Recent Talks

Impacto de la contaminación lumínica por LEOsats en detectores astronómicos 

El proyecto llevado a cabo ha consistido en actualizar la pipeline existente de análisis de trazas de satélites y basura espacial (SATRED) sobre imágenes del cielo, para poder procesar las observaciones de satélites en órbita baja, medir su magnitud aparente y determinar el grado de contaminación producido sobre las imágenes astronómicas usando tanto detectores CCD como sCMOS. 

Diseño de un telescopio astrofísico para observaciones en banda VIS-NIR

El trabajo realizado propone el diseño óptico de un telescopio completo para satélite que alimentará dos canales espectales: VIS-NIR para realizar fotometría de alta precisión y NUV para análisis de espectroscopia, ambos para el estudio de exoplanetas. El telescopio es de tipo Cassegrain (Ritchey-Chrétien), al que se acopla un elemento separador para dividir los canales. Para poder realizar fotometría correctamente, en el canal VIS-NIR se diseña un vehículo óptico que genera una pupila intermedia, con el fin de reducir el stray light. 

The discoveries of thousands of extrasolar planets have revealed an astonishing diversity in their physical characteristics - orbital properties, masses, radii, temperatures, and host stars. Exoplanets known today range from super Jupiters to Earth-size rocky planets over a wide range of temperatures, including several in the habitable zones of their host stars. Recent advances in atmospheric spectroscopy of exoplanets are leading to unprecedented insights into their atmospheric properties. I will discuss some of these developments in atmospheric characterisation of exoplanets and their implications for understanding atmospheric processes, formation mechanisms, and habitability across a wide range of planetary bulk properties. A survey of theoretical and observational directions in the field will be presented along with some open questions on the horizon.

Zoom:

https://rediris.zoom.us/j/86558203608?pwd=OXQyMmVMQTI2M2VSRUZldThkR0JqUT09

Meeting ID: 865 5820 3608

Passcode: 055970

Youtube. https://youtu.be/GvXv2RMbFz8

Automatización del POTEC

Explicación del problema de automatización del criostato de pruebas para la preóptica de Harmoni. Integración de diferentes protocolos de comunicación mediante el uso de lenguajes de alto nivel y un manejo de los errores que posibilite su integración dentro de un proceso industrial robusto acelerando el tiempo de prototipado y testeo. Uso de Python para la adquisición de datos y la supervisión del proceso en tiempo de ejecución.

Desarrollo de un sistema de medida optoelectrónico para la caracterización  de fotodetectores basado en un monocromador

Creación de una aplicación Python para el control de un sistema óptico y la toma de datos de dos picoamperímetros conectados a sendos fotodiodos que miden la intensidad de la radiación emitida. Esto nos servirá para la caracterización del fotodetectores

Tema: Seminario de Instrumentación: Presentaciones Becarios de Verano

Hora: 17 sept. 2021 12:00 p. m. Atlantic/Canary

Unirse a la reunión Zoom

https://rediris.zoom.us/j/81452070054

Youtube

https://youtu.be/7GSWv6mbQlg

The next decade will see a deluge of new cosmological data that will enable us to accurately map out the distribution of matter in the local Universe, image billions of stars and galaxies to unprecedented precision, and create high-resolution maps of the Milky Way. Signatures of new physics as well as astrophysical processes of interest may be hiding in these observations, offering significant discovery potential. At the same time, the complexity of astrophysical data provides significant challenges to carrying out these searches using conventional methods. I will describe how overcoming these issues will require a qualitative shift in how we approach modeling and inference in cosmology, bringing together several recent advances in machine learning and simulation-based (or likelihood-free) inference. I will ground the talk through examples of proposed analyses that use machine learning-enabled simulation-based inference with an aim to uncover the identity of dark matter, while at the same time emphasizing the generality of these techniques to a broad range of problems in astrophysics, cosmology, and beyond.

https://rediris.zoom.us/j/83193959785?pwd=TExXSDJ6UDg5a24yWDM1TnlOWkNTZz09

Meeting ID: 831 9395 9785
Passcode: 343950O

YouTube: https://youtu.be/1Nkzn-cGaIo

In cosmology, it is customary to convert observed redshifts into distances in order to study the large scale distribution of matter probes like galaxies and quasars, and to obtain cosmological constraints thereof. In this talk, I describe a new approach which bypasses such conversion and studies the "field of redshifts" as a new cosmological observable, dubbed thereafter as angular redshift fluctuations (ARF). By comparing linear theory predictions to the output of N-body cosmological simulations, I will show how the ARF are actually sensitive to both the underlying density and radial peculiar velocity fields in the universe, and how one can obtain cosmological and astrophysical constraints from them. And since "the prove of the pudding is in the eating", I will demonstrate how ARF provide, under a very simple setup, competitive constraints on the nature of peculiar velocities and gravity from BOSS DR13 data. Furthermore, I will also show that by combining ARF with maps of the cosmic microwave background (CMB), we can unveil the signature of the missing (and moving) baryons, doubling the amount of detected baryons in disparate cosmic epochs ranging from z=0 up to z=5, and providing today's most precise description of the spatial distribution of baryons in the universe.

Galaxy morphologies are one of the key diagnostics of galaxy evolutionary tracks, but visual classifications are extremely time-consuming. The sheer size of Big Data surveys, containing millions of galaxies, make this approach completely impractical. Deep Learning (DL) algorithms, where no image pre-processing is required, have already come to the rescue for image analysis of large data surveys. In this seminar, I will present the largest multi-band catalog of automated galaxy morphologies to date containing morphological classifications of ∼27 million galaxies from the Dark Energy Survey. The classification separates: (a) early-type galaxies (ETGs) from late-types (LTGs); and (b) face-on galaxies from edge-on. These classifications have been obtained using a supervised DL algorithm. Our Convolutional Neural Networks (CNNs) are trained on a small subset of DES objects with previously known classifications, but hese typically have mr < 17.7 mag. We overcome the lack ofa training sample by modeling fainter objects up to mr < 21.5 mag, i.e., by simulating what thebrighter objects with well-determined classifications would look like if they were at higher redshifts.The CNNs reach a 97% accuracy to mr < 21.5 on their training sets, suggesting that they are ableto recover features more accurately than the human eye. We obtain secure classifications for 87%and 73% of the catalog for the ETG vs. LTG and edge-on vs. face-on models, respectively.

En esta charla se dará a conocer la comisión de Medioambiente y Sostenibilidad del IAC y el trabajo que se está llevando a cabo. El IAC quiere ser parte activa de las soluciones para alcanzar los objetivos que marca Europa para los futuros años. Se expondrán algunos números relacionados con nuestro gasto y consumo en el IAC que nos pueden hacer reflexionar.

En este seminario se hablará de las características del sistema de control de GTC y cuáles son los componentes que hay que desarrollar para que un instrumento esté integrado dentro de la arquitectura del GCS.

The ExoMol project (www.exomol.com) provides comprehensive spectroscopic data (line lists) for the study of atmospheres of exoplanets and other hot bodies.  These line lists serve as input for models of radiative transport through hot atmospheres and are useful for a variety of terrestrial applications. The basic form of the database is extensive line lists; these are supplemented with partition functions, state lifetimes, cooling functions, Landé g-factors, temperature-dependent cross sections, opacities, k-coefficients and pressure broadening parameters. Currently containing 80 molecules and 190 isotopologues totaling over 700 billion transitions, the database covers infrared, visible and UV wavelengths. The field of the HR spectroscopy of exoplanets is growing extremely fast and urgently demands molecular data of high precision. Failure to detect molecules in atmospheres of exoplanets is often attributed to the lack of the underlying quality of
the line positions.  These developments have led us to begin a systematic attempt to improve the accuracy of the line positions for the line lists contained in the database. Our new ExoMolHD project aims to provide comprehensive line lists to facilitate their use in characterization of exoplanets using high resolution Doppler shift spectroscopy. Progress on this objective will be presented.

The Thirty Meter Telescope is a new class of extremely large telescopes that will allow us to see deeper into space and observe cosmic objects with unprecedented sensitivity. With its 30 m prime mirror diameter, TMT will be three times as wide, with nine times more area, than the largest currently existing visible-light telescope in the world. This will provide unparalleled resolution with TMT images more than 12 times sharper than those from the Hubble Space Telescope. When operational, TMT will provide new observational opportunities in essentially every field of astronomy and astrophysics.  Observing in wavelengths ranging from the ultraviolet to the mid-infrared, this unique instrument will allow astronomers to address fundamental questions in astronomy ranging from understanding star and planet formation to unraveling the history of galaxies and the development of large-scale structure in the universe. This talk will present the current stage of TMT development.