arXiv subjects

S. Mobina Hosseini

Publications and source records attributed to S. Mobina Hosseini.

5 recordsLinked to original sources

arXiv2026

The MAGPI Survey: Evidence for Non-Universal Resolved Dust Attenuation Relations Beyond the Local Universe

We study the spatially resolved relation between dust attenuation ($A_V$) and star formation rate surface density ($Σ_{\mathrm{SFR}}$) in galaxies from the MAGPI survey ($0.25 < z < 0.42$). Using Balmer-decrement-based attenuation maps for 178 galaxies, we investigate whether the locally calibrated resolved $A_V$--$Σ_{\mathrm{SFR}}$ relation remains valid at intermediate redshift by comparing MAGPI with the local relation measured from MaNGA. We find a clear positive correlation between $A_V$ and $Σ_{\mathrm{SFR}}$ in MAGPI, with systematically higher attenuation than in MaNGA at fixed $Σ_{\mathrm{SFR}}$. After matching galaxies in stellar mass ($M_{*}$) and offset from the star-forming main sequence ($Δ$SFMS), MAGPI galaxies remain more attenuated than MaNGA galaxies at fixed $Σ_{\mathrm{SFR}}$. The attenuation excess is strongest for galaxies below the SFMS ($ΔA_V \sim 0.40$ mag), weaker for galaxies on the SFMS ($ΔA_V \sim 0.28$ mag), and minimal for galaxies above the SFMS ($ΔA_V \sim 0.07$ mag). The dependence of the offset on $Δ$SFMS suggests that nebular attenuation on kpc scales is regulated not only by local star formation activity, but also by the global evolutionary state of the host galaxy. Together, these results indicate that the resolved $A_V$--$Σ_{\mathrm{SFR}}$ relation is not universal, and that locally calibrated attenuation relations may not fully describe galaxies at intermediate redshift. This highlights the need for attenuation calibrations that account for galaxy population and redshift when interpreting spatially resolved galaxy properties.

astro-ph.GA↗

arXiv2025

Uncertainty-Aware Neural Networks for Fuzzy Dark Matter Model Selection from \texorpdfstring{$x_{\rm HI}$}{x_HI} Measurements

The nature of dark matter remains a central question in cosmology, with fuzzy dark matter (FDM) models offering a compelling alternative to the cold dark matter (CDM) paradigm. We explore FDM scenarios by performing 21-cm simulations across a parameter space with \texorpdfstring{$f_{\rm FDM} \in [0.02, 0.10]$}{f_FDM in [0.02, 0.10]} and \texorpdfstring{$m_{\rm FDM} \in [10^{-24}, 10^{-21}]\,\mathrm{eV}$}{m_FDM in [10^-24, 10^-21] eV}, obtaining global neutral hydrogen fractions (\texorpdfstring{$x_{\rm HI}$}{x_HI}) for each model. Observational \texorpdfstring{$x_{\rm HI}$}{x_HI} data and associated uncertainties from JWST are incorporated by estimating full probability density functions (PDFs) for both \texorpdfstring{$x_{\rm HI}$}{x_HI} and redshift \texorpdfstring{$z$}{z} using Bayesian inference with the No-U-Turn Sampler (NUTS), yielding non-Gaussian multivariate uncertainty distributions. A hybrid machine learning framework is then trained on these observational PDFs to learn both central values and correlated uncertainties in \texorpdfstring{$x_{\rm HI}$}{x_HI} and \texorpdfstring{$z$}{z}, iteratively refining its parameters in each training epoch through direct incorporation of the multivariate PDFs derived from observational constraints. We then compare the simulation outputs to the machine-learned observational trends to identify the most consistent models. Our results indicate that FDM models with \texorpdfstring{$m_{\rm FDM} \simeq 10^{-22}\,\mathrm{eV}$}{m_FDM approx 10^-22 eV} and \texorpdfstring{$f_{\rm FDM} \simeq 0.04$}{f_FDM approx 0.04} best match current data, while lighter masses are strongly constrained. By integrating simulations and machine learning in an uncertainty-aware framework, this work explores the physics of the early Universe and guides future studies of 21-cm cosmology and reionization.

astro-ph.CO↗

arXiv2025

Stacked Hybrid RNN-CNN Reconstruction of X-ray Influence on 21-cm Brightness Temperature

The X-ray photons substantially affect the thermal and ionization states of the intergalactic medium (IGM) during the Epoch of Reionization (EoR), thereby significantly influencing the 21-cm line observables such as its sky-averaged (global) brightness temperature. Nevertheless, the complicated dependency of astrophysical processes on a broad spectrum of parameters, including X-ray efficiency, spectral characteristics, and gas dynamics, makes precisely simulating the effect of X-ray flux challenging. Traditional approaches, including N-body and hydrodynamical simulations, are computationally intensive and struggle to explore high-dimensional parameter spaces efficiently. We present a stacked hybrid model trained on a specific simulation intended to reconstruct the effect of X-ray flux on the global 21-cm brightness temperature during the EoR. Along with Convolutional Neural Networks (CNNs), this architecture combines two substantial forms of recurrent neural networks (RNNs), Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), therefore enabling fast adaptation to several X-ray flux levels. Without demanding repeated simulations, this emulator preserves temporal and spatial dependencies and generalizes to unseen parameter combinations. This matter reduces computation time by a factor of one million while preserving excellent prediction accuracy of 99.93\%, facilitating studies on high-dimensional parameter inference and sensitivity with an error margin of less than 0.35 mK. Our LSTM-GRU-CNN emulator combines recurrent and convolutional architectures to enable a robust and scalable analysis of X-ray heating effects on the global 21-cm brightness temperature during the EoR.

astro-ph.IM↗

arXiv2024

SVR Algorithm as a Tool for More Optimal Intergalactic Medium Simulation in the Epoch of Reionization

All kinds of simulations of the intergalactic medium, such as hydrodynamic simulation, N-body simulation, numerical and semi-numerical simulation, etc., have been used to realize the history of this medium. In addition, emulators also have become widely used in recent years. Especially because they are very fast, they are used in many works instead of actual complete simulations. Emulators are trained with the help of simulator results and can work with very high accuracy similar to real simulators. Usually, reliable machine learning algorithms, such as neural networks, are used to program these emulators. In this work, we show that one of the best machine learning algorithms that can be used in general and have extremely high accuracy is the Support Vector Regression algorithm. This algorithm works better than the Multilayer Perceptron algorithm not only from the practical point of view but also from the theoretical point of view. To prove this issue, we have considered the 21SSD hydrodynamical simulation in addition to the theoretical arguments, and we have used both algorithms to be trained by this simulation for comparison. Finally, we have shown that the Support Vector Regression algorithm can be a much better and more accurate algorithm than neural network algorithms in future emulations, and by mastering it, one can neglect other algorithms with full confidence. Although this work is focused only on an intergalactic medium simulation in the Epoch of Reionization, it can be used for all other simulations regardless of their type. In other words, it can be employed for all hydrodynamic simulations, N-body simulations, etc. in all cosmic epochs and rely on its results.

astro-ph.CO↗

arXiv2023

A New Constraint on the Simulation of the Intergalactic Medium through the Evolution of the Neutral Hydrogen Fraction in the Epoch of Reionization

The thermal history of the intergalactic medium is full of extremely useful data in the field of astrophysics and cosmology. In other words, by examining this environment in different redshifts, the effects of cosmology and astrophysics can be observed side by side. Therefore, simulation is our very powerful tool to reach a suitable model for the intergalactic medium, both in terms of cosmology and astrophysics. In this work, we have simulated the intergalactic medium with the help of the 21cmFAST code and compared the evolution of the neutral hydrogen fraction in different initial conditions. Considerable works arbitrarily determine many important effective parameters in the thermal history of the intergalactic medium without any constraints, and usually, there is a lot of flexibility for modeling. Nonetheless, in this work, by focusing on the evolution of the neutral hydrogen fraction in different models and comparing it with observational data, we have eliminated many models and introduced only limited simulation models that could confirm the observations with sufficient accuracy. This issue becomes thoroughly vital from the point that, in addition to restricting the models through the neutral hydrogen fraction, it can also impose restrictions on the parameters affecting its changes. However, we hope that in future works, by enhancing the observational data and increasing their accuracy, more compatible models with the history of the intergalactic medium can be achieved.

astro-ph.CO↗