# Revealing the Unusual Structure of the KAT-7-Discovered Giant Radio Galaxy
J0133$-$1302

N. Mhlahlo,1 M. Jamrozy,2
1School of Physics, University of the Witwatersrand, Private Bag 3,
2050-Johannesburg, South Africa
2Astronomical Observatory, Jagiellonian University, ul. Orla 171, 30-244
Krakow, Poland E-mail<EMAIL_ADDRESS><EMAIL_ADDRESS>
(Accepted XXX. Received YYY; in original form ZZZ)

###### Abstract

We present a new study of the 1.7 Mpc KAT-7-discovered giant radio galaxy,
J0133$-$1302, which was carried out using GMRT data at 323 and 608 MHz. This
source is located at RA $01^{h}33^{m}13^{s}$ and Dec
$-13^{\circ}03^{\prime}00^{\prime\prime}$ and has a photometric redshift of
$\sim$0.3. We discovered unusual morphological properties of the source which
include lobes that are exceptionally asymmetric, where the upper lobe is much
further from the core when compared to the lower lobe, and a complex structure
of the upper lobe. This complex structure of the upper lobe hints at the
presence of another source, in close proximity to the edge of the lobe, which
resembles a bent-double, or distorted bent tail (DBT) radio galaxy. Both the
upper lobe and the lower lobe have a steep spectrum, and the synchrotron age
of the lower lobe should be less than about 44 Myr. The core has an inverted
spectrum, and our results suggest that the parent galaxy in J0133$-$1302 is
starting a new jet activity. Our spectral analysis indicates that this source
could be a GigaHertz Peaked Spectrum (GPS) radio galaxy.

###### keywords:

Radiation mechanisms: non-thermal, galaxies: active, galaxies individual:
J0133$-$1302, galaxies: jets, radio continuum: galaxies

††pubyear: 2019††pagerange: Revealing the Unusual Structure of the
KAT-7-Discovered Giant Radio Galaxy J0133$-$1302–LABEL:lastpage

##  1 Introduction

Radio galaxies (RGs) are extragalactic radio sources that exhibit extended
radio emission on either side of the active galactic nucleus (AGN). These
sources are characterised by the presence of jets, which are usually two
collimated outflows from the AGN, and the radio lobes where the jets terminate
(Miley 1980; Giovannini et al. 2005; Lister et al. 2016; see also the recent
comprehensive review by Hardcastle & Croston 2020). The jets carry plasma away
from the nucleus to the opposite ends of the galaxy, additionally leading to
flows of momentum, energy and magnetic flux (Begelman et al., 1984; Laing et
al., 2005). The radio lobes, and the jets when they are present, can track the
largest sources among radio galaxies known as giant radio galaxies (GRGs).
GRGs represent the most energetic single-galaxy structures in the universe,
with jets and lobes extending on $\sim$Mpc scales (Ishwara-Chandra & Saikia,
1999; Lara et al., 2001a). These sources belong mostly to the Fanaroff-Riley
type II (FRII; Fanaroff & Riley 1974) radio morphology (Dabhade et al.,
2020a), having high radio luminosities when compared to the Fanaroff-Riley
type I (FRI) radio sources (Laing et al. 2005; but see the discussion by Mingo
et al. 2019 about the FRI/II luminosity break). They have been observed at
multifrequencies using a variety of radio instruments (Ishwara-Chandra &
Saikia, 1999; Lara et al., 2001b; Machalski et al., 2001; Ishwara-Chandra &
Saikia, 2002; Kronberg et al., 2004; Saripalli et al., 2005; Konar et al.,
2008; Jamrozy et al., 2008; Machalski et al., 2009; Malarecki et al., 2013;
Mingo et al., 2019; Maccagni et al., 2020; Cotton et al., 2020; Dabhade et
al., 2020a). The GRGs are essential for the investigation of the astronomical
questions about the evolution of radio sources, the acceleration of cosmic
rays, the density of the intergalactic medium at different redshifts, and the
nature of the AGN activity. The largest known GRG is J1420-0545 with a
projected linear size of 4.69 Mpc (Machalski et al. 2008; but also see
Hernández-García et al. 2017 for a potentially larger GRG). To date it is
still not clear what leads to the formation of GRGs. Two fundamental scenarios
have been postulated to describe their exceptional sizes: firstly, the lobes
could be fed by very powerful central engines which supply the jets with
enough energy to bore their way through the ambient medium (Gopal-Krishna et
al., 1989), and secondly, GRGs could be normal radio sources evolving in very
low-density environments that offer small resistance to the evolution of the
jets (Lara et al., 2000; Subrahmanyan et al., 2008). The first scenario
requires the presence of prominent cores, due to strong nuclear activity,
which are not always observed. Ishwara-Chandra & Saikia (1999) investigated
this possibility and found an inverse correlation between the degree of core
prominence and total radio luminosity, which indicated that the giant radio
objects have similar core strengths to those of smaller objects of similar
total luminosity.
A number of case and comparison studies of the properties of GRGs and the
ambient intergalactic medium (Lara et al., 2000; Subrahmanyan et al., 2008;
Safouris et al., 2009; Hardcastle & Croston, 2020) seem to point to the second
scenario. However, a study by Komberg & Pashchenko (2009) found that for a
sample of GRGs, the asymmetries in the radio morphology of a several GRGs
appeared to be related to the density anisotropy in the medium. If this
observation is indeed correct, it could imply that a low environmental density
cannot be the only origin of GRGs.
Most of the normal-size RGs ($<$ 1 Mpc), and GRGs, have their lobes
continuosly supplied with energy from the AGN via the jets. However, a number
of studies have shown that there are sources where the nuclear activity has
stopped, leading to the interruption of the jet production mechanism. This
cuts off the energy flow from the AGN, and results in a gradual fading of
structures due to adiabatic and radiative losses of relativistic electrons
(e.g. J0349+7511 in Abell 449; Hunik & Jamrozy 2016). The resulting diffuse
sources are sometimes referred to as relics, AGN relics, or loosely as dying
sources (Cordey, 1987; Rengelink et al., 1997; Jamrozy et al., 2004; Parma et
al., 2007; Murgia et al., 2011; Tamhane et al., 2015; Hurley-Walker et al.,
2015; Brienza et al., 2016; Shulevski et al., 2017; Mahatma et al., 2018;
Randriamanakoto et al., 2020; Shabala et al., 2020; Quici et al., 2021). They
are characterised by a steep spectrum with a high-energy cut-off or turnover
at some characteristic break frequency.
Curiously, some otherwise dying sources have shown hints of recurrent or
restarting AGN activity. It has been established beyond doubt that jet forming
activity in these sources is episodic and not continuous during the lifetime
of the source. These sources are called double-double RGs (DDRGs), and their
morphology carries information about their interrupted jet activity and
evolutionary history. A characteristic feature is a pair of double radio
sources emanating from the AGN, and this is thought to occur when a new epoch
of jet activity, after a quiescent or “off” phase, takes place in a RG with
older lobes still visible from the activity of the previous epoch
(Schoenmakers et al. 2000; Marecki et al. 2016; Hunik & Jamrozy 2016; Mingo et
al. 2019; Shabala et al. 2020; and for the recent reviews on DDRGs see Saikia
& Jamrozy 2009; Kuźmicz et al. 2017; Mahatma et al. 2019).
Since the lobes of extended radio sources can store the energy supplied by the
jets for longer than the duration of the “off” phase, radio galaxies are able
to preserve information on the past activity and history of the AGN (Jamrozy,
2012).

|
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Figure 1: Top left: AIPS radio image of the GRG at 323 MHz. The restoring beam
of the image is 11′′ $\times$7 ′′ (PA=43 deg), and the rms noise level in the
image plane is 0.1 mJy/beam. Top right: AIPS radio image at 608 MHz. The
restoring beam is 10′′ $\times$5 ′′ (PA=3.3 deg), and the rms noise is 0.03
mJy/beam.
Bottom: SPAM radio images of the GRG at 323 MHz (left) and 608 MHz (right) are
shown. The restoring beam of the image at 323 MHz is 12′′ $\times$ 7′′ (PA=24
deg), and that of the image at 608 MHz is 8′′ $\times$ 5′′ (PA=-2 deg). The
noise level in the image plane is 0.1 mJy/beam (left) and 0.08 mJy/beam
(right). In all the images radio contours start at $3\times rms$ and then
scale by a factor of 2. The restoring beam size is shown at the bottom-left
hand corner. L1 represents the south-eastern radio lobe and L2 the north-
western lobe; C stands for the radio core of the GRG and B for a
background/foreground source or a hotspot.

##  2 GRG J0133$-$1302

GRG J0133$-$1302 was discovered in the field of the cluster of galaxies ACO209
at a frequency of 1.83 GHz (Colafrancesco et al., 2016), using the
decomissioned 7-dish Karoo Array Telescope (KAT-7), located near the Square
Kilometer Array (SKA) core site in the Northern Cape Karoo, South Africa
(Foley et al., 2016). This source is one of the eight target clusters which
were observed with the KAT-7. It is located at RA $01^{h}33^{m}13^{s}$ and Dec
$-13^{\circ}03^{\prime}00^{\prime\prime}$ (J2000.0) and has a redshift of
$\sim$0.3 (Colafrancesco et al., 2016). This is, however, a photometric
redshift which might have a large error.
The KAT-7 radio telescope array detected extended emission in the form of two
symmetric lobes. A cross-correlation of the KAT-7, NRAO VLA Sky Survey (NVSS:
Condon et al. 1998), infra-red (IR), optical, and X-ray sources in the field
of GRG J0133$-$1302 revealed the KAT-7 extended source encompassing NVSS
sources. The NVSS sources are S1 (southern-east SE lobe), S2 (core), S3 and S4
(northern-west NW lobe), according to the nomenclature by Colafrancesco et al.
(2016), suggesting there was an astrophysical connection between the lobes and
the central core of an extended radio galaxy. This means the NVSS image
partially resolves the elongated KAT-7 radio structure into four distinct
sources (see Fig. 1 and 2 in Colafrancesco et al. 2016). The NVSS core is
associated with the X-ray source 1RXSJ013313.8-13031 in the ROSAT all-sky
survey (RASS) having a count rate of 0.04 cts/s (0.1-2.4 keV band).
At the position of the radio core, or host galaxy, there is also a strongly
detected WISE source J013313.50-130330.5. The infrared magnitudes of the host
galaxy from the Wide-field Infrared Survey Explorer (WISE; Wright et al. 2010)
and from Two Micron All-Sky Survey (2MASS; Skrutskie et al. 2006) are as
folows: W1(3.4$\mu m$)=14.1, W2(4.6$\mu m$)=13.2, W3(11.6$\mu m$)=10.7,
W4(22$\mu m$)=8.5 and Ks=15.1, H=15.4, J=16.7. The optical magnitudes taken by
the UK Schmidt Telescope and outlined by the SuperCOSMOS Sky Surveys (Hambly
et al., 2001) are I=17.5, R=18.1 and B(J)=19.6. In addition, the Panoramic
Survey Telescope & Rapid Response System (Pan-STARRS; Flewelling et al. 2020)
five bands magnitudes are y=18.5, z=18.6, i=19.1, r=19.5 and g=20.2. In two
ultraviolet bands, near-UV (NUV) and far-UV (FUV), the Galaxy Evolution
Explorer (GALEX; Martin et al. 2005) imaged the host galaxy, and their
magnitudes are NUV=21.4, FUV=22.4.
Wright et al. (2010) in their Fig. 12 show a colour-colour diagram with
regions where the different classes of the WISE-detected sources are located.
The host of J0133$-$1302 has the following WISE colors (W1$-$W2)$=$0.9 and
(W2$-$W3)$=$2.5 and therefore belongs to the quasar class. According to Izotov
et al. (2014), galaxies with (W1$-$W2) colours greater than 1 magnitude are
mainly luminous galaxies with high-excitation HII regions. In addition,
Colafrancesco et al. (2016) have reported that the host galaxy is associated
with the ROSAT X-ray source 1RXSJ013313.8-13031. All of this indicates that
this host is a powerful AGN. Taking into account colours in the other bands
indicates that this object has red continua with $J-K=1.6$ and $g-r=0.7$.
Urrutia et al. (2009) and Young et al. (2008) classified objects possessing
colours $J-K>1.3$ and $g-r>0.5$ as red quasars. This class of quasars were
first discovered by Webster et al. (1995).
The discovery of J0133$-$1302 with the KAT-7 telescope was achieved as a
result of the large field of view of the instrument and its sensitivity to
extended and low surface brightness radio emission. However, poor resolution
of the KAT-7 radio telescope, due to its small baselines, and small collecting
area meant that it could not resolve the various components of the radio
source into distinct sources. For a deeper and detailed analysis, there was a
need for high resolution observations, which we obtained from the Giant
Metrewave Radio Telescope (GMRT; Swarup et al. 1991). For the first time, our
GMRT observations have resolved the extended sources in Colafrancesco et al.
(2016) into new sources which were not previously observed in the KAT-7 and
NVSS structures. The current paper thus extends the observational effort to
detect the components of the GRG and to study the morphology and spectrum of
this source. This GRG could be a powerful source with hints of restarting AGN
activity.
We present the details of the GMRT observations and all the data in Section 3,
while the results from the radio observations and the analysis are presented
in Section 4. The summary and conclusions follow in Section 5.
Throughout the paper a flat, vacuum-dominated Universe with $\Omega_{m}=0.32$
and $\Omega_{\Lambda}=0.68$ and $H_{0}=67.3$ km s-1Mpc-1 is assumed.

##  3 The Data

###  3.1 GMRT Observations

The follow up observations were carried out using the GMRT instrument at two
frequency bands: 323 MHz and 608 MHz in January 2016. The project code was
29_004 (PI: N. Mhlahlo). The observation dates were 04 January (608 MHz), 06
January (323 MHz) and 16 January 2016 (608 MHz), with the latter being make-up
observations, as the observations of 04 January were unusable due to bad radio
frequency interference (RFI). The total observing time on the source was 4
hours for each observation, at the central frequencies of 306 MHz and 591 MHz,
with a total bandwidth of 33 MHz.
Data were recorded using an 8-s integration time with the available frequency
band divided into 512 channels. The uv-data were reduced using the standard
tasks in the Astronomical Image Processing System (AIPS; Greisen 2003)
software package. Bad data which resulted from RFI and antenna malfunctions
were flagged using AIPS tasks TVFLG, WIPER and CLIP. To calibrate the data in
phase and flux we used the phase calibrator source 0116-208 and flux density
calibrator sources 3C147 and 3C48. The flux density calibrator sources were
also used to do bandpass calibration. The SPLIT task was used to transfer the
calibration to the target source, and the 512 channels were averaged to 16
channels at 323 MHz, and to 4 channels at 608 MHz. The reduced data were
deconvolved using the CLEAN algorithm, and the images were generated by AIPS
task IMAGR. Several rounds of phase-based self-calibration were performed, and
primary beam correction was done on the resulting images using the task FLATN.
Furthermore, the same data were reduced using the Source Peeling and
Atmospheric Modeling (SPAM) software package (Intema et al., 2009; Intema,
2014). SPAM, which is an extension to AIPS software package, provides fully-
automated data reduction scripts for high-resolution, low-frequency radio
interferometric observations of the GMRT data. The software includes direction
dependent calibration and imaging, different RFI and bad data mitigation
tasks, and modeling. The benefits of using SPAM software on GMRT data is that
the data reductions are very efficient, highly reproducible, and give good
quality results (Intema, 2014). All the images were loaded into CASA (Common
Astronomy Software Applications; McMullin et al. 2007) for further analysis.
The resulting maps are displayed in Fig. 1. The top panels contain the AIPS
images, and the SPAM images are shown in the bottom panels. In the bottom-
right panel the components of the GRG are labelled, where L1 represents the
south-eastern lobe and L2 the north-western lobe; C stands for the radio core
of the GRG, and B is possibly a background or foreground source, or one of the
multiple hotspots of a complex lobe.
In all the images we see diminished emission between the upper and lower part
of the southern lobe. This effect is enhanced in the AIPS images especially at
323 MHz which could indicate some missing flux at this frequency. Our study,
as a result, will focus on the SPAM images, which are better, as already
mentioned above.

###  3.2 Archival Data: GLEAM, NVSS and VLASS

Details of the GaLactic and Extra-galactic All-sky MWA Survey (GLEAM), which
was carried out with the Murchison Wide-field Array (MWA; Lonsdale et al.
2009; Tingay et al. 2013) are described by Wayth et al. (2015) and Hurley-
Walker et al. (2017). We accessed the data from this survey on the MWA
Telescope website 111http://www.mwatelescope.org/GLEAM. We used a set of 20
images with the bandwidth of 7.7 MHz over a frequency range of 76-231 MHz,
which is the frequency range covered by the survey. GLEAM has a mean beam size
of $\sim$ 2′. In the vicinity of our target source the rms varies between 5
and 15 mJy/beam.
For a proper spectral ageing it is necessary to have a good spectrum at many
radio frequencies as possible. The low-frequency GLEAM data are important for
proper estimation of alpha injection, and despite the larger beam (see Fig. 2)
and flux uncertainties, we ensured that we used the GLEAM data in a proper
way. We have taken extreme care to check if there are any
background/foreground sources which are not part of the GRG within the
immediate vicinity of the GRG, and if their respective fluxes are convolved in
the broad beam of GLEAM. We found that all the external sources are
independent of the GRG’s emission.
We also used the GRG data from the NVSS, which has a beam size of
$45^{\prime\prime}$, at 1.4 GHz. In addition, obtained VLA Sky
Survey222https://science.nrao.edu/science/surveys/vlass (VLASS) data which are
available to the public. VLASS provides coverage of the entire sky visible to
the VLA, above declination -40 deg, at high angular resolution and observing
frequency of 2.5 arcsec and 3 GHz, respectively (Lacy et al., 2020). We
obtained a quicklook (QL) image with a rms level of $\sim$0.13 mJy/beam where
the GRG core is clearly visible.

##  4 The Analysis And Results

Flux density measurements at 323 MHz and 608 MHz were performed with the AIPS
task TVSTAT, which adds up all the pixel values within the selected area to
give the total flux density of the selected source. We checked the consistency
of the flux scale based on five strong point sources in the field of the GRG.
We also checked the source positions using the same five point sources for
both GMRT maps.
The errors in flux density were determined using the equation

Figure 2: Radio image of the GRG J0133$-$1302\. Blue contours at 0.03 mJy/beam $\times$ 1, 2, 4 are GLEAM at 158 MHz, and the black contours are from GMRT at 608 MHz with contour levels similar to those in Fig. 1-bottom right panel. The resulting beams size are shown at the top left hand corner. Table 1: GLEAM flux densities for the lobes of J0133$-$1302 are shown after subtracting the fluxes of the Core and the background B source that were predicted from a quadratic fit and a straight line, respectively (Fig. 6), to the values at higher frequencies. For GLEAM, the calibration errors are approximated at 10% (Hurley-Walker et al., 2017). The angular resolution of the GLEAM survey is 2.5${}^{\prime}\times 2.2^{\prime}$ [sec ($\delta+26.7^{\circ}$)] at 154 MHz (Wayth et al., 2015). At the highest frequencies the resolution is $\sim 2^{\prime}$. In addition, the NVSS values are given. Telescope | Frequency | Flux Density$\pm$ error ($mJy$)
---|---|---
| (MHz) | L1 | L2
GLEAM | 84 | 254.15$\pm$64.62 | 314.92$\pm$68.98
| 92 | 232.19$\pm$55.48 | 277.60$\pm$59.24
| 99 | 208.29$\pm$54.20 | 278.35$\pm$59.05
| 107 | 257.44$\pm$45.57 | 246.50$\pm$46.68
| 115 | 178.13$\pm$37.10 | 209.69$\pm$40.39
| 122 | 190.66$\pm$35.69 | 235.22$\pm$40.00
| 130 | 165.46$\pm$32.19 | 196.36$\pm$35.56
| 143 | 179.83$\pm$35.38 | 241.93$\pm$40.79
| 151 | 107.61$\pm$30.31 | 210.20$\pm$37.18
| 158 | 156.68$\pm$30.39 | 158.37$\pm$32.82
| 166 | 127.26$\pm$30.59 | 153.34$\pm$33.61
| 174 | 164.89$\pm$31.18 | 173.79$\pm$33.69
| 181 | 170.26$\pm$29.84 | 135.33$\pm$29.80
| 189 | 109.90$\pm$26.17 | 149.89$\pm$30.00
| 197 | 121.68$\pm$27.32 | 237.68$\pm$35.76
| 204 | 103.89$\pm$22.38 | 197.48$\pm$29.67
| 212 | 94.43 $\pm$21.77 | 180.04$\pm$27.97
| 220 | 101.55$\pm$20.87 | 134.07$\pm$23.99
| 227 | 108.80$\pm$21.86 | 113.90$\pm$23.52
NVSS | 1400 | 16.3$\pm$1.5 | 42.98$\pm$2.33

$\Delta S=\sqrt{(S\times
0.05)^{2}+\Big{(}rms\times\sqrt{\frac{area}{beam}}\Big{)}^{2}}$ (1)

We calculated the error in the integrated flux densities ($S$) from two error
contributions. The first is from an absolute calibration uncertainty, which is
estimated at approximately 5% (similar as Ainsworth et al. 2016; Lal & Rao
2005, 2007; Mauch et al. 2013). The second is the rms noise of the map which
is taken into account by the second term in eq. 1, with $area$ standing for
the area of the source and $beam$ being the beam size.
The flux densities at other frequencies were obtained from the archival data
(see Section 3.2). In the GLEAM and NVSS images of the GRG, the GRG core (C)
is embedded in the diffuse plasma of the southern lobe, L1. Furthermore, there
is what appears to be a background/foreground source (B), or one of the
multiple hotspots of a complex lobe near the outer edge of the northern lobe
L2, which is unresolved in NVSS and GLEAM images - and there is no redshift or
spectral information about B in the literature. As a result, the flux
densities of B, C, L1, L2 could not be measured directly from the GLEAM and
NVSS maps. The flux densities of B and C were estimated using the best-fitting
power law models at higher frequencies, and extrapolated to the low GLEAM
frequencies for which we could not directly measure them due to poor
resolution or contamination of the diffuse emission of the lobes.
We first measured the flux densities of sources C and B from the SPAM (323,
608 MHz) and VLASS (3000 MHz) maps where they are resolved or separated, and
fitted a line/curve through those data to determine the spectral index (see
Fig. 6). We then used the spectral index to predict the core and background
source fluxes at the lower GLEAM frequencies and in NVSS. We then obtained the
total flux density values of the entire lobes in GLEAM and NVSS from
Vizier333http://vizier.u-strasbg.fr/viz-bin/VizieR, from which we subtracted
the predicted core fluxes and the background source fluxes. This resulted in
the estimated lobe fluxes (which exclude the core and background fluxes) in
the GLEAM and NVSS maps which are displayed in Table 1. For GLEAM, the point
at 76 MHz was removed, as the beam is very large and the whole source
(northern and southern lobe) is just a single blob.

Table 2: GMRT flux densities and spectral index for the different components of J0133$-$1302 at 325 MHz and 608 MHz. Structure | Flux Density (mJy) | Spectral Index
---|---|---
| 323 (MHz) | 608 (MHz) |  $\pm$ error
C | 6.75$\pm$0.42 | 12.99$\pm$0.70 | 0.72$\pm$0.13
L1 | 71.56$\pm$4.09 | 39.67$\pm$2.83 | -0.92$\pm$0.14
L2 | 131.24$\pm$7.38 | 76.23$\pm$4.45 | -0.79$\pm$0.13
S3 | 27.05$\pm$1.51 | 12.57$\pm$0.72 | -0.92$\pm$0.13
B | 12.57$\pm$0.74 | 9.70$\pm$0.56 | -0.45$\pm$0.13
S4a | 51.76$\pm$2.68 | 29.40$\pm$1.52 | -0.79$\pm$0.12
S4b | 34.84$\pm$1.84 | 23.33$\pm$1.22 | -0.60$\pm$0.12
S5 | 3.51$\pm$0.41 | 1.57$\pm$0.21 | -0.92$\pm$0.28

The errors in the GLEAM flux density were estimated as (e.g. Whittam et al.
2017)

$\Delta S=\sqrt{(S\times 0.1)^{2}+rms^{2}}$ (2)

with the calibration uncertainty being 10%, and the total error $\lesssim
25\%$.

Figure 3: A close-up look at the northern lobe in Fig. 1 (bottom right panel).

The total errors for the predicted core and background source fluxes are also
estimated at $\lesssim 25\%$.
The fluxes of all the GRG components in the GMRT data are displayed in Table
2. These fluxes, which include those of the new observed radio sources B, S3,
S4a and S4b (see Fig. 3) which are not resolved in the KAT-7 and NVSS images,
were measured directly from the SPAM maps at 323 MHz and 608 MHz. In addition
to these fluxes, the flux density of the core in NVSS at 1400 MHz was measured
to be 18.8$\pm$3.0 mJy. The background source is not resolved in the NVSS map
and its flux could not be measured. Furthermore, since the VLASS map shows
only the core and the structure B, the flux density was measured only for the
core and the background source. The flux density measurement of the core at
3000 MHz gave 21.85$\pm$1.16 mJy, and that of the background source was found
to be 4.87$\pm$0.51 mJy.

###  4.1 Source Morphology

Figure 4: Radio contours of the smoothed GRG image at 608 MHz are overlaid on
the smoothed optical red ′band′ image from PanSTARRS. The restoring beam of
the image is 8′′ $\times$ 5′′ (PA=-2 deg) and is shown in the bottom-left hand
corner. Radio contours start at 0.3 mJy/beam ($3\times rms$) and then scale by
a factor of 2. Figure 5: Spectral index image of J0133$-$1302\. Radio contours
of the GRG in GMRT at 608 MHz are overlayed on the colour-scale image of
spectral index between 323 MHz and 608 MHz. The contours are at -3, 3, 6, 12,
24, 48, 96 mJy/beam times the noise level. The spectral index scale is shown
at the right hand side of the figure. Figure 6: The spectra of the core, and
of the background source B. The exact frequencies of the data points shown in
this plot are 323, 608, 1400, 3000 MHz in the case of the core and 323, 608,
3000 MHz in the case of the background source. The exact flux density values
and errors of these data points are given in Table2 and in the text.

Figure 7: Top panel: Regions where spectral analysis was performed are
indicated by the circles, along the ridge lines of the proposed DBT. Middle
panels: showing spectral distribution along the circles labeled 1-9 (left) and
10-18 (right). Bottom panels: corresponding flux profiles at 323 MHz along the
same circles labeled 1-9 (left) and 10-18 (right) following the same numbering
order. Profiles at 608 MHz show similar trends.  Figure 8: The total spectrum
of the lobes of J0133$-$1302\. Each GLEAM point is an average of three GLEAM
fluxes. The curves represent the spectral ageing JP model fit. The exact
frequencies of the data points shown in this plot are 92, 115, 143, 166, 189,
215.75, 322.88, 607.96, 1400 MHz.

As it can be observed in Fig. 1, J0133$-$1302 has a clear core detection at
the two GMRT frequencies, and an optical counterpart (Fig.
4)444https://panstarrs.stsci.edu. The core appears less bright at lower radio
frequencies (Table 2), and gets brighter as the frequency increases, with the
highest brightness recorded at 3000 MHz. All the radio images in Fig. 1 seem
to show a double-lobed structure, albeit with an axially asymmetric
orientation. Lobe L1 shows a clear connection to the radio core C, with a
slight decrement in flux at the waist of the lobe (which is more enhanced in
the AIPS image at 323 MHz). This apparent connection of the southern lobe with
the core indicates that a jet might be present. The angular size of L1 is
$\sim 2^{\prime}$, corresponding to a projected linear size of $\sim$ 554 kpc.
In constrast, lobe L2 presents a complicated structure, and does not appear to
be connected to the core. For the first time, our GMRT observations have
resolved source S4 in Colafrancesco et al. (2016) into three sources, which
are S4a, S4b, and B as shown in the zoomed image in Fig. 3. The complex
structure of L2 presents a number of scenarios pertaining to the morphology of
J0133$-$1302\.
In Fig. 4, source B can be identified with an optical source and could be a
background/foreground source, while S4a and S4b, together with S3, could be
part of the GRG’s northern lobe emission. In this scenario, the angular size
of L2 would be $\sim 5.4^{\prime}$ ($\sim 1496$ kpc). Alternatively, B could
be the core of a DBT radio galaxy, with S4a and S4b being its lobes. In the
latter case, only S3 would form the GRG northern lobe emission, with the
angular size of L2 would be $\sim 3.7^{\prime}$ ($\sim 1024$ kpc), and that of
the entire source being $\sim 6.3^{\prime}$ ($\sim 1745$ kpc).
Another possibility is that source B could be one of the hotspots of a complex
lobe. Best et al. (1999) showed that nine out of eleven of their sources
selected from the 6C sample of Eales displayed multiple hotspots in one or
both lobes, where two of the sources, 0825+34 and 1011+36, which contain
double hotspots, have an inverted spectrum radio core. Hardcastle et al.
(2007) also observed more than one radio hotspot in at least one of the lobes
of a small sample of nearby classical double radio galaxies from which they
also detected X-ray emission. Two hotspots have also been observed in the
radio galaxy Pictor A (Perley et al., 1997) where it was postulated that the
presence of its hotspots suggests that this object probably was recently re-
activated. In this scenario, just as in the first, all the northern sources
would constitute L2, and, considering B and S4b have the possible hotspots of
the northern lobe, the size of the entire structure for both scenarios would
be $\sim 7.8^{\prime}$ (2161 kpc).
Colafrancesco et al. (2016) found the angular size for the entire northern
lobe to be $\sim 4^{\prime}$ and that for the southern lobe to be $\sim
1.2^{\prime}$, corresponding to projected linear sizes of $\sim$ 1107 kpc and
$\sim$332 kpc, respectively. The value obtained by Colafrancesco et al. (2016)
agrees with the value we obtained for the scenario where S3 is regarded as the
northern lobe hotspot or the northernmost extent of the GRG. However, our
value of the angular size for L1 is larger than theirs by slightly less than a
factor of two. This is due to the fact that most of the southern lobe emission
was convolved with the core emission in Colafrancesco et al. (2016). In the
scenario where all the northern sources (except B) are part of a giant
structure, only S4b would be the hotspot. In that case, we would expect the
flux density of S4b to be higher than that of S4a, however, the flux density
of S4a is higher than that of S4b at both GMRT frequencies (Table 2).
The conservative approach would be to regard S3 as the northern lobe hotspot
or the northernmost extent of the source. In this case we would expect S3 to
show a similar spectrum to that of L1. Under the assumption that B is the core
of a DBT RG (meaning that only S3 is part of the GRG northern lobe as already
mentioned above), and that the lobes of the putative DBT RG are symmetric in
flux, the higher flux density of S4a would indicate the mixing of the emission
both from the DBT RG’s lower lobe (S4a) and the GRG’s upper lobe (associated
with S3) at or near the location of S4a. This suspected mixing of emission
should lead to spectral steepening at S4a.
We do not observe any compact and pronounced hotspots in L1.
We note that J0133$-$1302 presents a highly asymmetric large-scale structure
where the core is shifted towards the southern lobe. There are two main
effects that have been used to explain structural asymmetry in radio galaxies:
relativistic beaming (e.g. Alhassan et al. 2019) and jet-environment
interactions, via jet entraintment (e.g. Perucho 2014), jet stalling
(Massaglia et al., 2016) or failed collimation of an initially conical jet by
the environment (Krause et al., 2012) as well as lobe-environment interactions
which are important at large scales and which are supported by dynamical radio
source models (e.g. Hardcastle 2018) and numerical simulations (Hardcastle &
Krause, 2013, 2014). There are sources, however, whose asymmetric structure
cannot be understood easily by ascribing it either to orientation and
relativistic beaming effects, or to different kinds of interaction with the
environment or asymmetric distribution of gas in the environment (Saikia et
al., 1996). Some of these sources are characterised by the apparent absence of
a hotspot either on one lobe (e.g. J1211$+$743: Pirya et al. 2011), or both
lobes (e.g. 0500$+$630 (4C63.07): Saikia et al. 1996, J1918$+$742: Pirya et
al. 2011). In the former case, a diffuse radio component on one side of the
galaxy is observed while the opposite component appears edge-brightened with a
prominent hotspot. This also includes Hybrid morphology radio sources (HyMoRS)
which are a rare type of radio galaxies that display different FR types on
opposite sides of their nuclei (Gopal-Krishna & Wiita, 2000; Gawroński et al.,
2006; Kapińska et al., 2017). For some of these sources the radio jet is
facing the diffuse lobe (e.g. J1211$+$743: Pirya et al. 2011). J0133$-$1302,
to some extent, seems to show a structure that is similar to the two sources
that were studied by Pirya et al. (2011) as it shows a diffuse southern lobe
without a prominent hotspot at the outer edge, and a northern lobe with a
possibility of the presence of a single or multiple hotspots.
However, recently Rodman et al. (2019) investigated the relationship between
asymmetries in radio source properties and those of the environment where they
quantified the asymmetry in the radio source environment through optical
galaxy clustering which they argue provides a proxy for the ambient gas
density distribution which interacts with the radio lobes. They found that the
length of radio lobes in FRII sources is anticorrelated with both galaxy
clustering and lobe luminosity, suggesting that the environment is the cause
of radio source asymmetry. More light on the cause of the asymmetry of
J0133$-$1302 will be shed by future studies that will involve quantifying the
environment of J0133$-$1302, that will also be useful for testing the
predictions of the orientation unification model (Mullin et al. 2008,
Spinoglio & Fernández-Ontiveros 2021) for this source.
To probe the entire structure of J0133$-$1302 we used the symmetry parameters
of this source, and observed that it is very asymmetric in its arm-length
(separation) as well as flux density ratios. We have determined the arm-length
ratio (AR) and the flux ratio (FR) for two scenarios: the one where S4b has
the possible hotspot of the northern lobe (AR, FR = 3.35, 1.8, respectively),
and where S3 is the northern lobe hotspot, or the northernmost extent of the
source (AR, FR = 2.4, 2.6, respectively). Ishwara-Chandra & Saikia (1999)
found the median value of the higher luminosity GRGs in their sample to be
about 1.39 for the arm-length ratio, while Konar et al. (2008), for their
sample of 10 giant radio sources, found a median value of $\sim$1.31, and both
values are smaller than those we have obtained above, pointing to the
exceptionally large asymmetry of our source. Also, the flux ratios for our
source are larger than theirs, except for one source (if it is compared to
scenario 1 above).
Since the southern lobe has no pronounced hotspot, we cannot constrain the
beaming effect in J0133$-$1302.

###  4.2 Spectral Index Analysis

####  4.2.1 GRG lobes and core

The spectral index distribution of the lobes of a GRG can provide crucial
information about its history. The spectral index map of J0133$-$1302 was
obtained by comparing the SPAM images at 323 MHz and 608 MHz. The resolutions
of the two images were 12.27′′ $\times$ 6.70′′ at 323 MHz and 7.94′′ $\times$
5.09′′ at 608 MHz. To produce the spectral index map with the same beam and
cell size the following steps were taken: i) the images were convolved using
the task IMSMOOTH in CASA (since the resolutions of the two images were very
close), and the beams were made to be circular, with a resulting beam size of
13′′ $\times$ 13′′, ii) the geometry of the maps was aligned using the task
HGEOM in AIPS, iii) the task COMB was then used to produce the spectral index
image.
The spectral index map is shown in Fig. 5, revealing a very flat radio core
spectrum, with a mean spectral index ($S_{\nu}\propto\nu^{-\alpha}$) of
$\alpha^{0.6}_{0.3}=0.72\pm 0.13$. The spectrum in the lobes is patchy, with
regions of very steep and relatively flatter spectrum. The mean spectral index
in the lower lobe is $\alpha^{0.6}_{0.3}=-0.92\pm 0.14$ (exluding the two
flatter tiny patches in the south-west side of the lobe) while it is
$\alpha^{0.6}_{0.3}=-0.79\pm 0.13$ for L2 (after excluding only source B).
In Fig. 6 are the spectra for the radio core and the background source. The
observed $S-\nu$ relation was fitted with

$\log\left[\frac{S}{\mathrm{mJy}}\right]=-5.75+4.15\log\left[\frac{\nu}{\mathrm{MHz}}\right]-0.61\left(\log\left[\frac{\nu}{\mathrm{MHz}}\right]\right)^{2}$

for the core, and with

$\log{\left[\frac{S}{\mathrm{mJy}}\right]}=2.17-0.43\log\left[\frac{\nu}{\mathrm{MHz}}\right]$

for the background source. The core exhibits an inverted spectrum, and there
is an expectation for the fit to go down at higher frequencies. The flat and
inverted spectrum of the core indicates the presence of energised relativistic
electrons, and points to dynamical activity of a recurrent activity radio
galaxy (Saikia & Jamrozy, 2009). Such sources are characterised by their flat
spectral index of the core, and relic/dying lobes. The spectrum of the
resurrecting central engine becomes much flatter than those of the diffuse
emission, which is what we observe for J0133$-$1302\. We note that the
spectral index of S3 ($\alpha^{0.6}_{0.3}=-0.92\pm 0.13$) is very similar to
that of L1 ($\alpha^{0.6}_{0.3}=-0.92\pm 0.14$), a strong indication that
among the northern sources, only S3 belongs to J0133$-$1302\. The smaller
structure, S5 (see Fig. 5), could be part of L2. Its spectral index value
($\alpha^{0.6}_{0.3}=-0.91\pm 0.23$) is very similar to that of S3 and L1. The
measured flux and spectral index values for all the GRG components are
tabulated in Table 2.

####  4.2.2 Putative DBT radio galaxy core and lobes

As already indicated, sources S4a ($\alpha^{0.6}_{0.3}=-0.79\pm 0.12$) and S4b
($\alpha^{0.6}_{0.3}=-0.60\pm 0.12$) could be connected to the compact source
B ($\alpha^{0.6}_{0.3}=-0.45\pm 0.13$) (see Fig. 5). To investigate this
possibility, in Fig. 7 we show the spectral index distribution of the proposed
DBT source. We computed the spectral index at nine different positions for
both the southern blob (S4a) and the northern blob (S4b) at 323 MHz and 608
MHz, starting at B, and at about 7.5′′ from B, respectively, and going towards
the end of the tail, averaging the spectral index values within small circular
bins (3${}^{\prime\prime}\times 3^{\prime\prime}$ in size). The circles, along
the ridge lines of the proposed DBT, defining the regions where we did our
analysis, are shown in Fig. 7 (top panel).
If the proposed source were a typical tailed radio galaxy, it would be very
flat at, and near the nucleus. And as one gets into the brighter parts of the
tails, the spectral index might get a bit flatter again. But then, as one
progressed further along, there should be clear steepening, as one went off
the nucleus. This is what we observe (middle panels). The spectral index is
flatter in the regions closer to the nucleus for S4a
($\alpha^{0.6}_{0.3}=-0.1\div-0.35$) and S4b ($\alpha=-0.2\div-0.3$) where
more energetic electrons are continuously injected by the central engine, and
then it steepens along the lobes, as one moves futher from B, reaching values
of ($\alpha\sim-0.8\div-0.9$) for both lobes. The flattening in the southern
blob, from $20^{\prime\prime}-40^{\prime\prime}$, and at 20′′ in the northern
blob, should indicate where the flux is going up. This can be seen in the
bottom panels of Fig. 7, which show the variation in flux densities as one
moves away from B. This suggests that the spectral behaviour, of both the
northern and southern parts of the proposed source, is consistent with what is
expected from a tailed RG. The steepening of the spectral index along the tail
of the DBT RG implies that the relativistic electrons that are responsible for
the radio emission suffered energy losses after their first ejection from the
nucleus B. Furthermore, the average spectral index of S4a is steeper than that
of S4b. This asymmetry in spectral index could be the result of mixing of
emission between S3 and S4a, and might be an indication of some interaction
between the two sources. Investigating such interaction would require redshift
information on this proposed DBT source, as well as data at more than two
frequencies for a detailed spectral index analysis.

###  4.3 Source Energetics

The spectrum of J0133-1302 was initially fit with the JP (Jaffe & Perola,
1973) and continuous injection (CI: Pacholczyk 1970) models of radiative
losses which describe the time-evolution of the emission spectrum from
particles with an initial power-law energy distribution characterised by the
injection spectral index $\alpha_{inj}$ and distributed isotropically in pitch
angle relative to the magnetic field direction.
We found that the CI model does not provide a good fit to the data (e.g. has
worse values of the reduced $\chi^{2}$). In addition, its application to the
lobes of J0313$-$1302 is physically unjustifiable. This is because there could
hardly be any compact hotspots, and it seems that the jets are no longer
feeding the lobes. Therefore, the JP model is more appropriate to fit the
spectra of this source. However, caveats related to this model outlined e.g.
by Harwood et al. (2013, 2015); Harwood et al. (2017) need to be borne in
mind. In applying the JP model, our assumptions are: (i) the radiating
particles after entering the lobes are not re-accelerated, (ii) the magnetic
field lines are completely tangled and the field strength is constant
throughout the energy-loss process, (iii) the particles have a constant power-
law energy distribution and (iv) the time of isotropization of the pitch
angles of the particles is short compared with their radiative lifetime.
Using the SYNAGE software package (Murgia, 1996), the JP model fit to the
spectra of the lobes was performed, with the normalisation, the injection
spectral index ($\alpha_{inj}$) and the break frequency ($\nu_{br}$) left as
free parameters. Fitting results are shown in Fig. 8. The break frequency was
found to be $\nu_{br}=22.1$ GHz for the southern lobe and $\nu_{br}=19.7$ GHz
for the northern lobe. However, one has to remember that the break frequency
is based on an extrapolation of the measurement. The fitted injection spectral
index, $\alpha_{inj}\sim-0.89$ of the L1 southern lobe is different from the
fitted injection spectral index of L2 (all northern sources excluding B) which
is $\alpha_{inj}\sim-0.62$. In other words, while the injection spectral index
of the lower lobe is in agreement with what we measure from the spectral index
image ($\alpha\sim-0.92$), that of the upper lobe does not agree with the
image spectral index average value of $\alpha\sim-0.79$. This could be due to
the complicated structure of the northern lobe.
It is not easy to recognize conclusively what ingredients the northern lobe
consists of. However, and as already indicated, the fact that the S3 structure
has a spectral index value of $-0.92\pm 0.23$ which is similar to the spectral
index value of L1 (Table 2) could suggest that only S3 belongs to the source
J0133$-$1302, whereas S4a, S4b and B constitute a distinct source, which we
suggest is a DBT RG, or S4a and B are the hotspots of a complex lobe.
Because of the problems associated with the complex structure of the northern
lobe of J0133$-$1302, we have attempted to estimate the magnetic field
strength and synchrotron age for only the southern lobe L1.
The spectral age can be calculated using

$\tau_{rad}=50.3\frac{B_{eq}^{0.5}}{B_{eq}^{2}+B_{CMB}^{2}}(\nu_{br}(1+z))^{-0.5}{\mathrm{Myr}}$
(3)

$B_{CMB}=0.318(1+z)^{2}$ is the magnetic field strength equivalent to the
cosmic microwave background radiation at the redshift $z=0.3$ of our target.
Using the minimum energy arguments, we calculated the magnetic field following
Longair (2011). Our assumptions included the cutoff frequencies of
$\nu_{min}=10$ MHz and $\nu_{max}=100$ GHz, the filling factor of 1, and the
pure electron-positron plasma. The volume of the lobe was approximated by
assuming a cylindrical shape of 1.5 arcmin in length and a radius of 0.3
arcmin. This led to the value of the magnetic field strength of $B=1.3\pm 0.1$
$\mu G$. Our small value of the magnetic field strength is comparable to the
values estimated for other GRGs (see e.g. Konar et al. 2008; Machalski et al.
2009). Our ageing analysis suggests that at the estimated break frequency of
this lobe of 22.1 GHz, the corresponding spectral age is about 11 Myr.
However, the above break frequency is located outside the range of frequencies
(the highest value is 1.4 GHz) where the flux densities are measured. This
implies that the age of the southern lobe should be less than about 44 Myr.

##  5 Summary and Conclusion

We have performed an analysis of the radio core and lobes of GRG J0133$-$1302
at multi-radio frequencies using data from the GMRT and public surveys. Our
comparison of the radio spectral indices of the lobes and the radio core has
revealed a steep spectrum of the lobes, which is contrasted by the flat
inverted spectrum of the core. From the spectral index map, the lobes have
spectral index values of $\alpha\sim-0.92$ (L1), and $\sim-0.79$ (L2), while
the spectral index of the core is $\alpha\sim 0.7$. This suggests decaying
emission of the lobes and restarting core activity for J0133$-$1302 radio
galaxy, where the emission is breaking out once more, leading to the spectrum
of the central structure being inverted and much flatter than those of the
diffuse sources which were created by the previous cycle of AGN activity. At
the redshift of $\sim 0.3$ (Colafrancesco et al., 2016) L1 has a linear size
of $\sim 0.6$ Mpc, and the entire source has a projected linear size of
$\lesssim$2 Mpc.
We found that the structure of the northern lobe is complex, and this has led
us to identify four possibilities regarding the overall structure of the GRG
which are:
i) all the northern sources (except B) are part of a giant structure L2, where
only S4b could be the remnant hotspot,
ii) all the northern sources are part of a giant structure L2, where B and S4b
could be the remnant hotspots of a complex lobe.
iii) only S3 forms the GRG northern lobe, and subsequently
iv) the source B is possibly the core of a DBT RG, and S4a and S4b are its
lobes.
Our spectral index analysis seems to support ii), iii) and iv) for the
following reasons:
a) concerning ii), sources B and S4b have flatter spectra when compared to the
other northern sources and thus could be hotspots.
b) regarding iii), S3 and L1 have very similar spectral index values and are
steep, which is an indication of decaying lobe emission of a restarting AGN.
This suggests S3 belongs to the GRG.
c) and regarding iv), our spectral analysis provides evidence that suggests
that both the northern and southern parts of the proposed DBT source show a
behavour that is consistent with what is expected from a tailed RG. The
proposed DBT shows steepening of the spectral index along the tail, which
implies that the relativistic electrons that are responsible for the radio
emission suffered energy losses after their first ejection from the nucleus B.
DBT radio sources are generally associated with clusters of galaxies (Blanton
et al., 2000; Dehghan et al., 2014) and have been used to find nearby and
distant clusters (up to $z\sim 2$, e.g. Blanton et al. 2003; Dehghan et al.
2014). This association of DBT sources with clusters has been supported by
recent simulations (see Mguda et al. 2015) which have shown that clusters with
masses above $10^{13}h^{-1}$ M⊙ typically host at least one DBT radio source
at some epoch, and those with masses in excess of $10^{15}h^{-1}$ M⊙ are
likely to contain multiple DBT radio sources (subject to AGN duty-cycle and
projection effects). However, contrary to these expectations and the
simulations by Mguda et al. (2015), a study by O’Brien et al. (2018) using a
small sample of DBT sources found that there are a few DBT sources within
known clusters, and that most of the DBT sources do not reside in clusters.
They note that while the former observation may be explained by sensitivity
and resolution effects, the latter casts doubt on the current models of bent-
tail galaxies.
We find that the radial distance from the ACO209 cluster center to the
background source B is 8 Mpc, which is much larger than the size of this
cluster which is at a redshift of $\sim$0.206. This suggests our DBT source
lies outside the cluster environment, and could be one of the DBT galaxies
that should be found outside massive clusters (Mguda et al., 2015; O’Brien et
al., 2018).
It is known that the presence of a tailed RG can heavily influence some of the
giant radio sources, e.g. radio halos, by supplying relativistic electrons to
those sources (Giovannini et al., 1993). In our case, S4a could be associated
with the emission in the northern part of the northern lobe of the GRG. In
other words, the tailed RG’s southern lobe (S4a) might be embedded in, or
passing through, the northern part of the upper lobe of the GRG (S3). In this
situation the GRG upper lobe might have supplied relativistic electrons to the
tailed RG.
Having shown indications of restarting activity in the nucleus, J0133$-$1302
can be added to the list of a few sources where there is episodic activity in
an AGN but the source does not have a large-scale DDRG morphology (Hernández-
García et al. 2017; see also Mahatma et al. 2019; Dabhade et al. 2020a, b).
Thorough multi-frequency analysis combined with environmental analysis is
necessary to study the morphological and spectral details of these sources.
Furthermore, these radio sources will be perfect objective for the upcoming
deep, wide-field MeerKAT and Square Kilometre Array (SKA) surveys that will
have the potential to study their population evolution up to high redshifts.

## Acknowledgements

NM would like to thank Lawrence Rudnick for the insightful discussions on the
proposed DBT source. We thank the anonymous referee whose comments have helped
to improve the paper. This work is based on the research supported by the
National Research Foundation of South Africa (grant number 111735). MJ was
supported by Polish NSC grant UMO-2018/29/B/ST9/01793. We thank the staff of
the GMRT, who made these observations possible. GMRT is run by the National
Centre for Radio Astrophysics of the Tata Institute of Fundamental Research.

## Data availability

Data is available on request from the authors.

## References

  * Ainsworth et al. (2016) Ainsworth R. E., Scaife A. M. M., Green D. A., Coughlan C. P., Ray T. P., 2016, MNRAS, 459, 1248
  * Alhassan et al. (2019) Alhassan J. A., Ubachukwu A. A., Odo F. C., Onuchukwu C. C., 2019, Rev. Mex. Astron. Astrofis., 55, 151
  * Begelman et al. (1984) Begelman M. C., Blandford R. D., Rees M. J., 1984, Reviews of Modern Physics, 56, 255
  * Best et al. (1999) Best P. N., Eales S. A., Longair M. S., Rawlings S., Rottgering H. J. A., 1999, MNRAS, 303, 616
  * Blanton et al. (2000) Blanton E. L., Gregg M. D., Helfand D. J., Becker R. H., White R. L., 2000, ApJ, 531, 118
  * Blanton et al. (2003) Blanton E. L., Gregg M. D., Helfand D. J., Becker R. H., White R. L., 2003, AJ, 125, 1635
  * Brienza et al. (2016) Brienza M., et al., 2016, A&A, 585, A29
  * Colafrancesco et al. (2016) Colafrancesco S., Mhlahlo N., Jarrett T., Oozeer N., Marchegiani P., 2016, MNRAS, 456, 512
  * Condon et al. (1998) Condon J. J., Cotton W. D., Greisen E. W., Yin Q. F., Perley R. A., Taylor G. B., Broderick J. J., 1998, AJ, 115, 1693
  * Cordey (1987) Cordey R. A., 1987, MNRAS, 227, 695
  * Cotton et al. (2020) Cotton W. D., et al., 2020, MNRAS, 495, 1271
  * Dabhade et al. (2020a) Dabhade P., et al., 2020a, A&A, 635, A5
  * Dabhade et al. (2020b) Dabhade P., et al., 2020b, A&A, 642, A153
  * Dehghan et al. (2014) Dehghan S., Johnston-Hollitt M., Franzen T. M. O., Norris R. P., Miller N. A., 2014, AJ, 148, 75
  * Fanaroff & Riley (1974) Fanaroff B. L., Riley J. M., 1974, MNRAS, 167, 31P
  * Flewelling et al. (2020) Flewelling H. A., et al., 2020, ApJS, 251, 7
  * Foley et al. (2016) Foley A. R., et al., 2016, MNRAS, 460, 1664
  * Gawroński et al. (2006) Gawroński M. P., Marecki A., Kunert-Bajraszewska M., Kus A. J., 2006, A&A, 447, 63
  * Giovannini et al. (1993) Giovannini G., Feretti L., Venturi T., Kim K. T., Kronberg P. P., 1993, ApJ, 406, 399
  * Giovannini et al. (2005) Giovannini G., Taylor G. B., Feretti L., Cotton W. D., Lara L., Venturi T., 2005, ApJ, 618, 635
  * Gopal-Krishna & Wiita (2000) Gopal-Krishna Wiita P. J., 2000, A&A, 363, 507
  * Gopal-Krishna et al. (1989) Gopal-Krishna Wiita P. J., Saripalli L., 1989, MNRAS, 239, 173
  * Greisen (2003) Greisen E. W., 2003, AIPS, the VLA, and the VLBA. p. 109, doi:10.1007/0-306-48080-8_7
  * Hambly et al. (2001) Hambly N. C., et al., 2001, MNRAS, 326, 1279
  * Hardcastle (2018) Hardcastle M. J., 2018, MNRAS, 475, 2768
  * Hardcastle & Croston (2020) Hardcastle M. J., Croston J. H., 2020, New Astron. Rev., 88, 101539
  * Hardcastle & Krause (2013) Hardcastle M. J., Krause M. G. H., 2013, MNRAS, 430, 174
  * Hardcastle & Krause (2014) Hardcastle M. J., Krause M. G. H., 2014, MNRAS, 443, 1482
  * Hardcastle et al. (2007) Hardcastle M. J., Croston J. H., Kraft R. P., 2007, ApJ, 669, 893
  * Harwood et al. (2013) Harwood J. J., Hardcastle M. J., Croston J. H., Goodger J. L., 2013, MNRAS, 435, 3353
  * Harwood et al. (2015) Harwood J. J., Hardcastle M. J., Croston J. H., 2015, MNRAS, 454, 3403
  * Harwood et al. (2017) Harwood J. J., et al., 2017, MNRAS, 469, 639
  * Hernández-García et al. (2017) Hernández-García L., et al., 2017, A&A, 603, A131
  * Hunik & Jamrozy (2016) Hunik D., Jamrozy M., 2016, ApJ, 817, L1
  * Hurley-Walker et al. (2015) Hurley-Walker N., et al., 2015, MNRAS, 447, 2468
  * Hurley-Walker et al. (2017) Hurley-Walker N., et al., 2017, MNRAS, 464, 1146
  * Intema (2014) Intema H. T., 2014, in Astronomical Society of India Conference Series. p. 469 (arXiv:1402.4889)
  * Intema et al. (2009) Intema H. T., van der Tol S., Cotton W. D., Cohen A. S., van Bemmel I. M., Röttgering H. J. A., 2009, A&A, 501, 1185
  * Ishwara-Chandra & Saikia (1999) Ishwara-Chandra C. H., Saikia D. J., 1999, MNRAS, 309, 100
  * Ishwara-Chandra & Saikia (2002) Ishwara-Chandra C. H., Saikia D. J., 2002, New Astron. Rev., 46, 71
  * Izotov et al. (2014) Izotov Y. I., Guseva N. G., Fricke K. J., Henkel C., 2014, A&A, 561, A33
  * Jaffe & Perola (1973) Jaffe W. J., Perola G. C., 1973, A&A, 26, 423
  * Jamrozy (2012) Jamrozy M., 2012, in European Physical Journal Web of Conferences. p. 06007, doi:10.1051/epjconf/20123906007
  * Jamrozy et al. (2004) Jamrozy M., Klein U., Mack K. H., Gregorini L., Parma P., 2004, A&A, 427, 79
  * Jamrozy et al. (2008) Jamrozy M., Konar C., Machalski J., Saikia D. J., 2008, MNRAS, 385, 1286
  * Kapińska et al. (2017) Kapińska A. D., et al., 2017, AJ, 154, 253
  * Komberg & Pashchenko (2009) Komberg B. V., Pashchenko I. N., 2009, Astronomy Reports, 53, 1086
  * Konar et al. (2008) Konar C., Jamrozy M., Saikia D. J., Machalski J., 2008, MNRAS, 383, 525
  * Krause et al. (2012) Krause M., Alexander P., Riley J., Hopton D., 2012, MNRAS, 427, 3196
  * Kronberg et al. (2004) Kronberg P. P., Colgate S. A., Li H., Dufton Q. W., 2004, ApJ, 604, L77
  * Kuźmicz et al. (2017) Kuźmicz A., Jamrozy M., Kozieł-Wierzbowska D., Weżgowiec M., 2017, MNRAS, 471, 3806
  * Lacy et al. (2020) Lacy M., et al., 2020, PASP, 132, 035001
  * Laing et al. (2005) Laing R. A., Canvin J. R., Bridle A. H., 2005, in Sjouwerman L. O., Dyer K. K., eds, X-Ray and Radio Connections. p. 7.02 (arXiv:astro-ph/0405020)
  * Lal & Rao (2005) Lal D. V., Rao A. P., 2005, MNRAS, 356, 232
  * Lal & Rao (2007) Lal D. V., Rao A. P., 2007, MNRAS, 374, 1085
  * Lara et al. (2000) Lara L., Mack K. H., Lacy M., Klein U., Cotton W. D., Feretti L., Giovannini G., Murgia M., 2000, A&A, 356, 63
  * Lara et al. (2001a) Lara L., Cotton W. D., Feretti L., Giovannini G., Marcaide J. M., Márquez I., Venturi T., 2001a, A&A, 370, 409
  * Lara et al. (2001b) Lara L., Márquez I., Cotton W. D., Feretti L., Giovannini G., Marcaide J. M., Venturi T., 2001b, A&A, 378, 826
  * Lister et al. (2016) Lister M. L., et al., 2016, AJ, 152, 12
  * Longair (2011) Longair M. S., 2011, High Energy Astrophysics
  * Maccagni et al. (2020) Maccagni F. M., Serra P., Murgia M., Govoni F., Morokuma-Matsui K., Kleiner D., 2020, arXiv e-prints, p. arXiv:2006.00897
  * Machalski et al. (2001) Machalski J., Jamrozy M., Zola S., 2001, A&A, 371, 445
  * Machalski et al. (2008) Machalski J., Kozieł-Wierzbowska D., Jamrozy M., Saikia D. J., 2008, ApJ, 679, 149
  * Machalski et al. (2009) Machalski J., Jamrozy M., Saikia D. J., 2009, MNRAS, 395, 812
  * Mahatma et al. (2018) Mahatma V. H., et al., 2018, MNRAS, 475, 4557
  * Mahatma et al. (2019) Mahatma V. H., et al., 2019, A&A, 622, A13
  * Malarecki et al. (2013) Malarecki J. M., Staveley-Smith L., Saripalli L., Subrahmanyan R., Jones D. H., Duffy A. R., Rioja M., 2013, MNRAS, 432, 200
  * Marecki et al. (2016) Marecki A., Jamrozy M., Machalski J., 2016, MNRAS, 463, 338
  * Martin et al. (2005) Martin D. C., et al., 2005, ApJ, 619, L1
  * Massaglia et al. (2016) Massaglia S., Bodo G., Rossi P., Capetti S., Mignone A., 2016, A&A, 596, A12
  * Mauch et al. (2013) Mauch T., Klöckner H.-R., Rawlings S., Jarvis M., Hardcastle M. J., Obreschkow D., Saikia D. J., Thompson M. A., 2013, MNRAS, 435, 650
  * McMullin et al. (2007) McMullin J. P., Waters B., Schiebel D., Young W., Golap K., 2007, CASA Architecture and Applications. p. 127
  * Mguda et al. (2015) Mguda Z., Faltenbacher A., Heyden K. v. d., Gottlöber S., Cress C., Vaisanen P., Yepes G., 2015, MNRAS, 446, 3310
  * Miley (1980) Miley G., 1980, ARA&A, 18, 165
  * Mingo et al. (2019) Mingo B., et al., 2019, MNRAS, 488, 2701
  * Mullin et al. (2008) Mullin L. M., Riley J. M., Hardcastle M. J., 2008, MNRAS, 390, 595
  * Murgia (1996) Murgia M., 1996, PhD thesis, -
  * Murgia et al. (2011) Murgia M., et al., 2011, A&A, 526, A148
  * O’Brien et al. (2018) O’Brien A. N., Norris R. P., Tothill N. F. H., Filipović M. D., 2018, MNRAS, 481, 5247
  * Pacholczyk (1970) Pacholczyk A. G., 1970, Radio astrophysics. Nonthermal processes in galactic and extragalactic sources
  * Parma et al. (2007) Parma P., Murgia M., de Ruiter H. R., Fanti R., Mack K. H., Govoni F., 2007, A&A, 470, 875
  * Perley et al. (1997) Perley R. A., Roser H.-J., Meisenheimer K., 1997, A&A, 328, 12
  * Perucho (2014) Perucho M., 2014, in International Journal of Modern Physics Conference Series. p. 1460165 (arXiv:1310.7746), doi:10.1142/S2010194514601653
  * Pirya et al. (2011) Pirya A., Nandi S., Saikia D. J., Singh M., 2011, Bulletin of the Astronomical Society of India, 39, 547
  * Quici et al. (2021) Quici B., et al., 2021, Publ. Astron. Soc. Australia, 38, e008
  * Randriamanakoto et al. (2020) Randriamanakoto Z., Ishwara-Chandra C. H., Taylor A. R., 2020, MNRAS, 496, 3381
  * Rengelink et al. (1997) Rengelink R. B., Tang Y., de Bruyn A. G., Miley G. K., Bremer M. N., Roettgering H. J. A., Bremer M. A. R., 1997, A&AS, 124, 259
  * Rodman et al. (2019) Rodman P. E., et al., 2019, MNRAS, 482, 5625
  * Safouris et al. (2009) Safouris V., Subrahmanyan R., Bicknell G. V., Saripalli L., 2009, MNRAS, 393, 2
  * Saikia & Jamrozy (2009) Saikia D. J., Jamrozy M., 2009, Bulletin of the Astronomical Society of India, 37, 63
  * Saikia et al. (1996) Saikia D. J., Thomasson P., Jackson N., Salter C. J., Junor W., 1996, MNRAS, 282, 837
  * Saripalli et al. (2005) Saripalli L., Hunstead R. W., Subrahmanyan R., Boyce E., 2005, AJ, 130, 896
  * Schoenmakers et al. (2000) Schoenmakers A. P., de Bruyn A. G., Röttgering H. J. A., van der Laan H., Kaiser C. R., 2000, MNRAS, 315, 371
  * Shabala et al. (2020) Shabala S. S., Jurlin N., Morganti R., Brienza M., Hardcastle M. J., Godfrey L. E. H., Krause M. G. H., Turner R. J., 2020, MNRAS, 496, 1706
  * Shulevski et al. (2017) Shulevski A., et al., 2017, A&A, 600, A65
  * Skrutskie et al. (2006) Skrutskie M. F., et al., 2006, AJ, 131, 1163
  * Spinoglio & Fernández-Ontiveros (2021) Spinoglio L., Fernández-Ontiveros J. A., 2021, IAU Symposium, 356, 29
  * Subrahmanyan et al. (2008) Subrahmanyan R., Saripalli L., Safouris V., Hunstead R. W., 2008, ApJ, 677, 63
  * Swarup et al. (1991) Swarup G., Ananthakrishnan S., Kapahi V. K., Rao A. P., Subrahmanya C. R., Kulkarni V. K., 1991, Current Science, 60, 95
  * Tamhane et al. (2015) Tamhane P., Wadadekar Y., Basu A., Singh V., Ishwara-Chandra C. H., Beelen A., Sirothia S., 2015, MNRAS, 453, 2438
  * Urrutia et al. (2009) Urrutia T., Becker R. H., White R. L., Glikman E., Lacy M., Hodge J., Gregg M. D., 2009, ApJ, 698, 1095
  * Wayth et al. (2015) Wayth R. B., et al., 2015, Publ. Astron. Soc. Australia, 32, e025
  * Webster et al. (1995) Webster R. L., Francis P. J., Petersont B. A., Drinkwater M. J., Masci F. J., 1995, Nature, 375, 469
  * Whittam et al. (2017) Whittam I. H., Green D. A., Jarvis M. J., Riley J. M., 2017, MNRAS, 464, 3357
  * Wright et al. (2010) Wright E. L., et al., 2010, AJ, 140, 1868
  * Young et al. (2008) Young M., Elvis M., Risaliti G., 2008, ApJ, 688, 128


NANCY:
Next-generation All-sky Near-infrared Community surveY

Roman Core Community Survey Category: High Latitude Wide Area Survey

Scientific Categories: Solar system astronomy; stellar physics and stellar
types; stellar populations and the interstellar medium; galaxies; the
intergalactic medium and the circumgalactic medium, supermassive black holes
and active galaxies; large scale structure of the universe

Submitting Authors: Jesse Han<EMAIL_ADDRESS>Arjun Dey
<EMAIL_ADDRESS>
Affiliation: Harvard-Smithsonian Center for Astrophysics, NOIRLab

Contributing Authors

## Survey Scope

The Nancy Grace Roman Space Telescope (Roman) is capable of delivering an
unprecedented all-sky, high-spatial resolution, multi-epoch infrared map to
the astronomical community. This opportunity arises in the midst of numerous
ground- and space-based surveys that will provide extensive spectroscopy and
imaging together covering the entire sky (such as Rubin/LSST, Euclid, UNIONS,
SPHEREx, DESI, SDSS-V, GALAH, 4MOST, WEAVE, MOONS, PFS, UVEX, NEO Surveyor,
etc.). Roman can uniquely provide uniform high-spatial-resolution
($\approx$0.1”) imaging over the entire sky, vastly expanding the science
reach and precision of all of these near-term and future surveys. This imaging
will not only enhance other surveys, but also facilitate completely new
science. By imaging the full sky over two epochs, Roman can measure the proper
motions for stars across the entire Milky Way, probing 100 times fainter than
Gaia out to the very edge of the Galaxy. Here, we propose NANCY: a completely
public, all-sky survey that will create a high-value legacy dataset benefiting
innumerable ongoing and forthcoming studies of the universe. NANCY is a pure
expression of Roman’s potential: it images the entire sky, at high spatial
resolution, in a broad infrared bandpass that collects as many photons as
possible. The majority of all ongoing astronomical surveys would benefit from
incorporating observations of NANCY into their analyses, whether these surveys
focus on nearby stars, the Milky Way, near-field cosmology, or the broader
universe.

In this white paper, we propose using Roman to scan the entire sky to a
$5\sigma$ ($10\sigma$) single-exposure depth of 25 AB mag (24.5 mag) in at
least two epochs. There are several survey designs that can reach this goal
within the scope of a Core Community Survey (CCS), which we outline in Table
1. We present three “fiducial” designs that we consider equally, and two
“reduced” designs that are smaller in scope than the fiducial surveys. We note
that all of these surveys are significantly shorter than the notional High-
Latitude Wide-Area Survey, which is planned to take 24 months (730 days) of
on-sky time. We nominally adopt F146 ($\lambda_{\rm cen}=1.464\mu
m,\Delta\lambda=1.073\mu m$) as the primary filter due to its high throughput,
but also provide how the total survey time would scale up in other filters in
Figure 2. In one of the fiducial surveys, we describe an option to add a
second filter in F087, F106, or F129. In any survey design, completing the
first epoch as early in the mission as possible, and repeating the
observations near the end of the baseline mission is critical. This strategy
will allow the survey to deliver precise proper motions for faint stars across
the entire sky. We describe the fiducial surveys in detail in Section 2, and
the reduced surveys in Section 3.

Figure 1: Completed and on-going ground-based imaging surveys cover the entire
sky in multiple bands. The figure shows the footprints of the completed
PanSTARRS1 (Chambers et al., 2016), the ongoing UNIONS project (Ibata et al.,
2017), existing data from DECam in the NOIRLab archive, and the Legacy Surveys
DR9-North survey (Dey et al., 2019). The outline of the Rubin/LSST WFD survey
is shown by the blue dashed line. NANCY’s $\approx 0.1$ arcsec spatial
resolution infrared map will cover the _entire sky_ , completely overlapping
all of these surveys and greatly expanding the value and science of them all.

##  1 Science Impact

Observational cosmology is in its heyday, with a multitude of experiments
making precision measurements of the geometry and expansion history of the
universe (e.g., eROSITA, SDSS, DES, DESI, Rubin/LSST, Euclid, SPHEREx,
CMBS-4). Simultaneously, Galactic astronomy is undergoing a renaissance with
the advent of Gaia, time-domain surveys such as ATLAS, ZTF and TESS, and the
proliferation of highly multiplexed spectroscopic facilities like DESI and
4MOST. In the near-future, Rubin/LSST will be a weak-lensing, cluster-finding,
near-field cosmology, and Galactic astronomy engine. Several ongoing and
future space missions will result in mapping the sky at X-ray (SRG/eROSITA),
UV (UVEX in planning), optical and IR (Euclid in 2023, and SPHEREx in 2025).
In the radio, the combination of the VLA All-Sky Survey (VLASS; Lacy et al.,
2020) and ASKAP’s EMU survey (Norris, 2011) will cover the entire sky in
multiple epochs. All of these surveys will benefit from 0.1” NIR resolution
imaging to identify counterpart sources and their precise morphologies. As the
only all-sky, 0.1” resolution infrared survey, NANCY will indeed be the
preeminent dataset to fully leverage the investment in other wide-field
imaging, spectroscopic and multi-wavelength ground- and space-based missions.
For example, the combination of NANCY and Rubin/LSST data can deliver more
accurate photo-$z$s and mass measurements of the eROSITA selected galaxy
clusters out to redshifts of $z\sim 2$, which will constrain the evolution of
dark energy. NANCY can also provide SPHEREx (Crill et al., 2020) with a deep
prior catalog in the NIR, which will greatly improve the prior-driven SPHEREx
spectroscopy and target selection. By the time Roman launches, DESI (DESI
Collaboration et al., 2022) will have measured $\approx$40 million redshifts
and 10 million radial velocities; NANCY will yield near-IR morphologies and
photometry of every galaxy/QSO with a measured redshift, and proper motions
for every star observed by DESI. The legacy value of NANCY will span the whole
spectrum in wavelength and time.

At its core, NANCY will produce the highest resolution image of the entire sky
in the near-IR (NIR). From this all-sky image, we highlight three Key Products
(detailed below): (1) the highest resolution image of nearly every object in
the sky, enabling accurate source classification for ground-based telescopes
down to 25 mag in J/H band and accurate weak-lensing shape measurements; (2)
proper motion measurements to unprecedented depths, enabling kinematic studies
of the Galaxy that can pin down the nature of dark matter; and (3) a high-
spatial-resolution-NIR map of the Milky Way, enabling precision cosmology via
improved foreground modeling. Outside of these Key Products, NANCY will
broaden the horizon for virtually all aspects of astronomy, including (but not
limited to) detecting strong gravitational lenses, establishing a first epoch
for transient phenomena, searching for wandering intermediate-mass black
holes, discovering low-surface-brightness features such as merging galaxy
shells, searching for extragalactic globular clusters and dwarf galaxy
companions, and providing robust identifications for SN progenitors in nearby
galaxies. We emphasize that NANCY is the only opportunity to deliver such a
legacy dataset in the foreseeable future.

###  1.1 Key Product 1: The highest spatial resolution image of the entire sky

NANCY will create the highest resolution image of nearly every object in the
sky. The most basic use of these data will be the identification of point
sources (e.g., stars and quasars) and resolved objects (e.g., galaxies), as
well as blended groups of multiple sources. This information is critical
throughout astronomy. For instance, ongoing and forthcoming weak-lensing
cosmology experiments rely on the robust identification and shape measurements
of faint galaxies, but suffer from star–galaxy separation and source confusion
issues. Even Rubin/LSST will have star-galaxy confusion at $i\approx 24$ AB
mag (see, e.g., Fig 4, 5 of Bechtol et al. Roman White paper). The proposed
F146 $5\sigma$ depth of 25 AB mag means that NANCY can readily separate
point/extended sources brighter than this limit (e.g., Slater et al., 2020),
which is $>1$ mag fainter than feasible with only the Rubin data. Therefore,
NANCY will expand the reaches of the Rubin cosmology program. Rubin and Euclid
will also create considerable synergies. In the 15,000 sq. degrees of the
Euclid Wide Survey (Euclid Collaboration et al., 2022), Euclid will also
deliver $\sim 0.1"$ resolution imaging in the VIS filter ($0.55-0.9\mu m$,
$5\sigma$ at 26.2 mag) that can be combined with NANCY to measure colors of
these sources, which greatly enhances the legacy of both surveys. In the NIR,
Euclid will observe shallower ($5\sigma$ at 24.5 mag) at lower resolution
(0.3” vs. 0.1”) than Roman, but still provide an invaluable third epoch to
most NANCY sources. Due to its optimal NIR imaging, Roman is uniquely suited
to solve the problem of source classification for high-redshift sources. Faint
source classification also critically impacts near-field science, such as
searching for ultra-faint dwarf galaxies tracing the low-mass end of the halo
mass function (e.g., Drlica-Wagner et al., 2015), or studying rare stellar
objects in the Galaxy. With NANCY, Roman presents an opportunity to truly
“resolve” the source classification problem for all ground-based telescopes.
The only competition to NANCY in the forseeable future would be larger NANCY-
like programs using Roman—and these would benefit tremendously from initial
all-sky observations made as part of NANCY.

###  1.2 Key Product 2: All-sky astrometry of the lowest mass and most distant
stars

The Gaia mission (Gaia Collaboration et al., 2016) has showcased the impact
that precision astrometry can have throughout Galactic astronomy. Roman will
detect stars much further away and fainter than Gaia. As an example, a red
clump (RC) star at the Galaxy’s virial radius ($\sim 250\text{kpc}$) is 22 mag
in the F146 filter. NANCY will detect this star with an SNR of 80. The same
star is 23.5 mag in the Gaia G band, which is invisible to Gaia (limiting
magnitude G=21). Beyond the Galaxy, the tip of the red-giant branch will be
visible out to $\sim 10\text{Mpc}$ at the $5\sigma$ 25 mag limit of NANCY,
covering the entire Local Group including M31, M33, and numerous dwarf
galaxies. While it is yet challenging to accurately estimate the proper motion
uncertainty from two epochs with a 5-year baseline (the WFIRST Astrometry
Working Group et al., 2019, estimate $25~{}\mu$as/year for the High-latitude
Wide-Area survey), we estimate a rough proper motion uncertainty as
$\delta_{PM}\sim\text{max}(\sqrt{2}\times\text{FWHM}/\text{SNR}/\text{5years},0.01\text{pix}/\text{5years})$,
assuming a systematic floor of 0.01pix. From this we infer that NANCY will
provide $\sim 200~{}\mu$as/year precision proper motion measurements for all
stars brighter than 21.8 mag in F146, and a precision that scales inversely
with SNR down to the faint limit of 25 mag. In the region of overlap with
Euclid, the Euclid imaging data will provide a useful first epoch, increasing
the proper motion baseline by a maximum of a factor of $\sim 2$. GO
observations can also provide more epochs that can reduce the systematic
uncertainty floor by $1/\sqrt{N_{\text{epoch}}}$. In combination with millions
of radial velocity and chemical abundance measurements from large ground-based
spectroscopic surveys (e.g., DESI, SDSS-V, WEAVE, PFS, 4MOST), these
measurements will allow us to reveal the formation history of the Milky Way in
exquisite detail, and measure density and velocity perturbations in stellar
streams imprinted by past encounters with dark matter subhalos.

###  1.3 Key Product 3: A High-Spatial-Resolution-NIR Map of the Milky Way

Roman’s high angular resolution and deep NIR sensitivity enable an
unprecedented view of the entire Milky Way, including regions with extreme
crowding and extinction. Peering through dust to identify globular clusters in
the Galactic plane and embedded young stellar objects (YSOs), NANCY will
explore star formation in diverse environments from the densest regions of the
Galactic center to the spiral arms. By providing the astrometry for a
significant fraction of stars in the Galaxy, NANCY will establish the leading
catalog for identifying sources of transients, performing forced-photometry on
lower-resolution imaging, and targeting spectroscopic surveys, especially
those in H-band, such as SDSS-V and MOONS, which are mapping the chemical
evolution of the Milky Way Kollmeier et al. (2017); Taylor et al. (2018);
Almeida et al. (2023). Studies of dust cloud morphology at high angular
resolution will probe the mechanisms of molecular cloud assembly and evolution
as well as the turbulent structure of the ISM across orders of magnitude in
spatial scale. The deep F146 photometry will provide “background” sources both
at unprecedented distances and for lines of sight with extremely high column
densities of dust that, when combined with deep, all-sky, ground-based, multi-
color photometry, will extend 3D dust maps to larger distances and into denser
cores of molecular clouds (e.g., Green et al., 2019). These stellar-reddening
based maps of Galactic dust are imperative for precision cosmology to remove
Galactic foregrounds in dereddening extragalactic sources at high angular
resolution ($\leq 1$ arcmin).

Figure 2: The PSF size in each WFI filter versus the exposure time required to
reach 25 AB mag. On the top axis, we also show the time it takes in each
filter to scan the whole sky once (assuming 3 dithers, see Section 2). The
range of PSF width resulting from the width of the filter is represented by
the vertical bars. The Roman pixel scale of 0.11” is represented by the thick
grey horizontal line.

##  2 Fiducial Survey Design

Roman’s 0.28 sq. deg. camera can map the entire sky (4$\pi$ sr) in 147,332
contiguous fields. Using the exposure time calculator, we estimate that a
total exposure of 30s per field is sufficient to reach the desired $5\sigma$
depth of 25 AB mag in F146, assuming zodiacal light twice greater than
minimum. In Figure 2 we show the different exposure times required to achieve
the same depth in each filter. Based on these basic parameters, we present
three possible designs for the fiducial survey.

In the first design, each exposure is broken up into three 10s dithers (with a
20s slew time between dithers) in order to fill in the chip gaps and improve
the PSF sampling. After one field is completed, Roman will slew along its
short FoV axis (0.4 deg) to the next contiguous field, taking $\approx$50
seconds. Thus, each single-epoch field will take 30s (exposure) + 40s (dither)
+ 50s (slew) = 120s. This equates to 204 days for one epoch of full-sky, and
408 days for two epochs. We further partition each full-sky scan into two
equal (102-day) campaigns: the high-Galactic-latitude ($|b|>30$ deg, 50% of
the full sky) campaign, and the low-latitude ($|b|<30$ deg, 50% of the full
sky) campaign. This partition allows for more flexible scheduling within a
given year. It is imperative that the two epochs of a given field are taken at
the same time of year; this will minimize the parallax-induced astrometric
shifts and allow for accurate proper motion measurements. While this survey
design has the benefit that each exposure is well-sampled and void of chip
gaps, it is also not an efficient design: the shutter is open only 25% of the
survey time. It may be possible to utilize the slew time to spread out the
brightest targets, which can help improve astrometry along the axis
perpendicular to the slew. However, the prospect of such “slew exposures”
depends greatly on the data volume constraints, and we do not make
quantitative estimates here.

In the second design, we do not dither during a single epoch, but instead do
three tilings of the sky, with non-overlapping pointing centers for each
tiling to fill in the chip gaps. Each single-epoch field takes 30s (exposure)
+ 50s (slew) = 80s. This strategy allows us to add a third epoch at Y2.5,
while still taking 408 days of total survey time, identical to the first
design. By placing this intermediate epoch precisely 6 months after 2 years,
we can constrain the parallax as well as the proper motion. The astrometric
solution for stars that lie in the chip gaps will be more complicated, but
even such stars will have at least a 2.5 year baseline for proper motions. In
this design, we rely on up-the-ramp sampling for cosmic ray rejection.

A unique opportunity in this three-epoch design is that we can use a different
filter for the intermediate epoch. This is the third survey design. For
example, replacing the F146 with F062 in the Y2.5 epoch will add just 12 days
(420 days total), and F087, F106, or F129 will equally add 44 days to the
survey (452 days total). Since F146 is a wide-band filter, adding a narrower
filter such as F106 or F129 would serve as a complementary catalog for source
classification while also adding color information.

Survey | PM | Total duration | Campaign duration | Campaigns
---|---|---|---|---
|  | [days] | [days] | Y1 | Y2 | Y2.5 | Y4 | Y5
Fiducial (Dither) | AL | 408 | 102 | HL | LL | - | LL | HL
Fiducial (No Dither) | AL | 408 | 136 | AL | - | AL | - | AL
Fiducial (No Dither, Two-band) | AL | 452 | 136/179 | AL | - | AL [179 days] | - | AL
3/4 Reduced | HL | 306 | 102 | HL | LL | - | - | HL
Half Reduced | - | 204 | 102 | HL | LL | - | - | -
Table 1: Survey Options for implementing NANCY. The top three are the
“fiducial” designs that we consider equally, and the last two are the
“reduced” designs that take significantly less time than the fiducial surveys.
We note that all of these surveys are significantly shorter than the notional
High-Latitude Wide-Area Survey, which is estimated to take 24 months (730
days) of on-sky time. All exposure times assume a single-exposure depth of
$5\sigma$ at 25 AB mag. The F146 filter is used in all but the Y2.5 Campaign
of the Third Fiducial survey, which uses F087/F102/F126. Column 2 denotes the
survey area over which proper motions will be derived. Column 3 is the total
duration of the entire survey, and column 4 is the duration for each year-long
Campaign. In columns 2, 5-9, AL/HL/LL = All/High/Low Latitudes.

##  3 Design Trade Space

The three main parameters of the survey are: survey area (41,253 sq. deg),
exposure time (30s), and the F146 filter. As more than half of the survey time
is already dedicated to slew/settle, reducing the exposure time would yield a
less efficient survey. The choice of the F146 filter is driven by its
throughput and sampling. In Figure 1 we plot the exposure time required to
reach $5\sigma$ at 25 mag, and the PSF size in arcseconds for each filter.
F146 requires the least exposure time. The second fastest filter is F062
($\lambda_{\rm cen}=0.62\mu m,\Delta\lambda=0.28\mu m$) at 37s; however, F062
is less well sampled than F146 (0.058” vs. 0.105” PSF, while the pixel scale
is 0.11”), which makes the morphological classification of sources at the
faint end more difficult. Thus, F146 is the ideal filter for a fast survey.
Since reducing the exposure time is not viable, and using a different filter
only increases the total survey time, the survey area offers the only
meaningful trade space to reduce the total survey time. We thus present two
“reduced” surveys that are smaller in survey area.

The first reduced survey is the “3/4” survey, which scans the high-latitude
(HL) sky twice and the low-latitude (LL) sky only once (HL in Y1, LL spread
over Y2–4, HL in Y5). This will still enable astrometry in the halo and
extinction mapping in the Galactic plane. The second reduced survey is the
“half” survey, which scans the full sky once in Y1. This design will rely on
GO programs to obtain astrometry for targeted fields, but will still deliver
an invaluable all-sky source catalog. In all cases, it is still critical that,
at the minimum, an all-sky, high-Galactic-latitude campaign occurs in Y1 in
order to enable precise astrometric measurements later during the mission.

While in this white paper we have focused on delivering the fastest possible
full-sky survey, there are several reasons to consider a longer, more full-
fledged version of NANCY. First, a key challenge to designing any Roman survey
is the considerable overhead (20s per chip-gap dither, 50s per short-FoV axis
slew). A direct way to make the survey more efficient would be to increase the
exposure times, thereby reducing the fraction of time spent on slew/settle.
For example, if we entirely replaced F146 with F087, F106, or F129, the
required exposure time to reach the $5\sigma$ depth at 25 mag is 55s, and the
fiducial survey with dithering would take 491 days. Using these narrower
filters would also remedy a major disadvantage of the F146 filter that it is
difficult to accurately calculate the PSF for sources of unknown color due to
the exceptional wavelength range. One could even consider a multi-epoch,
multi-band all-sky survey that would provide colors for every object in the
survey; such a survey would likely take $\sim 900$ days of survey time. To
improve proper motion uncertainties, adding additional epochs is more
effective than taking deeper exposures, as the astrometric measurements are
limited by systematics for most sources of interest in the Galaxy. The same
strategy would benefit the Time Domain CCS as well: increasing the number of
epochs directly increases the discovery space in time.

##  4 Summary

Roman is the only instrument capable of carrying out a high-resolution, all-
sky NIR survey like NANCY for the foreseeable future. The legacy value of this
survey spans the whole spectrum of astronomy, and ties together the
innumerable small- and large-scale investments going into ground and space-
based telescopes. Furthermore, NANCY will only improve the science yield of
other Roman programs, including its core cosmology program (e.g., by creating
synergies with Rubin, Euclid and DESI) and its time domain program (by
establishing an all-sky single epoch baseline). We thus urge the Roman CCS
committee to broaden the scope of the High-Latitude Wide-Area Survey to
include, or expand upon, NANCY.

## References

  * Almeida et al. (2023) Almeida, A., Anderson, S. F., Argudo-Fernández, M., et al. 2023, arXiv e-prints, arXiv:2301.07688, doi: 10.48550/arXiv.2301.07688
  * Chambers et al. (2016) Chambers, K. C., Magnier, E. A., Metcalfe, N., et al. 2016, arXiv e-prints, arXiv:1612.05560, doi: 10.48550/arXiv.1612.05560
  * Crill et al. (2020) Crill, B. P., Werner, M., Akeson, R., et al. 2020, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 11443, Space Telescopes and Instrumentation 2020: Optical, Infrared, and Millimeter Wave, ed. M. Lystrup & M. D. Perrin, 114430I, doi: 10.1117/12.2567224
  * DESI Collaboration et al. (2022) DESI Collaboration, Abareshi, B., Aguilar, J., et al. 2022, AJ, 164, 207, doi: 10.3847/1538-3881/ac882b
  * Dey et al. (2019) Dey, A., Schlegel, D. J., Lang, D., et al. 2019, AJ, 157, 168, doi: 10.3847/1538-3881/ab089d
  * Drlica-Wagner et al. (2015) Drlica-Wagner, A., Bechtol, K., Rykoff, E. S., et al. 2015, ApJ, 813, 109, doi: 10.1088/0004-637X/813/2/109
  * Euclid Collaboration et al. (2022) Euclid Collaboration, Scaramella, R., Amiaux, J., et al. 2022, A&A, 662, A112, doi: 10.1051/0004-6361/202141938
  * Gaia Collaboration et al. (2016) Gaia Collaboration, Prusti, T., de Bruijne, J. H. J., et al. 2016, A&A, 595, A1, doi: 10.1051/0004-6361/201629272
  * Green et al. (2019) Green, G. M., Schlafly, E., Zucker, C., Speagle, J. S., & Finkbeiner, D. 2019, ApJ, 887, 93, doi: 10.3847/1538-4357/ab5362
  * Ibata et al. (2017) Ibata, R. A., McConnachie, A., Cuillandre, J.-C., et al. 2017, ApJ, 848, 128, doi: 10.3847/1538-4357/aa855c
  * Kollmeier et al. (2017) Kollmeier, J. A., Zasowski, G., Rix, H.-W., et al. 2017, arXiv e-prints, arXiv:1711.03234, doi: 10.48550/arXiv.1711.03234
  * Lacy et al. (2020) Lacy, M., Baum, S. A., Chandler, C. J., et al. 2020, PASP, 132, 035001, doi: 10.1088/1538-3873/ab63eb
  * Norris (2011) Norris, R. P. 2011, Journal of Astrophysics and Astronomy, 32, 599, doi: 10.1007/s12036-011-9119-z
  * Slater et al. (2020) Slater, C. T., Ivezić, Ž., & Lupton, R. H. 2020, AJ, 159, 65, doi: 10.3847/1538-3881/ab6166
  * Taylor et al. (2018) Taylor, W., Cirasuolo, M., Afonso, J., et al. 2018, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 10702, Ground-based and Airborne Instrumentation for Astronomy VII, ed. C. J. Evans, L. Simard, & H. Takami, 107021G, doi: 10.1117/12.2313403
  * WFIRST Astrometry Working Group et al. (2019) WFIRST Astrometry Working Group, Sanderson, R. E., Bellini, A., et al. 2019, Journal of Astronomical Telescopes, Instruments, and Systems, 5, 044005, doi: 10.1117/1.JATIS.5.4.044005