Related papers: Parameter estimation from Ly$\alpha$ forest in Fou…
We investigate the channel estimation for massive multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. We revisit the information geometry approach (IGA) for massive MIMO-OFDM channel estimation. By…
Larger Spiking Neural Network (SNN) models are typically favorable as they can offer higher accuracy. However, employing such models on the resource- and energy-constrained embedded platforms is inefficient. Towards this, we present a…
We model the $\lya$ forest in a spatially flat, CDM model with $\Omega=0.4$, with an Eulerian hydrodynamic simulation, and find that the intergalactic, photoionized gas collapses into sheet-like and filamentary structures which produce…
Physics-Informed Neural Networks (PINNs) have been shown to be an effective way of incorporating physics-based domain knowledge into neural network models for many important real-world systems. They have been particularly effective as a…
Our goal in this paper is to test some popular dark matter models by Ly-alpha forest in QSO spectra. Recent observations of the size and velocity of Ly-alpha forest clouds have indicated that the Ly-alpha absorption is probably not given by…
Accurately estimating spatially heterogeneous elasticity parameters, particularly Young's modulus and Poisson's ratio, from noisy displacement measurements remains significantly challenging in inverse elasticity problems. Existing inverse…
High-significance measurements of the monopole thermal Sunyaev-Zel'dovich CMB spectral distortions have the potential to tightly constrain poorly understood baryonic feedback processes. The sky-averaged Compton-y distortion and its…
We present an application of Physics-Informed Neural Networks to handle MultiPhase-Field simulations of microstructure evolution. It has been showcased that a combination of optimization techniques extended and adapted from the PINNs…
We combine COBE-DMR measurements of cosmic microwave background anisotropy with a recent measurement of the mass power spectrum at redshift z=2.5 from Lya forest data to derive constraints on cosmological parameters and test the…
We develop Structured-Knowledge-Informed Neural Networks (SKINNs), a unified estimation framework that embeds theoretical, simulated, previously learned, or cross-domain insights as differentiable constraints within flexible neural function…
Parallel imaging is a commonly used technique to accelerate magnetic resonance imaging (MRI) data acquisition. Mathematically, parallel MRI reconstruction can be formulated as an inverse problem relating the sparsely sampled k-space…
The online prediction of multivariate signals, existing simultaneously in space and time, from noisy partial observations is a fundamental task in numerous applications. We propose an efficient Neural Network architecture for the online…
We measure the intergalactic medium (IGM) opacity in the Ly$\alpha$ as well as in the Ly$\beta$ forest along $19$ quasar sightlines between $5.5\lesssim z_{\rm abs}\lesssim 6.1$, probing the end stages of the reionization epoch. Owing to…
Missing data are inevitable in longitudinal studies. Traditional methods, such as the full information maximum likelihood (FIML), are commonly used to handle ignorable missing data. However, they may lead to biased model estimation due to…
In our recently proposed Integrated Finite Element Neural Network (I-FENN) framework (Pantidis and Mobasher, 2023) we showcased how PINNs can be deployed on a finite element-level basis to swiftly approximate a state variable of interest,…
Large language models (LLMs) are increasingly recognized for their exceptional generative capabilities and versatility across various tasks. However, the high inference costs associated with these models have not received adequate…
We use an automated Voigt-profile fitting procedure to extract statistical properties of the Ly$\alpha$ forest in a numerical simulation of an $\Omega=1$, cold dark matter (CDM) universe. Our analysis method is similar to that used in most…
At $z \lesssim 1$, shock heating caused by large-scale velocity flows and possibly violent feedback from galaxy formation, converts a significant fraction of the cool gas ($T\sim 10^4$ K) in the intergalactic medium (IGM) into warm-hot…
Quantum state tomography (QST) faces exponential measurement requirements and noise sensitivity in multi-qubit systems, bottlenecking practical quantum technologies. We present a physics-informed neural network (PINN) framework integrating…
Numerical hydrodynamical simulations are used to predict the expected absorption properties of the Lyman-Alpha forest for a variety of Cold Dark Matter dominated cosmological scenarios: CHDM, OCDM, LCDM, SCDM, and tCDM. Synthetic spectra…