arXiv subjects

Amin Salehi

Publications and source records attributed to Amin Salehi.

At least 19 recordsLinked to original sources

arXiv2026

Coordinated Dynamic Operation of Integrated Electrolyzer-Compressor Systems

The increasing interaction between power and hydrogen sectors highlights the importance of coordinated operation of electrolyzers and electric-driven compressor stations (EDCSs). This becomes particularly of higher importance under transient disturbances. However, coordinated dynamic interactions of these coupled subsystems remain largely unexplored. This article addresses such gap by developing a dynamic model for an integrated electrolyzer-EDCS system and designing appropriate PID control schemes to address the potential disturbances affecting either component. To this end, linearized models of the electrolyzer and EDCS are first derived to enable systematic controller design. Then, two PID controllers, representing conservative and fast-tracking designs, are developed to coordinate the system response. The developed coordinated model is examined and verified under four different cases. The results demonstrate the effectiveness of the proposed model under disturbances from the compressor driver or the electrolyzer. Controlling the electrolyzer flow in response to EDCS disturbances coordinates system dynamics and mitigates undesirable transient fluctuations. Conversely, under electrolyzer disturbances, regulating the EDCS torque eliminates inconsistent responses in pressure, flow, and rotational speed, while preventing hazardous transient undershoots and overshoots. Overall, the proposed framework guarantees transient stability and operational reliability of the integrated electrolyzer-EDCS system.

eess.SY↗

arXiv2026

Comparative Analysis of Linepack Impact in Hydrogen and Natural Gas Networks under Dynamic Operating Conditions

Linepack is a critical buffer in gas networks, providing short-term storage and operational flexibility. This paper presents a comparative dynamic analysis of the linepack impact in hydrogen (H2) and natural gas (CH4) networks under compressor contingency conditions. A three-day dynamic simulation is conducted for a CH4 network and a H2 network integrated with a power system. Two cases are investigated: Case 1 with identical and Case 2 with different pipe inner diameters in CH4 and H2 networks. The results in both cases show that H2 exhibits faster transient recovery after the compressor contingency, although its linepack is less than that of CH4. On the other hand, depending on the selected pipe diameter, pressure losses in the two networks can differ significantly. With identical pipe diameters, H2 exhibits lower pressure drop than CH4, and its demand therefore experiences less curtailment. However, when the H2 pipe diameter is reduced, the pressure drop across the H2 pipes increases and the curtailed load becomes higher than in the CH4 network. These results can be used by gas TSOs in designing and operating their grid more efficiently.

eess.SY↗

arXiv2025

Towards a Machine Learning Solution for Hubble Tension: Physics-Informed Neural Network (PINN) Analysis of Tsallis Holographic Dark Energy in Presence of Neutrinos

We present a Physics-Informed Neural Network (PINN) framework for reconstructing the redshift-dependent Hubble parameter $H(z)$ within the Tsallis Holographic Dark Energy (THDE) model extended by massive neutrinos. In this approach, the modified Friedmann equation is incorporated into the neural network loss function, enabling training on Cosmic Chronometers data up to $z \leq 2$. The framework allows for the simultaneous estimation of the Hubble constant $H_0$, the neutrino density parameter $Ω_ν$, and the Tsallis non-extensivity index $δ$. Uncertainty quantification is performed through dropout simulations, resulting in statistically consistent $1σ$ confidence bands. Our results show that the THDE+$ν$ model, reconstructed via PINN, alleviates the statistical Hubble tension from the canonical $\sim 5σ$ level down to a range of $0.5σ\leq T \leq 2.2σ$, depending on the redshift sampling. Additionally, we constrain the total neutrino mass to $Σm_ν< 0.11\,\text{eV}$. A detailed comparison with the traditional Markov Chain Monte Carlo (MCMC) analysis demonstrates the consistency of both methods, while highlighting the competitiveness of the PINN-based THDE framework as a robust, data-driven approach for non-parametric cosmological inference within generalized thermodynamics.

astro-ph.CO↗

arXiv2025

Coupled non-canonical scalar field to neutrinos could alleviate the Hubble tension and cross the phantom barrier

This study presents an analysis of cosmological parameters, focusing on resolving the Hubble tension and constraining neutrino masses within a coupled quintom model. By utilizing datasets from the Cosmic Microwave Background (CMB), Pantheon + Analysis, Cosmic Chronometers (CC), Baryon Acoustic Oscillations (BAO), and CMB Lensing, we explore the interplay between cosmological parameters and observational constraints. The model effectively reduces the Hubble tension, achieving a consistency in $H_0$ measurements of $1.37σ$ and $1.24σ$ for the CMB + ALL dataset For Planck 2018 and R22 respectively. Additionally, the study refines constraints on the total mass of neutrinos ($Σ_{m_ν}$), with a finding of $0.115\,\text{eV}$ for the CMB + ALL dataset. The analysis examines the effective equation of state parameter ($w_{\text{eff}}$), indicating a transition towards a universe dominated by exotic energy forms. The combined datasets refine $w_{\text{eff}}$ to $-1.02\pm0.018$, underscoring the importance of multi-dataset integration in understanding dark energy dynamics. Furthermore, the interaction constant $β$ between the quintom scalar field and neutrinos is constrained to $0.65 \pm 0.12$ for the CMB + ALL dataset. The potential parameters $λ_σ = -2.09 \pm 0.082$ and $λ_ϕ = 2.43 \pm 0.12$ are also determined, providing insights into the quintom model's implications for cosmological dynamics. This study offers compelling evidence for the coupled quintom model's capability to resolve the Hubble tension and refine constraints on neutrino properties, enhancing our understanding of the universe's evolution.

astro-ph.CO↗

arXiv2025

A Bayesian PINN Framework for Barrow-Tsallis Holographic Dark Energy with Neutrinos: Toward a Resolution of the Hubble Tension

We investigate the Barrow-Tsallis Holographic Dark Energy (BTHDE) model using both traditional Markov Chain Monte Carlo (MCMC) methods and a Bayesian Physics-Informed Neural Network (PINN) framework, employing a range of cosmological observations. Our analysis incorporates data from Cosmic Microwave Background (CMB), Baryon Acoustic Oscillations (BAO), CMB lensing, Cosmic Chronometers (CC), and the Pantheon+ Type Ia supernova compilation. We focus on constraining the Hubble constant $ H_0 $, the nonextensive entropy index $ q $, the Barrow exponent $ Δ$, and the Granda-Oliveros parameters $ α$ and $ β$, along with the total neutrino mass $ Σm_ν$. The Bayesian PINN approach yields more precise constraints than MCMC, particularly for $ β$, and tighter upper bounds on $ Σm_ν$. The inferred values of $ H_0 $ from both methods lie between those from Planck 2018 and SH$_0$ES (R22), alleviating the Hubble tension to within $ 1.3σ$-$2.1σ$ depending on the dataset combination. Notably, the Bayesian PINN achieves consistent results across CC and Pantheon+ datasets, while maintaining physical consistency via embedded differential constraints. The combination of CMB and late-time probes leads to the most stringent constraints, with $ Σm_ν< 0.114 $ eV and $ H_0 = 70.6 \pm 1.35 $ km/s/Mpc. These findings suggest that the BTHDE model provides a viable framework for addressing cosmological tensions and probing modified entropy scenarios, while highlighting the complementary strengths of machine learning and traditional Bayesian inference in cosmological modeling.

astro-ph.CO↗

arXiv2025

Cosmic Bulk Flow Analysis in Modified Gravity Theories: $f(R)$ and Perturbed $f(R)$ Models with Neutrino Coupling

In this study, we explore the characteristics of bulk flow across various redshift ranges within the frameworks of $f(R)$ gravity, perturbed $f(R)$ gravity, and perturbed $f(R)$ gravity coupled with neutrinos. Our investigation reveals profound insights into large-scale cosmic flows and their interactions with major cosmic structures, such as the Sloan Great Wall (SGW) and the King Ghidorah Supercluster (KGSc). We find that incorporating neutrinos into the perturbed $f(R)$ gravity model results in a substantial increase in bulk flow velocities across all redshifts, with notable enhancements in the higher redshift ranges, where velocities can exceed $3000 \, \mathrm{km/s}$ in the $0.8 < z < 1.4$ range. Moreover, the direction of the bulk flow in this model closely aligns with the dark energy dipole, especially at redshifts $z > 0.4$, showing near-perfect congruence with cosmic superclusters. This suggests a significant interaction between neutrinos and cosmic structures, influencing cosmic acceleration. At lower redshifts, such as $0.1 < z < 0.2$, the bulk flow aligns with the SGW, while in the $0.4 < z < 0.6$ range, it aligns with the KGSc. In the low redshift range $0.001 < z < 0.016$, although velocities are lower, neutrinos still subtly increase the bulk flow velocity and maintain alignment with nearby cosmic structures, like the Local Supercluster. Our results underscore the critical role of neutrinos in shaping cosmic flows and offer new insights into the interplay between dark energy, neutrinos, and modified gravity models.

astro-ph.CO↗

arXiv2025

The interaction of neutrinos with Phantom, Quintessence, and Quintum scalar fields and its effect on the formation of structures in the early Universe

Despite the fact that the mass of the neutrinos is so small, they are produced in such vast numbers in the early Universe that their mass induces subtle effects on cosmological observables, primarily the growth of structure and the expansion history in the Universe. We consider the models where neutrino interacts with dark energy scalar field models; phantom, quintessence, and quintom. Also, we obtained the $z_{\rm nr}$ (the redshift at which a mass of neutrino $m_ν$ will become non-relativistic) and surveyed the effect of non-relativistic neutrinos on the structure formation. The data used in this paper are Pantheon + Analysis catalog, CMB, and BAO data. We obtained coupling constant $β$ for neutrino and three scalar fields and found that larger $β$ values will generally lead to larger neutrino mass in the Universe. For combination data, we found that the total mass of neutrino $\sum m_ν< 0.1197$eV $(95\% $ Confidence Level (C.L.) for quintom model and $\sum m_ν< 0.121 $eV $(95\% $ Confidence Level (C.L.) for phantom model and $\sum m_ν< 0.122$eV $(95\% $ Confidence Level (C.L.) for quintessence model. These results are in broad agreement with the results of Planck 2018 where the total neutrino mass is $\sum m_ν<0.12$eV ($95\%$ C.L., TT, TE, EE+lowE+lensing+BAO). Using the neutrino mass obtained from different models, we calculated $z_{\rm nr}$ and co-moving wave number $k_{\rm nr}$ and showed that neutrinos played a role on the structure formation in the early Universe.

gr-qc↗

arXiv2025

Using the Kaniadakis horizon entropy in the presence of neutrinos to alleviate the Hubble and $ S_{8} $ Tensions

The $H_{0}$ tension stands as a prominent challenge in cosmology, serving as a primary driver for exploring alternative models of dark energy. Another tension arises from measurements of the $ S_{8} $ parameter, which is characterize the amplitude of matter fluctuations in the universe. In this study, we address the alleviation of both the Hubble tension and $ S_{8} $ tension by incorporating Kaniadakis horizon entropy. We investigate two scenarios to explore the impact of this entropy on cosmological parameters. In the first scenario, utilizing modified Friedmann equations through Kaniadakis entropy, we estimate the values of $H_{0}$ and $ S_{8} $. In the subsequent scenario, we introduce the neutrino term and assess its effect on mitigating the Hubble and $ S_{8} $ tensions. Our findings reveal that when considering the first scenario, the results closely align with Planck's 2018 outcomes for Hubble and $ S_{8} $ tensions. Moreover, with the inclusion of neutrinos, these tensions are alleviated to approximately 2$σ$, and the $ S_{8} $ value is in full agreement with the results from the KiDS and DES survey. Furthermore, we impose a constraint on the parameter $K$ in each scenario. Our analysis yields $K = 0.12\pm 0.41$ for Kaniadakis entropy without neutrinos and $K = 0.39\pm 0.4$ for the combined dataset considering Kaniadakis entropy in the presence of neutrinos. We demonstrate that the value of K may be affected by neutrino mass, which can cause energy transfer between different parts of the universe and alter the Hubble parameter value.

astro-ph.CO↗

arXiv2025

Perturbed $f(R)$ gravity coupled with neutrinos: exploring cosmological implications

We conduct a thorough examination of cosmological parameters within the context of $f(R)$ gravity coupled with neutrinos, leveraging a diverse array of observational datasets, including Cosmic Microwave Background (CMB), Cosmic Chronometers (CC), Baryon Acoustic Oscillations (BAO), and Pantheon supernova data. Our analysis unveils compelling constraints on pivotal parameters such as the sum of neutrino masses ($\sum m_ν$), the interaction strength parameter ($Γ$), sound speed ($c_s$), Jean's wavenumbers ($k_J$), redshift of non-relativistic matter ($z_{\rm nr}$), and the redshift of the Deceleration-Acceleration phase transition ($z_{\rm DA}$). The incorporation of neutrinos within the $f(R)$ gravity framework emerges as a key factor significantly influencing cosmic evolution, intricately shaping the formation of large-scale structures and the dynamics of cosmic expansion. Additionally, a detailed analysis of bulk flow direction and amplitude across various redshifts provides valuable insights into the nature of large-scale structures. A notable aspect of our model is the nuanced integration of $f(R)$ gravity theory with neutrinos, representing a distinctive approach to unraveling cosmological phenomena. This framework, unlike previous models, explicitly considers the impact of neutrinos on gravitational interactions, the formation of large-scale structures, and the overarching dynamics of cosmic expansion within the $f(R)$ gravity paradigm. Furthermore, our study addresses the Hubble tension problem by comparing $H_0$ measurements within our model, offering a potential avenue for reconciling discrepancies. Our findings not only align with existing research but also contribute novel perspectives to our understanding of dark energy, gravitational interactions, and the intricate challenges posed by the Hubble tension.

astro-ph.CO↗

arXiv2025

Comparative Analysis of Perturbed $f(R)$ Gravity and Perturbed Rastall Gravity Models in Describing Cosmic Evolution from Early to Late Universe Relative to the $Λ$CDM Model

This study conducts a meticulous examination of the cosmological implications inherent in Rastall gravity and $f(R)$ gravity models, assessing their efficacy across distinct cosmic epochs, from early universe structure formation to late-time acceleration. In the initial stages, both models exhibit commendable compatibility with observed features of structure formation, aligning with the established $Λ$CDM model. The derived Jeans' wavenumbers for each model support their viability. However, as the cosmic timeline progresses into the late universe, a discernible disparity surfaces. Utilizing the Markov Chain Monte Carlo method, we reconstruct the deceleration parameter $(q)$ and identify Deceleration - Acceleration redshift transition values. For $f(R)$ gravity, our results align closely with previous studies, emphasizing its superior ability to elucidate the recent cosmic acceleration. In contrast, Rastall gravity exhibits distinct redshift transition values. Our rigorous analysis underscores the prowess of $f(R)$ gravity in capturing the observed cosmic acceleration, positioning it as a compelling alternative to the conventional $Λ$CDM model. The discernible shifts observed in the peaks of the CMB power spectrum and evolution of deceleration parameter (q) for both $f(R)$ gravity and Rastall gravity models in the Early and Late universe, in relation to the $Λ$CDM model, provide compelling evidence supporting the proposition that these alternative gravity models can account for the anisotropy of the universe without invoking the need for dark energy.

gr-qc↗

arXiv2023

Anisotropic Signatures: Neutrinos -- Dark Energy Interaction and Its Effect on the Transition from Radiation to Matter, and Dark Energy Dominated Phases

This paper explains the significance of neutrino mass in the cosmic progression from the radiation-dominated phase to matter and subsequently to the dark energy-dominated era. We have put a constraint on the total mass of neutrinos by coupling them with quintessence. For the combination of full data(Pantheon+CMB+BAO+CC), we find $ \sum m_ν<0.101$eV \ \ (95$\% $CL.) and for the relativistic to non-relativistic phase transition redshif ${z_{\rm nr}} = 180$ which is in the matter-dominated era. Our findings confirm that when neutrinos become non-relativistic, the universe transitions from a radiation-dominated era to a matter-dominated era. Coupled neutrinos with quintessence (CQ) have also a significant impact on transitions from a matter-dominated era to a dark energy era. We have shown this effect by investigating the impact of neutrino mass on the bulk flow direction and amplitude of bulk velocity. Moreover, we have discussed the impact of this coupling on the CMB power spectrum to show the anisotropy in the universe. Finally, we have established a link between the quintessence field coupled with neutrinos and the bulk flow, which allowed us to demonstrate that the mass of neutrinos could be the cause of anisotropy in the universe.

gr-qc↗

arXiv2023

Revisiting the history of the evolution of the universe from radiation dominated to dark energy dominated

Most of our knowledge of the universe has been obtained from the anisotropy spectrum of the cosmic microwave background and observations of large-scale structures. During the history of the Universe, neutrinos from the early Universe evolve from a relativistic phase at very early times to a massive-particle behavior at later times. The mass of neutrinos affects the history of the expansion of the universe and the growth of the disturbances of the various components of the cosmic microwave background, therefore the anisotropy spectrum of the cosmic radiation and the observations of the large-scale structures. In this article, by using the coupling of neutrinos with dark energy, we investigate the cosmic evolution from the era of matter dominated to the era of dark energy dominated and show that neutrinos can play an important role in the evolution from radiation dominated to matter dominated and the evolution from Matter dominated to dark energy dominated. Also, we investigate the effect of non-relativistic neutrino on bulk flow and show that the direction of bulk flow has a little difference in scales smaller than 0.1, and the more we consider the scales higher than the local universe, the more difference is observed in the direction of bulk flow.

gr-qc↗

arXiv2023

Test of Barrow entropy using a model independent approach

Taking into consideration of a fractal structure for the black hole horizon, Barrow argued that the area law of entropy get modified due to quantum-gravitational effects. Accordingly, the corrected entropy takes the form $S\sim A^{1+\fracΔ{2}}$, where $0\leqΔ\leq1,$ indicates the amount of the quantum-gravitational deformation effects. By considering the modified Barrow entropy associated with the apparent horizon, the Friedmann equations get modified as well. We show that considering a universe filled with the matter and cosmological constant $Λ$, it is possible to determine the amount of deviation from standard cosmology by reconstructing the parameter $δ$ in terms of curvature parameters $\{q,Q,Ω_{k}\}$ as $Δ=\frac{(Q-1-Ω_k)(1+Ω_k)}{(1+Ω_k+q)^{2}}$. Here, $q$ is the deceleration parameter and $Q$ is the third derivative of scale factor . This relation provides some advantages. The first is that it indicates that there is profound connection between quantum-gravitational deformation effects and curvature effects, for $Ω_k\simeq0$ the pair $\{q,Q\}$ can be regarded as deviation curvature factors which reflect the amount of deviation of the model from the standard model. The second interesting feature is that, since this pair are observational parameters which can be directly measured in a model independent approach, they can be regarded as powerful tools to enable us to put constraint on parameter $Δ$ and test the Barrow entropy model. Our analysis predicts the value for $Q_{0}$ which is slightly deviates from 1 as $(Q_{0}-1)<0.001$. This can be a relativity well target and criterion for theoretical and observational measurements of parameter $Q_{0}$. Hence we can hope and wait the improvement of the high redshift data in the future to support it.

gr-qc↗

arXiv2023

Accelerating universe in Kaniadakis cosmology without need of dark energy

Taking into consideration of Kaniadakis entropy associated with the apparent horizon of Friedmann-Robertson-Walker (FRW) Universe and using the gravity-thermodynamics conjecture, a new cosmological scenarios emerges based on corrected Friedmann equations, which contains a correction term $ α\left(H^2+\frac{k}{a^2}\right)^{-1}$ where $α\equiv\frac{K^2 π^2}{2 G^2}$ and $K$ is Kaniadakis parameter. We show that it is possible to reconstruct the parameters of the model, in terms of cosmographic parameters$\{ q, j, s\}$ analytically. For the flat universe, the parameters can be reconstructed in terms of only two cosmographic parameters $\{q, j\}$. The advantage of this analytical reconstruction is that it provides the possibility to test observational measurements on Kaniadakis cosmology using directly measurable cosmographic parameters. As an interesting result is that without any assumption about the value of $Λ$, we found that the set $\{q_{0}=-0.708, j_{0}=1.137\}$ automatically gives $Λ\simeq0$ and $\{Ω_{m0}\simeq0.325,Ω_{\alpha0}=0.671\}$. This result is in excellent agrement with pervious observational studies. Reconstructing the evolution of deceleration parameter against redshift $z$ for these values, shows that the correction term could plays the role of dark energy without any dark energy component or cosmological constant $Λ$. Finally, we formulate the deviation parameter in terms of $\{q,j\}$ which reflects the deviation of the model from $ΛCDM$ model. We Show that the deviation factor is very sensitive to the jerk parameter $j$, while the $Ω_{m0}$ is sensitive to deceleration parameter $q_{0}$. Hence, the set $\{j,q\}$ can be regarded as useful parameters to test the theoretical and observational studies in Kaniadakis cosmology.

gr-qc↗

arXiv2020

Does stability in Einstein frame guarantee stability in Jordan frame?

Scalar tensor theories of gravity can be formulated in the Einstein or in the Jordan frame, which are related by the conformal transformations. Although the two frames are describe the same physics, and are equivalent, the stability of the field equations in two frames are not the same. Here we implement dynamical system and phase space approach as a robustness tool to investigate this issue. We concentrate on the Brans Dicke theory, but the results can easily be generalized. Our analysis show that while there is one-to-one correspondence between critical points in two frames and each critical point in one frame is mapped to its corresponds in other frame , however stability of a critical points in one frame does not grantee the stability in other frame. Hence an unstable point in one frame may be mapped to a stable point in other frame. All trajectories between two critical points in phase space in one frame are different from their corresponds in other ones. This indicates that the dynamical behavior of variables and cosmological parameters are different in two frames. Hence for those features of the study which focus on observational measurements we must use the (JF) where experimental data have their usual interpretation

gr-qc↗

arXiv2019

Graph Attention Auto-Encoders

Auto-encoders have emerged as a successful framework for unsupervised learning. However, conventional auto-encoders are incapable of utilizing explicit relations in structured data. To take advantage of relations in graph-structured data, several graph auto-encoders have recently been proposed, but they neglect to reconstruct either the graph structure or node attributes. In this paper, we present the graph attention auto-encoder (GATE), a neural network architecture for unsupervised representation learning on graph-structured data. Our architecture is able to reconstruct graph-structured inputs, including both node attributes and the graph structure, through stacked encoder/decoder layers equipped with self-attention mechanisms. In the encoder, by considering node attributes as initial node representations, each layer generates new representations of nodes by attending over their neighbors' representations. In the decoder, we attempt to reverse the encoding process to reconstruct node attributes. Moreover, node representations are regularized to reconstruct the graph structure. Our proposed architecture does not need to know the graph structure upfront, and thus it can be applied to inductive learning. Our experiments demonstrate competitive performance on several node classification benchmark datasets for transductive and inductive tasks, even exceeding the performance of supervised learning baselines in most cases.

cs.LG↗

arXiv2018

Detecting Antagonistic and Allied Communities on Social Media

Community detection on social media has attracted considerable attention for many years. However, existing methods do not reveal the relations between communities. Communities can form alliances or engage in antagonisms due to various factors, e.g., shared or conflicting goals and values. Uncovering such relations can provide better insights to understand communities and the structure of social media. According to social science findings, the attitudes that members from different communities express towards each other are largely shaped by their community membership. Hence, we hypothesize that inter-community attitudes expressed among users in social media have the potential to reflect their inter-community relations. Therefore, we first validate this hypothesis in the context of social media. Then, inspired by the hypothesis, we develop a framework to detect communities and their relations by jointly modeling users' attitudes and social interactions. We present experimental results using three real-world social media datasets to demonstrate the efficacy of our framework.

cs.SI↗

arXiv2018

Sentiment-driven Community Profiling and Detection on Social Media

Web 2.0 helps to expand the range and depth of conversation on many issues and facilitates the formation of online communities. Online communities draw various individuals together based on their common opinions on a core set of issues. Most existing community detection methods merely focus on discovering communities without providing any insight regarding the collective opinions of community members and the motives behind the formation of communities. Several efforts have been made to tackle this problem by presenting a set of keywords as a community profile. However, they neglect the positions of community members towards keywords, which play an important role for understanding communities in the highly polarized atmosphere of social media. To this end, we present a sentiment-driven community profiling and detection framework which aims to provide community profiles presenting positive and negative collective opinions of community members separately. With this regard, our framework initially extracts key expressions in users' messages as representative of issues and then identifies users' positive/negative attitudes towards these key expressions. Next, it uncovers a low-dimensional latent space in order to cluster users according to their opinions and social interactions (i.e., retweets). We demonstrate the effectiveness of our framework through quantitative and qualitative evaluations.

cs.SI↗