in a bounded binary system, does kick velocity still play a role during merging
yes. the “kick” comes from momentum lost to gravitational waves
is the "kick" you meant the same kick during the pre-supernova?
No, the kick that is imparted by the supernova is the “natal kick”. The final merger remnant also gets a kick from the conversation of angular momentum after the merger
for example: https://arxiv.org/abs/1802.04276
cool thank you :D
I was wondering if you could expand on how deviations from GR searches are performed in LIGO.
why won't there is a head on collapseing,suppose a small BH is sucked to a galactic center..would there be a prturbation or wobling make GWS
Thanks for sharing the presentation Prof. Alan…It will be a good idea to have a folder in GitHub with all presentations, lots of details and additional resources sources in there. Thanks!
@Abhishek Yes, when a small black hole merges with a galactic center, this is called an extreme mass ratio inspiral. These types of systems emit GW’s at much lower frequencies than those probed by LIGO, and will be detectable by LISA, the space-based detector
Could you expand on how LIGO performs deviations from GR searches?
LIGO performs a number of tests of General relativity including looking for the alternative polarizations that Alan mentioned, calculating the speed of gravitational waves since they should travel at the speed of light if GR is correct, consistency tests looking at the estimated source parameters using different parts of the waveform in isolation like the inspiral and merger/ringdown, and also looking for deviations from the post-newtonian parameters used the describe the inspiral part of the waveform
And what are present days observational .results, even in low confidence level
Here is a good reference for the recent tests of GR that LIGO has performed https://arxiv.org/abs/1903.04467
Peter Saulson answers this question here
I know this paper. It seems to me that in it we already see deviation at low confidence level, but there are no such comments at all...
stationary on earth but still moving with a enormous around milkyway
pdf version: https://pdfs.semanticscholar.org/393a/af6b1ced305ee40d175d5f3c3a2b6020348d.pdf
I have a question: if derivation of waveforms is supposed to be hard (e.g. needs numerical relativity), how could we easily generate them with libraries like SEOBNR, Phenom etc.?
Thank you Sylvia and Gregory
The libraries like SEOB and Phenom are approximations based on the results of numerical relativity. Even with these approximations, the waveforms are extremely expensive to compute.
Phenom is much less expensive than SEOB. The SEOB waveforms are computed in the time domain by solving coupled differential eons, then you FFT them to get the freq domain waveform. Phenom, and NRSur, are computed quickly in the frequency domain
Many thanks Prof Weinstein!
The difficulty comes when “walking” through parameter space in an MCMC. There, you need to compute the waveforms maybe a million times. It can take hours or days.
Thank you all for answering. Just curious how long the developers of these libraries spent to develop them…
Many, many person years of effort. Hundreds of papers…
I see. Sometimes it feels complicated to use these products right away, without knowing much about their inner workings… ^^”
is applying matched filter limited to LIGO events?
can we take time corresponds to the peak in SNR as merger time
@Petra Matched filtering was developed in the 40’s for radar and (many, many) other applications for finding weak signals in noisy data. Your brain uses it to pick up “Hey Petra!” in a crowded noisy party (pre-covid).
How does LIGO deal with the "Look elsewhere effect" when considering such a big parameter spce for the search?
@Abhishek our matched filtering algorithm reports the time in terms of the “coalescence time” of the waveform template, which we *conventionally” define as the peak of the waveform template.
Sorry, I need to drop off for a bit
@Alan, thank you, so can we use matched filter for the stochastic GWBG?
@rcayruso Background estimation, as Derek will describe soon
Thank you Alan
@Petra for stochastic, we don’t have a “template”. Instead, we cross-correlate data from a pair of detectors (eg, LIGO Hanford and LIGO Livingston). The data from one detector is the stochastic “template” for the data from the other detector. So yes, it is a form of matched filtering.
@Petra All of the math for our (all sky) stochastic searches are in our many papers on the subject. Eg, our very first stochastic paper from 2003 - https://arxiv.org/pdf/gr-qc/0312088.pdf
@Alan perfect thank you
All developed by Joe Romano and Bruce Allen, more than 20 years ago
@rcayuso the plots Derek is showing now take into account the “look elsewhere” effect associated with 500,000 matched filter templates (also known as “trials factor”).
I’ve a question here in regards of GAN networks.
What is the research done in this regard?
In detecting GW?
“Many studies”. I just want to double click here….haha.
@Derek clap clap!!
can we use matched filter the strain data from one detector and use templet as strain data from another detector neglecting some known noice
How may I raise my hand?
in “participant window”, press raise hand
@Abhishek that’s essentially what unmodeled burst searches do.
Thank you @Jonnah.
And stochastic searches
@Ezekiel - MANY groups are working on this - https://phys.org/news/2018-04-machine-gravitational.html
if stochastic signal are in high frequency region
with less amplitude
@Ezekiel This is a recent summary of machine learning applications to GW data analysis: https://arxiv.org/pdf/2005.03745.pdf
Thank you @Alan! I’m just working into a postgraduate thesis that’s looking to improve on some of those methods. (Is not a PhD. something simpler…)
So, this link could be of huge help.
@Ezekiel There are many papers like this one - https://inspirehep.net/literature/1792015
(If you guys knows of any other, that could be really help full) thanks a ton!