1.1 : cos\cos Interferometer

1.1.0: A Universe with 1 Point Source

Let's start with a simplify universe. In this universe, there is only 1 source and 2 base stations:

A monochromatic point source that emits a radio wave with wavelength , frequency , and magnitude . By the time the radio wave reaches a point on Earth, we can express it as a cosine function of time:

Figure

Where is varying random phase with a uniform distribution:

And has a coherence Time , meaning for :

and , both stations' antennas have perfect Antenna Gain, meaning they can received signal from all directions with no phase distortion nor magnitude attenuation. Assuming the antennas are capable of observing just a single frequency.


Now the source sits somewhere in the sky far away from the stations, and the two antennas pointing directly up are receiving wave signals from source , and the signals are passed to the correlator for processing, as shown in the figure below.

Figure

Suppose the radio signal arrives at station is:

then signal at station , travels an extra length of compared to , which infer a time delay , so:

We assume that , the coherence time, meaning the phase does not change after the extra time traveled, , to reach :

so we can simply to:




1.1.1: Correlator Output

Next, signal and are passed to correlator to calculate the output :


Which is basically an autocorrelation function for , and , is referred as Integration Time:

Let's break down:

Step 1: Multiplication:

Step 2: Average over integration time :

(The first integral term = 0 is from Time average of cosine for fast varying random phase )

Also notice that the time instant and integration time are basically irrelevant compare to the geometric delay , so we often time write the correlator as function of geometric delay :




1.1.2: Time delay \leftrightarrow geometric vectors

Next we want to replace the time delay with geometric variables of the stations and source.


We introduce 2 new vectors to the picture:

  • : a unit vector that points at source from the stations, because source is far far away, we can treat the wave paths to be parallel for station and

  • : the baseline vector that points from station to station

See the figure below:

Figure

In the above figure, we can solve for :

Now we can express with :

So the correlator output can be rewritten and simplified as:

Also note a useful fact:




1.1.3: Put Geometric Vectors on Cartesian Grid

Let's further simplify the formula, let's see how to do it:

We put the stations and source on a cartesian (x,y) grid, with as unit vector:

Figure

From the figure above, we can rework :

Next, we introduce a new variable :

is a scalar that lies on the same axis, it is just but scaled by .

Basically, is the baseline length in units of wavelength.

So with , we can simplify further:

Next let's see how to simplify . Let's focus on the unit vectors and :

Figure

From the figure above, we can express as:

So back to :




1.1.4: Putting It All Together

Finally we plug this result back to the correlator output function :

In the above equation, you see that function depends on or & . And if you treat as a constant which it is for monochromatic radio wave, we can conclude that:

is determined by baseline, i.e., locations of the stations.

is determined by source, i.e., location of the source.

In short, when people say fringe function, it is a function of geometric delay , which is equivalent to function of baseline and angle .




1.1.5: cos\cos Fringe

For a single value, we can plot out the function for , then you will see a sinusoidal pattern. We refer them as Fringe Pattern as shown in the figure below.

In the interactive figure below, feel free to drag around the blue triangle source and the brown circle , and observe that:

  • Varying changes the fringe pattern function. The smaller the values, the lower the frequency in the fringe pattern.

  • Varying changes value of .

Figure :


Fringe for monochromatic Wave: draggable




1.1.6: Angular Resolution

Now we can show you that to distinguish 2 point sources, the minimum angular separation between them is:

is also referred as the angular resolution.

To prove the above equation, let's first look at the interactive figure below that shows fringe patterns for 2 sources ( and ) that have same brightness .

(Feel free to drag around the triangles for source & , and observe their respective correlator outputs and the angular distance between them.)

Figure :


Angular Resolution demonstration with 2 sources: draggable

Suppose the angular distance between and peak (bright fringe) is:

Looking at the figure above, notice that:

Meaning that the angular distance between and bright fringe is minimum compare to other bright fringe pairs.


To be able to distinguish the 2 sources, it is required for those 2 sources to be at least angular distance apart because if the angular distance between the two sources is anything smaller, then the two sources will look like a single bright spot.


Now let's we solve for :

There we have it, the minimum angular separation (angular resolution) is: