The experience of BEST
1 / 26

The experience of BEST - PowerPoint PPT Presentation

  • Uploaded on
  • Presentation posted in: General

The experience of BEST. Heike Rauer and the BEST Team Institut für Planetenforschung Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR) and Zentrum für Astronomie und Astrophysik Technische Universität Berlin +. The experience of BEST. Berlin Exoplanet Search Telescope System.

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.

Download Presentation

The experience of BEST

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript

The experience of BEST

Heike Rauer and the BEST Team

Institut für Planetenforschung

Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR)


Zentrum für Astronomie und Astrophysik

Technische Universität Berlin


The experience of BEST

Berlin Exoplanet Search Telescope System

Goals of BEST: - support for CoRoT

- detect large planets

- variable stars, additional science

Berlin Exoplanet Search Telescope



Aperture20 cm

Focal ratiof/2.7

InstrumentAP-10 CCD

Size2048 x 2048 pixels

Pixel size14 µm

Pixel scale5.5 arcsec/pixel

Field of view 3.1° x 3.1°

2001 - 2004 Thüringer Landessternwarte

Tautenburg (TLS), Germany

Since end 2004 Observatoire de Haute Provence (OHP), France




Observatorio Cerro Armazones, Chile

Instituto de Astronomía - Universidad Católica del Norte (UCN) in Antofagasta, Chile

Astronomisches Institut- Ruhr-Universität Bochum (RUB), Germany.



TelescopeBRC - 250

Aperture25 cm

Focal ratiof/5.0

InstrumentFLI IMG-1680 CCD

Size4096 x 4096 pixels

Pixel size9 µm

Pixel scale1.5 arcsec/pixel

Field of view 1.7° x 1.7°

Precision < 1% V=15-16

smaller FoV for BEST II is compensated by less stars influenced by crowding

Modes of operation

  • BEST I at TLS:

  • - obervations by observer at TLS

  • - data reduction at DLR

  • BEST I at OHP:

  • - observations via remote control from Berlin

  • - data reduction at DLR

  • BEST II at OCA

  • - „robotic“ observations (regular remote monitoring, manual interaction in case of alarm)

  • - basic calibration at OCA, full data reduction at DLR


  • The two critical factors for a transit search system are:

  • High duty cycle: full coverage of planetary orbits by observations.

  • 2. Large number of high quality lightcurves (e.g. rms < 1%).

Duty cycle

Need: High duty cycle, full coverage of planetary orbits by observations of sufficient quality.

BEST experience: duty cycle is the major limiting factor from central Europe (not a surprise  ). Next:

 place BEST II at OCA, Chile

 start building a network (NEST)

 participate to ASTEP


  • The two critical factors for a transit search system are:

  • High duty cycle, full coverage of planetary orbits by observations

  • 2. Large number of high quality lightcurves (e.g. rms < 1%)

  • - correction for detector effects (dark, bias, flats, hot/cold/defect pixels,…)

  • - correction of atmosphere (extinction, seeing, scientillation, …)

  • - accurate photometry (aperture/image subtraction/PSF fitting, crowding)

Detector effects

For example: a star moves across a hot pixel during the night due to imperfect guiding of the telescope….

  • Causes transit-like signal which has to be evaluated by comparison with the original data.

  • adds work-load on transit candidate evaluation

Detector effects

  • Correction for detector effects (dark, bias, flats, hot/cold/defect pixels,…)

  • Low-quality CCD: need to check transit events for detector effects, check position of the star on CCD

  • varying bias, dark, etc., adds to systematic noise residuals

  • Recommendation:

  •  buy good h/w

  •  adapt the observing sequence to calibration needs

Atmosphere effects

Correction of atmosphere (extinction, seeing, scintillation, …)

- Airmass correction is critical (no filter, large FOV)

 restriction in airmass, depending on site and target field

 adapt reduction method, e.g. work on sub-fields

 implement filter if possible

- Effect of seeing variations on crowding


Accurate photometry (aperture/image subtraction/PSF fitting, crowding)

- Crowding can be a major problem

 improve photometric method (image subtraction ok)

 match the pixel scale of h/w

B.E.S.T. Candidate 3



BEST Magnitude of host star12.1

Depth [%]2.5

Duration [h]3.0

Orbital period [d] 423.10/n

Number of detections2

BEST candidate 5

depth [%]1.0

duration [h]4.5

orbital period [d] > 10 ?

semi mayor axis[AU]?

number of detections1

target field No.8

host starM dwarf


V magnitude14.73

reference star

BEST 18.3‘ x 18.3‘

Crowded target fields lead to further reduction of the photometric accuracy

  • diluted signals

  • - neighboring stars are resolved

  • - but a neighbor contributes flux within the PSF or photometric aperture

  • b) unresolved stars

  • - neighboring stars are not resolved

  • c) a combination of a) and b)

  • - due to varying seeing the resolution of stars changes over the night

  •  a transit signal is weakend

  •  noise is added if the neighbor is variable

The photometric data reduction algorithm needs to be adopted.

Comparison of Photometric methods

* Source-Extractor, SExtractor (Bertin & Arnouts 1996)

Performs different kinds of aperture photometry

* Multi Object Multi Frame photometry, MOMF (Kjeldsen & Frandsen 1992) Combination of aperture and PSF photometry

* Image Subtraction, ISIS (Alard 2000)

Subtraction of a convolved reference frame from all frames.

 implementation of parallel approach in data pipeline (SExtractor, ISIS)

Karoff et al. 2005

SExtractor used in less crowded fields



Comparison of both methods for the COROT field

Data from 4 nights in spring 2005 obtained at OHP (COROT winter field)



Karoff et al. 2005

 a reduction routine able to deal with very crowded target fields is important

Performance of BEST I at OHP after evaluation of its first regular observing season at OHP in summer 2005.

BEST at OHP: Variable stars in the CoRoT center field

37 nights/142 hours observations from OHP in summer 2005.

  • Search for variable stars and eclipsing binaries:

  • 83 periodic variable stars identified: 76 new discoveries

  • 11 variable stars with period < 120 days known in GCVS, 8 confirmed variables, for 3 stars no variability found

  • 37 of the variables are eclipsing binaries

Karoff et al. 2006

Location of the variables in the center field

  • Periodic variable stars are detected over the whole magnitude range.

  • There are many more stars with high rms: real but non-periodic variables and distorted lightcurves

See Karoff et al. 2006

How complete is our search for variables from OHP?

Number of detected eclipsing binaries as a function of period

Eclipsing binaries in Hipparcos data

Eclipsing binaries in BEST observations

Söderhjelm & Dischler 2005

Karoff et al. 2006

The BEST survey is complete only up to 10 – 20% for

periods > 1 day.

But: we have indications that the detection algorithm for periodic variables is not perfect…

BEST – basic lessons from TLS and OHP

  • Strong points:

    • Simple robust system with good capability for long-term photometric surveys of a substantial number of stars

    • Well suited to catalog bright stars in the COROT fields

    • Demonstrated ability to reach the accuracy limit needed to discover Jupiter-sized planets

    • Cost efficient way to characterize stellar variability over long time periods

  • Weak point:

    • Transit detections limited by crowding and duty cycle (i.e. to few nights and/or to few stars)

  • Login