Astronomical Data Collection and Processing of LLPV’s in GGC’s at the BGSU Observatory J Leon Wilde TAA Seminar, UT, February 2nd, 2007

Intro Before observing… BGSU’s telescope CCD Imaging Typical observing night Image processing My Thesis Work

Before observing… What to look at Where to look from What instruments? –0.5 m Reflecting telescope –CCD imager

The telescope Incoming starlight Secondary Mirror Primary Mirror Focus on optics

The CCD Imager “Charge Coupled Device” Si diodes KAF-1000E –Specs.pdf for KAF-1001E

Why use CCDs? High QE High Linearity Large dynamic range Uniform response Low Noise Digital

Our CCD’s QE Blue – KAF-1001E Black – KAF-1401E

CCD Basic Design Our CCD –24x24 micron pixels –1024x1024 array

Gate Structure/Function Voltage push Sends data to onboard amplifier and A/D converter Our CCD –Two phase push –Charge transfer efficiency =

CCD illumination Frontside –Photons pass through phasing gates –QE lower than Bs Backside –Etched back –High QE –Hard to make, thus... –More expensive Our CCD –Frontside

CCD Drawbacks Noise! –Dark current –A/D conversion –CCD flaws –Worked out during processing Expensive! –Delicate manufacturing process –Better science means higher standards

Dark Current Thermal activity on CCD chip

CCD Linearity Pixel value (ADU’s) Integration time (seconds) SBIG ST8 Linearity Test

CCD Coatings CCDs naturally insensitive to blue Coatings used –Coronene & Lumogen phosphors –Lumogen better of the two –Lumogen commercially used in highlighters Our CCD –“Blue Plus Transparent Gate”

Blooming Our CCD –No anti-blooming gates –We’re careful!

Typical Night Arrive an hour before sunset Get equipment ready Take bias frames / flat field frames Observe! Take more bias / flat fields Send images to Dr. Layden’s computer Shut equipment down Go home!

Image Processing Correct the images –Optics aren’t perfect (dust donuts, vignetting) –CCDs aren’t perfect –Electronics aren’t perfect –Observers aren’t perfect “The problem exists between the chair and the computer.” “Garbage in, garbage out.” Get science from the data –Convert ‘relative’ values into ‘real’ values Programs: –IDL and IRAF

Processing… Zero (Bias) frame –Remove floor value –Subtract combined image from data Dark frame –Remove dark current –Subtract combined image from data Flat field –Remove non-uniformities arising from: CCD flaws Optics flaws –Divide combined image from data

Processing… Photometry –RR Lyrae Program, getting star magnitudes versus time Pretty pictures –Combine images from different color filters

Pretty pictures Ring Galaxy AM from Hubble

My Thesis Work: Why Study LPV’s? Variability provides distance calibrations LPV’s are understudied For SIM (Space Interferometry Mission)

Background What are they?

Why look in GGC’s? Stars are of the same age Stars are at the same distance Stars are similar in composition

Detection Acquire data over long enough time Process images Image subtraction –DAOPHOT, ISIS

Getting the Data

NGC years of data [Fe/H] = -0.66

New GGC’s “New” to us! Selected from Harris Catalogue –min Dec –max V_hb –Small: Core concentration E(B-V) - Foreground reddening –Span of [Fe/H]

PROMPT Images!

PROMPT Back to Harris Catalogue Tracked down known LPV’s Corrected coordinates

PROMPT NGC 288

PROMPT NGC 1261

PROMPT NGC 1851

Next steps… Our data: –Finish processing / Photometery –Learn DAOPHOT –Perform DAOPHOT on recent data / NGC 6539 PROMPT data: –Determine best collection method

References People –Dr Andy Layden for his time, Dr John Laird for his books –Mike Smitka –Brian Pohl & Dr. Bruce Carney, UNC Chapel Hill Book –Steve B. Howell, 2000, Handbook of CCD Astronomy, Cambridge University Press Websites – – – – – PowerPoint file available online – Contacting me:

Thanks for your attention!