# HST Low Resolution Stellar Library

Tathagata Pal Washington State University
1245 Webster Hall
Pullman, WA 99163, USA  Islam Khan Washington State University
1245 Webster Hall
Pullman, WA 99163, USA  Haverford College
370 Lancaster Ave
Haverford, PA 19041, USA  Guy Worthey Washington State University
1245 Webster Hall
Pullman, WA 99163, USA  Michael D. Gregg University of California, Davis
517 Physics Building
Davis, CA 95616, USA  David R. Silva The University of Texas at San Antonio
College of Sciences, Dean’s Office, Suite 3.205
One UTSA Circle San Antonio, TX 78249

###### Abstract

In order to provide fundamental stellar spectra that extend into the UV,
Hubble Space Telescope’s (HST) Space Telescope Imaging Spectrograph (STIS)
targeted 556 stars via proposals GO9088, GO9786, GO10222, and GO13776.
Exposures through three low resolution gratings provide wavelength coverage
from 0.2 $<\lambda<$ 1 $\mu$m at $\lambda/\Delta\lambda\sim$ 1000\. The UV
grating (G230LB) scatters red light that results in unwanted signal,
especially in cool stars. We applied scattered light corrections and flux
corrections arising from pointing errors relative to the center of the
0$\farcs$2 slit based on Worthey et al. (2022a). We present 513 fully reduced
stellar spectra, fluxed, dereddened, and cross-correlated to zero velocity.
Because of the broad spectral range, we can simultaneously study H$\alpha$ and
Mg II $\lambda$2800, indicators of chromospheric activity. Their behaviors are
decoupled. Besides three cool dwarfs and one giant with mild flares in
H$\alpha$, only Be stars show strong H$\alpha$ emission. Mg2800 emission,
however, strongly anti-correlates with temperature such that warm stars show
absorption and stars cooler than 5000 K universally show chromospheric
emission regardless of dwarf/giant status or metallicity. Transformed to
Mg2800 flux emerging from the stellar surface, we find a correlation with
temperature with approximately symmetric astrophysical scatter. Previous work
had indicated a basal level with asymmetric scatter to strong values. The
discrepancy is primarily due to our improved treatment of extinction. We
confirm statistically significant time variability in Mg2800 strength for one
star.

Galaxy: stellar content — stars: abundances — stars: chromospheres — stars:
flare — stars: fundamental parameters — ultraviolet: stars

##  1 Introduction

Stellar libraries are important tools used in far-flung corners of astronomy
and astrophysics. They contain stellar spectra of a number of pre-selected
stars in different wavelength regimes (UV, visible, NIR), a variety of
spectral resolutions, and with varied attention to flux calibration. Examples
include a library of stellar spectra by Jacoby et al. (1984), XSHOOTER (Verro
et al., 2022a), MILES (Sánchez-Blázquez et al., 2006), Indo-US (Valdes et al.,
2004), IRTF (Cesetti et al., 2013), ELODIE (Soubiran et al., 1998; Prugniel et
al., 2007), Lick (Worthey et al., 1994, 2014), and UVES-POP (Bagnulo et al.,
2003) libraries. Such libraries are often incorporated into stellar population
synthesis models. For example, the MILES library (Sánchez-Blázquez et al.,
2006) was used to compute simple stellar population (SSP) SEDs in the optical
wavelength range with comprehensive metallicity coverage (Vazdekis et al.,
2010; Falcón-Barroso et al., 2011). There are many other examples, such as
Bruzual & Charlot (2003); Verro et al. (2022b); Le Borgne et al. (2004);
Vazdekis et al. (2012); Worthey et al. (2022b). On a star by star basis,
libraries can be used to infer stellar parameters like $T_{\rm eff}$,
$\mathrm{log}\,g$, and [Fe/H] (e.g., Wu et al., 2011). Stellar libraries also
find application in study of stellar clusters (Alloin, 1996; Deng & Xin,
2010). One notable example is the BaSeL 3.1 stellar SED library (Lejeune et
al., 1997, 1998; Westera & Buser, 2003). This library is suitable for study of
clusters at low metallicities, and has been exploited for the study of
globular clusters (Bruzual A et al., 1997; Weiss & Salaris, 1999; Kurth et
al., 1999), open clusters (Pols et al., 1998; Lastennet et al., 1999), and
blue stragglers (Deng et al., 1999). When well flux-calibrated, stellar
libraries are also very important for characterization and performance
evaluation of observational missions like Gaia (Sudzius & Vansevicius, 2002;
Lastennet et al., 2002). Several stellar libraries are built into the exposure
time calculators for HST and JWST. They even find use in educational products
such as the University of Gettysburg’s CLEA and VIREO or New Mexico State
University’s GEAS laboratory software packages to illustrate the trends among
stellar spectra.

Spectral resolution and wavelength coverage vary among the various existing
libraries (c.f. Table 1 of Verro et al., 2022a), but none of them extend
shortward of 300 nm into the ultraviolet (UV) regime except those of Wu et al.
(1983) and Fanelli et al. (1990), who present 172 and 218 stellar spectra,
respectively, observed by the International Ultraviolet Explorer (IUE). An
important motivation for the present HST-based library is to relieve the
relative scarcity of spectral data in the UV.

Study of integrated spectra in the UV allows us access to the hottest stars,
which are main sequence turnoff stars with some blue straggler (BS)
contribution. For older stellar populations, UV bright populations include
blue horizontal branch (BHB) and post-asymptotic giant branch (PAGB) stars
(Koleva & Vazdekis, 2012). An important goal is to isolate the various main
sequences to chart the star formation history (SFH) of the galaxy (Vazdekis et
al., 2016). The $d\>\\!{\rm log\,age}$/$d\>\\!\mathrm{log}\,Z=-$3/2
age/metallicity degeneracy (Worthey, 1994) becomes more like $\approx-1/1$ in
the UV. In UV, we have an abundance of strong absorption features that help
constrain SFH, metallicity, and abundance ratios better (Serven et al., 2010;
Toloba et al., 2009; Ponder et al., 1998; Chavez et al., 2007). Needless to
say, if we want to extend the limit on redshift ($z$) for stellar population
studies, the UV regime is of utmost importance (Pettini et al., 2000; Daddi et
al., 2005; van Dokkum & Brammer, 2010).

Wu et al. (1983) and Fanelli et al. (1992) gave the first large, systematic
spectral library in UV using data from IUE. The library contained spectra of
around 218 stars with a spectral resolution of 7Å. Hubble Space Telescope’s
(HST’s) Space Telescope Imaging Spectrograph (STIS) improves upon IUE in both
flux calibration and spectral resolution. Forty O, PAGB, and He-burning stars
were observed with STIS to make a hot star spectral library (Khan & Worthey,
2018a). Made by stitching together spectra from three different gratings,
these spectra have wavelength coverage from $\sim$ 2000Å to $\sim$ 10000Å with
a resolution of $R\approx\lambda/\Delta\lambda\sim$ 1000\. The hot star
library was modeled after an earlier effort called the Next Generation
Spectral Library (NGSL, Gregg et al. (2006)) which has not so far been
completely described in the literature. The NGSL covers a wide range of
stellar parameters, including metallicity (Heap & Lindler, 2010; Koleva &
Vazdekis, 2012; Vazdekis et al., 2016). The original proposal was to obtain
spectra of close to 600 stars via “snapshot” style programs (GO9088, GO9786,
GO10222, and GO13776) in which single orbits left stranded between larger
programs are exploited for short observations. Spectra of more than half of
the stars that were observed (around 374 stars corresponding to proposals
GO9088, GO9786, and GO10222) were reduced and made publicly available by Heap
& Lindler (2009). The main intent of this paper is to provide a reduction of
the full library to the community. The spectral quality is improved by
applying additional corrections such as scattered light, slit off-center, and
dust corrections.

We also investigate the Mg II $\lambda 2800$ feature, which is a pair of
resonance lines designated by $h$ and $k$. Boehm-Vitense (1981) used high-
resolution IUE spectra on F stars to chart four origins for Mg2800 profile
morphology: the main, broad stellar absorption feature, a narrower
chromospheric emission core, a rare, even narrower self-absorption, and
interstellar absorption. Fanelli et al. (1990) also noted that, when in
emission, it probably indicates a chromospheric origin. Linsky & Ayres (1978)
argue that most of the Ca II emission ($\lambda\lambda$3933, 3968) arises in
the lower chromosphere, Mg II in the middle chromosphere, and Ly$\alpha$ in
the upper chromosphere, and that, together, these resonance features provide
the bulk of the radiative cooling that occurs in the layers exterior to the
photosphere.

The dynamo action brought about by differential stellar rotation is one of the
most commonly accepted mechanisms for magnetic field generations in main
sequence stars (Hartmann & Noyes, 1987; Fröhlich et al., 2012; Quentin & Tout,
2018). Chromospheric activity is generally associated with strong magnetic
fields (Musielak & Bielicz, 1982; Brown et al., 2022). Since stellar rotation
is expected to slow down over the lifetime of a star, activity can be presumed
to decrease (Barry, 1988). This leads to the possibility that chromospheric
activity indicators (CaII, MgII, or H$\alpha$) may provide relatively precise
chronometric information, at least in predefined spectral type bands (Barry,
1988). Although, in general ages would be poorly constrained (Pace, 2013). In
addition, acoustic shocks without a magnetohydrodynamic component may also
contribute to the chromospheric activity (Buchholz et al., 1998; Martínez et
al., 2011; Pérez Martínez et al., 2014).

Connections between Mg2800 strengths and the astrophysics of stellar
properties are still tenuous, but could eventually lead to realistic
chromosphere models as a function of stellar type and magnetic field strength.
In the meantime, we have various empirical clues. Houdebine & Stempels (1997)
finds that, at spectral type M1, metal-deficient stars are also activity-
deficient. Smith et al. (1991) compares Mg2800 with the Ca II S index (Vaughan
& Preston, 1980) which measures the width of the emission rather than its
strength. They also find that the available sample of 20 FGK stars can be
separated into “high activity” and “low activity” groups at an approximately
4:16 ratio, but that Mg2800 displays a large range of values even amongst the
low activity group (Martínez et al., 2011; Pérez Martínez et al., 2014).
Interstellar absorption usually dominates in OB stars (Khan & Worthey, 2018b).
Due to its wide coverage of parameter spaces, the present library can confirm
or extend these trends.

This paper is organized as follows. We describe the observations and sample in
$\S$2. The data reduction process is detailed in $\S$3, and additional
corrections that affect the continuum shape in $\S$4. The format of the data
catalog is described in $\S$5. In $\S$6, we investigate the Mg II 2800 feature
and chart the systematics of chromospheric activity across the H-R diagram. We
conclude in $\S$7 with a summary of the results and a discussion of their
implications.

##  2 Observations and Sample

The stars in the library were selected to cover $T\rm_{eff}$-$L$-$Z$ space
insofar as the Galaxy could provide them. For example, given that the metal-
poor components of the Milky Way are also ancient in age, no luminous, low-
metallicity stars exist. The parameter coverage is shown in Fig. 1 in
$\mathrm{log}\,g$-$\mathrm{log}\,T_{\rm eff}$ space with metallicity indicated
by symbol type. Fig. 2 on the other hand shows the distribution of all the
stars in different metallicity bins. The impact of including stars from
GO13776 significantly improves coverage of $T_{\rm eff}$-$L$-$Z$ space, as
shown in Figs. 1 and 2. Several A-type field horizontal branch stars were
observed to attempt to fill in the warm-and-metal-poor gap. Desirable faint
stars, such as individual Small Magellanic Cloud stars, could not be observed
due to the one-orbit limit on exposure time. The target list is hand-selected,
and should not be used for any statistical inferences. In addition, HST’s SNAP
mode selects from a larger input list according to schedulability, leading to
further randomization.

Figure 1: NGSL stars are plotted in $\mathrm{log}\,T_{\rm eff}$,
$\mathrm{log}\,g$ space. The previously published stars from proposals GO9088,
GO9786, and GO10222 (Koleva & Vazdekis, 2012, pluses) and the GO13776 stars
(circles) are split by metallicity, metal poor (MP): [Fe/H] $\leq$ $-$1 (red)
or metal rich (MR): [Fe/H] $>$ $-$1 (blue). An approximate Eddington stability
line and spectral type boundaries are included in the plot as visual guides.
Figure 2: The [Fe/H] distribution of all reduced targets in a stacked
histogram. Blue corresponds to 345 targets from Koleva & Vazdekis (2012) and
red corresponds to 169 targets from HST proposal GO13776.

During the orbit in which they were targeted, the NGSL stars were observed by
cycling through three different gratings. G230LB sees in UV (central
wavelength of 2375Å), G430L sees in blue (central wavelength of 4300Å) and
G750L sees in red (central wavelength of 7751Å). The three gratings overlap at
2990Å-3060Å and 5500Å-5650Å(Gregg et al., 2006). The CCD detector was employed
for these observations. UV exposure times were longer than exposures in the
blue or red. A $0\farcs 2$ slit, equivalent to $\pm 2$ pixels (Hernandez & et
al., 2012; Prichard et al., 2022) was used for all the observations and a
fringe flat was taken for the G750L grating at the end of each sequence of
exposures.

Figure 3: CCD images of HD102212 using (a) G230LB, (b) G430L, and (c) G750L.
Due to longer exposure time in the UV, the topmost panel shows the presence of
cosmic ray events whereas the bottom two do not have any significant ion
contamination. It is worth noting for this cool star that what appears to be a
stellar trace in the UV shortward of 2500Å is actually light scattered from
the visible portion of the spectrum into the UV by grating G230LB.

In addition to the usual observational defects (cosmic ray hits, charge
transfer efficiency effects, bad pixels, and photon noise) these data suffer
from two additional sources of error that affect fluxing. Firstly, the G230LB
grating scatters red light into the UV, creating a spurious signal that must
be corrected (Lindler & Heap, 2010; Worthey et al., 2022a). Secondly, scatter
in telescope pointing plus a narrow slit led to situations in which the jaws
of the slit sliced off portions of the PSF. Because STIS is an off-axis
instrument, the PSF is not symmetrical, so the resultant attenuation is
wavelength-dependent. Fortunately, both of these effects can be modeled, and
we give details in $\S 4$.

Of minor note, STIS spectral flux calibrations have improved since the
previous version of the NGSL library was placed at MAST.

##  3 Reduction and Quality Control

All 556 targets from proposals GO9088, GO9786, GO10222, and GO13776 were
reduced from raw observation files. Out of these 556 targets, 514 have been
reduced completely and additional corrections have been applied. The remaining
42 targets have not been reduced either because of faulty fringe-flat files or
because of the absence of one of the observations in UV, blue, or red. The raw
files for all the observations (which include observations in UV, blue, and
red as well as CCD flats) were downloaded from the Space Telescope Science
Institute (STScI) archive. The reduction process is carried on using the
stistools Python3 package developed by STScI. Out of these 514 targets, there
is a duplication for one of the targets (GJ 614 and HD 145675) leaving us with
513 unique targets.

The reduction procedure consisted of several steps starting from cosmic rays
correction to combining disparate spectral windows into one continuous
spectrum for each star.

###  3.1 Cosmic Ray Correction

Cosmic ray corrections are more crucial for observations using G230LB grating
that was used for longer-duration UV observations. This is illustrated in Fig.
3 where cosmic rays are common in the G230LB exposure. Accordingly, all
multiple UV observations were run through the ocrreject function of stistools.
This function combined two sets of science observations in UV into a single
file. In order to run ocrreject, we needed to have at least two observations
at each pointing. Unfortunately, the UV raw files from proposals GO10222 and
GO13776 did not have multiple UV exposures. For these, bad pixels were removed
manually from the spectra.

###  3.2 Defringing in the Red

Fringes are interference patterns caused by photons with wavelengths that are
integral multiples of the width of the CCD layer. In STIS, fringe patterns are
prominent redward of $\sim$7000Å and reach peak-to-peak amplitude of 25% at
9800Å (Kimble et al., 1998; Malumuth et al., 2003). The G750L grating produces
unwanted fringe patterns. Once per orbit, a fringe flat was obtained using the
tungsten lamp on board HST.

The defringing process was carried out using the defringe tool of stistools
(for details, see https://stistools.readthedocs.io/en/latest/). The following
three methods were used in sequence for all the NGSL observations.

  1. 1.

normspflat: this method normalizes the fringe-flat that is associated with
each observation

  2. 2.

mkfringeflat: this method cross correlates the normalized fringe-flat with
that of the observed spectrum to match the fringes between the two. It
minimizes the RMS within a given range of shift and scale values to find the
best shift and scale

  3. 3.

defringe: this method actually defringes the observed spectrum by removing the
fringing pattern from the observed spectrum using the shifted and scaled
fringe-flat

Fig. 4 shows the red spectrum of HD102212 before and after defringing.

Figure 4: Extracted, fluxed CCD/G750L spectrum of HD102212. The spectrum
before defringing (black) is compared to the same spectrum after (red).

While defringing the red spectra it was observed that no proper fringe-flat is
available for 27 targets. We dropped these stars from further analysis and
thus reduced the total number of targets from 556 to 529. While trying to
defringe red spectra from GO13776. although some of the targets from GO13776
have 2 or 3 red spectra, only one of them defringed properly. Investigation
yielded an observing irregularity. For run GO13776, the G750L (red third of
the spectrum) target exposures were preceded by a fringe flat through the
$0.3\times 0.09$ notch aperture, which is placed near row 512 of the chip (the
UV and blue spectra were taken at the E1 pseudoaperture around row 900 of the
CCD). The telescope was slewed to place the target star at row 512 of the chip
rather than 900, and one exposure taken through the nominal $52\times 0.2$
aperture. Due to an oversight, positional dithering occurred. The telescope
was slewed $0\farcs 5$, and an exposure was taken through the $52\times 0.2$
aperture followed by an exposure through the $52\times 0.5$ aperture. This
last exposure eliminates edge effects and provides the best fluxing, but it
cannot be fringe-corrected using the data collected on-orbit. Therefore, only
one red spectrum (for each target) was used for run GO13776. For three targets
from GO13776 (HD 65589, HD 84035, and HD 185264), none of the red observations
could be satisfactorily defringed. These stars were also dropped from further
analysis which reduced the total number of stars from 529 to 526.

Also unique to proposal GO13776, the last pair of red observations were often
a pair obtained through 0$\farcs$2 and 0$\farcs$5 apertures. Although these
could not be defringed due to the shift along the aperture center line, they
could be used to create a relative flux correction, should the star have been
placed off the central line of the entrance aperture. A smoothed division of
these two spectra was applied to the first, defringed observation in all cases
where the complete set of observations exists.

###  3.3 1-D Extraction

The final step in the reduction process was to extract the 1-D spectrum for
each target and each observation in UV, blue, and red using the x1d function
of stistools. This resulted in a separate file for each UV, blue, or red
observation for each target. Twelve of the remaining 526 targets did not have
one of either UV or blue or red observations. These stars were dropped. This
reduced the total number of available stars to 514. 278 targets have 2
observations each of UV, blue, and red. 189 targets have 2 observations each
of UV and blue, and 1 of red. The remaining 47 targets have varied numbers of
observations for UV, blue and red (at least 1 of each).

###  3.4 Bad Pixel Handling

As mentioned in Sec. 3.1, a cosmic ray rejection algorithm was not applied to
blue and red observations. Even after applying cosmic ray rejection to the UV
observations, the UV spectra had leftover wild pixels of unusually high and
non-astrophysical flux (or counts). In order to mitigate this problem, each
observation for each target was checked manually for bad pixels and those
pixel locations were flagged. This step generated a single text file for each
target containing information on the number of bad pixels for each observation
and values for those pixels. Fig. 5 shows an example of presence of bad pixels
in the spectrum.

Figure 5: Individual spectra for NGSL star HD190360 in the UV (blue and
orange) illustrate the presence of bad pixels. After marking, the bad pixels
were removed by the algorithm described in $\S$3.7. The cleaned spectrum is
also plotted (black). We elevated the errors for the corrected portions of the
spectrum.

We tried our best to remove as many bad pixels as possible from each spectrum,
but there are some stars for which many bad pixels could not be removed
cleanly.

###  3.5 Special Flux Scalings

After fluxing, some spectra appeared to have been scaled in comparison with
their neighbors. For example, suppose a star has been exposed twice in the UV,
twice in the blue, and twice in the red. Now and then, one of those six
exposures appears slightly too strong or too weak compared with either the
spectral overlap region or with its supposedly identical sister spectrum. A
scaling was applied to these deviant cases, as listed in Table 1. The dataset
labels relate closely to the ones assigned by STScI, but we prepended a short
string to indicate if the spectrum was UV (uv_), blue (b_), or red (r_).

Table 1: Special Scalings

Target | Deviant | Clean | Scale
---|---|---|---
| Dataset | Dataset | Factor
HD 224801 | b_o93a6qk2q_flt | b_o93a6qk3q_flt | 1.0506
BD+17 4708 | r_o6h03vawq_drj | r_o6h03vavq_drj | 1.0669
HD 3712 | r_o6h04kf0q_drj | r_o6h04kezq_drj | 1.2163
HD 137759 | r_o6h04bm3q_drj | r_o6h04bm2q_drj | 1.1468
HD 124547 | r_o6h038xkq_drj | r_o6h038xjq_drj | 1.0556
HD 172506 | r_o6h06jp4q_drj | r_o6h06jp3q_drj | 1.0639
HD 4128 | r_o6h04ynyq_drj | r_o6h04ynxq_drj | 1.0718
HD 146233 | r_o6h05wb0q_drj | r_o6h05wazq_drj | 1.0512
HD 81797 | b_o6h03rocq_flt | b_o6h03robq_flt | 1.1058
HD 30614 | uv_o8ru4c020_crj | uv_o8ru4c010_crj | 0.9720
HR 753 | b_o6h03ntyq_flt | b_o6h03ntzq_flt | 1.1994
HD 136442 | b_ocr7nwr6q_flt | b_ocr7nwrcq_flt | 0.9319
HD 58343 | uv_o8ru4s010_crj | uv_o8ru4s020_crj | 0.9668
HD 217014 | b_ocr7pxp7q_flt | b_ocr7pxp6q_flt | 0.9346
HD 144608 | r_ocr7feacq_drj | b_ocr7fea7q_flt | 0.9048
HD 183324 | b_o8ruclpqq_flt | b_o8ruclprq_flt | 1.0501
BD+37 1458 | b_o6h04ti6q_flt | b_o6h04ti7q_flt | 1.0302
HD 52089 | uv_o8ru46020_crj | uv_o8ru46010_crj | 0.9725
BD+29 366 | r_ocr7aif7q_drj | b_ocr7aif6q_flt | 0.947
BD+25 1981 | r_ocr7agwlq_drj | b_ocr7agwkq_flt | 0.9249
HD 9826 | r_ocr7kchgq_drj | b_ocr7kcheq_flt | 0.9354
HD 19994 | r_ocr7klq6q_drj | b_ocr7klq4q_flt | 0.852
HD 21019 | r_ocr7koizq_drj | b_ocr7koiyq_flt | 0.7542
HD 21770 | r_ocr7kpsuq_drj | b_ocr7kpssq_flt | 0.8409
HD 25457 | r_ocr7ksc9q_drj | b_ocr7ksc8q_flt | 0.7998
HD 31128 | r_ocr7hxziq_drj | b_ocr7hxzgq_flt | 0.9685
HD 34411 | r_ocr7kxklq_drj | b_ocr7kxkkq_flt | 0.9246
HD 44420 | r_ocr7lgwsq_drj | b_ocr7lgwrq_flt | 0.9174
HD 48737 | r_ocr7liuiq_drj | b_ocr7liuhq_flt | 0.9549
HD 52265 | r_ocr7lln2q_drj | b_ocr7lln1q_flt | 0.9594
HD 57118 | r_ocr7cqqaq_drj | b_ocr7cqq9q_flt | 0.9343
HD 67523 | r_ocr7ien9q_drj | b_ocr7ien8q_flt | 0.8912
HD 71369 | r_ocr7lrsqq_drj | b_ocr7lrspq_flt | 0.9432
HD 82328 | r_ocr7lyh7q_drj | b_ocr7lyh6q_flt | 0.9042
HD 121370 | r_ocr7erjeq_drj | b_ocr7erjdq_flt | 0.9313
HD 134169 | r_ocr7ezp9q_drj | b_ocr7ezp8q_flt | 0.9649
HD 160365 | r_ocr7odh7q_drj | b_ocr7odh6q_flt | 0.9293
HD 161797 | r_ocr7oeobq_drj | b_ocr7oeoaq_flt | 0.9371
HD 188510 | r_ocr7gff0q_drj | b_ocr7gfexq_flt | 0.9354
HD 190390 | r_ocr7ghheq_drj | b_ocr7ghhdq_flt | 0.939
HD 192718 | r_ocr7gkaeq_drj | b_ocr7gkadq_flt | 0.9066
HD 217014 | r_ocr7pxp8q_drj | b_ocr7pxp7q_flt | 0.8636

Note. — Additionally, for BD+17 2844 we averaged the red spectra, and for HD
183324 we scaled up both the UV spectra by a factor of 1.093 to match the blue
spectra

In addition to sporadic scaling issues, observations for HD 1638 may have
missed the target altogether, as all spectral segments contain mostly noise.

###  3.6 Relative Velocities and Template Matching

The NGSL stars were chosen to encompass a broad interval of [Fe/H],
$\mathrm{log}\,g$, and $T_{\rm eff}$ (Gregg et al., 2004). Galactic halo stars
are mostly metal poor but can possess high relative velocity with respect to
the local rest frame (Du et al., 2018). Thus, some of the stars in NGSL have
relative velocities $>250$ km s-1. This fact called for a relative velocity
correction before bringing all the spectra to rest frame. To be consistent, we
applied the relative velocity correction to all 514 stars even when the
effects would be negligible. The nonrelativistic formula was used to correct
for the relative velocity:

$d\lambda=\frac{v}{c}\times\lambda\,,$ (1)

where $d\lambda$ is correction to the wavelength $\lambda$, $v$ is the
relative velocity of the star in km s-1 and $c$ is the speed of light in km
s-1. $d\lambda$ was added or subtracted from corresponding $\lambda$ values
depending on the sign of $v$. The values of $v$ were obtained from the SIMBAD
astronomical database (Wenger et al., 2000).

After correcting for the relative velocities, residual shifts to rest frame
(vacuum wavelengths) were estimated by comparing with template spectra. The
choice of template spectrum was made based on the effective temperature of the
particular star. The high resolution templates were rebinned to match the
observed wavelength points, then cross-correlated. The following templates
were adopted.

  1. 1.

Synthetic spectra were used for cool stars ($T_{\rm eff}<$ 5000 K) and warm
stars (5000 K $<$ $T_{\rm eff}<$ 8000 K). The synthetic spectra were generated
using Worthey (1994) model of stellar population.

  2. 2.

The observed spectrum of $\alpha$ Lyrae was used for hot stars ($T_{\rm eff}>$
8000 K)

Figure 6: A part of spectrum for HD115383 (blue) showing shift of the spectrum
with respect to the template (red)

The cross correlation function (in Å) was fitted with a single peak Gaussian
function. Fig. 6 shows a part of the spectrum for HD 102212 and illustrates
the amount of shift present in the observed spectrum with respect to the
template. Correlation value as a function of shift is shown in Fig. 7 (for the
same star HD 102212). The same template was used for all the observations of a
particular target. To speed convergence, we added initial shifts of 3Å, 9Å and
14Å to UV, blue and red observations, respectively. This “pre-shift” evidently
arises because wavelength calibrations were not performed on-orbit for NGSL,
and so a default wavelength solution was assigned.

Figure 7: Typical cross correlation value as a function of pixel shift in Å,
in this case for the red spectrum of G0 V star HD 115383.

###  3.7 The Composite Spectrum

To assemble a single contiguous spectrum, we combined bad pixel information
and shift information from template matching to splice all the observations
for a particular target into one final spectrum. The shift obtained for each
observation was added algebraically to the wavelength values. While applying
the bad pixel information, we devised a method for suppressing the bad pixels.
We first divided the range of each observation into 50 overlapping boxes of 40
pixels each. For each box, we found out the average flux weighted by the
variance ($f_{box}$) using the following formula–

$f_{box}=\frac{f_{1}v_{1}+f_{2}v_{2}+...+f_{40}v_{40}}{v_{1}+v_{1}+...+v_{40}}\,,$
(2)

where $f_{n}$ is the flux at $n^{th}$ wavelength value for a particular box
and $v_{n}$ is the corresponding variance (defined by, $v_{n}=1/e_{n}^{2}$
where $e_{n}$ is corresponding error in flux for that particular wavelength
value). These flux values were then linearly fitted over the range of
observation. Now, the flux at the previously identified bad pixels was set to
a flux value according to this linearly extrapolated relation. It is to be
noted that the error values at the bad pixels were inflated by a factor of
1000 before calculating $f_{box}$. This was done to make sure that the
erroneous pixels do not contribute much to the weighted average (as bad pixels
generally have very high flux values).

Once the flux values at the bad pixels were set according to the above
mentioned algorithm, we then calculated the weighted average flux value for
all the observations of a particular type (for eg., UV, blue or red) at a
particular wavelength value. For eg., if there are 2 UV observations for a
particular target, then the average UV flux at $n^{th}$ wavelength value
($f^{UV}_{n}$) is given by–

$f^{UV}_{n}=\frac{f^{1}_{n}v^{1}_{n}+f^{2}_{n}v^{2}_{n}}{v^{1}_{n}+v^{2}_{n}}\,,$
(3)

where $f^{1}_{n}$ and $f^{2}_{n}$ are UV fluxes at $n^{th}$ wavelength value
for $1^{st}$ and $2^{nd}$ observations respectively and $v^{1}_{n}$ &
$v^{2}_{n}$ are corresponding variances as defined before. This formula can
easily be generalized for more than or less than 2 observations. Once this
operation was performed for all the observations of a target, we then combined
all the observations to make a single spectrum for a target treating
$\lambda<$3057Å as UV observation, 3057Å$<\lambda<$5679Å as blue observation
and $\lambda>$5679Å as red observation. This algorithm does not apply without
any caveat as sometimes the flux values at bad pixels were negative. Users are
advised to be careful of such artifacts in the spectrum by considering the
uncertainty we assign.

##  4 Continuum Corrections

The G230LB grating scatters some red light onto the portions of the CCD where
UV is expected (Worthey et al., 2022a). This is a problem mainly for cool
stars ($T_{\rm eff}\leq 5000$ K) where we do not expect significant UV flux.
This section summarizes the results from Worthey et al. (2022a) on scattered
light as well as slit off-center corrections. We also applied these
corrections to the 514 NGSL stars that we have reduced.

###  4.1 Scattered Light Correction

The scattered light ($S(\lambda)$) is approximated by the formula (Worthey et
al., 2022a):

$S(\lambda)=K_{0}\times(1+0.00104\times(\lambda-2000))\,,$ (4)

where $K_{0}$ is the scattered light count rate at 2000Å and $\lambda$ is the
wavelength. Targets with T${}_{eff}<$5000K, $K_{0}$ is given by the median
counts rate around 2000Å (median counts rate for 1950Å$<\lambda<$2050Å). Two
stars in our list, HD 124547 and HD 200905, are spectroscopic binary stars
with T${}_{eff}<$5000K. For these two stars, $K_{0}$ calculated using the
average counts rate around 2000Å resulted in over correction of the spectra.
After visually inspecting the spectrum for these two stars, the $K_{0}$ values
were modified by hand to mitigate the problem of over correction. Targets with
T${}_{eff}>$5000K and for which V magnitudes ($m_{v}$) are available, $K_{0}$
is given by–

$K_{0}=426\times 10^{-0.4m_{v}}\,.$ (5)

But, for some of the targets (with T${}_{eff}>$5000K) $m_{v}$ is not
available. For such targets, $K_{0}$ is given by–

$K_{0}=1.78\times 10^{-7}\times C\,,$ (6)

where C is the integrated count rate between 2000Å and 10000Å. $S(\lambda)$
was then subtracted from overall count at each $\lambda$. Fig. 8 shows an
example of scattered light correction applied to the spectrum of HD102212.

Figure 8: The fluxed spectrum of the star HD102212 in the UV region without
any scattered light correction (blue) and with scattered light correction
(red). It is seen that the spectrum is a little over corrected in the region
around 1800Å

After applying the above mentioned formula of $S(\lambda)$ for all the 514
stars, 96 stars (T${}_{eff}>$5000K) were over corrected and 8 stars
(T${}_{eff}>$5000K) were under corrected as judged by inspection of the
spectra. For these cases, the coefficient values ($426$ in Eqn. 5 and
$1.78\times 10^{-7}$ in Eqn. 6) was iteratively modified to calculate $K_{0}$
until the discrepant star fell among its peers in the UV. The updated $K_{0}$
values were then used to calculate $S(\lambda)$ for those 104 targets.

###  4.2 Slit Off-center Correction

The NGSL targets were observed using the $0\farcs 2$ slit. If the target is
not placed at the center of the slit, light at the edges of the point spread
function (PSF) gets attenuated by the slit edges. Because the STIS instrument
is off-axis, the PSF is asymmetric, and the attenuation is wavelength-
dependent. To correct for the attenuation effect, we use the attenuation
factor ($D_{\lambda}$) which is given by (Worthey et al., 2022a):

$D_{\lambda}=a+bq+cq^{2}+dq^{3}+eq^{4}+fq^{5}+gq^{6}\,,$ (7)

where $q=\sqrt{\lambda/4500}$. The coefficients for the above formula at
different slit off-center values are given in Table 3 of Worthey et al.
(2022a). The slit off-center value for each of the 514 NGSL spectra was
calculated during the defringing process as outlined in $\S$3.2. It is obvious
that the slit off-center values for our 514 targets were not matching the
exact values given in Table 3 of Worthey et al. (2022a). The $D_{\lambda}$
curve (as a function of $\lambda$) for each of our targets was calculated as
linearly interpolated curve between two nearest $D_{\lambda}$ curves (for
which coefficients are available from Worthey et al. (2022a)). Once the
$D_{\lambda}$ curve was calculated for each target, the flux of that target
was divided by $D_{\lambda}$ at each $\lambda$ value.

###  4.3 Dust

We compiled interstellar dust extinction data for our 513-star library sample.
Koleva & Vazdekis (2012) gives non-negative AV values for around 341 stars. AV
for 44 stars are calculated by us (following Khan & Worthey, 2018b) by
matching an observed spectrum with a synthetic spectrum and then fitting a
1-variable extinction law from Fitzpatrick (1999). The rest of the AV values
are taken from GALExtin website version 1.2 (Amôres et al., 2021) using a
three dimensional Galactic extinction model by Drimmel et al. (2003). These AV
values are used to find the E(B-V) values using the following equation:

$E(B-V)=\frac{A_{V}}{3.1}$ (8)

The extinction law of Fitzpatrick (1999) was used to correct the spectra to
dust-free versions. Possible self-reddening for mass-losing stars was not
considered. The $E(B-V)$ values were also used to deredden the observed colors
that we use for the analysis below.

##  5 Presentation of the Library

###  5.1 Archived Spectra

All 513 spectra have been made available at http://astro.wsu.edu/hststarlib/
and at the Mikulski Archive for Space Telescopes (MAST) as a High Level
Science Product via 10.17909/kmdt-pw63 (catalog 10.17909/kmdt-pw63) in
separate FITS (Wells et al., 1981) files. Each FITS file contains 5
extensions, briefly described in Table 2.

Extension |  Description
---|---
Primary |  Contains no data. The header contains information about basic stellar parameters ([Fe/H], $\mathrm{log}\,g$, etc.) and averaged pointing information. Exposure-level pointing is available from the original MAST archive files.
Flux Table |  Binary table extension with columns for wavelength (in Å), uncorrected flux, scattered light corrected flux, scattered light & slit off-center corrected flux, and scattered light, slit off-center & dust corrected flux (fluxes are in erg/s/cm2/Å). Flux errors are also included as separate columns.
Count Rate Table |  Binary table extension with columns for wavelength (in Å), uncorrected count rate, scattered light corrected count rate, scattered light & slit off-center corrected count rate, and scattered light, slit off-center & dust corrected count rate. Uncertainties are also included as separate columns.
Flux Table (Log Scale) |  This binary table extension contains the same information as the Flux Table but the wavelengths are spaced on log scale with $\mathrm{log}\,\Delta\lambda$ = 0.0002
Count Rate Table (Log Scale) |  This binary table extension contains the same information as the Count Rate Table but the wavelengths are spaced on log scale with $\mathrm{log}\,\Delta\lambda$ = 0.0002
Table 2: Brief description of the FITS file structure.

Table 3 summarizes a mixture of astrophysical and reduction-specific metadata
for each stellar target.

Table 3: Stellar Metadata

Simbad | Header | $T_{eff}$ | log $g$ | [Fe/H] | B | V | $\pi$ | $(M_{V})_{0}$ | dSlit | $v_{r}$ | $K_{0}$ | $A_{V}$ | src | $\rm{Mg2800}$ | $\rm{H\alpha}$ | $\rm{H\beta}$ | Note
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---
Name | Name | (K) | (dex) | (dex) | (mag) | mag | (mas) | (mag) | (pixel) | (km s-1) | (ADU) | (mag) |  | (mag) | (mag) | (mag) |
HD 60319 | HD060319 | 5907 | 4.03 | -0.82 | 9.46 |  $\cdots$ | 10.99 |  $\cdots$ | -0.20 | -34.1 | 0.2 | 0.08 | 1 | 1.27 | 0.07 | 0.08 |  $\cdots$
G 202-65 | G202-65 | 6656 | 4.25 | -1.37 |  $\cdots$ |  $\cdots$ | 3.88 |  $\cdots$ | 1.00 | -245.6 | 0.0 | 0.00 | 1 | 0.61 | 0.12 | 0.15 |  $\cdots$
HD 185351 | HD185351 | 4921 | 2.95 | 0.01 | 6.11 | 5.17 | 24.22 | 2.00 | 0.80 | -6.6 | 5.2 | 0.09 | 1 | 0.45 | 0.05 | 0.04 |  $\cdots$
HD 72184 | HD072184 | 4643 | 2.84 | 0.23 | 7.01 |  $\cdots$ | 14.55 |  $\cdots$ | -0.10 | 16.5 | 2.4 | 0.11 | 1 | 0.15 | -0.01 | 0.03 |  $\cdots$
HD 126614 | HD126614 | 5453 | 3.87 | 0.53 | 9.66 | 8.79 | 13.65 | 4.41 | -0.20 | -32.9 | 0.2 | 0.05 | 1 | 0.67 | 0.03 | 0.08 |  $\cdots$

Note. — In this table, B and V are as observed (not dereddened), but
$(M_{V})_{0}$ is dereddened. The ”src” column is for $V$-band extinction
$A_{V}$: 1 – Koleva & Vazdekis (2012); 2 – Our derivation based on comparison
with synthetic templates; or 3 – Drimmel et al. (2003). The ”Note” column
refers to objects noted in $\S$5.2: 1 – noisy; 2 – possible extraction error;
3 – chemically peculiar; 4 – binary that does or may suffer from
compositeness; 5 – photometric variable.  This is a portion of the table,
presented to show format and content. The entirety is available online.

###  5.2 Notable objects

  * •

Targeted object Gleise 15B, a late M dwarf in a visual binary system, was not
observed. Due to the count rate and spectral shape, it is near certain that
its primary (Gleise 15A, GJ 15A, HD 1326, GX And) was observed instead. Our
metadata has been updated to reflect this change.

  * •

Quite a few chemically peculiar stars were included in the library that
practitioners wishing to fit only “normal” stars should exclude. HD 319, HD
141851, HD 204041, HD 210111, and HD 210418 are $\lambda$ Bootis stars. HD
18769, HD 41357, HD 41770, HD 67230, HD 78209, HD 95418, HD 109510, HD 111786,
HD 140232, HD 141795, and HD 172230 are Am stars. HD 176232 and HD 175640 are
Ap/Bp stars. HD 79158, HD 163641, HD 196426, and HD 220575 are Hg-Mn stars. HD
103036 has anomalously-low Mn. CD$-$62 1346 is a carbon-enhanced metal-poor
star. HD 183915 and HD 101013 are Ba stars and spectroscopic binaries. HD
30834 and HD 104340 are Ba stars.

  * •

HD 54361 is a carbon star and it has very little Mg2800 emission. This might
indicate that C-stars have abnormal chromospheres. HD 158377 is also a carbon
star and BD+36 3168 is a J-type carbon star.

  * •

HD 37202, HD 58343, HD 109387, HD 138749, and HD 142926 are Be stars with
strong Balmer emission lines, presumably from a disk. HD 190073 is a Herbig Ae
star with similar strong emission. HD 30614 is a blue supergiant star with
strong emission for H$\alpha$.

  * •

HD 358, HD 15089, HD 18078, HD 34797, HD 72968, HD 78316, HD 108945, HD
112413, HD 137909, HD 176232, HD 201601, and HD 224801 are $\alpha^{2}$ CVn
variable stars, also, broadly, Ap/Bp stars or HgMn stars.

  * •

HD 232078 is a metal-poor long-period variable star for which we observe
little Mg2800 flux. This star appears in most of the large stellar libraries.
It is a probable Mg2800 variable star, since Dupree et al. (2007) give a
surface flux of $\mathrm{log}\,F=$ 5.17 erg s-1 cm-2. It has also been
observed to have H$\alpha$ emission in the wings of the line (Cohen, 1976). We
hypothesize that at some phase range of the variability cycle, perhaps during
heavy mass loss, the normal chromosphere structure is disrupted.

  * •

Variable stars: HD 173819 is a classical Cepheid variable star. HD 67523 and
HD 183324 are $\delta$ Scuti (dwarf Cepheid) variable stars. V* BN VUL, BD +06
4990, and CD$-$25 9286 are RR Lyrae variable stars. HD 96446 pulsates and is a
Bp star. HD 170756 is an RV Tauri variable star.

  * •

Stars with some degree of binary compositeness include HD 41357, HD 69083, HD
78362, HD 79469, HD 106516, HD 164402, HD 166208, HD 187879, HD 193495, HD
210111. In our spectra, extra UV light from a companion can be seen in HD
26630, HD 124547, and HD 200905.

  * •

HD 149382 is a hot subdwarf (sdB) star. The origin of these stars is not
perfectly clear, but they are highly evolved.

  * •

HD 1638 and LHS 10 have noisy spectra. For purposes of repeatability, we did
not pursue alternative spectral extraction methods, but we note that
stistools.x1d’s extractions for at least G 63-26, G 115-58, G 169-28, G
192-43, G 196-48, and BD +66 268 are probably incorrect.

The list above points out a problem for this library among AB main sequence
stars: chemically-peculiar stars comfortably outnumber chemically-normal
stars.

##  6 The Mg II 2800 Feature and Chromospheric Activity

In this section, we explore the chromospheric activity of the 513 NGSL stars
after full reduction, including extinction corrections. Wilson & Vainu Bappu
(1957) showed that the absolute visual magnitudes (MV) of late-type stars
correlate linearly with logarithm of H & K emission line width of CaII (the
Wilson-Bappu effect) and Mg2800 h & k share this behavior (Elgarøy et al.,
1999; Cassatella et al., 2001). However, because our spectra are low
resolution we could not reliably compute an analogous width for the twin MgII
2800 emission lines. We therefore measure overall strength only.

To summarize the strength of MgII 2800 emission, we adopt an equivalent width
style index ($\rm{Mg2800}$):

$\rm{Mg2800}=-2.5\times log_{10}\frac{\int F_{\lambda}^{i}\ d\lambda}{\int
F_{\lambda}^{c}\ d\lambda}\,,$ (9)

where $F_{\lambda}^{i}$ is the observed flux within the spectral feature band
and $F_{\lambda}^{c}$ is the expected flux without the spectral feature within
the same band. We approximate $F_{\lambda}^{c}$ by defining a pseudo-continuum
from side bands. A line is drawn between the central wavelengths and average
flux values of the two sidebands. The Mg2800 central feature band is defined
as wavelengths between [2784Å, 2814Å]. The blue side band is [2762Å, 2782Å]
and the red one is [2818Å, 2838Å]. These definitions of feature and side bands
are adopted from Fanelli et al. (1990). Fig. 9 shows the adopted definitions
for Mg2800 central feature band and the two side bands (blue and red).

Figure 9: Spectra of two stars, HD002857 (T${}_{eff}=$7607K, as blue line) and
HD102212 (T${}_{eff}=$3738K, as black line), showing feature band (green),
blue side band (blue), and red side band (red) for our calculation of Mg2800
feature strength. The flux for HD002857 is scaled up by a factor of 10 for
visual prominence. The hotter star (HD002857) and the cooler star (HD102212)
has Mg2800 in absorption and emission respectively. Figure 10: Mg2800 versus
(B-V)0. Dwarfs (red) and giants (blue) are given different symbol types to
denote metallicity groups: metal-poor (crosses), intermediate (filled
circles), and metal-rich (non-filled triangles). Carbon star HD 54361 lies
outside the plot limit and its position is indicated by a black arrow to the
right.

We keep the units (magnitudes) adopted by Fanelli et al. (1990). A negative
index value signifies net emission and a positive value signifies absorption.
Fig. 10 displays Mg2800 as a function of dereddened color for the library
stars. Hot stars have negligible Mg2800 absorption. We also note that,
although the sample contains some strongly-active Be stars, these stars show
no anomalous Mg2800 absorption or emission. Mg2800 absorption increases from
A0 stars to sunlike stars [$(B-V)_{0}=0.65$] and declines thereafter. In cool
stars, both giants and dwarfs, chromospheric Mg2800 emission overtakes
photospheric absorption at $(B-V)_{0}\approx 1$ and dominates for cooler
stars. Fig. 10 agrees well with Fig. 5c of Fanelli et al. (1990).

For the plots herein, the distinction between giants and dwarfs is
approximated via the color-magnitude diagram (CMD) as shown in Fig. 11. Stars
warmer than $(B-V)_{0}=0$ or fainter than $M_{V}=3.0$ were simply considered
dwarfs regardless of their spectral type. For $(B-V)_{0}>0$, any star with
$M_{V}>6.25\times(B-V)_{0}-2.5$ is considered a dwarf whereas
$M_{V}<6.25\times(B-V)_{0}-2.5$ is considered a giant.

The Fig. 11 CMD is color-coded by Mg2800 value. The verticality of the color
bands shows again that both cool dwarfs and cool giants have similar Mg2800.
Their chromospheres are similar by this measure despite vastly different size
scales ($\sim 0.1R_{\odot}$ versus $\sim 100R_{\odot}$). The emission
gradually changes to absorption for warm stars and declines to near zero for
hot stars. Note that some distant stars may have extra Mg2800 absorption due
to warm interstellar material along the line of sight.

Even given the intentional diversity in sample selection, outliers are
relatively few. One is G9 giant HD 222093, at $(B-V)_{0}\approx 1$ and
M${}_{V}\approx 1$ in Fig. 11. It has a high value for Mg2800 absorption,
signified by the red color in Fig. 11. The star’s spectrum shows emission
peaks at the core of a broad absorption feature at 2800Å, normal for a star
whose absorption competes with emission at $(B-V)_{0}\approx 1$, but this
star’s emission is weak. HD 222093 also shows up in Fig. 10 as the sole star
with the highest Mg2800 absorption at $(B-V)_{0}\approx 1$.

Figure 11: CMD for all 513 NGSL stars. The color bar shows Mg2800 strength.
Stars warmer than $(B-V)_{0}=0$ or fainter than $M_{V}=3.0$ were considered
dwarfs. For $(B-V)_{0}>0$, any star with $M_{V}>6.25\times(B-V)_{0}-2.5$ is
considered a dwarf whereas $M_{V}<6.25\times(B-V)_{0}-2.5$ is considered a
giant. For dwarfs, Mg II emission fills in the absorption redder than
$B-V=0.9$, whereas emission begins to dominate for giants at $B-V=1.2$.

Fig. 12 plots Mg2800 vs. metallicity, color-coded by $(B-V)_{0}$. It is clear
from this figure that no strong correlation exists between these two
quantities in any color regime, particularly for cools. An anticorrelation
among cool stars might have been expected from the Ca II H & K results of
Houdebine & Stempels (1997) who found that metal poor stars are activity
deficient, but we see no such trend. Peterson & Schrijver (1997) reports that
chromospheric characteristics do not have any metallicity dependence.

Figure 12: Mg2800 as a function of [Fe/H]. The color bar codes (B-V)0 and the
symbol type distinguishes dwarfs (crosses) and giants (circles).

A subtle declining trend among medium-temperature stars in Fig. 12 deserves a
note and an additional figure, namely Fig. 13, which restricts the color range
to be near solar (0.5$<$(B-V)${}_{0}<$0.8). Because these are positive values
of Mg2800, indicating absorption, one might expect a monotonic increase of
Mg2800 with [Fe/H]. Mg2800 absorption does increase for metal poor stars
($-2<$ [Fe/H] $<-1$) but then the index value saturates and falls for metal
rich objects. Although Lovis et al. (2011) reports not much of a correlation
with Ca II lower envelope and metallicity, but a decreasing trend can be seen
in Meunier et al. (2022) for [Fe/H]$>$-1. With the help of synthetic spectra,
two sequences of which are also plotted in Fig. 13, the reason appears to be a
simple curve of growth argument. Mg2800 is a resonance feature that scales
approximately as the abundance of the Mg II ion. It reaches full depth at
[Fe/H] $\sim-1$, but the flanking (in wavelength) absorption features from a
plethora of atomic species are still weak. From [Fe/H] $\sim-1$ and higher,
these weak features will grow faster than the central Mg II absorption pair.
As the pseudocontinuum drops, the Mg2800 index drops. Parenthetically, the
relatively poor agreement of synthetic spectra and observed spectra in Fig. 13
should be no surprise. The UV spectrum is crowded, its lines have not received
as much attention as optical ones, and for warm and cool stars the wavelength
regime is on the blue side of the blackbody curve, exposing defects in the
upper layers of the model atmosphere due to the absence of backwarming.

Figure 13: Mg2800 as a function of [Fe/H] for a narrowed color range of
0.5$<$(B-V)${}_{0}<$0.8. Dwarfs (crosses) and giants (circles) are color coded
by (B-V)0. Black lines indicate Mg2800 from synthetic LTE spectra for dwarfs
($T_{\rm eff}$=5770K, $\mathrm{log}\,g$=4.5, solid) and giants ($T_{\rm
eff}$=5770K, $\mathrm{log}\,g$=1.5, dashed).

H$\alpha$ emission is a separate indicator of stellar chromospheric activity
(Montes et al., 1995; Cincunegui et al., 2007; Gomes da Silva et al., 2014)
and also magnetic flare activity. An index for the H$\alpha$ feature is
calculated using the passband definitions of Cohen et al. (1998) but here we
convert it to magnitude units (Eqn. 9). The spectral feature band is [6548Å,
6578Å] and the blue pseudocontinuum is [6420Å, 6455Å] and the red
pseudocontinuum is [6600Å, 6640Å].

Mg2800 and H$\alpha$ are plotted against each other in Fig. 14. The strongest
H$\alpha$ emitters are Be stars, generally assumed to be young stars with
disks (Gray & Corbally, 2009). We might also expect to catch some flaring M
dwarfs, but apparently none of the M dwarfs were observed during outbursts, as
we see no cool dwarfs scattering to negative H$\alpha$ values. The “triangle”
in the positive-positive quadrant arises because peak H$\alpha$ absorption
occurs among hotter stars than peak Mg2800 absorption. Among cool stars with
negative Mg2800, the mild correlation is due to expected H$\alpha$ index
absorption behavior from species unrelated to H$\alpha$ itself, such as TiO
(e.g. Valdes et al., 2004). That is, it is a consequence of the strong
Mg2800-temperature anticorrelation in cool stars, and does not imply H$\alpha$
emission at all. The chromospheric emission has been studied using Ca II H & K
and H$\alpha$ as activity indicators. Some of these studies find a good
correlation between these two indicators (please see the review by Linsky,
2017, and references there in) whereas some studies find strong temporal anti
correlation between these two indices in certain percentage of their selected
stars (Cincunegui et al., 2007; Gomes da Silva et al., 2014). Meunier et al.
(2022) suggests that this type of behaviour needs to be explained by
considering contributions from plages and filaments.

Figure 14: Mg2800 is plotted against H$\alpha$ for dwarfs (crosses) and giants
(circles). The points are color coded by (B-V)0. Three stars to the extreme
left of the figure are all Be stars: HD 37202, HD 109387, and HD 190073.

Two stars lie at anomalously-negative H$\alpha$ values. They are: HD 126327
(giant) and GL 109 (dwarf). Presumably, HST serendipitously observed these
objects during flare events.

The correlation between Ca II H & K core emission strength (a third stellar
activity indicator) and H$\alpha$ emission is also well studied. Some authors
report a positive correlation between the two (Pasquini & Pallavicini, 1991;
Montes et al., 1995), some a lack of correlation, and some a negative
correlation (Cincunegui et al., 2007; Gomes da Silva et al., 2011). Our Mg2800
results shed little insight into this uncertain area.

##  7 Discussion and Conclusion

This paper presents a new reduction of the Next Generation (HST/STIS low
resolution) Spectral Library that includes updated flux calibration work,
updated scattered light corrections, and an increase in sample size (345 to
513) due to inclusion of stars from run GO13776. This increases the parameter
space coverage in $\mathrm{log}\,g$, $T_{\rm eff}$ and [Fe/H] (Figs. 1 and 2).

After correction for interstellar extinction, the spectra were used to explore
the chromospheric activity of stars using the Mg II 2800 h + k feature and
H$\alpha$ as likely indicators.

Against color, there is a gradual change of sign of Mg2800 from positive to
negative (signifying absorption to emission transition) for both dwarfs and
giants within 0.5$<$(B-V)${}_{0}<$1.5. From Fig. 10 it is evident that the
transition happens at (B-V)0=1.0 or spectral class K3 for dwarfs, and
(B-V)0=1.12 or spectral class K4-K5 for giants. The color calibration of
Worthey & Lee (2011) indicates that we expect dwarfs to have $B-V$ bluer than
giants by about 0.1 mag, so this crossover happens at about the same $T_{\rm
eff}$ for both dwarfs and giants. Largely, this result is consistent with
results from Gurzadian (1975) where it was shown that Mg II 2800 feature
starts dominating in emission in K2 and later-type stars. The photospheric
absorption gives way to strong chromospheric emission as the temperature
drops. Temperature is the emphatic controlling parameter of Mg2800 emission;
the cooler the star, the stronger the emission. [Fe/H] and log $g$ have little
influence on Mg2800, and we see no evidence of flare behavior.

We chart basic H$\alpha$ and H$\beta$ behavior in Figs. 15 and 16
respectively. The peaks are the deep absorptions in A stars, and strongly
negative values indicate that emission has overshadowed absorption. Fig. 15
shows four stars with mild flares in progress: GJ 551, GJ 876, and GL 109 are
dwarfs while HD 126327 is a giant. GJ 551 is Proxima Centauri and it shows up
as a flaring dwarf in a 20 seconds cadence Transiting Exoplanet Survey
Satellite (TESS) monitoring campaign (Howard & MacGregor, 2022). Evidence for
flares in GJ 876 is reported in Froning et al. (2019). GL 109 is listed as an
eruptive variable in SIMBAD and categorized as UC Cet-type flare star
(Gershberg et al., 1999). HD 126327 is the only cool giant that seems to be
flaring. Prominent TiO band absorption affects the coolest stars. Cool giants
saturate at $B-V\approx 1.65$ (Worthey & Lee, 2011) but especially H$\beta$
continues to increase, not because of actual H$\beta$ absorption, but because
of the increasing influence of TiO features. Fig. 17 shows the feature and
side bands used in calculation of H$\beta$ index strength. The hotter star
(upper panel (a)) shows clear H$\beta$ absorption. But for the cooler star
(lower panel (b)), the values obtained for the H$\beta$ strengths are mostly
from TiO features. The hot dwarfs with H$\alpha$ magnitudes less than -0.1 are
Be stars.

Figure 15: H$\alpha$ as a function of $(B-V)_{0}$ for dwarfs (red) and giants
(blue) are shown, segregated by metal-poor (crosses), intermediate (filled
circles), and metal-rich (non-filled triangles) status. Be stars scatter to
negative values for hot stars with $(B-V)_{0}<0$. Any star caught during a
flare event should also scatter toward negative index values. Four stars (3
dwarfs and 1 giant) with H$\alpha<-0.15$ and $(B-V)_{0}>1.5$ are thought to be
flaring: GJ 551, GJ 876, and GL 109 are dwarfs while HD 126327 is a giant.
Noise prevents reliable measurement of Mg2800 in GJ 551 (Proxima Centauri) and
GJ 876. Therefore, these stars do not appear in figures that illustrate
Mg2800. Carbon star HD 54361 lies outside the plot limit and its position is
indicated by a black arrow to the right. Figure 16: H$\beta$ as a function of
$(B-V)_{0}$ for dwarfs (red) and giants (blue), segregated by metal-poor
(crosses), intermediate (filled circles), and metal-rich (non-filled
triangles) status. H$\beta$ is less sensitive to emission than H$\alpha$.
Carbon star HD 54361 lies outside the plot limit and its position is indicated
by a black arrow to the right.

The Mg II 2800 line emission in UV is a major probe for chromospheric
radiative loss(Linsky & Ayres, 1978). From Fig. 10 it is evident that there is
scatter in Mg II 2800 line strength for a given temperature, but the character
of that scatter might be astrophysical. Various studies have suggested the
existence of a ‘basal’ flux level for Mg II 2800 that might indicate the level
of an ongoing, persistent mechanism (acoustic waves are often cited) that can
be supplemented by a more variable heating mechanism (such as
magnetohydrodynamic shocks) that adds Mg emission to some stars but not others
(Schrijver, 1987; Strassmeier et al., 1994; Martínez et al., 2011).

Figure 17: Spectra of two stars, HD221377 (T${}_{eff}=$6399K, in upper panel
(a)) and HD126327 (T${}_{eff}=$2874K, in lower panel (b)), showing feature
band (green), blue side band (blue), and red side band (red) for our
calculation of H$\beta$ feature strength. For the hotter star (HD221377, upper
panel (a)), we see clear absorption for H$\beta$ whereas the lower panel (b)
shows no apparent activity for H$\beta$ for the cooler star (HD126327).

Recast in terms of the Mg II $\lambda$2800 flux emerging from the star’s
surface ($F_{\lambda}$), the above authors find a ‘basal level’ that increases
with temperature. In order to confirm this, we select NGSL stars with $T_{\rm
eff}<$ 5000K and recast their emission line strengths as emergent fluxes as in
Martínez et al. (2011). The scheme follows Oranje et al. (1982), but extended
to account for interstellar extinction. Oranje et al. noted that

$\displaystyle\frac{F_{\lambda}}{f_{\lambda}}=\frac{F_{bol}}{f_{bol}}\,,$ (10)

where $F_{\lambda}$ is the star’s outbound surface flux (erg cm-2 s-1) at some
wavelength. For us, this wavelength is 2800Å, and it is chromospheric in
origin. The lower case $f_{\lambda}$ is then the flux received at earth. The
right hand side are the bolometric versions. This equation is only good in the
limit of zero extinction. Extinction at wavelength $\lambda$ (Aλ) is defined
by:

$\displaystyle A_{\lambda}=-2.5{\rm log}\
\frac{f_{\lambda}}{f_{0,\lambda}}\,,$ (11)

where $f_{0,\lambda}$ is the extinction corrected version of $f_{\lambda}$.
This equation can be inverted to

$\displaystyle f_{\lambda}=f_{0,\lambda}10^{-0.4A_{\lambda}}=f_{0,\lambda}\
g(A_{\lambda})\ ,$ (12)

where the function $g(A_{\lambda})$ is shorthand we introduce. By convention,
$A_{\lambda}$ is positive and thus, $f_{\lambda}$ is always less than
$f_{0,\lambda}$ and $0<g(A_{\lambda})\leq 1$. Besides $g(A_{\lambda})$, we
also invent $h(A_{bol})$ to represent the extinction in bolometric quantities,
which is more complicated to produce (it requires the integration of the dust-
attenuated flux over all wavelengths and thus depends on the spectral type of
the target star). Putting everything together:

$\displaystyle
F_{\lambda}=f_{0,\lambda}\frac{F_{bol}}{f_{0,bol}}\frac{g(A_{\lambda})}{h(A_{bol})}$
(13)

This can be rephrased in terms of $T_{\rm eff}$ by noting that:

$\displaystyle F_{bol}=\sigma T_{\rm eff}^{4}\,,$ (14)

where $\sigma$ is the Stephan-Boltzmann constant and

$\displaystyle f_{0,bol}=B10^{-0.4(V+BC_{V})}\,,$ (15)

where $B$ is a zeropoint adjustment between physical units and the
astronomical magnitude scale, $V$ is the apparent magnitude in V-band, and
$BC_{V}$ is the bolometric correction for V-band. The $B$ value is obtained by
noting that, $f_{bol,\odot}$=1361 Wm-2, V⊙=-26.76 (Willmer, 2018), and
BCV,⊙=0.09 (VandenBerg & Clem, 2003).

Figure 18: Inferred surface flux from Mg II 2800 (log10, cgs units) as a
function of $T_{\rm eff}$ for both giants (red) and dwarfs (blue) with $T_{\rm
eff}<$ 5000 K. The green line is the “basal flux” from Martínez et al. (2011).
Three stars with $\mathrm{log}\,(Flux)<$3.0 (HD 54361, HD 126327, and HD
232078) are below the plot limits. The downward black arrows show
$\mathrm{log10}\,(T_{\rm eff})$ for them. For comparison, the blackbody
emergent flux integrated over the Mg2800 central passband (black line) is
shown. Figure 19: Spectra of 5 stars are shown in the $\lambda$2800 region.
TOP: Fluxed spectra are normalized at 2820Å. BOTTOM: Fluxed spectra are
normalized such that the continuum-subtracted emission scales as the surface-
emergent emission $F_{\lambda}$ derived for Fig. 18. “Normal” HD 136726 and HD
131918 lie near the green line in Fig. 18 and the remaining three stars are
low outliers. HD 232078 and carbon star HD 54361 lie outside the plot limits
in Fig. 18 and HD 126327 was caught during a flare event (Fig. 14).

Known $T_{\rm eff}$, [Fe/H], and $\mathrm{log}\,g$ values for each star were
used to interpolate a low resolution synthetic flux from Worthey (1994). We
applied a Fitzpatrick (1999) cubic spline extinction curve to this synthetic
flux, then integrated (with and without extinction) to find $h(A_{bol})$. For
the bolometric correction, we used the Worthey & Lee (2011) calibration, which
also requires $T$, $\mathrm{log}\,g$, and [Fe/H]. We used these values and our
Eqn. 8 to get A2800. The quantity $f_{0,bol}$ was calculated by integrating
the flux over index band for Mg II 2800. A linear pseudocontinuum calculated
from the Mg II 2800 passbands was subtracted before the integration.

Fig. 18 shows the dependence of $F_{\lambda}$ as a function of $T_{\rm eff}$
in a log-log scale. Thus transformed to surface-emergent flux, cool dwarfs are
seen to emit an order of magnitude more Mg2800 flux per unit surface area,
with two notable low-lying objects. As for giants, a number of cool giants
have lower flux values than the basal line given by Martínez et al. (2011)
(solid green line in Fig. 18). One giant (HD 222093) lies two orders of
magnitudes brighter than typical, and three stars lie offscale on the low end.
A likely explanation for the difference in the morphology of our figure versus
Martínez et al.’s is our improved treatment of interstellar extinction. If we
artificially set our extinctions to zero, the figure’s morphology
qualitatively matches that of Martinez et al.’s. Despite our lower spectral
resolution compared to IUE’s, continuum subtraction is too minor to contribute
significant error.

Another giant, HD 126327, lies more than an order of magnitude lower than the
line but also was caught flaring in H$\alpha$ (Fig. 14). This might indicate
that stormy events in the photosphere and lower chromosphere might temporarily
disrupt the middle chromosphere where Mg2800 arises. Fig. 19 elucidates the
fact that stars lying close to the green line in Fig. 18 in fact have higher
Mg II $\lambda$2800 flux compared to stars lying way below the same green line
in Fig. 18.

Figure 20: Mg II 2800 feature in HD 102212 as observed by IUE (blue), in the
NGSL (red), and by Worthey et al. (2022a) (green). The IUE spectrum is at
lower resolution compared to Worthey et al. (2022a) and NGSL.

Fig. 20 shows variation in the MgII 2800 spectral lines using observations
from International Ultraviolet Explorer (IUE), NGSL, and Worthey et al.
(2022a) for the single star HD 102212. The observations were made in 1997,
2002, and 2021 for IUE, NGSL, and Worthey et al. (2022a) respectively. Mg2800
values for the three cases are -1.49$\pm$0.05, -1.81$\pm$0.003, and
-2.26$\pm$0.008 for IUE, NGSL, and Worthey et al. (2022a) respectively. The
errors in Mg2800 values are calculated by taking into consideration the errors
in flux at each pixel value and then propagating these errors while
calculating Mg2800 values. Even admitting a few percent additional fluxing
error, it is statistically certain that Mg2800 values show a temporal
variation in HD 102212.

Add this to HD 232078, a similar long-period variable listed in $\S$5.2 that
is probably also variable in Mg2800.

The sun is known to have a $\sim$7% Mg2800 variation that correlates with the
magnetic activity cycle (Deland & Cebula, 1993). Buccino & Mauas (2008) report
cyclic chromospheric activity in HD 22049 and HD 128621 using IUE spectral
data. At visible wavelengths, some studies show overall variation in
chromospheric activity from CaII H & K lines. Baliunas et al. (1998) report
that 85% of stars in the 40-year HK Project at Mount Wilson Observatory showed
either periodic (60%) or aperiodic (25%) variation in chromospheric activity.
Temporal variation possibly separates magnetically-driven chromospheric
heating, which can be expected to be cyclic, from acoustic wave-driven
heating, which might be expected to be steadier. In this regard, HD 102212 is
not an apt test case because it is a long-period variable star likely to
experience considerable “activity variability” in its gaseous envelope.

##  8 Acknowledgements

We acknowledge with thanks the variable star observations from the AAVSO
International Database contributed by observers worldwide and used in this
research. This work is based on observations made with the NASA/ESA Hubble
Space Telescope, program GO 16188, https://dx.doi.org/10.17909/t9-d42d-z465.
Support for this work was provided by NASA through grant number HST-
GO-16188.001-A from the Space Telescope Science Institute. STScI is operated
by the Association of Universities for Research in Astronomy, Inc. under NASA
contract NAS 5-26555. This research has made use of the SIMBAD database,
operated at CDS, Strasbourg, France.

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