11 pages, 7 figures
Kinetic approaches are generally accurate in dealing with microscale plasma physics problems but are computationally expensive for large-scale or multiscale systems. One of the long-standing problems in plasma physics is the integration of kinetic physics into fluid models, which is often achieved through sophisticated analytical closure terms. In this study, we successfully construct a multi-moment fluid model with an implicit fluid closure included in the neural network using machine learning. The multi-moment fluid model is trained with a small fraction of sparsely sampled data from kinetic simulations of Landau damping, using the physics-informed neural network (PINN) and the gradient-enhanced physics-informed neural network (gPINN). The multi-moment fluid model constructed using either PINN or gPINN reproduces the time evolution of the electric field energy, including its damping rate, and the plasma dynamics from the kinetic simulations. For the first time, we introduce a new variant of the gPINN architecture, namely, gPINN$p$ to capture the Landau damping process. Instead of including the gradients of all the equation residuals, gPINN$p$ only adds the gradient of the pressure equation residual as one additional constraint. Among the three approaches, the gPINN$p$-constructed multi-moment fluid model offers the most accurate results. This work sheds new light on the accurate and efficient modeling of large-scale systems, which can be extended to complex multiscale laboratory, space, and astrophysical plasma physics problems.
28 pages, 6 figures
Simulation-Based Inference of Galaxies (${\rm S{\scriptsize IM}BIG}$) is a forward modeling framework for analyzing galaxy clustering using simulation-based inference. In this work, we present the ${\rm S{\scriptsize IM}BIG}$ forward model, which is designed to match the observed SDSS-III BOSS CMASS galaxy sample. The forward model is based on high-resolution ${\rm Q{\scriptsize UIJOTE}}$ $N$-body simulations and a flexible halo occupation model. It includes full survey realism and models observational systematics such as angular masking and fiber collisions. We present the "mock challenge" for validating the accuracy of posteriors inferred from ${\rm S{\scriptsize IM}BIG}$ using a suite of 1,500 test simulations constructed using forward models with a different $N$-body simulation, halo finder, and halo occupation prescription. As a demonstration of ${\rm S{\scriptsize IM}BIG}$, we analyze the power spectrum multipoles out to $k_{\rm max} = 0.5\,h/{\rm Mpc}$ and infer the posterior of $\Lambda$CDM cosmological and halo occupation parameters. Based on the mock challenge, we find that our constraints on $\Omega_m$ and $\sigma_8$ are unbiased, but conservative. Hence, the mock challenge demonstrates that ${\rm S{\scriptsize IM}BIG}$ provides a robust framework for inferring cosmological parameters from galaxy clustering on non-linear scales and a complete framework for handling observational systematics. In subsequent work, we will use ${\rm S{\scriptsize IM}BIG}$ to analyze summary statistics beyond the power spectrum including the bispectrum, marked power spectrum, skew spectrum, wavelet statistics, and field-level statistics.
9 pages, 5 figures
We present the first-ever cosmological constraints from a simulation-based inference (SBI) analysis of galaxy clustering from the new ${\rm S{\scriptsize IM}BIG}$ forward modeling framework. ${\rm S{\scriptsize IM}BIG}$ leverages the predictive power of high-fidelity simulations and provides an inference framework that can extract cosmological information on small non-linear scales, inaccessible with standard analyses. In this work, we apply ${\rm S{\scriptsize IM}BIG}$ to the BOSS CMASS galaxy sample and analyze the power spectrum, $P_\ell(k)$, to $k_{\rm max}=0.5\,h/{\rm Mpc}$. We construct 20,000 simulated galaxy samples using our forward model, which is based on high-resolution ${\rm Q{\scriptsize UIJOTE}}$ $N$-body simulations and includes detailed survey realism for a more complete treatment of observational systematics. We then conduct SBI by training normalizing flows using the simulated samples and infer the posterior distribution of $\Lambda$CDM cosmological parameters: $\Omega_m, \Omega_b, h, n_s, \sigma_8$. We derive significant constraints on $\Omega_m$ and $\sigma_8$, which are consistent with previous works. Our constraints on $\sigma_8$ are $27\%$ more precise than standard analyses. This improvement is equivalent to the statistical gain expected from analyzing a galaxy sample that is $\sim60\%$ larger than CMASS with standard methods. It results from additional cosmological information on non-linear scales beyond the limit of current analytic models, $k > 0.25\,h/{\rm Mpc}$. While we focus on $P_\ell$ in this work for validation and comparison to the literature, ${\rm S{\scriptsize IM}BIG}$ provides a framework for analyzing galaxy clustering using any summary statistic. We expect further improvements on cosmological constraints from subsequent ${\rm S{\scriptsize IM}BIG}$ analyses of summary statistics beyond $P_\ell$.
46 pages, 19 figures, to be published by the AJ
We present wide-field and high-sensitivity CO(1-0) molecular line observations toward the Cassiopeia region, using the 13.7m millimeter telescope of the Purple Mountain Observatory (PMO). The CO observations reveal a large-scale highly filamentary molecular cloud within the Galactic region of 132\fdg0\,$\geq$\,$l$\,$\geq$\,122\fdg0 and -1\fdg0\,$\leq$\,$b$\,$\leq$\,3\fdg0 and the velocity range from approximately +1 to +4 km/s. The measured length of the large-scale filament, referred to as the Cassiopeia Filament, is about 390 pc. The observed properties of the Cassiopeia Filament, such as length, column density, and velocity gradient, are consistent with those synthetic large-scale filaments in the inter-arm regions. Based on its observed properties and location on the Galactic plane, we suggest that the Cassiopeia Filament is a spur of the Local arm, which is formed due to the galactic shear. The western end of the Cassiopeia Filament shows a giant arc-like molecular gas shell, which is extending in the velocity range from roughly -1 to +7 km/s. Finger-like structures, with systematic velocity gradients, are detected in the shell. The CO kinematics suggest that the large shell is expanding at a velocity of ~6.5 km/s. Both the shell and finger-like structures outline a giant bubble with a radius of ~16 pc, which is likely produced by stellar wind from the progenitor star of a supernova remnant. The observed spectral linewidths suggest that the whole Cassiopeia Filament was quiescent initially until its west part was blown by stellar wind and became supersonically turbulent.
We report the discovery of a very rare phenomenon, a multiply-imaged gravitationally lensed Type Ia supernova (SNe Ia), "SN Zwicky", a.k.a. SN 2022qmx, magnified nearly twenty-five times by a foreground galaxy. The system was identified as intrinsically bright thanks to the "standard candle" nature of SNe Ia. Observations with high-spatial resolution instruments resolved a system with four nearly simultaneous images, with an Einstein radius of only $\theta_E =0.167"$, corresponding to a lens mass of $8\cdot 10^9$ solar masses within a physical size below $0.8$ kiloparsecs. A smooth lens model fails to reproduce the image flux ratios, suggesting significant additional magnification from compact objects. Given the small image splitting and a relatively faint deflecting galaxy, the lensing system would not have been found through the angular separation technique generally used in large imaging surveys.
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8 pages, 4 figures, 1 table. Submitted to ApJ Letters
Accepted for publication in ApJS
19 pages, 15 figures
Submitted to AAS journals
17 pages. 12 figures. Re-submitted to A&A after minor revision. Comments welcome
submitted to A&A
10 pages, 2 figures
Accepted for publication in A&A. 20 pages, 8 figures
12 pages plus appendices. Accepted for publication in MNRAS
7 pages, accepted at MNRAS
3 figures, 1 table; accepted to Machine Learning and the Physical Sciences - Workshop at the 36th conference on Neural Information Processing Systems (NeurIPS)
10 pages, 6 figures, 2 tables; accepted for publication in MNRAS
accepted by ApJ
Accepted for publication in MNRAS; 16 pages, 11 figures
16 pages, 7 figures, accepted ApJ
15 pages, 11 figures, accepted for publication in AJ
Submitted to MNRAS
Accepted for publication in The Planetary Science Journal
Invited Chapter of Section "Active Galactic Nuclei in X- and Gamma-rays" (Section Editors: A. De Rosa and C. Vignali) of the "Handbook of X-ray and Gamma-ray Astrophysics" (Editors: C. Bambi and A. Santangelo), Springer Nature
Accepted for publication in MNRAS. 13 pages, 9 figures
Projet de fin d'\'etudes 2014, ISAE-Supaero
33 pages, 12 figures, accepted for publication in ApJ
10 pages, 5 figures; invited review to appear in the Proceedings of IAU Symposium 373 - Resolving the rise and fall of star formation in galaxies
Submitted to A&A. Main text: 23 pages, 35 figures. Four appendices (17 pages) with 38 figures
15 pages, 14 figures (including appendix), submitted to ApJ; comments welcome
6 pages with 4 figures; comments welcome
17 pages, 7 figuers, accepted for publication in MNRAS-MJ
12 pages, 6 figures, accepted in A&A
5 pages, 5 figures, submitted to MNRAS Letters (comments are welcome)
23 pages, 12 figures, 9 tables. Submitted to the Astrophysical Journal. Comments welcome!
18 pages, 4 figures, Proceedings of the 9th Conference on New Developments In Photodetection (NDIP20), Troyes (France), 04-08 July 2022. Published in Nuclear Instruments and Methods in Physics Research - section A (NIM-A)
10 pages, 8 Figures, accepted for publication in A&A
17 pages, 8 figures. Accepted for publication in MNRAS. arXiv admin note: text overlap with arXiv:2103.10302
26 pages, Accepted for publication in The Astrophysical Journal
38 pages, 21 figures. Accepted for publication in ApJ
15 pages, 12 figures
This work corresponds to the presentation at the ICNFP 2022 at Kolymbari, Crete, in September 2022. The proceedings will be published in Physica Scripta. arXiv admin note: text overlap with arXiv:2108.07527
11 figures, 12 tables; to be submitted to the AAS Journals in ~a week. Comments welcome!
13 pages, 10 figures, submitted to MNRAS
Submitted to: New Astronomy Reviews
25 pages, 18 figures, 2 tables; submitted to MNRAS
To appear in Geophysical and Astrophysical Fluid Dynamics [Accepted 2022-10-14]
Accepted for publication in PASP. 55 pages, 29 figures, 10 pages of Appendices
9 pages, 2 figures
30 pages, 4 figures. Invited chapter for the edited book "Regular Black Holes: Towards a New Paradigm of the Gravitational Collapse'' (Ed. C. Bambi, Springer Singapore, expected in 2023)
5 latex pages, final version for journal publication
57 pages, 23 figures, submitted to Prog. Part. Nucl. Phys
PhD thesis (defended 17/06/2022, Universit\'e Paris Cit\'e), 267 pages, 17 figures, 1 appendix, short introduction in French. Based on arXiv:2012.10218 , arXiv:2103.14744 , arXiv:2103.14750 , arXiv:2204.04107 , arXiv:2205.07746
8 pages, 4 figures, 2 tables plus appendices