11institutetext: School of Physics and Astronomy, University of Leeds, Leeds
LS2 9JT, UK. 22institutetext: Ingeniería de Sistemas para la Defensa de España
(Isdefe), XMM/Newton Science Operations Centre, ESA-ESAC Campus, PO Box 78,
28691 Villanueva de la Cañada, Madrid, Spain. 33institutetext: Quasar Science
Resources for ESA-ESAC, ESAC Science Data Center, PO Box 78, 28691 Villanueva
de la Cañada, Madrid, Spain. 44institutetext: Centro de Astrobiología (CSIC-
INTA), Departamento de Astrofísica, ESA-ESAC Campus, PO Box 78, 28691
Villanueva de la Cañada, Madrid, Spain.

#  Gaia DR2 study of Herbig Ae/Be stars

M. Vioque 1122<EMAIL_ADDRESS>R. D. Oudmaijer 11 D. Baines 33 I.
Mendigutía 44 R. Pérez-Martínez 22

(Accepted for publication in Astronomy & Astrophysics.)

###### Abstract

Aims. We use Gaia Data Release 2 (DR2) to place 252 Herbig Ae/Be stars in the
HR diagram and investigate their characteristics and properties.

Methods. For all known Herbig Ae/Be stars with parallaxes in Gaia DR2, we
collected their atmospheric parameters and photometric and extinction values
from the literature. To these data we added near- and mid-infrared photometry,
collected H$\alpha$ emission line properties such as equivalent widths and
line profiles, and their binarity status. In addition, we developed a
photometric variability indicator from Gaia’s DR2 information.

Results. We provide masses, ages, luminosities, distances, photometric
variabilities and infrared excesses homogeneously derived for the most
complete sample of Herbig Ae/Be stars to date. We find that high mass stars
have a much smaller infrared excess and have much lower optical variabilities
compared to lower mass stars, with the break at around 7M⊙. H$\alpha$ emission
is generally correlated with infrared excess, with the correlation being
stronger for infrared emission at wavelengths tracing the hot dust closest to
the star. The variability indicator as developed by us shows that $\sim$25% of
all Herbig Ae/Be stars are strongly variable. We observe that the strongly
variable objects display doubly peaked H$\alpha$ line profiles, indicating an
edge-on disk.

Conclusions.  The fraction of strongly variable Herbig Ae stars is close to
that found for A-type UX Ori stars. It had been suggested that this
variability is in most cases due to asymmetric dusty disk structures seen
edge-on. The observation here is in strong support of this hypothesis.
Finally, the difference in dust properties occurs at 7M⊙, while various
properties traced at UV/optical wavelengths differ at a lower mass, 3M⊙. The
latter has been linked to different accretion mechanisms at work whereas the
differing infrared properties and photometric variabilities are related to
different or differently acting (dust-)disk dispersal mechanisms.

###### Key Words.:

stars: Herbig Ae/Be – stars: Hertzsprung-Russell diagram – stars: formation –
stars: pre-main sequence – stars: emission-line – infrared: stars

##  1 Introduction

Herbig Ae/Be stars (HAeBes) are Pre-Main Sequence stars (PMS) of intermediate
mass, spanning the range between low mass T-Tauri stars and the embedded
Massive Young Stellar Objects (MYSOs). They are optically bright so they are
much easier to observe and to study than MYSOs and it is expected that within
the mass range of HAeBes a change in accretion mechanism from the magnetically
controlled accretion acting for T-Tauri stars (see Bouvier et al., 2007) to
an, as yet, unknown mechanism for high mass stars occurs. Indeed, there is
evidence that the magnetically driven accretion model is valid for Herbig Ae
stars but not for several Herbig Be stars (Fairlamb et al., 2015; Ababakr et
al., 2017; Oudmaijer, 2017; Grady et al., 2010; Schöller et al., 2016).
Moreover, there are multiple evidences that Herbig Ae and T-Tauri stars behave
more similarly than Herbig Be stars, and Herbig Ae and Herbig Be stars have
different observational properties. Examples of this are the different outer
gas dispersal rates (higher for Herbig Be stars, Fuente et al., 1998), the
higher incidence of clustering scenarios for Herbig Be stars (Testi et al.,
1999), and the evidences of Herbig Be stars hosting denser and larger inner
gaseous disks (Ilee et al., 2014; Monnier et al., 2005) that may suggest a
different accretion scenario with the disk reaching directly into the star
(Kraus, 2015). Other spectro-photometric (Mendigutía et al., 2011b; Cauley &
Johns-Krull, 2015 and Patel et al., 2017) and spectro-polarimetric studies
(Vink et al., 2002) also point in the direction that the accretion physics
change within the Herbig Ae/Be stars mass range. In addition, Herbig Be stars
are more likely to be found in binaries than Herbig Ae stars (Baines et al.,
2006).

An important indicator of their PMS nature, together with emission lines, is
the infrared (IR) excess that also traces the Herbig Ae/Be forming
environment. The IR excess profile have been classified into two groups
differentiated by a flat or rising shape of the continuum (Meeus et al.,
2001). This difference has a geometric origin depending on the presence of
flaring outer disks and puffed-up inner disks (Dullemond & Dominik, 2004a,
2004b, 2005), and the presence of gaps in the disk (Maaskant et al., 2013;
Honda et al., 2015). The IR excess of HAeBes is expected to be characteristic
and different from the IR excess of other similar objects like for example,
ordinary Be stars (Finkenzeller & Mundt, 1984).

Herbig Ae/Be stars are known to present irregular photometric variations, with
a typical timescale from days to weeks (Eiroa et al., 2002; Oudmaijer et al.,
2001) and of the order of one magnitude in the optical. This variability is
typically understood as due to variable extinction, due to for example
rotating circumstellar disks, or as an effect of rotation on cold photospheric
spots and also pulsation due to the source crossing the instability strip in
the HR diagram (Marconi & Palla, 1998). An extreme case of large non-periodic
photometric and polarimetric variations is observed in UX Ori type stars
(UXORs) with amplitudes up to $2-3$ mag. Many of them are catalogued as HAeBes
and their extreme variability is explained by eclipsing dust clouds in nearly
edge-on sources and the scattering radiation in the circumstellar environment
(see Grinin, 2000 and references therein; Natta et al., 1997 and Natta &
Whitney, 2000).

Infrared photometric variability, related to disk structure variations, is not
always correlated with the optical variability (Eiroa et al., 2002) which
implies that different mechanisms regarding both the disk structure and
accretion underlie the final observed variability. Spectroscopic variability
is also present in Herbig Ae/Be stars (Mendigutía et al., 2011a).

With the advent of the second data release of Gaia (DR2, Gaia Collaboration et
al., 2016, Gaia Collaboration et al., 2018b), providing parallaxes to over 1.3
billion objects (Lindegren et al., 2018), including the majority of known
Herbig Ae/Be stars, the time is right for a new study on the properties of the
class. Gaia DR2 contains a five dimensional astrometric solution ($\alpha$,
$\delta$, $\mu_{\alpha}$, $\mu_{\delta}$ and parallax ($\varpi$)) up to
$G\lesssim 21$ (white G band, described in Evans et al., 2018). Almost all of
the known Herbig Ae/Be stars have parallaxes in Gaia DR2, which allowed
luminosities to be derived and 252 HAeBes to be placed in the HR diagram, a
tenfold increase on earlier studies using Hipparcos data alone.

The paper is organized as follows: In Sect. 2, we describe the data
acquisition of not only the parallaxes, but also optical and infrared
photometry, effective temperatures, extinction values, H$\alpha$ emission line
information and binarity. In Sect. 3 we derive the stellar luminosities and
place the objects in an Hertzsprung-Russell (HR) diagram, while we also
present a method to derive a statistical assessment of the objects’
variability in Gaia’s database. In addition, we homogeneously derive masses
and ages for all the sources, together with near- and mid-infrared excesses.
In Sect. 4 we carry out an analysis of the data and present various
correlations and interdependencies, which we discuss in the context of
intermediate mass star formation in Sect. 5. We conclude in section Sect. 6.

##  2 Data acquisition

###  2.1 Construction of the sample

We have gathered the majority of Herbig Ae/Be stars known and proposed to date
from different works (272, see Chen et al., 2016 for a compilation of most of
them). Chen et al. (2016) based their sample mostly on the work of Zhang et
al. (2006) which in turn is based on the work of The et al. (1994) and Vieira
et al. (2003). In addition, we included a few HAeBes from Alecian et al.
(2013); Baines et al. (2006); Carmona et al., 2010; Fairlamb et al., 2015;
Hernández et al. (2005); Manoj et al. (2006) and Sartori et al. (2010) that
are not present in the aforementioned papers.

Although Herbig Ae/Be stars have long been considered, by definition, of type
A or B, there should be some flexibility in this constraint as the physical
boundary between Herbig Ae stars and intermediate mass T-Tauris is fairly
unstudied. This is because spectral types of T-Tauri stars are typically K-M
with some G-type objects while Herbig Ae/Be stars are, quite unsurprisingly,
limited to A and B spectral type. Hence, pre-Main Sequence stars of
intermediate spectral types have often been largely understudied. We therefore
keep objects with F-type classification in Chen et al. (2016) in the sample.
Similarly, no upper limit in mass was imposed, leaving the separation between
Massive Young Stellar Objects (MYSOs) and HAeBes to the optical brightness of
the sources111The MYSOs are typically infrared-bright and optically faint
(Lumsden et al., 2013). However, a number of optically visible objects are
known to have passed all selection criteria such as the early type objects PDS
27 and PDS 37 that are also classified as Herbig Be stars (Ababakr et al.,
2015)..

Then, we crossmatched the sources with Gaia DR2. Detections were considered to
be matched with the catalogue when their coordinates agreed to within 0.5
arcsecond. If more than one match was found we took the closest one. If no
match was found within 0.5 arcsecond, successive crossmatches with larger
apertures were performed up to 2 arcsecond. In these latter cases an
individual inspection of the crossmatch was applied. Finally, a comparison
between the Johnson V band magnitudes and the Gaia filters was done for each
source in order to discard possible incorrect matches. This provides us with
parallaxes for 254 HAeBes.

As Lindegren et al. (2018) point out, not all Gaia DR2 parallaxes are of the
same quality, and some values - despite their sometimes very small error bars
- appear erroneous (e.g. Lindegren et al. 2018). We included the following
constraint in astrometric quality following the indications in Appendix C of
Lindegren et al. (2018) and what was applied in Gaia Collaboration et al.
(2018). This constraint will remove from the sample objects with spurious
parallaxes:

$u<1.2\times{\rm max}(1,e^{-0.2(G-19.5)})$ (1)

where $G$ is the Gaia G band and $u$ is the unit weight error, defined as the
square root of the ratio of the astrometric$\\_$chi2$\\_$al and
(astrometric$\\_$n$\\_$good$\\_$obs$\\_$al $-$ $5$) columns (Lindegren et al.
2018, their Equation C.2). 228 of our sources satisfy this condition.

Some objects are found to be very close to this condition, PDS 144S, PV Cep
and V892 Tau, and as we will show later, they would appear significantly below
the Main Sequence in the HR-diagram. Given that the Lindegren condition is
presented as a guideline rather than a rule by the Gaia astrometry team, we
decided to treat these three objects as if they satisfy Eq. 1 as well.

We will refer to the set of astrometrically well behaved sources as the high
quality sample and to those that do not satisfy Eq. 1 as the low quality
sample. We will not be able to place 2 sources in the HR diagram because
lacking of appropriate parameters (Sect. 2.2). In addition, we will move 5
more sources to the low quality sample in Sect. 3.1 because of different
reasons. Summarizing, there are 218 objects ($228-3-2-5$) in the final high
quality sample and 34 in the low quality one. Information about the objects in
different samples is presented in separated tables at the end of the paper.
The high quality sample will be the one taken into account in further
considerations unless otherwise specified.

Distances are not obtained by straightforwardly inverting the parallax. The
conversion of one parameter to the other one is not strictly trivial because
of the non-linearity of the inverse function (see for example Bailer-Jones,
2015). In the case of Gaia DR2, Bailer-Jones et al. (2018) proposed distance
values using a weak distance prior that follows a galactic model. Their
distances begin to differ from the distances obtained through simple inversion
for sources with large errors, $\sigma_{\varpi}/\varpi\gtrsim 0.5$. Hence, in
our initial (high and low quality) sample only a small subset of 12 Herbig
Ae/Be stars will suffer substantially from this effect. Following the
indications in Luri et al. (2018) on how to treat the Gaia parallaxes we
decided to apply a simpler exponentially decreasing prior to estimate
distances. For completeness, we should note that the parallaxes provided by
Gaia DR2 have a regional, not gaussian systematic error as large as $0.1$mas
and a global zero point error of about $-0.029$mas that are not included in
the gaussian random errors provided in the Gaia archive (see Arenou et al.,
2018 and Lindegren et al., 2018). Hence, the uncertainty in the parallaxes is
slightly underestimated. The final errors in the high quality sample range
from $0.016$ to $0.37$mas.

Herbig Ae/Be stars have been historically confused with classical Be stars,
with which they share many characteristics (Rivinius et al., 2013; Klement et
al., 2017; Grundstrom & Gies, 2006). Indeed, the nature of some of the objects
in our sample is still under debate. An interesting example in this respect is
HD 76534, a B2Ve object that appears in listings of Be stars (eg. Oudmaijer &
Drew, 1997) and Herbig Be stars alike (Fairlamb et al., 2015). The latest
dedicated study puts the object in the Herbig Be category (Patel et al.,
2017). To assess the effect of ambiguous classifications in our study we will
also, next to the full sample, consider the subset of Herbig Ae/Be stars in
Table 1 of The et al. (1994). This catalogue contains all historically known,
and best studied, Herbig Ae/Be stars. 98/254 of our initial sources with
parallaxes are present in this table (their best candidates).

###  2.2 Atmospheric parameters, photometry and extinction values

Figure 1: 223 Herbig Ae/Be stars in the HR diagram satisfying Eq. 1
constraint. In most cases vertical error bars are dominated by parallax
uncertainties. Sources with a white dot have been classified as binaries. The
mass of each Pre-Main Sequence track (Bressan et al., 2012) is indicated on
the righthand side. An isochrone (Bressan et al., 2012; Marigo et al., 2017)
of $2.5$ Myr is also shown for reference as a dashed line.

Figure 2: Left: 223 high quality and 29 low quality Herbig Ae/Be stars in the
HR diagram after the cut in astrometric quality described in Eq. 1. Right: 218
Herbig Ae/Be stars in the final high quality sample after removing the 5
problematic objects described in Sect. 3.1. In red those objects present in
Table 1 of The et al. (1994). The mass of each Pre-Main Sequence track
(Bressan et al., 2012) is indicated on the righthand side. An isochrone
(Bressan et al., 2012; Marigo et al., 2017) of $2.5$ Myr is also shown for
reference as a dashed line.

We obtained atmospheric parameters and photometric and extinction values for
all the sources from the literature. These were mainly Alecian et al., 2013;
Carmona et al., 2010; Chen et al., 2016; Fairlamb et al., 2015; Hernández et
al., 2004; Hernández et al., 2005; Manoj et al., 2006; Montesinos et al.,
2009; Mendigutía et al., 2012; Sartori et al., 2010; Vieira et al., 2003 and
the APASS Data Release 9\. Whenever the effective temperature (Teff) was not
available it was derived from the spectral type with the effective temperature
calibration tables of Gray & Corbally (2009). A 1 subspectral type uncertainty
was assigned in all cases. When not listed in the literature, AV values were
derived from the observed photometry and using the intrinsic colours of Pecaut
& Mamajek (2013). An $R_{V}=3.1$ was used in all cases in which AV was derived
although other studies like Hernández et al. (2004) or Manoj et al. (2006)
have suggested that a larger value of for example $R_{V}=5$ could be more
appropriate for HAeBes where local extinction dominates the total extinction.
This is a topic for future investigations using Diffuse Interstellar Bands (as
done by for example Oudmaijer et al., 1997). The relevant data of each source
is presented in Table LABEL:table2 and Table LABEL:table2_2 for the high
quality and low quality samples respectively.

HAeBes usually show photometric variability. Thus, for objects with multi-
epoch photometry available, we selected the brightest set to determine the
extinction towards the objects and thus their intrinsic brightnesses. As we
will also show later, the variability is often caused by irregular extinction,
using those data with minimum extinction introduces the smallest errors in the
determination of the stellar parameters. For this reason, we only used
simultaneous photometry when deriving AV values. All the photometric values
were corrected for extinction using the reddening law of Cardelli et al.
(1989).

Two sources, V833 Ori and GSC 1829-0331, do not have enough simultaneous
photometry available to derive extinctions for them and hence they were
excluded for the sample. The total number of Herbig Ae/Be stars that can be
placed in the HR diagram and for which we can derive stellar luminosities,
masses, ages, IR excesses and variabilities in Sect. 3 is therefore reduced to
252 objects.

###  2.3 Infrared photometry

All the sources were crossmatched with the Two-Micron All Sky Survey (2MASS,
see Skrutskie et al., 2006) and with the Wide-Field Infrared Survey Explorer
‘AllWISE’ all-sky catalogue (hereafter WISE, see Cutri et al., 2013). Both
these surveys contain hundreds of millions of stars, guaranteeing a large
overlap with Gaia. We used a 3 arcsecond aperture for the crossmatch. The few
sources that did not lie within that 3 arcsecond threshold were studied
individually and, if present, their IR photometry was included. This provides
values and uncertainties for the J, H and Ks bands ($1.24$, $1.66$ and
$2.16\mu$m respectively) and for the W1, W2, W3 and W4 bands ($3.4$, $4.6$,
$12$, and $22\mu$m respectively) for most of the HAeBes. Note that for some
sources some of the bands may be missing or just be upper limits. We double-
checked all infrared matches with the dereddened optical photometry and found
no inconsistencies.

###  2.4 H$\alpha$ equivalent width and emission line profile

We collected all the H$\alpha$ equivalent widths (EW) we could find in the
literature for the Herbig Ae/Be stars. Not only the intensity of the line but
also the shape contains very useful information. Therefore, when possible,
information about the shape of the H$\alpha$ line was included. We have
classified the H$\alpha$ line profile as single-peaked (s), double-peaked (d)
and showing a P-Cygni profile (P), both regular or inverse. EW and line shape
information are presented in Table LABEL:table3 and Table LABEL:table3_2 for
the high quality and low quality samples respectively. Many Herbig Ae/Be stars
are quite variable in their H$\alpha$ emission and its EW may significantly
change at short timescales (e.g. Costigan et al., 2014). This is also the case
for the line shape, although spot checks on objects that have more than one
H$\alpha$ observation listed in the literature appear to indicate that there
are not many changes in line profile classification (see also for example
Aarnio et al., 2017), although changes between single-peaked and double-peaked
profiles in a given star are also observed (Mendigutía et al., 2011a). We do
note the additional complication that emission line shapes are often difficult
to unambiguously classify.

Regarding the H$\alpha$ EWs compiled, we note that our main references
(Fairlamb et al., 2015 and Mendigutía et al., 2011a) provide the non-
photospheric contribution of the EW, while most other authors state the
observed EW, which includes the photospheric contribution. This photospheric
absorption peaks for A0-A1 type objects, with EW values of $\sim+10\AA$ (See
e.g. Fig. 7 of Joner & Hintz, 2015) but is only $\sim+2\AA$ for B0 objects. We
used the Joner & Hintz (2015) results to correct those EWs that were not
corrected for absorption.

We have H$\alpha$ EWs for 218/252 of the HAeBes and line profiles for 197 of
these: 31% are single-peaked, 52% double-peaked and 17% P-Cygni (of which the
vast majority are of regular P-Cygni type). This is in agreement with
Finkenzeller & Mundt (1984) who found that out of 57 HAeBes, 25% were single-
peaked, 50% showed double-peaked H$\alpha$ profiles and 20% presented a
P-Cygni profile (both regular and inverse). The main references for the EW
values are Baines et al. (2006); Fairlamb et al. (2017); Hernández et al.
(2004); Mendigutía et al. (2011a) and Wheelwright et al. (2010). Main
references for the line profiles are van den Ancker et al. (1998); Baines et
al. (2006); Mendigutía et al. (2011a); Vieira et al. (2003) and Wheelwright et
al. (2010). The rest of the references can be found in Table LABEL:table3 and
Table LABEL:table3_2.

###  2.5 Binarity

More than half of the Herbig Ae/Be stars are known to be in binary systems
(Duchêne, 2015). The true number is likely much larger, as there have been a
small number of targeted surveys for binarity of HAeBe stars, the largest are
Wheelwright et al. (2010) and Baines et al. (2006) who performed spectro-
astromety of 45 HAeBes and 31 HAeBes respectively, probing companions in the
$\approx 0.1$ \- $2$ arcsec range, and Leinert et al. (1997) who performed
speckle interferometry of 31 objects, sampling separations of order $0.1$
arcsec. 81/252 HAeBes ($\sim 32\%$) of our set are catalogued as binary
systems, a fraction in agreement with the Duchêne (2015) findings if we take
into account the large number of faint Herbig Ae/Be stars which have never
been studied for binarity. The binary status of each HAeBe is presented in
Table LABEL:table2 and Table LABEL:table2_2 for the high quality and low
quality samples respectively; main references were Baines et al. (2006);
Leinert et al. (1997) and Wheelwright et al. (2010), we refer to Table
LABEL:table2 and Table LABEL:table2_2 for a complete list.

Baines et al. (2006) found a typical wide (few hundred au) separation in the
binary systems. Wheelwright et al. (2010) detected no binaries closer than 30
au and established a range of $\approx 40$ \- $4000$ au in their data.

##  3 Derived quantities

###  3.1 Luminosity and Hertzsprung-Russell diagram

Using the parallaxes, atmospheric parameters and extinction values we derived
the luminosity for the 252 HAeBes with parallaxes employing a similar method
to Fairlamb et al. (2015), which is similar to Montesinos et al. (2009) and
van den Ancker et al. (1997). In short, it first consists of using values of
Teff and surface gravity (log(g)) to select an atmosphere model from Castelli
& Kurucz (2004) (referred to as CK-models hereafter) for each star to be used
for its intrinsic spectral energy distribution (SED). Solar metallicity CK-
models were used in all cases but for BF Ori, RR Tau, SV Cep, XY Per and WW
Vul for which the metallicities are known not to be solar from the
spectroscopic work of Montesinos et al. (2009). When possible, the log(g)
values were estimated from the luminosity class; otherwise they were taken as
4.00 (typical values range from 3.5 to 4.5). Uncertainties in log(g) and
metallicity can be neglected in our study as their effect on the model SED and
derived quantities is negligible.

We then scaled the model to the dereddened photometric Johnson V band. The
energy distribution is then integrated over frequency to get the total flux.
The final luminosities, presented in Table LABEL:table2 and Table
LABEL:table2_2 for the high quality and low quality samples respectively, are
then obtained by means of the total flux and the parallax. All sources of
uncertainty were taken into account at this step including using different CK
models for the different temperatures within the $T\textsubscript{eff}$
uncertainty range.

The 223 Herbig Ae/Be stars satisfying Eq. 1 constraint are plotted in the
resulting HR diagram in Fig. 1. This number is an increase of more than a
factor of ten compared to the previous, Hipparcos-based, study by van den
Ancker et al. (1998). PMS evolutionary tracks from Bressan et al. (2012) are
also plotted in Fig. 1 plus a $2.5$Myr isochrone (Bressan et al., 2012, Marigo
et al., 2017), all of them with solar metallicities ($Z=0.01$ and $Y=0.267$).

Before we analyze this sample, we also plot the HR diagram for all 252 objects
with parallaxes (the high and low quality samples together, hence including
those which failed the Lindegren quality selection criteria) in Fig. 2 on the
left. Many of these badly astrometrically behaved sources are located in
unphysical positions, significantly below the Main Sequence, validating our
approach of removing those from our analyses.

Returning to the HR diagram in Fig. 1, there are still several outliers that
do not seem to be PMS objects. GSC 5360-1033 and UY Ori appear way below the
Main Sequence, just like the lower quality objects that were removed earlier.
However, the Gaia DR2 data of these two objects appear of good quality.
Regarding GSC 5360-1033 the situation is not clear, an ambiguous spectral type
or photometry for this object, or an incorrect estimation or the extinction
may be the reason for the unexpected location of the object. For UY Ori,
Fairlamb et al. 2015 assigned a spectral type of B9 to this object, but the
photometry listed in simbad indicates a large variability. Pending more
certainty, we decided to remove these two objects from the high quality sample
and place them in the low quality sample.

MWC 314, MWC 623 and MWC 930 on the other hand appear quite luminous and very
much to the right of the Main Sequence, something very unusual for high mass
PMS objects. An individual inspection reveals that these objects are more
likely to be evolved giants and they appear in the literature as such (e.g.
for MWC 314: Carmona et al., 2010, for MWC 623: Lee et al., 2016, for MWC 930:
Miroshnichenko et al., 2014). Deciding on the nature of the various Herbig
Ae/Be candidates in our master sample is not our intention and it is beyond
the scope of this paper that is essentially a statistical study. However,
these objects occupy a special place in the HR diagram that is consistent with
both a pre- as well as a post-Main Sequence nature while there is much
information regarding these objects supporting their post-Main Sequence
nature. We therefore decided to err on the cautious side and remove these as
well from further analysis.

The final HR diagram without these $2+3$ problematic objects is presented in
Fig. 2 on the right. In addition, in this graph, we highlight the sample of
The et al. 1994 bonafide HAeBes in red. This final high quality sample of 218
objects will be the one we will use in the following plots and studies. The
information concerning the 34 discarded objects in the low quality sample can
be found in the tables at the end of the paper.

In this last high quality HR diagram we see that there are many more low mass
HAeBes than high mass HAeBes (69% of the sources are below $4M_{\odot}$). This
is most likely because of the Initial Mass Function (IMF). This trend of more
objects for lower masses discontinues below $\sim 2M_{\odot}$. This is roughly
the mass corresponding to the boundary between Main Sequence A- and F-type
stars, and thus the traditional lower mass boundary at which the Herbig Ae/Be
stars were originally selected.

For lower masses the sources are more spread in temperature, occupying larger
parts of the PMS tracks, while, instead, the high mass objects tend to be
predominately located close to the Zero Age Main Sequence (ZAMS). This is
likely because the higher the mass the faster the PMS evolution is. This fast
evolution could explain why high mass objects at low temperatures (and thus
low surface gravities) are hardly present in Fig. 1 or the sample.

We will encounter more examples below where high mass and low mass objects
have different properties.

###  3.2 Mass and age

Using the isochrones, the mass and age of the Herbig Ae/Be stars were
estimated. We used a hundred PARSEC isochrones with solar metallicity (Bressan
et al., 2012; Marigo et al., 2017) from $0.01$ to $20$Myr, from which we only
use the PMS tracks. To each Herbig Ae/Be star we assigned the closest two
isochrone points in the HR diagram; the solar metallicity isochrones did not
match seven sources from the high quality sample in the HR diagram and
isochrones with lower metallicities were used in those cases. As each point is
associated with a mass ($M$) and an age, we computed for each HAeBe an average
of those values weighted by the distance to the points. The result is an
estimate of age and mass for 236/252 HAeBes. These values are presented in
Table LABEL:table3 and Table LABEL:table3_2 for the high quality and low
quality samples respectively. Uncertainties were derived from the error bars
in the HR diagram (Fig. 1 and Fig. 2) keeping a minimum error of $5\%$. We
compared many of our masses and ages with those of Alecian et al. (2013) and
Reiter et al. (2018). We found that our determinations of these parameters are
consistent with the results of the previous authors.

###  3.3 Infrared excesses

In the process of deriving the luminosity it is also possible to derive the
infrared excess. We have logarithmically interpolated the different dereddened
observed fluxes from the J band ($1.24\mu$m) to the W4 band ($22\mu$m) and
defined the infrared excess ($E$) as:

$E=\frac{(F\textsubscript{e}-F_{*})_{[\lambda_{1},\lambda_{2}]}}{F_{*}}$ (2)

$F\textsubscript{e}$ is the total flux underneath the observed dereddened
photometry (the infrared photometry has also been dereddened) and $F_{*}$ is
the total photospheric flux below the CK model. $\lambda_{1}$ and
$\lambda_{2}$ define the range of wavelengths of interest and the total fluxes
in the numerator just refer to that range. This measure expresses the excess
in terms of the total luminosity of the object. For example, all things being
equal, if we have two stars with the same amount of dust surrounding them,
with one of them brighter, the infrared re-radiated emission will be larger,
but the IR excess as defined here, would be the same as it is a relative
measure. The same or a very similar indicator was used by Cote & Waters (1987,
their Eq. 8), Waters et al. (1987, Eq. 3), and more recently by Banzatti et
al. (2018) in their Sect. 2.3.

Uncertainties in the infrared excesses were derived using the uncertainties in
the observed fluxes and the uncertainties in the temperature (which affect the
CK models) of each object.

We have split the total infrared excess in two, a Near Infrared Excess
($1.24-3.4\mu$m, roughly the 2MASS region) and a Mid Infrared Excess
($3.4-22\mu$m, the WISE region). The values for these excesses are presented
in Table LABEL:table3 and Table LABEL:table3_2 for the high quality and low
quality samples respectively. The total infrared excess ($1.24-22\mu$m) is the
sum of the two.

In addition, we also computed the infrared excess at each individual band (J,
H, Ks, W1, W2, W3 and W4) as the flux ratio between the dereddened observed
monochromatic flux and the expected flux according to the CK model. The values
for these excesses are presented in Table LABEL:table4 and Table
LABEL:table4_2 for the high quality and low quality samples respectively

###  3.4 Variability information

Gaia DR2 does not provide a general variability indicator for all sources.
Here, we use Gaia’s repeated observations to extract photometric variability
information. Gaia DR2 used a total of 22 months of observations and each
source was observed repeatedly in a non periodic fashion. Data Release 2
provides the average photometry, the uncertainty on this value and the number
of observations. All things being equal, the photometric “error” will be
larger for a photometrically variable object than for a stable object. Here we
aim to quantify the variability of the objects. We start with the “Variability
Amplitude” ($A_{i}$) for a certain source i as presented in Deason et al.
(2017):

$A_{i}=\sqrt{N\textsubscript{obs,{i}}}\;e(F_{i})/F_{i}$ (3)

where $N\textsubscript{obs}$ is the number of CCD crossings, $F$ and $e(F)$
are the flux and flux error respectively. This quantity is powerful in
identifying objects that show larger flux variations than expected for a
stable star. However, in order to statistically assess the level of
variability, we introduce a variability indicator $V_{i}$, which quantifies
how much more variable an object is compared to stable objects of the same
brightness. In short it compares the Variability Amplitude from Eq. 3 of a
given object ($i$) to that of all Gaia objects in a brightness interval of
$\pm$0.1 magnitude around the G band value of the object (i.e. to
${A_{a}}_{,G_{a}\in{(a_{1},a_{2})}}$, with a indexing the Gaia catalogue and
being $a_{1}=G_{i}-0.1$mag and $a_{2}=G_{i}+0.1$mag). The equation is as
follows:

$V_{i}=\frac{A_{i}-\overline{A_{a}}_{,G_{a}\in{(a_{1},a_{2})}}}{\sigma[A_{a}]_{G_{a}\in{(a_{1},a_{2})}}}$
(4)

$G$ is the Gaia white G band magnitude and $\sigma$ is the standard deviation.
In essence, we subtract the error to flux ratio of each HAeBe, weighted by the
number of observations, to the mean of the same expression ($A_{a}$, Eq. 3)
for the sources in the Gaia catalogue within $\pm{\rm 0.1mag}$ of the Herbig
star in the G band. Then we divide by the standard deviation of $A_{a}s$ of
that Gaia subset. This results in a variability indicator which measures the
variability (in standard deviations, $\sigma$) for each Herbig Ae/Be star
compared to the mean of field objects of the same brightness.

Figure 3: Distribution of the variability indicator for Herbig Ae/Be stars and
two catalogues of photometric standards; one of bright sources (Landolt, 2009)
and one of faint sources (Clem & Landolt, 2016). As a class, the Herbig Ae/Be
stars are more variable than the photometric standards.

Figure 4: Left: IR excess in the range $1.24-22\mu$m vs. estimated mass of the
objects. The most massive objects (more massive than $\sim 7M_{\odot}$) barely
show an infrared excess. Right: IR excess in the range $1.24-22\mu$m vs.
estimated age. Ages and effective temperatures are respectively colour coded
in the legend. The symbols stand for the H$\alpha$ line profiles: circles
(double-peaked), triangles (single-peaked), stars (P-Cygni profile) and
diamonds (no information). Note that although it is not necessarily a one-to-
one correlation, lower ages correspond to higher masses.

For completeness, we note that it is necessary to impose more constraints to
exclude the cases in which a larger error is not due to intrinsic variability.
Following Deason et al. (2017), Appendix C of Lindegren et al. (2018) and what
was done in Gaia Collaboration et al. (2018) we require
$N\textsubscript{obs}\geqslant 70$ and more than 8 visibility periods (i.e.,
groups of observations separated by at least four days), plus the Eq. 1
constraint that limits the astrometric quality (and hence the variability
indicator just can be derived for sources in the high quality sample). In
order to also limit the photometric quality we included the following
criterion presented in Gaia Collaboration et al. (2018):

$1.0+0.015(G\textsubscript{BP}-G\textsubscript{RP})^{2}<E\textsubscript{F}<1.3+0.06(G\textsubscript{BP}-G\textsubscript{RP})^{2}$
(5)

where EF is the flux excess factor and $G\textsubscript{BP}$ and
$G\textsubscript{RP}$ the Gaia blue and red passbands respectively. Note that
these constraints may inevitably exclude many of the very variable HAeBes as
they also trace larger errors and hence variability. These constraints will
also be biased to discarding binaries and faint sources in crowded areas
(Lindegren et al., 2018; Gaia Collaboration et al., 2018).

The variability indicator values for the 193 sources satisfying the previous
conditions are presented in Table LABEL:table3.

In Fig. 3, we show the $V_{i}$ distribution of Herbig Ae/Be stars and compare
it to the $V_{i}$ distribution of bright photometric standards from Landolt
(2009) and faint photometric standards taken from Clem & Landolt (2016). If
Eq. 4 would have not been used these two latter samples would have had a
different mean in the distribution of $A_{i}$. The Herbig Ae/Be stars appear
to show, on average, a larger variability indicator value than the standard
stars, being the break at $\sim V_{i}=2$. We performed a two-sample
Kolmogorov-Smirnov (KS) statistical test to study whether Herbig Ae/Be stars
can be drawn from those two samples of standard stars. The result shows that
we can reject that hypothesis to within a 0.001 significance and hence this
variability indicator differentiates them as a group.

In order to assess the relation between our variability indicator (G band
variability) and variability in the V band we compared the magnitude
variations in the V band as presented in the International Variable Star Index
VSX (Watson et al., 2006) with our variability indicator values. We found that
we are tracing variabilities as small as $\sim 0.5$mag with the $V_{i}=2$ cut-
off. In Eiroa et al. (2002) 7/23 (30%) PMS objects homogeneously observed for
variability have variabilities above 0.5mag. In our case 48/193 sources have
values above $V_{i}=2$ (25%) and hence can be considered as strongly variable.
Of those 48, 17 are catalogued as UXOR type (Mendigutía, 2011c; Oudmaijer et
al., 2001; Poxon, 2015). There are 5 other UXORs in our sample with $V_{i}$
values, 4 of them have reported optical variabilities smaller than $0.5$mag in
the V band. The other one is BO Cep. This object has been reported to have a
periodic variability with a single prominent peak with a period of $\sim 10$
days (Gürtler et al., 1999). The regular non periodic variability of the
object is smaller than $0.5$mag which explains why this UXOR has not been
detected by our variability indicator. Supporting this, it appears as UXOR in
Poxon (2015) but not in Oudmaijer et al. (2001) or Mendigutía (2011c).

To put the variability indicator into perspective, we find that 6 out of 411
photometric standards from Landolt (2009) have variability indicator values
larger than 2. We would therefore expect only 3 of our 193 Herbig Ae/Be stars
for which we could determine $V_{i}$ to be strongly variable, at amplitudes of
0.5 magnitudes in the V band or higher. However, we find 45 more, indicating
that a large fraction of Herbig Ae/Be stars exhibit strong variations.

In addition, it is interesting to compare our variability indicator with the
variability catalogues published alongside the Gaia DR2 general catalogue
(Holl et al., 2018). Just 1 every 3000 objects passed the Gaia DR2 stringent
selection criteria for variability. 10/252 objects in our list fall in this
category and appear as variable in those catalogues. Of the 5 of those that
have derived $V_{i}$ values they are larger than $V_{i}=5$.

##  4 Data analysis

###  4.1 Infrared excesses

In Fig. 4 the total infrared excess ($1.24-22\mu$m) vs. the estimated mass and
age of the sources is plotted. There appears a difference in IR properties
between high and low mass stars. Whereas low mass stars show a range of
infrared excess, the higher mass stars in general only present very low levels
of excess. A similar behaviour is seen when the excess is plotted as function
of age; the excess for the youngest objects is smallest. This is probably
readily explained by the fact that the more massive PMS objects in the HR
diagram have the lowest ages by virtue of their rapidly evolving isochrones,
so trends in mass will automatically also be present in those with age. To
study trends as a function of age, it would be necessary to consider
subsamples with a narrow range in mass. We therefore consider that the main
result of this exercise is that high mass objects have a very low infrared
excess, and that there appears to be a break at $\sim 7M_{\odot}$ from where
almost no sources with significant excess appear.

Fig. 5 splits the total infrared excess into two, a near-infrared and a mid-
infrared part. It demonstrates that the excess at both wavelength ranges are
highly correlated with each other (the linear fit in logarithmic space that
can be seen in the plot has a correlation coefficient of $r=0.88$). Therefore,
it is not unexpected that the $\sim 7M_{\odot}$ break is also present at near-
and mid-infrared.

###  4.2 H$\alpha$ equivalent width

Fig. 6 shows the EW as a function of mass and age respectively. As the
definition of a Herbig Ae/Be star includes the presence of emission, which is
mostly from the H$\alpha$ line, it may not come as a surprise that essentially
all measurements are negative (i.e. tracing emission).

The EWs show a large range of values, which appears to increase with
increasing mass and decrease with increasing age (studied by Manoj et al.,
2006). The older objects typically have lower EW’s than younger objects. It is
tempting to read an evolutionary effect in this finding - after all it would
be expected that the accretion (and therefore emission) would decrease when
the PMS objects are closer to the MS. However, we should recall that there is
a strong correlation between the age and the mass of the stars, so we may well
be looking at a mass effect instead. As the EW is a relative measurement with
respect to the stellar continuum, a larger EW for otherwise similar objects
indicates a stronger emission line. The observed trend towards higher
temperatures/masses and thus higher luminosities implies that the lines become
even stronger than the EW alone would seem to imply.

Figure 5: IR excess in the range $3.4-22\mu$m (Mid IR excess) vs. IR excess in
the range $1.24-3.4\mu$m (Near IR excess). The symbols stand for the H$\alpha$
line profiles: circles (double-peaked), triangles (single-peaked), stars
(P-Cygni profile) and diamonds (no information). A linear fit in the log space
is shown in blue ($\log($Mid IRexcess$)=1.16\log($Near IRexcess$)+0.23$,
$r=0.88$).

###  4.3 H$\alpha$ EW and infrared excess

The correlation between H$\alpha$ emission, measured by its equivalent width,
and near- and mid-infrared excess is studied in Fig. 7 and Table 1 for each
one of the infrared bands (J, H, Ks, W1, W2, W3 and W4). In this case, we
computed the infrared excess as the flux ratio between the dereddened observed
monochromatic flux and the expected flux according to the CK model at each
band (the values for these excesses are presented in Table LABEL:table4 and
Table LABEL:table4_2 for the high quality and low quality samples
respectively). In all cases, there is a general and consistent increase of the
H$\alpha$ EW from sources with very little IR excess to those with higher IR
excess.

In Table 1 we show that the H$\alpha$ emission line equivalent width is more
correlated with the infrared excess at shorter wavelengths than at larger
wavelengths, with the correlation peaking at $2.16\mu$m (Ks band).

An obvious question might be whether there is a causal correlation between the
H$\alpha$ emission and presence of emission due to dust around these objects.
The various excesses at various wavebands are correlated with each other (Fig.
5), and as a consequence the IR excess at many wavelengths also correlate with
the EW. However, the correlation with H$\alpha$ is strongest at the Ks band
which traces the hot dust in the inner disk, suggesting the accretion
mechanism or wind activity as traced by H$\alpha$ is related to the inner
parts of the dusty disk (see also Manoj et al., 2006). As presented in Table
1, the correlation rises from a minimum at $1.24\mu$m (effectively tracing the
stellar photosphere) up to $3.4\mu$m and then goes down again to the same
minimum at $22\mu$m (W4 band), where dust in the outer disk is found. In fact,
Mendigutía et al. (2012) discovered the same correlation between IR excess and
accretion rate and they found that it is no longer present beyond $20\mu$m.

For comparison purposes, in Fig. 7 the Ks band is plotted in the upper panel
and the W4 band in the lower. It is noteworthy that for the Ks band, where we
have the strongest correlation, small EWs are almost only present in sources
with little IR excess and, in consonance with Sect. 4.1, for a given H$\alpha$
EW value low mass stars ($M<7M_{\odot}$) tend to have higher IR excesses.
However, these trends are weaker or non existent in the case of the W4 band,
where we have the weaker correlation. This reinforces the idea that the
H$\alpha$ emission is correlated with the inner parts of the disk. Note that
in both panels the average excess is still lower for the higher mass objects.
The emission line strengths will also be subject of a follow-on study using
accretion rates (Wichittanakom et al. in preparation).

Figure 6: Left: H$\alpha$ EW vs. estimated mass. Right: H$\alpha$ EW vs.
estimated age. Effective temperatures and masses are respectively colour coded
in the legend. The symbols stand for the H$\alpha$ line profiles: circles
(double-peaked), triangles (single-peaked), stars (P-Cygni profile) and
diamonds (no information).

###  4.4 Variability

We conclude this section by studying the variability of the objects and its
correlation with the various properties discussed so far, including the
H$\alpha$ line profiles we took from the literature.

The left panel of Fig. 8 presents the variability indicator as function of the
total (near plus mid) IR excess. As described in Sect. 3.4 the variability
indicator states the number of standard deviations a certain source is
separated from the mean of the Gaia objects of the same brightness. No, or
hardly any variability is present at the lowest IR excesses but sources can be
both variable and non-variable at the higher IR excesses, consistent with van
den Ancker et al. (1998) based on a smaller sample.

The figure next to it shows the variability as a function of mass. As high
mass stars in this sample generally do not have a strong IR excess, we find
that mostly the lower mass and cooler objects display high variabilities, with
the break also around 7 M⊙, corresponding to a Main Sequence spectral type of
around B3. Although cooler objects tend to have larger variabilities (also
observed by van den Ancker et al., 1998), we can observe how the range in
temperatures for variable sources is wide in the right panel of Fig. 8, and
that there are in fact many Herbig Be stars with very strong variabilities.
Hence, this is more likely a trend with mass and not with temperature. We do
note that although we detect photometric variability from the $V_{i}=2$ value,
the $V_{i}=5$ value is a better separation boundary for the observed trends in
both panels of Fig. 8.

The challenge is to identify which property lies at the cause of the
variability, is it the mass of the objects, their age or infrared excess
emission or something else? An important clue is that many objects with strong
variability (above $V_{i}=2$) and line shape information have doubly peaked
H$\alpha$ profiles ( 31 out of 43; $72\pm$7%, 68% confidence interval). In
general, double-peaked emission line profiles are due to rotating disks, so
the data are suggestive of an edge-on disk-type orientation and structure
(from the remaining 12 objects they all have a P-Cygni profile and none have a
single-peaked profile). The number of variable objects with doubly peaked line
profiles is significantly different from the full sample, in which only half
of the targets with known line classifications have a double-peaked profile
(of the sources with derived variability indicator and known line profile 79
out of 155; 51$\pm$4% are double-peaked and 48 our of 155; 31$\pm$4% are
single-peaked). These fractions are significantly different, and we therefore
suspect that the variable sources are mostly oriented edge-on, and that the
line-of-sight inclination to the objects could be a decisive factor in the
cause of the variability. This is in agreement with the trend observed in the
left panel of Fig. 8. Sources with large amounts of circumstellar material
show large infrared excesses and high or low levels of variability depending
on the inclination of their disk whilst sources with little material around
have low infrared excesses and low variabilities in all cases (also discussed
in van den Ancker et al., 1998).

##  5 Discussion

###  5.1 General findings

In the above we have determined fundamental parameters such as temperature,
mass, age, IR excess, variability and luminosity for a large sample of Herbig
Ae/Be stars which was made possible due to the more than a factor of ten
increase in available distances to these objects compared to Hipparcos. With
the Gaia DR2 data, the majority of known Herbig Ae/Be stars could be placed in
the HR diagram. We found the following:

  * •

There are more low mass objects than high mass objects, with the high mass
objects mostly located close to the Main Sequence.

  * •

High mass objects have in general very small infrared excesses and low
variability, the properties appear to differ around 7M⊙.

  * •

H$\alpha$ emission is generally correlated with infrared excess, with the
correlation stronger for IR emission at wavelengths tracing the hot dust
closest to the star.

  * •

More massive and younger objects have higher H$\alpha$ EWs.

  * •

When split at 7M⊙ into “low” and “high” mass samples, the H$\alpha$ \- IR
excess correlations hold for both mass ranges, with the average excess lower
for the higher mass objects.

  * •

Photometric variability can be traced back to those objects with double-peaked
H$\alpha$ emission and large infrared excesses.

  * •

All catalogued UXORs in the sample with detected variabilities above $0.5$mag
in the V band appear as strongly variable (above $V_{i}=2$) with the exception
of BO Cep (discussed in Sect. 3.4).

Here, we will discuss these findings and their implications for the formation
of intermediate mass stars.

###  5.2 Selection effects

Let us first investigate the various selection effects and biases that could
potentially affect the results.

Quality parallaxes: It could be argued that the quality of the astrometric
data has an effect on the findings. The parallax errors occupy a comparatively
small range, from $\sim$0.016-0.37 mas, but because of the large spread in
distances, the relative uncertainties can be very large. To investigate
whether this has a detrimental effect on the results, we repeated the analysis
with only the objects with the very best parallaxes
($\varpi/\sigma_{\varpi}>10$). This, of course, limits the sample and 182/218
objects remain in the high quality sample. These 182 objects are less
luminous, which may be expected as in general they have larger parallaxes and
are thus closer. As a result they will be less massive and have larger ages
than the objects in the entire sample. This, as a consequence of the trends
described in previous sections, implies that these objects also show larger
infrared excesses and variabilities as well as smaller H$\alpha$ EWs (see Fig.
4, Fig. 6 and Fig. 8). However, we find that essentially all correlations also
hold for the higher quality parallax sample, and if anything, they appear
stronger. For example almost all of the high mass sources that have large
infrared excesses and variabilities in figures Fig. 4 and Fig. 8 have
$\varpi/\sigma_{\varpi}<10$. The inclusion of lower quality parallaxes induces
an extra scatter in the results, but the larger sample and wider coverage in
luminosity aids in reinforcing them.

Quality identification as Herbig Ae/Be star: Another potential source of error
is source misclassification. We have used the largest sample of Herbig Ae/Be
stars published to date (Chen et al., 2016 with some added from Alecian et al.
(2013); Baines et al. (2006); Carmona et al., 2010; Fairlamb et al., 2015;
Hernández et al. (2005); Manoj et al. (2006) and Sartori et al. (2010)). The
defining characteristics of HAeBes are not unique to the class, and can often
also be found in other types of stars such as classical Be stars, which
display H$\alpha$ emission and a near-infrared excess (e.g. Rivinius et al.,
2013) or evolved stars which can have spectral types A and B, display hydrogen
recombination emission and be surrounded by dusty shells and disks such as the
Luminous Blue Variables and B[e] stars (Davies et al., 2007; Oudmaijer, et
al., 1998 on HD 87643). It is therefore inevitable that some sources will have
been misclassified. It would be fair to say that the more “classical” Herbig
Ae/Be stars going back to the Herbig (1960) and The et al. (1994) papers have
been studied in more detail and are better established as young pre-Main
Sequence stars.

We therefore studied the The et al. sample of objects (their Table 1, 85
sources out of our 218) separately and find that all correlations do hold for
this “gold standard” sample as well. We do find that on average these objects
have a larger H$\alpha$ EW and have larger IR excesses than the full sample.
These properties are the defining characteristics of a Herbig Ae/Be star, and
it may not be surprising that the first objects to be proposed as Herbig Ae/Be
stars are on average more extreme in these properties. Yet, again, as with the
higher quality parallax sample, the trends are still present in this sub-
sample.

Figure 7: $2.16\mu$m (blue markers) and $22\mu$m (red markers) infrared
excesses defined as $F_{observed}/F_{CK}$ vs. H$\alpha$ equivalent width
(absolute value). Note that this IR excess indicator is a flux ratio and not
the one described in Eq. 2 where we integrated under the SED. Dots are Herbig
Ae/Be stars with $M<7M_{\odot}$ and triangles are Herbig Ae/Be stars with
$M>7M_{\odot}$. Lines are linear fits to the data, dashed for HAeBes with
$M>7M_{\odot}$ and in solid colours for HAeBes with $M<7M_{\odot}$; black
solid lines are the linear fits for all the sources (equations and correlation
coefficients for these fits to all the sources for all the infrared bands can
be seen in Table 1). Note the difference in the scale of the vertical axis
between the two panels.  Table 1: Correlation between IR excess and H$\alpha$
EW at different wavelengths.

Band | Correlation | A | B
---|---|---|---
| coefficient (r) |  |
J ($1.24\mu$m) | $0.41$ | $0.15\pm{0.03}$ | $0.025\pm{0.034}$
H ($1.66\mu$m) | $0.56$ | $0.32\pm{0.03}$ | $0.0024\pm{0.0478}$
Ks ($2.16\mu$m) | $0.60$ | $0.48\pm{0.05}$ | $0.046\pm{0.066}$
W1 ($3.4\mu$m) | $0.57$ | $0.64\pm{0.07}$ | $0.15\pm{0.10}$
W2 ($4.6\mu$m) | $0.57$ | $0.78\pm{0.09}$ | $0.24\pm{0.12}$
W3 ($12\mu$m) | $0.52$ | $0.93\pm{0.12}$ | $0.79\pm{0.16}$
W4 ($22\mu$m) | $0.41$ | $0.71\pm{0.12}$ | $2.05\pm{0.17}$
222Correlation between IR excess (defined as a flux ratio, Fobserved/FCK) and
H$\alpha$ EW at different wavelengths for all the sources. The coefficients
are defined by: $\log($Fobserved/FCK$)=A\log(|\rm EW|)+B$. The Ks band, with
the higher correlation, and the W4 band are in bold; both are shown in Fig. 7.

Mass distribution of the sample: The known Herbig Ae/Be stars have mostly been
found serendipitously, and a large-scale systematic search for them has yet to
be carried out. Yet, an interesting question is how representative the present
sample is for the class. To this end, we consider the mass distribution of the
objects. There are more or less the same number of low mass, A-type objects
than higher mass B-type objects. There are more Herbig Be stars than might be
expected from the Initial Mass Function, however, the B-type objects are
brighter and are sampled from a larger volume, as also attested by their
smaller parallaxes. We will therefore expect a larger fraction of Herbig Be
stars in the sample. When limiting our sample in distance, we obtain a Herbig
Ae/Herbig Be ratio that is close to the IMF. As far as the mass distribution
is concerned, we may say that the current sample is representative of the
class. One of our future goals is to draw an increased and well-selected
sampled of Herbig Ae/Be stars from the Gaia catalogues.

Binarity: One may think that binarity may affect the observed photometry and
for example produce fake levels of variability in our variability indicator.
This is because binary sources tend to be more astrometrically and
photometrically irregular. We studied the group of binaries against the group
of isolated sources and overall we find that the known binaries are slightly
brighter than the objects that have not been reported to be a binary. This is
probably a selection effect in that brighter objects were more likely to be
included in the binary surveys. We compared the brightnesses of binaries and
non-binaries in the Baines et al. (2006), Wheelwright et al. (2010) and
Leinert et al. (1997) studies separately and find that within the surveys
there are indeed no brightness differences between binaries and non-binaries.

Returning to the Gaia sample; all other properties but infrared excesses,
including variability, are similar. We do find that binaries have in general
slightly larger IR excesses. With the benefit of hindsight, this is perhaps
something that could have been expected. Most of the binaries are distant
binaries with separations larger than 0.1 arcsec (Gaia’s resolution). Indeed,
no binaries are found closer than 30au so it is expected that binarity does
not play a significant role in the optical photometry. At the same time,
companions could potentially contribute to the infrared emission whose fluxes
have been measured with apertures larger than the typical separations. Given
that we do detect slight differences in IR-excess between binaries and non-
binaries, a preliminary inference would be that the companions may contribute
to the infrared flux in some cases.

###  5.3 Infrared excess as function of mass

Fig. 4 shows the infrared excess as function of mass and age respectively.
There is a marked difference in the infrared excess observed towards high and
low mass objects. Herbig Be stars more massive than $\sim$7 M⊙ in general
appear to have little to no excess, while the lower mass objects show a wide
range of excesses. There is also a trend with age with the youngest objects
having the smallest infrared excess. Although it would be tempting to assume a
causal relation between age and presence of dust, and try to explain why the
youngest objects have the smallest amount of dust around them, we suspect the
stellar mass is the dominant factor. The durations of the PMS evolutionary
tracks are progressively shorter for higher masses, and an underlying relation
between mass and infrared excess would therefore also appear as a correlation
between age and infrared excess.

Either way, the lack of dusty emission from high mass objects is puzzling, as
we might expect the more massive objects to be formed in more massive clouds
and therefore be more embedded. A natural conclusion would be that at any time
of their PMS evolution, these young objects would be surrounded by more dust
than their lower mass counterparts and therefore, at any stage, they would
have a stronger infrared emission. A counterargument is that the Herbig Be
stars are predominately found closer to the ZAMS and are therefore more
evolved, having dispersed their circumstellar material. Supporting this idea,
Alonso-Albi et al. (2009) found, from their compilation of millimetre
observations of 44 objects, that Herbig Be stars have much weaker millimetre
emission than their later type counterparts. In addition, they found that the
masses of the disks around Herbig Be stars traced at mm wavelengths are
usually 5-10 times lower than those around lower mass stars, with the boundary
also around 7 M⊙. These authors suggest that the disk dispersal is more
efficient and faster in high mass objects above 7 M⊙. Indeed, the disk
dispersal times are a steep, declining function with stellar mass, from
millions of years for the lower mass stars to tens of thousands of years for
the highest mass young stars of 10 M⊙ and higher (Gorti et al., 2009).

The latter timescales are comparable to the evolutionary timescales as for
example computed by Bressan et al. (2012) for these massive objects. Thus, the
observation here is consistent with the classical scenario that the Kelvin-
Helmholtz contraction timescale is much smaller for massive objects compared
to the free-fall timescale of the collapsing parental cloud. In this scenario,
the massive young stars only become visible once they are on, or close to, the
Main Sequence - the so-called birthline. We will discuss more on this later,
but note that with this interpretation one still would expect a range of
infrared excesses in any sample. This is consistent with what we find for
massive objects (larger than 7 M⊙); a large number of low excess stars, but
still a few with noticeable excess (see Fig. 4).

Moving to the lower mass objects, which do display a large range of infrared
excess emission, an immediate question to ask is whether we can detect any
evolutionary effect in the sense that objects that are further evolved have
smaller infrared excesses, as one expected from the progressive dust
dispersal, and as suggested by Fuente et al. (1998). For example, if the
inside out clearing model of disk evolution is correct, we should see a trend
at each PMS track from high excess to little excess.

However, it appears Herbig Ae/Be stars do not show any consistent evolution of
the infrared excess from high to low excess at any mass range. There are many
objects appearing younger than 2.5 Myr or even 1 Myr at all mass ranges with
little IR excess. Arguably the lack of an evolutionary effect can be explained
by the size of the error bars on for example the luminosity. The evolutionary
timescales vary strongly with mass (and thus luminosity), masking any trend of
infrared excess emission with age. Here, we would highlight that many young
Herbig Ae stars show little excess. By looking at these objects in the right
panel of Fig. 2 it is not difficult to find sources with error bars small
enough to discard the contribution of uncertainty to the problem. Finally, the
contamination by binaries as discussed in Sect. 5.2 can play a role in here as
many HAeBes can still remain as undetected binaries.

We should also note that the underlying assumption of the evolutionary
calculations is that the conditions under which the stars form are uniform,
the accretion rates a smooth function of time resulting in an overall similar
evolution for all stars. However, the final configuration is undoubtedly
affected by inhomogeneities, varying accretion rates and even the masses of
the initial clouds. Nevertheless, looking for real evolutionary effects in the
spectral energy distributions requires selecting subsamples of objects that
are located at or close to the same mass tracks. This may require even more
precise parallaxes than can be provided by Gaia at the moment in many cases.
It also requires precise determinations of the atmospheric parameters and
extinction values. A proper statistical study with high quality parameters of
the evolutionary properties of the HAeBes as they move towards the Main
Sequence is hence still pending and planned for the future.

###  5.4 Variability in terms of the UXOR phenomenon

Figure 8: Left: Variability indicator vs. IR excess in the range
$1.24-22\mu$m. It can be seen how objects with the lower IR excess do not show
high variability. Right: Variability indicator vs. estimated mass. It can be
seen how the most massive objects (more massive than $\sim 7M_{\odot}$) do
barely show variability. Line profiles and temperatures are colour coded in
the legend in the left and right panel respectively. The symbols stand for the
H$\alpha$ line profiles: circles (double-peaked), triangles (single-peaked),
stars (P-Cygni profile) and diamonds (no information). The $V_{i}=2$ and
$V_{i}=5$ values are stressed for clarity.

The variability indicator that was developed specifically for the Gaia data
demonstrates that the class of Herbig Ae/Be stars is more variable than the
general population of stars. Fig. 8 shows that the lower mass objects are much
more photometrically variable than the higher mass objects, for which the
variability appears to cease beyond $\sim$7 M⊙. The photometrically variable
objects contain most of the so-called UXOR variables reported in the
literature. Using the compilation of UXOR variables by Mendigutía (2011c);
Oudmaijer et al. (2001) and Poxon (2015), we find that 17 out of the 48
strongly variable objects - those with variability indicator values larger
than 2, representing variations of 0.5 magnitudes (in the V band) or higher -
are classified as UXORs. The remaining 5 UXORs with variability indicator
values present in the sample have documented variabilities below 0.5
magnitudes with the exception of BO Cep (discussed in Sect. 3.4).

The defining characteristic of the UXOR phenomenon is not only the photometric
variability but also the reddening and blueing associated during the
variations. The explanation put forward for this behaviour is the obscuration
of the star by a rotating, inhomogeneous, dusty edge-on disk. The objects
first become redder when dust obscures the object, and can even become blue at
their faintest phases, when the direct light from the stars is blocked and,
predominately blue light is scattered into the line of sight. As the
polarization - resulting from scattered light - also peaks during the faintest
phases (e.g. Grinin 2000), the obscuring disk hypothesis is favoured.
Interestingly, observational evidence other than the polarization supporting
this conclusion has been relatively sparse.

With the large sample of Herbig Ae/Be stars, and the large number of UXORs
among them, we can repeat a similar experiment using the H$\alpha$ line as a
proxy for the inclination of the circumstellar disks. We will consider the
line profiles of the H$\alpha$ emission in tandem with the variability
indicator. Fig. 8 shows that all but twelve of the strongly variable objects
with documented line profiles (above $V_{i}=2$, those with $\Delta V>0.5$mag)
have double-peaked H$\alpha$ emission. In fact, the five objects for which no
line profile is listed have, to our knowledge, no reported profiles. The
occurrence of double-peaked profiles in the highly variable sample is
significantly higher than for the other objects (see Sec. 4.4). It is
significant that the other twelve objects have P-Cygni profiles and none of
them show a single-peaked profile. The P-Cygni profile is often related to
episodic energetic phenomena and it is not unexpected that it is also traced
by our variability indicator. Given that doubly peaked line profiles are most
easily explained by at least part of the emission originating in a rotating
disk leads us to conclude that the photometrically variable objects are seen
edge-on and surrounded by a disk-like structure. It is true that outflows or
winds not limited to the disk can produce double-peaked H$\alpha$ profiles
(Kurosawa et al., 2006; Tambovtseva et al., 2014). Supporting the hypothesis
of edge-on disks being the main cause of photometric variability, we find in
variability the same separation at $\sim$7 M⊙ between low and high mass
objects we found when studying IR excesses, which suggests that photometric
variability and IR excess have the same cause. In addition, sources with high
IR excesses have both high and low variability levels, which can be understood
as depending on the disk inclination, while sources with lower IR excesses
show little variability in all cases (left panel of Fig. 8, discussed in Sect.
4.4). This would also explain the few high mass strongly variable objects that
can be seen in the right panel of Fig. 8; they are mostly the ones with high
IR excess in the left panel of Fig. 4 (discussed before in Sect. 5.3). Given
that an edge-on orientation is the major and main ingredient of the dust
obscuration hypothesis, these results lend very strong support to it using a
large sample of Herbig Ae/Be stars.

The large fraction of objects with double-peaked line profiles or variability
is in agreement with the model predictions by Natta & Whitney (2000) who
worked out how many Herbig Ae/Be stars would undergo the UXOR phenomenon
considering the scale heights of dusty disks and under which inclinations the
photometric variability would still be visible. They conclude that around half
of the Herbig Ae stars could be UXORs. In our high quality sample we have $85$
A type stars with variability indicator values and just $16$ of them were
previously listed as UXORs, but again most of them have been largely
unstudied. However, of the $25$ A type stars with variabilities above
$V_{i}=2$, $13$ are known UXORs. This means that for the Herbig Ae stars for
which we detect variability at the $V_{i}=2$ level, $\sim 52\%$ are known
UXORs (and just two have P-Cygni profiles). Moreover, this implies that we are
retrieving $\sim 81\%$ of known A-type UXORs with our variability indicator
and hence, assuming that all the $25$ A type stars with variabilities above
$V_{i}=2$ are of UXOR type, there should be about 31/85 UXORs in the sample.
In turn this would imply that $\sim 37\%$ of all Herbig Ae stars belong to the
UXOR class. If we also take into account that we have potentially removed some
UXORs, possibly the most variable ones, from consideration when applying the
constraints described in Sec. 3.4 we get to values close to the $50\%$
predicted by Natta & Whitney (2000).

Finally, Davies et al. (2018) recently studied in detail the UXOR object CO
Ori, which has single-peaked H$\alpha$ emission. Consequently, they found that
the inclination of its disk is of $\sim 30^{\circ}$ (i.e. it is nearly face-
on). In this particular case, whether if the disk is still causing the UXOR
phenomenon or if it is caused through fluctuations in the circumstellar
material outside the disk is still uncertain. We could not derive a
variability indicator value for this object to assess its variability.
Inspired by this example, we took a look to the other UXORs in our sample with
single-peaked profiles, they all have variabilities below $V_{i}=2$ in our
variability indicator (HD 100546, HD 142527, HD 98922 and IL Cep), this
suggesting a category of low variability UXORs with nearly face-on disks.
Nonetheless, the results presented in this section strongly support the idea
that most UXORs are caused by edge-on disks, which are responsible of large
photometric variabilities.

###  5.5 Missing objects in the HR diagram

When inspecting the right panel of Fig. 2, it appears that most Herbig Be
stars are located relatively close to the Main Sequence, whereas the lower
mass Herbig Ae stars occupy a larger part of their evolutionary tracks,
contracting to higher temperatures at constant luminosity. In other words, the
late type Herbig Be and Herbig Ae stars at high luminosities (and low surface
gravities) that would occupy the tracks towards the locations of B-type stars
on the Main Sequence are missing. It is only due to the use of Gaia
parallaxes, expanding the number of Herbig Ae/Be stars with well established
luminosities that we can make this observation.

In our discussion earlier, we mentioned the fact that these objects could
still be heavily embedded in their parental clouds, preventing them from being
optically visible when evolving on their way to the Main Sequence. There is
evidence for optically invisible, but infrared bright objects at locations in
these regions of the HR-diagram. For example, Pomohaci et al. (2017) were the
first to spectrally type an infrared bright Massive Young Stellar Object based
on the, rare, absorption spectrum at near-infrared wavelengths (higher order
Brackett lines are in absorption for this object, while Br$\gamma$ is in
emission). They found that the object could be fitted with that of an A-type
giant star. Had this object been optically visible, it would have occupied the
empty region in the right panel of Fig.2. To this, we add the early B-type
Herbig Be stars/infrared bright MYSOs PDS 27 and PDS 37 (Ababakr et al.,
2015). They are found in the upper regions of the HR diagram, slightly off the
Main Sequence. They are optically visible, but not overly bright at $V\sim
13$mag, and have not been included in many (optical) magnitude limited
catalogues. Thus, there are several examples that might lead us to conclude
that the - implicit - optical brightness limit of any catalogue of Herbig
Ae/Be stars would prevent the inclusion of massive pre-Main Sequence stars on
the horizontal portions of the evolutionary PMS tracks. However, these object
are present in Gaia DR2 although they are yet uncatalogued as HAeBes. In a
sense this is a situation similar to that outlined for the low infrared
excesses observed toward the Herbig Be stars that are mostly located close to
the Main Sequence. This could be explained by the fact that the objects would
be embedded and thus optically invisible or faint in earlier phases of their
evolution.

Further observations of optically fainter objects will be necessary to settle
this issue. Additional progress can be made by connecting the PMS evolutionary
tracks with radiative transfer codes to provide synthetic observations (as
e.g. Davies et al., 2011, or Zhang et al., 2014 for Massive Young Stellar
Objects) extended to optical wavelengths in the Herbig Be mass range. Related
to the “missing” high mass stars in the HR diagram, it will be important to
fill the historic, and entirely man-made, gap between the Herbig Ae stars and
the T-Tauri stars. The latter are confined to have spectral types G-K-M, and
typically Herbig Ae/Be stars, in this case by definition, have spectral types
A and B. We are missing out the F-type stars, resulting in an incomplete
coverage of the HR diagram for pre-Main Sequence stars.

###  5.6 On the difference between Herbig Ae and Herbig Be stars

From the above it appears that the dusty disks surrounding Herbig Ae and
Herbig Be stars are different, with the break in IR excess occurring at 7M⊙
(around B3 spectral type), a value which was also found by Alonso-Albi et al.
(2009) from their compilation of millimetre emission tracing the outer parts
of the dusty disks. As discussed, given the much stronger radiation field from
B-stars, both in intensity and photon-energies, the most straightforward
explanation for the much less massive disks of higher mass objects is a more
efficient disk dispersal mechanism (see e.g. Gorti et al., 2009). This also
explains why the same 7M⊙ break is seen in variability (Fig. 8). As described
in Sect. 5.4, the high levels of variability in some sources are caused by
edge-on dusty disks. A more efficient disk dispersal mechanism beyond 7M⊙
would result in these sources showing no strong variability in our indicator.
It also explains why the objects with the lower IR excesses are not strongly
variable while the rest can have both high and low variability values.

Other studies of large samples of Herbig Ae/Be stars indicate a break in
properties at a much lower mass of 3M⊙, around the B7 spectral boundary.
Fairlamb et al. (2015) studied the accretion rates, which are proportional to
the mass of the objects, and found a different slope for lower mass than for
higher mass objects. Ababakr et al. (2017), extending the work of Mottram et
al. (2007), found a distinct difference in spectro-polarimetric properties
across the H$\alpha$ line between the Herbig Ae and late Be type stars on the
one hand and earlier Herbig Be type objects on the other hand. These authors
also point out the similarity in the H$\alpha$ spectro-polarimetry of the
Herbig Ae stars and T-Tauri stars. Finally, Mendigutía et al. (2011a) noted
the difference in H$\alpha$ variability; Herbig Ae and late Be stars are
largely variable, whereas Herbig Be stars are not. Later, Fang et al. (2013)
showed that T-Tauri stars display even more variable H$\alpha$ emission -
again hinting at a similar accretion mechanism for the T-Tauri stars and
Herbig Ae stars.

How can we reconcile the fact that some studies show a different break in
properties than others? It is worth pointing out that the latter
investigations consider regions much closer to the star than the dusty
emission. Fairlamb et al. (2015) derives accretion rates from the UV-excess,
which trace the shocked material on the stellar surface, Ababakr et al.
(2017)’s spectropolarimetry traces the free electrons in ionized material at
distances of order stellar radii from the stars. The spectro-polarimetric
properties of the B-type stars can be explained by stable circumstellar disks,
while the line properties for T-Tauri and Herbig Ae objects are consistent
with magnetically controlled accretion. Likewise, the H$\alpha$ emission
traces the ionized zones close to the star, such as the accretion columns and
circumstellar disks and the variability is explained due to the accretion
columns orbiting the central star (e.g Kurosawa et al., 2008).

Earlier, we showed that the IR fluxes and H$\alpha$ properties are largely
correlated, but that the IR fluxes are smaller for the earlier type objects.
We therefore conclude this section with the observation that the infrared and
millimetre emission trace the circumstellar disks and originates much further
from the stars than the UV, hydrogen recombination emission and free electrons
which trace the accretion onto the stars. The break in accretion mechanism
appears to occur around 3M⊙, whereas the disk dispersal becomes significant at
higher masses, 7M⊙.

##  6 Conclusions

In this paper we have collated the largest astrometric dataset of Herbig Ae/Be
stars. We present parallaxes for the vast majority of known Herbig Ae/Be stars
and have gathered atmospheric parameters, optical and infrared photometry,
extinction values, H$\alpha$ emission line information, binary statistics, and
devised an objective measure for the photometric variability. From these we
derive luminosities which allow us to place the objects in an HR diagram,
containing over ten times more objects than previously possible.

Thus, we homogeneously derived luminosities, distances, masses, ages,
variabilities and infrared excesses for the most complete sample of Herbig
Ae/Be stars to date. We investigated the various properties and reach the
following conclusions:

  1. 1.

The Gaia photometric variability indicator as developed here indicates that
48/193 or $\sim$25% of all Herbig Ae/Be stars are strongly variable. We find
that the presence of variability correlates very well with the H$\alpha$ line
profile. The variable objects display doubly peaked profiles, indicating an
edge-on disk. It had been suggested that this variability is in most cases due
to asymmetric dusty disk structures seen edge-on. The observation here is the
most compelling confirmation of this hypothesis. Most sources catalogued as
UXORs in the sample appear as strongly variable with double-peaked profiles.
The fraction of strongly variable A-type objects is close to that found for
the A-type objects with the UXOR phenomenon.

  2. 2.

High mass stars do not display an infrared excess and show no strong
photometric variability. Several suggestions have been put forward to explain
this. These include fast evolutionary timescales and fast dust dispersion
timescales for high mass objects. We do note that the break is around 7 M⊙,
which is intriguingly similar to other statistical studies related to dusty
disks around Herbig Ae/Be stars which signpost a different or more efficient
disk dispersal mechanism for high mass objects.

  3. 3.

Whereas the break in IR properties and photometric variabilities occurs at 7
M⊙, various H$\alpha$ line properties including mass accretion rates,
spectropolarimetric properties and emission line variability seem to differ at
a lower mass, 3 M⊙. The latter has been linked to different accretion
mechanisms at work; magnetospheric accretion for the A-type objects and
another mechanism, possibly boundary layer accretion, for the B-type objects.
The differing IR and variability properties are related to different or
differently acting (dust-)disk dispersal mechanisms, which occurs at much
larger size scales than the accretion traced by hydrogen recombination line
emission.

Finally, the findings presented in this paper signal just the beginning in
unveiling the formation of intermediate mass stars using Gaia. Gaia presents
us with an excellent opportunity to search and identify new Herbig Ae/Be
stars, resulting in a well-selected and properly characterized sample. The
results presented here will assist greatly in identifying new Herbig Ae/Be
objects from the more than a billion stars with astrometric parameters in
Gaia. This is the subject of our follow-on study, the STARRY project.

###### Acknowledgements.

The STARRY project has received funding from the European Union’s Horizon 2020
research and innovation programme under MSCA ITN-EID grant agreement No
676036. This work has made use of data from the European Space Agency (ESA)
mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data
Processing and Analysis Consortium (DPAC,
https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has
been provided by national institutions, in particular the institutions
participating in the Gaia Multilateral Agreement. This research also made use
of Astropy, a community-developed core Python package for Astronomy (Astropy
Collaboration, 2013), the TOPCAT tool (Taylor, 2005) and the VizieR catalogue
access tool and the SIMBAD database, operated at CDS, Strasbourg, France. This
research was made possible through the use of the AAVSO Photometric All-Sky
Survey (APASS), funded by the Robert Martin Ayers Sciences Fund. We thank the
referee for his/her insightful comments which have improved the paper.

## References

  * Aarnio et al. (2017) Aarnio, A. N., Monnier, J. D., Harries, T. J., et al. 2017, ApJ, 848, 18
  * Ababakr et al. (2015) Ababakr, K. M., Fairlamb, J. R., Oudmaijer, R. D., & van den Ancker, M. E. 2015, MNRAS, 452, 2566
  * Ababakr et al. (2016) Ababakr, K. M., Oudmaijer, R. D., & Vink, J. S. 2016, MNRAS, 461, 3089
  * Ababakr et al. (2017) Ababakr, K. M., Oudmaijer, R. D., & Vink, J. S. 2017, MNRAS, 472, 854
  * Acke et al. (2005) Acke, B., van den Ancker, M. E. & Dullemond, C. P. 2005, A&A, 436, 209
  * Alecian et al. (2013) Alecian, E., Wade, G. A., Catala, C., et al. 2013, MNRAS, 429, 1001
  * Alonso-Albi et al. (2009) Alonso-Albi, T., Fuente, A., Bachiller, R., et al. 2009, A&A, 497, 117
  * van den Ancker et al. (1997) van den Ancker, M. E., The, P. S., Feinstein, A., et al. 1997, A&AS, 123, 63
  * van den Ancker et al. (1998) van den Ancker, M. E., de Winter, D., & Tjin A Djie, H. R. E. 1998, A&A, 330, 145
  * Arenou et al. (2018) Arenou, F., Luri, X., Babusiaux, C., et al. 2018, submitted to A&A.
  * Aspin (1998) Aspin, C. 1998, A&A, 335, 1040
  * Bailer-Jones et al. (2018) Bailer-Jones, C. A. L., Rybizki, J., Fouesneau, M., et al. 2018, submitted to ApJ.
  * Bailer-Jones (2015) Bailer-Jones, C. A. L. 2015, PASP, 127, 994
  * Baines et al. (2006) Baines, D., Oudmaijer, R. D., Porter, J. M., & Pozzo, M. 2006, MNRAS, 367, 737
  * Banzatti et al. (2018) Banzatti, A., Garufi, A., Kama, M., et al. 2018, A&A, 609, L2
  * Biller et al. (2012) Biller, B., Lacour, S., Juhász, A., et al. 2012, ApJ, 753, L38
  * Boehm & Catala (1995) Boehm, T., & Catala, C. 1995, A&A, 301, 155
  * Boersma et al. (2009) Boersma, C., Peeters, E., Martín-Hernández, N. L., et al. 2009, A&A, 502, 175
  * Borges Fernandes et al. (2007) Borges Fernandes, M., Kraus, M., Lorenz Martins, S., & de Araújo, F. X. 2007, MNRAS, 377, 1343
  * Bouvier et al. (2007) Bouvier, J., Alencar, S. H. P., Harries, T. J., Johns-Krull, C. M., & Romanova, M. M. 2007, Protostars and Planets V, 479
  * Bressan et al. (2012) Bressan, A., Marigo, P., Girardi, L., et al. 2012, MNRAS, 427, 127
  * Cardelli et al. (1989) Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1989, ApJ, 345, 245
  * Carmona et al. (2010) Carmona, A., van den Ancker, M. E., Audard, M., et al. 2010, A&A, 517, A67
  * Castelli & Kurucz (2004) Castelli, F., & Kurucz, R. L. 2004, arXiv:astro-ph/0405087
  * Cauley & Johns-Krull (2015) Cauley, P. W., & Johns-Krull, C. M. 2015, ApJ, 810, 5
  * Chelli et al. (1995) Chelli, A., Cruz-Gonzalez, I., & Reipurth, B. 1995, A&AS, 114, 135
  * Chen et al. (2016) Chen, P. S., Shan, H. G., & Zhang, P. 2016, New A, 44, 1
  * Clem & Landolt (2016) Clem, J. L., & Landolt, A. U. 2016, AJ, 152, 91
  * Connelley et al. (2008) Connelley, M. S., Reipurth, B. & Tokunaga, A. T. 2008, AJ, 135, 2496.
  * Corporon & Lagrange (1999) Corporon, P., & Lagrange, A.-M. 1999, A&AS, 136, 429
  * Costigan et al. (2014) Costigan, G., Vink, J. S., Scholz, A., Ray, T., & Testi, L. 2014, MNRAS, 440, 3444
  * Coulson & Walther (1995) Coulson, I. M., & Walther, D. M. 1995, MNRAS, 274, 977
  * Cote & Waters (1987) Coté, J., & Waters, L. B. F. M. 1987, A&A, 176, 93
  * Cutri et al. (2013) Cutri, R. M., Wright, E. L., Conrow, T., et al. 2013, Explanatory Supplement to the AllWISE Data Release Products, by R. M. Cutri et al. ,
  * Davies et al. (2007) Davies, B., Oudmaijer, R. D., & Sahu, K. C. 2007, ApJ, 671, 2059
  * Davies et al. (2011) Davies, B., Hoare, M. G., Lumsden, S. L., et al. 2011, MNRAS, 416, 972
  * Davies et al. (2018) Davies, C. L., Kreplin, A., Kluska, J., et al. 2018, MNRAS, 474, 5406
  * Deason et al. (2017) Deason, A. J., Belokurov, V., Erkal, D., Koposov, S. E., & Mackey, D. 2017, MNRAS, 467, 2636
  * Doering & Meixner (2009) Doering, R. L., & Meixner, M. 2009, AJ, 138, 780
  * Duchêne (2015) Duchêne, G. 2015, Ap&SS, 355, 291
  * Dullemond & Dominik (2004a) Dullemond, C. P., & Dominik, C. 2004a, A&A, 417, 159
  * Dullemond & Dominik (2004b) Dullemond, C. P., & Dominik, C. 2004b, A&A, 421, 1075
  * Dullemond & Dominik (2005) Dullemond, C. P., & Dominik, C. 2005, A&A, 434, 971
  * Dunhill et al. (2015) Dunhill, A. C., Cuadra, J., & Dougados, C. 2015, MNRAS, 448, 3545
  * Dunkin et al. (1997) Dunkin, S. K., Barlow, M. J., & Ryan, S. G. 1997, MNRAS, 290, 165
  * Eiroa et al. (2002) Eiroa, C., Oudmaijer, R. D., Davies, J. K., et al. 2002, A&A, 384, 1038
  * Evans et al. (2018) Evans, D. W., Riello, M., De Angeli, F., et al. 2018, ArXiv e-prints , arXiv:1804.09368
  * Fairlamb et al. (2015) Fairlamb, J. R., Oudmaijer, R. D., Mendigutía, I., Ilee, J. D., & van den Ancker, M. E. 2015, MNRAS, 453, 976
  * Fairlamb et al. (2017) Fairlamb, J. R., Oudmaijer, R. D., Mendigutia, I., Ilee, J. D., & van den Ancker, M. E. 2017, MNRAS, 464, 4721
  * Fang et al. (2013) Fang, M., Kim, J. S., van Boekel, R., et al. 2013, ApJS, 207, 5
  * Arellano Ferro & Giridhar (2003) Arellano Ferro, A., & Giridhar, S. 2003, A&A, 408, L29
  * Finkenzeller & Mundt (1984) Finkenzeller, U., & Mundt, R. 1984, A&AS, 55, 109
  * Folsom et al. (2008) Folsom, C. P., Wade, G. A., Kochukhov, O., et al. 2008, Contributions of the Astronomical Observatory Skalnate Pleso, 38, 245
  * Frasca et al. (2016) Frasca, A., Miroshnichenko, A. S., Rossi, C., et al. 2016, A&A, 585, A60
  * Friedemann et al. (1996) Friedemann, C., Guertler, J., & Loewe, M. 1996, A&AS, 117, 205
  * Fuente et al. (1998) Fuente, A., Martin-Pintado, J., Bachiller, R., Neri, R., & Palla, F. 1998, A&A, 334, 253
  * Gaia Collaboration et al. (2016) Gaia Collaboration, Prusti, T., de Bruijne, J. H. J., et al. 2016, A&A, 595, A1.
  * Gaia Collaboration et al. (2018) Gaia Collaboration, Babusiaux, C., van Leeuwen, F., et al. 2018, accepted for publication by A&A.
  * Gaia Collaboration et al. (2018b) Gaia Collaboration, Brown, A. G. A., Vallenari, A., et al. 2018, ArXiv e-prints , arXiv:1804.09365.
  * Gorti et al. (2009) Gorti, U., Dullemond, C. P., & Hollenbach, D. 2009, ApJ, 705, 1237
  * Grady et al. (2010) Grady, C. A., Hamaguchi, K., Schneider, G., et al. 2010, ApJ, 719, 1565
  * Gray & Corbally (2009) Gray, R. O., & Corbally, C., J. 2009, Stellar Spectral Classification by Richard O. Gray and Christopher J. Corbally. Princeton University Press, 2009. ISBN: 978-0-691-12511-4
  * Grinin & Rostopchina (1996) Grinin, V. P. & Rostopchina, A. N. 1996, Astronomy Reports, 40, 171
  * Grinin (2000) Grinin, V. P. 2000, Disks, Planetesimals, and Planets, 219, 216
  * Grundstrom & Gies (2006) Grundstrom, E. D., & Gies, D. R. 2006, ApJ, 651, L53
  * Gürtler et al. (1999) Gürtler, J., Friedemann, C., Reimann, H.-G., et al. 1999, Astronomy and Astrophysics Supplement Series, 140, 293
  * Hamaguchi et al. (2008) Hamaguchi, K., Choi, M., Corcoran, M. F., et al. 2008, ApJ, 687, 425-432
  * Herbig (1960) Herbig, G. H. 1960, ApJS, 4, 337
  * Herbig & Bell (1988) Herbig, G. H. & Bell, K. R. 1988, Third catalog of emission-line stars of the Orion population.
  * Hernández et al. (2004) Hernández, J., Calvet, N., Briceño, C., Hartmann, L., & Berlind, P. 2004, AJ, 127, 1682
  * Hernández et al. (2005) Hernández, J., Calvet, N., Hartmann, L., et al. 2005, AJ, 129, 856
  * Holl et al. (2018) Holl, B., Audard, M., Nienartowicz, K., et al. 2018, accepted for publication by A&A.
  * Honda et al. (2015) Honda, M., Maaskant, K., Okamoto, Y. K., et al. 2015, ApJ, 804, 143
  * Hou et al. (2016) Hou, W., Luo, A.-L., Hu, J.-Y., et al. 2016, Research in Astronomy and Astrophysics, 16, 138
  * Ilee et al. (2014) Ilee, J. D., Fairlamb, J., Oudmaijer, R. D., et al. 2014, MNRAS, 445, 3723
  * Joner & Hintz (2015) Joner, M. D., & Hintz, E. G. 2015, AJ, 150, 204
  * Klement et al. (2017) Klement, R., Carciofi, A. C., Rivinius, T., et al. 2017, A&A, 601, A74
  * Kraus et al. (2012) Kraus, S., Calvet, N., Hartmann, L., et al. 2012, ApJ, 746, L2
  * Kraus (2015) Kraus, S. 2015, Ap&SS, 357, 97
  * Kubát et al. (2010) Kubát, J., Saad, S. M., Kawka, A., et al. 2010, A&A, 520, A103
  * Kučerová et al. (2013) Kučerová, B., Korčáková, D., Polster, J., et al. 2013, A&A, 554, A143
  * Kurosawa et al. (2006) Kurosawa, R., Harries, T. J. & Symington, N. H. 2006, MNRAS, 370, 580
  * Kurosawa et al. (2008) Kurosawa, R., Romanova, M. M., & Harries, T. J. 2008, MNRAS, 385, 1931
  * Lazareff et al. (2017) Lazareff, B., Berger, J.-P., Kluska, J., et al. 2017, A&A, 599, A85
  * Landolt (2009) Landolt, A. U. 2009, AJ, 137, 4186
  * Lee et al. (2016) Lee, C.-D., Chen, W.-P. & Liu, S.-Y. 2016, A&A, 592, A130
  * Leinert et al. (1997) Leinert, C., Richichi, A., & Haas, M. 1997, A&A, 318, 472
  * Lindegren et al. (2018) Lindegren, L., Hernandez, J., Bombrun, A., et al. 2018, accepted for publication by A&A.
  * Liu et al. (2000) Liu, Q. Z., van Paradijs, J., & van den Heuvel, E. P. J. 2000, A&AS, 147, 25
  * Lumsden et al. (2013) Lumsden, S. L., Hoare, M. G., Urquhart, J. S., et al. 2013, ApJS, 208, 11
  * Luri et al. (2018) Luri, X., Brown, A. G. A., Sarro, L. M., et al. 2018, accepted for publication by A&A.
  * Maaskant et al. (2013) Maaskant, K. M., Honda, M., Waters, L. B. F. M., et al. 2013, A&A, 555, A64
  * Maheswar et al. (2002) Maheswar, G., Manoj, P., & Bhatt, H. C. 2002, A&A, 387, 1003
  * Malkov et al. (2006) Malkov, O. Y., Oblak, E., Snegireva, E. A., & Torra, J. 2006, A&A, 446, 785
  * Manoj et al. (2006) Manoj, P., Bhatt, H. C., Maheswar, G., & Muneer, S. 2006, ApJ, 653, 657
  * Marigo et al. (2017) Marigo, P., Girardi, L., Bressan, A., et al. 2017, ApJ, 835, 77
  * Marconi & Palla (1998) Marconi, M., & Palla, F. 1998, ApJ, 507, L141
  * Marston & McCollum (2008) Marston, A. P. & McCollum, B. 2008, A&A, 477, 193
  * Mayer et al. (2016) Mayer, A., Deschamps, R., & Jorissen, A. 2016, A&A, 587, A30
  * Meeus et al. (2001) Meeus, G., Waters, L. B. F. M., Bouwman, J., et al. 2001, A&A, 365, 476
  * Mendigutía et al. (2011a) Mendigutía, I., Eiroa, C., Montesinos, B., et al. 2011a, A&A, 529, A34
  * Mendigutía et al. (2011b) Mendigutía, I., Calvet, N., Montesinos, B., et al. 2011b, A&A, 535, A99
  * Mendigutía (2011c) Mendigutía, I. 2011c, Ph.D. thesis, Universidad Autónoma de Madrid
  * Mendigutía et al. (2012) Mendigutía, I., Mora, A., Montesinos, B., et al. 2012, A&A, 543, A59
  * Millour et al. (2009) Millour, F., Chesneau, O., Borges Fernandes, M., et al. 2009, A&A, 507, 317
  * Miroshnichenko et al. (1998) Miroshnichenko, A. S., Fremat, Y., Houziaux, L., et al. 1998, Astronomy and Astrophysics Supplement Series, 131, 469
  * Miroshnichenko et al. (1999) Miroshnichenko, A. S., Gray, R. O., Vieira, S. L. A., Kuratov, K. S., & Bergner, Y. K. 1999, A&A, 347, 137
  * Miroshnichenko et al. (2000) Miroshnichenko, A. S., Chentsov, E. L., Klochkova, V. G., et al. 2000, Astronomy and Astrophysics Supplement Series, 147, 5
  * Miroshnichenko et al. (2002) Miroshnichenko, A. S., Bjorkman, K. S., Chentsov, E. L., et al. 2002, A&A, 388, 563
  * Miroshnichenko et al. (2004) Miroshnichenko, A. S., Levato, H., Bjorkman, K. S., et al. 2004, A&A, 417, 731
  * Miroshnichenko et al. (2014) Miroshnichenko, A. S., Manset, N., Zharikov, S. V., et al. 2014, Advances in Astronomy, 2014, E7
  * Monnier et al. (2005) Monnier, J. D., Millan-Gabet, R., Billmeier, R., et al. 2005, ApJ, 624, 832
  * Montesinos et al. (2009) Montesinos, B., Eiroa, C., Mora, A., & Merín, B. 2009, A&A, 495, 901
  * Morrell & Levato (1991) Morrell, N., & Levato, H. 1991, ApJS, 75, 965
  * Mottram et al. (2007) Mottram, J. C., Vink, J. S., Oudmaijer, R. D., & Patel, M. 2007, MNRAS, 377, 1363
  * Nakano et al. (2012) Nakano, M., Sugitani, K., Watanabe, M., et al. 2012, AJ, 143, 61
  * Natta et al. (1997) Natta, A., Grinin, V. P., Mannings, V., & Ungerechts, H. 1997, ApJ, 491, 885
  * Natta & Whitney (2000) Natta, A., & Whitney, B. A. 2000, A&A, 364, 633
  * Oudmaijer & Drew (1997) Oudmaijer, R. D., & Drew, J. E. 1997, A&A, 318, 198
  * Oudmaijer et al. (1997) Oudmaijer, R. D., Busfield, G., & Drew, J. E. 1997, MNRAS, 291, 797
  * Oudmaijer, et al. (1998) Oudmaijer, R. D., Proga, D., Drew, J. E., et al. 1998, MNRAS, 300, 170
  * Oudmaijer & Drew (1999) Oudmaijer, R. D., & Drew, J. E. 1999, MNRAS, 305, 166
  * Oudmaijer et al. (2001) Oudmaijer, R. D., Palacios, J., Eiroa, C., et al. 2001, A&A, 379, 564
  * Oudmaijer (2017) Oudmaijer, R. D. 2017, The B[e] Phenomenon: Forty Years of Studies, 508, 175
  * Patel et al. (2017) Patel, P., Sigut, T. A. A., & Landstreet, J. D. 2017, ApJ, 836, 214
  * Pecaut & Mamajek (2013) Pecaut, M. J., & Mamajek, E. E. 2013, ApJS, 208, 9
  * Pogodin et al. (2012) Pogodin, M. A., Hubrig, S., Yudin, R. V., et al. 2012, Astronomische Nachrichten, 333, 594
  * Polster et al. (2012) Polster, J., Korčáková, D., Votruba, V., et al. 2012, A&A, 542, A57
  * Pomohaci et al. (2017) Pomohaci, R., Oudmaijer, R. D., Lumsden, S. L., Hoare, M. G., & Mendigutía, I. 2017, MNRAS, 472, 3624
  * Poxon (2015) Poxon, M. 2015, Journal of the American Association of Variable Star Observers (JAAVSO), 43, 35
  * Reiter et al. (2018) Reiter, M., Calvet, N., Thanathibodee, T., et al. 2018, ApJ, 852, 5
  * Rivinius et al. (2013) Rivinius, T., Carciofi, A. C., & Martayan, C. 2013, A&A Rev., 21, 69
  * Sartori et al. (2010) Sartori, M. J., Gregorio-Hetem, J., Rodrigues, C. V., Hetem, A., Jr., & Batalha, C. 2010, AJ, 139, 27-38
  * Schöller et al. (2016) Schöller, M., Pogodin, M. A., Cahuasquí, J. A., et al. 2016, A&A, 592, A50
  * Schütz et al. (2011) Schütz, O., Meeus, G., Carmona, A., Juhász, A., & Sterzik, M. F. 2011, A&A, 533, A54
  * Skrutskie et al. (2006) Skrutskie, M. F., Cutri, R. M., Stiening, R., et al. 2006, AJ, 131, 1163
  * Spezzi et al. (2008) Spezzi, L., Alcalá, J. M., Covino, E., et al. 2008, ApJ, 680, 1295
  * Tambovtseva et al. (2014) Tambovtseva, L. V., Grinin, V. P. & Weigelt, G. 2014, A&A, 562, A104
  * Taylor (2005) Taylor, M. B. 2005, Astronomical Data Analysis Software and Systems XIV, 347, 29
  * Testi et al. (1999) Testi, L., Palla, F., & Natta, A. 1999, A&A, 342, 515
  * The et al. (1994) Thé, P. S., de Winter, D., & Perez, M. R. 1994, A&AS, 104, 315
  * Torres et al. (2000) Torres, C. A. O., Quast, G. R., da Silva, L., & de La Reza, R. 2000, IAU Symposium, 200, 118
  * Vieira et al. (2003) Vieira, S. L. A., Corradi, W. J. B., Alencar, S. H. P., et al. 2003, AJ, 126, 2971
  * Vieira et al. (2011) Vieira, R. G., Gregorio-Hetem, J., Hetem, A., et al. 2011, A&A, 526, A24
  * Vink et al. (2002) Vink, J. S., Drew, J. E., Harries, T. J., & Oudmaijer, R. D. 2002, MNRAS, 337, 356
  * Waters et al. (1987) Waters, L. B. F. M., Cote, J., & Lamers, H. J. G. L. M. 1987, A&A, 185, 206
  * Watson et al. (2006) Watson, C. L., Henden, A. A., & Price, A. 2006, Society for Astronomical Sciences Annual Symposium, 25, 47
  * Wheelwright et al. (2010) Wheelwright, H. E., Oudmaijer, R. D., & Goodwin, S. P. 2010, MNRAS, 401, 1199
  * Wheelwright et al. (2011) Wheelwright, H. E., Vink, J. S., Oudmaijer, R. D., & Drew, J. E. 2011, A&A, 532, A28
  * Zhang et al. (2006) Zhang, P., Yang, H. T., & Liu, J. 2006, Ap&SS, 305, 11
  * Zhang et al. (2014) Zhang, Y., Tan, J. C., & Hosokawa, T. 2014, ApJ, 788, 166
  * Zhang et al. (2017) Zhang, Q., Claus, B., Watson, L., et al. 2017, ApJ, 837, 53
  * Zuckerman et al. (2008) Zuckerman, B., Melis, C., Song, I., et al. 2008, ApJ, 683, 1085

Table 2:  Main parameters of each Herbig Ae/Be star belonging to the high quality sample of 218 sources. Name | RA | DEC | Parallax | Distance | Teff | Log(L) | AV | V | Binary
---|---|---|---|---|---|---|---|---|---
| (h:m:s) | (deg:m:s) | (mas) | (pc) | (K) | ($L_{\odot}$) | (mag) | (mag) |
AB Aur | 04:55:45.9 | +30:33:04 | $6.140\pm{0.057}$ | $162.9^{+2.6}_{-2.4}$ | $9500^{+750}_{-790}$ | $1.61^{+0.19}_{-0.21}$ | $0.43^{+0.28}_{-0.35}$ | 7.32 | Yes1
AK Sco | 16:54:44.8 | -36:53:19 | $7.113\pm{0.062}$ | $140.6^{+2.1}_{-2.0}$ | $6250^{+250}_{-250}$ | $0.623^{+0.028}_{-0.005}$ | $0.000^{+0.050}_{-0.000}$ | 8.90 | Yes6
AS 310 | 18:33:21.2 | -04:58:06 | $0.390\pm{0.046}$ | $2110^{+350}_{-240}$ | $24500^{+4500}_{-5000}$ | $4.17^{+0.39}_{-0.44}$ | $4.13^{+0.26}_{-0.29}$ | 12.49 | -
AS 470 | 21:36:14.2 | +57:21:31 | $0.137\pm{0.027}$ | $4040^{+620}_{-440}$ | $8200^{+1600}_{-800}$ | $3.01^{+0.47}_{-0.27}$ | $2.27^{+0.62}_{-0.42}$ | 12.44 | -
AS 477 | 21:52:34.1 | +47:13:44 | $1.290\pm{0.029}$ | $773^{+30}_{-27}$ | $10000^{+1700}_{-500}$ | $2.22^{+0.36}_{-0.12}$ | $1.19^{+0.46}_{-0.12}$ | 10.05 | Yes4
BD+30 549 | 03:29:19.8 | +31:24:57 | $3.384\pm{0.083}$ | $295^{+13}_{-11}$ | $11500^{+1500}_{-800}$ | $1.54^{+0.25}_{-0.14}$ | $1.73^{+0.24}_{-0.12}$ | 10.51 | -
BD+41 3731 | 20:24:15.7 | +42:18:01 | $0.987\pm{0.035}$ | $1003^{+64}_{-53}$ | $17000^{+1000}_{-1000}$ | $2.96^{+0.31}_{-0.31}$ | $1.06^{+0.50}_{-0.50}$ | 9.90 | -
BF Ori | 05:37:13.3 | -06:35:01 | $2.570\pm{0.053}$ | $389^{+14}_{-12}$ | $8970^{+200}_{-200}$ | $1.287^{+0.060}_{-0.051}$ | $0.330^{+0.030}_{-0.020}$ | 9.82 | -
BH Cep | 22:01:42.9 | +69:44:36 | $2.984\pm{0.018}$ | $335.1^{+3.4}_{-3.3}$ | $6630^{+210}_{-300}$ | $0.76^{+0.10}_{-0.14}$ | $0.83^{+0.24}_{-0.35}$ | 11.23 | -
BO Cep | 22:16:54.1 | +70:03:45 | $2.670\pm{0.020}$ | $374.5^{+4.7}_{-4.5}$ | $6650^{+100}_{-100}$ | $0.467^{+0.088}_{-0.056}$ | $0.12^{+0.20}_{-0.12}$ | 11.52 | -
CO Ori | 05:27:38.3 | +11:25:39 | $2.474\pm{0.042}$ | $404^{+12}_{-11}$ | $6250^{+150}_{-80}$ | $1.50^{+0.10}_{-0.09}$ | $2.14^{+0.20}_{-0.19}$ | 11.13 | Yes4
CPM 25 | 06:23:56.3 | +14:30:28 | $0.293\pm{0.066}$ | $2130^{+470}_{-290}$ | $19500^{+5000}_{-3000}$ | $2.85^{+0.51}_{-0.39}$ | $3.83^{+0.29}_{-0.23}$ | 14.94 | -
CQ Tau | 05:35:58.5 | +24:44:54 | $6.131\pm{0.082}$ | $163.1^{+3.7}_{-3.5}$ | $6750^{+370}_{-200}$ | $0.87^{+0.18}_{-0.12}$ | $0.41^{+0.42}_{-0.28}$ | 8.98 | Yes5
DG Cir | 15:03:23.8 | -63:22:59 | $1.191\pm{0.042}$ | $833^{+52}_{-43}$ | $11000^{+3000}_{-3000}$ | $1.58^{+0.33}_{-0.45}$ | $3.94^{+0.13}_{-0.54}$ | 14.75 | -
GSC 1876-0892 | 06:07:15.4 | +29:57:55 | $0.154\pm{0.046}$ | $3000^{+580}_{-390}$ | $19500^{+5000}_{-3000}$ | $3.85^{+0.49}_{-0.38}$ | $4.64^{+0.29}_{-0.23}$ | 14.00 | -
GSC 3975-0579 | 21:38:08.5 | +57:26:48 | $1.055\pm{0.029}$ | $942^{+46}_{-39}$ | $8900^{+600}_{-380}$ | $1.53^{+0.23}_{-0.13}$ | $0.78^{+0.35}_{-0.17}$ | 11.59 | -
GSC 6546-3156 | 07:24:17.5 | -26:16:05 | $0.701\pm{0.023}$ | $1409^{+82}_{-68}$ | $9800^{+900}_{-300}$ | $1.38^{+0.26}_{-0.11}$ | $1.92^{+0.34}_{-0.12}$ | 14.13 | -
GSC 8143-1225 | 07:59:11.6 | -50:22:47 | $2.588\pm{0.021}$ | $386.3^{+5.3}_{-5.1}$ | $6750^{+250}_{-100}$ | $0.47^{+0.13}_{-0.09}$ | $0.89^{+0.29}_{-0.20}$ | 12.35 | -
GSC 8581-2002 | 08:44:23.6 | -59:56:58 | $1.792\pm{0.023}$ | $558^{+12}_{-11}$ | $9750^{+250}_{-250}$ | $1.243^{+0.055}_{-0.038}$ | $0.940^{+0.040}_{-0.000}$ | 11.48 | -
GSC 8645-1401 | 12:17:47.5 | -59:43:59 | $0.538\pm{0.030}$ | $1780^{+170}_{-130}$ | $7000^{+250}_{-250}$ | $2.17^{+0.18}_{-0.18}$ | $2.58^{+0.25}_{-0.29}$ | 13.08 | -
GSC 8994-3902 | 13:19:04.0 | -62:34:10 | $0.346\pm{0.037}$ | $2390^{+370}_{-250}$ | $19500^{+5000}_{-3000}$ | $3.70^{+0.46}_{-0.35}$ | $1.51^{+0.29}_{-0.23}$ | 10.73 | -
HBC 217 | 06:40:42.2 | +09:33:37 | $1.432\pm{0.040}$ | $696^{+35}_{-30}$ | $6250^{+150}_{-80}$ | $0.79^{+0.12}_{-0.06}$ | $0.06^{+0.20}_{-0.06}$ | 12.00 | -
HBC 222 | 06:40:51.2 | +09:44:46 | $1.411\pm{0.035}$ | $706^{+31}_{-27}$ | $6250^{+150}_{-80}$ | $0.82^{+0.12}_{-0.08}$ | $0.11^{+0.20}_{-0.11}$ | 12.01 | -
HBC 334 | 02:16:30.7 | +55:23:00 | $0.535\pm{0.032}$ | $1770^{+180}_{-140}$ | $16500^{+3000}_{-800}$ | $2.18^{+0.35}_{-0.19}$ | $2.37^{+0.23}_{-0.15}$ | 14.32 | -
HBC 442 | 05:34:14.2 | -05:36:54 | $2.592\pm{0.039}$ | $386^{+10}_{-9}$ | $6170^{+80}_{-160}$ | $0.983^{+0.093}_{-0.046}$ | $0.07^{+0.19}_{-0.07}$ | 10.27 | -
HBC 7 | 00:43:25.3 | +61:38:23 | $0.338\pm{0.019}$ | $2760^{+250}_{-190}$ | $19500^{+5000}_{-3000}$ | $3.87^{+0.42}_{-0.32}$ | $4.53^{+0.29}_{-0.23}$ | 13.65 | -
HBC 705 | 20:51:02.7 | +43:49:32 | $0.456\pm{0.027}$ | $2070^{+210}_{-160}$ | $19500^{+5000}_{-3000}$ | $3.71^{+0.42}_{-0.33}$ | $5.48^{+0.29}_{-0.23}$ | 14.37 | -
HD 100453 | 11:33:05.5 | -54:19:29 | $9.597\pm{0.039}$ | $104.20^{+0.70}_{-0.69}$ | $7250^{+250}_{-250}$ | $0.790^{+0.024}_{-0.003}$ | $0.000^{+0.050}_{-0.000}$ | 7.78 | Yes7
HD 100546 | 11:33:25.3 | -70:11:41 | $9.089\pm{0.051}$ | $110.0^{+1.0}_{-1.0}$ | $9750^{+500}_{-500}$ | $1.371^{+0.069}_{-0.046}$ | $0.000^{+0.050}_{-0.000}$ | 6.69 | -
HD 101412 | 11:39:44.4 | -60:10:28 | $2.431\pm{0.028}$ | $411.3^{+8.1}_{-7.6}$ | $9750^{+250}_{-250}$ | $1.581^{+0.049}_{-0.036}$ | $0.210^{+0.030}_{-0.000}$ | 9.24 | Yes5
HD 104237 | 12:00:04.9 | -78:11:35 | $9.226\pm{0.058}$ | $108.4^{+1.1}_{-1.1}$ | $8000^{+250}_{-250}$ | $1.329^{+0.035}_{-0.011}$ | $0.000^{+0.050}_{-0.000}$ | 6.52 | Yes8
HD 114981 | 13:14:40.7 | -38:39:06 | $1.405\pm{0.062}$ | $705^{+57}_{-44}$ | $16000^{+500}_{-500}$ | $3.24^{+0.12}_{-0.09}$ | $0.000^{+0.050}_{-0.000}$ | 7.23 | -
HD 130437 | 14:50:50.2 | -60:17:10 | $0.574\pm{0.036}$ | $1650^{+180}_{-130}$ | $24500^{+4500}_{-5000}$ | $4.31^{+0.34}_{-0.40}$ | $2.61^{+0.26}_{-0.29}$ | 10.05 | -
HD 132947 | 15:04:56.0 | -63:07:53 | $2.618\pm{0.057}$ | $382^{+15}_{-13}$ | $10250^{+250}_{-250}$ | $1.606^{+0.073}_{-0.050}$ | $0.000^{+0.050}_{-0.000}$ | 8.91 | -
HD 135344 | 15:15:48.9 | -37:08:56 | $7.036\pm{0.090}$ | $142.1^{+3.1}_{-2.9}$ | $6750^{+250}_{-250}$ | $1.119^{+0.015}_{-0.013}$ | $0.00$ | 7.65 | -
HD 135344B | 15:15:48.4 | -37:09:16 | $7.365\pm{0.077}$ | $135.8^{+2.4}_{-2.3}$ | $6380^{+120}_{-120}$ | $0.786^{+0.033}_{-0.035}$ | $0.230^{+0.050}_{-0.060}$ | 8.63 | Yes9
HD 139614 | 15:40:46.4 | -42:29:54 | $7.424\pm{0.053}$ | $134.7^{+1.6}_{-1.6}$ | $7750^{+250}_{-250}$ | $0.773^{+0.032}_{-0.010}$ | $0.000^{+0.050}_{-0.000}$ | 8.40 | -
HD 141569 | 15:49:57.7 | -03:55:17 | $9.039\pm{0.044}$ | $110.63^{+0.91}_{-0.88}$ | $9750^{+250}_{-250}$ | $1.216^{+0.032}_{-0.027}$ | $0.010^{+0.010}_{-0.000}$ | 7.10 | Yes4
HD 141926 | 15:54:21.8 | -55:19:44 | $0.717\pm{0.044}$ | $1340^{+150}_{-110}$ | $28000^{+1500}_{-1500}$ | $4.74^{+0.15}_{-0.14}$ | $2.400^{+0.030}_{-0.040}$ | 8.64 | Yes10
HD 142527 | 15:56:41.9 | -42:19:24 | $6.356\pm{0.047}$ | $157.3^{+2.0}_{-1.9}$ | $6500^{+250}_{-250}$ | $0.963^{+0.026}_{-0.005}$ | $0.000^{+0.050}_{-0.000}$ | 8.27 | Yes11
HD 142666 | 15:56:40.0 | -22:01:40 | $6.744\pm{0.053}$ | $148.3^{+2.0}_{-1.9}$ | $7500^{+250}_{-250}$ | $0.939^{+0.043}_{-0.045}$ | $0.500^{+0.080}_{-0.090}$ | 8.67 | -
HD 143006 | 15:58:36.9 | -22:57:16 | $6.02\pm{0.15}$ | $166.1^{+7.1}_{-6.2}$ | $5430^{+38}_{-80}$ | $0.46^{+0.09}_{-0.12}$ | $0.31^{+0.12}_{-0.25}$ | 10.10 | -
HD 144432 | 16:06:57.9 | -27:43:10 | $6.437\pm{0.058}$ | $155.4^{+2.4}_{-2.2}$ | $7500^{+250}_{-250}$ | $0.971^{+0.038}_{-0.011}$ | $0.000^{+0.060}_{-0.000}$ | 8.17 | Yes4
HD 149914 | 16:38:28.6 | -18:13:14 | $6.296\pm{0.080}$ | $158.8^{+3.5}_{-3.2}$ | $10250^{+850}_{-600}$ | $2.09^{+0.14}_{-0.12}$ | $0.95^{+0.14}_{-0.14}$ | 6.75 | -
HD 150193 | 16:40:17.9 | -23:53:45 | $6.632\pm{0.070}$ | $150.8^{+2.7}_{-2.5}$ | $9000^{+250}_{-250}$ | $1.367^{+0.039}_{-0.044}$ | $1.550^{+0.020}_{-0.040}$ | 8.80 | Yes4
HD 155448 | 17:12:58.8 | -32:14:34 | $1.024\pm{0.058}$ | $950^{+100}_{-70}$ | $10700^{+800}_{-900}$ | $2.74^{+0.20}_{-0.28}$ | $0.47^{+0.12}_{-0.34}$ | 8.64 | Yes12
HD 158643 | 17:31:25.0 | -23:57:46 | $8.15\pm{0.30}$ | $122.8^{+8.2}_{-6.7}$ | $9800^{+900}_{-300}$ | $2.22^{+0.26}_{-0.07}$ | $0.00^{+0.34}_{-0.00}$ | 4.81 | -
HD 163296 | 17:56:21.3 | -21:57:22 | $9.85\pm{0.11}$ | $101.5^{+2.0}_{-1.9}$ | $9250^{+250}_{-250}$ | $1.199^{+0.055}_{-0.032}$ | $0.000^{+0.050}_{-0.000}$ | 6.85 | -
HD 169142 | 18:24:29.8 | -29:46:50 | $8.775\pm{0.064}$ | $114.0^{+1.4}_{-1.3}$ | $10700^{+800}_{-900}$ | $1.31^{+0.12}_{-0.22}$ | $1.02^{+0.12}_{-0.34}$ | 8.16 | -
HD 17081 | 02:44:07.3 | -13:51:32 | $9.38\pm{0.37}$ | $106.7^{+7.9}_{-6.3}$ | $13000^{+1000}_{-1500}$ | $2.58^{+0.19}_{-0.17}$ | $0.00^{+0.14}_{-0.00}$ | 4.24 | -
HD 174571 | 18:50:47.2 | +08:42:10 | $0.879\pm{0.059}$ | $1100^{+130}_{-90}$ | $19500^{+5000}_{-3000}$ | $4.23^{+0.43}_{-0.34}$ | $2.50^{+0.29}_{-0.23}$ | 8.70 | -
HD 176386 | 19:01:38.9 | -36:53:27 | $6.281\pm{0.061}$ | $159.2^{+2.6}_{-2.5}$ | $10700^{+800}_{-900}$ | $1.58^{+0.12}_{-0.22}$ | $0.38^{+0.12}_{-0.34}$ | 7.56 | Yes13
HD 179218 | 19:11:11.3 | +15:47:15 | $3.759\pm{0.047}$ | $266.0^{+5.6}_{-5.2}$ | $9500^{+200}_{-200}$ | $2.05^{+0.09}_{-0.14}$ | $0.53^{+0.12}_{-0.26}$ | 7.38 | Yes2
HD 199603 | 20:58:41.8 | -14:29:00 | $11.20\pm{0.10}$ | $89.3^{+1.4}_{-1.3}$ | $7380^{+220}_{-130}$ | $1.391^{+0.036}_{-0.012}$ | $0.000^{+0.059}_{-0.000}$ | 5.96 | Yes14
HD 200775 | 21:01:36.9 | +68:09:48 | $2.771\pm{0.045}$ | $361^{+10}_{-9}$ | $16500^{+3000}_{-800}$ | $3.07^{+0.29}_{-0.14}$ | $1.05^{+0.23}_{-0.15}$ | 7.33 | Yes4
HD 235495 | 21:21:27.5 | +50:59:48 | $1.907\pm{0.032}$ | $524^{+15}_{-14}$ | $9800^{+900}_{-300}$ | $1.51^{+0.23}_{-0.08}$ | $0.09^{+0.34}_{-0.09}$ | 9.82 | -
HD 244314 | 05:30:19.0 | +11:20:20 | $2.313\pm{0.059}$ | $432^{+19}_{-17}$ | $8500^{+250}_{-250}$ | $1.153^{+0.058}_{-0.063}$ | $0.100^{+0.020}_{-0.050}$ | 10.10 | -
HD 244604 | 05:31:57.3 | +11:17:41 | $2.374\pm{0.062}$ | $421^{+19}_{-17}$ | $9000^{+250}_{-250}$ | $1.461^{+0.057}_{-0.066}$ | $0.140^{+0.000}_{-0.040}$ | 9.38 | -
HD 245185 | 05:35:09.6 | +10:01:51 | $2.32\pm{0.11}$ | $429^{+37}_{-29}$ | $10000^{+500}_{-500}$ | $1.29^{+0.13}_{-0.10}$ | $0.000^{+0.050}_{-0.000}$ | 9.91 | Yes2
HD 249879 | 05:58:55.8 | +16:39:57 | $1.476\pm{0.078}$ | $669^{+66}_{-49}$ | $11500^{+1500}_{-800}$ | $1.56^{+0.29}_{-0.18}$ | $0.20^{+0.24}_{-0.12}$ | 10.69 | -
HD 250550 | 06:02:00.0 | +16:30:57 | $1.401\pm{0.098}$ | $697^{+94}_{-64}$ | $11000^{+500}_{-500}$ | $1.94^{+0.17}_{-0.12}$ | $0.000^{+0.050}_{-0.000}$ | 9.54 | -
HD 259431 | 06:33:05.2 | +10:19:20 | $1.379\pm{0.047}$ | $721^{+44}_{-37}$ | $14000^{+2100}_{-2900}$ | $2.97^{+0.27}_{-0.40}$ | $1.11^{+0.21}_{-0.30}$ | 8.72 | Yes2
HD 287823 | 05:24:08.0 | +02:27:47 | $2.784\pm{0.053}$ | $359^{+12}_{-11}$ | $8380^{+120}_{-120}$ | $1.116^{+0.053}_{-0.031}$ | $0.000^{+0.050}_{-0.000}$ | 9.68 | Yes6
HD 288012 | 05:33:04.8 | +02:28:10 | $2.524\pm{0.056}$ | $396^{+15}_{-13}$ | $9800^{+900}_{-300}$ | $1.66^{+0.24}_{-0.10}$ | $0.57^{+0.34}_{-0.12}$ | 9.32 | -
HD 290380 | 05:23:31.0 | -01:04:24 | $2.821\pm{0.048}$ | $354^{+10}_{-9}$ | $6400^{+150}_{-150}$ | $0.84^{+0.13}_{-0.04}$ | $0.06^{+0.27}_{-0.06}$ | 10.40 | -
HD 290409 | 05:27:05.5 | +00:25:08 | $2.191\pm{0.082}$ | $455^{+31}_{-25}$ | $9750^{+500}_{-500}$ | $1.27^{+0.12}_{-0.09}$ | $0.000^{+0.050}_{-0.000}$ | 10.02 | Yes6
HD 290500 | 05:29:48.1 | -00:23:43 | $2.277\pm{0.068}$ | $438^{+24}_{-20}$ | $9500^{+500}_{-500}$ | $0.81^{+0.11}_{-0.08}$ | $0.000^{+0.050}_{-0.000}$ | 11.04 | -
HD 290764 | 05:38:05.3 | -01:15:22 | $2.510\pm{0.063}$ | $398^{+18}_{-15}$ | $7880^{+380}_{-380}$ | $1.178^{+0.093}_{-0.091}$ | $0.16^{+0.12}_{-0.14}$ | 9.88 | -
HD 290770 | 05:37:02.4 | -01:37:21 | $2.502\pm{0.074}$ | $399^{+21}_{-18}$ | $10500^{+250}_{-250}$ | $1.522^{+0.085}_{-0.060}$ | $0.000^{+0.050}_{-0.000}$ | 9.27 | -
HD 305298 | 10:33:05.0 | -60:19:51 | $0.134\pm{0.027}$ | $4040^{+630}_{-440}$ | $34000^{+1000}_{-1000}$ | $4.55^{+0.15}_{-0.14}$ | $1.300^{+0.000}_{-0.020}$ | 10.86 | -
HD 313571 | 18:01:07.2 | -22:15:04 | $0.616\pm{0.077}$ | $1400^{+280}_{-170}$ | $16500^{+3000}_{-800}$ | $3.47^{+0.42}_{-0.23}$ | $1.80^{+0.23}_{-0.15}$ | 10.01 | -
HD 31648 | 04:58:46.3 | +29:50:37 | $6.182\pm{0.076}$ | $161.8^{+3.4}_{-3.2}$ | $8250^{+200}_{-200}$ | $1.27^{+0.14}_{-0.05}$ | $0.06^{+0.28}_{-0.06}$ | 7.62 | -
HD 319896 | 17:31:05.9 | -35:08:29 | $0.716\pm{0.063}$ | $1300^{+200}_{-130}$ | $15750^{+750}_{-750}$ | $3.19^{+0.24}_{-0.21}$ | $2.38^{+0.15}_{-0.17}$ | 10.99 | -
HD 323771 | 17:34:04.6 | -39:23:41 | $0.908\pm{0.055}$ | $1070^{+120}_{-90}$ | $15000^{+800}_{-1000}$ | $2.51^{+0.20}_{-0.21}$ | $1.32^{+0.17}_{-0.16}$ | 11.11 | -
HD 34282 | 05:16:00.5 | -09:48:35 | $3.210\pm{0.047}$ | $311.5^{+7.9}_{-7.2}$ | $9500^{+250}_{-250}$ | $0.980^{+0.049}_{-0.039}$ | $0.010^{+0.020}_{-0.000}$ | 9.89 | Yes2
HD 344261 | 19:21:53.5 | +21:31:51 | $3.328\pm{0.036}$ | $300.5^{+5.6}_{-5.2}$ | $7000^{+120}_{-250}$ | $0.72^{+0.11}_{-0.13}$ | $0.39^{+0.25}_{-0.29}$ | 10.65 | -
HD 34700 | 05:19:41.4 | +05:38:43 | $2.805\pm{0.048}$ | $356^{+11}_{-10}$ | $5900^{+110}_{-100}$ | $1.36^{+0.10}_{-0.02}$ | $0.00^{+0.21}_{-0.00}$ | 9.09 | Yes15
HD 35187 | 05:24:01.2 | +24:57:37 | $6.13\pm{0.10}$ | $163.0^{+4.6}_{-4.2}$ | $9800^{+900}_{-300}$ | $1.45^{+0.30}_{-0.24}$ | $0.81^{+0.50}_{-0.50}$ | 8.17 | Yes4
HD 35929 | 05:27:42.8 | -08:19:39 | $2.580\pm{0.052}$ | $387^{+13}_{-12}$ | $7000^{+250}_{-250}$ | $1.789^{+0.046}_{-0.023}$ | $0.000^{+0.050}_{-0.000}$ | 8.12 | Yes2
HD 36112 | 05:30:27.5 | +25:19:57 | $6.240\pm{0.067}$ | $160.3^{+2.9}_{-2.8}$ | $7600^{+220}_{-300}$ | $1.04^{+0.12}_{-0.08}$ | $0.15^{+0.25}_{-0.15}$ | 8.27 | Yes5
HD 36408 | 05:32:14.1 | +17:03:29 | $2.288\pm{0.098}$ | $435^{+35}_{-27}$ | $11930^{+830}_{-830}$ | $3.13^{+0.18}_{-0.22}$ | $0.38^{+0.12}_{-0.24}$ | 6.09 | Yes16
HD 36917 | 05:34:47.0 | -05:34:15 | $2.103\pm{0.072}$ | $474^{+29}_{-24}$ | $11200^{+1100}_{-1300}$ | $2.43^{+0.24}_{-0.29}$ | $0.52^{+0.24}_{-0.34}$ | 8.03 | -
HD 36982 | 05:35:09.8 | -05:27:53 | $2.447\pm{0.064}$ | $408^{+19}_{-16}$ | $20000^{+1000}_{-1000}$ | $2.83^{+0.14}_{-0.15}$ | $0.82^{+0.12}_{-0.16}$ | 8.45 | -
HD 37258 | 05:36:59.3 | -06:09:16 | $2.751\pm{0.099}$ | $363^{+24}_{-19}$ | $9750^{+500}_{-500}$ | $1.24^{+0.12}_{-0.10}$ | $0.060^{+0.050}_{-0.040}$ | 9.67 | Yes5
HD 37357 | 05:37:47.1 | -06:42:30 | $1.27\pm{0.30}$ | $650^{+280}_{-120}$ | $9500^{+250}_{-250}$ | $2.04^{+0.35}_{-0.20}$ | $0.000^{+0.050}_{-0.000}$ | 8.84 | Yes2
HD 37371 | 05:38:09.9 | -00:11:01 | $2.428\pm{0.062}$ | $411^{+18}_{-16}$ | $10700^{+800}_{-900}$ | $2.45^{+0.15}_{-0.24}$ | $0.83^{+0.12}_{-0.34}$ | 7.90 | -
HD 37490 | 05:39:11.1 | +04:07:17 | $3.16\pm{0.36}$ | $312^{+80}_{-43}$ | $16500^{+3000}_{-800}$ | $3.69^{+0.46}_{-0.25}$ | $0.17^{+0.23}_{-0.15}$ | 4.59 | Yes17
HD 37806 | 05:41:02.3 | -02:43:01 | $2.335\pm{0.058}$ | $428^{+19}_{-16}$ | $10500^{+1000}_{-700}$ | $2.17^{+0.19}_{-0.14}$ | $0.13^{+0.19}_{-0.13}$ | 7.94 | Yes5
HD 38087 | 05:43:00.6 | -02:18:45 | $2.95\pm{0.10}$ | $338^{+22}_{-18}$ | $13600^{+2900}_{-800}$ | $2.19^{+0.30}_{-0.22}$ | $0.46^{+0.24}_{-0.18}$ | 8.38 | Yes18
HD 38120 | 05:43:11.9 | -04:59:50 | $2.463\pm{0.081}$ | $405^{+24}_{-20}$ | $10700^{+800}_{-900}$ | $1.72^{+0.31}_{-0.20}$ | $0.21^{+0.50}_{-0.21}$ | 9.07 | -
HD 39014 | 05:44:46.3 | -65:44:08 | $22.68\pm{0.30}$ | $44.1^{+1.0}_{-0.9}$ | $7830^{+160}_{-220}$ | $1.42^{+0.12}_{-0.02}$ | $0.00^{+0.25}_{-0.00}$ | 4.36 | -
HD 41511 | 06:04:59.1 | -16:29:04 | $4.50\pm{0.17}$ | $222^{+16}_{-13}$ | $8900^{+600}_{-380}$ | $2.83^{+0.24}_{-0.14}$ | $0.51^{+0.35}_{-0.17}$ | 4.93 | Yes19
HD 45677 | 06:28:17.4 | -13:03:11 | $1.603\pm{0.058}$ | $620^{+41}_{-33}$ | $16500^{+3000}_{-800}$ | $2.88^{+0.32}_{-0.17}$ | $0.57^{+0.23}_{-0.15}$ | 8.50 | Yes1
HD 46060 | 06:30:49.8 | -09:39:15 | $1.049\pm{0.058}$ | $930^{+100}_{-70}$ | $21000^{+3400}_{-4200}$ | $3.89^{+0.33}_{-0.38}$ | $1.79^{+0.25}_{-0.22}$ | 8.64 | -
HD 50083 | 06:51:45.8 | +05:05:04 | $0.897\pm{0.046}$ | $1090^{+100}_{-80}$ | $16500^{+3000}_{-800}$ | $4.04^{+0.34}_{-0.18}$ | $0.68^{+0.23}_{-0.15}$ | 6.91 | -
HD 50138 | 06:51:33.4 | -06:57:59 | $2.630\pm{0.064}$ | $380^{+16}_{-14}$ | $9450^{+450}_{-450}$ | $2.46^{+0.13}_{-0.09}$ | $0.03^{+0.12}_{-0.03}$ | 6.67 | Yes5
HD 56895B | 07:18:31.8 | -11:11:34 | $6.051\pm{0.049}$ | $165.3^{+2.2}_{-2.1}$ | $7000^{+250}_{-250}$ | $0.97^{+0.11}_{-0.04}$ | $0.08^{+0.25}_{-0.08}$ | 8.42 | -
HD 58647 | 07:25:56.1 | -14:10:44 | $3.139\pm{0.043}$ | $318.5^{+7.4}_{-6.8}$ | $10500^{+200}_{-200}$ | $2.44^{+0.11}_{-0.09}$ | $0.37^{+0.19}_{-0.12}$ | 6.85 | Yes1
HD 59319 | 07:28:36.8 | -21:57:49 | $1.489\pm{0.049}$ | $668^{+39}_{-33}$ | $12500^{+500}_{-500}$ | $2.51^{+0.11}_{-0.08}$ | $0.000^{+0.050}_{-0.000}$ | 8.31 | -
HD 68695 | 08:11:44.6 | -44:05:09 | $2.526\pm{0.037}$ | $396^{+10}_{-9}$ | $9250^{+250}_{-250}$ | $1.193^{+0.060}_{-0.036}$ | $0.000^{+0.050}_{-0.000}$ | 9.82 | -
HD 76534 | 08:55:08.7 | -43:28:00 | $1.089\pm{0.037}$ | $911^{+55}_{-46}$ | $19000^{+500}_{-500}$ | $3.549^{+0.087}_{-0.074}$ | $0.620^{+0.020}_{-0.010}$ | 8.07 | Yes4
HD 85567 | 09:50:28.5 | -60:58:03 | $0.971\pm{0.028}$ | $1023^{+53}_{-45}$ | $13000^{+500}_{-500}$ | $3.19^{+0.10}_{-0.08}$ | $0.890^{+0.030}_{-0.020}$ | 8.51 | Yes1
HD 87403 | 10:02:51.4 | -59:16:55 | $0.465\pm{0.043}$ | $1910^{+280}_{-190}$ | $10000^{+250}_{-250}$ | $2.84^{+0.16}_{-0.11}$ | $0.000^{+0.050}_{-0.000}$ | 9.26 | -
HD 87643 | 10:04:30.3 | -58:39:52 | $0.01\pm{0.12}$ | $2010^{+570}_{-350}$ | $19500^{+5000}_{-3000}$ | $4.60^{+0.64}_{-0.53}$ | $1.90^{+0.50}_{-0.50}$ | 8.51 | Yes30
HD 94509 | 10:53:27.2 | -58:25:24 | $0.511\pm{0.034}$ | $1830^{+210}_{-150}$ | $11500^{+1000}_{-1000}$ | $2.99^{+0.19}_{-0.15}$ | $0.000^{+0.050}_{-0.000}$ | 9.12 | -
HD 95881 | 11:01:57.6 | -71:30:48 | $0.844\pm{0.033}$ | $1168^{+82}_{-66}$ | $10000^{+250}_{-250}$ | $2.85^{+0.10}_{-0.07}$ | $0.000^{+0.050}_{-0.000}$ | 8.19 | -
HD 96042 | 11:03:40.5 | -59:25:59 | $0.217\pm{0.034}$ | $3100^{+510}_{-350}$ | $25500^{+1500}_{-1500}$ | $4.81^{+0.20}_{-0.17}$ | $0.780^{+0.030}_{-0.010}$ | 8.47 | -
HD 9672 | 01:34:37.9 | -15:40:35 | $17.52\pm{0.10}$ | $57.07^{+0.55}_{-0.53}$ | $8900^{+200}_{-200}$ | $1.174^{+0.093}_{-0.020}$ | $0.00^{+0.18}_{-0.00}$ | 5.61 | -
HD 97048 | 11:08:03.2 | -77:39:17 | $5.411\pm{0.039}$ | $184.8^{+2.2}_{-2.1}$ | $10500^{+500}_{-500}$ | $1.544^{+0.072}_{-0.060}$ | $0.900^{+0.050}_{-0.020}$ | 8.44 | -
HD 98922 | 11:22:31.7 | -53:22:11 | $1.448\pm{0.034}$ | $689^{+28}_{-25}$ | $10500^{+250}_{-250}$ | $3.032^{+0.059}_{-0.052}$ | $0.090^{+0.010}_{-0.000}$ | 6.77 | Yes1
HR 5999 | 16:08:34.3 | -39:06:19 | $6.207\pm{0.070}$ | $161.1^{+3.1}_{-2.9}$ | $8500^{+250}_{-250}$ | $1.717^{+0.048}_{-0.041}$ | $0.330^{+0.050}_{-0.040}$ | 6.78 | Yes3
HT CMa | 07:02:42.5 | -11:26:12 | $0.879\pm{0.036}$ | $1121^{+83}_{-66}$ | $10500^{+500}_{-500}$ | $1.47^{+0.12}_{-0.10}$ | $0.230^{+0.050}_{-0.020}$ | 11.87 | -
HU CMa | 07:04:06.7 | -11:26:08 | $0.834\pm{0.039}$ | $1170^{+100}_{-80}$ | $13000^{+250}_{-250}$ | $2.06^{+0.10}_{-0.08}$ | $0.800^{+0.020}_{-0.010}$ | 11.55 | -
Hen 3-1121 | 15:58:09.6 | -53:51:18 | $0.310\pm{0.098}$ | $1750^{+460}_{-280}$ | $26800^{+5100}_{-4800}$ | $3.9^{+1.3}_{-1.3}$ | $4.1^{+2.3}_{-2.3}$ | 13.00 | -
Hen 3-1121S | 15:58:09.7 | -53:51:35 | $0.55\pm{0.17}$ | $1150^{+390}_{-210}$ | $29000^{+3900}_{-4500}$ | $4.12^{+0.44}_{-0.43}$ | $3.48^{+0.18}_{-0.26}$ | 11.02 | -
Hen 3-1191 | 16:27:15.1 | -48:39:27 | $0.487\pm{0.069}$ | $1660^{+340}_{-210}$ | $29000^{+3900}_{-4500}$ | $3.49^{+0.34}_{-0.37}$ | $3.84^{+0.18}_{-0.26}$ | 13.76 | -
Hen 3-823 | 12:48:42.4 | -59:54:35 | $0.805\pm{0.068}$ | $1170^{+180}_{-120}$ | $16500^{+3000}_{-800}$ | $2.93^{+0.39}_{-0.21}$ | $1.18^{+0.23}_{-0.15}$ | 10.35 | -
Hen 3-847 | 13:01:17.8 | -48:53:19 | $1.03\pm{0.23}$ | $780^{+290}_{-140}$ | $14000^{+500}_{-500}$ | $2.07^{+0.32}_{-0.22}$ | $0.570^{+0.010}_{-0.030}$ | 10.61 | -
Hen 3-938 | 13:52:42.8 | -63:32:49 | $0.118\pm{0.032}$ | $3850^{+640}_{-450}$ | $32900^{+2000}_{-3900}$ | $5.03^{+0.25}_{-0.29}$ | $5.24^{+0.14}_{-0.18}$ | 13.40 | -
IL Cep | 22:53:15.6 | +62:08:45 | $1.238\pm{0.027}$ | $805^{+31}_{-27}$ | $16500^{+3000}_{-800}$ | $3.86^{+0.29}_{-0.15}$ | $3.16^{+0.23}_{-0.15}$ | 9.21 | Yes2
IP Per | 03:40:47.0 | +32:31:54 | $3.250\pm{0.078}$ | $308^{+13}_{-11}$ | $7990^{+340}_{-380}$ | $0.89^{+0.13}_{-0.18}$ | $0.52^{+0.22}_{-0.37}$ | 10.42 | -
KK Oph | 17:10:08.1 | -27:15:19 | $4.52\pm{0.14}$ | $221^{+12}_{-10}$ | $8500^{+500}_{-500}$ | $0.71^{+0.11}_{-0.11}$ | $2.70^{+0.10}_{-0.15}$ | 12.36 | Yes3
LKHa 260 | 18:19:09.4 | -13:50:41 | $0.771\pm{0.056}$ | $1230^{+160}_{-110}$ | $14000^{+1000}_{-1000}$ | $2.09^{+0.24}_{-0.23}$ | $3.20^{+0.16}_{-0.18}$ | 14.16 | -
LKHa 338 | 06:10:47.1 | -06:12:51 | $1.119\pm{0.044}$ | $885^{+63}_{-50}$ | $10700^{+800}_{-900}$ | $1.13^{+0.17}_{-0.26}$ | $2.60^{+0.12}_{-0.34}$ | 14.63 | -
LkHa 208 | 06:07:49.5 | +18:39:26 | $1.49\pm{0.20}$ | $630^{+170}_{-90}$ | $7830^{+500}_{-580}$ | $1.04^{+0.35}_{-0.28}$ | $0.36^{+0.34}_{-0.36}$ | 11.44 | Yes3
LkHa 215 | 06:32:41.8 | +10:09:34 | $1.395\pm{0.045}$ | $713^{+41}_{-34}$ | $14000^{+1000}_{-1000}$ | $2.57^{+0.18}_{-0.19}$ | $2.02^{+0.16}_{-0.18}$ | 10.60 | Yes2
LkHa 257 | 21:54:18.8 | +47:12:10 | $1.258\pm{0.016}$ | $794^{+18}_{-16}$ | $15000^{+800}_{-1000}$ | $1.91^{+0.13}_{-0.15}$ | $2.65^{+0.17}_{-0.16}$ | 13.29 | -
LkHa 259 | 23:58:41.6 | +66:26:13 | $1.319\pm{0.033}$ | $755^{+34}_{-29}$ | $7380^{+220}_{-130}$ | $1.16^{+0.09}_{-0.13}$ | $4.05^{+0.14}_{-0.24}$ | 15.20 | -
LkHa 324 | 21:03:54.2 | +50:15:10 | $1.651\pm{0.025}$ | $605^{+16}_{-14}$ | $11500^{+1500}_{-800}$ | $2.08^{+0.23}_{-0.13}$ | $3.64^{+0.24}_{-0.12}$ | 12.63 | -
LkHa 339 | 06:10:57.8 | -06:14:40 | $1.163\pm{0.026}$ | $857^{+33}_{-29}$ | $10500^{+250}_{-250}$ | $1.922^{+0.058}_{-0.055}$ | $3.540^{+0.010}_{-0.010}$ | 13.47 | -
MQ Cas | 00:09:37.6 | +58:13:11 | $1.217\pm{0.089}$ | $800^{+110}_{-80}$ | $9800^{+900}_{-300}$ | $1.10^{+0.32}_{-0.16}$ | $0.64^{+0.34}_{-0.12}$ | 12.31 | -
MWC 1021 | 20:29:26.9 | +41:40:44 | $0.507\pm{0.066}$ | $1640^{+320}_{-200}$ | $19800^{+9200}_{-9200}$ | $5.49^{+0.77}_{-0.87}$ | $8.89^{+0.60}_{-0.34}$ | 12.85 | -
MWC 1080 | 23:17:25.6 | +60:50:43 | $0.729\pm{0.092}$ | $1200^{+260}_{-150}$ | $29000^{+3900}_{-4500}$ | $4.52^{+0.37}_{-0.37}$ | $5.03^{+0.18}_{-0.26}$ | 11.61 | Yes1
MWC 137 | 06:18:45.5 | +15:16:52 | $0.110\pm{0.055}$ | $2910^{+600}_{-400}$ | $29000^{+3900}_{-4500}$ | $4.94^{+0.37}_{-0.38}$ | $4.63^{+0.18}_{-0.26}$ | 12.10 | -
MWC 297 | 18:27:39.5 | -03:49:52 | $2.663\pm{0.085}$ | $375^{+22}_{-18}$ | $24500^{+1500}_{-1500}$ | $4.59^{+0.12}_{-0.12}$ | $8.470^{+0.040}_{-0.030}$ | 12.03 | Yes2
MWC 342 | 20:23:03.6 | +39:29:50 | $0.536\pm{0.024}$ | $1810^{+140}_{-110}$ | $26000^{+5900}_{-4000}$ | $4.89^{+0.35}_{-0.34}$ | $4.25^{+0.23}_{-0.33}$ | 10.56 | -
MWC 593 | 17:49:10.2 | -24:14:21 | $0.682\pm{0.064}$ | $1340^{+220}_{-140}$ | $15750^{+750}_{-750}$ | $3.58^{+0.25}_{-0.21}$ | $2.31^{+0.15}_{-0.17}$ | 10.03 | -
MWC 655 | 22:38:31.8 | +55:50:05 | $0.424\pm{0.029}$ | $2170^{+250}_{-180}$ | $24500^{+4500}_{-5000}$ | $4.12^{+0.36}_{-0.40}$ | $0.94^{+0.26}_{-0.29}$ | 9.39 | -
MWC 657 | 22:42:41.8 | +60:24:01 | $0.265\pm{0.023}$ | $3160^{+400}_{-290}$ | $19800^{+9200}_{-9200}$ | $4.62^{+0.72}_{-0.83}$ | $5.03^{+0.60}_{-0.34}$ | 12.60 | Yes32
MWC 878 | 17:24:44.7 | -38:43:51 | $0.486\pm{0.053}$ | $1770^{+300}_{-200}$ | $24500^{+4500}_{-5000}$ | $4.32^{+0.38}_{-0.44}$ | $3.06^{+0.26}_{-0.29}$ | 10.62 | -
MWC 953 | 18:43:28.4 | -03:46:17 | $0.493\pm{0.058}$ | $1720^{+310}_{-200}$ | $19500^{+5000}_{-3000}$ | $4.21^{+0.48}_{-0.37}$ | $3.62^{+0.29}_{-0.23}$ | 10.84 | -
NSV 2968 | 06:26:53.9 | -10:15:35 | $0.942\pm{0.062}$ | $1030^{+120}_{-90}$ | $29000^{+3900}_{-4500}$ | $3.62^{+0.28}_{-0.33}$ | $5.88^{+0.18}_{-0.26}$ | 14.43 | -
NV Ori | 05:35:31.4 | -05:33:09 | $2.585\pm{0.057}$ | $387^{+15}_{-13}$ | $6750^{+250}_{-200}$ | $1.19^{+0.15}_{-0.08}$ | $0.13^{+0.29}_{-0.13}$ | 9.78 | -
PDS 002 | 01:17:43.5 | -52:33:31 | $2.411\pm{0.027}$ | $414.6^{+7.8}_{-7.3}$ | $6750^{+250}_{-100}$ | $0.79^{+0.12}_{-0.01}$ | $0.00^{+0.26}_{-0.00}$ | 10.81 | -
PDS 004 | 03:39:00.6 | +29:41:46 | $2.505\pm{0.050}$ | $399^{+14}_{-12}$ | $9800^{+900}_{-300}$ | $1.28^{+0.24}_{-0.10}$ | $0.91^{+0.34}_{-0.12}$ | 10.63 | -
PDS 021 | 06:02:14.9 | -10:00:59 | $1.119\pm{0.037}$ | $887^{+53}_{-44}$ | $15000^{+1500}_{-1500}$ | $2.58^{+0.18}_{-0.16}$ | $1.170^{+0.060}_{-0.040}$ | 10.38 | -
PDS 022 | 06:03:37.1 | -14:53:03 | $1.11\pm{0.10}$ | $850^{+140}_{-90}$ | $9800^{+900}_{-300}$ | $1.82^{+0.34}_{-0.17}$ | $0.20^{+0.34}_{-0.12}$ | 10.23 | -
PDS 025 | 06:54:27.9 | -25:02:16 | $1.308\pm{0.019}$ | $763^{+19}_{-18}$ | $8150^{+180}_{-160}$ | $0.60^{+0.10}_{-0.09}$ | $1.44^{+0.19}_{-0.16}$ | 14.03 | -
PDS 123 | 05:50:54.8 | +20:14:48 | $0.649\pm{0.035}$ | $1490^{+140}_{-110}$ | $19800^{+9200}_{-9200}$ | $2.80^{+0.69}_{-0.82}$ | $2.64^{+0.60}_{-0.34}$ | 13.11 | -
PDS 124 | 06:06:58.5 | -05:55:07 | $1.160\pm{0.048}$ | $853^{+64}_{-51}$ | $10250^{+250}_{-250}$ | $1.38^{+0.10}_{-0.07}$ | $1.230^{+0.030}_{-0.000}$ | 12.44 | -
PDS 126 | 06:13:37.3 | -06:25:02 | $1.173\pm{0.040}$ | $847^{+51}_{-42}$ | $7830^{+160}_{-220}$ | $1.37^{+0.15}_{-0.14}$ | $0.90^{+0.25}_{-0.25}$ | 11.78 | -
PDS 129 | 06:31:03.6 | +10:01:13 | $1.447\pm{0.069}$ | $684^{+60}_{-46}$ | $6550^{+100}_{-150}$ | $0.96^{+0.15}_{-0.16}$ | $0.67^{+0.20}_{-0.27}$ | 12.15 | -
PDS 130 | 06:49:58.6 | -07:38:52 | $0.754\pm{0.020}$ | $1316^{+62}_{-53}$ | $10500^{+250}_{-250}$ | $1.734^{+0.064}_{-0.057}$ | $2.070^{+0.010}_{-0.000}$ | 13.40 | -
PDS 133 | 07:25:05.0 | -25:45:50 | $0.668\pm{0.024}$ | $1475^{+92}_{-76}$ | $14000^{+2000}_{-2000}$ | $1.95^{+0.23}_{-0.24}$ | $1.43^{+0.09}_{-0.10}$ | 13.13 | -
PDS 134 | 07:32:26.6 | -21:55:36 | $0.328\pm{0.033}$ | $2550^{+370}_{-260}$ | $14000^{+500}_{-500}$ | $2.72^{+0.17}_{-0.13}$ | $1.220^{+0.030}_{-0.020}$ | 12.20 | -
PDS 138 | 11:53:13.2 | -62:05:21 | $0.043\pm{0.029}$ | $4630^{+750}_{-540}$ | $29000^{+3900}_{-4500}$ | $5.14^{+0.31}_{-0.36}$ | $5.29^{+0.18}_{-0.26}$ | 13.31 | -
PDS 174 | 05:06:55.5 | -03:21:13 | $2.514\pm{0.035}$ | $398^{+10}_{-9}$ | $17000^{+2000}_{-2000}$ | $1.96^{+0.16}_{-0.18}$ | $3.510^{+0.070}_{-0.070}$ | 12.84 | -
PDS 211 | 06:10:17.3 | +29:25:17 | $0.922\pm{0.031}$ | $1074^{+65}_{-54}$ | $10700^{+800}_{-900}$ | $1.79^{+0.16}_{-0.25}$ | $2.99^{+0.12}_{-0.34}$ | 13.79 | -
PDS 24 | 06:48:41.7 | -16:48:06 | $0.881\pm{0.019}$ | $1130^{+42}_{-37}$ | $10500^{+500}_{-500}$ | $1.274^{+0.088}_{-0.082}$ | $1.110^{+0.040}_{-0.030}$ | 13.26 | -
PDS 241 | 07:08:38.8 | -04:19:05 | $0.118\pm{0.054}$ | $2890^{+600}_{-400}$ | $26000^{+1500}_{-1500}$ | $4.05^{+0.27}_{-0.19}$ | $2.600^{+0.040}_{-0.010}$ | 12.06 | -
PDS 27 | 07:19:35.9 | -17:39:18 | $0.275\pm{0.044}$ | $2550^{+460}_{-310}$ | $17500^{+3500}_{-3500}$ | $4.15^{+0.37}_{-0.39}$ | $5.03^{+0.13}_{-0.13}$ | 13.00 | -
PDS 277 | 08:23:11.8 | -39:07:01 | $2.891\pm{0.036}$ | $345.8^{+7.3}_{-6.8}$ | $6750^{+250}_{-100}$ | $0.948^{+0.074}_{-0.016}$ | $0.00^{+0.15}_{-0.00}$ | 10.02 | -
PDS 286 | 09:06:00.0 | -47:18:58 | $0.515\pm{0.034}$ | $1820^{+210}_{-150}$ | $30000^{+3000}_{-3000}$ | $5.21^{+0.20}_{-0.18}$ | $6.270^{+0.050}_{-0.040}$ | 12.15 | -
PDS 290 | 09:26:11.1 | -52:42:27 | $1.146\pm{0.027}$ | $869^{+36}_{-31}$ | $13000^{+1000}_{-1500}$ | $1.60^{+0.18}_{-0.24}$ | $3.31^{+0.18}_{-0.24}$ | 14.55 | -
PDS 297 | 09:42:40.3 | -56:15:34 | $0.610\pm{0.031}$ | $1590^{+140}_{-110}$ | $10750^{+250}_{-250}$ | $2.12^{+0.14}_{-0.16}$ | $1.21^{+0.12}_{-0.19}$ | 12.02 | -
PDS 324 | 10:57:24.2 | -62:53:13 | $0.307\pm{0.023}$ | $2880^{+330}_{-240}$ | $24500^{+4500}_{-5000}$ | $3.43^{+0.35}_{-0.42}$ | $3.57^{+0.26}_{-0.29}$ | 14.45 | -
PDS 33 | 08:48:45.7 | -40:48:21 | $1.046\pm{0.027}$ | $951^{+43}_{-37}$ | $9750^{+250}_{-250}$ | $1.193^{+0.075}_{-0.054}$ | $0.520^{+0.040}_{-0.000}$ | 12.34 | -
PDS 34 | 08:49:58.5 | -45:53:06 | $0.457\pm{0.017}$ | $2130^{+140}_{-110}$ | $19500^{+5000}_{-3000}$ | $2.87^{+0.39}_{-0.31}$ | $2.96^{+0.29}_{-0.23}$ | 14.04 | -
PDS 344 | 11:40:32.8 | -64:32:06 | $0.395\pm{0.016}$ | $2440^{+170}_{-140}$ | $15250^{+500}_{-500}$ | $2.24^{+0.09}_{-0.10}$ | $0.860^{+0.010}_{-0.020}$ | 13.15 | -
PDS 361S | 13:03:21.5 | -62:13:26 | $0.266\pm{0.030}$ | $2950^{+430}_{-300}$ | $18500^{+1000}_{-1000}$ | $2.87^{+0.37}_{-0.35}$ | $1.20^{+0.50}_{-0.50}$ | 12.85 | Yes27
PDS 37 | 10:10:00.3 | -57:02:07 | $0.416\pm{0.056}$ | $1930^{+360}_{-230}$ | $17500^{+3500}_{-3500}$ | $4.00^{+0.37}_{-0.39}$ | $5.81^{+0.13}_{-0.13}$ | 13.54 | -
PDS 389 | 15:14:47.0 | -62:17:00 | $1.238\pm{0.033}$ | $804^{+38}_{-32}$ | $8520^{+380}_{-180}$ | $1.95^{+0.13}_{-0.15}$ | $4.84^{+0.17}_{-0.28}$ | 14.18 | -
PDS 415N | 16:18:37.2 | -24:05:18 | $6.93\pm{0.13}$ | $144.2^{+4.7}_{-4.2}$ | $6250^{+250}_{-250}$ | $0.44^{+0.16}_{-0.12}$ | $1.48^{+0.35}_{-0.25}$ | 10.88 | -
PDS 431 | 16:54:59.2 | -43:21:50 | $0.531\pm{0.027}$ | $1810^{+160}_{-120}$ | $10500^{+500}_{-500}$ | $1.88^{+0.12}_{-0.11}$ | $1.760^{+0.030}_{-0.030}$ | 13.42 | -
PDS 469 | 17:50:58.1 | -14:16:12 | $0.864\pm{0.083}$ | $1080^{+190}_{-120}$ | $9800^{+900}_{-300}$ | $1.60^{+0.35}_{-0.17}$ | $1.73^{+0.34}_{-0.12}$ | 12.80 | -
PDS 477 | 18:00:30.3 | -16:47:26 | $-0.19\pm{0.10}$ | $2470^{+640}_{-410}$ | $24500^{+4500}_{-5000}$ | $3.61^{+0.46}_{-0.50}$ | $4.28^{+0.26}_{-0.29}$ | 14.38 | -