Fractal analysis of noise buried time series signals with applications to exoplanet spectroscopy and bio-data

George Tremberger Jr.; T. Holden; E. Cheung; A. Flamholz; P. Marchese; H. Yao; P. Schneider; D. H. Lieberman; T. D. Cheung

doi:10.1117/12.732987

19 September 2007 Fractal analysis of noise buried time series signals with applications to exoplanet spectroscopy and bio-data

George Tremberger Jr., T. Holden, E. Cheung, A. Flamholz, P. Marchese, H. Yao, P. Schneider, D. H. Lieberman, T. D. Cheung

Author Affiliations +

Proceedings Volume 6693, Techniques and Instrumentation for Detection of Exoplanets III; 66931D (2007) https://doi.org/10.1117/12.732987
Event: Optical Engineering + Applications, 2007, San Diego, California, United States

Abstract

The shape of an exoplanet lightcurve is usually obtained by averaging the noise over multiple datasets. Fractal analysis has been demonstrated to be an effective tool for the detection of exoplanet transits using lightcurves summed over all wavelengths sensitive to the detector (G. Tremberger, Jr et. al, 2006 Proc SPIE Vol 6265). The detection of spectral features would depend on the extent to which the signal was buried in the noise. Different noise sources would have different fractal characteristics. Also, the signal strength could be discontinuous in time depending on the exoplanet's local atmospheric environment. Such a discontinuity is unlikely to be detected with time integrated data. The lightcurve noise and shape information were characterized with fractal dimension analysis of a noise buried time series signal. Computer simulation revealed that when the noise is three times that of the signal, the fractal algorithm could detect the signal at about the 87% confidence level. Application to noise buried time series datasets (HD 209458b lightcurve, HD149026b lightcurve) detected discontinuities consistent with the results obtained by averaging datasets. Extension to individual wavelength lightcurves would establish a detection limit for the existence of spectral features at wavelengths important for exoplanet study. Other applications such as pre-implantation genetic screening spectroscopy and spatially varied aneuploidy bio-data could use the same analysis principle as well.

Citation Download Citation

George Tremberger Jr., T. Holden, E. Cheung, A. Flamholz, P. Marchese, H. Yao, P. Schneider, D. H. Lieberman, and T. D. Cheung "Fractal analysis of noise buried time series signals with applications to exoplanet spectroscopy and bio-data", Proc. SPIE 6693, Techniques and Instrumentation for Detection of Exoplanets III, 66931D (19 September 2007); https://doi.org/10.1117/12.732987

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Fractal analysis

Interference (communication)

Exoplanets

Signal detection

Stars

Spectroscopy

Calibration

Show All Keywords

Keywords/Phrases

Search In:

Publication Years