SFTP on the go
A lightweight, dockerized sftp server with basic authentication and security
- Lightweight, Debian-based sftp server ready-made for Docker deployment.
- Includes basic user authentication
- Allows direct SSH and TLS connections.
A lightweight, dockerized sftp server with basic authentication and security
A Python module for advanced data science procedures.
Functionality currently includes:
Machine learning is poised to significantly expand the capabilities of observational astronomical research. I have designed a generative artificial neural network model for use with the Southern Photometric Local Universe Survey, demonstrating an unprecedented capability to estimate the metal and carbon abundances of stellar atmospheres.
Training on photometric inputs for estimation of Absolute Carbon Abudance, using monte carlo generative training procedure. Activation functions and hidden layer size are optimized within a randomize hyperparameter space.
Constraints on the Galactic Inner Halo Assembly History from the Age Gradient of Blue Horizontal-branch Stars
Analysis of the Milky Way Halo radial age distribution using Blue Horizontal-Branch stars.
Developed pipeline for determination of chemical abundances in stellar atmospheres
Bayesian spectral matching is a revolutionary method to estimate stellar parameters for among the most strongly depressed stellar atmospheres. By implementing a procedure that weighs the influence of multiple molecular and atomic features associated with the presence of CH, C2, and CaII, stellar parameter determination can appropriately mitigate the effects of carbon and metal-line blanketing. This technique promises to provide parameter estimates for countless stellar sources at low- and medium-resolution, previously inaccessable by alternative methods.
Automated spectral normalization
Intuitive spectral normalization procedures are crucial to automate the stellar parameter determination process, considering the overwhelming wealth of spectrscopic data being acquired by multi-fiber survey expeditions. The idenfication of strong molecular depression in the spectral energy distribution is essential to provide accurate continua, and by extension, chemical abundance determinations. I have designed such a procedure, based on 2nd order numerical differentiation of spectral convolutions. This procedure has made possible the first detection of a Group III carbon-enhanced metal-poor star in the Canes Venatici I dwarf galaxy.