Binary Supernova Ejected Runaway Stars Code

Dias 2021 [https://vizier.cds.unistra.fr/viz-bin/VizieR-3?-source=J/MNRAS/504/356&-out.max=50&-out.form=HTML%20Table&-out.add=_r&-out.add=_RAJ,_DEJ&-sort=_r&-oc.form=sexa]

Sample Color-Magnitude Diagram

Demo

Part 0: Import necessary libraries

Import the functions necessary for the code:

%run runaway_functionsv2
%matplotlib qt

This also imports a list of young open clusters from (based on Dias+ 2021, Gaia DR2):

display(cluster_list)

Table length=399

Cluster	RA_ICRS	DE_ICRS	r50	Diameter	r50_table2	N	pmRA	e_pmRA	pmDE	e_pmDE	Plx	e_Plx	RV	e_RV	NRV	Dist	e_Dist	logage	e_logage	__Fe_H_	e__Fe_H_	Av	e_Av	FileName	SimbadName	_RA.icrs	_DE.icrs
	deg	deg	deg				mas / yr	mas / yr	mas / yr	mas / yr	mas	mas	km / s	km / s		pc	pc	log(yr)	log(yr)			mag	mag			deg	deg
str16	float64	float64	float32	float64	float64	int16	float32	float32	float32	float32	float32	float32	float64	float32	int16	int16	int16	float32	float32	float32	float32	float32	float32	str30	str31	float64	float64
ASCC_107	297.1623	22.0071	0.156	20.88	0.174	59	-0.144	0.135	-5.158	0.141	1.118	0.055	--	--	--	864	30	7.440	0.121	0.353	0.103	1.372	0.129	clusters1/ASCC_107.dat	[KPR2005] 107	297.1623	22.0071
ASCC_114	324.9790	53.9990	0.180	25.92	0.216	149	-3.754	0.210	-3.435	0.145	1.063	0.039	--	--	--	911	12	7.632	0.271	0.035	0.078	1.216	0.091	clusters1/ASCC_114.dat	[KPR2005] 114	324.9790	53.9990
ASCC_127	347.1807	64.9151	0.541	75.24	0.627	113	7.490	0.261	-1.781	0.319	2.618	0.080	-11.267	2.676	16	365	10	7.496	0.131	0.152	0.115	0.668	0.080	clusters1/ASCC_127.dat	[KPR2005] 127	347.1806	64.9151
ASCC_13	78.3057	44.4212	0.564	73.08	0.609	110	-0.477	0.111	-1.737	0.108	0.899	0.076	--	--	--	1066	26	7.615	0.098	-0.075	0.078	0.915	0.027	clusters1/ASCC_13.dat	[KPR2005] 13	78.3057	44.4212
ASCC_16	81.2025	1.6256	0.367	45.12	0.376	207	1.363	0.280	0.002	0.274	2.844	0.113	21.308	1.696	12	348	3	7.088	0.061	-0.062	0.069	0.224	0.045	clusters1/ASCC_16.dat	[KPR2005] 16	81.2025	1.6256
ASCC_19	82.0035	-1.9617	0.613	72.6	0.605	173	1.112	0.263	-1.303	0.241	2.756	0.088	23.576	2.719	10	356	2	7.139	0.030	0.076	0.077	0.189	0.043	clusters1/ASCC_19.dat	[KPR2005] 19	82.0035	-1.9617
ASCC_21	82.1423	3.4771	0.419	49.2	0.41	102	1.381	0.292	-0.610	0.237	2.893	0.132	15.313	3.818	8	343	5	7.102	0.038	-0.008	0.029	0.236	0.048	clusters1/ASCC_21.dat	[KPR2005] 21	82.1423	3.4771
ASCC_32	105.7112	-26.5758	0.646	78.72	0.656	255	-3.317	0.232	3.475	0.126	1.240	0.067	34.607	4.624	10	792	11	7.432	0.022	-0.003	0.048	0.220	0.019	clusters1/ASCC_32.dat	[KPR2005] 32	105.7112	-26.5758
ASCC_67	175.2892	-60.9906	0.165	21.96	0.183	46	-6.775	0.064	0.925	0.059	0.482	0.026	--	--	--	1921	89	7.483	0.227	0.215	0.095	0.810	0.044	clusters1/ASCC_67.dat	[KPR2005] 67	175.2893	-60.9906
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
UPK_540	114.5354	-58.4348	0.766	98.64	0.822	48	-4.815	0.212	7.661	0.210	2.663	0.097	14.456	3.188	3	365	4	7.513	0.043	-0.008	0.070	0.448	0.071	clusters1/UPK_540.dat	UPK 540	114.5354	-58.4348
UPK_604	224.3164	-59.8095	0.260	42.36	0.353	43	-4.548	0.144	-3.711	0.199	1.307	0.079	--	--	--	745	9	7.113	0.492	-0.209	0.314	1.773	0.417	clusters1/UPK_604.dat	UPK 604	224.3164	-59.8095
UPK_606	216.1298	-46.3629	0.716	93.84	0.782	46	-20.147	0.688	-16.551	0.686	5.882	0.184	10.435	2.725	7	167	2	7.231	0.142	-0.052	0.175	0.133	0.284	clusters1/UPK_606.dat	UPK 606	216.1299	-46.3628
UPK_62	289.7268	20.8263	0.110	13.92	0.116	33	-0.452	0.111	-5.418	0.128	1.075	0.056	--	--	--	885	21	7.039	0.246	0.021	0.254	3.421	0.257	clusters1/UPK_62.dat	UPK 62	289.7268	20.8263
UPK_621	237.1990	-54.3853	0.425	56.52	0.471	57	-2.471	0.150	-3.101	0.100	1.126	0.058	--	--	--	878	32	7.559	0.229	0.150	0.134	0.942	0.206	clusters1/UPK_621.dat	UPK 621	237.1990	-54.3853
UPK_640	250.4137	-39.5740	1.231	163.32	1.361	540	-12.014	0.917	-21.350	0.779	5.666	0.239	1.174	2.002	50	173	1	7.379	0.091	0.149	0.102	0.189	0.101	clusters1/UPK_640.dat	UPK 640	250.4138	-39.5739
vdBergh_130	304.4624	39.3404	0.049	5.88	nan	62	-3.609	0.308	-5.075	0.292	0.521	0.154	--	--	--	1456	240	6.974	0.091	-0.029	0.163	2.356	0.042	clusters2/vdBergh_130.dat	Cl VDB 130	304.4624	39.3404
vdBergh_80	97.7471	-9.6215	0.151	17.16	0.143	60	-3.285	0.430	0.481	0.361	1.026	0.112	--	--	--	947	2	6.790	0.046	-0.148	0.091	1.726	0.219	clusters1/vdBergh_80.dat	Cl VDB 80	97.7471	-9.6215
vdBergh_85	101.7288	1.3329	0.045	4.8	0.04	29	-0.973	0.147	0.345	0.164	0.550	0.049	--	--	--	1720	167	7.104	0.125	-0.055	0.124	1.206	0.270	clusters1/vdBergh_85.dat	Cl VDB 85	101.7288	1.3329
vdBergh_92	106.0426	-11.4884	0.114	13.44	0.112	154	-4.539	0.219	1.607	0.211	0.834	0.091	27.580	6.680	2	1114	42	6.749	0.074	0.025	0.087	0.984	0.062	clusters1/vdBergh_92.dat	Cl VDB 92	106.0426	-11.4884

Part 1: Obtain the cluster class object

using the get_cluster function from the runaway_functions.py, with the cluster_name as the input, we obtain the parameters of the cluster.

example usage:

cluster_name = 'ASCC_21'
import os
from astropy.table import Table, Column
from runaway_functions import get_cluster
cluster = get_cluster(cluster_name)
display(cluster)

This imports all the details for the cluster. Various parameters of the cluster can be accessed:

• Name
• Diameter (r50 Diameter: Diameter within which 50% of the cluster members lie)
• Number of Cluster members etc. All parameters can be accessed together by:

cluster_name = 'ASCC_21'
cluster = Cluster(cluster_name)
cluster.all

Row index=0

Cluster	RA_ICRS	DE_ICRS	r50	Diameter	r50_table2	N	pmRA	e_pmRA	pmDE	e_pmDE	Plx	e_Plx	RV	e_RV	NRV	Dist	e_Dist	logage	e_logage	__Fe_H_	e__Fe_H_	Av	e_Av	FileName	SimbadName	_RA.icrs	_DE.icrs
	deg	deg	deg				mas / yr	mas / yr	mas / yr	mas / yr	mas	mas	km / s	km / s		pc	pc	log(yr)	log(yr)			mag	mag			deg	deg
str16	float64	float64	float32	float64	float64	int16	float32	float32	float32	float32	float32	float32	float64	float32	int16	int16	int16	float32	float32	float32	float32	float32	float32	str30	str31	float64	float64
ASCC_21	82.1423	3.4771	0.419	49.2	0.41	102	1.381	0.292	-0.610	0.237	2.893	0.132	15.313	3.818	8	343	5	7.102	0.038	-0.008	0.029	0.236	0.048	clusters1/ASCC_21.dat	[KPR2005] 21	82.1423	3.4771

Part 2: Search stars in a region around the cluster

Using the calculate_search_arcmin function from runaway_functions, calculate the region to be searched around the cluster. by default it is $10\ \mathrm{pc}$ around the clusters (from the edge of the cluster). This returns an astropy quantity object and prints its value.

cluster.calculate_search_arcmin()

$124.771 \mathrm{{}^{\prime}}$

We can also visualize this search region using:

cluster.plot_search_region()

Using this as the search radius for a conic search around the cluster center coordinates, we find a table of all the stars in the cone.

Getting runaways (all functions necessary included):

cluster = Cluster('Ruprecht_170')
cluster.generate_tables()
theoretical_data = theoretical_isochrone(cluster,output="table",printing=False)
fs = cluster.read_table('fs')
runaways = get_runaways(cluster,fs,theoretical_data)
display(runaways)