statistics and map making
  • [astro-ph:0804.4142] M.Kowalski et al.
    Improved Cosmological Constraints from New, Old and Combined Supernova Datasets
  • [astro-ph:0804.4219] M. Bazarghan and R. Gupta
    Automated Classification of Sloan Digital Sky Survey (SDSS) Stellar Spectra using Artificial Neural Networks
  • [gr-qc:0804.4144]E. L. Robinson, J. D. Romano, A. Vecchio
    Search for a stochastic gravitational-wave signal in the second round of the Mock LISA Data challenges
  • [astro-ph:0804.4483]C. Lintott et al.
    Galaxy Zoo : Morphologies derived from visual inspection of galaxies from the Sloan Digital Sky Survey
  • [astro-ph:0804.4692] M. J. Martinez Gonzalez et al.
    PCA detection and denoising of Zeeman signatures in stellar polarised spectra
  • [astro-ph:0805.0101] J. Ireland et al.
    Multiresolution analysis of active region magnetic structure and its correlation with the Mt. Wilson classification and flaring activity

A relevant post related machine learning on galaxy morphology from the slog is found at svm and galaxy morphological classification

< Added: 3rd week May 2008>[astro-ph:0805.2612] S. P. Bamford et al.
Galaxy Zoo: the independence of morphology and colour

  1. Wikipedia link: Hubble sequence
]]> http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-5th-week-apr-2008/feed/ 0 [ArXiv] 3rd week, Jan. 2008 http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-3rd-week-jan-2008/ http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-3rd-week-jan-2008/#comments Fri, 18 Jan 2008 18:24:23 +0000 hlee http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-3rd-week-jan-2008/ Seven preprints were chosen this week and two mentioned model selection.

  • [astro-ph:0801.2186] Extrasolar planet detection by binary stellar eclipse timing: evidence for a third body around CM Draconis H.J.Deeg (it discusses model selection in section 4.4)
  • [astro-ph:0801.2156] Modeling a Maunder Minimum A. Brandenburg & E. A. Spiegel (it could be useful for those who does sunspot cycle modeling)
  • [astro-ph:0801.1914] A closer look at the indications of q-generalized Central Limit Theorem behavior in quasi-stationary states of the HMF model A. Pluchino, A. Rapisarda, & C. Tsallis
  • [astro-ph:0801.2383] Observational Constraints on the Dependence of Radio-Quiet Quasar X-ray Emission on Black Hole Mass and Accretion Rate B.C. Kelly et.al.
  • [astro-ph:0801.2410] Finding Galaxy Groups In Photometric Redshift Space: the Probability Friends-of-Friends (pFoF) Algorithm I. Li & H. K.C. Yee
  • [astro-ph:0801.2591] Characterizing the Orbital Eccentricities of Transiting Extrasolar Planets with Photometric Observations E. B. Ford, S. N. Quinn, &D. Veras
  • [astro-ph:0801.2598] Is the anti-correlation between the X-ray variability amplitude and black hole mass of AGNs intrinsic? Y. Liu & S. N. Zhang
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