טכניון מכון טכנולוגי לישראל
הטכניון מכון טכנולוגי לישראל - בית הספר ללימודי מוסמכים  
M.Sc Thesis
M.Sc StudentYaron Shulamy
SubjectAdvanced Methods for Improvement of Stellar Intensity
Interferometry
DepartmentDepartment of Physics
Supervisor Dr. Ribak Erez
Full Thesis text - in Hebrew Full thesis text - Hebrew Version


Abstract

One of the hottest topics in intensity interferometry is the question of the ability to use this technology outside the Earth's atmosphere, i.e., with the help of satellites. This is because in space there is less scattering and light absorption than in the atmosphere, and that objects can be tracked for hours and days. These are only some of the reasons for the need to realize a complex system of this type. However, such a system adds some new problems that should be taken into account, one of which is the ability of saving optical information digitally. Another problem is transferring the information to a control center where it will be possible to perform the correlation between the intensity of the telescopes.

Another method for measuring the properties of astronomical objects is by an amplitude interferometer. The advantage of the intensity interferometer over the amplitude interferometer is that using the former we calculate the correlation between the intensity of the telescopes and not of the electromagnetic fields reaching the detector, as in the later. Thus, we can actually save the information on the satellite without the need to interfere the light directly between the two telescopes (as required in an amplitude interferometer).

During the period of development of the intensity interferometry, the signal processing technique of compressed sensing did not exist, and therefore a question arises whether the new approach can help in this case. The motivation behind the idea that this method can be very useful is that the physics behind the signals is known and that if we look at the problem in terms of signal processing the signal is indeed very sparse. The idea is that if we know how to characterize signals in terms of physical behavior, we can build a dictionary consisting of several typical signals with known properties which are used to represent the original signal.

In this current study, we tried using these methods in order to improve intensity intereformtry signal to noise ratio and compress the signal.