Basic Principles of X-ray Source Detection Or Who Stole All Our Photons?.....

1. Basic Principles of X-ray Source Detection Or Who Stole All Our Photons?.....

2. Overview • Optical sources • Comparison to X-ray images • Why so few X-rays? • What can we do about it? • The theory of low count levels • Application to X-ray sources • Calculating flux and luminosity.

3. Optical Sources

4. X-ray Images

5. Why so few X-rays? - Mirrors & PSF • Mirrors • Made from Zerodur • Coated with Iridium • 100% reflectivity at 0.1keV • 10% reflectivity at 10keV • 10m focal length • Optical/UV filters remove 20% of low energy X-rays. • PSF • Angular resolution of 0.5” on axis • PSF increases rapidly off axis • Also a function of energy

6. Why so few X-rays? - Background 99.7% of detections are or could be background – that is of a non cosmic origin. • Distant Sources • Solar wind – 11 year cycle • Solar flares – short time scale • Radiation belt • (Cosmic rays) • Local Sources • Flaring pixels • Detector radiation – gold, aluminium, silicon • Trailing (only for bright sources) • Types of Particle • Mostly protons – magnets deflect those with lowest momentum • Heavy ions • Neutrons • Gamma rays • X-rays In a normal image, these would completely swamp the sources, but in X-ray astronomy we have one major advantage………………

7. Why so few X-rays? – CCD’s Position - x, y - obvious Can obtain x, y, E, t and “grade” • Energy • 1 electron per 3.7eV • Typically ~1000 electrons • Read noise ~ 2 electrons • E/ E =~ 50 • Energy is summed over the surrounding pixels which share the signal. • Time of arrival • Low count rate • 3.2 sec frame time • 0.04 sec readout time • Fine for most sources (no pileup unless very bright) • Removes flickering pixels • Grade • Triggering one pixel will effect those around it in a way that depends on the type of particle and its incident angle. • Therefore looking at the 3x3 region around a peak can distinguish between true X-rays and background events.

8. Why so few X-rays? – Grades and Filters The 3x3 region around a peak can predict the cause of the event. If all pixels with a value above a given threshold are included, the resulting shape determines the grade. Rejecting certain grades greatly increases the signal to noise ratio. Rejected grades > Accepted grades > • Probable background events are removed by filtering for grade. • Events received during times of particularly high background are removed. • Events with E<0.5keV or E>8keV are removed.

9. Source Detection • Detect using Wavelets • Apertures and annulus defined by wavelet • Calculate counts and background • Find errors

10. Calculating Flux and Luminosity • Select all significant sources • Find source counts and error • Assume a source spectrum • Convert counts to ergs using assumed spectrum • Create Exposure Map allowing for Quantum Efficiency and source spectrum • Convert ergs to ergs/cm2/sec using exposure map • Convert to luminosity using distance (requires optical astronomers!) • Finished!