[1]Samuel G Pearson

[1]Mark J McCaughrean

[1]European Space Research and Technology Centre (ESTEC), European Space
Agency (ESA), Keplerlaan 1, Noordwĳk, 2201 AZ, Zuid Holland, The Netherlands

# Jupiter Mass Binary Objects in the Trapezium Cluster

<EMAIL_ADDRESS><EMAIL_ADDRESS>*

###### Abstract

A key outstanding question in star and planet formation is how far the initial
mass function of stars and sub-stellar objects extends, and whether or not
there is a cut-off at the very lowest masses. Isolated objects in the
planetary-mass domain below 13 Jupiter masses, where not even deuterium can
fuse, are very challenging to observe as these objects are inherently faint.
Nearby star-forming regions provide the best opportunity to search for them
though: while they are young, they are still relatively warm and luminous at
infrared wavelengths. Previous surveys have discovered a handful of such
sources down to 3–5 Jupiter masses, around the minimum mass limit established
for formation via the fragmentation of molecular clouds, but does the mass
function extend further? In a new James Webb Space Telescope near-infrared
survey of the inner Orion Nebula and Trapezium Cluster, we have discovered and
characterised a sample of 540 planetary-mass candidates with masses down to
0.6 Jupiter masses, demonstrating that there is indeed no sharp cut-off in the
mass function. Furthermore, we find that 9% of the planetary-mass objects are
in wide binaries, a result that is highly unexpected and which challenges
current theories of both star and planet formation.

###### keywords:

surveys, (stars:) binaries: visual, (stars:) brown dwarfs, stars: low-mass

##  1 Main

The Orion Nebula is arguably the most famous and well-studied H II region in
the sky. It is the nearest site of recent massive star formation, producing
stars spanning the full spectral range from massive O-types to M dwarfs, a
rich population of sub-stellar brown dwarfs, and many planetary-mass objects.
Collectively, these objects are known as the Orion Nebula Cluster and the
densest inner core, within 0.5 parsec of the eponymous Trapezium stars, is
called the Trapezium Cluster, with a core density reaching $5\times 10^{4}$
stars pc-3 [1]. Due to its large population of $\sim 2000$ members [2], young
age (0.5–2 Myr) [3], low foreground extinction (${\rm A}_{\rm v}\sim 1$) [4],
and close proximity to the Sun [$390\pm 2$ pc; 5], the Trapezium Cluster
provides an ideal laboratory for studies of star and planet formation [6, 7].

Sub-stellar objects below the hydrogen-burning limit [0.075 $M_{\odot}$; 8, 9,
10] never reach the main sequence and continually cool, becoming fainter as
they age. However, when young, sub-stellar sources remain relatively luminous
and easy to detect as they shed gravitational energy while contracting: brown
dwarfs also undergo a period of deuterium fusion, while sources below 13
$M_{\rm Jup}$, the planetary-mass objects (henceforth PMOs) do not. The
Trapezium Cluster is a particularly advantageous location to study such
sources: it is young and has a large enough sample size for robust population
statistics, while its relative proximity, location out of the galactic plane,
and the dense molecular cloud behind it help minimise contamination due to
foreground or background field stars.

Past ground- and space-based surveys of the Trapezium Cluster have revealed a
rich population of brown dwarfs and PMOs down to $\sim 3$ $M_{\rm Jup}$ [11,
12, 13, 14, 15, 16, 17, 18, 19, 20], but reaching masses below that is
challenging, partly because lower-mass objects are cooler and thus emit most
of their energy in the thermal infrared, and partly due to the bright
background of the Orion Nebula. Similarly, spectroscopically-confirmed objects
below the deuterium burning limit remain relatively rare due to their
faintness [21, 14, 22, 23, 24, 25, 26, 27].

As a large, diffraction-limited, cryogenic space telescope, however, the JWST
is ideally suited to pushing further into the planetary-mass domain than
previously possible, and the wide range of filters allow us to search for
tell-tale atmospheric features which can help distinguish between bona fide
PMOs and distant field stars. Imaging surveys with NIRCam over wide areas can
discover many new candidates, while multi-object follow-up spectroscopy is
possible with NIRSpec.

An $11\times 7.5$ arcminute (or $1.2\times 0.8$ parsec) region of the inner
Orion Nebula and Trapezium Cluster was observed using the Near Infrared Camera
(NIRCam) on the NASA/ESA/CSA James Webb Space Telescope (JWST), as part of
Cycle 1 GTO programme 1256111 Please refer to the following links for full
resolution colour images:  •
https://www.esa.int/Science_Exploration/Space_Science/Webb/
Webb_s_wide-angle_view_of_the_Orion_Nebula_is_released_in_ESASky •
https://www.esa.int/ESA_Multimedia/Images/2023/09/
Orion_Nebula_in_NIRCam_short-wavelength_channel •
https://www.esa.int/ESA_Multimedia/Images/2023/09/
Orion_Nebula_in_NIRCam_long-wavelength_channel •
https://sky.esa.int/?jwst_image=webb_orionnebula_shortwave •
https://sky.esa.int/?jwst_image=webb_orionnebula_longwave . A total of 34.9
hours of observing were carried out between 26 September and 2 October 2022,
split across 12 filters: F115W, F140M, F162M, F182M, F187N, F212N, F277W,
F300M, F335M, F360M, F444W, and F470N (see McCaughrean & Pearson 2023,
submitted, for full details)

Young (1 Myr) PMOs with masses between 1–13 $M_{\rm Jup}$ have effective
temperatures of 890–2520 K [28], which means that their spectral energy
distributions (SED) peak in the range 1–3.3 ${\mu}$m. These SEDs are not
blackbodies, but are dominated by broad molecular absorption features as seen
in Figure 1. The upper panel shows a model spectrum of a young PMO with
$T_{\mbox{\footnotesize eff}}$ = 900 K and $\log({\rm g})=5.0$, taken from the
ATMO 2020 chemical equilibrium model set [28]. The molecular absorption bands
due H2O, CH4, and CO are shown in blue, red, and black, respectively, and are
seen to radically alter the SED, confining the spectrum to a series of narrow
peaks and troughs. Our selection of NIRCam filters was designed to target
these peaks and troughs, in order to robustly distinguish PMOs from more
massive and reddened background objects. We have used photometry in the F115W,
F140M, F162M, F182M, and F227W filters to measure the depth of the 1.4 and 1.9
${\mu}$m H2O absorption features, classifying sources according to Equation 1.
We have also quantified the level of H2O absorption using the W-index, defined
in Equation 2. As this index utilises the short-wavelength filters, it is
susceptible to reddening and so can only be treated as a reliable indicator
for low-extinction sources. To identify lower-mass, cooler sources, we use
F300M, F335M, and F360M photometry to measure the 3.35 ${\mu}$m CH4 absorption
feature, classifying sources according to Equation 3.

The power of medium-band near-infrared photometry to identify PMOs using these
absorption features is demonstrated in Figure 1. The blue curve in the middle
panel shows JWST NIRCam photometry of a candidate PMO, while the black curve
shows synthetic photometry derived from evolutionary models of a 1 Myr old, 1
$M_{\rm Jup}$ object at the distance of Orion [10], calculated using a new
equation-of-state for dense hydrogen-helium mixtures [29], combined with the
atmospheric models from ATMO 2020 [28]. The model fluxes have been adjusted
with the further addition of ${\rm A}_{\rm V}=20$ of reddening to best fit the
candidate PMO. The strong molecular absorption dips can clearly be seen in the
F140M and F182M filters due to the presence of H2O, as well as a strong dip in
F335M due to CH4. In contrast, the black curve in the bottom panel shows
synthetic photometry of a model 1 Myr, 2 $M_{\rm Jup}$ object adjusted by
${\rm A}_{\rm V}=14$. This clearly provides a bad fit to the JWST photometry
of a candidate reddened background star, seen in red: a much better solution
to its smooth SED is arrived at by assuming a reddened blackbody at
$T_{\mbox{\footnotesize eff}}$ = 4042 K, with reddening of ${\rm A}_{\rm
V}=19.9$.

Figure 1: The upper panel shows a model spectrum of a young PMO with
$T_{\mbox{\footnotesize eff}}$ = 900 K and $\log({\rm g})=5.0$ from the ATMO
2020 chemical equilibrium model set [28]. The molecular absorption bands with
line intensities greater than $5\times 10^{-23}$ cm-1 / molecule cm${}^{-2})$
at ${\rm T}_{\rm ref}$ = 900 K for H2O, CH4, and CO are shown in blue, red and
black, respectively [30]. Due the low temperatures of PMOs, these molecules
are present in their atmospheres and absorption radically alters the spectral
energy distribution into a series of narrow peaks. Using medium- and wide-band
photometry, these peaks and troughs can be readily identified and provide a
robust method for distinguishing PMOs from more massive background objects. In
the middle panel, the black line shows synthetic photometry of a 1 Myr, 1
$M_{\rm Jup}$ PMO, using the atmospheric models from ATMO 2020 [28] combined
with the new equation of state from Chabrier & Debras (2021) [29, 10]. The
model photometry has been reddened by ${\rm A}_{\rm V}=20$. The blue line
shows our JWST NIRCam photometry of a candidate $\sim 1$ $M_{\rm Jup}$ PMO:
the nominal errorbars are smaller than the markers. The strong molecular
absorption dips can clearly be seen in the F140M and F182M filters due to the
presence of H2O, as well as a strong dip in F335M due to CH4. The match
between the data and model SEDs is excellent. The bottom panel shows synthetic
photometry of a 1 Myr, 2 $M_{\rm Jup}$ PMO with ${\rm A}_{\rm V}=14$ in black,
alongside NIRCam photometry of a candidate reddened background star shown in
red. The candidate reddened background star does not show any molecular
absorption features, and instead has much smoother spectral energy
distribution: it is well fit by blackbody with $T_{\mbox{\footnotesize eff}}$
= 4042 K and reddening of ${\rm A}_{\rm V}=19.9$. For reference, the
bandpasses of the nine NIRCam filters (F115W, F140M, F162M, F182M, F277W,
F300M, F335M, F360M, and F444W) used to classify the sources is shown along
the bottom of the plot.

For all unsaturated stars in our JWST survey (Pearson & McCaughrean 2023, in
prep), we have fit the medium- and wide-band filter SED to evolutionary models
by varying the mass and extinction, assuming a constant age of 1 Myr and a
distance of 390 pc. We use three grids of models, one using equilibrium
chemistry (CEQ), and two using non-equilibrium chemistry (NEQweak & NEQstrong)
[10]. These models cover PMOs with masses in the range 0.0004 $M_{\odot}$ to
0.015 $M_{\odot}$ (0.42 $M_{\rm Jup}$to 15.7 $M_{\rm Jup}$). We also use the
models which cover brown dwarfs and low mass stars from 0.01 $M_{\odot}$ to
1.4 $M_{\odot}$[8]. The extinction is allowed to vary from ${\rm A}_{\rm V}$ =
1–100. For each combination of model mass and extinction, we reddened the
model SED using the reddening law from [31] with ${\rm R}_{\rm V}=3.1$, and
calculated the $\chi^{2}$ goodness of fit. The lowest $\chi^{2}$ value was
taken as the best fit. This process was also repeated using a blackbody model
with $T_{\mbox{\footnotesize eff}}$ = 500–50,000 K and ${\rm A}_{\rm V}$ =
0–100.

Figure 2 shows dereddened NIRCam photometry for a sample of candidate brown
dwarfs and PMOs in blue. In each case, the light grey curve shows the best-
fitting unreddened model assuming an age of 1 Myr and a distance of 390 pc
[10, 8]. This plot demonstrates how the SED sampled by our nine NIRCam medium-
and wide-band filters evolves with decreasing mass. The H2O absorption
features at 1.4 and 1.9 ${\mu}$m are already present for brown dwarfs and
strengthen with decreasing effective temperature. The CH4 absorption at 3.35
${\mu}$m emerges at temperatures below $T_{\mbox{\footnotesize eff}}$ $\sim$
1500 K, making it sensitive to PMOs below 5 $M_{\rm Jup}$. It also strengthens
as the effective temperature decreases.

Figure 2: The blue lines show dereddened NIRCam photometry for a sample of
candidate brown dwarfs and PMOs in the Trapezium Cluster. This plot
demonstrates how the SED sampled by our nine NIRCam medium- and wide-band
filters evolves with decreasing mass for young brown dwarfs and PMOs. The
light grey lines show the best-fitting unreddened model assuming an age of 1
Myr and distance of 390 pc [10, 8]. The H2O absorption features at 1.4 and 1.9
${\mu}$m are present for brown dwarfs and strengthen with decreasing mass,
while below 5 $M_{\rm Jup}$, CH4 absorption at 3.35 ${\mu}$m becomes prominent
and also strengthens with decreasing effective temperature.

$\displaystyle{\rm F140M}-{\rm F162M}\geq 1.605({\rm F162M}-{\rm
F182M})+0.565$ (1) $\displaystyle{\rm Windex}={\rm F115W}+2\times({\rm
F140M}-{\rm F162M}+{\rm F182M})-{\rm F277W}$ (2) $\displaystyle{\rm
F335M}-{\rm F360M}\geq 0.488({\rm F300M}-{\rm F355M})+0.206$ (3)

Background field stars are ruled out on the basis of their smooth SED, but
older, cooler, foreground brown dwarfs could be identified as false positives.
However, given the relative proximity of the Orion Nebula and its location out
of the galactic plane, such contamination is expected to be minimal [32].
Another potential contaminant is distant galaxies. Towards the centre of the
region where the extinction due to the background OMC-1 core is high [${\rm
A}_{\rm V}\geq$ 50–100, 33], this is not a concern, but at the edges of our
survey, a population of galaxies is evident (McCaughrean & Pearson 2023,
submitted). The aperture photometry technique described in the Supplementary
Material detects extended sources like galaxes and, inter alia, circumstellar
disks and outflow nebulosities, but also close binaries, so such sources are
marked and checked manually.

In this way, we have identified 540 candidate PMOs in the Trapezium Cluster
with SEDs best fit by evolutionary models with masses of 13 $M_{\rm Jup}$ or
lower. For low extinction sources (${\rm A}_{\rm V}<10$), we also include
candidates which show H2O absorption according to Equation 1 and which have a
W-index of $\geq$ 0.47 (Equation 2). A total of 168 of these PMO candidates
also show CH4 absorption and are best fit by models with masses of 5 $M_{\rm
Jup}$ or less. The most extreme candidate PMO in our sample has a mass of 0.6
$M_{\rm Jup}$ or 2 Saturn masses. Our PMO candidates show a smooth
continuation of the IMF to low masses, with no evidence for a sharp cutoff. We
find no evidence for a large population of marginally-detected sources, which
indicates that it is very unlikely that the mass function rises significantly
below 1 $M_{\rm Jup}$. We cautiously note a moderate increase in the number of
objects in the 1–3 $M_{\rm Jup}$ range, that might be consistent with an over
density of low-mass PMOs formed through ejection [34, 32]. However, as these
are currently unconfirmed PMO candidates and the masses are not well
constrained, we will leave a full analysis of the IMF to future work, which
will greatly benefit from scheduled follow up spectroscopy (JWST cycle 2
programme 2770).

We find that the chemical equilibrium models (CEQ) give the best fit to the
data for PMOs down to 2 $M_{\rm Jup}$. Below this mass, we see that the
NEQweak models are preferred, with CEQ second best, and NEQstrong worst. For
the 0.6–2 $M_{\rm Jup}$ PMOs, we find that the F360M, F162M, and F444W filters
that generally most badly fit by the CEQ models. This could be an indication
that vertical mixing is affecting the nitrogen and carbon non-equilibrium
chemistry [cf. 35], causing an increased abundance and absorption of CO and
${\rm CO}_{2}$ suppressing the flux in the 3.5–5 ${\mu}$m range. We will
obtain R$\sim$100 NIRSpec prism spectroscopy for many of these PMO candidates
as part of JWST cycle 2 programme 2770, which should help further investigate
this tentative finding.

A remarkable finding is that a significant fraction of our candidate PMOs are
in binaries. Across the initial mass function, the multiplicity fraction,
defined as the fraction of primaries that have at least one companion, is seen
to decrease with mass. For massive O- and B-type stars, the multiplicity
fraction is close to 100%; this fraction decreases to 50–60% for solar type
stars [36], drops to 15% for higher-mass brown dwarfs [50–80 $M_{\rm Jup}$,
37], and falls further to 8% for lower-mass brown dwarfs [20–60 $M_{\rm Jup}$,
38]. Following this trend, and also in accordance with theoretical
expectations [e.g., 39], it would be expected that the multiplicity fraction
for PMOs below 13 $M_{\rm Jup}$ should be close to zero. However, within our
sample of 540 PMO candidates there are a 40 systems that have a binary
companion within 1 arcsec (390 au), and two visual triple systems, a
multiplicity fraction of at least 9%. The existence of these “Jupiter-Mass
Binary Objects”, henceforth JuMBOs, is an unexpected result that breaks a
trend that holds for over three orders of magnitude in mass [38, 40].

Figure 3 shows a subsection of the full JWST short-wavelength colour composite
mosaic (McCaughrean & Pearson 2023, submitted), located to the east of the
Trapezium and south of the Dark Bay. Five JuMBOs are seen in this one small
region, as highlighted in the cutouts. All ten of the individual PMO
candidates in these systems are best fit by 1 Myr evolutionary models with
masses 3–7 $M_{\rm Jup}$ and thus $T_{\mbox{\footnotesize eff}}$ = 900–1200 K.
The H2O and CH4 in their SEDs, along with the background molecular cloud,
rules out background field stars, and we can also rule out the possibility
that these may be foreground T-dwarfs using the known space densities of field
brown dwarfs [41] combined with the footprint and depth of the NIRCam
observations: we would expect to find $<2$ field brown dwarfs across the full
NIRCam mosaic [32]. Furthermore, as is immediately evident just visually, we
can exclude the possibility that many if any of these are chance alignments:
based on the density of sources in our survey, we can calculate that we would
expect to find 3.1 chance alignments within 1 arcsec across the whole region.

Assuming then that the JuMBOs are real binary PMOs, we can compare their
statistical properties properties (see Table. 1) with higher-mass systems. The
JuMBOs span the full mass range of our PMO candidates, from 13 $M_{\rm Jup}$
down to 0.7 $M_{\rm Jup}$. They have evenly distributed separations between
$\sim$25–390 au, which is significantly wider than the average separation of
brown dwarf-brown dwarf binaries which peaks at $\sim 4$ au [42, 43]. However,
as our imaging survey is only sensitive to visual binaries with separations
$>25$ au, we can not rule out an additional population of JuMBOs with closer
orbits. For this reason we take 9% as a lower bound for the PMO multiplicity
fraction. The average mass ratio of the JuMBOs is $q=0.66$. While there are a
significant number of roughly equal-mass JuMBOs, only 40% of the them have
$q\geq 0.8$. This is much lower than the typical mass ratios for brown dwarfs,
which very strongly favour equal masses [42, 43].

Figure 4 shows the wide binary fraction (WBF) as a function of primary mass,
where wide is defined as projected separations $\geq$100 au, equivalent to
0.26 arcsec at the distance of the Trapezium Cluster. Each data point is
illustrated with a cross: the horizontal bar indicates the mass interval,
while the height of the vertical bar shows the statistical uncertainty in the
WBF. The blue points show a compilation of multiplicity surveys of the stellar
neighbourhood [43]. The green points show the WBF for stars and brown dwarfs
in the Trapezium Cluster calculated by compiling known binaries from the
literature [44, 45, 46, 47, 48, 49, 50, 20, 51, 52, 53]. The red points are
from this work and show the WBF for PMOs in the Trapezium Cluster. The WBF
starts at $50-60$% for massive stars and decreases monotonically across three
orders of magnitude in mass, down to $\sim$2% in the brown dwarf regime in the
Trapezium Cluster. This is consistent with the current predictions of star
formation models and the consensus view that the more massive brown dwarfs
($>30{\rm M}_{\rm Jup}$) share the same formation mechanisms as stars [54, 55,
56].

However, the PMOs clearly break that trend and prediction, rising back up to
at least 9%. The sudden divergence and increased WBF at planetary masses
suggests that new formation mechanisms must come into play at such masses.
Broadly speaking, there are two key formation scenarios to consider. If the
JuMBOs formed via a “star-like” mechanism, i.e., via core collapse and
turbulent fragmentation, then there must be some fundamental extra ingredient
involved at these very low masses. Indeed, the JuMBOs in our sample cover the
whole range of PMO masses, down to 0.7 $M_{\rm Jup}$, well below the minimum
mass that is thought to be able to form via 3D fragmentation or 2D shocks [57,
58, 59, 55]: the formation of such low mass objects raises significant
questions in itself.

Alternatively, perhaps the JuMBOs formed through a “planet-like” mechanism in
a circumstellar disk around a host star and were violently ejected. Ejections
can be caused through planet-planet scattering in the disk [60] or by
dynamical interactions between stars [61]. The latter are relatively common in
dense star-forming regions like the Trapezium Cluster. In either case,
however, how pairs of young planets can be ejected simultaneously and remain
bound, albeit weakly at relatively wide separations, remains quite unclear.
The ensemble of PMOs and JuMBOs that we see in the Trapezium Cluster might
arise from a mix of both of these “classical” scenarios, even if both have
significant caveats, or perhaps a new, quite separate formation mechanism,
such as a fragmentation of a star-less disk is required [62, 63].

Figure 3: A subsection of the full JWST NIRcam short-wavelength colour
composite image of the Orion Nebula, located to the east of the Trapezium and
south of the Dark Bay. It is centred at 05h35m27.0s, $-05$∘23’27” (J2000.0)
and covers $52.3\times 35.3$ arcsec or $0.10\times 0.067$ pc assuming a
distance of 390 pc. The image has been rotated with N left and E down to show
this E-W strip of JuMBOs more effectively. Five JuMBOs are highlighted with
zoomed cutouts: all ten of these PMOs have masses $<7$ $M_{\rm Jup}$ Figure 4:
The wide binary fraction (WBF) as a function of primary mass, where wide is
defined as projected separations $\geq$100 au, equivalent to 0.26 arcsec at
the distance of the Trapezium Cluster. For each point, the horizontal bar
indicates the mass interval and the height of the vertical bar indicates the
statistical uncertainty in the WBF. Blue points show a compilation of
multiplicity surveys for the solar neighbourhood [43]. Green points show the
WBF for stars and brown dwarfs in the Trapezium Cluster [44, 45, 46, 47, 48,
49, 50, 20, 51, 52, 53]. Red points are for PMOs in the Trapezium Cluster from
this work.

The advent of JWST marks an exciting milestone for the field of star and
planet formation, where observations of isolated objects down to and below 1
$M_{\rm Jup}$ will soon become routine. Imaging with NIRCam will reveal many
candidates through filter-based SEDs as shown here, while follow-up
spectroscopy with NIRSpec (and in lower-density regions with NIRISS) will
allow us to place much tighter constraints on their effective temperatures,
spectral types, and chemical compositions. We will obtain NIRSpec prism
spectra of many of the Trapezium Cluster PMO and JuMBO candidates as part of
JWST programme 2770 in spring 2024. It would be particularly beneficial to see
how the demographics of PMOs change as a function of environmental parameters
such as cluster density and how they evolve with age, as this may provide
crucial insights that allow us to differentiate between the “star-like” and
“planet-like” formation scenarios for PMOs and JuMBOs alike. It is also clear
that further simulations and modelling will be needed to understand how a
substantial population of objects can form below 5 $M_{\rm Jup}$ and how a
significant fraction of them can end up in multiple systems.

##  2 Supplementary Materials

###  2.1 Observations

The data presented in this paper were obtained with the Near Infrared Camera
(NIRCam) onboard the James Webb Space Telescope (JWST), as part of Cycle 1 GTO
programme 1256, (P.I. M. McCaughrean). The observations cover an
$11^{\prime}\times 7.5^{\prime}$ area focused on the inner region of the
Trapezium Cluster. A total of 34.9 hours of observing were carried out between
September 26th and October 2nd 2022, and split between 12 filters: F115W,
F140M, F162M, F182M, F187N, F212N, F277W, F300M, F335M, F360M, F444W and
F470N. The observations are split into two mosaic patterns. For two wide-band
filters (F115W and F444W), a $7$ mosaic covers the $11^{\prime}\times
7.5^{\prime}$ field with considerable overlap between the rows and columns.
Due to the mosaic pattern, the exposure time is not uniform across the field.
This was chosen to ensure accurate registration of the full mosaic using stars
in the overlapping regions to yield a good astrometric base for future proper
motion studies. These observations used the INTRAMODULEX dither pattern, with
four primary dithers, the BRIGHT1 (NGROUPS = 6, NINT = 1) readout pattern and
a total exposure time of 515 seconds per visit. This readout pattern was
selected to maximise the dynamic range. As the Trapezium Cluster contains a
significant number of bright, massive stars, these sources will inevitably be
saturated. However, maximising the dynamic range ensures a solid overlap
between JWST and existent ground and space-based photometry for intermediate-
bright sources in order to bootstrap calibrate the faintest sources in the
JWST data. For the remaining five pairs of filters, a $5\times 2$ mosaic
covers the same region but with only marginal overlap in rows, allowing for a
more efficient use of observing time. These observations used the INTRAMODULEX
dither pattern with six primary dithers, the SHALLOW2 (NGROUPS = 3, NINT = 1)
readout pattern to reduce data volumes and a total exposure time of 773
seconds per visit. For further details on the observations, JWST and its
instruments and the Trapezium Cluster, we direct the reader to Paper I.
Observations & overview (McCaughrean & Pearson 2023).

###  2.2 Data reduction

To reduce the observations, we retrieved the stage 0 data products from the
Barbara A. Mikulski Archive for Space Telescopes (MAST) and re-ran the stage
1, 2 and 3 reduction steps using a custom version of the 1.11.3 pipeline and
Calibration Reference Data System mapping jwst _pmap_1100_. Stage 1 was run
using the optional step argument ${\rm
det1.ramp\\_fit.suppress\\_one\\_group=False}$. Stage 2 was run using the
default reduction pipeline. A custom version of the stage 3 pipeline was used
to align the individual images to Gaia Data Release 3 (GDR3) [64, 65] and
combine the images into the final full mosaics. A brief summary of this
process is given below.

The WCS of visit 2 for (F140M, F162M, F182M, F187N, F212N, F277W, F300M, F335M
and F360M) and visit 7 for (F115W and F444W) were found to be offset by
$\sim$15 arcseconds. This was corrected by manually adding an offset to the
wcs data stored in data model in the asdf tree in the fits header of each
_cal.fits file. This is was an approximate correction that does not take into
account distortion effects, but significantly reduced the search radius needed
for later fine alignment.

We first aligned the F470N data to GDR3, as this filter had the largest
overlap between the faintest Gaia sources and unsaturated JWST sources. We
compiled an absolute reference catalog of $\sim 650$ high quality GDR3 sources
that excluded flagged binaries, close pairs, extended galaxies and knots of
nebulosity; the latter being a large source of contamination for H II regions
such as the Trapezium Cluster. As this catalogue forms the basis of the
alignment, care should be taken to remove spurious sources in order to achieve
an accurate registration.

For each of the stage 2 _cal.fits images we compiled an individual source
catalogue. The x, y coordinates of the centre of the corresponding GDR3
sources were determined using a non-pipeline recentring routine. Each source
was also weighted depending on the quality of the fit and whether it was found
to be saturated in the _cal.fits data. The stage 3 TweakReg routine was then
run on each of the _cal.fits individually. The absolute reference catalogue
was passed to the TweakReg routine using the ${\rm
tweakreg.abs\\_refcat=path\\_to\\_file}$ step argument. The source catalogues
were saved as .ecsv files and were passed to the TweakReg routine by updating
the asn with the file path. This process was repeated for each _cal.fits file
individually, as the pipeline defaults to expanding the absolute reference
catalogue, which causes alignment errors. The individually aligned files were
then resampled into a full combined mosaic using step arguments: ${\rm
tweakreg.skip=True}$, ${\rm skymatch.skip=True}$, ${\rm
resample.fillval=`nan^{\prime}}$.

From this F470N mosaic a new absolute reference catalog of $\sim$1500 sources
was constructed. The F470N absolute reference catalogue had significantly more
overlap of non-saturated sources than GDR3 for the remaining filters, which
improved the alignment. This catalogue was used to repeat the above process
for the remaining 11 filters, aligning the individual _cal.fits files to the
F470N absolute reference catalogue and then combining and resampling the full
mosaics.

###  2.3 Source detection

Sources were detected in the level 3 mosaics produced by stage 3 of the
pipeline. First, the two dimensional background of each image was estimated
and subtracted using the DAOPHOT MMM algorithm as implemented in Astropy [66,
67] using a $30\times 30$ pixel box and a $5\times 5$ pixel filter. We used
the MMMBackground algorithm to divide the input data into a grid of $30\times
30$ pixels boxes and then used its mode estimator of the form (3 $\times$
median) - (2 $\times$ mean) to calculate the background level of each box,
thus creating a low resolution background map. This image was then median
filtered to suppress local under or over estimations, with a window of size of
$5\times 5$ pixels. The final background map was calculated by interpolating
the low-resolution background map. Sources were then identified using
DAOStarFinder with a threshold of $2\sigma$ and a model PSF for each of the 12
JWST filters employed [68]. Sources that were detected in $\geq$ 3 filters
were then added to a preliminary source catalogue, which was checked by eye
against the images to remove spurious sources, such as bad pixels, knots of
nebulosity, diffraction spikes, and persistence spots that had been
erroneously flagged as point sources. The by-eye examination was also used to
visually classify other sources including proplyds, outflows, and galaxies.
The final catalogue contains 3092 sources.

###  2.4 Aperture photometry

Aperture photometry was performed using Photutils [66], a package of Astropy
[67]. We used the aperture_photometry routine to obtain fluxes for all of the
sources in our catalogue, using apertures of 2.5 and 4.5 pixels radius for the
sources, while the background was measured in an annulus with inner and outer
radii of 5 and 10 pixels, respectively, using a sigma-clipped median. The
PIXAR_SR header keyword was used to convert from surface brightness (${\rm
MJy\ sr^{-1}}$) to point source flux (Jy) and then to Vega magnitudes using
the zero-points provided by the Spanish Virtual Observatory (SVO) filter
profile service [69]. To convert the aperture magnitudes to total magnitudes,
we used the aperture corrections provided by the JWST reference files for the
respective filter, interpolated to the corresponding aperture radius.

###  2.5 Extended sources

Extended sources were identified using aperture photometry and comparing the
apparent magnitudes that are calculated with inner apertures of 2.5 and 4.5
pixels. Unresolved point sources will have the same apparent magnitude
independent of the choice of inner aperture, whereas extended sources, such as
background galaxies and nebular knots, will appear brighter with larger
apertures. Sources where the median difference across all 12 filters between
2.5 and 4.5 pixel apertures was greater than 0.1 mag were classified as
extended. Sources with a neighbour within 1 arcsec were excluded from this
automated classification and checked manually. As well as galaxies, this
selection has the potential to flag highly embedded objects, objects with
resolved disks and outflows, unresolved binaries and objects in highly
featured areas of gas and dust. For this reason our sample of young PMO
candidates may not be fully complete, but will be a clean sample of reliable
candidates.

###  2.6 Evolutionary models

Throughout our analysis we have utilised the CBPD22 evolutionary models [10],
which combine the atmospheric models from ATMO 2020 [28] with the a new
equation of state for dense hydrogen-helium mixtures [29]. In earlier models
the equation of state was based on the so-called additive volume law [70, 71],
which does not take into account the interactions between hydrogen and helium
species. This updated equation of state takes these interactions into account
and modifies the thermodynamic properties of the H/He mixture. This primarily
affects the entropy profiles, which in turn alters the development of
degeneracy and internal structure. The ATMO 2020 models use a 1D radiative-
convective equilibrium code to generate three grids of atmospheric models, one
using equilibrium chemistry (CEQ) and two using non-equilibrium chemistry
(NEQ_weak & NEQ_strong). The non-equilibrium models use a weak and a strong
scaling relation for the eddy diffusion coefficient with surface gravity,
which alter the vertical mixing relationships. These models cover the
planetary mass regime from $(0.0004{\rm M}_{\odot}-0.015{\rm M}_{\odot})$. In
order to cover the brown dwarf and stellar mass ranges $(0.01{\rm
M}_{\odot}-1.4{\rm M}_{\odot})$ we have used the BHAC15 evolutionary models
[8].

##  3 JuMBO Catalogue

Name | RA (deg) | DEC (deg) | M_Pri | Av_Pri | M_Sec | Av_Sec | Proj_Sep | M_Ter | Av_Ter
---|---|---|---|---|---|---|---|---|---
JuMBO 1 | 83.716375 | -5.374688 | 0.001 | 6.3 | 0.001 | 4.3 | 357.7 | - | -
JuMBO 2 | 83.718439 | -5.391585 | 0.002 | 16.4 | 0.002 | 13.1 | 114.7 | - | -
JuMBO 3 | 83.720854 | -5.379591 | 0.003 | 19.7 | 0.003 | 10.8 | 52.3 | - | -
JuMBO 4 | 83.727380 | -5.444921 | 0.002 | 23.7 | 0.001 | 10.6 | 324.4 | - | -
JuMBO 5 | 83.727997 | -5.389459 | 0.003 | 10 | 0.002 | 32.8 | 384.3 | - | -
JuMBO 6 | 83.734156 | -5.368803 | 0.003 | 46.6 | 0.003 | 56.5 | 70.2 | - | -
JuMBO 7 | 83.735012 | -5.387694 | 0.001 | 17.4 | 0.001 | 17.3 | 119 | - | -
JuMBO 8 | 83.736001 | -5.445662 | 0.002 | 21 | 0.002 | 15.9 | 101.2 | - | -
JuMBO 9 | 83.736884 | -5.332175 | 0.001 | 13.1 | 0.0007 | 8.8 | 211.5 | - | -
JuMBO 10 | 83.748149 | -5.445690 | 0.001 | 6.9 | 0.001 | 8.9 | 342.5 | - | -
JuMBO 11 | 83.753378 | -5.431788 | 0.0008 | 10.4 | 0.0007 | 15.9 | 192.2 | - | -
JuMBO 12 | 83.753580 | -5.354639 | 0.003 | 20.1 | 0.001 | 19.8 | 366.2 | - | -
JuMBO 13 | 83.760064 | -5.393619 | 0.001 | 20.5 | 0.001 | 26.5 | 192.6 | - | -
JuMBO 14 | 83.767052 | -5.406016 | 0.009 | 39.5 | 0.008 | 36 | 55.6 | - | -
JuMBO 15 | 83.768695 | -5.440258 | 0.003 | 39.8 | 0.002 | 26.5 | 329.8 | - | -
JuMBO 16 | 83.769429 | -5.415209 | 0.001 | 5.3 | 0.001 | 6.5 | 273.9 | - | -
JuMBO 17 | 83.775698 | -5.432976 | 0.001 | 24.5 | 0.0006 | 10.7 | 194.9 | - | -
JuMBO 18 | 83.779749 | -5.424113 | 0.003 | 11.7 | 0.002 | 6.6 | 150.6 | - | -
JuMBO 19 | 83.785686 | -5.345893 | 0.003 | 22.6 | 0.002 | 31.5 | 273.6 | - | -
JuMBO 20 | 83.786364 | -5.411568 | 0.003 | 19.1 | 0.002 | 11.3 | 149.4 | - | -
JuMBO 21 | 83.788762 | -5.398635 | 0.007 | 74.2 | 0.002 | 26.1 | 200.5 | - | -
JuMBO 22 | 83.801462 | -5.342754 | 0.004 | 51.6 | 0.003 | 29.4 | 127.4 | - | -
JuMBO 23 | 83.829058 | -5.446920 | 0.004 | 35.2 | 0.002 | 11.3 | 314.7 | - | -
JuMBO 24 | 83.831262 | -5.394369 | 0.011 | 3.6 | 0.011 | 3.5 | 28 | - | -
JuMBO 25 | 83.836455 | -5.371124 | 0.005 | 14.2 | 0.004 | 16.4 | 46.1 | 0.004 | 6.1
JuMBO 26 | 83.838007 | -5.366544 | 0.008 | 12.5 | 0.003 | 9.1 | 267.1 | - | -
JuMBO 27 | 83.846621 | -5.399533 | 0.009 | 2.4 | 0.002 | 2.8 | 333.1 | - | -
JuMBO 28 | 83.846940 | -5.392726 | 0.011 | 8.7 | 0.009 | 20.1 | 58.9 | - | -
JuMBO 29 | 83.847252 | -5.346677 | 0.012 | 11.9 | 0.003 | 14.4 | 135 | - | -
JuMBO 30 | 83.848540 | -5.405963 | 0.005 | 33.1 | 0.002 | 2.2 | 374.1 | - | -
JuMBO 31 | 83.856732 | -5.387897 | 0.007 | 12.8 | 0.003 | 15.2 | 206.7 | - | -
JuMBO 32 | 83.860453 | -5.388966 | 0.004 | 14.4 | 0.003 | 11.9 | 118 | - | -
JuMBO 33 | 83.863086 | -5.388234 | 0.004 | 17.8 | 0.004 | 23.1 | 73.7 | - | -
JuMBO 34 | 83.867221 | -5.388611 | 0.005 | 15.4 | 0.005 | 13.9 | 66.4 | - | -
JuMBO 35 | 83.868427 | -5.390019 | 0.004 | 10.1 | 0.003 | 10.3 | 84.5 | - | -
JuMBO 36 | 83.878803 | -5.340274 | 0.013 | 32.3 | 0.004 | 36 | 363 | - | -
JuMBO 37 | 83.882254 | -5.330745 | 0.003 | 18.3 | 0.002 | 32.2 | 317.6 | - | -
JuMBO 38 | 83.883267 | -5.351932 | 0.004 | 27.8 | 0.002 | 24.4 | 213.6 | - | -
JuMBO 39 | 83.886789 | -5.372932 | 0.004 | 41.9 | 0.002 | 32.9 | 251 | - | -
JuMBO 40 | 83.886856 | -5.364031 | 0.005 | 18.1 | 0.005 | 23 | 164.3 | - | -
JuMBO 41 | 83.887251 | -5.375283 | 0.011 | 31.7 | 0.0008 | 17.2 | 287.2 | - | -
JuMBO 42 | 83.897548 | -5.333713 | 0.003 | 17.8 | 0.0007 | 15.2 | 123.3 | 0.0007 | 10.8
|  |  |  |  |  |  |  |  |
Table 1: A short summary of the key JuMBO properties. All masses are in units
of  $M_{\odot}$, projected separation are given in au. For an extend version
of this table that includes photometry, see the supplementary catalogue.

##  4 Data Availability

The data presented in this paper were obtained with the Near Infrared Camera
(NIRCam) onboard the NASA/ESA/CSA James Webb Space Telescope (JWST), as part
of Cycle 1 GTO programme 1256, (P.I. M. McCaughrean). They are available on
the Barbara A. Mikulski Archive for Space Telescopes (MAST):
http://dx.doi.org/10.17909/vjys-x251.

##  5 Acknowledgements

SGP acknowledges support through the ESA research fellowship programme. The
time used to make these JWST observations come from the Guaranteed Time
Observation allocation made to MJM upon selection as one of two ESA
Interdisciplinary Scientists on the JWST Science Working Group (SWG) in
response to NASA AO-01-OSS-05 issued in 2001. SGP would like to thank Victor
See for helpful discussions and Katja Fahrion for valuable insights on the
JWST calibration pipeline. This work has made use of data from the European
Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed
by the Gaia Data Processing and Analysis Consortium (DPAC,
https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has
been provided by national institutions, in particular the institutions
participating in the Gaia Multilateral Agreement. This research has made use
of the Spanish Virtual Observatory (https://svo.cab.inta-csic.es) project
funded by MCIN/AEI/10.13039/501100011033/ through grant PID2020-112949GB-I00.
This work made use of Astropy:222http://www.astropy.org a community-developed
core Python package and an ecosystem of tools and resources for astronomy
[67]. This research made use of Photutils, an Astropy package for detection
and photometry of astronomical sources [66].

## References

  *   * [1] McCaughrean, M. J. & Stauffer, J. R.  High Resolution Near-Infrared Imaging of the Trapezium: A Stellar Census.  _AJ_ 108, 1382 (1994).
  * [2] Morales-Calderón, M. _et al._ Ysovar: The First Sensitive, Wide-area, Mid-infrared Photometric Monitoring of the Orion Nebula Cluster.  _ApJ_ 733, 50 (2011).
  * [3] Hillenbrand, L. A.  On the Stellar Population and Star-Forming History of the Orion Nebula Cluster.  _AJ_ 113, 1733–1768 (1997).
  * [4] Scandariato, G., Robberto, M., Pagano, I. & Hillenbrand, L. A.  The extinction map of the OMC-1 molecular cloud behind the Orion nebula.  _A &A_ 533, A38 (2011).
  * [5] Maíz Apellániz, J. _et al._ The Villafranca catalog of Galactic OB groups. II. From Gaia DR2 to EDR3 and ten new systems with O stars.  _A &A_ 657, A131 (2022).
  * [6] Muench, A., Getman, K., Hillenbrand, L. & Preibisch, T.  in Star Formation in the Orion Nebula I: Stellar Content (ed.Reipurth, B.) _Handbook of Star Forming Regions, Volume I_ , Vol. 4 483 (2008).
  * [7] O’Dell, C. R., Muench, A., Smith, N. & Zapata, L.  in Star Formation in the Orion Nebula II: Gas, Dust, Proplyds and Outflows (ed.Reipurth, B.) _Handbook of Star Forming Regions, Volume I_ , Vol. 4 544 (2008).
  * [8] Baraffe, I., Homeier, D., Allard, F. & Chabrier, G.  New evolutionary models for pre-main sequence and main sequence low-mass stars down to the hydrogen-burning limit.  _A &A_ 577, A42 (2015).
  * [9] Dupuy, T. J. & Liu, M. C.  Individual Dynamical Masses of Ultracool Dwarfs.  _ApJS_ 231, 15 (2017).
  * [10] Chabrier, G., Baraffe, I., Phillips, M. & Debras, F.  Impact of a new H/He equation of state on the evolution of massive brown dwarfs. New determination of the hydrogen burning limit.  _A &A_ 671, A119 (2023).
  * [11] Lucas, P. W. & Roche, P. F.  A population of very young brown dwarfs and free-floating planets in Orion.  _MNRAS_ 314, 858–864 (2000).
  * [12] McCaughrean, M., Zinnecker, H., Andersen, M., Meeus, G. & Lodieu, N.  Standing on the shoulder of a giant: ISAAC, Antu, and star formation.  _The Messenger_ 109, 28–36 (2002).
  * [13] Slesnick, C. L., Hillenbrand, L. A. & Carpenter, J. M.  The Spectroscopically Determined Substellar Mass Function of the Orion Nebula Cluster.  _ApJ_ 610, 1045–1063 (2004).
  * [14] Meeus, G. & McCaughrean, M. J.  Using near-IR spectroscopy to classify substellar candidates in the Trapezium Cluster.  _Astronomische Nachrichten_ 326, 977–980 (2005).
  * [15] Lucas, P. W., Roche, P. F. & Tamura, M.  A deep survey of brown dwarfs in Orion with Gemini.  _MNRAS_ 361, 211–232 (2005).
  * [16] Riddick, F. C., Roche, P. F. & Lucas, P. W.  An optical spectroscopic HR diagram for low-mass stars and brown dwarfs in Orion.  _MNRAS_ 381, 1077–1092 (2007).
  * [17] Weights, D. J., Lucas, P. W., Roche, P. F., Pinfield, D. J. & Riddick, F.  Infrared spectroscopy and analysis of brown dwarf and planetary mass objects in the Orion nebula cluster.  _MNRAS_ 392, 817–846 (2009).
  * [18] Anderson, M. M. & Biller, B.  Searching for Brown Dwarfs and Brown Dwarf Binaries in Upper Scorpius, the Trapezium, and IC 348 Using the UKIDSS Galactic Cluster Survey (2011).
  * [19] Da Rio, N., Robberto, M., Hillenbrand, L. A., Henning, T. & Stassun, K. G.  The Initial Mass Function of the Orion Nebula Cluster across the H-burning Limit.  _ApJ_ 748, 14 (2012).
  * [20] Robberto, M. _et al._ HST Survey of the Orion Nebula Cluster in the H2O 1.4 $\mu$m Absorption Band. I. A Census of Substellar and Planetary-mass Objects.  _ApJ_ 896, 79 (2020).
  * [21] Lucas, P. W., Roche, P. F., Allard, F. & Hauschildt, P. H.  Infrared spectroscopy of substellar objects in Orion.  _MNRAS_ 326, 695–721 (2001).
  * [22] Lucas, P. W., Weights, D. J., Roche, P. F. & Riddick, F. C.  Spectroscopy of planetary mass brown dwarfs in Orion.  _MNRAS_ 373, L60–L64 (2006).
  * [23] Scholz, A. _et al._ Substellar Objects in Nearby Young Clusters (SONYC). VI. The Planetary-mass Domain of NGC 1333.  _ApJ_ 756, 24 (2012).
  * [24] Peña Ramírez, K., Béjar, V. J. S., Zapatero Osorio, M. R., Petr-Gotzens, M. G. & Martín, E. L.  New Isolated Planetary-mass Objects and the Stellar and Substellar Mass Function of the $\sigma$ Orionis Cluster.  _ApJ_ 754, 30 (2012).
  * [25] Gagné, J. _et al._ Banyan. ix. the initial mass function and planetary-mass object space density of the tw hya association.  _The Astrophysical Journal Supplement Series_ 228, 18 (2017).
  * [26] Lodieu, N., Hambly, N. C. & Cross, N. J. G.  Exploring the planetary-mass population in the Upper Scorpius association.  _MNRAS_ 503, 2265–2279 (2021).
  * [27] Bouy, H. _et al._ Infrared spectroscopy of free-floating planet candidates in Upper Scorpius and Ophiuchus.  _A &A_ 664, A111 (2022).
  * [28] Phillips, M. W. _et al._ A new set of atmosphere and evolution models for cool T-Y brown dwarfs and giant exoplanets.  _A &A_ 637, A38 (2020).
  * [29] Chabrier, G. & Debras, F.  A New Equation of State for Dense Hydrogen-Helium Mixtures. II. Taking into Account Hydrogen-Helium Interactions.  _ApJ_ 917, 4 (2021).
  * [30] Gordon, I. _et al._ The hitran2020 molecular spectroscopic database.  _Journal of Quantitative Spectroscopy and Radiative Transfer_ 277, 107949 (2022).  URL https://www.sciencedirect.com/science/article/pii/S0022407321004416.
  * [31] Mathis, J. S.  Interstellar dust and extinction.  _ARA &A_ 28, 37–70 (1990).
  * [32] Scholz, A., Muzic, K., Jayawardhana, R., Quinlan, L. & Wurster, J.  Rogue Planets and Brown Dwarfs: Predicting the Populations Free-floating Planetary Mass Objects Observable with JWST.  _PASP_ 134, 104401 (2022).
  * [33] Castets, A. _et al._ A multi-transition study of carbon monoxide in the Orion A molecular cloud.  _A &A_ 234, 469 (1990).
  * [34] van Elteren, A., Portegies Zwart, S., Pelupessy, I., Cai, M. X. & McMillan, S. L. W.  Survivability of planetary systems in young and dense star clusters.  _A &A_ 624, A120 (2019).  URL https://doi.org/10.1051/0004-6361/201834641.
  * [35] Zahnle, K. J. & Marley, M. S.  Methane, Carbon Monoxide, and Ammonia in Brown Dwarfs and Self-Luminous Giant Planets.  _ApJ_ 797, 41 (2014).
  * [36] Duquennoy, A. & Mayor, M.  Multiplicity among Solar Type Stars in the Solar Neighbourhood - Part Two - Distribution of the Orbital Elements in an Unbiased Sample.  _A &A_ 248, 485 (1991).
  * [37] Burgasser, A. J.  Binaries and the L Dwarf/T Dwarf Transition.  _ApJ_ 659, 655–674 (2007).
  * [38] Fontanive, C., Biller, B., Bonavita, M. & Allers, K.  Constraining the multiplicity statistics of the coolest brown dwarfs: binary fraction continues to decrease with spectral type.  _MNRAS_ 479, 2702–2727 (2018).
  * [39] Bate, M. R.  The statistical properties of stars and their dependence on metallicity.  _MNRAS_ 484, 2341–2361 (2019).
  * [40] Fontanive, C. _et al._ An HST survey of 33 T8 to Y1 brown dwarfs: NIR photometry and multiplicity of the coldest isolated objects.  _MNRAS_ (2023).
  * [41] Best, W. M. J., Liu, M. C., Magnier, E. A. & Dupuy, T. J.  A Volume-limited Sample of Ultracool Dwarfs. I. Construction, Space Density, and a Gap in the L/T Transition.  _AJ_ 161, 42 (2021).
  * [42] Close, L. M., Siegler, N., Freed, M. & Biller, B.  Detection of Nine M8.0-L0.5 Binaries: The Very Low Mass Binary Population and Its Implications for Brown Dwarf and Very Low Mass Star Formation.  _ApJ_ 587, 407–422 (2003).
  * [43] Offner, S. S. R. _et al._ The Origin and Evolution of Multiple Star Systems.  _arXiv e-prints_ arXiv:2203.10066 (2022).
  * [44] Reipurth, B., Guimarães, M. M., Connelley, M. S. & Bally, J.  Visual Binaries in the Orion Nebula Cluster.  _AJ_ 134, 2272–2285 (2007).
  * [45] Correia, S. _et al._ Stellar and circumstellar properties of visual binaries in the Orion Nebula Cluster.  _A &A_ 557, A63 (2013).
  * [46] Kounkel, M. _et al._ Spectroscopic Binaries in the Orion Nebula Cluster and NGC 2264.  _ApJ_ 821, 8 (2016).
  * [47] Kounkel, M., Megeath, S. T., Poteet, C. A., Fischer, W. J. & Hartmann, L.  An HST Survey for 100-1000 au Companions around Young Stellar Objects in the Orion Molecular Clouds: Evidence for Environmentally Dependent Multiplicity.  _ApJ_ 821, 52 (2016).
  * [48] Duchêne, G., Lacour, S., Moraux, E., Goodwin, S. & Bouvier, J.  Is stellar multiplicity universal? Tight stellar binaries in the Orion nebula Cluster.  _MNRAS_ 478, 1825–1836 (2018).
  * [49] Jerabkova, T. _et al._ When the tale comes true: multiple populations and wide binaries in the Orion Nebula Cluster.  _A &A_ 627, A57 (2019).
  * [50] De Furio, M. _et al._ A Search for Intermediate-separation Low-mass Binaries in the Orion Nebula Cluster.  _ApJ_ 886, 95 (2019).
  * [51] Strampelli, G. M. _et al._ HST Survey of the Orion Nebula Cluster in the H2O 1.4 $\mu$m Absorption Band. III. The Population of Substellar Binary Companions.  _ApJ_ 896, 81 (2020).
  * [52] De Furio, M. _et al._ Demographics of the M-star Multiple Population in the Orion Nebula Cluster.  _ApJ_ 941, 161 (2022).
  * [53] De Furio, M. _et al._ Binary Formation in the Orion Nebula Cluster: Exploring the Substellar Limit.  _ApJ_ 925, 112 (2022).
  * [54] Luhman, K. L.  The formation and early evolution of low-mass stars and brown dwarfs.  _Annual Review of Astronomy and Astrophysics_ 50, 65–106 (2012).  URL https://doi.org/10.1146/annurev-astro-081811-125528.
  * [55] Whitworth, A., Bate, M. R., Nordlund, Å., Reipurth, B. & Zinnecker, H.  Reipurth, B., Jewitt, D. & Keil, K. (eds) _The Formation of Brown Dwarfs: Theory_.  (eds Reipurth, B., Jewitt, D. & Keil, K.) _Protostars and Planets V_ , 459 (2007).
  * [56] Parker, R. J. & Alves de Oliveira, C.  On the origin of planetary-mass objects in NGC1333.  _arXiv e-prints_ arXiv:2308.01335 (2023).
  * [57] Low, C. & Lynden-Bell, D.  The minimum Jeans mass or when fragmentation must stop.  _MNRAS_ 176, 367–390 (1976).
  * [58] Rees, M. J.  Opacity-limited hierarchical fragmentation and the masses of protostars.  _MNRAS_ 176, 483–486 (1976).
  * [59] Boyd, D. F. A. & Whitworth, A. P.  The minimum mass for opacity-limited fragmentation in turbulent cloud cores.  _A &A_ 430, 1059–1066 (2005).
  * [60] Smullen, R. A., Kratter, K. M. & Shannon, A.  Planet scattering around binaries: ejections, not collisions.  _MNRAS_ 461, 1288–1301 (2016).
  * [61] Bonnell, I. A., Smith, K. W., Davies, M. B. & Horne, K.  Planetary dynamics in stellar clusters.  _MNRAS_ 322, 859–865 (2001).
  * [62] Bodenheimer, P.  Evolution of rotating interstellar clouds. III. On the formation of multiple star systems.  _ApJ_ 224, 488–496 (1978).
  * [63] Tohline, J. E.  The Origin of Binary Stars.  _ARA &A_ 40, 349–385 (2002).
  * [64] Gaia Collaboration _et al._ The Gaia mission.  _A &A_ 595, A1 (2016).
  * [65] Gaia Collaboration _et al._ Gaia Data Release 3. Summary of the content and survey properties.  _A &A_ 674, A1 (2023).
  * [66] Bradley, L. _et al._ astropy/photutils: 1.8.0 (2023).  URL https://doi.org/10.5281/zenodo.7946442.
  * [67] Astropy Collaboration _et al._ The Astropy Project: Sustaining and Growing a Community-oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package.  _apj_ 935, 167 (2022).
  * [68] Perrin, M. D. _et al._ Jr., J. M. O., Clampin, M., Fazio, G. G. & MacEwen, H. A. (eds) _Updated point spread function simulations for JWST with WebbPSF_.  (eds Jr., J. M. O., Clampin, M., Fazio, G. G. & MacEwen, H. A.) _Space Telescopes and Instrumentation 2014: Optical, Infrared, and Millimeter Wave_ , Vol. 9143, 91433X. International Society for Optics and Photonics (SPIE, 2014).  URL https://doi.org/10.1117/12.2056689.
  * [69] Rodrigo, C. & Solano, E.  The SVO Filter Profile Service (2020).
  * [70] Saumon, D., Chabrier, G. & van Horn, H. M.  An Equation of State for Low-Mass Stars and Giant Planets.  _ApJS_ 99, 713 (1995).
  * [71] Chabrier, G., Mazevet, S. & Soubiran, F.  A New Equation of State for Dense Hydrogen-Helium Mixtures.  _ApJ_ 872, 51 (2019).