Questions for Day 1 tutorials (May 15, 2023) can be posted here
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I have a one simple query to ask.
Is the tutorial lectures, assignments available even after 17th May ,2023 so that we can do it further and gain the certificates?
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Hi @curiousabhi, yes, the Thinkific course is going to be open even after the workshop. You can complete it and get your certificate whenever you want
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Hi, could you please tell us where the data challenge can be found?
What are GWTC-1,2,3?
At the end of each tutorial notebook!
GWTC stands for “Gravitational-Wave Transient Catalog” and the ones you mention are the catalogs of all gravitational wave events detected in the past 3 observing runs of the LIGO-Virgo-GEO-KAGRA collaboration. Here more information for GWTC-1 and -2, for example: GWTC-1 Documentation (gwosc.org) and GWTC-2 Data Release Documentation (gwosc.org).
you are right, thanks for the feedback, I just corrected it
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sir, from second code, there was error
“No module named ‘gwosc’”
Hi, what platform are you using to run the code?
If you are using Colab, in the first box:
#! pip install -q ‘gwosc==0.7.1’
you have to change this removing the dash to:
! pip install -q ‘gwosc==0.7.1’
so that the module can be imported.
If you are using conda, from terminal in your environment type:
pip install gwosc
to import the module
Here a reference for completing your setup: odw-2023/setup.md at main · gw-odw/odw-2023 (github.com)
Hi @Ambarish1234 I don’t understand the question, the tutorial is meant to explain how to use the package gwosc and in this case how to use the event_gps method. If you want to know the gps time of GW150914 then you can replace GW190412 with GW150914 to get it.
Why exactly is the first plot of amplitude spectrum obtained wrong?(physically and mathematically too)
Which Time domain waveform models to choose when we are trying to plot a BNS merger?
Should we avoid the Taylor series model as they do not have the ringdown component in them?
Hi @abdyoyo, I would suggest you to use IMRPhenomD_NRTidalv2, IMRPhenomPv2_NRTidalv2, TEOBResum_ROM or SEOBNRv4_ROM_NRTidalv2.
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Hi @AmbicaG!
We did select a precise 10 seconds TimeSeries from time gps-5 to time gps+5. One action of the FFT is to extend the input time series in the whole (real) axis, copying it foverever, with the first new fake data just after the last old data, in order to assume periodicity. For example, if we have a sinusoid in input, with period t related to the input TimeSeries time range T as T=Nt, where N is a real number, the FFT will extend this sinusoid to the whole time range, without any discontinuity on edges between different copies. In our case this repeated copy is a problem because at the edges we create a discontinuity between the last real data and the first new data. FFT algorithm tries to approximate the whole time axis as a series of sinusoids with different weights, but it sees this discontinuity as a step to include in the approximation as well, giving us a wrong answer. The proposed solution helps to mitigate this effect by removing the discontinuity at the edges via the convolution of the time series with a window function, which smoothly brings the edges to zero.
For a more mathematical view, you can visit this page.
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Hello there, question in the datasets.find_datasets for the keyword detector which detector is which?
Hi @rafaeld1, the keyword detector corresponds to the standard prefix used to identify our detectors (it was mentioned in the lecture about GW public data):
- L1 = LIGO Livingston
- H1 = LIGO Handford
- V1 = Virgo
- K1 = Kagra
- G1 = GEO
Hello, I am trying to use the code that is shown for the 1.3 tutorial in the Q-scan challenge, but it is not able to compile. Is there any other place to get example code to see how the solution can be obtained? The error is appearing in the plot.subplots parameters.