linan7788626 / Arc_Finding_CNN

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About the arc from 'test.fits' #2

Closed WentaoLuo closed 8 years ago

WentaoLuo commented 8 years ago

Is there a lens galaxy or the smoothed profile of the dark matter that creates the arcs?

linan7788626 commented 8 years ago

yes, the mass model of this lens is Non-singular Isothermal Ellipsoid, and the velocity dispersion is 320 km/s.

linan7788626 commented 8 years ago

@WentaoLuo try this http://www.syntevo.com/smartgit/ for using github under linux.

WentaoLuo commented 8 years ago

Thanks, I am fine with git now after one night training. It is basically SSH.

WentaoLuo commented 8 years ago

I am wondering if we could combine the arc image and simulated SDSS image together and form a more realistic one?

WentaoLuo commented 8 years ago

And I would then simulate more image, maybe 10000. And add others to th github.

linan7788626 commented 8 years ago

hold on, I have question, is sdssgal is the image with noise? you told me the noise should be white noise, but in this fits, it is not flat...

WentaoLuo commented 8 years ago

It is Gaussian. With a galaxy image in the center.

WentaoLuo commented 8 years ago

And also notice that the image size is not 120x120, instead. It is 119x119, or things like that due to the scaling from cosmos to SDSS by SHERA.

WentaoLuo commented 8 years ago

When do you think we add other people?

linan7788626 commented 8 years ago

How do you identify the parameters of the gaussian distribution? it should be related to the dark matter halo we are using. Also, please set the images size to be 128x128. it should be easier for both of us.

When do you think we add other people? At least, after producing one simulated images. Do you have any suggestion?

WentaoLuo commented 8 years ago

I will go to some details later. Sure, 128x128 sounds good.

linan7788626 commented 8 years ago

for the lensed images using toy models, you do not need to worry about the image of the lens galaxy, please just give noise and PSF.

WentaoLuo commented 8 years ago

The Gaussian noise is 58.7 in terms of variance (in unit of count^2, photon-electron counts), and the mean is 0.0.

WentaoLuo commented 8 years ago

I will update the sdss galaxy image soon with 128x128.

linan7788626 commented 8 years ago

the PSF you give me is not normalized......

WentaoLuo commented 8 years ago

You mean the size is not 128x128?

WentaoLuo commented 8 years ago

Or I could try combine those images together?

WentaoLuo commented 8 years ago

The convolution between them in IDL does not require the same size for both images.

linan7788626 commented 8 years ago

no, I mean the summary of all pixels is not one.

linan7788626 commented 8 years ago

the values of the pixels in the sdssgal.fits is too high, what is the units of the value of these pixels? screen shot 2015-12-08 at 1 46 07 pm

WentaoLuo commented 8 years ago

Both is galaxy image and PSF image there are softbias=1000.0, before any scale. the images should subtract 1000.0. For the psf, after subtraction, scale the image using psf/total(psf).

linan7788626 commented 8 years ago

all right, before we combine them together, the most important thing is that we have to make sure we are using the same unit in all images.....

linan7788626 commented 8 years ago

I updated a new lensed image which is in ./output_fits/, it looks realistic, but the flux of source and lens are incorrect. And another issue, noise should be added separately, but not added with lens galaxy. otherwise, how could we convolve PSF for the lens galaxy. Anyway, please tell me what is the unit of the value of the pixels in the fits files you gave me.

WentaoLuo commented 8 years ago

what I use is count of photon-electron, produced by CCD. It mimics SDSS detector. The count magnitude relation is :http://classic.sdss.org/dr7/algorithms/fluxcal.html. f/f0 = counts/exptime * 10^{-0.4_(aa + kk * airmass)}, And number of photon-electron=count_gain, gainr=4.7 mag = -2.5 * log10(f/f0) SDSS exposure time 54 minutes. We simply set {-0.4(aa+kk_airmass)) to be -9.6 meaning we fix a zero-point and airmass.

Then, given an wanted SDSS magnitude MAG MAG--->f/f0--->counts.

By the way, I think the unit we use should be counts rather than photon-electron, so we do not need gain_r value.

Sorry for that.

WentaoLuo commented 8 years ago

figure_1

Nice work, man!

WentaoLuo commented 8 years ago

We should definitely add the others to this project, so we could brainstorm. What do you think. I think we are ready to simulate a larger set of images, don't we?

linan7788626 commented 8 years ago

I know we should add others to this project, how about later this week, before that we have a couple of things to fix:

If we do not figure our these problems, the images we produced are not naturally right. After this, we add them in the collaborators list. Does it make sense ?

WentaoLuo commented 8 years ago

Yes, you are right. We should at least fix the above three issues before we add them.

WentaoLuo commented 8 years ago

I believe the velocity dispersion you need of the lens galaxy should be taken as the dispersion of the dark matter halo with an SIE profile?

linan7788626 commented 8 years ago

the velocity dispersion I am using here is the velocity dispersion of stars in the lens galaxy. It is also the velocity dispersion of the total mass distribution, not dark matter halo only.

On Dec 8, 2015, at 3:56 PM, Wentao Luo notifications@github.com wrote:

I believe the velocity dispersion you need of the lens galaxy should be taken as the dispersion of the dark matter halo with an SIE profile?

— Reply to this email directly or view it on GitHub https://github.com/linan7788626/Arc_Finding_with_CMU/issues/2#issuecomment-163030639.

WentaoLuo commented 8 years ago

Or you mean the "the velocity dispersion of the lenses" are the dispersion of the dark matter halo? And then using Faber-Jackson relation, we could estimate the luminosity of the galaxy reside in the halo?

WentaoLuo commented 8 years ago

I see.

linan7788626 commented 8 years ago

do not be struggling in dark matter halo or what, let’s use total mass distribution here.

On Dec 8, 2015, at 4:00 PM, Wentao Luo notifications@github.com wrote:

I see.

— Reply to this email directly or view it on GitHub https://github.com/linan7788626/Arc_Finding_with_CMU/issues/2#issuecomment-163031806.

WentaoLuo commented 8 years ago

I am on it. velocity dispersion----->luminosity(Faber-Jackson relation)----> SDSS CCD counts.

WentaoLuo commented 8 years ago

Alright, I will add the according calibration python code to our repository.

linan7788626 commented 8 years ago

how you model the surface brightness distribution? use 1/4 law please , if you can.

WentaoLuo commented 8 years ago

Sure, n=1/4. typical elliptical galaxy profile, a.k.a de Vaucouleurs profile.

linan7788626 commented 8 years ago

yes

On Dec 8, 2015, at 4:06 PM, Wentao Luo notifications@github.com wrote:

Sure, n=1/4. typical elliptical galaxy profile, a.k.a de Vaucouleurs profile.

— Reply to this email directly or view it on GitHub https://github.com/linan7788626/Arc_Finding_with_CMU/issues/2#issuecomment-163033182.

WentaoLuo commented 8 years ago

I hope your computer will be fine. I decide to make generate the lens galaxy profile using the following steps: 1, Fundamental plane: given a velocity dispersion(no scatter first)--> R_e, miu_e, luminosity 2, de Vaucouleurs profile with certain R_e *3, We finally need to take the scatter of the fundamental plane into consideration, with assigning a random Number from Normal distribution with the same scatter of a certain scaling relation, e.g. miu_e vs R_e, or vel_dis vs miu_e, e.t.c.

The attached is an example of fundamental plane,

/home/wtluo/Desktop/figure2.jpg

WentaoLuo commented 8 years ago

figure2

linan7788626 commented 8 years ago

it looks great, everything sounds reasonable, but I have one question: how we identify the parameter I_0 of the de Vaucouleurs profile profile? we need to use I_0 and R_e to describe the profile fully.

WentaoLuo commented 8 years ago

Do not worry, in that profile, the I_0 is actually I_e. People build the fundamental plane to make thins easier rather than more complex. See the link :https://en.wikipedia.org/wiki/De_Vaucouleurs'_law. The only thing is the empirical number: 7.669, which change the I_0 to I_e.

Once we have the fundamental plane, everything is good, except for the scatter.

linan7788626 commented 8 years ago

Great, I am looking forward to your result of the lens galaxies, please do not forget the ellipticity and orientation, if possible just set them as input parameters as well. here e = 0.8 , phi = 45 degree.

On Dec 10, 2015, at 11:03 AM, Wentao Luo notifications@github.com wrote:

Do not worry, in that profile, the I_0 is actually I_e. People build the fundamental plane to make thins easier rather than more complex. See the link :https://en.wikipedia.org/wiki/De_Vaucouleurs'_law https://en.wikipedia.org/wiki/De_Vaucouleurs'_law. The only thing is the empirical number: 7.669, which change the I_0 to I_e.

Once we have the fundamental plane, everything is good, except for the scatter.

— Reply to this email directly or view it on GitHub https://github.com/linan7788626/Arc_Finding_with_CMU/issues/2#issuecomment-163688422.

WentaoLuo commented 8 years ago

Sorry, I_o is not I_e. But can be scaled to I_e with some weird number 7.669.

WentaoLuo commented 8 years ago

Sure, I will take ellipticity into consideration.

linan7788626 commented 8 years ago

could you Point me to the reference for identify I_e R_e and I_0 , please. Thanks

On Dec 10, 2015, at 11:06 AM, Wentao Luo notifications@github.com wrote:

Sorry, I_o is not I_e. But can be scaled to I_e with some weird number 7.669.

— Reply to this email directly or view it on GitHub https://github.com/linan7788626/Arc_Finding_with_CMU/issues/2#issuecomment-163689141.

WentaoLuo commented 8 years ago

AS3011_5.pdf

I_e=I_0exp(-7.669)

WentaoLuo commented 8 years ago

We need to find out a paper that describe this relation. The PDF is only from a lecture.

WentaoLuo commented 8 years ago

An example of Poisson noise poisson_noise

WentaoLuo commented 8 years ago

An example of Gaussian noise. gaussian_noise