Related papers: Applications of Machine Learning Algorithms In Pro…
Machine learning techniques are utilised in several areas of astrophysical research today. This dissertation addresses the application of ML techniques to two classes of problems in astrophysics, namely, the analysis of individual…
Performance of distributed optimization and learning systems is bottlenecked by "straggler" nodes and slow communication links, which significantly delay computation. We propose a distributed optimization framework where the dataset is…
Terahertz time-domain spectroscopy systems based on resonator-internal repetition-rate modulation, such as SLAPCOPS [12] and ECOPS [11], rely on electronic phase detectors which are typically prone to exhibit both a non-negligible random…
We present the end-to-end data reduction pipeline for SCALES (Slicer Combined with Array of Lenslets for Exoplanet Spectroscopy), the upcoming thermal-infrared, diffraction-limited imager, and low and medium-resolution integral field…
I combine duplicate spectroscopic stellar parameter estimates in the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Data Release 6 Low Resolution Spectral Survey A, F, G, and K Type stellar parameter catalog. Combining…
Terahertz Time Domain Spectroscopy (THz-TDS) systems have emerged as mature technologies with significant potential across various research fields and industries. However, the lack of standardized methods for signal and noise estimation and…
As part of the EU-funded Center of Excellence SPACE (Scalable Parallel Astrophysical Codes for Exascale), seven commonly used astrophysics simulation codes are being optimized to exploit exascale computing platforms. Exascale cosmological…
Distributed Acoustic Sensing (DAS) is a novel technology that allows sampling of the seismic wavefield densely over a broad frequency band. This makes it an ideal tool for surface wave studies. In this study, we evaluate the potential of…
Generation of science-ready data from processed data products is one of the major challenges in next-generation radio continuum surveys with the Square Kilometre Array (SKA) and its precursors, due to the expected data volume and the need…
We present the third data release of the LOFAR Two-metre Sky Survey (LoTSS-DR3). The survey images cover 88% of the northern sky and were created from 12,950 hrs of data (18.6 PB) accumulated over 10.5 years. The images were produced…
We present a method for deriving stellar fundamental parameters. It is based on a regularized sliced inverse regression (RSIR). We first tested it on noisy synthetic spectra of A, F, G, and K-type stars, and inverted simultaneously their…
The DRAO Synthesis Telescope (ST) is a forefront telescope for imaging large-scale neutral hydrogen and polarized radio continuum emission at arcminute resolution. Equipped for observations at 1420 and 408 MHz, the ST completed the Canadian…
The measurement of atmospheric parameters is fundamental for scientific research using stellar spectra. The Chinese Space Station Telescope (CSST), scheduled to be launched in 2024, will provide researchers with hundreds of millions of…
A scheme for estimating atmospheric parameters T$_{eff}$, log$~g$, and [Fe/H] is proposed on the basis of Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and Haar wavelet. The proposed scheme consists of three processes. A…
The Terahertz or millimeter wave frequency band (300 GHz - 3 THz) is spectrally located between microwaves and infrared light and has attracted significant interest for applications in broadband wireless communications, space-borne…
Aerosol scattering influences the retrieval of the column-averaged dry-air mole fraction of CO2 (XCO2) from the Orbiting Carbon Observatory-2 (OCO-2). This is especially true for surfaces with reflectance close to a critical value where…
In modern astrophysics, the machine learning has increasingly gained more popularity with its incredibly powerful ability to make predictions or calculated suggestions for large amounts of data. We describe an application of the supervised…
The next generation of adaptive optics (AO) systems will require tomographic reconstruction techniques to map the optical refractive index fluctuations, generated by the atmospheric turbulence, along the line of sight to the astronomical…
We employ an Artificial Neural Network (ANN) based technique to develop a pipeline for automated segregation of stars from the galaxies to be observed by Tel-Aviv University Ultra-Violet Experiment (TAUVEX). We use synthetic spectra of…
Accurate measurements of statistical properties, such as the star formation rate and the lifetime of young stellar objects (YSOs) in different stages, is essential for constraining star formation theories. However, it is a difficult task to…