NGC 2516 vs the Pleiades

These two clusters have similar ages, but do their CMDs show a similar morphology for low-mass stars?


In [1]:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np

Import NGC 2516 low-mass star data.


In [2]:
ngc2516 = np.genfromtxt('data/ngc2516_Christophe_v3.dat')                   # data for this study from J&J (2012)
irwin07 = np.genfromtxt('data/irwin2007.phot')                              # data from Irwin+ (2007)
jeffr01 = np.genfromtxt('data/jeff_2001.tsv', delimiter=';', comments='#')  # data from Jeffries+ (2001)
jeffr01 = np.array([star for star in jeffr01 if star[9] == 1])              # extract candidate members

Jackson et al. (2009) recommend a small correction to I-band magnitudes from Irwin et al. (2007) to place them on the same photometric scale as Jeffries et al. (2001), which they deem to be "better calibrated." Jackson & Jeffries (2012) suggest that the tabulated data (on Vizier) has been transformed to the "better calibrated" system. Key to understanding their results, however, is to also transform $(V-I_C)$ and then calculate a correction to $V$-band magnitudes, as well.


In [3]:
irwinVI       = (irwin07[:, 7] - irwin07[:, 8])*(1.0 - 0.153) + 0.300
irwin07[:, 8] = (1.0 - 0.0076)*irwin07[:, 8] + 0.080
irwin07[:, 7] = irwinVI + irwin07[:, 8]

Note that it is not immediately clear whether this correction should be applied to photometric data cataloged by Jackson & Jeffries (2012). Reading through Irwin et al. (2007) and Jackson & Jeffries (2012), it appears that the transformations are largely performed to transform the Irwin+ photometric system (Johnson $I$-band) into Cousins $I_C$ magnitudes. There may be reasons related to a "better calibration," but the issue is to first and foremost put them in the same photometric system. Why that involves altering the $V$-band magnitudes is not abundantly clear.

Now data for the Pleiades.


In [4]:
pleiades_s07 = np.genfromtxt('../pleiades_colors/data/Stauffer_Pleiades_litPhot.txt', usecols=(2, 3, 5, 6, 8, 9, 13, 14, 15))
pleiades_k14 = np.genfromtxt('../pleiades_colors/data/Kamai_Pleiades_cmd.dat', usecols=(0, 1, 2, 3, 4, 5))
iso_emp_k14  = np.genfromtxt('../pleiades_colors/data/Kamai_Pleiades_emp.iso') # empirical Pleiades isochrone

Adopt literature values for reddening, neglecting differential reddening across the Pleiades.


In [5]:
pl_dis = 5.61
pl_ebv = 0.034
pl_evi = 1.25*pl_ebv
pl_evk = 2.78*pl_ebv
pl_eik = pl_evk - pl_evi
pl_av  = 3.12*pl_ebv

ng_dis = 7.95
ng_ebv = 0.12
ng_evi = 1.25*ng_ebv
ng_evk = 2.78*ng_ebv
ng_eik = ng_evk - ng_evi
ng_av  = 3.12*ng_ebv

Overlay the CMDs for each cluster, corrected for reddening and distance.


In [6]:
fig, ax = plt.subplots(1, 2, figsize=(12., 8.), sharex=True, sharey=True)

for axis in ax:
    axis.grid(True)
    axis.tick_params(which='major', axis='both', length=15., labelsize=16.)
    axis.set_ylim(12., 5.)
    axis.set_xlim(0.5, 3.0)
    axis.set_xlabel('$(V - I_C)$', fontsize=20.)

ax[0].set_ylabel('$M_V$', fontsize=20.)

ax[0].plot(jeffr01[:,5] - ng_evi, jeffr01[:,3] - ng_av - ng_dis, 
            'o', markersize=4.0, c='#555555', alpha=0.2)
ax[0].plot(irwin07[:, 7] - irwin07[:, 8] - ng_evi, irwin07[:, 7] - ng_av - ng_dis, 
            'o', c='#1e90ff', markersize=4.0, alpha=0.6)
ax[0].plot(ngc2516[:, 1] - ngc2516[:, 2] - ng_evi, ngc2516[:, 1] - ng_av - ng_dis, 
            'o', c='#555555', markersize=4.0, alpha=0.8)
ax[0].plot(iso_emp_k14[:, 2] - pl_evi, iso_emp_k14[:, 0] - pl_av - pl_dis, 
               dashes=(20., 5.), lw=3, c='#b22222')

ax[1].plot(irwin07[:, 7] - irwin07[:, 8] - ng_evi, irwin07[:, 7] - ng_av - ng_dis, 
            'o', c='#1e90ff', markersize=4.0, alpha=0.6)
ax[1].plot(ngc2516[:, 1] - ngc2516[:, 2] - ng_evi, ngc2516[:, 1] - ng_av - ng_dis, 
            'o', c='#555555', markersize=4.0, alpha=0.6)
ax[1].plot(iso_emp_k14[:, 2] - pl_evi, iso_emp_k14[:, 0] - pl_av - pl_dis, 
               dashes=(20., 5.), lw=3, c='#b22222')


Out[6]:
[<matplotlib.lines.Line2D at 0x1085b4a10>]

While the Stauffer et al (2007) and Jackson et al. (2009) samples lie a bit redward of the median sequence in the Jeffries et al. (2001), the former two samples compare well against the empirical cluster sequence (shown as a red dashed line; Kamai et al. 2014) from the Pleiades in a $M_V/(V-I_C)$ CMD.

What about $M_V/(V-K)$ and $M_V/(I_C-K)$ CMDs?


In [7]:
fig, ax = plt.subplots(1, 2, figsize=(12., 8.), sharey=True)

for axis in ax:
    axis.grid(True)
    axis.tick_params(which='major', axis='both', length=15., labelsize=16.)
    axis.set_ylim(12., 5.)
    
ax[0].set_xlim(1.0, 6.0)
ax[0].set_xlabel('$(V - K)$', fontsize=20.)
ax[0].set_ylabel('$M_V$', fontsize=20.)

# include K_CIT --> K_2mass correction for NGC 2516
ax[0].plot(ngc2516[:, 1] - ngc2516[:, 3] - 0.024 - ng_evk, ngc2516[:, 1] - ng_av - ng_dis, 
            'o', c='#555555', markersize=4.0, alpha=0.6)
ax[0].plot(iso_emp_k14[:, 3] - pl_evk, iso_emp_k14[:, 0] - pl_av - pl_dis, 
               dashes=(20., 5.), lw=3, c='#b22222')

ax[1].set_xlim(0.5, 3.0)
ax[1].set_xlabel('$(I_C - K)$', fontsize=20.)

ax[1].plot(ngc2516[:, 2] - ngc2516[:, 3] - 0.024 - ng_eik, ngc2516[:, 1] - ng_av - ng_dis, 
            'o', c='#555555', markersize=4.0, alpha=0.6)
ax[1].plot(iso_emp_k14[:, 3] - iso_emp_k14[:, 2] - pl_eik, iso_emp_k14[:, 0] - pl_av - pl_dis, 
               dashes=(20., 5.), lw=3, c='#b22222')


Out[7]:
[<matplotlib.lines.Line2D at 0x107b2bc50>]

While data in the $M_V/(V-I_C)$ CMD appears to be bluer for early M-dwarf stars and redder for later M-dwarf stars, we find that M-dwarfs in NGC 2516 appear to be generally bluer than low-mass stars in the Pleiades.

An interesting implication is that empirical isochornes based on the Pleiades or NGC 2516 may not reliably fit other clusters. Something is different between the two. Is it magnetic activity, or perhaps chemical composition?


$(B-V)/(V-I_C)$ color-color diagram using data from Jeffries et al. (2001) for NGC 2516.


In [8]:
fig, ax = plt.subplots(1, 1, figsize=(6., 8.))

ax.grid(True)
ax.tick_params(which='major', axis='both', length=15., labelsize=16.)
ax.set_xlim(-0.5, 2.0)
ax.set_ylim( 0.0, 2.5)
ax.set_ylabel('$(V - I_C)$', fontsize=20.)
ax.set_xlabel('$(B - V)$', fontsize=20.)

ax.plot(jeffr01[:,4] - ng_ebv, jeffr01[:,5] - ng_evi, 
            'o', markersize=4.0, c='#555555', alpha=0.2)
ax.plot(iso_emp_k14[:, 1] - pl_ebv, iso_emp_k14[:, 2] - pl_evi, 
               dashes=(20., 5.), lw=3, c='#b22222')


Out[8]:
[<matplotlib.lines.Line2D at 0x108275e10>]

The empirical isochrone from Kamai et al. (2014) agrees well with photometric data for NGC 2516, with both corrected for differential extinction. There may be some small disagreements at various locations along the sequence, but the morphology of the empirical isochrone is broadly consistent with NGC 2516. However, stars in NGC 2516 appear to have bluer $(B-V)$ colors for $(V-I_C) > 1.8$.


Exploring a transformation of the Irwin+ data from Johnson $(V-I)$ to Cousins $(V-I_C)$ from Bessell (1979). This is ignoring issues related to photometric calibrations, that Jackson & Jeffries posit is important. I'm not claiming JJ are wrong, just wondering how using a more standard photometric transformation would affect the resulting CMDs.

WAIT: The Irwin et al. (2007) data file suggests the I band photometry is quoted in terms of Cousins I, not Johnson... unlike what is stated in their paper.


In [9]:
tmp_data = np.genfromtxt('data/irwin2007.phot')  # re-load Irwin et al. (2007) data into new array

Now, applying transformation from Bessell (1979), which states that


In [10]:
old_vmi = tmp_data[:, 7] - tmp_data[:, 8]
new_vmi = old_vmi*0.835 - 0.130

In [14]:
fig, ax = plt.subplots(1, 1, figsize=(6., 8.))

ax.grid(True)
ax.tick_params(which='major', axis='both', length=15., labelsize=16.)
ax.set_xlim(2.0, 3.0)
ax.set_ylim(22., 16.)
ax.set_xlabel('$(V - I_C)$', fontsize=20.)
ax.set_ylabel('$M_V$', fontsize=20.)

ax.plot(jeffr01[:, 5], jeffr01[:, 3], 'o', markersize=4.0, c='#555555', alpha=0.2)
ax.plot(old_vmi, tmp_data[:, 7], 'o', c='#b22222', alpha=0.6)


Out[14]:
[<matplotlib.lines.Line2D at 0x108eb94d0>]

In [ ]: