# Why are radio telescopes so large?

Hi,
take a Hubble telescope, it has primary mirror 2.4 meters tall. Now take this:

I mean the thing above which is Arecibo radio telescope has diameter of 305 meters. Both things are for the same thing, to observe the Universe.

So the answer lies in the name. Arecibo is a RADIO telescope which means that it works on quite different wavelengths, actually magnitudes bigger wavelengths since the wavelength of for example visible light for Hubble is 550 nanometers which is quite small while radio waves can have wavelength of hundreds of meters.

This is essentially the key. If you want to see clear image in light (that we can see) you need just a small telescope. Both work the same way though from what I understand you need larger area to collect all of those waves and reflect them on the focus which is above. The equation shows it clear:

θ=1.22*λ/D

Where θ shows how close two points can be to each other without you being able to distinquish them. λ is the wavelength of the light and D is the diameter of your telescope. So you will see best when wavelength is small and diameter is huge since this will lower the angle that you are not able to distinquish. Of course that there is huge difference when you insert meters instead of nanometers so you must compensate it with the diameter of the telescope.[1]

If you want to have a clear image in radio waves, well you have to build Arecibo.. really? Isn’t there another option?

Yes there is! You can build a lot of small radio telescope that would alone be very weak but if you take lot of them you can have a Diameter of kilometers. Such a device is called interferometer which means that is “operates by myltiplying the data from each pair of telescopes together to form interference patterns”.

There is more of them and this one is ALMA observatory.

So those are huge fields or rows of smaller (even 60 meter) discs that collect data. They have to be extremely accurate what is time concerned (atomic clocks).

Dragallur

[1]1.22 is just an empirical value.