Uploaded February 2021 | Updated September 2026, 2 weeks ago
This webinar took place on January 23, 2021, and features talks from two figures in astronomy research: first, Melanie Crowson, "Study of and Reclassification Evidence For Four Candidate RR Lyraes - TY Cam, V0363 Dra, NSV 13109, V1386 Aql," and second, Dr. Sarah Antier and Pr. Dr. Coughlin (start time at 38:22) on "GW astronomy and Kilonova-catcher."
The purpose of Crowson's research is to examine four RR Lyraes (two confirmed and two candidates) in an attempt to determine their periodicities and assess their classifications. This study determined the most likely periods of TY Cam and V0363 Dra, and sided with the reclassification suggestion by ASAS-SN for NSV 13109 as an L class, irregular variable. For V1386 Aql, it was found that much inaccurate data has been collected on this star due to its proximity to a brighter companion; however, it appears to be a promising variable candidate, but requires more precision photometry to solidify its classification.
Dr. Antier and Pr. Dr. Coughlin discuss how diverse messengers (photons and gravitational waves) provide a new picture of the collision of two neutron stars, and review how coherent analysis of the messengers can better constrain the astrophysical scenarios at play, and further knowledge on cosmology and fundamental physics. They also describe the Global Rapid Advanced Network Devoted to the Multi-messenger Addicts, which aims to identify and characterize the optical counterparts of gravitational-wave sources. Lastly, they cover how you, as an amateur astronomer, can join the project and participate in observations of neutron star mergers.
This webinar took place on January 23, 2021, and features talks from two figures in astronomy research: first, Melanie Crowson, "Study of and Reclassification Evidence For Four Candidate RR Lyraes - TY Cam, V0363 Dra, NSV 13109, V1386 Aql," and second, Dr. Sarah Antier and Pr. Dr. Coughlin (start time at 38:22) on "GW astronomy and Kilonova-catcher."
The purpose of Crowson's research is to examine four RR Lyraes (two confirmed and two candidates) in an attempt to determine their periodicities and assess their classifications. This study determined the most likely periods of TY Cam and V0363 Dra, and sided with the reclassification suggestion by ASAS-SN for NSV 13109 as an L class, irregular variable. For V1386 Aql, it was found that much inaccurate data has been collected on this star due to its proximity to a brighter companion; however, it appears to be a promising variable candidate, but requires more precision photometry to solidify its classification.
Dr. Antier and Pr. Dr. Coughlin discuss how diverse messengers (photons and gravitational waves) provide a new picture of the collision of two neutron stars, and review how coherent analysis of the messengers can better constrain the astrophysical scenarios at play, and further knowledge on cosmology and fundamental physics. They also describe the Global Rapid Advanced Network Devoted to the Multi-messenger Addicts, which aims to identify and characterize the optical counterparts of gravitational-wave sources. Lastly, they cover how you, as an amateur astronomer, can join the project and participate in observations of neutron star mergers.
![AAVSO How to [Python! Visualizing MESA models with TULIPS]](https://i.ytimg.com/vi/YmwHwGK6Y60/mqdefault.jpg "AAVSO How to [Python! Visualizing MESA models with TULIPS]
AAVSo webinar
Instructor: Eva Laplace (Heidelberg Institute for Theoretical Studies HITS)
Please note: Dr. Laplace has provided links for you to download and install Tulips prior to her presentation: https://www.aavso.org/sites/default/files/education/presentations/How-toTulip_Instructions_12.22.pdf
In this third How to Python! broadcast, Dr. Eva Laplace will teach attendees how to use her Python package, TULIPS, to visualize MESA models. MESA models track the changing temperature, radius, composition, and structure of stars as they evolve, making them valuable tools for stellar researchers; but they are famously difficult to use. TULIPS makes it easy to visualize complex information, allowing you to create beautiful plots and animations showing the changes a star will undergo during its lifetime. Knowledge of basic Python is recommended. Attendees are encouraged to familiarize themselves with TULIPS ahead of time: https://pypi.org/project/astro-tulips/
Our previous How to Python webinars will help you become familiar with Python:
The basics: https://www.youtube.com/watch?v=7eMTgQuKGHA&list=PLnZ_rvnR35rfGTaq4g3kzVOfkna1JeDyX&index=7&t=2s
Finding Frequency Solutions for Variable Star Light Curves: https://www.youtube.com/watch?v=ZhtHBkbTuWY&t=3s
Join us for our 2023 webinars!
www.aavso.org/programs-events")
![AAVSO How to [Python! Finding Frequency Solutions for Variable Star Light Curves]](https://i.ytimg.com/vi/ZhtHBkbTuWY/mqdefault.jpg "AAVSO How to [Python! Finding Frequency Solutions for Variable Star Light Curves]
AAVSO webinar, originally broadcast Oct. 1, 2022.
This is the second session in a three-part series. Basic knowledge of Python is assumed. If youve never used Python before, we recommend installing it and watching AAVSOs recording of the first session (The Basics https://www.youtube.com/watch?v=7eMTgQuKGHA) before watching this one.
Many stars vary in brightness at one or many frequencies. Measuring these frequencies reveals valuable information about the physical properties of the observed systems. This tutorial demonstrates how to measure the frequencies (or periods) of variation in light curve data with the interactive Python package Pyriod. The tutorial will introduce periodograms, significance testing, and the iterative prewhitening algorithm for fitting signals to the data. Attendees will benefit from previous experience with light curves and Python, but this is not required to follow the presentation.
Dr. Bell works with time series photometry from surveys like TESS, Kepler, and the Zwicky Transient Facility. Dr. Bell is the author of the Python package Pyriod for prewhitening frequency analysis of time series astronomical data.")
