THE LYOT PROJECT DIRECT IMAGING SURVEY OF SUBSTELLAR COMPANIONS: STATISTICAL ANALYSIS AND INFORMATION FROM NONDETECTIONS

AbstractWe present preliminary results from two parallel programs to search for new substellar companions to nearby, young M-stars and to characterize the atmospheres of known planetary mass and temperature substellar companions. For the M-star survey, we are analyzing high angular resolution archival data on systems within 15pc, complementing a subset with well-determined young ages based on measurements of several age indicators. The results include stellar and substellar companion candidates, which we are currently pursuing with follow-up second epoch images. The characterization component of the project involves using LBT LMIRCam and MMT ARIES direct imaging and spectroscopy data to investigate the atmospheres of known young substellar companions with masses overlapping the planetary regime. These atmospheric studies will represent an analogous comparison to the atmospheres of young imaged planets, and provide a means to fundamentally test evolutionary models, enhancing our understanding of the overall substellar population.

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Quick-MESS: A fast statistical tool for Exoplanet Imaging Surveys

Proceedings of the International Astronomical Union ◽

10.1017/s1743921313007710 ◽

2013 ◽

Vol 8 (S299) ◽

pp. 28-29

Author(s):

Mariangela Bonavita ◽

Ernst De Mooij ◽

Ray Jayawardhana ◽

Raffaele Gratton

Keyword(s):

Monte Carlo ◽

Statistical Analysis ◽

Monte Carlo Simulations ◽

Bayesian Approach ◽

Direct Imaging ◽

Statistical Tool ◽

Novel Approach

AbstractSeveral tools have been developed for the analysis of the results of direct imaging exoplanet surveys, mostly using a combination of Monte-Carlo simulations or a Bayesian approach. Here we present a novel approach to the statistical analysis of Direct Imaging surveys, called Quick-MESS, which allows for a much faster and flexible analysis.

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Direct imaging search for substellar companions around neutron stars

Proceedings of the International Astronomical Union ◽

10.1017/s1743921306009045 ◽

2005 ◽

Vol 1 (C200) ◽

pp. 35-40

Author(s):

B. Posselt ◽

R. Neuhäuser ◽

F. Haberl

Keyword(s):

Neutron Stars ◽

Direct Imaging ◽

Substellar Companions

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Direct imaging and new technologies to search for substellar companions around MGs cool dwarfs

EPJ Web of Conferences ◽

10.1051/epjconf/20111603007 ◽

2011 ◽

Vol 16 ◽

pp. 03007

Author(s):

M.C. Gálvez-Ortiz ◽

J.R.A. Clarke ◽

D.J. Pinfield ◽

S.L. Folkes ◽

J.S. Jenkins ◽

...

Keyword(s):

New Technologies ◽

Direct Imaging ◽

Substellar Companions ◽

Cool Dwarfs

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Direct Imaging and Spectroscopy of Substellar Companions Next to Young Nearby Stars in TWA

The Origin of Stars and Planets: The VLT View - ESO ASTROPHYSICS SYMPOSIA ◽

10.1007/10856518_50 ◽

2006 ◽

pp. 383-390 ◽

Cited By ~ 1

Author(s):

Ralph Neuhäuser ◽

Eike Guenther ◽

Wolfgang Brandner ◽

Nuria Húelamo ◽

Thomas Ott ◽

...

Keyword(s):

Direct Imaging ◽

Nearby Stars ◽

Substellar Companions ◽

Imaging And Spectroscopy

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Statistical analysis of classification

Symposium - International Astronomical Union ◽

10.1017/s0074180900053420 ◽

1966 ◽

Vol 24 ◽

pp. 188-189

Author(s):

T. J. Deeming

Keyword(s):

Multivariate Analysis ◽

Statistical Analysis ◽

Classification Scheme ◽

Analytical Procedure ◽

Narrow Band ◽

Scientific Research ◽

Maximum Amount ◽

Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

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Quantitative parallel EELS spectrum imaging developed as a new tool in AEM

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s042482010013064x ◽

1992 ◽

Vol 50 (2) ◽

pp. 1202-1203

Author(s):

Gianluigi Botton ◽

Gilles L'espérance

Keyword(s):

Statistical Analysis ◽

Spatial Resolution ◽

Personal Computer ◽

Systematic Study ◽

Present Author ◽

Chemical Elements ◽

Detection Limits ◽

Research Groups ◽

Quantitative Performance ◽

Spectrum Imaging

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.

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