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Earthshine blog

"Earthshine blog"

A blog about a telescopic system at the Mauna Loa Observatory on Hawaii to determine terrestrial albedo by earthshine observations. Feasible thanks to sheer determination.

List of possible student projects

Student projects Posted on Mar 22, 2013 09:51

We have often come across good ideas for student projects. Here is a start of a collection of projects – just links, but text can be added to explain more.

How do meteorological conditions determine seeing at the telescope?

Was the bias pattern constant?

Understanding the PSF:

Albedo maps and their use in modelling observations:

Atmospheric turbulence studied via Moon images:

Colour of earthshine – Danjons work:

Image analysis methods – Laplacian method:

Modelling Earth:

Understanding the linear slopes

Exploring the PSF Posted on Mar 22, 2013 09:30

In this post we saw that the difference between B and V (magnitude) images could have the shape of a linear slope on the DS and plateau on the BS. We are trying to recreate that using synthetic models. It is surprisingly difficult!

Using V and V images we saw that differences typically had the shape of level offsets – not slopes. In the B-V images we saw linear slopes on the BS. I thought the linear slopes originated in different PSFs in two filters – different alfa-parameters, for instance.

Well, taking a synthetic image and convolving it twice with two slightly different PSFs and converting to magnitudes and subtracting gives this:

Upper panel shows the ideal image we are using – BS to the right and the rest is DS. Bottom panel shows the difference between the image convolved with alfa=1.73 and alfa=1.72*1.02. DS is columns left of 360 – there is no linear slope. There are plenty of features on the DS above, but none ‘slope away linearly from the BS’.

A straight line in a lin-log plot corresponds to an exponential term. The difference between two Gaussians of different width is probably another Gaussian. Are we learning that the real PSF has a Gaussian term in it that varies between filters? Since V-V images did not show this behaviour the Gaussian is not manifested by the inevitable slight image alignment problems. Our model PSF is an empirical core with power-law extensions – and the above experiments show that such PSFs do not yield linear-slope differences.

Perhaps we could study the real PSF by studying difference images in a thorough way? Student project!