Vol. 0 (200x) No. 0, 000–000

11institutetext: CAS Key Laboratory for Research in Galaxies and Cosmology,
Department of Astronomy, University of Science and Technology of China, Hefei
230026, China; E-mail<EMAIL_ADDRESS><EMAIL_ADDRESS>
22institutetext: School of Astronomy and Space Science, University of Science
and Technology of China, Hefei 230026, China
33institutetext: Key Laboratory of Optical Astronomy, National Astronomical
Observatories, Chinese Academy of Sciences, Beijing 100012, China
44institutetext: Nanjing Institute of Astronomical Optics $\&$ Technology,
National Astronomical Observatories, Chinese Academy of Sciences, Nanjing
210042, China

# A sample of metal-poor galaxies identified from the LAMOST spectral survey

Yulong Gao 1122 Jianhui Lian 1122 Xu Kong 1122 Zesen Lin 1122 Ning Hu 1122
Haiyang Liu 1122 Enci Wang 1122 Zihuang Cao 33 Yonghui Hou 44 Yuefei Wang 44
Yong Zhang 44

(Received 2009 month day; accepted 2009 month day)

###### Abstract

We present a sample of 48 metal-poor galaxies at $z<0.14$ selected from 92,510
galaxies in the LAMOST survey. These galaxies are identified for their
detection of the auroral emission line [O iii]$\lambda$4363 above $3\sigma$
level, which allows a direct measurement of the electron temperature and the
oxygen abundance. The emission line fluxes are corrected for internal dust
extinction using Balmer decrement method. With electron temperature derived
from [O iii]$\lambda\lambda 4959,5007/\hbox{[O\,{\sc iii}]}\lambda 4363$ and
electron density from $\hbox{[S\,{\sc ii}]}\lambda 6731/\hbox{[S\,{\sc
ii}]}\lambda 6717$, we obtain the oxygen abundances in our sample which range
from $\hbox{$12\,+\,{\rm log(O/H)}$}=7.63$ (0.09 ${\rm Z}_{\sun}$) to $8.46$
(0.6 ${\rm Z}_{\sun}$). We find an extremely metal-poor galaxy with
$\hbox{$12\,+\,{\rm log(O/H)}$}=7.63\pm 0.01$. With multiband photometric data
from FUV to NIR and H$\alpha$ measurements, we also determine the stellar
masses and star formation rates, based on the spectral energy distribution
fitting and H$\alpha$ luminosity, respectively. We find that our galaxies have
low and intermediate stellar masses with $\rm 6.39\leq log(M/M_{\sun})\leq
9.27$, and high star formation rates (SFRs) with $\rm-2.18\leq
log(SFR/M_{\sun}yr^{-1})\leq 1.95$. We also find that the metallicities of our
galaxies are consistent with the local $T_{e}$-based mass-metallicity
relation, while the scatter is about 0.28 dex. Additionally, assuming the
coefficient of $\rm\alpha=0.66$, we find most of our galaxies follow the local
mass-metallicity-SFR relation, while a scatter about 0.24 dex exists,
suggesting the mass-metallicity relation is weakly dependent on SFR for those
metal-poor galaxies.

###### keywords:

galaxies: abundances - galaxies: evolution - galaxies: starburst - galaxies:
star formation

##  1 Introduction

Metal-poor galaxies are less chemically evolved galaxies and provide ideal
laboratory for investigating galaxy properties in extreme condition (Shi et
al., 2005; Lian et al., 2016). Among them, extremely metal-poor galaxies
(hereafter XMPGs), defined by their low oxygen abundance with
$\hbox{$12\,+\,{\rm log(O/H)}$}\leq 7.65$ (Kniazev et al., 2003; Pustilnik &
Martin, 2007; Doyle et al., 2005), are the most promising young galaxy
candidates in the local universe (Izotov & Thuan, 2004). These XMPGs are
suspected to be primeval galaxies that are undergoing their first major mass
assembly at the observed redshift (Kniazev et al., 2003). Studying these
extreme objects can improve our understanding about the early stages of galaxy
assembly.

The determination for abundance of elements are considered more reliable if
the electron temperature $T_{e}$ can be measured directly, because the
metallicity is anti-correlated with the electron temperature. The electron
temperature can be obtained using the auroral line ratios, such as [O
iii]$\lambda 4363/$[O iii]$\lambda\lambda 4959,5007$. This technique is often
called the $T_{e}$ method (Aller, 1984). However, galaxies with metallicities
derived from the $T_{e}$ method with $\hbox{[O\,{\sc iii}]}\lambda 4363$
detections above 3$\sigma$ are extremely rare. To date, only about 174 such
objects has been found (Ly et al., 2014, 2016b).

In order to enlarge the sample of metal-poor galaxies with [O
iii]$\lambda$4363 detection, we carry out a systematic search for such objects
in the LAMOST Data Release (DR3, DR4 Q1 and Q2). In Section 2, we present our
approach for detecting and measuring nebular emission lines, and the selection
criteria used to identify the metal-poor galaxies. We describe the
determination for the dust attenuation properties and the gas-phase oxygen
abundances in Section 3. In Section 4, we describe the methods for estimating
stellar masses and SFRs, and then compare the mass-metallicity relation (MZR)
and mass-metallicity-SFR relation with local $T_{e}$-based relation in Section
5. In addition, we discuss our results in the context of other studies in
Section 6. Finally, we summarize our main conclusions in Section 7.

Throughout this paper, we adopt a flat cosmology with $\Omega_{\Lambda}=0.7$,
$\Omega_{M}=0.3$, and $H_{0}=70$ km s-1 Mpc-1 to determine distance-dependent
measurements. For reference, we adopt $\hbox{$12\,+\,{\rm
log(O/H)}$}_{\sun}=8.69$ (Allende Prieto et al., 2001) for metallicity
measurements quoted against the solar value, ${\rm Z}_{\sun}$.

##  2 Sample selection

###  2.1 LAMOST dataset

The Large Sky Area Multi–Object Fiber Spectroscopic Telescope (LAMOST, also
called the Guo Shou Jing Telescope) is a special reflecting Schmidt telescope
with an effective aperture of 4 m and a field of view (FoV) of 5∘ (Wang et
al., 1996; Su & Cui, 2004; Zhao et al., 2012; Cui et al., 2012; Luo et al.,
2012). It is equipped with 4000 fibers, covering a wavelength range of 3800
$-$ 9000 $\mathrm{\AA}$ (Luo et al., 2015) at a resolving power R $\approx$
1800\. The LAMOST Data Release 3 (DR3), Data Release 4 (DR4) Q1 and Q2, based
on the past survey from October 2011 to February 2016, contain about three
million spectra with limiting magnitude of $r\approx$ 18.5 mag. The LAMOST 1D
pipeline classifies spectroscopic targets as galaxies, stars, and QSOs by
matching against observed SDSS spectral templates, see Luo et al. (2015) for
detail. 92,510 objects from the LAMOST catalog are spectroscopically
classified as galaxies (‘OBJTYPE’ = ‘GALAXY’).

###  2.2 Emission-line fluxes determination

According to Song et al. (2012) and Luo et al. (2015), LAMOST 1D spectra are
extracted from the CCD images used by the LAMOST 2D pipeline. The wavelength
calibration of each spectrum is accomplished by using arc lamp spectra lines,
with an average calibration error less than 0.02$\rm\AA$. The accuracy of the
relative flux calibration of LAMOST is above 90$\%$.

Assuming unimodal gaussian line profile, we obtain fluxes of strong emission
lines such as $\hbox{[O\,{\sc ii}]}\lambda 3727$, $\hbox{[O\,{\sc
iii}]}\lambda 4363$, H$\beta$, $\hbox{[O\,{\sc iii}]}\lambda\lambda
4959,5007$, H$\alpha$ and $\hbox{[S\,{\sc ii}]}\lambda\lambda 6717,6731$ by
fitting their line profile using the IDL package mpfit (Markwardt et al.,
2009). The expected location of emission lines are based on a priori redshift
determined by the [O iii] line. In addition, to estimate the signal-to-noise
ratios (S/N) of emission lines, we follow the calculation method in Ly et al.
(2014).

###  2.3 Sample selection

Among all the galaxies from the LAMOST ExtraGAlactic Surveys (LEGAS), we first
select a subsample of metal-poor galaxies with emission line flux ratios
$\hbox{[N\,{\sc ii}]}\lambda 6583/\hbox{H$\alpha$}\leq 0.1$, which consists of
665 galaxies. Among them, we identify 237 objects with $\hbox{[O\,{\sc
iii}]}\lambda 4363$ detection at $\geq 3\sigma$. We inspect these 237 objects
visually, and find 73 of them are false detections. We also exclude 115
objects that are $\rm\hii$ regions in nearby large galaxies using optical
images with SDSS DR12 skyserver
111http://skyserver.sdss.org/dr12/en/tools/chart/listinfo.aspx. Finally, we
check the right ascension and declination of the remaining sources, and note
that 1 object was observed twice by LAMOST. We keep the observation that has
better spectral quality.

As a consequence, our final sample consists of 48 galaxies, making up only
$\rm 0.05\%$ of all the LAMOST galaxies until DR4 Q2; this fraction is nearly
the same as SDSS (Ly et al., 2014). The median S/N of $\hbox{[O\,{\sc
iii}]}\lambda 4363$ is 6.1. We obtain the H$\beta$ equivalent width (EW) by
dividing the H$\beta$ flux by continuum spectral flux intensity, which is
assumed as the average value of observed flux intensities within 50$\rm\AA$
wide component around the H$\beta$ line. All of the galaxy spectra in our
sample show strong emission lines with a median (average) EW of H$\beta$ of
42.9 (53.5) $\mathrm{\AA}$. The EW distribution of H$\beta$ is shown in Figure
1.

Figure 1: The distribution of H$\beta$ equivalent widths in our sample. The
dashed line and dotted line represent the median and average equivalent widths
of 42.9 $\rm\mathrm{\AA}$ and 53.5 $\rm\mathrm{\AA}$, respectively.

To exclude possible AGN contamination, we use the BPT diagram (see Baldwin et
al., 1981; Veilleux & Osterbrock, 1987; Kewley et al., 2001; Kauffmann et al.,
2003). Figure 2 shows the distribution of our sample in the BPT diagram. The
grayscale 2D histogram shows the number density of LAMOST galaxies. The blue
dots represent 48 galaxies in our final sample, and the black crosses
represent 24 galaxies in our final sample that have also been spectrally
detected by SDSS. Among these 24 galaxies detected with SDSS, 19 galaxy
spectra also have the $\hbox{[O\,{\sc iii}]}\lambda 4363$ detections above
3$\sigma$; we will compare these 19 galaxy spectra from LAMOST and SDSS in
Section 6.1. The solid and dashed lines are the demarcation curves between
SFGs and AGNs derived by Kauffmann et al. (2003) and Kewley et al. (2001).
Galaxies located between the two lines are usually classified as composite
objects, which may host a mixture of star formation and AGN. It can be seen
that all of the galaxies in our final sample are located in the star-forming
region; however, this is unsurprising since we initially selected sources with
$\hbox{[N\,{\sc ii}]}\lambda 6583/\hbox{H$\alpha$}\leq 0.1$.

Figure 2:  BPT diagram for our metal-poor galaxy (MPG) sample and all the
LAMOST galaxies. The blue dots represent our final sample galaxies. The black
crosses represent these objects in our final sample that have also been
spectrally detected with SDSS. The grayscale 2D histogram shows the number
density of LAMOST galaxies. The solid and dashed lines are the demarcation
curves between SFGs and AGNs defined by Kauffmann et al. (2003) and Kewley et
al. (2001), respectively.

Figure 3 shows example spectra for eight galaxies in our sample that have both
been spectrally detected by LAMOST and SDSS. For each object, the left panel
shows the LAMOST spectrum, while the right panel shows the SDSS spectrum. All
of these spectra show strong emission lines such as $\hbox{[O\,{\sc
ii}]}\lambda 3727$ (for all LAMOST spectra and part of SDSS spectra),
H$\beta$, $\hbox{[O\,{\sc iii}]}\lambda\lambda 4959,5007$, H$\alpha$ and
$\hbox{[S\,{\sc ii}]}\lambda\lambda 6717,6731$. The inserted panels show the
zoomed spectra adjacent to $\hbox{[O\,{\sc iii}]}\lambda 4363$ lines. It can
be seen that the weak [O iii]$\lambda 4363$ lines are all detected in the
spectra of these galaxies.

Figure 3: Example spectra of objects in our sample that have both been
spectrally detected with LAMOST and SDSS. For every object, the left panel
shows LAMOST spectrum, while the right panel shows SDSS spectrum. Inserted
panels show the zoomed in spectra adjacent to the [O iii]$\lambda 4363$ lines.

##  3 Metallicity determination

###  3.1 Dust attenuation correction

We correct the emission-line fluxes for internal dust attenuation using the
Balmer decrement measurements, which estimate the dust extinction by
inspecting the change of Balmer line ratio, such as
$\hbox{H$\alpha$}/\hbox{H$\beta$}$, from intrinsic value. Generally, the
underlying stellar absorption in the Balmer lines should be well determined to
obtain a reliable emission line measurement (Hu et al., 2016). In this work,
we first subtract the underlying stellar continuum and stellar absorption for
each spectrum using the starlight spectral synthesis code (Cid Fernandes et
al., 2005). We assume the intrinsic flux ratio of
$(\hbox{H$\alpha$}/\hbox{H$\beta$})_{0}=2.86$ (Hummer & Storey, 1987) under
Case B recombination and use the Calzetti et al. (2000) reddening formalism to
derive the color excesses $E(B-V)$, and then correct the emission line fluxes.
In addition, we manually set the color excesses $E(B-V)$ to zero when the
$\hbox{H$\alpha$}/\hbox{H$\beta$}$ ratios are less than 2.86.

The resulting reddening-corrected emission line fluxes relative to H$\beta$
and color excesses are listed in Table 1. As showed in panel $a$ of Figure 4,
the measured dust extinction are very low with an average $E(B-V)$ value as
0.03 mag.

###  3.2 Metallicity calculation

With significant detection of [O iii]$\lambda 4363$, we can determine the
metallicity using the so-called $T_{e}$ method. In this work, we use the
python package pyneb 222http://www.iac.es/protecto/PyNeb/ (Luridiana et al.,
2015) to calculate the electron densities ($n_{e}$) and electron temperatures
($T_{e}$), which is evolved from the IRAF nebular package (Shaw & Dufour,
1995; Shaw et al., 1998). Nicholls et al. (2013) have demonstrated that the
electron temperatures would be overestimated, and thus the oxygen abundances
would be underestimated when using older collision strength data and
approximate temperature calibration methods from Izotov et al. (2006).
Therefore, we need to set the atomic recombination data and atomic collision
strength data before the calculation. We adopt the atomic recombination data
of Froese Fischer & Tachiev (2004) for $\rm O^{+}$, $\rm O^{++}$, and Tayal &
Zatsarinny (2010) for $\rm S^{+}$. For collision strength data, we adopt those
from Kisielius et al. (2009) for $\rm O^{+}$, Storey et al. (2014) for $\rm
O^{++}$, and Tayal & Zatsarinny (2010) for $\rm S^{+}$.

As encouraged in Luridiana et al. (2015), we use a cross-converging method to
calculate the electron temperatures of $\rm O^{++}$ regions
($T_{e}(\hbox{[O\,{\sc iii}]})$) and electron densities ($n_{e}$) with ratios
of $\hbox{[O\,{\sc iii}]}\lambda 4363/\hbox{[O\,{\sc iii}]}\lambda\lambda
4959,5007$ (Nicholls et al., 2013) and $\hbox{[S\,{\sc ii}]}\lambda
6717/\hbox{[S\,{\sc ii}]}\lambda 6731$ (Tayal & Zatsarinny, 2010). Once the
electron temperatures $T_{e}(\hbox{[O\,{\sc iii}]})$ and densities $n_{e}$ are
determined, we can obtain the ionic oxygen $\rm O^{++}$ abundances using the
$\hbox{[O\,{\sc iii}]}\lambda\lambda 4959,5007/\hbox{H$\beta$}$ ratios with
the relation derived from Izotov et al. (2006). In order to derive the
electron temperatures $T_{e}(\hbox{[O\,{\sc ii}]})$ of $\rm O^{+}$ regions, we
follow an iterative method used in Nicholls et al. (2014),

$T_{e}(\hbox{[O\,{\sc ii}]})=T_{e}(\hbox{[O\,{\sc
iii}]})\times\rm(3.0794-0.086924Z-0.1053Z^{2}+0.010225Z^{3}),$ (1)

where $\rm Z$ is the total oxygen abundance, $\rm 12+log(O/H)$. The
temperature $T_{e}(\hbox{[O\,{\sc ii}]})$ and abundance $\rm Z$ will converge
within five iterations, starting by using the $\rm O^{++}$ abundance as the
total oxygen abundance. Here, the $\rm O^{+}$ abundance is determined from
$T_{e}(\hbox{[O\,{\sc ii}]})$ and the $\hbox{[O\,{\sc ii}]}\lambda
3727/\hbox{H$\beta$}$ ratio using the Izotov et al. (2006) relation. Using
other methods from Garnett (1992) or López-Sánchez et al. (2012), we will get
a higher $T_{e}(\hbox{[O\,{\sc ii}]})$ about 0.02 dex and a lower metallicity
about 0.05 dex given a $T_{e}(\hbox{[O\,{\sc iii}]})$. Similarly, we will get
a higher $T_{e}(\hbox{[O\,{\sc ii}]})$ about 0.03 dex and thus get a lower
metallicity about 0.05 dex when adopt the standard two-zone temperature model
from Izotov et al. (2006) and Andrews & Martini (2013). In our final sample,
31 galaxies also have the $\hbox{[O\,{\sc ii}]}\lambda\lambda 7320,7330$
detections above 3$\sigma$. Using the $\hbox{[O\,{\sc ii}]}\lambda
3727/\hbox{[O\,{\sc ii}]}\lambda\lambda 7320,7330$ ratios to derive
$T_{e}(\hbox{[O\,{\sc ii}]})$, we will get lower $T_{e}(\hbox{[O\,{\sc ii}]})$
and higher metallicities, the differences between these average values on
$T_{e}(\hbox{[O\,{\sc ii}]})$ and metallicities are about 360 $\rm K$ and 0.06
dex, respectively.

To estimate the uncertainties of electron temperatures, electron densities and
oxygen abundances, we repeat the calculation 2000 times. For every object, we
produce a series of fluxes for each emission line with a Gaussian
distribution, assuming its average is the measured line flux and standard
deviation is the measured error. Then, our final temperature, density and
oxygen abundance are deemed to be the median values of these 2000
calculations, and the corresponding errors are estimated as the half of
$16\%\\--84\%$ range of their distributions. We list the final electron
temperatures, electron densities and oxygen abundances of our sample in Table
1.

Figure 4 shows the distributions of color excesses, electron densities,
electron temperatures and oxygen abundances. The electron densities and
temperatures in our sample range from $\rm 6.7$ to $\rm 475.0\ cm^{-3}$ and
$\rm(0.96\\--1.82)\times 10^{4}\ K$, with median values of $\rm 67.0\ cm^{-3}$
and $\rm 1.21\times 10^{4}\ K$, respectively. Their oxygen abundances range
from 7.63 to 8.46, with a median of 8.16. The only XMPG found in our sample is
ID26 with $\rm\hbox{$12\,+\,{\rm log(O/H)}$}=7.63\pm 0.01$, which has already
been found by Izotov et al. (2012a) with $\rm\hbox{$12\,+\,{\rm
log(O/H)}$}=7.64\pm 0.01$. Interestingly, galaxy ID33, also named as RC2
A1228+12, was regarded as an XMPG in Kunth & Östlin (2000) and Brorby et al.
(2014), but the metallicity $\rm\hbox{$12\,+\,{\rm log(O/H)}$}=7.70\pm 0.01$
indicates it is not an XMPG. This judgement was also supported by Pustilnik et
al. (2002) and Izotov et al. (2012b) with metallicity measurements of $\rm
7.73\pm 0.06$ and $\rm 7.70\pm 0.01$, respectively.

Figure 4: The distributions of color excesses, electron densities, electron
temperatures and oxygen abundances of our sample galaxies. The dashed lines
represent the median values of these parameters, 0.00 mag, 67.0 $\rm cm^{-3}$,
1.20 $\rm\times 10^{4}\ K$ and 8.16, respectively. The dotted lines represent
the average values 0.03 mag, 98.9 $\rm cm^{-3}$, 1.24 $\rm\times 10^{4}\ K$
and 8.13, respectively.

##  4 stellar masses and star formation rates

###  4.1 Stellar masses

To determine the galactic stellar masses of our sample galaxies, we use the
IDL code library fast developed by Kriek et al. (2009) to perform the spectral
energy distribution (SED) fitting. fast compares the photometry measurements
with stellar population synthesis models, based on the minimum $\chi^{2}$
template-fitting procedure, to determine mass-to-light ratios, which can be
used to estimate the stellar masses of galaxies. We use the stellar templates
of Bruzual & Charlot (2003) and a Chabrier (2003) initial mass function (IMF)
to synthesize magnitudes. These models span four metallicities (0.004, 0.008,
0.02, 0.05 ${\rm Z}_{\sun}$) and an exponentially decreasing star formation
models (SFR $\propto\rm e^{-t/\tau}$) with a step $\Delta log(\tau)=0.1$ from
$6.6\leq log(\tau)\leq 10.8$. We assume the dust attenuation law from Calzetti
et al. (2000) allowing $E(B-V)$ to vary from 0.0 to 2.0 and stellar population
ages ranging from 0 to 100 Gyr. To determine the uncertainties of stellar
masses, we use the Monte Carlo simulations and define the number of
simulations as 1000. We choose the confidence interval as 68$\%$.

Photometric measurements are collected from various survey catalogue. We adopt
values of modelmag magnitudes of $u,g,r,i$, and $z$ bands from SDSS DR12
photometry catalogue (Abazajian et al., 2004; Alam et al., 2015), magnitudes
of $J,H$, and $K_{s}$ bands from 2MASS All-Sky Point Source catalog (PSC) and
2MASS All-Sky Extended Source Catalog (XSC) (Skrutskie et al., 2006),
magnitudes of $W1$ (3.4 $\mu m$) and $W2$ (4.6 $\mu m$) from All WISE Source
Catalog (Wright et al., 2010), and magnitudes of FUV and NUV from $GALEX$
GR6/7 Data Release Catalog (Bianchi et al., 2014). However, not all of our
sample galaxies have these photometric measurements. For example, 45 galaxies
have FUV photometry, while 3 galaxies are not located in $GALEX$ surveyed
areas. For these three galaxies, we just use their magnitudes from $u$ band to
$W2$ band to perform the SED fitting. We find our sample galaxies spanning
three orders with $\rm 6.39\leq log(M/M_{\sun})\leq 9.27$. We should note that
we do not make the point spread function (PSF) matching for our photometric
data using same observation aperture, which may lead to some uncertainties in
stellar mass measurements. The average and median values on stellar mass
measurement uncertainties are 0.14 dex and 0.12 dex, respectively. However,
comparing our results with total stellar masses in MPA-JHU catalog (Kauffmann
et al., 2003; Brinchmann et al., 2004) for these galaxies included in MPA-JHU
catalog, we find the differences of average and median values are about 0.1
dex and 0.03 dex, respectively.

Table 1: The sample of metal-poor galaxies in LAMOST survey IDa |  RAb |  DECb | $z\rm^{b}$ |  $I(\lambda)/I(\hbox{H$\beta$})$ c | $I(\hbox{H$\beta$})\rm^{c}$ | $EW(\hbox{H$\beta$})\rm^{d}$ | $E(B-V)\rm^{e}$ | ${T_{e}\hbox{[O\,{\sc iii}]}\rm^{f}}$ | $n_{e}\rm^{f}$ | $\rm\hbox{$12\,+\,{\rm log(O/H)}$}_{\rm T_{e}}$ | $\rm log(M)$ | $\rm log(SFR)$ |  SDSSg
---|---|---|---|---|---|---|---|---|---|---|---|---|---
| (deg) | (deg) |  | $\hbox{[O\,{\sc ii}]}\lambda 3727$ | $\hbox{[O\,{\sc iii}]}\lambda 4363$ | $\hbox{[O\,{\sc iii}]}\lambda 4959$ | $\hbox{[O\,{\sc iii}]}\lambda 5007$ | H$\alpha$ | $\hbox{[S\,{\sc ii}]}\lambda 6717$ | $\hbox{[S\,{\sc ii}]}\lambda 6731$ |  | (Å) | (mag) |  ($10^{4}$K) |  ($\rm cm^{-3}$) |  |  ($M_{\sun}$) |  ($M_{\sun}yr^{-1}$) |
1 | 0.04352 | 4.93125 | 0.031 | 1.748 | 0.049 | 1.760 | 5.432 | 2.326 | 0.114 | 0.063 | 1761.90 | 81.46 | 0.00 | 1.16 | 38.78 | 8.22 | 8.250 | -0.556 | 0
|  |  |  | 0.054 | 0.013 | 0.018 | 0.051 | 0.022 | 0.007 | 0.007 | 15.87 | 0.22 | 0.01 | 0.10 | 42.91 | 0.12 | 0.050 | 0.009 |
2 | 0.22617 | 18.50614 | 0.055 | 2.205 | 0.030 | 1.267 | 3.924 | 2.135 | 0.178 | 0.133 | 7058.70 | 46.76 | 0.00 | 1.05 | 99.45 | 8.29 | 9.180 | 0.527 | 0
|  |  |  | 0.018 | 0.004 | 0.007 | 0.019 | 0.010 | 0.002 | 0.001 | 33.06 | 0.23 | 0.01 | 0.05 | 15.32 | 0.06 | 0.090 | 0.005 |
3 | 17.64580 | 2.11408 | 0.016 | 2.258 | 0.032 | 1.333 | 3.876 | 2.685 | 0.193 | 0.159 | 3282.40 | 34.17 | 0.00 | 1.07 | 234.91 | 8.28 | 8.720 | -0.782 | 0
|  |  |  | 0.018 | 0.004 | 0.004 | 0.010 | 0.007 | 0.002 | 0.002 | 8.34 | 0.31 | 0.01 | 0.05 | 22.81 | 0.05 | 0.120 | 0.003 |
4 | 19.02766 | 1.03444 | 0.035 | 2.164 | 0.072 | 1.335 | 3.977 | 2.054 | 0.130 | 0.108 | 439.67 | 43.01 | 0.00 | 1.47 | 272.39 | 7.88 | 7.600 | -1.185 | 1
|  |  |  | 0.759 | 0.021 | 0.022 | 0.059 | 0.028 | 0.007 | 0.007 | 5.88 | 0.26 | 0.01 | 0.19 | 142.65 | 0.16 | 0.175 | 0.014 |
5 | 23.00047 | -2.74083 | 0.018 | 1.681 | 0.056 | 1.632 | 5.063 | 2.362 | 0.177 | 0.152 | 797.69 | 62.08 | 0.00 | 1.19 | 303.92 | 8.16 | 7.880 | -1.382 | 0
|  |  |  | 0.062 | 0.010 | 0.016 | 0.043 | 0.021 | 0.008 | 0.006 | 6.63 | 0.48 | 0.01 | 0.08 | 110.75 | 0.09 | 0.180 | 0.009 |
6 | 31.87386 | 4.73166 | 0.011 | 3.279 | 0.019 | 1.089 | 3.269 | 2.579 | 0.267 | 0.193 | 5354.90 | 32.06 | 0.00 | 0.97 | 50.44 | 8.44 | 8.230 | -0.863 | 0
|  |  |  | 0.026 | 0.003 | 0.003 | 0.007 | 0.006 | 0.001 | 0.001 | 11.49 | 0.52 | 0.01 | 0.05 | 8.88 | 0.07 | 0.110 | 0.002 |
7 | 37.72624 | 1.91723 | 0.025 | 3.333 | 0.069 | 0.997 | 2.839 | 2.860 | 0.379 | 0.229 | 1143.89 | 12.62 | 0.20 | 1.82 | 30.48 | 7.67 | 8.050 | -0.931 | 0
|  |  |  | 1.790 | 0.035 | 0.031 | 0.068 | 0.067 | 0.017 | 0.016 | 26.25 | 0.58 | 0.02 | 0.37 | 34.73 | 0.25 | 0.125 | 0.024 |
8 | 39.07656 | 1.75273 | 0.023 | 2.130 | 0.053 | 1.828 | 5.206 | 2.860 | 0.200 | 0.144 | 6174.59 | 55.21 | 0.25 | 1.23 | 79.89 | 8.17 | 8.020 | -0.187 | 0
|  |  |  | 0.037 | 0.009 | 0.018 | 0.046 | 0.026 | 0.009 | 0.008 | 54.01 | 0.07 | 0.01 | 0.06 | 65.41 | 0.06 | 0.015 | 0.009 |
9 | 43.15004 | 19.68750 | 0.029 | 3.078 | 0.044 | 1.270 | 3.582 | 1.836 | 0.174 | 0.128 | 4755.70 | 27.36 | 0.00 | 1.22 | 73.19 | 8.15 | 8.010 | -0.304 | 0
|  |  |  | 0.015 | 0.003 | 0.003 | 0.008 | 0.004 | 0.002 | 0.002 | 10.31 | 0.16 | 0.01 | 0.04 | 21.25 | 0.04 | 0.100 | 0.002 |
10 | 47.66477 | 5.23287 | 0.064 | 2.962 | 0.015 | 1.111 | 3.332 | 2.853 | 0.242 | 0.182 | 3494.70 | 35.56 | 0.00 | 0.96 | 113.42 | 8.44 | 9.150 | 0.199 | 0
|  |  |  | 0.053 | 0.005 | 0.011 | 0.029 | 0.025 | 0.002 | 0.002 | 30.42 | 0.23 | 0.01 | 0.07 | 15.29 | 0.10 | 0.140 | 0.009 |
11 | 47.91879 | 2.57282 | 0.020 | 1.685 | 0.098 | 2.115 | 6.153 | 2.582 | 0.139 | 0.086 | 6170.00 | 103.02 | 0.00 | 1.37 | 15.47 | 8.05 | 8.070 | -0.389 | 0
|  |  |  | 0.021 | 0.003 | 0.005 | 0.013 | 0.005 | 0.001 | 0.001 | 12.86 | 6.06 | 0.01 | 0.00 | 4.26 | 0.00 | 0.035 | 0.002 |
12 | 49.35046 | 3.50387 | 0.039 | 2.179 | 0.047 | 1.523 | 4.753 | 2.860 | 0.177 | 0.129 | 2297.92 | 81.85 | 0.09 | 1.17 | 67.05 | 8.19 | 8.350 | -0.161 | 0
|  |  |  | 0.181 | 0.009 | 0.010 | 0.027 | 0.016 | 0.005 | 0.004 | 12.85 | 0.73 | 0.01 | 0.08 | 44.49 | 0.08 | 0.140 | 0.006 |
13 | 51.95898 | 1.02635 | 0.109 | 2.973 | 0.030 | 1.111 | 3.332 | 2.816 | 0.443 | 0.300 | 1148.30 | 45.87 | 0.00 | 1.11 | 6.72 | 8.25 | 9.020 | 1.945 | 1
|  |  |  | 1.280 | 0.232 | 0.193 | 0.458 | 0.403 | 0.154 | 0.132 | 151.78 | 0.21 | 0.01 | 0.06 | 7.13 | 0.07 | 0.395 | 0.005 |
14 | 123.48118 | 23.14714 | 0.015 | 3.171 | 0.052 | 1.245 | 3.601 | 2.339 | 0.226 | 0.161 | 1515.70 | 50.33 | 0.00 | 1.33 | 45.20 | 8.06 | 6.600 | -1.290 | 0
|  |  |  | 0.077 | 0.008 | 0.007 | 0.017 | 0.011 | 0.003 | 0.003 | 6.85 | 0.31 | 0.01 | 0.09 | 29.09 | 0.08 | 0.305 | 0.005 |
15 | 129.35571 | 37.51241 | 0.042 | 2.942 | 0.050 | 1.118 | 3.206 | 2.639 | 0.340 | 0.230 | 942.03 | 30.75 | 0.00 | 1.34 | 25.58 | 8.01 | 8.550 | -0.561 | 1
|  |  |  | 0.178 | 0.018 | 0.017 | 0.038 | 0.032 | 0.009 | 0.009 | 10.81 | 0.22 | 0.01 | 0.21 | 26.69 | 0.18 | 0.195 | 0.012 |
16 | 136.71599 | 41.36413 | 0.135 | 3.205 | 0.056 | 1.107 | 3.224 | 2.166 | 0.231 | 0.182 | 446.71 | 32.70 | 0.00 | 1.43 | 187.71 | 7.95 | 9.270 | 0.031 | 1
|  |  |  | 0.077 | 0.016 | 0.030 | 0.070 | 0.045 | 0.012 | 0.008 | 9.18 | 0.42 | 0.02 | 0.17 | 100.22 | 0.14 | 0.280 | 0.021 |
17 | 139.46461 | 40.97089 | 0.024 | 2.608 | 0.031 | 1.403 | 3.912 | 2.207 | 0.262 | 0.189 | 721.63 | 42.77 | 0.00 | 1.06 | 52.69 | 8.32 | 8.110 | -1.160 | 0
|  |  |  | 0.075 | 0.013 | 0.015 | 0.035 | 0.020 | 0.004 | 0.004 | 6.30 | 0.10 | 0.01 | 0.14 | 23.70 | 0.17 | 0.095 | 0.009 |
18 | 139.95418 | 4.48470 | 0.012 | 2.452 | 0.057 | 1.376 | 4.164 | 2.338 | 0.227 | 0.167 | 2868.10 | 34.57 | 0.00 | 1.32 | 73.19 | 8.04 | 8.070 | -1.211 | 0
|  |  |  | 0.194 | 0.015 | 0.016 | 0.041 | 0.023 | 0.005 | 0.004 | 27.82 | 0.09 | 0.01 | 0.14 | 38.93 | 0.13 | 0.180 | 0.010 |
19 | 140.17699 | 5.73677 | 0.038 | 1.029 | 0.082 | 2.450 | 7.272 | 2.860 | 0.100 | 0.071 | 11516.86 | 96.12 | 0.23 | 1.20 | 38.78 | 8.22 | 8.220 | 0.525 | 0
|  |  |  | 0.014 | 0.003 | 0.007 | 0.019 | 0.008 | 0.001 | 0.001 | 30.64 | 0.31 | 0.01 | 0.02 | 23.27 | 0.02 | 0.205 | 0.003 |
20 | 140.92796 | 3.36689 | 0.012 | 2.760 | 0.050 | 1.340 | 3.788 | 2.312 | 0.210 | 0.150 | 1090.50 | 34.17 | 0.00 | 1.30 | 52.69 | 8.07 | 7.330 | -1.629 | 1
|  |  |  | 0.086 | 0.014 | 0.015 | 0.035 | 0.021 | 0.006 | 0.005 | 9.79 | 0.16 | 0.01 | 0.14 | 41.58 | 0.12 | 0.355 | 0.010 |
21 | 142.63454 | 34.43079 | 0.017 | 1.689 | 0.045 | 1.443 | 4.180 | 2.860 | 0.190 | 0.104 | 1297.69 | 34.84 | 0.01 | 1.10 | 56.29 | 8.24 | 7.740 | -1.114 | 1
|  |  |  | 0.037 | 0.010 | 0.012 | 0.029 | 0.020 | 0.006 | 0.006 | 8.78 | 0.21 | 0.01 | 0.10 | 66.58 | 0.11 | 0.300 | 0.007 |
22 | 145.71992 | 35.79055 | 0.015 | 1.676 | 0.055 | 1.538 | 4.217 | 2.210 | 0.166 | 0.081 | 2180.30 | 100.80 | 0.00 | 1.21 | 19.54 | 8.10 | 7.339 | -1.147 | 1
|  |  |  | 0.021 | 0.005 | 0.006 | 0.015 | 0.008 | 0.002 | 0.002 | 7.31 | 0.15 | 0.01 | 0.03 | 10.87 | 0.03 | 0.074 | 0.004 |
23 | 146.00691 | 50.87919 | 0.038 | 2.683 | 0.028 | 1.048 | 2.923 | 2.471 | 0.320 | 0.235 | 1322.90 | 37.23 | 0.00 | 1.12 | 73.19 | 8.19 | 8.960 | -0.485 | 1
|  |  |  | 0.036 | 0.009 | 0.008 | 0.018 | 0.015 | 0.004 | 0.003 | 7.63 | 0.64 | 0.01 | 0.11 | 22.38 | 0.13 | 0.185 | 0.006 |
24 | 147.03999 | 2.52892 | 0.021 | 2.681 | 0.032 | 1.348 | 4.014 | 2.844 | 0.279 | 0.194 | 2646.10 | 35.59 | 0.00 | 1.18 | 30.48 | 8.19 | 8.270 | -0.638 | 1
|  |  |  | 0.086 | 0.009 | 0.010 | 0.026 | 0.019 | 0.005 | 0.006 | 16.94 | 0.09 | 0.01 | 0.10 | 26.41 | 0.10 | 0.175 | 0.007 |
25 | 148.70041 | 38.45017 | 0.017 | 3.040 | 0.024 | 0.939 | 2.683 | 2.440 | 0.370 | 0.269 | 1971.30 | 29.46 | 0.00 | 1.09 | 62.79 | 8.24 | 8.320 | -1.003 | 1
|  |  |  | 0.036 | 0.008 | 0.008 | 0.016 | 0.014 | 0.004 | 0.004 | 11.02 | 0.17 | 0.01 | 0.13 | 17.34 | 0.15 | 0.070 | 0.006 |
26 | 154.10216 | 37.91277 | 0.004 | 0.687 | 0.097 | 1.346 | 4.106 | 2.860 | 0.074 | 0.056 | 3778.46 | 138.04 | 0.01 | 1.64 | 115.85 | 7.63 | 6.550 | -2.029 | 1
|  |  |  | 0.022 | 0.003 | 0.003 | 0.007 | 0.005 | 0.001 | 0.002 | 6.15 | 0.19 | 0.01 | 0.02 | 52.03 | 0.01 | 0.070 | 0.002 |
27 | 157.45534 | 16.18091 | 0.011 | 3.230 | 0.040 | 1.187 | 3.468 | 2.007 | 0.278 | 0.203 | 1701.80 | 27.67 | 0.00 | 1.22 | 64.22 | 8.16 | 8.430 | -1.548 | 1
|  |  |  | 0.059 | 0.010 | 0.012 | 0.028 | 0.016 | 0.005 | 0.005 | 13.14 | 0.21 | 0.01 | 0.11 | 33.81 | 0.11 | 0.005 | 0.008 |
28 | 161.47824 | 1.06829 | 0.026 | 2.243 | 0.045 | 1.549 | 4.167 | 2.860 | 0.216 | 0.161 | 22426.28 | 108.84 | 0.18 | 1.17 | 91.11 | 8.19 | 7.860 | 0.478 | 1
|  |  |  | 0.012 | 0.002 | 0.003 | 0.006 | 0.004 | 0.001 | 0.001 | 33.64 | 0.24 | 0.01 | 0.02 | 7.99 | 0.02 | 0.005 | 0.001 |
29 | 162.63853 | 22.31531 | 0.046 | 2.084 | 0.052 | 1.394 | 3.964 | 2.826 | 0.313 | 0.218 | 1269.00 | 39.66 | 0.00 | 1.25 | 16.87 | 8.07 | 8.360 | -0.308 | 1
|  |  |  | 0.030 | 0.007 | 0.008 | 0.019 | 0.014 | 0.004 | 0.004 | 6.06 | 0.19 | 0.01 | 0.06 | 15.18 | 0.06 | 0.305 | 0.005 |
30 | 163.09535 | 32.63737 | 0.005 | 2.665 | 0.028 | 1.020 | 2.611 | 2.412 | 0.319 | 0.225 | 1828.20 | 20.58 | 0.00 | 1.18 | 22.43 | 8.12 | 7.640 | -2.135 | 1
|  |  |  | 0.022 | 0.004 | 0.004 | 0.007 | 0.006 | 0.002 | 0.001 | 4.74 | 0.06 | 0.01 | 0.06 | 8.89 | 0.06 | 0.110 | 0.002 |
31 | 170.34760 | 6.66713 | 0.009 | 2.816 | 0.064 | 1.052 | 3.069 | 2.860 | 0.257 | 0.193 | 1169.43 | 27.91 | 0.01 | 1.30 | 99.45 | 8.03 | 7.410 | -1.762 | 1
|  |  |  | 0.073 | 0.013 | 0.012 | 0.027 | 0.025 | 0.006 | 0.006 | 9.96 | 0.05 | 0.01 | 0.15 | 51.12 | 0.14 | 0.280 | 0.009 |
32 | 186.62852 | 28.84698 | 0.027 | 3.039 | 0.046 | 0.929 | 2.844 | 2.860 | 0.423 | 0.315 | 1498.23 | 25.58 | 0.03 | 1.44 | 89.21 | 7.91 | 8.650 | -0.727 | 0
|  |  |  | 0.062 | 0.012 | 0.011 | 0.025 | 0.024 | 0.007 | 0.006 | 12.52 | 0.35 | 0.01 | 0.15 | 32.31 | 0.12 | 0.075 | 0.009 |
33 | 187.70251 | 12.04523 | 0.004 | 1.118 | 0.109 | 1.565 | 4.442 | 2.697 | 0.109 | 0.080 | 4437.80 | 85.03 | 0.00 | 1.67 | 73.19 | 7.70 | 6.390 | -1.976 | 1
|  |  |  | 0.016 | 0.002 | 0.003 | 0.008 | 0.005 | 0.001 | 0.001 | 7.57 | 0.16 | 0.01 | 0.02 | 26.96 | 0.01 | 0.070 | 0.002 |
34 | 188.68443 | 10.71915 | 0.032 | 2.124 | 0.052 | 1.531 | 4.283 | 2.740 | 0.185 | 0.171 | 1392.00 | 67.30 | 0.00 | 1.23 | 464.63 | 8.13 | 8.240 | -0.583 | 1
|  |  |  | 0.017 | 0.004 | 0.005 | 0.012 | 0.008 | 0.002 | 0.002 | 3.93 | 0.43 | 0.01 | 0.04 | 34.42 | 0.04 | 0.020 | 0.003 |
35 | 189.23994 | 10.13030 | 0.027 | 1.485 | 0.039 | 1.366 | 4.083 | 2.856 | 0.249 | 0.183 | 445.10 | 37.11 | 0.00 | 1.13 | 85.32 | 8.14 | 8.640 | -1.205 | 1
|  |  |  | 0.064 | 0.016 | 0.019 | 0.049 | 0.034 | 0.008 | 0.008 | 5.16 | 0.31 | 0.01 | 0.17 | 62.00 | 0.19 | 0.225 | 0.012 |
36 | 189.52870 | 10.16557 | 0.004 | 0.642 | 0.099 | 1.953 | 5.567 | 2.703 | 0.089 | 0.062 | 2579.20 | 156.19 | 0.00 | 1.43 | 16.87 | 7.90 | 6.590 | -2.177 | 1
|  |  |  | 0.019 | 0.003 | 0.004 | 0.011 | 0.006 | 0.001 | 0.001 | 5.14 | 0.05 | 0.01 | 0.02 | 15.98 | 0.01 | 0.035 | 0.002 |
37 | 189.73721 | 38.09029 | 0.007 | 2.820 | 0.032 | 1.046 | 2.960 | 2.729 | 0.367 | 0.257 | 1454.40 | 11.09 | 0.00 | 1.19 | 20.55 | 8.13 | 8.320 | -1.887 | 1
|  |  |  | 0.040 | 0.007 | 0.007 | 0.014 | 0.013 | 0.004 | 0.004 | 6.43 | 0.23 | 0.01 | 0.09 | 15.20 | 0.09 | 0.060 | 0.005 |
38 | 196.86958 | 54.44713 | 0.033 | 2.544 | 0.035 | 1.524 | 4.133 | 2.860 | 0.242 | 0.190 | 10397.45 | 73.00 | 0.03 | 1.08 | 162.86 | 8.30 | 8.590 | 0.381 | 1
|  |  |  | 0.014 | 0.003 | 0.004 | 0.009 | 0.006 | 0.001 | 0.001 | 22.36 | 0.13 | 0.01 | 0.03 | 9.56 | 0.03 | 0.075 | 0.002 |
39 | 198.22404 | 17.20867 | 0.052 | 2.129 | 0.049 | 1.436 | 4.157 | 2.860 | 0.210 | 0.150 | 3750.41 | 70.01 | 0.21 | 1.21 | 57.52 | 8.12 | 8.020 | 0.285 | 1
|  |  |  | 0.071 | 0.014 | 0.016 | 0.039 | 0.027 | 0.005 | 0.006 | 34.19 | 0.11 | 0.01 | 0.13 | 44.45 | 0.14 | 0.155 | 0.009 |
40 | 212.67758 | 38.71842 | 0.025 | 3.061 | 0.028 | 1.114 | 3.227 | 2.860 | 0.378 | 0.274 | 1216.35 | 23.52 | 0.00 | 1.09 | 52.69 | 8.27 | 8.370 | -0.796 | 1
|  |  |  | 0.041 | 0.008 | 0.008 | 0.019 | 0.017 | 0.005 | 0.004 | 6.84 | 0.26 | 0.01 | 0.10 | 22.31 | 0.12 | 0.160 | 0.006 |
41 | 220.85265 | 28.30123 | 0.013 | 2.490 | 0.029 | 1.199 | 3.575 | 2.551 | 0.291 | 0.206 | 2186.30 | 34.68 | 0.00 | 1.07 | 27.92 | 8.28 | 8.210 | -1.161 | 0
|  |  |  | 0.038 | 0.007 | 0.007 | 0.018 | 0.013 | 0.003 | 0.003 | 10.51 | 0.67 | 0.01 | 0.09 | 16.76 | 0.11 | 0.120 | 0.005 |
42 | 222.59503 | 11.40265 | 0.006 | 1.260 | 0.036 | 1.543 | 4.234 | 1.543 | 0.115 | 0.214 | 2445.60 | 68.75 | 0.00 | 1.10 | 475.04 | 8.39 | 7.500 | -1.823 | 0
|  |  |  | 12.190 | 0.007 | 0.008 | 0.019 | 0.007 | 0.003 | 0.002 | 10.98 | 0.37 | 0.01 | 0.07 | 48.24 | 0.25 | 0.080 | 0.005 |
43 | 321.52011 | 8.68640 | 0.010 | 1.850 | 0.061 | 1.617 | 4.840 | 2.809 | 0.200 | 0.144 | 2200.90 | 49.17 | 0.00 | 1.24 | 44.22 | 8.12 | 7.900 | -1.386 | 0
|  |  |  | 0.030 | 0.007 | 0.009 | 0.023 | 0.014 | 0.002 | 0.002 | 10.48 | 0.21 | 0.01 | 0.06 | 22.79 | 0.06 | 0.100 | 0.005 |
44 | 325.30099 | 8.68733 | 0.032 | 3.758 | 0.033 | 1.055 | 3.104 | 2.678 | 0.343 | 0.248 | 1105.70 | 23.31 | 0.00 | 1.19 | 55.05 | 8.20 | 8.600 | -0.675 | 0
|  |  |  | 0.032 | 0.007 | 0.006 | 0.016 | 0.012 | 0.003 | 0.003 | 4.89 | 0.34 | 0.01 | 0.09 | 15.64 | 0.09 | 0.325 | 0.004 |
45 | 327.59015 | 7.60371 | 0.027 | 1.501 | 0.094 | 1.929 | 5.831 | 2.420 | 0.109 | 0.082 | 1003.90 | 75.16 | 0.00 | 1.37 | 116.11 | 8.02 | 8.030 | -0.952 | 0
|  |  |  | 0.098 | 0.009 | 0.012 | 0.033 | 0.014 | 0.003 | 0.004 | 5.56 | 0.24 | 0.01 | 0.05 | 72.01 | 0.04 | 0.130 | 0.006 |
46 | 336.10513 | 6.25363 | 0.016 | 2.475 | 0.054 | 1.631 | 4.790 | 2.327 | 0.156 | 0.130 | 2647.40 | 63.85 | 0.00 | 1.20 | 260.72 | 8.19 | 8.200 | -0.962 | 0
|  |  |  | 0.010 | 0.007 | 0.008 | 0.020 | 0.010 | 0.003 | 0.003 | 10.75 | 0.34 | 0.01 | 0.05 | 53.29 | 0.05 | 0.160 | 0.004 |
47 | 341.07831 | 5.36256 | 0.006 | 2.681 | 0.046 | 1.436 | 4.053 | 2.669 | 0.228 | 0.177 | 6841.20 | 55.27 | 0.00 | 1.19 | 154.47 | 8.18 | 7.960 | -1.344 | 0
|  |  |  | 0.022 | 0.003 | 0.003 | 0.007 | 0.005 | 0.001 | 0.001 | 11.57 | 0.46 | 0.01 | 0.02 | 10.14 | 0.02 | 0.190 | 0.002 |
48 | 352.58768 | 5.52682 | 0.014 | 2.313 | 0.057 | 1.646 | 4.242 | 2.860 | 0.234 | 0.173 | 13399.27 | 66.73 | 0.10 | 1.26 | 79.89 | 8.10 | 7.800 | -0.306 | 0
|  |  |  | 0.018 | 0.003 | 0.003 | 0.007 | 0.005 | 0.001 | 0.002 | 21.79 | 0.29 | 0.01 | 0.02 | 14.80 | 0.02 | 0.010 | 0.002 |
Table 1: – continued from previous page

Notes: — Basic information, emission line fluxes, electron temperatures and
oxygen abundances for our sample galaxies. For every object, the first
(second) line presents the parameter (error) values.

a ’ID’ is the serial number for every object and it will be referred to
throughout this paper.

b The right ascension (J2000) and declination (J2000) of our sample galaxies
are given in units of degrees. The RA, DEC, and redshift are obtained from the
header of the spectral FITS files.

c Reddening corrected emission line fluxes for our sample galaxies measured
from the LAMOST spectra are relative to H$\beta$. The H$\beta$ fluxes are
reported in units of $\rm 10^{-17}erg\ s^{-1}cm^{-2}$.

d The H$\beta$ equivalent widths are given in units of $\rm\AA$, assuming the
mean values of observed flux intensities within 50$\rm\AA$ wide component
around the H$\beta$ as the continuum spectral flux intensities.

e The nebular color excesses are derived from the observed flux ratios
$\hbox{H$\alpha$}/\hbox{H$\beta$}$, and are assumed to be zero when the
observed flux ratios $\hbox{H$\alpha$}/\hbox{H$\beta$}$ are less than 2.86.

f Electron temperatures are computed from the oxygen emission line ratios
$\hbox{[O\,{\sc iii}]}\lambda\lambda 4959,5007/\hbox{[O\,{\sc iii}]}\lambda
4363$. Electron densities are calculated from an iterative process with
$\hbox{[O\,{\sc iii}]}\lambda\lambda 4959,5007/\hbox{[O\,{\sc iii}]}\lambda
4363$ and $\hbox{[S\,{\sc ii}]}\lambda 6717/\hbox{[S\,{\sc ii}]}\lambda 6731$
ratios.

g The flag numbers indicate the spectral detected states for our objects with
SDSS. ”1” (”0”) represent this object has (not) been spectroscopically
detected by SDSS.

###  4.2 Star formation rates

In this work, we use the H$\alpha$ emission line luminosities to determine
dust-corrected SFRs, assuming a Chabrier (2003) IMF and solar metallicity. The
SFR can be calculated from H$\alpha$ luminosity as:

${\rm SFR(M_{\sun}yr^{-1})}=R\ {\rm\times\ L(erg\ s^{-1})},$ (2)

where $R=4.4\ \times\ {\rm 10^{-42}}$. However, the latest work of Ly et al.
(2016a) demonstrated that the above parameter $R$ would overestimate the SFR
at lower metallicities, and gave the metallicity-dependent parameter $R$ as:

${\rm log}(R)={\rm
log(\frac{SFR}{L(\hbox{H$\alpha$})})}=-41.34+0.39y+0.127y^{2},$ (3)

where $y=\rm log(O/H)+3.31$. Above all, the final stellar masses and SFRs in
our sample are listed in Table 1.

##  5 The Mass–Metallicity and Mass–Metallicity–SFR Relations

###  5.1 The mass-metallicity relation

In panel $a$ of Figure 5, we plot the mass-metallicity relation (MZR) with
$T_{e}$-based metallicities for our sample. These dot symbols of our galaxies
are colour-coded by their SFRs. For comparison, we also show the MZRs obtained
by Andrews & Martini (2013) and Berg et al. (2012) for their galaxy sample in
local universe, which are shown as solid and dotted-dashed black lines, based
on $T_{e}$ metallicity calculation.

The MZR in Berg et al. (2012) is a simple linear fit for a small sample of low
luminosity metal-poor galaxies with stellar masses $\rm log(M/M_{\sun})$
ranging from 5.9 to 9.15. As is shown in panel $a$, the metallicities of our
metal-poor galaxies are systematic higher than the MZR in Berg et al. (2012)
by about 0.25 dex. The MZR of Andrews & Martini (2013) is fitted with a
asymptotic logarithmic formula for about two hundred thousands nearby star-
forming galaxies in stellar mass from $\rm log(M/M_{\sun})=7.4\\--10.5$. Most
of our galaxies are in good agreement with the MZR in Andrews & Martini
(2013), the average and median values of residuals between metallicities and
MZR are 0.0015 dex and 0.025 dex, respectively. We find that the scatter in
the MZR from LAMOST data, relative to the MZR of Andrews & Martini (2013), is
0.28 dex.

Figure 5: The $T_{e}$ method mass-metallicity relation and fundamental
metallicity relation for our sample galaxies. In both panels, these dot
symbols of our galaxies are colour-coded by their SFRs. Panel $a$: the solid
and dotted-dashed black lines represent these MZRs derived from nearby star
forming galaxies by Andrews & Martini (2013) and Berg et al. (2012),
respectively. Panel $b$: the solid black line represents the FMR relation
derived by Andrews & Martini (2013), which assumed the coefficient on $\rm
log(SFR)$ is 0.66 with $\rm\mu_{0.66}=log(M)-0.66log(SFR)$. The uncertainties
of stellar masses are presented at 68$\%$ confidence interval limits.

###  5.2 Mass-metallicity-SFR relation

The mass-metallicity-SFR relation, also referred to as the fundamental
metallicity relation (FMR), is proposed by Mannucci et al. (2010) to describe
the anti-correlation between metallicity and SFR at fixed stellar mass.
Mannucci et al. (2010) defined a new quantity $\rm\mu_{\alpha}=log(M)-\alpha
log(SFR)$ to minimize the dispersion in MZR for local galaxies. Using the
semi-empirical “strong-line” metallicity calibration of Maiolino et al.
(2008), Mannucci et al. (2010) yielded $\rm\alpha=0.32$. However, Andrews &
Martini (2013) found a new value of $\rm\alpha=0.66$ based on the $T_{e}$
metallicity calculation method. In this work, we assume the value of
$\rm\alpha=0.66$, since metallicities of our sample galaxy are also determined
with $T_{e}$ method.

The panel $b$ of Figure 5 shows the FMR for our metal-poor galaxies. The solid
black line represents the FMR relation derived by Andrews & Martini (2013).
Most of our galaxies are consistent with the FMR, the average and median
values of the residuals between metallicities and FMR are 0.002 dex and 0.009
dex, respectively. The scatter in the FMR from LAMOST data, relative to the
FMR of Andrews & Martini (2013), is about 0.24 dex.

##  6 discussion

###  6.1 Comparison with SDSS spectrum

Among our metal-poor galaxy sample, 24 galaxies are also spectrally detected
by SDSS, and are marked with flag ”1” in ’SDSS’ column of Table 1. We select
these galaxies from SDSS DR12 by matching the RA and DEC with our sample
within one arcsec. We also obtain the emission line fluxes from these 24 SDSS
galaxy spectra and find that there are 19 spectra with $\hbox{[O\,{\sc
iii}]}\lambda 4363$ detections above 3$\sigma$. Similarly, we calculate their
metallicities with the $T_{e}$ method. Figure 6 shows the comparisons of S/Ns
for weak $\hbox{[O\,{\sc iii}]}\lambda 4363$ lines, [O iii] and [S ii] line
fluxes ratios ($\hbox{[O\,{\sc iii}]}\lambda\lambda 4959,5007/\hbox{[O\,{\sc
iii}]}\lambda 4363$, $\hbox{[S\,{\sc ii}]}\lambda 6717/\hbox{[S\,{\sc
ii}]}\lambda 6731$), electron temperatures ($T_{e}(\hbox{[O\,{\sc iii}]})$),
electron densities ($n_{e}$) and oxygen abundances derived from LAMOST spectra
and from SDSS spectra. The quality of the SDSS spectra are generally better
than those from LAMOST with higher S/N on the weak $\hbox{[O\,{\sc
iii}]}\lambda 4363$. Panels $b$ and $d$ present strong correlation for [O iii]
ratios and electron temperatures between the LAMOST and SDSS measurements.
Although there are several objects that have large dispersion in the
comparison for [S ii] ratios and electron densities, the differences between
the final oxygen abundances from these two measurements are less than 0.01
dex.

Figure 6: The comparisons of signal noise ratios for weak [O iii]$\lambda
4363$ lines, [O iii] line fluxes ratios ($R\hbox{[O\,{\sc
iii}]}=\hbox{[O\,{\sc iii}]}\lambda\lambda 4959,5007/\hbox{[O\,{\sc
iii}]}\lambda 4363$), [S ii] line fluxes ratios ($R\hbox{[S\,{\sc
ii}]}=\hbox{[S\,{\sc ii}]}\lambda 6717/\hbox{[S\,{\sc ii}]}\lambda 6731$),
electron temperatures, electron densities and oxygen abundances derived from
LAMOST spectra and from SDSS spectra for 19 galaxies in our sample. The solid
line indicate equality between the LAMOST and SDSS measurements.

###  6.2 Comparison with other [O iii]$\lambda 4363$ galaxy samples

All of galaxies in our sample are selected from the local universe ($0.004\leq
z\leq 0.14$), and have stellar masses spanning three orders with $\rm 6.39\leq
log(M/M_{\sun})\leq 9.27$. The only XMPG is detected with $\hbox{$12\,+\,{\rm
log(O/H)}$}=7.63\pm 0.01$ in our sample, however, it has already been found by
Izotov et al. (2012a). In the past decades, there have been many efforts to
search for $\hbox{[O\,{\sc iii}]}\lambda 4363$ galaxies and XMPGs in local
universe. For example, Kniazev et al. (2003) discovered 12 XMPGs with $\rm
7.13\leq\hbox{$12\,+\,{\rm log(O/H)}$}\leq 7.64$ using SDSS spectroscopy.
Izotov et al. (2006) found 6 new XMPGs in 310 $\hbox{[O\,{\sc iii}]}\lambda
4363$ galaxies from SDSS DR3. And Berg et al. (2012) also researched 19
$\hbox{[O\,{\sc iii}]}\lambda 4363$ low luminosity galaxies with MMT
telescope. Additionally, for the intermediate and high redshift universe,
Kakazu et al. (2007) mapped 12 XMPGs to $z=1.0$ with Keck II DEIMOS. Ly et al.
(2014) identified 4 XMPGs in 20 emission-line galaxies with $\hbox{[O\,{\sc
iii}]}\lambda 4363$ at $z=0.065-0.90$ by MMT and Keck telescope. Amorín et al.
(2014) also discovered 4 XMPGs from 31 low-luminosity extreme emission line
galaxies out to $z=0.9$ in the VIMOS Ultra-Deep Survey. Recently, Ly et al.
(2015) found 28 metal-poor galaxies with stellar mass spanning $\rm 7.1\times
10^{7}-2.2\times 10^{9}M_{\sun}$ in DEEP2 at redshift $z\sim 0.8$. Ly et al.
(2016a) also presented a larger sample of 164 galaxies with weak
$\hbox{[O\,{\sc iii}]}\lambda 4363$ line at $z=0.1\\--1.0$ from the “Metal
Abundances across Cosmic Time” survey. Compared with these samples, the galaxy
number in our sample is small, which may be caused by a limiting magnitude
selection of LAMOST. However, the fraction of galaxies with $\hbox{[O\,{\sc
iii}]}\lambda 4363$ detections in LAMOST data is nearly same as that in SDSS.

###  6.3 MZR and FMR

The MZR relation, which was established originally by Lequeux et al. (1979)
and developed by Garnett & Shields (1987), Skillman et al. (1989), Brodie &
Huchra (1991), Zaritsky et al. (1994), Tremonti et al. (2004), indicates that
the metallicities of galaxies correlate with their stellar masses. Taking SFR
into consideration, Mannucci et al. (2010) found that metallicity decreases
with increasing SFR at low stellar mass, while does not depend on SFR at high
stellar mass ($\rm log(M/M_{\sun})\geq 10.7$). However, Yates et al. (2012)
suggested that high-mass ($\rm log(M/M_{\sun})\geq 10.4$) galaxies have lower
metallicities when their SFRs are lower. These different results may be caused
by different metallicity calculation methods. In addition, the MZR is also
affected by other physical parameters, such as stellar age and gas fraction.
Lian et al. (2015) found that the metallicity is strongly dependent on the
$D\rm_{n}(4000)$, which interpreted galaxies with older stellar ages as having
higher metallicities at a fixed stellar mass. Hughes et al. (2013) found that
galaxies with higher gas fraction have lower metallicities at a fixed mass.
Lara-López et al. (2010) and Mannucci et al. (2010) argued that the MZR is in
fact a projection of FMR. In the past years, many efforts (e.g., Mannucci et
al. (2010); Berg et al. (2012); Andrews & Martini (2013); Salim et al. (2014);
Ly et al. (2015, 2016b)) have been made to explore the MZR and FMR feasibility
from low mass to high mass, as well as the evolution with redshift. In the
local universe, the metallicity increases with increasing stellar mass, and
decreases with increasing SFR at a fixed stellar mass when $\rm
log(M/M_{\sun})\leq 10.5$. Salim et al. (2014) found that the metallicity is
anti-corrected with specific SFR regardless of different metallicity
indicators or methods used when $\rm 9.0\leq log(M/M_{\sun})\leq 10.5$, while
the dependence is weak or absent for massive galaxies when $\rm
log(M/M_{\sun})>10.5$. Salim et al. (2014) also demonstrated that the relative
specific SFR is a more physically motivated second parameter for the MZR, and
found that the overall scatter in the FMR relation does not significantly
decrease relative to the dispersion in the MZR. Recently, Bothwell et al.
(2016) reported that the FMR is between stellar mass, metallicity and gas mass
instead of the SFR. In addition, Kashino et al. (2016) measured the
metallicity of star-forming galaxies based on Dopita et al. (2016) and
Maiolino et al. (2008) calibrations, and found that whether the FMR exists or
not depend on the metallicity measurement method. The dependence on
metallicity and SFR at high stellar mass is still in argument (Kashino et al.,
2016). For the intermediate redshift universe, Ly et al. (2016b) showed
clearly that the MZR evolves toward lower metallicity at fixed stellar mass
with increasing redshift $z$, and found a much weaker dependence of MZR on SFR
than in the local universe.

In panel $a$ of Figure 5, we colour-code our galaxy points with their SFRs.
Figure 5 shows that most of galaxies in our sample have higher metallicities
than that of galaxies in Berg et al. (2012), but are consistent with the
result in Andrews & Martini (2013). The difference between our work and Berg
et al. (2012) may be caused by difference in sample selection and calibrations
for electron temperatures $T_{e}(\hbox{[O\,{\sc iii}]})$ and
$T_{e}(\hbox{[O\,{\sc ii}]})$. Andrews & Martini (2013) found that the scatter
in MZR for the M-SFR stacks with $T_{e}$-based metallicity is 0.22 dex, while
the scatter in the FMR is 0.13 dex. The decrease of scatter value in Andrews &
Martini (2013) reflects a strong SFR-dependence on the MZR. From visual
examination, we do not find strong dependence of MZR on SFR. However, the
scatter in FMR is 0.24 dex, lower than the 0.28 dex scatter in MZR, suggesting
MZR is weakly dependent on SFR. We note that the average and median values of
metallicity measurement uncertainties are 0.09 dex and 0.08 dex, respectively.
The average and median values on stellar mass measurement uncertainties are
about 0.14 dex and 0.12 dex, respectively. The larger scatters in MZR and FMR
compared with Andrews & Martini (2013) relations may be caused by the small
galaxy sample size, as well as the measurement uncertainties on stellar mass.

##  7 summary

We inspect all the 92,510 galaxies in LAMOST DR3, DR4 Q1 and Q2, and select 48
galaxies with $\hbox{[O\,{\sc iii}]}\lambda 4363$ detected at $\geq 3\sigma$
as our metal-poor galaxy sample. Using the $T_{e}$ method, we obtain the
metallicities of these metal-poor galaxies with a median $\hbox{$12\,+\,{\rm
log(O/H)}$}=8.16$, spanning from 7.63 to 8.46. The most metal-deficient galaxy
in our sample is ID26 with $\rm\hbox{$12\,+\,{\rm log(O/H)}$}=7.63\pm 0.01$,
which is the only XMPG we found, but has already been discovered by Izotov et
al. (2012a). We also confirm that the galaxy ID33 (RC2 A1228+12) is not an
XMPG.

With multiband photometric data from FUV to NIR and H$\alpha$ measurements, we
determine the stellar masses and dust-corrected SFRs, based on the SED fitting
and reddening corrected H$\alpha$ luminosities, respectively. We compare the
relationship between stellar mass, $T_{e}$-based metallicity and SFR of our
galaxies with galaxies in the local universe. We find that the metallicities
of our galaxies are in good agreement with the local $T_{e}$-based MZR in
Andrews & Martini (2013) with average and median values of residuals as 0.0015
dex and 0.025 dex, respectively. However, the MZR in Berg et al. (2012) may be
systematic lower than the metallicities of our metal-poor galaxies. Assuming
the coefficient of $\rm\alpha=0.66$, we find most of our galaxies are
consistent with the FMR in Andrews & Martini (2013). However, the scatter in
FMR is 0.24 dex, lower than the 0.28 dex scatter in MZR, suggesting MZR has a
weak dependence on SFR.

###### Acknowledgements.

We are very grateful to the referee’s insightful suggestions and comments, who
greatly improve the manuscript for this work. Guoshoujing Telescope (the Large
Sky Area Multi-Object Fiber Spectroscopic Telescope LAMOST) is a National
Major Scientific Project built by the Chinese Academy of Sciences. Funding for
the project has been provided by the National Development and Reform
Commission. LAMOST is operated and managed by the National Astronomical
Observatories, Chinese Academy of Sciences. This work is supported by the
Strategic Priority Research Program ”The Emergence of Cosmological Structures”
of the Chinese Academy of Sciences (No. XDB09000000), the National Basic
Research Program of China (973 Program)(2015CB857004), and the National
Natural Science Foundation of China (NSFC, Nos. 11225315, 1320101002, 11433005
and 11421303).

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#  Design, fabrication and characterization of 8x9 n-type Silicon pad array
detector fabrication and its performance tests using HGCROCv2 ASICsilicon pad
array for sampling calorimetry

###### Abstract

This paper reports the development and testing of n-type silicon pad array
detectors targeted for the Forward Calorimeter (FoCal) detector, which is an
upgrade of the ALICE detector at CERN, scheduled for data taking in Run 4
(2029-2034). The FoCal detector includes hadronic and electromagnetic
calorimeters, with the latter made of tungsten absorber layers and granular
silicon pad arrays read out using the High Granularity Calorimeter Readout
Chip (HGCROC). This paper covers the Technology Computer-Aided Design (TCAD)
simulations, the fabrication process, current versus voltage (IV) and
capacitance versus voltage (CV) measurements, test results with a blue LED and
90Sr beta source, and neutron radiation hardness tests. IV measurements for
the detector showed that 90% of the pads had leakage current below 10 nA at
full depletion voltage. Simulations predicted a breakdown voltage of 1000 V
and practical tests confirmed stable operation up to 500 V without breakdown.
CV measurements in the data and the simulations gave a full depletion voltage
of around 50 V at a capacitance of 35 pF. LED tests verified that all detector
pads responded correctly. Additionally, the 1$\times$1 cm2 pads were also
tested with the neutron radiations at a fluence of $5\times 10^{13}$ 1 MeV
neq/cm2.

Si microstrip and pad detectors, Detector design and construction technologies
and materials, Calorimeters 1234.5678

##  1 Introduction

Silicon detectors are widely used in particle physics experiments for their
fast response, flexibility in design, and ability to withstand high radiation
doses [ATLASpixeldetector, CMSbarrelPixelDetector]. The Forward Calorimeter
(FoCal) which is a part of the ALICE detector upgrade for Run 4 at the Large
Hadron Collider (LHC), utilizes silicon detectors for calorimetry and tracking
in its electromagnetic component.
Starting in 2029, the ALICE experiment plans to install the FoCal detecter
detector 7 meters away from the ALICE interaction point. FoCal aims to measure
small-$\it{x}$ (Bjorken variablescaling factor) gluon distributions via the
measurements of direct photons in the forward pseudo-rapidity range of 3.4 ¡
$\eta$ ¡ 5.8. This will support ALICE in conducting inclusive and correlation
measurements of photons, mesons, and jets to study the dynamics of the Quark-
Gluon Plasma (QGP) at small-$\it{x}$ down to $10^{-6}$ [focal_LOI]. The ALICE
FoCal consists of an Electromagnetic Calorimeter (EMCALFoCal-E) and a Hadronic
Calorimeter (HCALFoCal-H). The EMCAL FoCal-E is made up of 20 alternating
layers of silicon detectors and tungsten absorbers. Eighteen of these silicon
layers are arrays of 8 $\times$ 9 Si pads, each 1 cm2, fabricated on 325
$\mu$m thick, 6-inch Si wafer. Additionally, two high-granularity CMOS pixel
layers with an individual pixel size of 30 $\times$ 30 $\mathrm{\mu m^{2}}$
are included for high position resolution.
Based on the substrate, silicon detectors are categorized into n-type and
p-type detectors. A p-type n-type detector has a p-type silicon substrate
doped with a higher concentration of electrons n-type silicon substrate with a
high concentration of electron donors (n+) on one side and a higher
concentration of holes electron acceptors (p+) on the other, while an n-type
detector has an n-type silicon substrate doped . Conversely, a p-type detector
has a p-type substrate with p+ on one side and n+ on the other. This article
focuses on the study of 8$\times$9 n-type silicon pad array detectors and
their characterization in the laboratory. For the response of the detector to
high-energy pion and electron beams refer to paper [testbeampaper], in
addition and for comparison with the p-type pad arrays presented in the
Technical Design Report (TDR) [focaltdr]. These detectors are fabricated on
6-inch, 325 $\muup$m $\pm$ 20 $\muup$m thick, high-resistivity ($\sim$ 7
k$\Omega\thinspace$cm) silicon wafers, with each array containing 72 single
pads of area 1 $\times$ 1 cm2 per pad. Similar silicon detector designs and
their use in electromagnetic calorimeters have been previously reported
[Clice_ILC_1, Clice_ILC_2, Clice_ILC_3, Tsukuba_paper, sanjib_paper]. The
large-area n-type (8$\times$9) sensors detectors discussed here are being
fabricated for the first time in India. The size requirements of the silicon
sensors are based on the HGCROCv2 readout chipsimulated physics performance
and cost. The number of pads in a monolithic array matches the number of
readout channels in the HGCROC readout ASIC [HGCROCv2_paper], which has 72
readout channels and can be directly attached to the silicon sensors, reducing
the overall detector sizemeets the demanding dynamic range requirements of the
FoCal. This paper will discuss the detector design, Technology Computer-Aided
Design (TCAD) device simulation, fabrication process, and electrical and
performance tests using a light-emitting diode (LED) and a 90Sr electron
source. Additionally, it will report on radiation hardness studies conducted
using a fast neutron beam at RANS, RIKEN, Japan. For the response of the
detector to high-energy pion and electron beams refer to paper
[testbeampaper].

##  2 Silicon pad array design

Figure 1: Design of the 8 $\times$ 9 Si pad array: (a) Wafer-level mask design
layout showing main pad array in the center and small pad cells in the
periphery, (b) Guard ring design showing the three guard rings, inter-guard
ring distances, and scribe line, (c) Zoomed-in view of the layout showing
inter pad distance of around 80 $\muup$m, (d) Layout of a single pad cell
showing positions of the probing and wire bonding pads, respectively.
Dimensions are in $\muup$m.

The n-type Si pad array design consists of an 8 $\times$ 9 array of pad cells,
with each cell measuring 1 $\times$ 1 cm2. Figure 1(a) shows the full wafer-
level design layout, with the main die (82.6 mm $\times$ 92.6 mm) in the
center and test samples of pad cells around the wafer’s periphery. Three guard
rings are located at the outer edge of the pad array, as seen in Figure 1(b),
which also shows part of the pads and the scribe line, with dimensions in
$\muup$mmicrometers. The pad cell is approximately 1340 $\muup$m away from the
scribe line. Figure 1(c) illustrates that the pads are separated by a small
distance of 80 $\muup$m to reduce the cross-talk in the detector and also
ensure a minimal dead area in the array. Each pad cell has six contact points,
shown as dark green squares (350 $\muup$m2) in Figure 1(d). The wire bonding
pads at the corners connect the pad cells to readout electronics, while the
probing pads are used for electrical testing of the detector after
fabrication.

##  3 TCAD device simulation

The detector fabrication process and its electrical characteristics are
simulated using the Athena and Atlas modules of Silvaco Technology Computer-
Aided Design (TCAD) software [TCAD_simulations]. For this simulation, a
Passivated Implanted Planar Silicon (PIPS) type standard P+/N-/N+ vertical
stack was used as shown in Figure 2. To reduce mesh size and computational
time, only the edge of the end pad cell and the guard ring structures (three
p-type guard rings and one n-type guard ring) were simulated. The color legend
on the left indicates the doping concentration(in cm3), where the top of the
n-type substrate wafer was doped with boron impurities at 80 keV energy to
form the p+ regions (anode and p-type guard rings) and with the n-type
phosphorus impurities to form the n+ regions (n-type guard ring (NGR)). The
NGR is introduced to prevent the depletion region from reaching the detector
edge, which could cause premature breakdown. The simulated junction depth
exceeds 1 micron for both the active area and the p-type guard rings. The
simulation also accounts for the effects of metal overhang and field oxide,
ensuring a comprehensive analysis of the electrical characteristics of the
detector.

Figure 2: The design and doping profile of the 8×9 Si pad array: The layout
includes the anode, three p-type guard rings (PGR1, PGR2, PGR3), and a n-type
guard ring (NGR). The vertical axis represents depth in microns, while the
horizontal axis shows the position in microns. The color gradient indicates
the absolute net doping concentration in cm3-3 whose values are listed in the
left legend. The materials are labeled with colors: silicon (pinkorange), SiO2
(orangeblue), conductor (purple), and electrodes (striped blue).The legend
inside the plot shows the net doping concentrations.

The various parameters such as Implant dosage, Drive-in implant dose, drive-in
time and temperature, Guard guard ring distance, Metal overhang, Oxide metal
overhang, oxide thickness, etc. were optimized for the highest possible
breakdown voltage and the desired value for the full depletion voltageof the
detector.

In the simulation, a part of the pad cell was considered where the anode and
cathode in the design were kept at the negative and positive potential to
simulate the leakage current as well as the device capacitance as a function
of reverse bias voltage. The simulated Current-Voltage (I-V) and Capacitance-
Voltage (C-V) IV and CV plots are shown in Figure 3. The I-V IV
characteristics indicate a breakdown voltage exceeding 1000volts V, while the
C-V CV characteristics suggest a full depletion voltage of around 45
voltsbetween 40-50 V.

Figure 3: Simulated I-V IV (Left) and C-V CV (Right) curves of 1$\times$1 cm2
pad cell.

The mask layout (see Figure 1 (a)) was created using L-edit layout editor
software, incorporating the optimized simulation results. The PCB layout was
superimposed on the final photomask Graphic Data System (GDS) to ensure proper
alignment of the wire bond pads. Before finalizing the detector design layout,
an alignment test was conducted in the software. This test confirmed that the
wire bonding pads on the Si detector were perfectly aligned with the center of
the 2.1 mm circular opening on the Front-End-Electronics (FEE) board. The FEE
board is a 10-layer printed circuit board (PCB) hosting the HGCROCv2
chipcurrently available version 2 of HGCROC chip [bourrion2023prototype].

##  4 Si pad array (8 $\times$ 9) fabrication

Based on the TCAD device simulations and the design discussed in the previous
section, several samples of the n-type Si pad array detector were fabricated.
The target parameters for the device fabrication were: reverse saturation
current or leakage current less than 10 nA, detector capacitance of about 4535
pF at a full depletion voltage (FDV) of around 50 V, and a breakdown voltage
of 500 V or more per pad cell. To achieve these parameters, the detectors were
fabricated using Si wafers and photomasks with the specifications listed in
Table 1 and Table 2. The fabrication process involved using a five-layered
photomask and a negative photoresist. Standard bipolar fabrication technology
was employed at the Bharat Electronics Limited (BEL) wafer fab in Bangalore,
India [bel]. The starting substrates were n-type silicon wafers with
$\langle$100$\rangle$ orientation, high resistivity, 150 mm diameter, and 325
microns thickness. The fabrication process included steps such as thermal
oxidation, photolithography, ion implantation, wet and dry etching, diffusion,
metallization, and protective layer deposition. The cleaning and etching steps
were optimized through trials to minimize contamination and achieve the lowest
possible leakage current at full depletion voltage. Additionally, the
diffusion and oxidation steps were optimized to maintain the uniformity of the
wafer within 10%. A sample After these steps, an 8×9 array was cut from the
wafer, and a 6 $\mu$m aluminum layer was deposited on the backside (n+) of the
detector. A photograph of the finished wafer is shown in Figure 4. The
$8\times 9$ pad array die is visible in the middle, while the test samples of
1 $\times$ 1 cm2 pad cells are seen at the periphery.

Table 1: Specification of Si wafers used for device fabrication. Parameter |  Description
---|---
Type |  n-type prime, Single crystal Si
Growth |  Float Zone (FZ)
Diameter |  150 $\pm$ 0.5 mm
Orientation |  $\langle 1\ 0\ 0\rangle$
Thickness |  325 $\pm$ 20 $\muup$m
Substrate resistivity |  $\sim$ 7 k$\Omega\thinspace$cm
Dopant |  Phosphorus, n-type
Total Thickness Variation (TTV) |  10 $\muup$m
Maximum Oxygen and Carbon Conc. |  $10^{16}$/cm3
Minority carrier recombination lifetime |  1 ms
Table 2: Specification of photo-mask used during device fabrication. Parameter |  Description
---|---
Material |  Soda lime glass / Anti-reflective chrome
Dimensions |  $7^{\prime\prime}\times 7^{\prime\prime}\times 0.12^{\prime\prime}$
Pattern generation |  Direct write
Max. defect size |  0.5 $\muup$m
Max. defect density |  0
Min. size of layout elements in layer |  10 $\muup$m $\pm$ 1 $\muup$m
Writing grids |  0.1 $\muup$m
Mask order |  7′′/BFBright Field (BF)/CDChrome Down (CD)/RR Right Reading (RR) (for 4 layers) and 7′′/DFDark Field (DF)/CD/RR (for 1 layer)
MixMax. misalignment between layers |  0.5 $\muup$m
Figure 4: Photograph of fabricated Si pad array on a 6-inch n-type Si wafer.

##  5 Detector integration with FEE

Figure 5: The photographs show the packing procedure of Si detector (die): (a)
The die (82.6 mm$\times$ 92.6 mm) is held in place inside the Al jig with glue
dots added at the center of each pad, (b) FEE board (82.6 mm$\times$ 100.6 mm)
is placed on top of the detector and left for 12 hours for the glue to settle,
(c) Side view of FEE board glued to the detector, and (d) 25 $\mu$m thick gold
wire bonds connected to the corners of four pads (top), and gold wire bonds
connecting the two floating guard rings and one guard ring to the ground
(bottom).

After completion of device fabrication, wafer-level electrical tests (IV/CV)
were carried out. The good wafers that met the design criteria mentioned in
section 4, were selected for dicing the pad array (die). The procedure
followed in attaching the die to the FEE board is depicted in Figure 5. An
aluminum jig of the same dimensions as the die was made with a provision to
apply suction from the bottom so that the die would be temporally fixed in the
jig, then manually Sader epoxy glue dots were placed at the center of each pad
cell as shown in Figure 5 (a). The FEE board was gently placed on top of the
die as shown in Figure 5 (b) and rested in place overnight so that, the glue
could settle and make a robust packaged detector. The side view of the
packaged detector is shown in the photograph of Figure 1 (c). A 25 $\muup$m
thick gold wire bonding was carried out on the packaged detector. The upper
panel in Figure 1 (d) shows a zoomed picture of one of the openings on the FEE
board where gold wire bonds from the FEE board to the bonding pads on the four
pad cells are shown. Each pad cell is connected with the three wire bonds to
reduce the inductive reactance of wires. There are in total 20 circular
openings on the FEE board, where the four openings in the top row connect to
two bonding pads each, while the remaining 16 openings connect to four bonding
pads each. This way all the the 72 pads of the detector array are connected to
the FEE board. The bottom panel in Figure 1 (d) shows the wire bonds to the
innermost and outermost guard rings. The inner guard ring is kept at the same
voltage as the detector, the middle two guard rings are kept floating and the
outermost guard ring is connected to the ground. After wire bonding, the glob
top was done using transparent glue (dow sylgard Dow Sylgard 186 silicone
elastomer) to protect the wire bonds. The details about the FEE are discussed
in the following section 6.2.

##  6 Test results and discussion

In this section, various tests of the fabricated and packaged Si pad array
detectors are reported. Test done using bare detectors include electrical
characteristics: IV (Leakage leakage current versus voltage) and CV (Junction
junction capacitance versus voltage), breakdown voltage test, and effect of
temperature on the leakage current. For packaged detectors, the tests include
the data acquisition optimization using a blue LED and the detector response
to the Strontium-90 (90Sr ) $\beta^{-}$ source which emits electrons up to 2.2
MeV energy. In addition, radiation hardness studies of the detector sample
irradiated with a fast neutron fluence of $5\times 10^{13}$ 1 MeV
$\mathrm{n_{eq}}$/cm2 are also reported.

###  6.1 Electrical tests (IV and CV)

This section reports the IV and CV tests of Si pad arrays carried out using
the Keithley 4200A-SCS parameter Analyzer. The IV test was performed at the
die level using a probe station. During the test, all neighboring pad cells
were kept at the same potential as the pad cell under test (PCUT). This
procedure was followed manually for each pad cell to acquire leakage current
data at a fixed reverse bias voltage of 50 V. The leakage current for the best
25 Si pad arrays is shown in Figure 6 Left(Left). About 90 % of the pad cells
have leakage current less than 10 nA/cm2. While a lower leakage current is
generally preferable, achieving an extremely low current over the large
detector area was challenging, so the design aimed for a leakage current of
less than , meeting the design requirements, as the HGCROCv2 can compensate
for up to 10 nA/cm2$\mu$A of current [hgcroc_proceedings]. Thus, the total
leakage current across the entire detector with 72 pads remains well within
the HGCROCv2 limit. Figure 6 (right) shows an example of a current-voltage map
of a single pad array, where the leakage current in most pads stays below the
10 nA/cm2 target.

Figure 6: (Left) The number of pad cells in a wafer with leakage current less
than or equal to 10 nA (teal) and greater than 10 nA (grey) plotted as a
function of wafer number. (Right) Leakage current map for a single pad array
at a reverse bias voltage of 50 V.

To test the higher voltage tolerance of the detector beyond the full depletion
voltage (FDV), four random pads on a detector array were probed (Figure 7
left). The results show the detectors can operate safely up to 500 V and might
handle even higher voltages as expected from the simulations. However, for
safety, the reverse bias voltage was not increased further. The measured
current-voltage data matches is in agreement with the simulations.

Leakage current in semiconductor detectors is sensitive to temperature due to
the generation of thermally induced electron-hole pairs. Therefore to
[leobook1994]. To test the effect of temperature on the leakage current of the
detector, a single pad cell was placed on a Peltier peltier module. Applying
voltage across the Peltier peltier module causes one side to heat up while the
other cools down. This setup allowed for measuring leakage current at reverse
bias voltages up to 100 V, across temperatures ranging from 10.5 °C to 60.5 °C
with interval of 10 °C as shown in Figure 7. As expected the leakage current
varies inversely as a function of temperature. The optimal operating condition
is around 20 °C, where the leakage current is well below Considering that the
HGCROCv2 readout ASIC is capable of compensating up to 10 nA at the FDV$\mu$A
of leakage current, the detector could operate even at the highest tested
temperature.

Figure 7: (Left) Leakage current as a function of applied reverse bias voltage
for a few randomly selected pads in the detector, shown along with the
simulation result. (Right) Leakage current as a function of reverse bias
voltage at various temperatures.

Figure 8: (Left) Detector capacitance as a function of applied reverse bias
voltage, with the measured capacitance of about 40 pF matching the
simulations. (Right) The inverse square of capacitance as a function of
applied voltage, indicates a full depletion voltage of about 50 V.

In addition to the I-V measurements, capacitance versus applied reverse bias
voltage (C-V) IV measurements, CV measurements were performed to determine the
full depletion voltage (FDV) of the detector and compare it with simulations.
The C-V CV characteristics for one of the detector array samples are shown in
Figure 8 Left. Most of the (Left). The pads have a capacitance between 4032 pF
and 5046 pF above 50 V, which is in accordance with the simulations. To obtain
the FDV, the inverse of the capacitance squared ($1/C^{2}$) is plotted against
the applied voltage for all 72 pads in Figure 8 Right(Right). The voltage at
which the $1/C^{2}$ values saturate is considered the FDV, which is around 50
V in this case. Therefore, the operating voltage of the detector would be
slightly above the FDV, around 60 V, to ensure stable conditions.

Figure 9: The LED test setup used to obtain the trigger parameters for
calibrating the configuration of HGCROCv2 chip: The setup includes a blue LED,
a pulse generator, a Si pad array coupled to the HGCROCv2 chip, and a an
Xilinx AMD Kintex UltraScale FPGA KCU105 Evaluation Kit DAQ board. The blue
LED illuminates the Si pad array, with the pulse generator driving the LED and
controlling the trigger signals passed to the DAQ board.

###  6.2 Detector test with LED

Figure 10: This figure shows signal pulses measured in ADC counts (y-axis) and
time in ns (x-axis). The left panel confirms the functionality of all 72
detector pads by showing their LED light pulses. The right panel compares the
signal strength from Sr-90 90Sr electrons with the blue LED light signal..
Figure 11: The flow chart of the detector setup. (a) The pulse generator
drives the LED and sends a trigger to the DAQ board. (b) The pulse generator
drives the LED, with the trigger split into two paths: one directly to the DAQ
board and the other via NIM logic to introduce an additional delay in the
trigger.

This section reports the test performed on the packaged detectors using a blue
LED light. The LED test is performed to calibrate configure the HGCROCv2 chip
hosted by the FEE board. The HGCROCv2 is a highly integrated chip consisting
of 72 readout channels with each channel consisting of a pre-amplifier,
shaping amplifier, analog-to-digital converters (ADCs), and two time-to-
digital converters (TDCs). The 10-bit ADC samples data at a 40 MHz clock with
a selectable dynamic range of 80 fC, 160 fC, or 320 fC, depending on the gain
setting of the pre-amplifier. When the ADC saturates, the two TDCs provide
charge and time information, increasing the total dynamic range up to 10 pC.
Sampled data is stored in a 10-bit (1024 samples) circular buffer, which
releases the data upon receiving an external trigger. The data is then
transmitted via two serial links (1.28 Gb/s each), one for data and the other
for trigger information. The trigger phase (offset) is programmable and can be
set in the HGCROCv2 configuration via the tuning of coarse and fine phase
parameters. All the measurements with the LED and 90Sr reported here are done
with the 80 fC dynamic range.
The HGCROCv2 was designed primarily for the Compact Muon Solenoid (CMS)
experiment at the LHC, which plans to use p-type detectors. It can read both
n-type and p-type Si pad detectors, howeverthe internal , charge injection for
the calibration of the chip ASIC configuration is only possible with electrons
(which are charge carriers in p-type sensorsdetectors), not with holes (which
correspond to the n-type detectors under investigation). Therefore to
calibrate configure the chip for n-type sensorsdetectors, an external
injection using a blue LED light was performed by shining the LED directly
onto the detector pads through the top-side opening on the FEE board (top
panel in the Figure 5 (d)). Calibration Configuration involves tuning the
pedestal, adjusting pre-amplifier gain settings, and optimizing trigger
parameters. Figure 9 shows the LED test setup, which includes a pulse
generator that provides peak-to-peak amplitude ($V_{pp}$) of 1.2 V with a 50%
duty cycle to drive the LED and provide a transistor-transistor logic (TTL)
trigger signal to the Xilinx KCU105 AMD Kintex UltraScale FPGA KCU105
Evaluation Kit data acquisition (DAQ) board. The LED was shined through all
the FEE openings to produce pulses in all 72 pads of the detector, as shown in
Figure 10 Left(Left). The x-axis of the plot represents the ADC sampling
clock, which samples every 25 ns (40 MHz), and the y-axis shows the amplitude
of the recorded pulse in ADC values. The figure shows that all 72 pads wire-
bonded to the FEE board responded to the LED light, with their pulses peaking
at 150 ns. The pulse amplitude during the LED scan varies from pad to pad
because the light cannot be shined directly onto each pad due to the presence
of transparent glue used as a glop top. Therefore, the LED test was performed
at different angles through each opening to get a signal in each pad. This
test aimed to check and confirm that all 72 pads were working and responding
to the external injection.

The peak of the pulse The time at which the pulse reaches its maximum ADC
value depends on the coarse and fine phase parameters configured in the chip,
which vary with changes in the setup, such as additional delays caused by
cables and NIM modules. To estimate the delay in phase due to the NIM modules,
the signal from the pulse generator was split with one sending to drive the
LED and the other through the NIM logic which consists of a leading edge
discriminator and a NIM to TTL converter module. The TTL signal compatible
with the DAQ board is then sent to the DAQ board as shown in Figure 11. The
acquired LED pulse showed a 60 ns delay, shifting the peak from 150 ns to
around 10090 ns. This confirms that the ADC calculates the delay based on the
buffer ’s end timing is relative to the end of the buffer (512 bits in this
case). Therefore it is important to adjust the trigger offset parameter
accordingly. These parameters are kept constant during tests with both the LED
and the Sr-90 90Sr source to ensure a fair comparison of their pulses (see
Figure 10, right panel). More discussion on the detector testing with the
Sr-90 90Sr source is detailed in the following section.

###  6.3 Detector test with Sr-90 90Sr $\beta^{-}$ source

To test the detector with electrons, a 2.237 MBq 90Sr $\beta^{-}$ source was
used, which produces electrons with energies up to 2.2 MeV. A dedicated test
setup was created, as shown in Figure 12. The setup includes the detector
connected to the DAQ board through an interface card. The collimated 90Sr
source was placed below inside a 6 mm thick aluminum collimator with a
circular opening 0f of 5 mm diameter to focus the constrain the 2.2 MeV
electrons onto one of the pad cells. The 6 mm thickness was selected based on
the CSDA (continuous-slowing-down approximation) range, which indicates that 5
mm of aluminum fully absorbs electrons up to 2.5 MeV. The detector was
reverse-biased and kept at 8060 V, while the scintillator placed above the
detector was powered at 1200 V. The setup schematic is shown in Figure 12
(Right-Bottom). The signal generated by the electrons in the scintillator,
along with the TTL signal obtained from the NIM logic, is shown in Figure 12
(Right-Top). The entire setup was operated in the dark to reduce the leakage
current due to light. The right panel of Figure 10 shows the Sr-90 90Sr
electron pulse in comparison with the LED pulse. The 90Sr electron pulse has a
much smaller amplitude compared to the LED light-induced signals. This is
because the high-intensity LED light generates many more electron-hole pairs
compared to a single electron passing through the 325-micron thick silicon,
resulting in a larger pulse.

Figure 12: (Left) Test setup of the 90Sr source, showing detector testing with
the source placed below a 6 mm thick aluminum collimator with a 0.5 mm
diameter hole to focus electrons onto a single pad. The Si detector connects
assembly connected to the KCU105 DAQ board via an interface board. A , a 90Sr
source inside an Al collimator, and a plastic scintillator placed above the
detectortriggers . The scintillator sends a NIM signal to a discriminator,
which converts it to TTL and sends it to the DAQ to release board. (Right-Top)
NIM signal from the data stored in scintillator and TTL signal from the
bufferdiscriminator. (Right Bottom) Schematic of the test setup.

Figure 13: (Left) Energy-loss distribution of electrons coming from sr-90 90Sr
source. It is fitted with a Gaussian plus a convolution of Landau and Gaussian
functions. The Gaussian fits the pedestal while the convoluted function fits
the signal. (Right) Hitmap of 90Sr electrons placed below the detector.

Figure 14: (LeftSr-90 ) 90Sr energy loss signal peak (ADC values) as a
function of reverse bias voltage for one of the Si pad cells. The peak
position shifts to higher values with an increase in the reverse bias voltage
and then starts to saturate after full depletion occurs in the detector.
(Right) Position scan using the electrons from Sr-90 90Sr source, showing the
homogeneity in the response of various detector pads selected randomly for the
test.

The measured energy-loss distribution of the 90Sr electrons in the detector is
shown in Figure 13 Left(Left). The offset is removed, so the pedestal peaks at
zero ADC value. The distribution is fitted with a Gaussian plus a convolution
of Landau and Gaussian functions. The Gaussian fits the pedestal, while the
Landau-Gaussian convolution fits the MIP peak. Minimum Ionizing Particle (MIP)
peak. A MIP is a particle whose mean energy loss rate through matter is close
to the minimum. Electrons with energy of few MeV acts approximately as MIP
[NIST]. Figure 13 Right(Right) shows the electron hit position on the detector
array, indicating energy deposition in a few pad cells.

A voltage scan was conducted to measure the effect of reverse bias voltage on
the electron energy-loss distribution. Figure 14 Left(Left) shows the peak and
width of the energy-loss distribution as functions of reverse bias voltage.
The peak position increases with applied voltage and starts to saturate around
6080 V, while the width remains mostly unchanged. The peak saturation occurs
because the detector achieves full depletion at around 50 V. Additionally, a
position scan was also performed to measure the homogeneity in the response of
different detector pads to energy loss distributions. Various pad cells were
irradiated with the 90Sr source under the same conditions and their MIP peak
position values were recorded as shown in Figure 14 Right(Right). Most tested
pads have a mean value of around 25 ADC values with a deviation of about 2 ADC
value, indicating minor variations in pad response to electron energy loss.

###  6.4 Radiation hardness studies

During the LHC Run 4, spanning about four years, the innermost part of the
ALICE FoCal detector will be exposed to the radiation equivalent to $5\times
10^{13}$$7\times 10^{12}$ 1 MeV $\mathrm{n_{eq}}$/cm2. To test the performance
of the fabricated detectors under these conditions, several test samples of
$1\times 1$ cm2 pads were irradiated with fast neutrons up to the same fluence
fluence of $5\times 10^{13}$ 1 MeV $\mathrm{n_{eq}}$/cm2 at the RIKEN
Accelerator-driven compact Neutron Systems (RANS) in Japan, where neutrons are
produced using the proton-beryllium (p-Be) reaction [RANS_Facility]. The
leakage current of the irradiated pads was measured at different neutron
fluence levels as a function of reverse bias voltage at room temperature, as
shown in Figure 15 Left(Left). As expected, the irradiated pad cell current
increased with neutron fluence. The leakage current increased by three orders
of magnitude for a fluence of $10^{13}$ 1 MeV $\mathrm{n_{eq}}$/cm2 compared
to a non-irradiated test sample (blue data points scaled by $10^{3}$). Figure
15 Right(Right) shows the current of the irradiated pad cell monitored over a
period of 55 days after irradiation, where the current decreased from 64
$\muup$A to 47 $\muup$A within a week. The irradiated pads showed no response
to the electron source, indicating that the detector might not tolerate the
given fluenceand , possibly due to the substrate-type inversioncould have
occurred [Moll:1999kv]. Therefore, using Thus, it is recommended to use p-type
substrate-based detectorsis recommended for meeting substrate detectors, which
operate stably up to a fluence of $5\times 10^{13}$ 1 MeV
$\mathrm{n_{eq}}$/cm2, provided they are maintained below 20°C. Although the
fluence increases leakage current, it decreases over time and mainly affects
the baseline, which can be adjusted in the preamplifier. These detectors are
recommended to meet the high radiation tolerance requirement ($5\times
10^{13}$ requirements ($\sim 10^{13}$ 1 MeV $\mathrm{n_{eq}}$/cm2) of the
ALICE FoCal project.

Figure 15: (Left) IV curve comparison of non-irradiated and irradiated single
pad cell as a function of radiation fluence. The non-irradiated leakage
current data is scaled by 103. (Right) The leakage current was measured after
irradiation for 55 days at two fixed reverse bias voltages.

##  7 Summary

The 8$\times$9 n-type silicon pad array detectors were successfully designed
and fabricated at Bharat Electronics Limited, India. The detectors met the
design specifications for leakage current, full depletion voltage, and
capacitance. They were packaged using a FEE board with HGCROCv2 ASIC, and the
ASIC was calibrated configured by externally shining an LED onto the detector
pads. The packaged detectors were tested with 90Sr electrons to perform
voltage scans, position scans, and measure energy deposition in the detector’s
active volume. The voltage scan showed the variation of the 90Sr peak position
with voltage, which saturated after reaching full depletion. The position scan
demonstrated the homogeneity of response across different detector pads. The
energy deposition in the detector showed a clear separation of the pedestal
and electron signal. The radiation hardness tests revealed that the leakage
current in the detector increased with a neutron fluence of $5\times 10^{13}$
1 MeV $\mathrm{n_{eq}}$/cm2. Although the leakage current decreased
significantly over two months post-irradiation, it remained high enough to
cause weak signals like MIP to merge with the noise, indicating that the
n-type silicon detectors are unsuitable for high-radiation environments.
Therefore, p-type substrate-based detectors are recommended for the high
radiation tolerance required by the ALICE FoCal project. The authors would
like to thank the ALICE-FoCal and ALICE-India collaboration for their constant
support throughout the project work. They also thank Mr. Debasis Barik
(Scientific Assistant, CMRP NISER) for help with the Mechanical support
structure, and Mr. Samar Mohan Mohanty (Project associate, CMRP) for his
constant support throughout the project work. Additionally, the authors would
like to thank DAE and DST India for their financial support through the
project entitled ”Indian participation in the ALICE experiment at CERN,” and
the work is also partly funded through the J.C. Bose fellowship of DST awarded
to BM.