45 research outputs found
Group-galaxy correlations in redshift space as a probe of the growth of structure
We investigate the use of the cross-correlation between galaxies and galaxy
groups to measure redshift-space distortions (RSD) and thus probe the growth
rate of cosmological structure. This is compared to the classical approach
based on using galaxy auto-correlation. We make use of realistic simulated
galaxy catalogues that have been constructed by populating simulated dark
matter haloes with galaxies through halo occupation prescriptions. We adapt the
classical RSD dispersion model to the case of the group-galaxy
cross-correlation function and estimate the RSD parameter by fitting
both the full anisotropic correlation function and its multipole
moments. In addition, we define a modified version of the latter statistics by
truncating the multipole moments to exclude strongly non-linear distortions at
small transverse scales. We fit these three observable quantities in our set of
simulated galaxy catalogues and estimate statistical and systematic errors on
for the case of galaxy-galaxy, group-group, and group-galaxy
correlation functions. When ignoring off-diagonal elements of the covariance
matrix in the fitting, the truncated multipole moments of the group-galaxy
cross-correlation function provide the most accurate estimate, with systematic
errors below 3% when fitting transverse scales larger than . Including
the full data covariance enlarges statistical errors but keep unchanged the
level of systematic error. Although statistical errors are generally larger for
groups, the use of group-galaxy cross-correlation can potentially allow the
reduction of systematics while using simple linear or dispersion models.Comment: 18 pages, 16 figure
Improving fast generation of halo catalogs with higher-order Lagrangian perturbation theory
We present the latest version of Pinocchio, a code that generates catalogues
of DM haloes in an approximate but fast way with respect to an N-body
simulation. This code version extends the computation of particle and halo
displacements up to 3rd-order Lagrangian Perturbation Theory (LPT), in contrast
with previous versions that used Zeldovich approximation (ZA).
We run Pinocchio on the same initial configuration of a reference N-body
simulation, so that the comparison extends to the object-by-object level. We
consider haloes at redshifts 0 and 1, using different LPT orders either for
halo construction - where displacements are needed to decide particle accretion
onto a halo or halo merging - or to compute halo final positions.
We compare the clustering properties of Pinocchio haloes with those from the
simulation by computing the power spectrum and 2-point correlation function
(2PCF) in real and redshift space (monopole and quadrupole), the bispectrum and
the phase difference of halo distributions. We find that 2LPT and 3LPT give
noticeable improvement. 3LPT provides the best agreement with N-body when it is
used to displace haloes, while 2LPT gives better results for constructing
haloes. At the highest orders, linear bias is typically recovered at a few per
cent level.
In Fourier space and using 3LPT for halo displacements, the halo power
spectrum is recovered to within 10 per cent up to Mpc. The
results presented in this paper have interesting implications for the
generation of large ensemble of mock surveys aimed at accurately compute
covariance matrices for clustering statistics.Comment: 20 pages, 20 figures, submitted to MNRA
Inpainting hydrodynamical maps with deep learning
From 1,000 hydrodynamic simulations of the CAMELS project, each with a
different value of the cosmological and astrophysical parameters, we generate
15,000 gas temperature maps. We use a state-of-the-art deep convolutional
neural network to recover missing data from those maps. We mimic the missing
data by applying regular and irregular binary masks that cover either or
of the area of each map. We quantify the reliability of our results
using two summary statistics: 1) the distance between the probability density
functions (pdf), estimated using the Kolmogorov-Smirnov (KS) test, and 2) the
2D power spectrum. We find an excellent agreement between the model prediction
and the unmasked maps when using the power spectrum: better than for
Mpc for any irregular mask. For regular masks, we observe a systematic
offset of when covering of the maps while the results become
unreliable when of the data is missing. The observed KS-test p-values
favor the null hypothesis that the reconstructed and the ground-truth maps are
drawn from the same underlying distribution when irregular masks are used. For
regular-shaped masks on the other hand, we find a strong evidence that the two
distributions do not match each other. Finally, we use the model, trained on
gas temperature maps, to perform inpainting on maps from completely different
fields such as gas mass, gas pressure, and electron density and also for gas
temperature maps from simulations run with other codes. We find that visually,
our model is able to reconstruct the missing pixels from the maps of those
fields with great accuracy, although its performance using summary statistics
depends strongly on the considered field.Comment: 14 pages, 6 figures, Submitted to AP
Solubility of CO2 in Aqueous Solutions of 2-Amino-2-Methyl-1-Propanol at High Pressure
Carbon dioxide is one of the major green house gases.
It is removed from different streams using amine absorption process.
Sterically hindered amines are suggested as good CO2 absorbers.
Solubility of carbon dioxide (CO2) was measured in aqueous
solutions of 2-Amino-2-methyl-1-propanol (AMP) at temperatures 30
oC, 40 oC and 60 oC. The effect of pressure and temperature was
studied over various concentrations of AMP. It has been found that
pressure has positive effect on CO2 solubility where as solubility
decreased with increasing temperature. Absorption performance of
AMP increased with increasing pressure. Solubility of aqueous AMP
was compared with mo-ethanolamine (MEA) and the absorption
capacity of aqueous solutions of AMP was found to be better
The CAMELS Project: Public Data Release
The Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4233 cosmological simulations, 2049 N-body simulations, and 2184 state-of-the-art hydrodynamic simulations that sample a vast volume in parameter space. In this paper, we present the CAMELS public data release, describing the characteristics of the CAMELS simulations and a variety of data products generated from them, including halo, subhalo, galaxy, and void catalogs, power spectra, bispectra, Lyα spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over 1000 catalogs that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz semianalytic model. We release all the data, comprising more than 350 terabytes and containing 143,922 snapshots, millions of halos, galaxies, and summary statistics. We provide further technical details on how to access, download, read, and process the data at https://camels.readthedocs.io
The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: exploring the Halo Occupation Distribution model for Emission Line Galaxies
We study the modelling of the Halo Occupation Distribution (HOD) for the
eBOSS DR16 Emission Line Galaxies (ELGs). Motivated by previous theoretical and
observational studies, we consider different physical effects that can change
how ELGs populate haloes. We explore the shape of the average HOD, the fraction
of satellite galaxies, their probability distribution function (PDF), and their
density and velocity profiles. Our baseline HOD shape was fitted to a
semi-analytical model of galaxy formation and evolution, with a decaying
occupation of central ELGs at high halo masses. We consider Poisson and
sub/super-Poissonian PDFs for satellite assignment. We model both NFW and
particle profiles for satellite positions, also allowing for decreased
concentrations. We model velocities with the virial theorem and particle
velocity distributions. Additionally, we introduce a velocity bias and a net
infall velocity. We study how these choices impact the clustering statistics
while keeping the number density and bias fixed to that from eBOSS ELGs. The
projected correlation function, , captures most of the effects from the
PDF and satellites profile. The quadrupole, , captures most of the
effects coming from the velocity profile. We find that the impact of the mean
HOD shape is subdominant relative to the rest of choices. We fit the clustering
of the eBOSS DR16 ELG data under different combinations of the above
assumptions. The catalogues presented here have been analysed in companion
papers, showing that eBOSS RSD+BAO measurements are insensitive to the details
of galaxy physics considered here. These catalogues are made publicly
available.Comment: Data available here: http://popia.ft.uam.es/eBOSS_ELG_OR_mocks. A
description of eBOSS and links to all associated publications can be found
here: https://www.sdss.org/surveys/eboss/ ; 24 pages, 17 Figures; Published
in MNRAS 25 Sep 202
The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey : pairwise-inverse probability and angular correction for fibre collisions in clustering measurements
HJS is supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics under Award Number DE-SC0014329. Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. This project has received funding from the European Research Council (ERC) under the European Unionâs Horizon 2020 research and innovation programme (grant agreement No 693024).The completed extended Baryon Oscillation Spectroscopic Survey (eBOSS) catalogues contain redshifts of 344â080 quasars at 0.8 < z < 2.2, 174â816 luminous red galaxies between 0.6 < z < 1.0, and 173â736 emission-line galaxies over 0.6 < z < 1.1 in order to constrain the expansion history of the Universe and the growth rate of structure through clustering measurements. Mechanical limitations of the fibre-fed spectrograph on the Sloan telescope prevent two fibres being placed closer than 62 arcsec in a single pass of the instrument. These âfibre collisionsâ strongly correlate with the intrinsic clustering of targets and can bias measurements of the two-point correlation function resulting in a systematic error on the inferred values of the cosmological parameters. We combine the new techniques of pairwise-inverse probability and the angular upweighting (PIP+ANG) to correct the clustering measurements for the effect of fibre collisions. Using mock catalogues, we show that our corrections provide unbiased measurements, within data precision, of both the projected wp(rp) and the redshift-space multipole Ο(â = 0, 2, 4)(s) correlation functions down to 0.1hâ1Mpcâ , regardless of the tracer type. We apply the corrections to the eBOSS DR16 catalogues. We find that, on scales sâł20hâ1Mpcsâł20hâ1Mpc for Οâ, as used to make baryon acoustic oscillation and large-scale redshift-space distortion measurements, approximate methods such as nearest-neighbour upweighting are sufficiently accurate given the statistical errors of the data. Using the PIP method, for the first time for a spectroscopic program of the Sloan Digital Sky Survey, we are able to successfully access the one-halo term in the clustering measurements down to âŒ0.1hâ1Mpc scales. Our results will therefore allow studies that use the small-scale clustering to strengthen the constraints on both cosmological parameters and the halo occupation distribution models.Publisher PDFPeer reviewe
The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Large-scale structure catalogues for cosmological analysis
We present large-scale structure catalogues from the completed extended Baryon Oscillation Spectroscopic Survey (eBOSS). Derived from Sloan Digital Sky Survey (SDSS) IV Data Release 16 (DR16), these catalogues provide the data samples, corrected for observational systematics, and random positions sampling the survey selection function. Combined, they allow large-scale clustering measurements suitable for testing cosmological models. We describe the methods used to create these catalogues for the eBOSS DR16 Luminous Red Galaxy (LRG) and Quasar samples. The quasar catalogue contains 343â708 redshifts with 0.8 1000âkmâsâ1). For quasars, these rates are 95 and 2 per cent (with Îz > 3000âkmâsâ1). We apply corrections for trends between the number densities of our samples and the properties of the imaging and spectroscopic data. For example, the quasar catalogue obtains a Ï2/DoF = 776/10 for a null test against imaging depth before corrections and a Ï2/DoF= 6/8 after. The catalogues, combined with careful consideration of the details of their construction found here-in, allow companion papers to present cosmological results with negligible impact from observational systematic uncertainties
The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis
Background: The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools. Methods: In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST. Results and Conclusion: The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events
The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: measurement of the BAO and growth rate of structure of the luminous red galaxy sample from the anisotropic power spectrum between redshifts 0.6 and 1.0
We analyse the clustering of the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 16 luminous red galaxy sample (DR16 eBOSS LRG) in combination with the high redshift tail of the Sloan Digital Sky Survey III Baryon Oscillation Spectroscopic Survey Data Release 12 (DR12 BOSS CMASS). We measure the redshift space distortions (RSD) and also extract the longitudinal and transverse baryonic acoustic oscillation (BAO) scale from the anisotropic power spectrum signal inferred from 377â458 galaxies between redshifts 0.6 and 1.0, with the effective redshift of zeff = 0.698 and effective comoving volume of 2.72Gpc3â . After applying reconstruction, we measure the BAO scale and infer DH(zeff)/rdrag = 19.30 ± 0.56 and DM(zeff)/rdrag = 17.86 ± 0.37. When we perform an RSD analysis on the pre-reconstructed catalogue on the monopole, quadrupole, and hexadecapole we find, DH(zeff)/rdrag = 20.18 ± 0.78, DM(zeff)/rdrag = 17.49 ± 0.52 and fÏ8(zeff) = 0.454 ± 0.046. We combine both sets of results along with the measurements in configuration space and report the following consensus values: DH(zeff)/rdrag = 19.77 ± 0.47, DM(zeff)/rdrag = 17.65 ± 0.30 and fÏ8(zeff) = 0.473 ± 0.044, which are in full agreement with the standard ÎCDM and GR predictions. These results represent the most precise measurements within the redshift range 0.6 †z †1.0 and are the culmination of more than 8 yr of SDSS observations.HG-M acknowledges the support from la Caixa Foundation (ID 100010434) which code LCF/BQ/PI18/11630024. RP, SdlT, and SE acknowledge support from the ANR eBOSS project (ANR-16-CE31-0021) of the French National Research Agency. SdlT and SE acknowledge the support of the OCEVU Labex (ANR-11-LABX-0060) and the A*MIDEX project (ANR-11-IDEX-0001-02) funded by the âInvestissements dâAvenirâ French government program managed by the ANR. MV-M and SF are partially supported by Programa de Apoyo a Proyectos de InvestigaciĂłn e InovaciĂłn TeconolĂłgica (PAPITT) no. IA101518, no. IA101619 and Proyecto LANCAD-UNAM-DGTIC-136. GR acknowledges support from the National Research Foundation of Korea (NRF) through Grants No. 2017R1E1A1A01077508 and No. 2020R1A2C1005655 funded by the Korean Ministry of Education, Science and Technology (MoEST), and from the faculty research fund of Sejong University. SA is supported by the European Research Council through the COSFORM Research Grant (#670193). E-MM is supported by the European Research Council (ERC) under the European Unionâs Horizon 2020 research and innovation programme (grant agreement No 693024).Peer reviewe