21 pages, 12 Figures, 3 Tables. Submitted to ApJ on July 1
We quantify evolution in the cluster scale stellar mass - halo mass (SMHM) relation's parameters using 2323 clusters and brightest central galaxies (BCGs) over the redshift range $0.03 \le z \le 0.60$. The precision on inferred SMHM parameters is improved by including the magnitude gap ($\rm m_{gap}$) between the BCG and fourth brightest cluster member (M14) as a third parameter in the SMHM relation. At fixed halo mass, accounting for $\rm m_{gap}$, through a stretch parameter, reduces the SMHM relation's intrinsic scatter. To explore this redshift range, we use clusters, BCGs, and cluster members identified using the Sloan Digital Sky Survey C4 and redMaPPer cluster catalogs and the Dark Energy Survey redMaPPer catalog. Through this joint analysis, we detect no systematic differences in BCG stellar mass, $\rm m_{gap}$, and cluster mass (inferred from richness) between the datsets. We utilize the Pareto function to quantify each parameter's evolution. We confirm prior findings of negative evolution in the SMHM relation's slope (3.5$\sigma$) and detect negative evolution in the stretch parameter (4.0$\sigma$) and positive evolution in the offset parameter (5.8$\sigma$). This observed evolution, combined with the absence of BCG growth, when stellar mass is measured within 50kpc, suggests that this evolution results from changes in the cluster's $\rm m_{gap}$. For this to occur, late-term growth must be in the intra-cluster light surrounding the BCG. We also compare the observed results to Illustris TNG 300-1 cosmological hydrodynamic simulations and find modest qualitative agreement. However, the simulations lack the evolutionary features detected in the real data.
20 pages, submitted to MNRAS, numerical tools available at this https URL
We study the connection of matter density and its tracers from the PDF perspective. One aspect of this connection is the conditional expectation value $\langle \delta_{\mathrm{tracer}}|\delta_m\rangle$ when averaging both tracer and matter density over some scale. We present a new way to incorporate a Lagrangian bias expansion of this expectation value into standard frameworks for modelling the PDF of density fluctuations and counts-in-cells statistics. Using N-body simulations and mock galaxy catalogs we confirm the accuracy of this expansion and compare it to the more commonly used Eulerian parametrization. For halos hosting typical luminous red galaxies, the Lagrangian model provides a significantly better description of $\langle \delta_{\mathrm{tracer}}|\delta_m\rangle$ at second order in perturbations. A second aspect of the matter-tracer connection is shot-noise, \ie the scatter of tracer density around $\langle \delta_{\mathrm{tracer}}|\delta_m\rangle$. It is well known that this noise can be significantly non-Poissonian and we validate the performance of a more general, two-parameter shot-noise model for different tracers and simulations. Both parts of our analysis are meant to pave the way for forthcoming applications to survey data.
14 pages + appendix, to be submitted to ApJ
We present GIGANTES, the most extensive and realistic void catalog suite ever released -- containing over 1 billion cosmic voids covering a volume larger than the observable Universe, more than 20 TB of data, and created by running the void finder VIDE on QUIJOTE's halo simulations. The expansive and detailed GIGANTES suite, spanning thousands of cosmological models, opens up the study of voids, answering compelling questions: Do voids carry unique cosmological information? How is this information correlated with galaxy information? Leveraging the large number of voids in the GIGANTES suite, our Fisher constraints demonstrate voids contain additional information, critically tightening constraints on cosmological parameters. We use traditional void summary statistics (void size function, void density profile) and the void auto-correlation function, which independently yields an error of $0.13\,\mathrm{eV}$ on $\sum\,m_{\nu}$ for a 1 $h^{-3}\mathrm{Gpc}^3$ simulation, without CMB priors. Combining halos and voids we forecast an error of $0.09\,\mathrm{eV}$ from the same volume. Extrapolating to next generation multi-Gpc$^3$ surveys such as DESI, Euclid, SPHEREx, and the Roman Space Telescope, we expect voids should yield an independent determination of neutrino mass. Crucially, GIGANTES is the first void catalog suite expressly built for intensive machine learning exploration. We illustrate this by training a neural network to perform likelihood-free inference on the void size function. Cosmology problems provide an impetus to develop novel deep learning techniques, leveraging the symmetries embedded throughout the universe from physical laws, interpreting models, and accurately predicting errors. With GIGANTES, machine learning gains an impressive dataset, offering unique problems that will stimulate new techniques.
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14 pages + appendix, to be submitted to ApJ
22 pages, 15 figures
22 pages, 19 figures, accepted for publication in Astronomy and Astrophysics
8 pages, 3 figures
Submitted to ApJ. 19 pages, 15 figures (+ appendix)
Accepted for publication in MNRAS. 15 pages, 13 figures
35 pages, 9 figures, 3 tables, 1 appendix. Comments are welcome
Accepted for publication in A&A
25 pages; 20 figures. Accepted for publication in ApJS
Review chapter in "The Pluto System After New Horizons" University of Arizona Press, 2021. this https URL
Accepted for publication in Astronomy & Astrophysics. 17 pages, 11 figures, 2 tables
6 pages, 1 figure, 2 tables
Accepted for publication in A&A Letters.The movie file can be downloaded from this https URL
21 pages, 6 figures
14 pages, 11 figures. Submitted to MNRAS, all comments welcome
18 pages, 13 figures, codes and data available at this https URL , text in portuguese
13 pages, 6 figures, 2 tables
4 pages, 6 figures. In 8th European Conference on Space Debris, 20 April 2021 - 23 April 2021, Darmstadt, Germany, published by ESA Space Debris Office
4 pages, 3 figures. In 8th European Conference on Space Debris, 20 April 2021 - 23 April 2021, Darmstadt, Germany, published by ESA Space Debris Office
35 pages, 21 figures. Accepted for publication in ApJ
29 pages, 14 figures, accepted by Astronomy and Computing
15 pages, 8 figures, accepted for publication in MNRAS
Accepted for publication in ApJS (49 pages; 32 figures)
Accepted to be published in Astronomy and Astrophysics; main-body: 11 pages, 3 figures and 3 tables
17 pages, 16 figures, to be published in A&A
30 pages, 10 figures, 2 tables, accepted for publication in ApJ
21 pages, prepared for submission to EPJ-C
14 pages, 7 figures
12 pages, 13 figures, comments are welcome
9 Pages
24 pages
29 pages, 22 figures, 14 tables, Accepted for Publication in ApJ
11 pages, 10 figures; comments and suggestions are welcome; submitted to MNRAS Github repo: this https URL YouTube: this https URL
21 pages, 3 Figures, Accepted to ApJ
25 pages including appendices, published MNRAS
6 pages, with 2 figures. RAA accepted
9 pages, 9 figures, accepted for publication in Astronomy & Astrophysics
7 pages, 1 figure, 5 tables
6 pages, 8 figures
25 pages, 15 figures, comments welcome
15 pages, 8 figures
12 pages, 8 figures
45 pages, 15 figures
15 pages, 4 figures
18 pages, 14 figures. Accepted for publication in Physics of Plasmas
11 pages, 1 figure
6 pages, 4 figures
18 pages, 6 figures, comments welcome