LSS Mocks - User contributions [en-ca]

WebSky Extragalactic CMB Mocks

2021-08-27T21:37:24Z

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<gallery mode="packed-hover" heights="300px">
File:montage.png | [[Media:montage.png|Websky maps]]
File:Lightcone_60arcmin_300dpi.png | [[Media:Lightcone_60arcmin_300dpi.png | Websky halos ]]

</gallery>

Provided are [https://healpix.jpl.nasa.gov/ HEALPix] .fits files over the full sky at nside=4096 of CIB (in MJy/sr) intensity, Compton-y, kSZ (mu K), CMB lensing convergence, and lensed and un-lensed CMB TT, EE, and BB maps, all from the same 12288^3 particle, 15.4 Gpc peak-patch and 2LPT based cosmological simulation, as well as the light cone halo catalog itself. The minimum halo mass used was ~1.4e12 M200,M. Higher resolution maps and different frequencies are available upon request. For a full description of the contents of these maps see ''The Websky Extragalactic CMB Simulations'' - https://arxiv.org/abs/2001.08787.

= Data =
Data, including [http://mocks.cita.utoronto.ca/data/websky/v0.0 README], available [http://mocks.cita.utoronto.ca/data/websky/v0.0 here]

= Figures =
<gallery mode="packed-hover" heights="250px">
File:tsz.png | [[Media:tsz.png | tSZ power spectrum ]]
File:ksz.png | [[Media:ksz.png | kSZ power spectrum ]]
File:cib.png | [[Media:cib.png | CIB power spectra ]]
File:KappaPower.png | [[Media:KappaPower.png | Convergence power spectrum ]]
File:conversion_factors.png | [[Media:conversion_factors.png | Conversion factors from native maps to delta Tcmb]]
</gallery>

= Acknowledgments =
The WebSky Extragalactic CMB Mocks Collaboration consists of George Stein, Marcelo Alvarez, Dick Bond, Alex van Engelen, Nick Battaglia, and Zack Li, with additional contributions from Amir Hajian.

In order to properly acknowledge our efforts, we request the following paragraph to be included in the “Acknowledgements” section of any publication
which makes use of the simulation data above, and ask you to cite the following papers:

Paper 2: ''The Websky Extragalactic CMB Simulations'' - G. Stein, M. A. Alvarez, J. R. Bond, A. v. Engelen, N. Battaglia (2020). https://arxiv.org/abs/2001.08787

Paper 1: ''The mass-Peak Patch algorithm for fast generation of deep all-sky dark matter halo catalogues and its N-Body validation'' - G. Stein, M. A. Alvarez, J. R. Bond (2019). https://arxiv.org/abs/1810.07727

"The sky simulations used in this paper were developed by the WebSky Extragalactic CMB Mocks team, with the continuous support of the Canadian Institute for Theoretical Astrophysics (CITA), the Canadian Institute for Advanced Research (CIFAR), and the Natural Sciences and Engineering Council of Canada (NSERC), and were generated on the Niagara supercomputer at the SciNet HPC Consortium (cite https://arxiv.org/abs/1907.13600). SciNet is funded by: the Canada Foundation for Innovation under the auspices of Compute Canada; the Government of Ontario; Ontario Research Fund - Research Excellence; and the University of Toronto."

[[ Documentation | Internal Pages ]]

File:Montage.png

2019-04-09T21:52:55Z

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File:Montage.png

2019-04-09T21:51:55Z

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File:Montage.png

2019-04-09T21:46:33Z

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File:Ksz.png

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File:Tsz.png

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The Compton-y power spectrum of the WebSky tSZ map (blue line). We also include the Planck results (black), the external Planck re-analysis taking into account the trispectrum in the covariance matrixand an extended marginalization (gray), the ACT measurement (green), and the SPT measurement (orange).

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File:Cib.png

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File:Tsz.png

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File:Lightcone 60arcmin 300dpi.png

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File:KSZPower.png

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Documentation

2018-01-24T05:03:15Z

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== Software ==

== Data ==

[http://cita.utoronto.ca/~malvarez/research/ksz-data/ Patchy kSZ Maps]

[https://www.dropbox.com/sh/deqz1gekpw0fapw/AABGKqqzG9wMnLP0LqFzE6i-a?dl=0/ Kappa, unlensed and lensed maps (LP)]

[https://www.dropbox.com/s/1evuw17snfqzhwj/all.pdf?dl=0 K, Phi, unlensed, lensed PDF (LP)]

== Transferring Data to Nersc ==

1.) log in to nersc - $ssh <username>@edison.nersc.gov

2.) log into edisongrid - $ssh edisongrid

3.) Sign into collaboration account
$module load globus
$myproxy-logon -s nerscca.nersc.gov !Password is the same as your username
$gsissh localhost -l cmbs4

4.) $cd /project/projectdirs/cmbs4

5.) ensure that the permissions are set appropriately (g+rX,o-rwx)

6.) Update README and cmbs4 wiki for any new files you add or changes you make!

README snippet for .npz catalogues
HALO CATALOGUES:
Contains (x,y,z,mass,redshift) for each halo. They are saved in the npz format of numpy (see http://docs.scipy.org/doc/numpy/reference/generated/numpy.savez.html). To load simply use
halo_cat = np.load(outfile)
xpk = halo_cat["xpk"]
ypk = halo_cat["ypk"]
zpk = halo_cat["zpk"]
M = halo_cat["M"]
redshift = halo_cat["redshift"]

README snippet for .pksc catalogues

Contains (x,y,z,v_x,v_y,v_z,R_TH) for each halo. The final halo catalog is a binary file with a 12 byte header, R_TH is the Lagrangian top hat radius of the halo. The conversion to mass is M_halo = 4*pi/3 * R_TH**3 * rho_bar, where rho_mean = 2.775e11*Omega_M*h**2.
header = (int Non, float RTHmax, float redshiftbox)
where Non is the total number of halos found,
RTHmax is the radius of the largest halo in the simulation,
redshiftbox is the redshift of the box, which will be negative for lightcone runs.
This 12 byte header is then followed by a list of Non*7 4 byte floats that represent (x_halo,y_halo,z_halo,vx_halo,vy_halo,vz_halo,Rth_halo)

Sample Python and Fortran code to load a datafile:

Python:
pkfile = open(filein,"rb")
Non = np.fromfile(pkfile, dtype=np.int32, count=1)
RTHMAXin = np.fromfile(pkfile, dtype=np.float32, count=1)
redshiftbox = np.fromfile(pkfile, dtype=np.float32, count=1)
print "Non = ", Non
npkdata = 7*Non
peakdata = np.fromfile(pkfile, dtype=np.float32, count=npkdata)
peakdata = np.reshape(peakdata,(Non,7))
xpos = peakdata[:,0]
ypos = peakdata[:,1]
zpos = peakdata[:,2]
vxpos = peakdata[:,3]
vypos = peakdata[:,4]
vzpos = peakdata[:,5]
Rth = peakdata[:,6]
Omega_M = 0.25
h = 0.7
rhomean = 2.775e11*Omega_M*h**2
M = 4.0/3*np.pi*Rth**3*rhomean

Redshifts
z=np.linspace(0,4,1000)
def hubble(z):
return h*100*np.sqrt(omegam*(1+z)**3+1-omegam)
def drdz(z):
return 3e5 / hubble(z)
r = np.cumsum(drdz(z)*(z[1]-z[0]))
r -= r[0]
z_to_r = sp.interpolate.interp1d(z,r)
r_to_z = sp.interpolate.interp1d(r,z)

Fortran:
open(4,file=filein,status='old',access='stream')
read(4) Npk,RTHLmax_in,boxredshift
allocate(posxyz(3,nhalo))
allocate(velxyz(3,nhalo))
allocate(rth(nhalo))
allocate(mass(nhalo))
allocate(vrad(nhalo))
offset_num_floats = 7*nhalo*myid
read(4) ((posxyz(j,i),j=1,3),&
(velxyz(j,i),j=1,3),&
rth(i),i=1,nhalo)
close(4)

== Modeling ==

=== CMB Lensing ===

Using a 'field+halo' model to generate lensing kappa maps from Gaussian random field (GRF) of density fluctuations on the past light cone.

'''Halo Model:''' The peak patch algorithm is run on the GRF to produce a catalog of halos with [RA, Dec, redshift, velocity, mass]. The halos are assumed to have a spherically-symmetric matter distribution parameterized by a generalized NFW density profile. This contribution to the convergence from each halo is then projected onto the kappa map, appropriately weighted by the lensing kernel, W(z).
<gallery mode=packed heights="300px">
File:fullskykappa.png|"Halo only" full sky kappa map
File:flatskykappa.png|"Halo only" zoomed in kappa map
</gallery>

'''Field Model:''' (development in progress) Lagrangian perturbation theory is used to move matter not within halos to its final Eulerian position. This field matter distribution is then added directly to the kappa map. A [260 x 260 x 60] Mpc/h slab at z=0 is shown below with all the matter moved with either first (1LPT) or second (2LPT) order Lagrangian perturbation theory, in addition to the halos found with the peak patch method (these peak patch halos are also moved with either . Shown below are the same peak patch halo distributions, but also the

Large Scale Structure Mocks

2018-01-24T04:56:41Z

MediaWiki default: Malvarez moved page CITA Large Scale Structure Mocks to Large Scale Structure Mocks

Welcome to the CITA LSS Mocks Portal.

= [http://mocks.cita.utoronto.ca/websky WebSky Extragalactic CMB Mocks] =
CIB intensity, Compton-y, CMB lensing convergence, lensed and unlensed CMB temperature, all from the same 8192^3 16 Gpc simulation.

= [http://cita.utoronto.ca/~malvarez/research/ksz-data Patchy kSZ Maps] =
Data and figures to accompany [http://adsabs.harvard.edu/abs/2016ApJ...824..118A Alvarez (2016)].

Documentation

2018-01-24T04:52:03Z

MediaWiki default: Malvarez moved page Internal to Documentation

<math>M_{200,M} = 2.62 \times 10^{13} M_\odot</math>

== Software ==

== Data ==

[http://cita.utoronto.ca/~malvarez/research/ksz-data/ Patchy kSZ Maps]

[https://www.dropbox.com/sh/deqz1gekpw0fapw/AABGKqqzG9wMnLP0LqFzE6i-a?dl=0/ Kappa, unlensed and lensed maps (LP)]

[https://www.dropbox.com/s/1evuw17snfqzhwj/all.pdf?dl=0 K, Phi, unlensed, lensed PDF (LP)]

== Transferring Data to Nersc ==

1.) log in to nersc - $ssh <username>@edison.nersc.gov

2.) log into edisongrid - $ssh edisongrid

3.) Sign into collaboration account
$module load globus
$myproxy-logon -s nerscca.nersc.gov !Password is the same as your username
$gsissh localhost -l cmbs4

4.) $cd /project/projectdirs/cmbs4

5.) ensure that the permissions are set appropriately (g+rX,o-rwx)

6.) Update README and cmbs4 wiki for any new files you add or changes you make!

README snippet for .npz catalogues
HALO CATALOGUES:
Contains (x,y,z,mass,redshift) for each halo. They are saved in the npz format of numpy (see http://docs.scipy.org/doc/numpy/reference/generated/numpy.savez.html). To load simply use
halo_cat = np.load(outfile)
xpk = halo_cat["xpk"]
ypk = halo_cat["ypk"]
zpk = halo_cat["zpk"]
M = halo_cat["M"]
redshift = halo_cat["redshift"]

README snippet for .pksc catalogues

Contains (x,y,z,v_x,v_y,v_z,R_TH) for each halo. The final halo catalog is a binary file with a 12 byte header, R_TH is the Lagrangian top hat radius of the halo. The conversion to mass is M_halo = 4*pi/3 * R_TH**3 * rho_bar, where rho_mean = 2.775e11*Omega_M*h**2.
header = (int Non, float RTHmax, float redshiftbox)
where Non is the total number of halos found,
RTHmax is the radius of the largest halo in the simulation,
redshiftbox is the redshift of the box, which will be negative for lightcone runs.
This 12 byte header is then followed by a list of Non*7 4 byte floats that represent (x_halo,y_halo,z_halo,vx_halo,vy_halo,vz_halo,Rth_halo)

Sample Python and Fortran code to load a datafile:

Python:
pkfile = open(filein,"rb")
Non = np.fromfile(pkfile, dtype=np.int32, count=1)
RTHMAXin = np.fromfile(pkfile, dtype=np.float32, count=1)
redshiftbox = np.fromfile(pkfile, dtype=np.float32, count=1)
print "Non = ", Non
npkdata = 7*Non
peakdata = np.fromfile(pkfile, dtype=np.float32, count=npkdata)
peakdata = np.reshape(peakdata,(Non,7))
xpos = peakdata[:,0]
ypos = peakdata[:,1]
zpos = peakdata[:,2]
vxpos = peakdata[:,3]
vypos = peakdata[:,4]
vzpos = peakdata[:,5]
Rth = peakdata[:,6]
Omega_M = 0.25
h = 0.7
rhomean = 2.775e11*Omega_M*h**2
M = 4.0/3*np.pi*Rth**3*rhomean

Redshifts
z=np.linspace(0,4,1000)
def hubble(z):
return h*100*np.sqrt(omegam*(1+z)**3+1-omegam)
def drdz(z):
return 3e5 / hubble(z)
r = np.cumsum(drdz(z)*(z[1]-z[0]))
r -= r[0]
z_to_r = sp.interpolate.interp1d(z,r)
r_to_z = sp.interpolate.interp1d(r,z)

Fortran:
open(4,file=filein,status='old',access='stream')
read(4) Npk,RTHLmax_in,boxredshift
allocate(posxyz(3,nhalo))
allocate(velxyz(3,nhalo))
allocate(rth(nhalo))
allocate(mass(nhalo))
allocate(vrad(nhalo))
offset_num_floats = 7*nhalo*myid
read(4) ((posxyz(j,i),j=1,3),&
(velxyz(j,i),j=1,3),&
rth(i),i=1,nhalo)
close(4)

== Modeling ==

=== CMB Lensing ===

Using a 'field+halo' model to generate lensing kappa maps from Gaussian random field (GRF) of density fluctuations on the past light cone.

'''Halo Model:''' The peak patch algorithm is run on the GRF to produce a catalog of halos with [RA, Dec, redshift, velocity, mass]. The halos are assumed to have a spherically-symmetric matter distribution parameterized by a generalized NFW density profile. This contribution to the convergence from each halo is then projected onto the kappa map, appropriately weighted by the lensing kernel, W(z).
<gallery mode=packed heights="300px">
File:fullskykappa.png|"Halo only" full sky kappa map
File:flatskykappa.png|"Halo only" zoomed in kappa map
</gallery>

'''Field Model:''' (development in progress) Lagrangian perturbation theory is used to move matter not within halos to its final Eulerian position. This field matter distribution is then added directly to the kappa map. A [260 x 260 x 60] Mpc/h slab at z=0 is shown below with all the matter moved with either first (1LPT) or second (2LPT) order Lagrangian perturbation theory, in addition to the halos found with the peak patch method (these peak patch halos are also moved with either . Shown below are the same peak patch halo distributions, but also the

Large Scale Structure Mocks

2018-01-24T04:40:25Z

MediaWiki default:

Large Scale Structure Mocks

2018-01-24T04:40:09Z

MediaWiki default: Malvarez moved page CITA LSS Mocks to CITA Large Scale Structure Mocks

Welcome to the CITA Cosmology Mocks Portal.

= [http://mocks.cita.utoronto.ca/websky WebSky Extragalactic CMB Mocks] =
CIB intensity, Compton-y, CMB lensing convergence, lensed and unlensed CMB temperature, all from the same 8192^3 16 Gpc simulation.

= [http://cita.utoronto.ca/~malvarez/research/ksz-data Patchy kSZ Maps] =
Data and figures to accompany [http://adsabs.harvard.edu/abs/2016ApJ...824..118A Alvarez (2016)].

Large Scale Structure Mocks

2018-01-24T04:39:39Z

MediaWiki default: Malvarez moved page LSS Mocks:CITA LSS Mocks to CITA LSS Mocks

Large Scale Structure Mocks

2018-01-24T04:39:22Z

MediaWiki default: Malvarez moved page CITA Cosmology Mock Portal to LSS Mocks:CITA LSS Mocks

Large Scale Structure Mocks

2018-01-24T04:38:11Z

MediaWiki default: Created page with "Welcome to the CITA Cosmology Mocks Portal. = [http://mocks.cita.utoronto.ca/websky WebSky Extragalactic CMB Mocks] = CIB intensity, Compton-y, CMB lensing convergence, lense..."

File:Logo.png

2017-12-14T23:24:07Z