Tutorials

aswns

Anonymous (anonymous@undisclosed.example.com) — 2022-08-16T20:55:00+00:00

ASWNS Summary ASWNS stands for “Arcetri-Stockholm-Warsaw Neutron Stars”. The code was mainly developed by G. Camelio, is an extension of the XNS-v2 code , and computes rotating neutron star configurations using the extended Conformal Flatness approximation and is written in FORTRAN 90. The main assumptions used in the code are stationarity, axisymmetry, and circularity (the matter motion is purely toroidal) of the solution. However, the rotation profile can be generic, i.e., both rigid and di…

at2017gfo_data

Anonymous (anonymous@undisclosed.example.com) — 2022-02-20T10:10:34+00:00

AT2017gfo data 2017-08-18T00:00:00.000 g 17.41000 0.02000 2017-08-18T00:00:00.000 r 17.56000 0.04000 2017-08-18T00:00:00.000 i 17.48000 0.03000 2017-08-18T00:00:00.000 z 17.59000 0.03000 2017-08-18T00:00:00.000 y 17.46000 0.01000 2017-08-18T00:00:00.000 J 17.88000 0.03000 2017-08-18T00:00:00.000 H 18.26000 0.15000 2017-08-18T00:00:00.000 K 18.62000 0.11000 2017-08-18T05:32:38.400 i 17.24000 0.06000 2017-08-18T05:32:38.400 z 17.26000 0.06000 2017-08-18T05:32:38.400 y 17.38000 0.10000 2017-08-18T1…

basics_gwinf

Anonymous (anonymous@undisclosed.example.com) — 2022-08-19T08:55:02+00:00

Basics of Inference The General Idea Statistical inference refers to any method that tries to infer knowledge on an underlying distribution, e.g. neutron star masses, from the analysis of a limited dataset, e.g. observed neutron stars. In the specific case of Bayesian Inference this is done by applying Bayes' theorem. The sought-after$n_{live}* ln(1+ n_{cores}/n_{live})$$n_{modes} << n_{live}$

bilby

Anonymous (anonymous@undisclosed.example.com) — 2022-08-30T14:34:17+00:00

Tutorial for Bilby Bilby is a user-friendly Bayesian inference library developed by Gregory Ashton et al. (2018) [1]. The aim of bilby is to provide a user-friendly interface to perform gravitational-wave parameter estimation for compact binary coalescence events. Plesae note that bilby is explained in-depth

bilbyfw_install

Anonymous (anonymous@undisclosed.example.com) — 2022-09-12T15:32:58+00:00

Installation of the Bilby Framework All of the following explanations expect that you use a linux command line. Whenever some names are subject to your choice, they are marked as [CHOICE]. If you encounter trouble, consider the remarks at the end of the page.

binary_neutron_stars

Anonymous (anonymous@undisclosed.example.com) — 2022-07-18T10:27:16+00:00

Binary Neutron Star Systems A system consisting of two neutron stars is called a binary neutron star or a double neutron star system. Numerous of these systems exist and have been observed through electromagnetic observations. Among the best well-known binary neutron star system is the Hulse-Taylor Pulsar. The observation of the increase in the orbital frequency of the Hulse-Taylor Pulsar has been the first indirect evidence for the emission of gravitational waves. In 2017 it was for the first…

black_hole_neutron_star_binary

Anonymous (anonymous@undisclosed.example.com) — 2022-07-18T10:30:21+00:00

Black Hole - Neutron Star Systems Similar to binary neutron star systems, a neutron star can also be on a bound orbits with a black hole. Such black hole - neutron star systems have been observed for the first time in January 2020 with GW200105 and GW200115. Given the presence of matter the collision of a black hole neutron star system could in principle also be connected with electromagnetic counterparts, however, we have not been able to confidentially detect a short gamma-ray burst or a kil…

black_holes

Anonymous (anonymous@undisclosed.example.com) — 2022-07-18T09:23:04+00:00

Black Holes Black holes are characterized by extreme gravity, which is so strong that not even electromagnetic radiation can escape. Within Einstein's Theory of General Relativity, such objects could exist if enough mass/energy is comprised in a sufficiently small volume. While black holes have no clear boundary, one often uses the event horizon to determine the size of a black hole. The event horizon characterizes the distance at which nothing (not even light) can escape from the black hole. T…

comb_analysis

Anonymous (anonymous@undisclosed.example.com) — 2022-02-27T08:46:12+00:00

Combined Analysis NMMA is capable of performing combined analyses to constrain: * the neutron star equation of state (EOS), and * the Hubble Constant. In the following, we will take the EOS analysis as an example. EOS analysis Generate a simulation set

compact_objects

Anonymous (anonymous@undisclosed.example.com) — 2022-07-18T09:02:47+00:00

Compact Objects * Neutron Stars * Black Holes * Exotic Compact Objects

config-jointinf

Anonymous (anonymous@undisclosed.example.com) — 2022-02-26T10:06:53+00:00

conig.ini for GW170817+GRB170817A+AT2017gfo ################################################################################ ## Data generation arguments ################################################################################ trigger_time = 1187008882.43 ################################################################################ ## Detector arguments ################################################################################ detectors = [H1, L1, V1] psd_dict = {H1=data/GW17081…

ejecta

Anonymous (anonymous@undisclosed.example.com) — 2021-08-05T12:36:08+00:00

Examples for the computation of ejecta properties An essential part in the modeling of kilonova lightcurves is the computation of ejecta properties based on the binary parameters. Below are some simple code snippets that allow for such a computation.

examples_aswns

Anonymous (anonymous@undisclosed.example.com) — 2022-08-16T20:54:17+00:00

Examples * Computing non-barotropic stars * This test follows the computation focusses on the computation of a non-barotropic configuration * Computing stars at the Kepler limit * This test follows the computation performed in Camelio et al., 2019. While the code is not perfectly identical to the one used for the paper, the code changes have been minimal.

examples_aswns_kepler

Anonymous (anonymous@undisclosed.example.com) — 2022-08-16T22:02:32+00:00

Computing stars at the Kepler limit It is worth pointing out that this test case takes up more runtime than the other that is provided for the computation of the non-barotropic configuration, hence, it might be useful to check out this test first if you have not done so. Theoretical Background and Input Parameters

examples_aswns_nonbaro

Anonymous (anonymous@undisclosed.example.com) — 2022-08-16T20:52:13+00:00

Computing non-barotropic stars Theoretical Background and Model Parameters For a careful theoretical understanding, one has to investigate the exact model parameters that are employed. The equation of state follows the form (Eq. 45 of Camelio et al., 2019): [EOS1] with the thermal barotropic law

excotic_compact_objects

Anonymous (anonymous@undisclosed.example.com) — 2022-07-18T09:36:38+00:00

Exotic Compact Objects In addition to black holes and neutron stars, which have been detected in the past and which we know exist, there are numerous proposals for exotic compact objects, the following is a not complete list of various possibilities:

general_aswns

Anonymous (anonymous@undisclosed.example.com) — 2022-08-16T21:17:05+00:00

General Settings In addition to the tests, we will here consider the general settings of the ASWNS code. These settings can be found in the file ASWNS.f90 and determine fundamental constants, but also the grid setup, or iteration details. If you open ASWNS.f90, you will find the following parameters

grb170817a

Anonymous (anonymous@undisclosed.example.com) — 2022-02-21T10:46:00+00:00

GRB170817A data 2017-12-06T00:31:40.800 F606W 26.31 0.19 2018-01-01T13:45:07.200 F606W 26.59 0.23 2018-01-29T17:18:14.400 F606W 26.50 0.19 2018-02-05T17:45:36.000 F606W 26.58 0.22 2018-03-14T15:01:26.400 F606W 26.61 0.26 2018-03-23T21:28:48.000 F606W 26.90 0.31 2018-06-10T07:50:52.800 F606W 27.29 0.35 2018-07-11T18:02:52.800 F606W 27.58 0.35 2018-07-20T08:34:04.800 F606W 27.20 inf 2018-08-14T20:26:52.800 F606W 27.83 0.29 2019-03-24T15:48:57.600 F606W 28.20 inf 2018-05-11T12:41:41.430 radio-5.5GH…

grb211211a-data

Anonymous (anonymous@undisclosed.example.com) — 2022-05-18T11:52:19+00:00

GRB211211A data 2021-12-11T14:06:36.000 u 19.72 0.15 2021-12-11T14:35:24.000 u 19.45 0.19 2021-12-11T17:42:36.000 u 19.76 0.07 2021-12-11T19:37:48.000 g 20.34 0.2 2021-12-11T19:37:48.000 r 20.26 0.1 2021-12-11T19:37:48.000 i 20.37 0.3 2021-12-11T23:28:12.000 r 20.25 0.07 2021-12-11T23:57:00.000 z 19.88 0.3 2021-12-12T00:11:24.000 r 20.26 0.13 2021-12-12T04:59:24.000 u 20.36 inf 2021-12-12T05:28:12.000 i 20.75 0.08 2021-12-12T05:42:36.000 g 21.0 0.04 2021-12-12T05:42:36.000 r 20.81 0.05 2021-12-1…

gw_inference

Anonymous (anonymous@undisclosed.example.com) — 2023-06-25T15:26:28+00:00

Inference of gravitational-wave signals A Bayesian analysis of a gravitational-wave signal which is not accompanied by electromagnetic signals can be performed within nmma following two main steps: 1) setting up a config.ini file and running the command

gw_routines

Anonymous (anonymous@undisclosed.example.com) — 2022-08-19T07:50:02+00:00

Helpful Routines In this directory, you will find multiple helpful routines that can assist the previous steps.

gwem_resampling

Anonymous (anonymous@undisclosed.example.com) — 2023-01-04T11:46:24+00:00

GW-EM Resampling In NMMA, it is possible to use the results from GW, kilonova and GRB afterglow inferences to get estimates on the binary properties. This is based on phenomenological relations, i.e., via fits based on numerical-relativity relations. The dynamical ejecta mass, $M_{ej}^{dyn}$$m_{1,2}$$\mathcal{M}_{c}$$q$$D_{L}$$M_{c}$$q$$\tilde{\Lambda}$$\alpha$$\zeta$

gwemlightcurves

Anonymous (anonymous@undisclosed.example.com) — 2022-07-22T19:30:08+00:00

Tutorial for gwemlightcurves The gwemlightcurve package provides a possibility to compute kilonova lightcurves and spectra. The package is developed by Prof. M. W. Coughlin and collaborators. Over the last years, multiple features from gwemlightcurves got ported and it is likely that gwemlightcurve will (at some point) not be supported anymore.

gwprior-grb211211a

Anonymous (anonymous@undisclosed.example.com) — 2022-05-19T09:58:00+00:00

GRB211211A - GW prior file chirp_mass = Uniform(name='chirp_mass', minimum=0.8, maximum=2.0) mass_ratio = Uniform(name='mass_ratio', minimum=0.125, maximum=1) mass_1 = Constraint(name='mass_1', minimum=1.001398, maximum=4.313897948277728) mass_2 = Constraint(name='mass_2', minimum=1.001398, maximum=4.313897948277728) a_1 = Uniform(name='a_1', minimum=0, maximum=0.05, boundary='reflective') a_2 = Uniform(name='a_2', minimum=0, maximum=0.05, boundary='reflective') tilt_1 = Sine(name='tilt_1', boun…

gwsample-generation

Anonymous (anonymous@undisclosed.example.com) — 2022-05-19T09:53:59+00:00

GW sample generation In order to generate EOS samples, we need a posterior probability file computed for a certain EOS set. Here, we use the 15nsat_cse_uniform_R14 EOS folder (get tar.gz) and its respective probability file, which can be found here. import numpy as np import pandas as pd import bilby # load posterior file eos_post = np.loadtxt('./posterior_probability_files/Astro/15nsat_cse_uniform_R14/posterior_probability.txt') npts = 150000 Neos = 5000 nparams = 3 ############# [mass1, …

h0_estimate

Anonymous (anonymous@undisclosed.example.com) — 2022-05-19T08:58:35+00:00

Hubble Constant Estimation

incl_eos

Anonymous (anonymous@undisclosed.example.com) — 2023-06-10T19:28:54+00:00

Including EOS information NMMA enables to include nuclear physics information by sampling on the equation-of-state (EOS). Explanation of EOS sets - compatible with NMMA Weighting and sorting of EOS information

inf_gw_only

Anonymous (anonymous@undisclosed.example.com) — 2022-03-02T10:28:35+00:00

Gravitational-Wave Inference For gravitational-wave parameter estimation, NMMA builds on bilby, parallel-bilby and bilby-pipe as back-end packages. For a detailed description follow the links to respective repositories. However, with special patches developed for bilby and parallel-bilby, NMMA enables to sample over EOSs during parameter estimation runs and, hence, allows to include more physical information of BNSs.

inf_mma

Anonymous (anonymous@undisclosed.example.com) — 2023-06-16T14:28:26+00:00

Multi-messenger inference A joint inference on gravitational-wave and electromagnetic signals requires NMMA to run on a supercomputer cluster because large memory space are required and need to be shared across many CPU cores. Here, we consider a full joint inference on the binary neutron star merger observed on 17th August 2017. For an example installtion of NMMA on the supercomputer cluster HAWK consult

infparams_nmma

Anonymous (anonymous@undisclosed.example.com) — 2022-06-09T10:33:43+00:00

Inference parameters In nmma/em/analysis.py, several inference parameters can be chosen. Some of the most important parameters will be explained in more detail in the following. Trigger time trigger-time Depending on the type of inference, the trigger time for an observed event needs to be provided:

injections_nmma

Anonymous (anonymous@undisclosed.example.com) — 2023-06-15T14:48:40+00:00

Injections using NMMA Injections files For a parameter estimation run on simulated data (i.e., when no observational data is available), an injection-file line is required in your config.ini-file pointing a dat or json injection file. The injection file itself contains a list of values for each source parameter (such as masses, spins, distance etc.) and is used to generate synthetic electromagnetic or gravitational-wave signals for particular sources (e.g. BNS, NSBH).

installation

Anonymous (anonymous@undisclosed.example.com) — 2021-08-04T21:44:51+00:00

Installation Setting up a virtual environment (Optional) While it is not strictly necessary, it reduces possible conflicts if one installs python packages that do not need to be avalable systemwide into local, virtual environments. An easy option to setup such virtual environments is the

installation_aswns

Anonymous (anonymous@undisclosed.example.com) — 2022-08-16T08:03:41+00:00

Installation ASWNS requires the following prerequisites: * a suitable fortran compiler, e.g., gfortran * lapack library or separately the XEBLA subroutine The easiest way to achieve these requirement is simply by typing: sudo apt-get install gfortran liblapack3

installation_nmma

Anonymous (anonymous@undisclosed.example.com) — 2023-06-10T18:51:44+00:00

Installation For the installation of NMMA on smaller servers (e.g. our Uni Potsdam machines) a conda environment can be used for installation, while for larger cluster such as HAWK or Supermuc, a python virtual-environment is the better way to install NMMA. The main reason for the latter is that the mpi4py python package installed within a conda environment can be incompatible with default modules given by a specific cluster.

lc_comb_inference

Anonymous (anonymous@undisclosed.example.com) — 2023-06-16T13:14:29+00:00

Combined light curve inference Whereas the previous section dealt with stand-alone Bayesian inferences with different models (kilonova, GRB afterglow), NMMA enables to run a combined inference using multiple models. Below, we show examples for 2 different types of sources:

lc_generation

Anonymous (anonymous@undisclosed.example.com) — 2023-06-02T17:05:52+00:00

Light curve generation NMMA enables to generate electromagnetic light curves in different electromagnetic regimes. For the light curve generation, the user can select among different models. The current version of NMMA includes three kilonova light curve models and enables to compute Gamma-ray burst afterglow light curves which is based on the model

lc_inference

Anonymous (anonymous@undisclosed.example.com) — 2023-06-10T18:58:39+00:00

Inference of electromagnetic signals NMMA enables to perform parameter estimation in different electromagnetic regimes such as for kilonovae and gamma-ray burst afterglows. Similarly to light curve generation, the following models are available for kilonova inference:

lc_training

Anonymous (anonymous@undisclosed.example.com) — 2022-02-13T14:35:41+00:00

Light curve training

lightcurves

Anonymous (anonymous@undisclosed.example.com) — 2022-07-22T19:14:22+00:00

Computation of lightcuves * How to compute lightcurves * Detailed list of lightcurve models

lightcurves_examples

Anonymous (anonymous@undisclosed.example.com) — 2021-08-04T22:14:14+00:00

Examples for the computation of lightcurves This code snippet should allow the computation of the lightcurves using the simple, analytical model derived by Brian Metzger: import matplotlib import matplotlib.pyplot as plt matplotlib.use('TkAgg') %matplotlib inline from gwemlightcurves.sampler.model import Me2017_model t_Me, lbol_Me, mag_Me = Me2017_model(mej=1e-2,vej=0.1,beta=3,kappa_r=25) for i in range(1,8): plt.plot(t_Me, mag_Me[i]) plt.xlim(1, 14) plt.ylim(-10, -15) plt.show(…

lightcurves_models

Anonymous (anonymous@undisclosed.example.com) — 2022-07-22T19:13:46+00:00

List of available lightcurve models In the following, we present a list of kilonova models, for the most important ones, we provide references and list the input parameters. KaKy2016 Kawaguchi et al., Astrophys.J. 825 (2016) 1, 52 Simplified analytical model for the description of BHNS systems.

model_grids

Anonymous (anonymous@undisclosed.example.com) — 2023-06-16T10:38:42+00:00

Create model grids Some models are analytic / semi-analytic that can be sampled. Others rely on sampling from a grid of modeled light curves through the use of Principle Component Analysis (PCA) and an interpolation scheme which can be: * Gaussian process modeling, or

models_nmma

Anonymous (anonymous@undisclosed.example.com) — 2023-06-16T10:32:46+00:00

Available models NMMA will be under continuous development meaning that new astrophysical models such as for kilonovae, supernovae, gamma-ray bursts and so on will be implemented over time. Therefore, it is worthwhile to check out the model_parameters_dict$M_{ej}^{dyn}$$M_{ej}^{wind}$$\phi$$\theta_{obs}$$E_{K, iso}$$\theta_{c}$$\theta_{v}$$n$$p$$\epsilon_{e}$$\epsilon_{B}$$M_{e}$$R_{e}$$E_{e}$

neutron_stars

Anonymous (anonymous@undisclosed.example.com) — 2022-07-18T08:59:41+00:00

Neutron Stars In the 1930s the concept of a neutron star was introduced as a theoretically possible state of an astrophysical compact object. The first observational evidence arose in 1967 when Jocelyn Bell, Antony Hewish, and Martin Ryle detected radio signals from a pulsar. Since now more than 2000 neutron stars have been detected, but only for a few of them, it was possible to measure the neutron star masses reliably.

nmma-hawk-install

Anonymous (anonymous@undisclosed.example.com) — 2022-02-26T08:49:03+00:00

Installation of NMMA on supercomputer clusters Example: HAWK

nmma

Anonymous (anonymous@undisclosed.example.com) — 2023-06-16T14:37:49+00:00

Tutorial for NMMA NMMA is a fully featured, Bayesian multi-messenger pipeline targeting joint analyses of gravitational-wave and electromagnetic data. Using bilby as the back-end, the software is capable of sampling these data sets using a variety of samplers. It uses chiral effective field theory based neutron star equation of states when performing inference, and is also capable of estimating the Hubble Constant.

obs_data

Anonymous (anonymous@undisclosed.example.com) — 2023-06-16T10:24:42+00:00

Observational data In contrast to synthetic data, NMMA can make use of observational data both from electromagnetic and gravitational-wave observations. In order to make sure that the NMMA framework can smoothly read in and interpret observed signals, a short description of the data structure can be found below.

pbilby_ana

Anonymous (anonymous@undisclosed.example.com) — 2022-08-30T18:45:35+00:00

Parallel Bilby Analysis The Basic Idea Once everything is set up, parallel_bilby is ready to go and you might simply hit parallel_bilby_analysis to finish the job. However, in a realistic setting of gravitational wave inference, the run will hardly converge in an acceptable amount of time on your local machine. Instead, you will need to work on a computer cluster that handles expensive computations. To allocate its ressources efficiently, most modern clusters use a

pbilby_gen

Anonymous (anonymous@undisclosed.example.com) — 2022-08-30T14:32:06+00:00

Parallel Bilby Generation The Basic Idea To run efficiently, parallel bilby requires some preparatory work, just as efficient construction work requires some preparatory logistical planning. Fortunately, you do not need to do this on your own. Instead, you can outsource this task to a $\Lambda_{1,2}$$Lambda$$i$$i$

prior-bunsbh-grb211211a

Anonymous (anonymous@undisclosed.example.com) — 2022-05-18T13:33:39+00:00

GRB211211A prior - NSBH source luminosity_distance = Uniform(minimum=0, maximum=1000, name='luminosity_distance',latex_label='$D_L$') inclination_EM = Sine(name='inclination_EM', minimum=0., maximum=np.pi/2., latex_label='$\\iota$') KNtimeshift = 0.0 log10_E0 = Uniform(minimum=49., maximum=55., name='log10_E0',latex_label='$\\log_{10}E_0$') thetaCore = Uniform(name='theta_core', minimum=0.01, maximum=np.pi/5., latex_label='$\\theta_c$') thetaWing = Uniform(name='theta_wing', minimum=0.01, maxim…

prior-grb211211a

Anonymous (anonymous@undisclosed.example.com) — 2022-05-18T13:40:02+00:00

GRB211211A prior - BNS source KNphi = Uniform(name='KNphi', minimum=15., maximum=75., latex_label='$\Phi$') inclination_EM = Sine(name='inclination_EM', minimum=0., maximum=np.pi/2., latex_label='$\\iota$') KNtimeshift = 0.0 log10_mej_dyn = Uniform(name='log10_mej_dyn', minimum=-3., maximum=-1., latex_label='$\\log_{10}M^{\\rm{dyn}}_{\\rm{ej}}$') log10_mej_wind = Uniform(name='log10_mej_wind', minimum=-3., maximum=-0.5, latex_label='$\\log_{10}M^{\\rm{wind}}_{\\rm{ej}}$') luminosity_distance = …

running

Anonymous (anonymous@undisclosed.example.com) — 2022-07-22T20:14:58+00:00

Running The gwemlightcurves package enables us to compute a variety of things and has different packages: * Computation of ejecta properties * Computation of lightcurves * Bayesian Analysis of observational data (outdated and removed, we suggest to use the NMMA pipeline)

start

Anonymous (anonymous@undisclosed.example.com) — 2024-08-16T20:48:52+00:00

Tutorials and Documentation The tutorials and documentation are provided by the Theoretical Astrophysics Group and Friends. Theoretical Brackground * Compact Objects * Compact Binary Merger * Gravitational Waves * Kilonovae Software Packages * ASWNS, a software package for the computation of rotating stars

theoreticalbackground_cbc

Anonymous (anonymous@undisclosed.example.com) — 2022-07-18T10:10:35+00:00

Compact Binary Mergers Numerous compact objects are bound inside binary systems, some of these, so-called compact binary systems are either binary neutron star systems (often also called double neutron star systems), black hole - neutron star systems, and binary black hole systems. On top of these, well-established scenarios, there is also the possibility for the existence of exotic compact objects that also could be bound inside compact binaries. In the following, we will provide some addit…

theoreticalbackground_kilonovae

Anonymous (anonymous@undisclosed.example.com) — 2022-07-22T18:53:26+00:00

Kilonovae Kilonovae are electromagnetic transients observable in the infrared, optical, and ultraviolet bands (see below for a comparison between the observed data for AT2017gfo and theoretical predictions). Kilonovae originate from the neutron-rich outflows that are created during and after the merger of a binary neutron star or black hole – neutron star systems. During these outflows, it is possible that due to the r-process (see below), heavy, unstable elements can form. These unstable elem…

theoreticalbrackground

Anonymous (anonymous@undisclosed.example.com) — 2021-08-04T21:56:08+00:00

Theoretical Background Kilonovae Kilonovae are electromagnetic transients observable in the infrared, optical, and ultraviolet bands. They originate from the neutron-rich outflows that are created during and after the merger of a binary neutron star or black hole – neutron star systems.

theoreticalbrackground_gw

Anonymous (anonymous@undisclosed.example.com) — 2022-07-18T11:05:23+00:00

Gravitational-Wave Emission Gravitational waves are tiny ripples of the spacetime. These ripples are produced through the accelerated motion of heavy objects and they propagate as transversal waves outward from their source at the speed of light. While already proposed by Heaviside and Poincaré, it was Albert Einstein who had set the fundament for a correct interpretation and computation of these sources based on his Theory of General Relativity.