Utilities for lstm model using gravitaion waves

source <path>/anaconda3/bin/activate
conda activate base

python3 -m venv env

Activation:

. env/bin/activate

pip install -r requirements.txt

# We'll first download some data for this demonstration
!curl -O -J -L https://losc.ligo.org/s/events/LVT151012/H-H1_LOSC_4_V2-1128678884-32.gwf

Parameters for generating one waveform in multiple detectors

from generator_waveform import generate_wave

apx = 'SEOBNRv4'


params = {
    'approximant':apx,
    'mass1':100,
    'mass2':10,
    'spin1z':0.9,
    'spin2z':0.4,
    'inclination':1.23,
    'coa_phase':2.45,
    'delta_t':1.0/4096,
    'f_lower':40
}

signal_h1, signal_l1, signal_v1 = generate_wave(params)

import keras.optimizers as optim

opt = optim.Adam(clipvalue=1,lr = 0.001)
model.compile(optimizer=opt, loss='mse')

Simple command:

	python dump_dataset.py -m1=10 -m2=20 -n=100 -time_steps=300 -quark=True

• m1 -- first mass of black hole,
• m2 -- second mass of black hole,
• -n -- numbers of signals,
• -time_steps -- lengh of signal,
• -create one feature with quark mass using ruleMc = (m1*m2)^(3/5)/(m1 + m2)^{1/5}

Datasets are stored into .hkl files. Example paterns of files D-SET-norm(100,300).hkl

• https://www.gw-openscience.org/auxiliary/GW170814/

References:

• https://dcc.ligo.org/LIGO-P1800129/public
• https://arxiv.org/abs/1602.03837