Archive for the ‘Stars’ Category.

after “Thanks to Henrietta Leavitt”

flyer
Personally, it was a highly anticipated symposium at CfA because I was fascinated about the female computers’ (or astronomers’) contributions that occurred here about a century ago even though at that time women were not considered as scientists but mere assistants for tedious jobs. Continue reading ‘after “Thanks to Henrietta Leavitt”’ »

“Thanks to Henrietta Leavitt”

[9/30/2008]

The CfA is celebrating the 100th anniversary of the discovery of the Cepheid period-luminosity relation on Nov 6, 2008. See http://www.cfa.harvard.edu/events/2008/leavitt/ for details.

[Update 10/03] For a nice introduction to the story of Henrietta Swan Leavitt, listen to this Perimeter Institute talk by George Johnson: http://pirsa.org/06050003/

[Update 11/06] The full program is now available. The symposium begins at Noon today.

The Big Picture

Our hometown rag (the Boston Globe) runs an occasional series of photo collections that highlight news stories called The Big Picture. This week, they take a look at the Sun: http://www.boston.com/bigpicture/2008/10/the_sun.html

The pictures come from space and ground observatories, from SoHO, TRACE, Hinode, STEREO, etc. Goes without saying, the images are stunning, and some are even animated. The real kicker is that images such as these are being acquired by the hundreds, every hour upon the hour, 24/7/365.25 . It is like sipping from a firehose. Nobody can sit there and look at them all, so who knows what we are missing out on. Can statistics help? Can we automate a statistically robust “interestingness” criterion to filter the data stream that humans can then follow up on?

Differential Emission Measure [Eqn]

Differential Emission Measures (DEMs) are a summary of the temperature structure of the outer atmospheres (aka coronae) of stars, and are usually derived from a select subset of line fluxes. They are notoriously difficult to estimate. Very few algorithms even bother to calculate error envelopes on them. They are also subject to numerous systematic uncertainties which can play havoc with proper interpretation. But they are nevertheless extremely useful since they allow changes in coronal structures to be easily discerned, and observations with one instrument can be used to derive these DEMs and these can then be used to predict what is observable with some other instrument. Continue reading ‘Differential Emission Measure [Eqn]’ »

Line Emission [EotW]

Spectral lines are a ubiquitous feature of astronomical data. This week, we explore the special case of optically thin emission from low-density and high-temperature plasma, and consider the component factors that determine the line intensity. Continue reading ‘Line Emission [EotW]’ »

[ArXiv] Pareto Distribution

Astronomy is ruled by Gaussian distribution with a Poisson distribution duchy. From time to time, ranks are awarded to other distributions without their own territories to be governed independently. Among these distributions, Pareto deserves a high rank. There is a preprint of this week on the Pareto distribution: Continue reading ‘[ArXiv] Pareto Distribution’ »

Dance of the Errors

One of the big problems that has come up in recent years is in how to represent the uncertainty in certain estimates. Astronomers usually present errors as +-stddev on the quantities of interest, but that presupposes that the errors are uncorrelated. But suppose you are estimating a multi-dimensional set of parameters that may have large correlations amongst themselves? One such case is that of Differential Emission Measures (DEM), where the “quantity of emission” from a plasma (loosely, how much stuff there is available to emit — it is the product of the volume and the densities of electrons and H) is estimated for different temperatures. See the plots at the PoA DEM tutorial for examples of how we are currently trying to visualize the error bars. Another example is the correlated systematic uncertainties in effective areas (Drake et al., 2005, Chandra Cal Workshop). This is not dissimilar to the problem of determining the significance of a “feature” in an image (Connors, A. & van Dyk, D.A., 2007, SCMA IV). Continue reading ‘Dance of the Errors’ »

~ Avalanche(a,b)

Avalanches are a common process, occuring anywhere that a system can store stress temporarily without “snapping”. It can happen on sand dunes and solar flares as easily as on the snow bound Alps.

Melatos, Peralta, & Wyithe (arXiv:0710.1021) have a nice summary of avalanche processes in the context of pulsar glitches. Their primary purpose is to show that the glitches are indeed consistent with an avalanche, and along the way they give a highly readable description of what an avalanche is and what it entails. Briefly, avalanches result in event parameters that are distributed in scale invariant fashion (read: power laws) with exponential waiting time distributions (i.e., Poisson).

Hence the title of this post: the “Avalanche distribution” (indulge me! I’m using stats notation to bury complications!) can be thought to have two parameters, both describing the indices of power-law distributions that control the event sizes, a, and the event durations, b, and where the event separations are distributed as an exponential decay. Is there a canned statistical distribution that describes all this already? (In our work modeling stellar flares, we assumed that b=0 and found that a>2 a<-2, which has all sorts of nice consequences for coronal heating processes.)

Betraying your heritage

[arXiv:0709.3093v1] Short Timescale Coronal Variability in Capella (Kashyap & Posson-Brown)

We recently submitted that paper to AJ, and rather ironically, I did the analysis during the same time frame as this discussion was going on, about how astronomers cannot rely on repeating observations. Ironic because the result reported there hinges on the existence of small, but persistent signal that is found in repeated observations of the same source. Doubly ironic in fact, in that just as we were backing and forthing about cultural differences I seemed to have gone and done something completely contrary to my heritage! Continue reading ‘Betraying your heritage’ »

Spurious Sources

[arXiv:0709.2358] Cleaning the USNO-B Catalog through automatic detection of optical artifacts, by Barron et al.

Statistically speaking, “false sources” are generally in the domain of Type II Type I errors, defined by the probability of detecting a signal where there is none. But what if there is a clear signal, but it is not real? Continue reading ‘Spurious Sources’ »

[ArXiv] NGC 6397 Deep ACS Imaging, Aug. 29, 2007

From arxiv/astro-ph:0708.4030v1
Deep ACS Imaging in the Globular Cluster NGC 6397: The Cluster Color Magnitude Diagram and Luminosity Function by H.B. Richer et.al

This paper presented an observational study of a globular cluster, named NGC 6397, enhanced and more informative compared to previous observations in a sense that 1) a truncation in the white dwarf cooling sequence occurs at 28 magnitude, 2) the cluster main sequence seems to terminate approximately at the hydrogen-burning limit predicted by two independent stellar evolution models, and 3) luminosity functions (LFs) or mass functions (MFs) are well defined. Nothing statistical, but the idea of defining color magnitude diagrams (CMDs) and LFs described in the paper, will assist developing suitable statistics on CMD and LF fitting problems in addition to the improved measurements (ACS imaging) of stars in NGC 6397.
Continue reading ‘[ArXiv] NGC 6397 Deep ACS Imaging, Aug. 29, 2007’ »

[ArXiv] Numerical CMD analysis, Aug. 28th, 2007

From arxiv/astro-ph:0708.3758v1
Numerical Color-Magnitude Diagram Analysis of SDSS Data and Application to the New Milky Way Satellites by J. T. A. de Jong et. al.

The authors applied MATCH (Dolphin, 2002[1] -note that the year is corrected) to M13, M15, M92, NGC2419, NGC6229, and Pal14 (well known globular clusters), and BooI, BooII, CvnI, CVnII, Com, Her, LeoIV, LeoT, Segu1, UMaI, UMaII and Wil1 (newly discovered Milky Way satellites) from Sloan Digital Sky Survey (SDSS) to fit Color Magnitude diagrams (CMDs) of these stellar clusters and find the properties of these satellites.
Continue reading ‘[ArXiv] Numerical CMD analysis, Aug. 28th, 2007’ »

  1. Numerical methods of star formation history measurement and applications to seven dwarf spheroidals,Dolphin (2002), MNRAS, 332, p. 91[]

[ArXiv] Isochrone database, Aug. 20, 2007

From arxiv/astro-ph:0708.1204v3
An Isochrone Database and a Rapid Model for Stellar Population Synthesis by Li and Han

This paper emphasize the binary population: CMD fitting with the binary population synthetic model outperformed to the single population model. They used Hurley code (Hurley, Tout, and Pols (2002). Evolution of binary stars and the effect of tides on binary populations, MNRAS, 329(4), p.897-928). They mentioned that two color-color grids can disentangle the age-metallicity degeneracy via binary stellar populations. They fitted their isochrone database to M67 and NGC 1868 with the gT-grid and concluded that the database of binary stellar populations fitted the color magnitude diagrams better.
Continue reading ‘[ArXiv] Isochrone database, Aug. 20, 2007’ »

Summarizing Coronal Spectra

Hyunsook and I have preliminary findings (work done with the help of the X-Atlas group) on the efficacy of using spectral proxies to classify low-mass coronal sources, put up as a poster at the XGratings workshop. The workshop has a “poster haiku” session, where one may summarize a poster in a single transparency and speak on it for a couple of minutes. I cannot count syllables, so I wrote a limerick instead: Continue reading ‘Summarizing Coronal Spectra’ »