13 pages, 7 figures, submitted to PRD, comments welcome
We present the first cosmological constraints from analyzing higher-order galaxy clustering on non-linear scales. We use ${\rm S{\scriptsize IM}BIG}$, a forward modeling framework for galaxy clustering analyses that employs simulation-based inference to perform highly efficient cosmological inference using normalizing flows. It leverages the predictive power of high-fidelity simulations and robustly extracts cosmological information from regimes inaccessible with current standard analyses. In this work, we apply ${\rm S{\scriptsize IM}BIG}$ to a subset of the BOSS galaxy sample and analyze the redshift-space bispectrum monopole, $B_0(k_1, k_2, k_3)$, to $k_{\rm max}=0.5\,h/{\rm Mpc}$. We achieve 1$\sigma$ constraints of $\Omega_m=0.293^{+0.027}_{-0.027}$ and $\sigma_8= 0.783^{+0.040}_{-0.038}$, which are more than 1.2 and 2.4$\times$ tighter than constraints from standard power spectrum analyses of the same dataset. We also derive 1.4, 1.4, 1.7$\times$ tighter constraints on $\Omega_b$, $h$, $n_s$. This improvement comes from additional cosmological information in higher-order clustering on non-linear scales and, for $\sigma_8$, is equivalent to the gain expected from a standard analysis on a $\sim$4$\times$ larger galaxy sample. Even with our BOSS subsample, which only spans 10% of the full BOSS volume, we derive competitive constraints on the growth of structure: $S_8 = 0.774^{+0.056}_{-0.053}$. Our constraint is consistent with results from both cosmic microwave background and weak lensing. Combined with a $\omega_b$ prior from Big Bang Nucleosynthesis, we also derive a constraint on $H_0=67.6^{+2.2}_{-1.8}\,{\rm km\,s^{-1}\,Mpc^{-1}}$ that is consistent with early universe constraints.
13 pages, 5 figures, submitted to Nature Astronomy, comments welcome
The 3D distribution of galaxies encodes detailed cosmological information on the expansion and growth history of the Universe. We present the first cosmological constraints that exploit non-Gaussian cosmological information on non-linear scales from galaxy clustering, inaccessible with current standard analyses. We analyze a subset of the BOSS galaxy survey using ${\rm S{\scriptsize IM}BIG}$, a new framework for cosmological inference that leverages high-fidelity simulations and deep generative models. We use two clustering statistics beyond the standard power spectrum: the bispectrum and a convolutional neural network based summary of the galaxy field. We infer constraints on $\Lambda$CDM parameters, $\Omega_b$, $h$, $n_s$, $\Omega_m$, and $\sigma_8$, that are 1.6, 1.5, 1.7, 1.2, and 2.3$\times$ tighter than power spectrum analyses. With this increased precision, we derive constraints on the Hubble constant, $H_0$, and $S_8 = \sigma_8 \sqrt{\Omega_m/0.3}$ that are competitive with other cosmological probes, even with a sample that only spans 10% of the full BOSS volume. Our $H_0$ constraints, imposing the Big Bang Nucleosynthesis prior on the baryon density, are consistent with the early time constraints from the cosmic microwave background (CMB). Meanwhile, our $S_8$ constraints are consistent with weak lensing experiments and similarly lie below CMB constraints. Lastly, we present forecasts to show that future work extending ${\rm S{\scriptsize IM}BIG}$ to upcoming spectroscopic galaxy surveys (DESI, PFS, Euclid) will produce leading $H_0$ and $S_8$ constraints that bridge the gap between early and late time measurements and shed light on current cosmic tensions.
11+5 pages, 8+2 figures
The non-Gaussisan spatial distribution of galaxies traces the large-scale structure of the Universe and therefore constitutes a prime observable to constrain cosmological parameters. We conduct Bayesian inference of the $\Lambda$CDM parameters $\Omega_m$, $\Omega_b$, $h$, $n_s$, and $\sigma_8$ from the BOSS CMASS galaxy sample by combining the wavelet scattering transform (WST) with a simulation-based inference approach enabled by the ${\rm S{\scriptsize IM}BIG}$ forward model. We design a set of reduced WST statistics that leverage symmetries of redshift-space data. Posterior distributions are estimated with a conditional normalizing flow trained on 20,000 simulated ${\rm S{\scriptsize IM}BIG}$ galaxy catalogs with survey realism. We assess the accuracy of the posterior estimates using simulation-based calibration and quantify generalization and robustness to the change of forward model using a suite of 2,000 test simulations. When probing scales down to $k_{\rm max}=0.5~h/\text{Mpc}$, we are able to derive accurate posterior estimates that are robust to the change of forward model for all parameters, except $\sigma_8$. We mitigate the robustness issues with $\sigma_8$ by removing the WST coefficients that probe scales smaller than $k \sim 0.3~h/\text{Mpc}$. Applied to the BOSS CMASS sample, our WST analysis yields seemingly improved constraints obtained from a standard PT-based power spectrum analysis with $k_{\rm max}=0.25~h/\text{Mpc}$ for all parameters except $h$. However, we still raise concerns on these results. The observational predictions significantly vary across different normalizing flow architectures, which we interpret as a form of model misspecification. This highlights a key challenge for forward modeling approaches when using summary statistics that are sensitive to detailed model-specific or observational imprints on galaxy clustering.
12+2 pages, 7+1 figures. The template bank described here will be publicly available at this https URL
Searches for gravitational wave events use models, or templates, for the signals of interest. The templates used in current searches in the LIGO-Virgo-Kagra (LVK) data model the dominant quadrupole mode $(\ell,m)=(2,2)$ of the signals, and omit sub-dominant higher-order modes (HM) such as $(\ell,m)=(3,3)$, $(4,4)$, which are predicted by general relativity. Hence, these searches could lose sensitivity to black hole mergers in interesting parts of parameter space, such as systems with high-masses and asymmetric mass ratios. We develop a new strategy to include HM in template banks that exploits the natural connection between the modes. We use a combination of post-Newtonian formulae and machine learning tools to model aligned-spin $(3,3)$, $(4,4)$ waveforms corresponding to a given $(2,2)$ waveform. Each of these modes can be individually filtered against the data to yield separate timeseries of signal-to-noise ratios (SNR), which can be combined in a relatively inexpensive way to marginalize over extrinsic parameters of the signals. This leads to a HM search pipeline whose matched-filtering cost is just $\approx 3\times$ that of a quadrupole-only search (in contrast to being $\approx\! 100 \times$, as in previously proposed HM search methods). Our method is effectual and is generally applicable for template banks constructed with either stochastic or geometric placement techniques. Additionally, we discuss compression of $(2,2)$-only geometric-placement template banks using machine learning algorithms.
33 pages, 20 figures. Astrophysical Journal, accepted
Aligned interstellar grains produce polarized extinction (observed at wavelengths from the far-ultraviolet to the mid-infrared), and polarized thermal emission (observed at far-infrared and submm wavelengths). The grains must be quite nonspherical, but the actual shapes are unknown. The \emph{relative} efficacy for aligned grains to produce polarization at optical vs.\ infrared wavelengths depends on particle shape. The discrete dipole approximation is used to calculate polarization cross sections for 20 different convex shapes, for wavelengths from $0.1\mu$m to $100\mu$m, and grain sizes $a_{\rm eff}$ from $0.05\mu$m to $0.3\mu$m. Spheroids, cylinders, square prisms, and triaxial ellipsoids are considered. Minimum aspect ratios required by the observed starlight polarization are determined. Some shapes can also be ruled out because they provide too little or too much polarization at far-infrared and sub-mm wavelengths. The ratio of $10\mu$m polarization to integrated optical polarization is almost independent of grain shape, varying by only $\pm8\%$ among the viable convex shapes; thus, at least for convex grains, uncertainties in grain shape cannot account for the discrepancy between predicted and observed 10$\mu$m polarization toward Cyg OB2-12.
Submitted to ApJ, main body is 35 pages of which ~half are full-page figures, comments welcome
The 3D geometry of high-redshift galaxies remains poorly understood. We build a differentiable Bayesian model and use Hamiltonian Monte Carlo to efficiently and robustly infer the 3D shapes of star-forming galaxies in JWST-CEERS observations with $\log M_*/M_{\odot}=9.0-10.5$ at $z=0.5-8.0$. We reproduce previous results from HST-CANDELS in a fraction of the computing time and constrain the mean ellipticity, triaxiality, size and covariances with samples as small as $\sim50$ galaxies. We find high 3D ellipticities for all mass-redshift bins suggesting oblate (disky) or prolate (elongated) geometries. We break that degeneracy by constraining the mean triaxiality to be $\sim1$ for $\log M_*/M_{\odot}=9.0-9.5$ dwarfs at $z>1$ (favoring the prolate scenario), with significantly lower triaxialities for higher masses and lower redshifts indicating the emergence of disks. The prolate population traces out a ``banana'' in the projected $b/a-\log a$ diagram with an excess of low $b/a$, large $\log a$ galaxies. The dwarf prolate fraction rises from $\sim25\%$ at $z=0.5-1.0$ to $\sim50-80\%$ at $z=3-8$. If these are disks, they cannot be axisymmetric but instead must be unusually oval (triaxial) unlike local circular disks. We simultaneously constrain the 3D size-mass relation and its dependence on 3D geometry. High-probability prolate and oblate candidates show remarkably similar S\'ersic indices ($n\sim1$), non-parametric morphological properties and specific star formation rates. Both tend to be visually classified as disks or irregular but edge-on oblate candidates show more dust attenuation. We discuss selection effects, follow-up prospects and theoretical implications.
29 pages, 11 figures. For the reference in the abstract (de Santi et al. 2023) see arXiv:2302.14101
It has been recently shown that a powerful way to constrain cosmological parameters from galaxy redshift surveys is to train graph neural networks to perform field-level likelihood-free inference without imposing cuts on scale. In particular, de Santi et al. (2023) developed models that could accurately infer the value of $\Omega_{\rm m}$ from catalogs that only contain the positions and radial velocities of galaxies that are robust to uncertainties in astrophysics and subgrid models. However, observations are affected by many effects, including 1) masking, 2) uncertainties in peculiar velocities and radial distances, and 3) different galaxy selections. Moreover, observations only allow us to measure redshift, intertwining galaxies' radial positions and velocities. In this paper we train and test our models on galaxy catalogs, created from thousands of state-of-the-art hydrodynamic simulations run with different codes from the CAMELS project, that incorporate these observational effects. We find that, although the presence of these effects degrades the precision and accuracy of the models, and increases the fraction of catalogs where the model breaks down, the fraction of galaxy catalogs where the model performs well is over 90 %, demonstrating the potential of these models to constrain cosmological parameters even when applied to real data.
14 pages, 4 figures. A previous version of the paper was published in the ICML 2023 Workshop on Machine Learning for Astrophysics
We present the first simulation-based inference (SBI) of cosmological parameters from field-level analysis of galaxy clustering. Standard galaxy clustering analyses rely on analyzing summary statistics, such as the power spectrum, $P_\ell$, with analytic models based on perturbation theory. Consequently, they do not fully exploit the non-linear and non-Gaussian features of the galaxy distribution. To address these limitations, we use the {\sc SimBIG} forward modelling framework to perform SBI using normalizing flows. We apply SimBIG to a subset of the BOSS CMASS galaxy sample using a convolutional neural network with stochastic weight averaging to perform massive data compression of the galaxy field. We infer constraints on $\Omega_m = 0.267^{+0.033}_{-0.029}$ and $\sigma_8=0.762^{+0.036}_{-0.035}$. While our constraints on $\Omega_m$ are in-line with standard $P_\ell$ analyses, those on $\sigma_8$ are $2.65\times$ tighter. Our analysis also provides constraints on the Hubble constant $H_0=64.5 \pm 3.8 \ {\rm km / s / Mpc}$ from galaxy clustering alone. This higher constraining power comes from additional non-Gaussian cosmological information, inaccessible with $P_\ell$. We demonstrate the robustness of our analysis by showcasing our ability to infer unbiased cosmological constraints from a series of test simulations that are constructed using different forward models than the one used in our training dataset. This work not only presents competitive cosmological constraints but also introduces novel methods for leveraging additional cosmological information in upcoming galaxy surveys like DESI, PFS, and Euclid.
12 pages, 5 figures
Several large JWST blank field observing programs have not yet discovered the first galaxies expected to form at $15 \leq z \leq 20$. This has motivated the search for more effective survey strategies that will be able to effectively probe this redshift range. Here, we explore the use of gravitationally lensed cluster fields, that have historically been the most effective discovery tool with HST. In this paper, we analyze the effectiveness of the most massive galaxy clusters that provide the highest median magnification factor within a single JWST NIRCam module in uncovering this population. The results of exploiting these lensing clusters to break the $z > 15$ barrier are compared against the results from large area, blank field surveys such as JADES and CEERS in order to determine the most effective survey strategy for JWST. We report that the fields containing massive foreground galaxy clusters specifically chosen to occupy the largest fraction of a single NIRCam module with high magnification factors in the source plane, whilst containing all multiple images in the image plane within a single module provide the highest probability of both probing the $15 \leq z \leq 20$ regime, as well as discovering the highest redshift galaxy possible with JWST. We also find that using multiple massive clusters in exchange for shallower survey depths is a more time efficient method of probing the $z > 15$ regime.
23 pages, 9 figures, 3 tables, accepted for publication in RAA
Using archival {\it Fermi}-LAT data with a time span of $\sim12$ years, we study the population of Millisecond Pulsars (MSPs) in Globular Clusters (GlCs) and investigate their dependence on cluster dynamical evolution in the Milky Way Galaxy. We show that the $\gamma$-ray luminosity ($L_{\gamma}$) and emissivity ($\epsilon_{\gamma}=L_{\gamma}/M$) are good indicators of the population and abundance of MSPs in GlCs, and they are highly dependent on the dynamical evolution history of the host clusters. Specifically speaking, the dynamically older GlCs with more compact structures are more likely to have larger $L_{\gamma}$ and $\epsilon_{\gamma}$, and these trends can be summarized as strong correlations with cluster stellar encounter rate $\Gamma$ and the specific encounter rate ($\Lambda=\Gamma/M$), with $L_{\gamma}\propto \Gamma^{0.70\pm0.11}$ and $\epsilon_{\gamma}\propto \Lambda^{0.73\pm0.13}$ for dynamically normal GlCs. However, as GlCs evolve into deep core collapse, these trends are found to be reversed, implying that strong encounters may have lead to the ejection of MSPs from core-collapsed Systems. Besides, the GlCs are found to exhibit larger $\epsilon_{\gamma}$ with increasing stellar mass function slope, decreasing tidal radius and distances from the Galactic Center (GC). These correlations indicate that, as GlCs losing kinetic energy and spiral in towards GC, tidal stripping and mass segregation have a preference in leading to the loss of normal stars from GlCs, while MSPs are more likely to concentrate to cluster center and be deposited into the GC. Moreover, we gauge $\epsilon_{\gamma}$ of GlCs is $\sim10-1000$ times larger than the Galactic bulge, the latter is thought to reside thousands of unresolved MSPs and may responsible for the GC $\gamma$-ray excess, which support that GlCs are generous contributors to the population of MSPs in the GC.
12 pages of main text, 4 figures, 1 table; submitted to ApJ
Determining how galactic environment, especially the high gas densities and complex dynamics in bar-fed galaxy centers, alters the star formation efficiency (SFE) of molecular gas is critical to understanding galaxy evolution. However, these same physical or dynamical effects also alter the emissivity properties of CO, leading to variations in the CO-to-H$_2$ conversion factor ($\alpha_\rm{CO}$) that impact the assessment of the gas column densities and thus of the SFE. To address such issues, we investigate the dependence of $\alpha_\rm{CO}$ on local CO velocity dispersion at 150-pc scales using a new set of dust-based $\alpha_\rm{CO}$ measurements, and propose a new $\alpha_\rm{CO}$ prescription that accounts for CO emissivity variations across galaxies. Based on this prescription, we estimate the SFE in a sample of 65 galaxies from the PHANGS-ALMA survey. We find increasing SFE towards high surface density regions like galaxy centers, while using a constant or metallicity-based $\alpha_\rm{CO}$ results in a more homogeneous SFE throughout the centers and disks. Our prescription further reveals a mean molecular gas depletion time of 700 Myr in the centers of barred galaxies, which is overall 3-4 times shorter than in non-barred galaxy centers or the disks. Across the galaxy disks, the depletion time is consistently around 2-3 Gyr regardless of the choice of $\alpha_\rm{CO}$ prescription. All together, our results suggest that the high level of star formation activity in barred centers is not simply due to an increased amount of molecular gas but also an enhanced SFE compared to non-barred centers or disk regions.
These are papers reserved by people for discussion at a later date. All reservations are kept for 2 days after the date of the reservation.
13 pages, 7 figures, submitted to PRD, comments welcome
Invited peer-reviewed article (author version) for a theme issue of Phil. Trans. R. Soc. A on 'Astronomy from the Moon: the next decades (Part 2)' eds. I. Crawford, M. Elvis, J. Silk and J. Zarnecki. Comments/collaboration welcome
19 pages, 10 figures. Submitted to MNRAS. Comments welcome!
10 pages, 6 figures, accepted for publication in Astronomy and Astrophysics (A&A)
7 pages with 4 figures, along with Supplementary Material; Submitted
Prepared for submission to JCAP. 28 pages, 15 figures
5 pages, 4 figures, plus appendices
7 pages, 10 figures. Submitted to MNRAS
13 pages and 11 figures. Submitted to A&A. Comments welcome
26 pages, 13 pages, submitted to PASP
Submitted to MNRAS
16 pages, 13 figures, submitted to MNRAS
13 pages, 5 figures, 1 table, accepted for publication in The Planetary Science Journal
12 pages, 11 figures. Submitted to MNRAS
39 pages, 16 figures
19 pages, 9 figures, 3+2 tables. Comments welcome
Accepted to MNRAS
23 pages, 16 figures, 1 table. Submitted to AAS Journals, comments welcome. Associated catalog of high precision, Cannon-rederived abundances for GALAH giants to be made publicly available upon acceptance and available now upon request. See Walsen et al. 2023 for a complementary, high precision, Cannon-rederived abundance catalog for GALAH solar twins
23 pages, 7 figures, and 2 tables. Accepted for publication in PSJ
White paper developed by the Early Career Perspectives Working Group for the NASA SMD Bridge Program Workshop. 11 pages
9 pages, 5 figures
4 pages, 5 figures, proceedings of the XLV annual meeting of the Brazilian Astronomical Society
11 pages, 6 figures, plus appendix. MNRAS submitted. Comments welcome!
13 pages, 10 figures, Publications of the Astronomical Society of the Pacific
16 figures, 18 pages, accepted for publication in Astronomy and Astrophysics
7 pages, 5 figures, Proceedings of the 40th Annual Meeting of the Astronomical Society of India
20 pages, 16 figures, submitted to MNRAS
36 pages, 31 figures, 3 tables, accepted for publication in ApJ
Eleven pages. Accepted for publication in MNRAS
6 pages, 5 figures, submitted to A&A Letters
24 pages, invited review talk, Proceedings of the 38th International Cosmic Ray Conference (ICRC2023), 26 July - 3 August, 2023, Nagoya, Japan. The DOI link provides an access to the slides (Supplementary files)
30 pages, 18 figures, submitted to ApJL
Paper 10 of the ALMA eDisk Large Program. Accepted for publication in ApJ
15 pages, 13 figures (2 appendix figures), Accepted for publication in MNRAS
11 pages, 11 figures, 8 tables, comments are welcome
14 pages, 14 figures, submitted to ApJ
Accepted for publication in MNRAS
10 pages, 2 figures
9 pages, 5 figures, ApJ accepted
52 pages, 6 figures, submitted to the Journal of Quantitative Spectroscopy and Radiative transfer (JQSRT) on October 20th 2023
6 pages, 4 figures and 3 tables, accepted for publication in New Astronomy
Proceeding to the International Cosmic Ray Conference, ICRC 2023, Nagoya, Japan
12 pages, 11 figures
Submitted to MNRAS
7 pages, 3 figures. Submitted to A&A
20 pages, 31 figures, accepted for publication in MNRAS
On the revision in MNRAS
21 pages, 12 figures. Monthly Notices of the Royal Astronomical Society, in the press
15 Pages, 16 Figures, 2 Machine Readable Tables
22 pages, 13 figures
17 pages, 10 figures, submitted to ApJ
10 pages, 8 figures. Submitted to AO4ELT7 conference proceedings
Will be submitted in one week to the Proceedings of IAU Symposium 384: Planetary Nebulae: a Universal Toolbox in the Era of Precision Astrophysics. Eds: O. De Marco, A. Zijlstra, R. Szczerba
8 pages, 4 figures
8 pages, 3 Figures, 1 Table. this https URL
15 pages, 4 figures, submitted to Physical Review D
8 pages, 4 figures, 1 table, Submitted to ApJ Letters
Accepted for publication in MNRAS
14 pages,10 figures
9 pages, 14 figures
Accepted for publication in MNRAS 24/10/23, 14 pages + 6 pages supplementary material, 13 figures
12 pages, 9 figures
17 pages, 5 figures and 1 table. Submitted to ApJ on September 9
17 pages, 15 figures, submitted
7 pages, 7 figures, submitted to A&A
20 pages, 17 figures
10 pages, 7 figures, Accepted by the Monthly Notices of the Royal Astronomical Society
For submission to MNRAS; comments welcome. 21 pages, 13 figures
accepted to MNRAS
Accepted into The Planetary Science Journal (35 pages, 12 Figures, 4 Tables)
19 pages, 8 figures, submitted to ApJ
8 pages, Presented at the 38th International Cosmic Ray Conference (ICRC2023)
26 pages, 13 figures, ApJ Submitted, preprint
White Paper in support of a mission concept to be submitted for the 2023 NASA Astrophysics Probes opportunity. This White Paper will be updated when required. 30 pages, 25 figures
Invited chapter for the edited book Hubble Constant Tension (Eds. E. Di Valentino and D. Brout, Springer Singapore, expected in 2024)
22 pages, 12 figures, submitted to Phys. Rev. Fluids
23 pages, 0 figures
12 pages, 5 figures
7 pages, 5 figures (8 panels). Proceedings of the CGS-17 conference. To be published in EPJ Web of Conferences
18 pages, 1 figure
23+20 pages, 5 appendices
5 pages, 6 figures
10 pages, 5 figures