I don't know about that.

Linear term should dominate. That is so far the trend that has been observed. However, as we have no way of observing the future, we can't determine for sure whether H would indeed be decreasing, increasing, or becoming constant.

@leokap ok. Suppose from gsl, omega >=-1 , means energy density decrease. So suppose if H is decreasing and I have a friedmann equation says (H^2+k/a^2)-(H^2+k/a^2)^-1 =8 pi G/3 rho. In the late time limit, as a tends to infinity, considering H to be decrease , Here we neglect the second term right and the consider first one as dominant? And approximate the first one to r.h.s? If opposite is the case, negative power of H could lead to diverging scenario right if H is considered to be decreasing in late time limit.

the denominator becomes 1 and numerator will become x^2-y^2

Kindly see my latest video where I explained supernova data. There you won't need to create any environment and you can directly start with the Ubuntu terminal using VS code. In the ubuntu terminal you will not find any error, while some syntax error can be found in windows terminal.

​@@cosmickap ok. Then after installing mcmc, and vc code, skip the remainjng portion of the first video? Before there any other content that may get affected directly switching to ubuntu?

​@@cosmickapthe problem I encounter is that I choose venv and microsoft global version of python 3.9.13. Then requirements_full.txt selected and it runs but after sometimes runs into error.

If you are using windows, most probably you will encounter error.

@@cosmickap ok I will try.

You can download vscode in ubuntu.. and run your code in the terminal. You can see my recent videos on how to compile in the ubuntu terminal.

I presume you're referring to the exchange at 55:04. I just heard Von Hausegger address specifically Lerner's statement that the fractal structure of mass concentrations disproves the homogeneiry hypothesis. Von Hausegger agreed about the fractal structure but not that it invalidated homgeneity at large scale, showing the graph of clumpiness that flattens out by 1 gigaparsec. His larger point was that Lambda CDM expllains a huge number of data sets, as summarized in his presentation, and that alternative theories have a lot of work cut out for them to explain the whole array of astrophysical phenomena to such a degree of detail.

@@johnsorrelw849 But it does invalidate homogeneity, because we see these fractal patterns repeating on larger and larger *scales*. It's not just a web-like pattern on a single scale. Galaxies are strung out on plasma filaments with vast spaces between the filaments. Galaxy clusters are strung out on cluster-sized filaments with even larger spaces between those. And then we see galactic walls showing the edges of what are likely gigantic filament structures that span billions of light years across. Not only could these structures not have formed in 14 billions years, but they must be larger than the visible universe (consider the Hercules-Corona Borealis Great Wall, for example). But for this conversation, the point is that we see matter in fractal-like structures that *scale*. The scaling aspect shows clumpiness in ever greater and greater concentrations, clearly disproving homogeneity.

@@johnsorrelw849 Did you see a reply I made here? It seems to be missing now.

​@@emanuelsferios5783 No, I did not see it. I might add to the previous comment that I wonder if Von H's claim that the homogeneiry remains at the largest scales holds up in light of the huge structure (the Great Circle? I forget what they are calling it) that's like a billion light years across.

@@johnsorrelw849 I made a comment which seems to have disappeared. Basically I said that the fractal structure we see (and that Lerner describes) is, by definition, non-homogeneous. This is precisely because it *scales*. The helical filaments on the smaller scales (that hold the galaxies) are separated by vast spaces. But then the clusters are also on much larger filaments with even vaster spaces between them, up to the galactic walls, that suggest the edges of even larger filaments with even larger empty space. Is this patterned? Yes. Is it homogeneous? Absolutely not. The homogeneity needed for general relativity to work (a gravity-only system) requires relatively even distribution of matter, not a scaling fractal system. (Let's see if this comment appears.)

Thank you😊. The natural Logarithm of likelihood is proportional to the negative of 1/2 of chi squared; that's why I have calculated it. If you are looking for the differential equation for LambdaCDM model, you may find it in Chapter II of my thesis work: inspirehep.net/literature/2807106 and references therein. For the differential equation of D_L, you have to do a deep search for papers, since more often authors report the integral form. Further, you can check out my GitHub link pinned in the comment section, where you may find more references and a link to a recent video on BAO analysis. Let me know if you have any other queries.

Thanks. Yeah, in the 2nd column it is the values of Hubble parameter binned at different redshift. From there we are estimating H_0 a constant quantity which should be the same at all the redshift.

You are welcome!

I'll make one. 🎉

@@zdvzxdvxdv-r8n use that complete file. I have renamed that one.

@@cosmickap okay sir. Thank you.

@@cosmickap sorry to interrupt. it gives error: cov_mat = cov_data.reshape(1701,1701) ValueError: cannot reshape array of size 2893402 into shape (1701,1701)

@@zdvzxdvxdv-r8n open that file, remove the first digit =1701.

@@cosmickap Okay Sir

@@harishankarjoc use english word.

subscribe and share it ur friends

@@adamkaczmarek4751 Thanks for following.

everything u can find here. Just watch till the end.

Yes. I was to comment back. Everything, you have mentioned.​@@leokap thanks a lot.

add find chi square for each data sets simultaneously and add them in the end.

Oh.. Okay. I will try doing this. Thank you so much.​@@cosmickap

use the argument np.shape(1701,1701).

Thanks.. I guess this week I will put my video on BAO data.

The formula used here is absolutely fine. Here i am using the shoes calibrated data, the data corresponding to mu not m.

Thanks.

you can find some interesting review papers. just search k-essence and quintessence review.

Yeah . Thanks.

@@cosmickap so im starting my 1st research internship in Cosmology which will focus on DATA SIMULATION AND PARAMETER FITTING. what i will need it will help me if yu can suggest/advice something

@@FermionAP As you are entering in research I would advice, solidify your basic theoretical cosmology part, model building and analysis. As you are interested in numerical simulations, I think you must have already known python. Grasp its advanced concepts, go through the statistical analysis. Make sure to learn a little bit of C programming, Parallelization techniques, and Mathematica (for theoretical work).

yeah, sure

@@cosmickap Sir! I am not getting your contact email/number.. Please.

@@jamahmad-d5b [email protected]

This is compiled in linux.

I have tested numba. not useful with scipy libraries.

@@cosmickap yes, it cannot work with scipy. Can you give me any references to learn how to code in cython? I have a system of differential equations, but as you said in the video, it's very slow. I would like to 'cythonize' my code.

you can find some reference books. A book by Kurt W Smith - Cython_A Guide for python.

Thanks

It is a bit of a complicated program. But the code I have given gains enough speed with parallelization.

I have mentioned how to find the data in the video.

​@@cosmickapok sir

Thanks for the nice video, and good explanation. I checked the repository. the code is not there. the one that include cython.

yeah... you can try to write yourself by watching the video.. I will add it in a few days.

@@cosmickap Thanks for the nice one! Could you add the code with cython to the repository? That'll be a huge help!