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1993) requires a shift of the X-rav image: 07227 to the west and 17000 to the north.
1998) requires a shift of the X-ray image: 27 to the west and 00 to the north.
Making this shift leads to the finding of several other associations between oplical/near-IR. objects aud N-ray. sources (position coincidences within the 26
Making this shift leads to the finding of several other associations between optical/near-IR objects and X-ray sources (position coincidences within the $\sigma$
Out of the circa 350 exoplanets found to date. the 50 that transit their host stars allow several follow-up studies. based either on the occultation of part of the stellar disk by the planet (transits) or on the disappearance of the planet behind the star (secondary eclipses).
Out of the circa 350 exoplanets found to date, the 50 that transit their host stars allow several follow-up studies, based either on the occultation of part of the stellar disk by the planet (transits) or on the disappearance of the planet behind the star (secondary eclipses).
Observations of the secondary eclipses of several exoplanets have enabled measurements of their emitted flux at different wavelengths. providing clues to their cο”tmospheres (Charbonneauetal.2005;Deming 2005)).
Observations of the secondary eclipses of several exoplanets have enabled measurements of their emitted flux at different wavelengths, providing clues to their atmospheres \citealt{char05,dem05}) ).
Temperature inversions at stratospheric levels have been found on several occasions among the hottest known transiting Jupiters (Burrowsetal.2007:Knutson2008. 2009)). and several detections of the modulation of the planetary flux with "Sbital phase have been claimed by Knutsonetal.(2007) and eenellenetal.(2009).
Temperature inversions at stratospheric levels have been found on several occasions among the hottest known transiting Jupiters \citealt{burr07,knu08,knu09}) ), and several detections of the modulation of the planetary flux with orbital phase have been claimed by \cite{knu07} and \cite{sne09}.
The transiting planet CoRoT-2b (Alonsoetal..2008) was discovered during the first ~150-d pointing of the CoRoT mission (Baglinetal..2006).
The transiting planet CoRoT-2b \citep{alo08a} was discovered during the first $\sim$ 150-d pointing of the CoRoT mission \citep{baglin06}.
. The spectral type of the star (GOV) and the period of the planet dd) suggest that it belongs to the pM class of exoplanets as defined by Fortneyetal. (2008).. for which the strong incident flux is thought to cause stratospheric thermal inversions,
The spectral type of the star (G0V) and the period of the planet d) suggest that it belongs to the $pM$ class of exoplanets as defined by \cite{fort}, for which the strong incident flux is thought to cause stratospheric thermal inversions.
One of the intriguing characteristics of the hot Jupiters is their variety 1n planetary radius.
One of the intriguing characteristics of the hot Jupiters is their variety in planetary radius.
While for several planets the measured radius agrees with theoretical models of planetary formation and evolution. some of them appear larger than expected.
While for several planets the measured radius agrees with theoretical models of planetary formation and evolution, some of them appear larger than expected.
A range of scenarios have been suggested to account for the phenomenon. but no clear picture has been delineated to date.
A range of scenarios have been suggested to account for the phenomenon, but no clear picture has been delineated to date.
CoRoT-2b not only belongs to this class of "bloated" planets. but it is one with the most difficult radius as to explain. because of its high mass ofMj.
CoRoT-2b not only belongs to this class of “bloated" planets, but it is one with the most difficult radius as to explain, because of its high mass of.
.. The host star of CoRoT-2b exhibits several signs of youth (Bouchyetal..2008).. namely the detection of the Li 6708 aabsorption line. an inversion of the cores of the H and K lines. and a faster-than-expected rotation period of 4.5 d (Lanzaetal..2009).
The host star of CoRoT-2b exhibits several signs of youth \citep{bou08}, namely the detection of the Li 6708 absorption line, an inversion of the cores of the $H$ and $K$ lines, and a faster-than-expected rotation period of 4.5 d \citep{lanza09}.
. While these "patterns" are traditionally attributed to stellar youth. it 1s also possible that the stellar evolution has been affected by tidal interactions with the close-in massive planet.
While these “patterns" are traditionally attributed to stellar youth, it is also possible that the stellar evolution has been affected by tidal interactions with the close-in massive planet.
Recently. Jacksonetal.(2009) and Pont(2009) have suggested some observational evidence for strong tidal etfects on exoplanets' host stars.
Recently, \cite{jack09} and \cite{pont09} have suggested some observational evidence for strong tidal effects on exoplanets' host stars.
The activity of the star leaves footprints in the photometric light curve of CoRoT-2 that can be used to infer characteristics of the distribution and lifetimes of the spots on the stellar surface.
The activity of the star leaves footprints in the photometric light curve of CoRoT-2 that can be used to infer characteristics of the distribution and lifetimes of the spots on the stellar surface.
By modeling the flux of the star in the parts of the light curve without transits. Lanzaetal.(2009) observed a cyclic oscillation of the total spotted area of the star with a period of 28.9:4.3 days.
By modeling the flux of the star in the parts of the light curve without transits, \cite{lanza09} observed a cyclic oscillation of the total spotted area of the star with a period of $\pm$ 4.3 days.
In a different study. Valioetal.(2009) looked at the effects of the occultation of spots in the planet's path along the stellar surface.
In a different study, \cite{valio} looked at the effects of the occultation of spots in the planet's path along the stellar surface.
In this paper we describe detection of the secondary eclipse in the white light curve of the CoRoT public data.
In this paper we describe detection of the secondary eclipse in the white light curve of the CoRoT public data.
The technique 1s similar to the one used to detect the secondary eclipse of CoRoT-Ib (Alonsoetal.2009b).
The technique is similar to the one used to detect the secondary eclipse of CoRoT-1b \citep{alo09b}.
A tentative detection of a 5.5x107? eclipse. based on the same data. has been claimed by Alonsoetal.(2009a).
A tentative detection of a $\times$ $^{-5}$ eclipse, based on the same data, has been claimed by \cite{alo08b}.
. Here we refine the analysis by carrying out a more careful filtering of the stellar variability. estimate the significance of the detection. and discuss the results.
Here we refine the analysis by carrying out a more careful filtering of the stellar variability, estimate the significance of the detection, and discuss the results.
CoRoT-2b was observed during the first pointing of the satellite. which lasted 142-days.
CoRoT-2b was observed during the first pointing of the satellite, which lasted 142-days.
We used the data corrected to the level (the processing steps are described in Auvergneetal. 2009). which contains 369695 flux measurements. with a time sampling of 512-s from the first 5.2 days of data. after which it was changed to 32-s. The standard deviation of the normalized data after filtering the low frequencies as described below is 0.0014 (1n units of normalized flux) for the 32-s sampled data. while 1t is 0.00056 for the 512 s data.
We used the data corrected to the level (the processing steps are described in \citealt{auv09}) ), which contains 369695 flux measurements, with a time sampling of 512-s from the first 5.2 days of data, after which it was changed to 32-s. The standard deviation of the normalized data after filtering the low frequencies as described below is 0.0014 (in units of normalized flux) for the 32-s sampled data, while it is 0.00056 for the 512 s data.
For comparison. the photon noise level in the 32-s datais of 0.0011.
For comparison, the photon noise level in the 32-s datais of 0.0011,
The ROSAT data form a long series of uniform observations. suitable for temporal analvsis.
The ROSAT data form a long series of uniform observations, suitable for temporal analysis.
Instead. the wide beam of ASC'A and BeppoSAX data includes much galaxian enission. and we do not include them in the following analvsis. except for the long-term light-curve.
Instead, the wide beam of ASCA and BeppoSAX data includes much galaxian emission, and we do not include them in the following analysis, except for the long-term light-curve.
In. Figure 1 we show the 1991-1999 long term Leht curve of the nucleus of AISI in the 0.5-2.4 keV band.
In Figure \ref{flux} we show the 1991-1999 long term light curve of the nucleus of M81 in the 0.5-2.4 keV band.
The PSPC fluxes were calculated assuming a power-law wilh ID=179 plus a thermal component with 42ο0.5 keV. obtained as final result. of the speclval analvsis (see Section 4)).
The PSPC fluxes were calculated assuming a power-law with $\Gamma=1.79$ plus a thermal component with $kT\sim 0.5$ keV, obtained as final result of the spectral analysis (see Section \ref{spec}) ).
The same model was used to calculate the f[Iuxes from the ROSAT/IIRI count rates. through thetool!.
The same model was used to calculate the fluxes from the ROSAT/HRI count rates, through the.
. ASCA/SIS fIuxes were evaluated using a power-law model. since the soft thermal component is negligible in (he ASCA spectral band: the BeppoSAX flix was extrapolated from the value reported in for the 0.1-2.0 keV band using their best-fit model.
ASCA/SIS fluxes were evaluated using a power-law model, since the soft thermal component is negligible in the ASCA spectral band; the BeppoSAX flux was extrapolated from the value reported in \citet{pelle} for the 0.1-2.0 keV band using their best-fit model.
We note that the light curve in Figure 1 has been derived using data from four different detectors. and therefore one max expect some cross-calibration problems.
We note that the light curve in Figure \ref{flux} has been derived using data from four different detectors, and therefore one may expect some cross-calibration problems.
In our case this is not a problem. since data taken with cifferent instrumentis very close in time give consistent results.
In our case this is not a problem, since data taken with different instruments very close in time give consistent results.
This happens in most WRI/ASCA pairs of data (see. for example. the groups of observations at 5.00x10/d. 5.02x10d. 5.04x10d): see also the group of observation at 5.09x10/d which consists of IIRL ASCA and BeppoSAX points.
This happens in most HRI/ASCA pairs of data (see, for example, the groups of observations at $5.00\times10^4 d$, $5.02\times10^4 d$ , $5.04\times10^4 d$ ); see also the group of observation at $5.09\times10^4 d$ which consists of HRI, ASCA and BeppoSAX points.
We observe a [nctor of 2-4 flux. dillerence between the two high count-rate PSPC observations IP and 3P and all the other PSPC pointings (all of which vielcl a simülar. lower. count rates).
We observe a factor of 2-4 flux difference between the two high count-rate PSPC observations 1P and 3P and all the other PSPC pointings (all of which yield a similar, lower, count rates).
We can confidently exclude an unlikely variability in the instrumental calibration. because no [Iux enhancement is seen in anv of the sources in the field (see. e.g.. LaParolaetal.2001 and other fainter sources (Immler&Wang2001).
We can confidently exclude an unlikely variability in the instrumental calibration, because no flux enhancement is seen in any of the sources in the field (see, e.g., X-9 \citealp{lapa} and other fainter sources \citep{imm}.
. We can also rule out transient sources near (he nucleus. because there is no significant spectral variation between 1P and 3P and the immediately following pointings (Section 4)).
We can also rule out transient sources near the nucleus, because there is no significant spectral variation between 1P and 3P and the immediately following pointings (Section \ref{spec}) ).
The above considerations suggest that this variation should be ascribed entirely to the nuclear source.
The above considerations suggest that this variation should be ascribed entirely to the nuclear source.
To search for short term variations. we examined the light-eurves from individual ROSAT observations.
To search for short term variations, we examined the light-curves from individual ROSAT observations.
Figure 2. presents these light-curves in order of their observation.
Figure \ref{ltc} presents these light-curves in order of their observation.
Each bin corresponds to one GTI (Good Time Interval ?)) and the timeis given in days starting from the ROSAT launch (June 1990).
Each bin corresponds to one GTI (Good Time Interval ) and the timeis given in days starting from the ROSAT launch (June 1990).
2010).
.
. In general. they have estimated stellar masses of 10°7 37. and fainter UV luminosities than lower redshif Lyman break galaxies (Finkelsteinetal.2010).. Le. their properties resemble those of the luminous DCCis.
In general, they have estimated stellar masses of $10^{8-9}$ $\msun$ and fainter UV luminosities than lower redshift Lyman break galaxies \citep{2010ApJ...719.1250F}, i.e. their properties resemble those of the luminous BCGs.
The studies of BCGs can. therefore. give importan insights in understanding how star formation proceeds in dwarf starburst galaxies and possibly in. high-redshift| systems. with spatial ane spectral resolution impossible to achieve for the latter with the current facilities.
The studies of BCGs can, therefore, give important insights in understanding how star formation proceeds in dwarf starburst galaxies and possibly in high-redshift systems, with spatial and spectral resolution impossible to achieve for the latter with the current facilities.
Llieh-resolution imaging data of BCGs revealed that the starburs regions in these galaxies are formed. by massive and voung star cluster. complexes (c.g.Ostlinetal.2003:Adamoetal.2010a. 2011a.b).
High-resolution imaging data of BCGs revealed that the starburst regions in these galaxies are formed by massive and young star cluster complexes \citep[e.g.][]{2003A&A...408..887O, A2010, A2010c, A2011a}.
. The peak age of the star cluster distributions and the estimated. ages of the starbursts in these svstenis are in σους agreement.
The peak age of the star cluster distributions and the estimated ages of the starbursts in these systems are in good agreement.
The host morphologies suggest that the galaxies have recently. undergone a merger or interaction event. which has likely refurbished the galaxy with metal-poor gas. and triggered. a vigorous starburst episode.
The host morphologies suggest that the galaxies have recently undergone a merger or interaction event, which has likely refurbished the galaxy with metal-poor gas, and triggered a vigorous starburst episode.
Star clusters are à natural outcome of the star formation process (see Lada&2003. for a review).
Star clusters are a natural outcome of the star formation process (see \citealp{2003ARA&A..41...57L} for a review).
However. for very voung stellar svstems (e.g. a few Myr or less). it is not trivial to make a clear delinition of a cluster (Bressertetal. 2010)...
However, for very young stellar systems (e.g. a few Myr or less), it is not trivial to make a clear definition of a cluster \citep{2010MNRAS.409L..54B}.
Usually. it is assumed that stars form in a clustered. fashion ancl that. alter roughly LO Myr. 90. of clusters are cestrovecd due to gas expulsion.
Usually, it is assumed that stars form in a clustered fashion and that, after roughly 10 Myr, 90 of clusters are destroyed due to gas expulsion.
Bressertetal.(2010). suggest that all the stars form in a continuos hierarchy. even the dense regions and estimate that. in the solar neighbourhood. only ~26% of voung stellar objects (new born stars) are located in denser regions. ie. embedded star clusters.
\citet{2010MNRAS.409L..54B} suggest that all the stars form in a continuos hierarchy, even the dense regions and estimate that, in the solar neighbourhood, only $\sim 26 \%$ of young stellar objects (new born stars) are located in denser regions, i.e. embedded star clusters.
Phe remaining stars form in associations and agelomoerates following a hierarchical continuum clistribution with clusters at the bottom of the process.
The remaining stars form in associations and agglomerates following a hierarchical continuum distribution with clusters at the bottom of the process.
PortegiesZwartectal.(2010) and Gieles&PortegiesZwart(2010) defined an empirical relation to separate clusters from loose associations.
\citet{2010ARA&A..48..431P} and \citet{2010MNRAS.tmpL.168G} defined an empirical relation to separate clusters from loose associations.
For the latter the crossing time is much larger than the age of the stars. Le. they are dynamically unbound systems.
For the latter the crossing time is much larger than the age of the stars, i.e. they are dynamically unbound systems.
They observed that the division. between bound and unbound. systems. becomes more clear once the expulsion phase is over ( 10-20 Myr).
They observed that the division between bound and unbound systems becomes more clear once the gas-expulsion phase is over $\sim$ 10-20 Myr).
Cluster formation at high-redshift is almost. unknown.
Cluster formation at high-redshift is almost unknown.
In the local Universe. we observe the evolved counterparts. i.c.. the globular clusters (GC's).
In the local Universe, we observe the evolved counterparts, i.e., the globular clusters (GCs).
However. there is no direct evidence that the voung star clusters we observe locally will eventually evolve into GC's (deGrijs&Parmenticr2007)..
However, there is no direct evidence that the young star clusters we observe locally will eventually evolve into GCs \citep{2007ChJAA...7..155D}.
If one looks at the number of GCs per mass (Luminosity) ins (Lo. AN(AL/dAl= CAL") thedistribution can be itteck by two power-Iaws with a slope of ~2.0 at the massive (luminous) ends. a break corresponding to the AL.~2.1O°AL.. anel a llattening (go0.2 which variates rom system: to system) at lower masses.
If one looks at the number of GCs per mass (luminosity) bins (i.e., $dN(M)/dM=CM^{\eta}$ ) thedistribution can be fitted by two power-laws with a slope of $\sim-2.0$ at the massive (luminous) ends, a break corresponding to the $M_c\sim2\times10^5 \msun$, and a flattening $\eta\sim-0.2$ which variates from system to system) at lower masses.
Several possible scenarios are addressed: by theoretical studies to explain he origin of the GC mass (luminosity) function: dynamical evolution. i.e. due to preferential disruption of the low mass systems: or a primordial origin. i.c. the GC mass function aas been established. at the time when the GC's [ormed (deCirijs&Parmenticr2007)...
Several possible scenarios are addressed by theoretical studies to explain the origin of the GC mass (luminosity) function: dynamical evolution, i.e. due to preferential disruption of the low mass systems; or a primordial origin, i.e. the GC mass function has been established at the time when the GCs formed \citep{2007ChJAA...7..155D}.
Cosmological simulations seem to suggest that GCs may have formed in dark matter ialos (e.g.WKravtsov&Cinedin2005:Mashchenko 2005).
Cosmological simulations seem to suggest that GCs may have formed in dark matter halos \citep[e.g.][]{2005ApJ...623..650K, 2005ApJ...619..258M}.
. I£ this is the case. there is no connection between he YSC's forming at the present time and the ancient. GCs.
If this is the case, there is no connection between the YSCs forming at the present time and the ancient GCs.
llowever. some recent works suggest that cluster formation in dwarl galaxies may be the Κον to explain observed: properties of the ancient GCs (blue. versus red. ie. metal poor versus metal rich).
However, some recent works suggest that cluster formation in dwarf galaxies may be the key to explain observed properties of the ancient GCs (blue versus red, i.e. metal poor versus metal rich).
Muratov&Gnedin(2010). recovered a bimocdal metallicity distribution as a product of cluster formation in different: phases of galaxy evolution.
\citet{2010ApJ...718.1266M} recovered a bimodal metallicity distribution as a product of cluster formation in different phases of galaxy evolution.
Cluster formation in dwarl galaxies produced the blue. metal-poor GCs.
Cluster formation in dwarf galaxies produced the blue, metal-poor GCs.
Dwarl systems were successively accreted to form. more massive systems.
Dwarf systems were successively accreted to form more massive systems.
During the merger ancl formation of these massive ealaxies the more metal-rich clusters were formed.
During the merger and formation of these massive galaxies the more metal-rich clusters were formed.
Accretion of dwarf galaxies together with their GC systems is also one of the proposed. scenarios by Chies-Santosetal.(2011). to explain why the vounger GCs in SO type of galaxies appear blue instead of the expected metal-rich populations (Broclic&Stracler2006)..
Accretion of dwarf galaxies together with their GC systems is also one of the proposed scenarios by \citet{2011A&A...525A..20C} to explain why the younger GCs in S0 type of galaxies appear blue instead of the expected metal-rich populations \citep{2006ARA&A..44..193B}.
In the present work. we will investigate how cluster formation has proceeded in BCCs.
In the present work, we will investigate how cluster formation has proceeded in BCGs.
We will test. whether BGs follow the cluster-host relations available in. the literature and constrained using local star-forming ealaxies. like spirals ancl cdwarls.
We will test whether BCGs follow the cluster-host relations available in the literature and constrained using local star-forming galaxies, like spirals and dwarfs.
“hese results will be used. to constrain the environmental properties. of BCCs and whether star formation operates on similar modes even uncler extreme conclitions.
These results will be used to constrain the environmental properties of BCGs and whether star formation operates on similar modes even under extreme conditions.
The paper is organized. as follow: In Section. 2. we present the 5 BCG targets used in this work.
The paper is organized as follow: In Section 2, we present the 5 BCG targets used in this work.
In Section 3. we first cliscuss the uncertainties which allect the analysis.
In Section 3, we first discuss the uncertainties which affect the analysis.
In the second. part of this section. we show the three cluster-host relations including the BCC sample.
In the second part of this section, we show the three cluster-host relations including the BCG sample.
X. discussion of the results is) presented. in Section 4.
A discussion of the results is presented in Section 4.
Here. we also discuss possible similarities between DCCGs and high redshift ealaxies.
Here, we also discuss possible similarities between BCGs and high redshift galaxies.
Conclusions are summarized in the last section.
Conclusions are summarized in the last section.
1n this section we shortly. introduce the DCGs included in the analvsis.
In this section we shortly introduce the BCGs included in the analysis.
Some of these BOCs have been studied in a series of 3 papers: Haro 11 analysis is presented. in etal. (20102): ESO 185-1613 (ESO 185) in Adamoοἱal. (20112):: and 9930 in Aclamoetal.(2011b).
Some of these BCGs have been studied in a series of 3 papers: Haro 11 analysis is presented in \citet[][]{A2010}; ESO 185-IG13 (ESO 185) in \citet[][]{A2010c}; ; and 930 in \citet[][]{A2011a}.
. We refer to those papers for details on the analysis of the data used in this work.
We refer to those papers for details on the analysis of the data used in this work.
The analysis of the star cluster population in ESQ 338-104 (ESO 338) has been presented in Ostlinetal.(2003)..
The analysis of the star cluster population in ESO 338-IG04 (ESO 338) has been presented in \citet{2003A&A...408..887O}.
The masses have been obtained [rom mocdels that assume a Salpeter initial mass function (LAL.Salpeter1955)..
The masses have been obtained from models that assume a Salpeter initial mass function \citep[IMF,][]{1955ApJ...121..161S}.
We show. in Figure L.. the cluster formation history during the last 40 Myr of galaxy. evolution.
We show, in Figure \ref{CMF_eso338}, the cluster formation history during the last 40 Myr of galaxy evolution.
Using the age anc mass estimates from Ostlinetal.(2003).. we assumed that the analysis is complete in detecting clusters more massive than 5.lo? M. formed during the last 40 Myr.
Using the age and mass estimates from \citet{2003A&A...408..887O}, we assumed that the analysis is complete in detecting clusters more massive than $5\times10^3$ $\msun$ formed during the last 40 Myr.
A power law cluster mass function with index —2.0 has then been used to extrapolate the total fraction of mass in clusters including objects with masses between 107 M&ο
A power law cluster mass function with index $-2.0$ has then been used to extrapolate the total fraction of mass in clusters including objects with masses between $10^2\leq$ $\leq5\times10^3 \msun$ .
Following Weidnerctal.(2004)... we assume for simplicity that a cluster. population forms every 10 Myr anclestimate. the cluster formation rate (CE) in the galaxy.
Following \citet[][]{2004MNRAS.350.1503W}, we assume for simplicity that a cluster population forms every 10 Myr andestimate the cluster formation rate (CFR) in the galaxy.
In agreement with Ostlinetal. (2003)... we observe a cluster formation enhancement between 20 and 30 Myr ago.
In agreement with \citet{2003A&A...408..887O}, , we observe a cluster formation enhancement between 20 and 30 Myr ago.
However. the
However, the
Supra-arcade downflows (SADs) are downward-moving features observed in the hot. density region above posteruption flare arcades.
Supra-arcade downflows (SADs) are downward-moving features observed in the hot, low-density region above posteruption flare arcades.
Initially detected with the Soft X-ray
Initially detected with the Soft X-ray
using parallaxes. and their errors are a reflection of errors propagating through this calculation. whilst for the remaining stars isochrones were used.
using parallaxes, and their errors are a reflection of errors propagating through this calculation, whilst for the remaining stars isochrones were used.
The isochronal gravities are sensitive to age. with a | Gyr difference leading to a change of ~ 0.03 dex for main sequence (MS) stars and ~ 0.06 dex for sub-giant (SGB) stars.
The isochronal gravities are sensitive to age, with a 1 Gyr difference leading to a change of $\sim$ 0.03 dex for main sequence (MS) stars and $\sim$ 0.06 dex for sub-giant (SGB) stars.
This equates to a change in 7| of 12 K and 24 K respectively.
This equates to a change in $T_{\rm \chi}$ of 12 K and 24 K respectively.
These errors are based on LTE sensitivities. as are other errors quoted below.
These errors are based on LTE sensitivities, as are other errors quoted below.
There is also a dependence on the initial temperature. a photometric temperature from Ryan et al (1999), used to determine the isochronal gravity.
There is also a dependence on the initial temperature, a photometric temperature from Ryan et al (1999), used to determine the isochronal gravity.
A +100 K difference leads to +0.06 dex and —0.06 dex for MS and SGB stars respectively.
A +100 K difference leads to +0.06 dex and –0.06 dex for MS and SGB stars respectively.
This equates to + 24 K in 7, which shows. importantly. that 7, is only weakly dependent on the initial photometric temperature.
This equates to $\pm$ 24 K in $T_{\rm \chi}$ which shows, importantly, that $T_{\rm \chi}$ is only weakly dependent on the initial photometric temperature.
Contributions to 7, is also sensitive to microturbulence. for which an error of ~ 0.1 km s! equates to an error of = 60 K. In the nulling procedure any trends between [Fe/H] and y are removed.
Contributions to $T_{\rm \chi}$ is also sensitive to microturbulence, for which an error of $\sim$ 0.1 km $\rm s^{-1}$ equates to an error of $\approx$ 60 K. In the nulling procedure any trends between [Fe/H] and $\chi$ are removed.
Due to the range in line to line Fe abundances for a particular star. there is a statistical error in the trend which is of order c = 0.011 dex per eV. which equates to = 40 K - 100 K depending on the star under study.
Due to the range in line to line Fe abundances for a particular star, there is a statistical error in the trend which is of order $\sigma$ = 0.011 dex per eV, which equates to $\approx$ 40 K - 100 K depending on the star under study.
This error also contains the random line-to-Dine errors due to equivalent width. gf. and damping values.
This error also contains the random line-to-line errors due to equivalent width, $gf$, and damping values.
The final 7; error in Table 5 is thena conflation of this statistical error and the errors from Aage = | Gyr. Ac = 0.1 kms'. A[Fe/H] = 0.05 and AT, = 100 K. These new Το; values and equivalent widths from ? werethen used to calculate new by interpolating within a grid of equivalent width versus abundance for different Των.
The final $T_{\rm eff}$ error in Table \ref{Table2} is thena conflation of this statistical error and the errors from $\Delta$ age = 1 Gyr, $\Delta\xi$ = 0.1 $\rm s^{-1}$, $\Delta$ [Fe/H] = 0.05 and $\Delta T_{\rm phot}$ = 100 K. These new $T_{\rm eff}$ values and equivalent widths from \citet{Ryanetal1999} werethen used to calculate new by interpolating within a grid of equivalent width versus abundance for different $T_{\rm eff}$ .