Vera C. Rubin Observatory first look, La Serena base facility celebration
When
From Oct 2020 to Today.
Where
I started as developer at INRIA Chile, the contractor for the initial development of the project. I was also able to take a tech lead and project management position in the project to lead the successful completion of the contract with the Vera C. Rubin Observatory. Then I was hired as Frontend Web Developer by the Rubin Observatory to keep maintaning the project.
What
The LSST Operators Visualization Environment (LOVE) is a web application designed to monitor and control the various subsystems of the Vera C. Rubin Observatory. It provides a unified interface for operators to visualize real-time data from over 60 different systems, facilitating efficient management and operation of the observatory’s complex infrastructure. The Legacy Survey of Space and Time (LSST) is a groundbreaking astronomical survey that will capture vast amounts of data, and LOVE plays a crucial role in ensuring the observatory’s systems are functioning optimally.
I initially started working as a programmer, I had to understand the basis of a complex sensoring system that needs to be reflected through user itnerfaces for active monitoring and controling. The application is built through different modules that allows the full system to read telemetries from the observatory components and being able to display those thorugh a web application user interface that several users can connect through, even remotely. Performance and reliability are key aspects of the application, as it needs to handle large volumes of data and provide real-time updates to users.
My role to proyect leader shortened my time programing but also gave me more time to deal with project management tasks in order to successufly finish the contract between Inria and the Vera C. Rubin Observatory that ended by the finish of 2023. I was able to lead a team of 4 developers, and I also had the opportunity to work on the project as a frontend developer, where I could apply my knowledge in ReactJS and Django Rest Framework (DRF) to develop new features and improve the existing ones.
Working in an astrnomy observatory is amazing, you can check one of my first pictures there where I was working on the right side of the following picture:
Most of the Rubin Observtory code is Open Source, so I invite you to check some of the repositories of the LOVE project:
I’ve worked implementing a lot of LMS systems (Learning Management Systems) used for e-learning education. I’ve developed several components of different kind, in Frontend and Backend. Also worked with a lot of clients, using and agile approach with regular meetings to indentify, discuss and validate requirements.
How
Frontend: HMTL, CSS, CSS3, SASS, Javascript
Backend: AMP stack (Apache, Mysql -Maria DB- and PHP)
I’ve participated on the creation an entrepreneurship company called OSARE, we focused on developing innovative apps. This was one of my first job approachs, so it was the beginning of my development carrer. We were able to develop two applicaitons:
HelpyCar: an application used to geolocate car workshops in case you required any urgent service. This was developed in native Android and we never did a release, but it served as a first approach to the software development.
Dubbin: an entertainment application used to create dubs of scenes of any video you uploaded to the app. I’ve participated on the firt release of the app which was developed using native Android. I didn’t participate on the last release which got published on the Apps Stores.
How
Frontend: Android Native
Backend: AMP stack (Apache, Mysql -Maria DB- and PHP)
The discipline of astroinformatics has grown a lot over the past few years thanks to the creation of bigger and more sophisticated telescopes, such as the Atacama Large Millimeter/submillimeter Array. With better spectral resolution in data, a new challenge is set in the way astronomical data is analyzed. In particular, data cubes produced by radioastronomy projects have generated an explosion in the volume of data retrieved. Some tasks, such as
the identification of spectral lines becomes more complex. For this reason it is essential to develope accurate analysis tools that allows data to be processed automatically.
This works propose a novel method in the way spectra can be classified. The approach is based on an algorithm used in the world of Text Mining, named Latent Dirichlet Allocation, a probabilistic generative model capable of describing documents as a random mixture of words over topics. Here, each spectrum is represented as a mixture of transitions over species. A spectral line transitions database named Splatalogue is used to train different models based on the type of observed object or ALMA band. The algorithm is evaluated using the model to analyze real world data cubes and spectral line surveys from radioastronomy observations of ALMA. The main advantage of the proposal is the ability to model sparse and high dimensional data using posterior inference to classify new spectral observations. Results shows that L-LDA can be used to clasifiy spectral lines on data cubes with up to 97 % of accuracy.
