Hydrogen Line project with 1.4m geodesic dish

[ZiHao]

The 21cm hydrogen line is a spectral line produced by atomic hydrogen. Due to the abundance of hydrogen atoms and the nature of radio waves to penetrate dust clouds in our galaxy, we can study the milky way by observing the doppler-shifted spectral line.

Construction of the geodesic parabolic dish developed by JA6XKQ and 1.42Ghz cantenna for the hydrogen line project:

For the introduction of the design, please read this article [1] written by JA6XKQ. For those who are interested in the details of the derivation and surface accuracy of the structure, you can refer to [2]. Another important thing is the supporting structures such as adding supporting rods behind the dish or additional inner meshes to prevent the heavy feed from deforming the structure. See [3] and [4].
This is a 1.4m f/D 0.345 dish. Three L shape aluminium bar as supporting structure is attached to a stainless steel bowl. The same material is used for the feed supports and the reflector is made from galvanized wire mesh. This picture is taken months ago and the mesh is now covered with rust, I plan to apply rust converter to the surface and spray paint at the end. An alternative is to use stainless steel mesh at the beginning, but the cost will be high. If you are interested, please refer to the excel sheet at [5] to obtain the specific dimensions.

Cantenna's diameter: 14.5cm, length: 18cm, probe's distance from the back (1/3 of the length): 6cm, probe's length: I started with 0.25*λ, and it is trimmed until a good SWR is obtained with a NanoVNA. These dimensions are based off from the design from Figure 3 at [6] If you want to determine the diameter based on your desired edge taper, you can see page 3 at [7]. A N type female connector is used to attach the copper probe. No soldering needed as there's a hole where the probe can be slid in tightly. To compute the dimensions of the cantenna and a choke ring, refer to the excel sheet from SETI League at [8].

Special thanks to my dad's friend for providing material for the dish and fabricating the feedhorn and its bracket.

Observations and results:

Spectra below are along the plane of our galaxy from galactic longitude 0 to 360 degrees at latitude 0 degrees and they are the combination of multiple gaussian curves and the corresponding radial velocity of the individual peaks are then used to construct the structure and rotation curve of the milky way. Radial velocities are corrected to the local standard of rest (LSR). Individual spectrum is multiplied by a constant obtained from the calibration using the S7 region's peak brightness temperature value from the LAB survey, at [9].

Observations for the hydrogen line map from declination -60 to 60 degrees are done by pointing the dish at a specific declination and different regions of the sky will be captured thanks to Earth's rotation. This is a technique known as drift scan. Hydrogen column density is calculated by integrating the area under the spectrum from radial velocity -150km/s to 150km/s and times 1.82x10^18, given at [10].

Milky way structure. Data seemed to only match with the Perseus and Carina-Sagittarius arms. Most of the points are in between the Perseus and Norma arm, this is probably due to unresolved peaks in the spectrum from smaller radio telescope. Parameters for the spirals arm plot can be found on page 7 at [11].

Lastly the rotation curve fitted with a logarithmic curve. The rotation speed is obtained by choosing the most red-shifted and blue-shifted radial velocities in the spectra obtained from Quadrant I and IV respectively. The rotation speed are lower compared to the published data from Clemens (1985) attached, because the most red and blue-shifted peaks are often weak and difficult to detect with good SNR and hence the chosen peaks will be not be the maximum and minimum radial velocities. But the general trend can be seen clearly in the graph, a flat curve as you go further away from the center of milky way, suggesting that something is giving them extra speed and most of the mass might not be concentrated in the center. Thanks for reading!

References:
[1]http://www.terra.dti.ne.jp/~takeyasu/Geodesic_Parabola_Antenna_2_1.pdf
[2]https://f4buc.pagesperso-orange.fr/parabole_geodesique2.htm
[3]http://www.terra.dti.ne.jp/~takeyasu/PhotoGallery.html#new_photo
[4]https://www.youtube.com/watch?v=od2SEhq8DR4&t=11s
[5]http://www.terra.dti.ne.jp/~takeyasu/
[6]https://www.semanticscholar.org/paper/A-compact-radio-telescope-for-the-21cm-line%3B-za-21-Saje-Vidmar/e5baaf7450e0aea72e7926e1bdd75d3175f23424
[7]http://www.w1ghz.org/antbook/chap6-3.pdf
[8]http://www.setileague.org/hardware/feedchok.htm
[9]https://www.astro.uni-bonn.de/hisurvey/euhou/LABprofile/
[10]https://www.cv.nrao.edu/~sransom/web/Ch7.html
[11]https://iopscience.iop.org/article/10.1086/501516/pdf

Edited January 19, 2023 by ZiHao

[davew]

That looks a really nice build. Very interesting results too.

Thanks for posting,

Dave.

[Victor Boesen]

Excellent work ZiHao!!! Good to see you're still working on H-line stuff I haven't had much time to do the same lately, but hopefully I will in the future. I'm currently working on refurbishing the ground station at my university. If I succeed I should have a 3m dish to do radio astronomy with

Victor

[ZiHao]

4 hours ago, Victor Boesen said:

Excellent work ZiHao!!! Good to see you're still working on H-line stuff I haven't had much time to do the same lately, but hopefully I will in the future. I'm currently working on refurbishing the ground station at my university. If I succeed I should have a 3m dish to do radio astronomy with

Victor

Thank you! Not too sure when I can start a new radio astronomy project since I have started university recently. Little space to work with in campus, but I will try. All the best with the refurbishment, and I look forward to the 3m dish. It will open up many opportunities for challenging radio astronomy projects!

[Alex_Fla]

Outstanding Work !  Congrats.    Alex Winter Springs Fla

[athornett]

This is just what I need to help me with my hydrogen line radio observations - particularly your atlas of plots at various galactic longitudes gives me something to compare = I am on holiday at present but as soon as I get home I will compare I have so far with yours.

do you know of any more comprehensive resource that shows expected plots and graphs?
also what software you use to collect data, process and plot it and then superimpose your results on galactic structure?
I am currently using ezRA suite from Ted a line in SARA.

thanks for posting!
Andy

[ZiHao]

18 hours ago, athornett said:

This is just what I need to help me with my hydrogen line radio observations - particularly your atlas of plots at various galactic longitudes gives me something to compare = I am on holiday at present but as soon as I get home I will compare I have so far with yours.

do you know of any more comprehensive resource that shows expected plots and graphs?
also what software you use to collect data, process and plot it and then superimpose your results on galactic structure?
I am currently using ezRA suite from Ted a line in SARA.

thanks for posting!
Andy

I am writing my own python code for data acquisition, calibration and representation. Plotting the data is done with matplotlib and some formulae that you can refer to here. I will try to take a look at my code again as it doesn't look very user friendly for now, and if I have the time, I will publish it on github.

 

[athornett]

Hi Zihao,

Thanks for getting back to me.

I am VERY excited = I have compared my data plots at different galactic longitudes with yours and there is close match for areas I have so far been able to study. Wow!

I would love to go the next step and create the same plots as you have done labelled "Milky Way Structure" - I don't mind if your scripts are not perfect! Any chance you could PM me with info on how to do it? Perhaps I could help polish them up a bit, if that would help in any way?

By the way, although I live in England, my wife is from Penang - so its definitely a small world and wonderful to have folks from Malaysia on this forum!! I am an associate member of the Astronomical Society of Penang, who are a wonderful group doing marvellous outreach.

Andy

[ZiHao]

On 11/10/2023 at 05:19, athornett said:

Hi Zihao,

Thanks for getting back to me.

I am VERY excited = I have compared my data plots at different galactic longitudes with yours and there is close match for areas I have so far been able to study. Wow!

I would love to go the next step and create the same plots as you have done labelled "Milky Way Structure" - I don't mind if your scripts are not perfect! Any chance you could PM me with info on how to do it? Perhaps I could help polish them up a bit, if that would help in any way?

By the way, although I live in England, my wife is from Penang - so its definitely a small world and wonderful to have folks from Malaysia on this forum!! I am an associate member of the Astronomical Society of Penang, who are a wonderful group doing marvellous outreach.

Andy

What a coincidence! I am not a member of the society but I was a participant of their astrophotography competition in 2019.

The first step would be fitting multiple gaussians to the spectrum, you can do this in either the Origin software (https://www.youtube.com/watch?v=WX_X3XlbKRA) or the python script below where you need to manually enter the guesses for the parameters of the gaussians.

import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
import scipy as sp
import scipy.signal

def gaussian(x, A, x0, sig):
    return A*np.exp(-(x-x0)**2/(2*sig**2))

def multi_gaussian(x,*pars):
    total = 0
    offset = pars[-1]
    i = 0
    for j in range(int(len(guess)/3):
        single_g = gaussian(x, pars[i+j], pars[i+j+1], pars[i+j+2])
        total+=single_g
        i+=2
    return total + offset

para = []
data = #yaxis data
data = sp.signal.medfilt(data,5)
velocity = #xaxis data
guess = #guesses for parameters
    
popt, pcov = curve_fit(multi_gaussian, velocity, data, guess)

j = 0
for k in range(int(len(guess)/3)):
    para.append(popt[j+k+1])
#save the parameters

plt.plot(velocity, data, 'b')
plt.plot(velocity, multi_gaussian(velocity, *popt), 'r')
plt.show()

 

The second step is to obtain the x-y coordinates in the milky way structure using the mean value (which refers to the radial velocity) from the parameters.

Vo = 220
Ro = 8.5
x = []
y = []

l = #longitude in radians
para = #parameters

for a in range(len(para)):
    Vr = para[a]
    Rs = Ro*Vo*np.sin(l)/(Vo*np.sin(l)+Vr)

    if Rs**2-Ro**2*(np.sin(l))**2 < 0:
        continue
        
    rpos = np.sqrt(Rs**2-Ro**2*(np.sin(l))**2) + Ro*np.cos(l)
    rneg = -np.sqrt(Rs**2-Ro**2*(np.sin(l))**2) + Ro*np.cos(l)

    if rpos > 0 and rneg > 0:
        continue

    elif rpos < 0:
        continue

    else:
        x.append(rpos*np.sin(l))
        y.append(-rpos*np.cos(l) + Ro)

 

The final step is superimposing our data on top of the galactic structure plotted using the parameters provided from [11].

ro = [3.48, 3.48, 4.90, 4.90]
theta_o = [1.57, 4.71, 4.09, 0.95]
k = [4.25, 4.25, 4.89, 4.89]

for i in range(4):
    theta = np.linspace(theta_o[i], theta_o[i] + 2*np.pi, num = 500)
    r = ro[i]*np.exp((theta - theta_o[i])/k[i])
    xm = r*np.cos(theta)
    ym = r*np.sin(theta)
    wains = plt.plot(xm, ym, 'k')
plt.show()

 

Edited October 13, 2023 by ZiHao

[athornett]

That is marvellous! Thanks