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The properties of exoplanet host stars are traditionally characterized through a detailed forward-modeling analysis of high-resolution spectra. However, many exoplanet radial velocity surveys employ iodine-cell-calibrated spectrographs,…
Upcoming large-scale spectroscopic surveys such as WEAVE and 4MOST will provide thousands of spectra of massive stars, which need to be analysed in an efficient and homogeneous way. Studies on massive stars are usually based on samples of a…
Since the first observations of interstellar molecules, astrochemical simulations have been employed to model and understand its formation and destruction path- ways. With the advent of high-resolution telescopes such as JWST and ALMA, the…
Machine learning catalyzes a revolution in chemical and biological science. However, its efficacy heavily depends on the availability of labeled data, and annotating biochemical data is extremely laborious. To surmount this data sparsity…
Earth's atmosphere imprints a large number of telluric absorption and emission lines on astronomical spectra, especially in the near infrared, that need to be removed before analysing the affected wavelength regions. These lines are…
Complex organic molecules (COM) are detected in many sources in the warm inner regions of envelopes surrounding deeply embedded protostars. Exactly how these COM form remains an open question. This study aims to constrain the formation of…
Raman spectroscopy is frequently used to identify composition, structure and layer thickness of 2D materials. Here, we describe an efficient first-principles workflow for calculating resonant first-order Raman spectra of solids within…
We present an automatic, fast, accurate and robust method of classifying astronomical objects. The Self Organizing Map (SOM) as an unsupervised Artificial Neural Network (ANN) algorithm is used for classification of stellar spectra of…
In this work we investigate a novel approach to handle the challenges of face recognition, which includes rotation, scale, occlusion, illumination etc. Here, we have used thermal face images as those are capable to minimize the affect of…
Serving ML prediction pipelines spanning multiple models and hardware accelerators is a key challenge in production machine learning. Optimally configuring these pipelines to meet tight end-to-end latency goals is complicated by the…
Observations of ionic, atomic, or molecular lines are performed to improve our understanding of the interstellar medium (ISM). However, the potential of a line to constrain the physical conditions of the ISM is difficult to assess…
We proposed a machine learning approach to identify and distinguish dusty stellar sources employing supervised and unsupervised methods and categorizing point sources, mainly evolved stars, using photometric and spectroscopic data collected…
We illustrate an iterative method for retrieving the internuclear separations of N$_2$, O$_2$ and CO$_2$ molecules using the high-order harmonics generated from these molecules by intense infrared laser pulses. We show that accurate results…
We introduce a new stacking method in Keplerian disks that (1) enhances signal-to-noise ratios (S/N) of detected molecular lines and (2) that makes visible otherwise undetectable weak lines. Our technique takes advantage of the Keplerian…
Temporal variation of millimeter lines is a new direction of research for evolved stars. It has the potential to probe the dynamical wind launching processes from time dimension. We report here the first ALMA (Atacama Large Millimeter…
Stellar population synthesis is an important method in the galaxy and star-cluster studies. In the stellar population synthesis models, stellar spectral library is necessary for the integrated spectra of the stellar population. Usually, the…
A novel framework has recently been proposed for designing the molecular structure of chemical compounds with a desired chemical property using both artificial neural networks and mixed integer linear programming. In this paper, we design a…
The luminosity of embedded protostars is commonly measured via observations of the dust continuum spectral energy distribution from millimetre to infrared wavelengths. However, this method cannot be applied to embedded protostars in binary…
Diffuse interstellar bands are usually observed in spectra of hot stars, where interstellar lines are rarely blended with stellar ones. The need for hot stars is a strong limitation in the number of sightlines we can observe and the…
Upcoming large astronomical surveys are expected to capture an unprecedented number of strong gravitational lensing systems. Deep learning is emerging as a promising practical tool for the detection and quantification of these galaxy-scale…