11institutetext: Astronomical Institute of the Romanian Academy, 5 Cuţitul de
Argint, 040557 Bucharest, Romania 22institutetext: Isaac Newton Group of
Telescopes (ING), Apto. 321, E-38700 Santa Cruz de la Palma, Canary Islands,
Spain 33institutetext: Instituto de Astrofísica de Canarias (IAC), C/Vía
Láctea s/n, 38205 La Laguna, Tenerife, Spain 44institutetext: The University
of Craiova, Str. A. I. Cuza nr. 13, 200585 Craiova, Romania 55institutetext:
Departamento de Astrofísica, Universidad de La Laguna, 38206 La Laguna,
Tenerife, Spain 66institutetext: Universidad Complutense de Madrid, Ciudad
Universitaria, E-28040 Madrid, Spain 77institutetext: AEGORA Research Group,
Facultad de CC. Matemáticas, Universidad Complutense de Madrid, Spain
88institutetext: Department of Physics and Astronomy, University of Sheffield,
Sheffield S3 7RH, UK 99institutetext: Isaac Aznar Observatory, Alcublas,
Valencia, Spain 1010institutetext: ROASTERR-1 observatory, Cluj-Napoca,
Romania 1111institutetext: Institute of Space Science (ISS), 409, Atomiştilor
Street, 077125 Măgurele, Ilfov, Romania

# Discovery and physical characterization as the first response to a potential
asteroid collision: The case of 2023 DZ2††thanks: Based on observations made
with the Gran Telescopio Canarias (GTC) telescope and the Isaac Newton
Telescope (INT), in the Spanish Observatorio del Roque de los Muchachos of the
Instituto de Astrofísica de Canarias (program IDs GTC31-23A and
INT99-MULTIPLE-2/23A), and the Two-Meter Twin Telescope (TTT) and the
Telescopio Carlos Sanchez (TCS), in the Spanish Observatorio del Teide of the
Instituto de Astrofísica de Canarias (commissioning phase).

Marcel M. Popescu 11 O. Văduvescu 223344 Julia de León 3355 C. de la Fuente
Marcos 66 R. de la Fuente Marcos 77 M. O. Stănescu 11 M. R. Alarcon 3355 M.
Serra Ricart 33 5 5 J. Licandro 3355 D. Berteşteanu 11 M. Predatu 44 L.
Curelaru 11 F. Barwell 2288 K. Jhass 2288 C. Boldea 44 A. Aznar Macías 99 L.
Hudin 1010 B. A. Dumitru 1111<EMAIL_ADDRESS>
(Received 26 April 2023 / Accepted DD Mmmmm YYYY)

###### Abstract

Context. Near-Earth asteroids (NEAs) that may evolve into impactors deserve
detailed threat assessment studies. Early physical characterization of a
would-be impactor may help in optimizing impact mitigation plans. We first
detected NEA 2023 DZ2 on 27–February–2023. After that, it was found to have a
Minimum Orbit Intersection Distance (MOID) with Earth of 0.00005 au as well as
an unusually high initial probability of becoming a near-term (in 2026)
impactor.

Aims. We aim to perform a rapid but consistent dynamical and physical
characterization of 2023 DZ2 as an example of a key response to mitigate the
consequences of a potential impact.

Methods. We use a multi-pronged approach, drawing from various methods
(observational/computational) and techniques (spectroscopy/photometry from
multiple instruments), and bringing the data together to perform a rapid and
robust threat assessment.

Results. The visible reflectance spectrum of 2023 DZ2 is consistent with that
of an X-type asteroid. Light curves of this object obtained on two different
nights give a rotation period $P$=6.2743$\pm$0.0005 min with an amplitude
$A$=0.57$\pm$0.14 mag. We confirm that although its MOID is among the smallest
known, 2023 DZ2 will not impact Earth in the foreseeable future as a result of
secular near-resonant behaviour.

Conclusions. Our investigation shows that coordinated observation and
interpretation of disparate data provides a robust approach from discovery to
threat assessment when a virtual impactor is identified. We prove that
critical information can be obtained within a few days after the announcement
of the potential impactor.

###### Key Words.:

Minor planets, asteroids: individual: 2023 DZ2 – – techniques: spectroscopic –
techniques: photometric – methods: observational – methods: numerical –
celestial mechanics

††offprints: Marcel M. Popescu,

##  1 Introduction

When a new Solar system body (asteroid or comet) is discovered and its
observations cover a short time interval, the orbit determination has a large
uncertainty. Thus, at a given moment, the object can be anywhere inside a
region defined by the propagation of the orbital uncertainties. Milani et al.
(2000) introduced the concept of virtual asteroid, a hypothetical object that
follows any possible orbital solution obtained from the existing observations.
If the dynamical evolution of any of these virtual asteroids is compatible
with an Earth collision this is called a virtual impactor (abbreviated VI).
Consequently, additional astrometric observations are needed to improve the
orbit determination so the impact probability is better constrained, leading
to its eventual removal as a threat (see e.g. Milani et al. 2000; Milani
2005). This can be accomplished either by triggering new telescope
observations or by data-mining the various observatories databases for
”precoveries” (unnoticed apparitions in images acquired prior to its
discovery) or both (see e.g. Vaduvescu et al. 2013, 2020).

Large robotic surveys, such as the Panoramic Survey Telescope and Rapid
Response System (Pan-STARRS, Kaiser 2004; Denneau et al. 2013), the Catalina
Sky Survey (CSS, Christensen et al. 2012), the Asteroid Terrestrial-impact
Last Alert System (ATLAS, Tonry et al. 2018), and the Zwicky Transient
Facility (ZTF, Ye et al. 2019) are continuously discovering most of the near-
Earth asteroids (NEAs, or NEOs for near-Earth objects) down to an apparent $V$
magnitude as faint as 22 (depending on the survey). Nevertheless, there are
regions of the sky which may not be observed for a long time by these
facilities (due to the observing strategy, the weather, instrument updates,
technical issues). Thus, the complementary observations performed by other
facilities around the world are of significant importance for confirming,
recovering, orbit refinement, and discovering NEOs.

The efficiency in finding unknown Solar system objects (SSOs) depends on two
factors, the limiting magnitude that can be reached with an instrument and the
sky area that can be covered. Because the majority of the facilities that aim
at finding NEAs do not have access to telescopes with large aperture (compared
with those of the above mentioned surveys), a wide field of view (FoV) covered
during an observing run remains the accessible option. For example, an
ingenious approach is used by Alain Maury, Georges Attard, Daniel Parrott, and
their collaborators (the team of the MAP telescopes) to survey the Southern
sky with small aperture telescopes having large
FoV.111https://www.spaceobs.com/en/Alain-Maury-s-Blog/2023-DW accessed on
22-April-2023

Close passers are small bodies that experience periodic close encounters with
the Earth-Moon system and may eventually collide with Earth. Considering
geological time scales, these small bodies represent a potential threat to
life on our planet. This fact is evidenced by past impact events such as
super-bolides, known craters, and mass extinctions attributed to major
impacts. According to the most recent work, there are at least 210 known Earth
craters caused by asteroids or comets (Kenkmann & Artemieva 2021; James et al.
2022), while, on average, every year one meteoroid of about 3–4 m explodes in
the atmosphere of our planet (see e.g. Devillepoix et al. 2019).

The Chelyabinsk superbolide fall on 15-February-2013, reminded us that
collisions of small Solar system bodies with Earth may have catastrophic
consequences (Brown et al. 2013; Borovička et al. 2013). Despite the
relatively small size of this asteroid that entered through the atmosphere
(about 18 m) on that date, it caused a significant amount of ground damage due
to the air burst, affecting an area of more than 10 000 $km^{2}$ and causing
injuries to more than 1500 people (see e.g. Kartashova et al. 2018). This
small NEA was not detected by active NEA surveys because its apparent motion
was too close to the Sun prior to impact. Thus, no mitigation measurements
were attempted.

In order to mitigate these natural disasters, it is critical that these NEOs
are first discovered with sufficient time prior to impact, and then their
physical properties are determined as accurately and rapidly as possible. For
example, metallic asteroids may overcome current asteroid impact avoidance
strategies and survive after falling through the atmosphere causing major
damage when they collide with our planet. The measures to prevent the impact
or mitigate its consequences can only be taken based on information gained
from detailed telescopic observations. The capability to offer a rapid
response to a potential danger is a key factor for proper mitigation. Early
physical characterization of a would-be impactor may help in optimizing impact
mitigation plans.

A recent example of this sequence of events at work is represented by 2023
DZ2. We discovered this Apollo-class NEA on the night of 27-February-2023
using the 2.54 m Isaac Newton Telescope
(INT)222https://www.ing.iac.es/astronomy/telescopes/int/ within the context of
the EURONEAR (EUROpean Near Earth Asteroids Research)
collaboration.333http://www.euronear.org We promptly followed-up this
discovery with astrometric observations during the next two nights. The data
were submitted to the Minor Planet Center
(MPC).444https://www.minorplanetcenter.net/iau/mpc.html Immediately after the
announcement of its discovery trough an Minor Planet Electronic Circular (MPEC
2023-F12, Vaduvescu et al. 2023), it was catalogued as a VI by Jet Propulsion
Laboratory’s (JPL) Sentry System for Earth impact
monitoring,555https://cneos.jpl.nasa.gov/sentry/ by the NEODyS CLOMON2 Risk
page666https://newton.spacedys.com/neodys/index.php?pc=4.0 list, and also by
ESA Risk List.777https://neo.ssa.esa.int/risk-list As additional observations
were reported to the MPC by multiple observers around the world, the
cumulative impact probability increased by several orders of magnitude (up to
a cumulative impact probability of 0.0023 on March 18) but the analysis of the
improved orbits led to the eventual removal of 2023 DZ2 from the Sentry System
on March 21.

Table 1: Values of the heliocentric Keplerian orbital elements and their
respective 1$\sigma$ uncertainties of 2023 DZ2.

Orbital parameter |  | value$\pm$1$\sigma$ uncertainty
---|---|---
Semimajor axis, $a$ (au) | = | 2.1555715$\pm$0.0000002
Eccentricity, $e$ | = | 0.53892721$\pm$0.00000005
Inclination, $i$ (°) | = | 0.0814345$\pm$0.0000012
Longitude of the ascending node, $\Omega$ (°) | = | 187.91380$\pm$0.00006
Argument of perihelion, $\omega$ (°) | = | 5.95978$\pm$0.00006
Mean anomaly, $M$ (°) | = | 348.674236$\pm$0.000002
Perihelion distance, $q$ (au) | = | 0.993875393$\pm$0.000000007
Aphelion distance, $Q$ (au) | = | 3.3172677$\pm$0.0000003
Absolute magnitude, $H$ (mag) | = | 24.3$\pm$0.4
888The orbit determination of 2023 DZ2 is referred to epoch JD 2460000.5
(25-Feb-2023) TDB (Barycentric Dynamical Time, J2000.0 ecliptic and equinox)
and it is based on 635 observations with a data-arc span of 72 days (solution
date, 24-April-2023, 08:41:00 PDT). The input data also include radar
observations (4 delay and 1 Doppler). Source: JPL’s SBDB.

Based on the apparent magnitude values reported together with the astrometric
measurements by various observers, an absolute magnitude $H\approx$24 was
estimated, which indicates a size in the range of 40 m to 100 m. A potential
impact of such an asteroid can cause damages at local or regional level (see
e.g. Morrison 1992). A close approach date of 25-March-2023 was estimated. As
this NEA became brighter, more observations were reported including many by
amateur astronomers who are able to acquire highly accurate data with
affordable equipment (e.g. Farnocchia et al. 2022; Bertesteanu et al. 2022).
Fortunately, the impact probability decreased at insignificant levels
($\approx 10^{-7}$) during the following days. The orbital elements of 2023
DZ2 derived by using 634 observations with a data-arc covering of 72 days are
reported in Table 1.

Nevertheless, 2023 DZ2 safely passed at a distance of 175 030 km from Earth,
on March 25 at 19:51 TDB (time-scale conversion difference TDB $-$ UT
69.185285 s), when it reached an apparent visual magnitude of 10.3 (for a
minimum of $\approx$10 mag reached about two hours prior to perigee). Thanks
to its brightness it offered a unique opportunity for characterization with
various observational techniques: photometry, spectro-photometry, spectroscopy
of various spectral intervals (visible, near-infrared, mid-infrared),
polarimetry, and radar.

The International Asteroid Warning Network (IAWN)999https://iawn.net/
organized a world wide campaign with the aim of involving as many observing
facilities as possible, in a coordinated manner, to obtain the most accurate
physical information about this object. This international organization was
established in 2013 as a result of the UN-endorsed recommendations for an
international response to a potential NEO impact threat. Their objective is to
develop a ”strategy using well-defined communication plans and protocols to
assist Governments in the analysis of asteroid impact consequences and in the
planning of mitigation responses.”

The close approach of 2023 DZ2 offered a great opportunity for a world-wide
collaboration to study a potential NEA impactor discovered one month prior to
its close approach. Previous IAWN campaigns (Reddy et al. 2019, 2022;
Farnocchia et al. 2022) targeted NEAs discovered some years before , thus
allowing plenty of time to organize them.

Table 2: Observational circumstances of 2023 DZ2. .

Obs. | Date | $m_{V}$ | $\alpha$ | $\Delta$ | $r$
---|---|---|---|---|---
Type | Obs. (UTC) |  | (∘) | (au) | (au)
Phot. | 2023 03 20.9143 | 18.0 | 60.5 | 0.021 | 1.006
| 2023 03 21.9284 | 17.5 | 60.9 | 0.017 | 1.004
| 2023 03 22.9467 | 16.8 | 60.8 | 0.013 | 1.003
Colo. | 2023 03 22.8725 | 17.0 | 60.7 | 0.013 | 1.003
Spec. | 2023 03 17.8739 | 19.0 | 57.9 | 0.034 | 1.013
| 2023 03 20.9161 | 18.0 | 60.5 | 0.021 | 1.006
101010Observation type includes time-series photometry (Phot.), colour
photometry (Colo.) and visible spectra (Spec.). The UTC time corresponding to
the start of the observations, the predicted apparent $V$ magnitude ($m_{V}$),
the phase angle ($\alpha$), the geocentric($\Delta$) and heliocentric ($r$)
distances are shown (these were obtained using the MPC ephemeris service
accessed on 30-March-2023).

In this paper, we show the results of our observing campaign, performed using
several telescopes from the observatories of the Canary Islands and aimed at
determining the physical properties of 2023 DZ2. The objective of our work is
to highlight the critical observational capabilities, both in terms of
instruments and data analysis resources, required to implement mitigation
strategies to face the potential disasters coming from a cosmic hazard such as
an asteroid impact.

In less than a week since the announcement of the discovery and initial
classification as VI of 2023 DZ2, we were able to determine its spin rate and
the light curve amplitude, its visible colours, and to obtain its visible
spectrum. The observations performed are shown in Table 2. Based on these
observational data, we were able to constrain its size and estimate its
composition. In addition, we were able to predict reliably its dynamical
evolution in the time interval ($-$47, +142) yr. This paper is organized as
follows. In Section 2, we present the observations of 2023 DZ2 and the methods
used for its detection. The dynamical evolution is discussed in Section 3. In
Section 4, we present the photometric observations and the spin properties.
The results of the analysis of the spectro-photometric data and the spectra
are shown in Section 5. The discussion and the conclusions are shown in
Section 6. Additional data obtained within the framework of our professional
and amateur astronomers collaboration (the so-called ProAm) are discussed in
Appendix A.

##  2 The detection of 2023 DZ2

The traditional way of finding new NEAs in CCD frames is the blinking
detection technique. It begins with sequences of a few consecutive images of
the same area of the sky, acquired with the same exposure parameters (exposure
time, gain, etc.) during several tens of minutes. The raw images are processed
and aligned using the stars in the field, so that any moving source (asteroid)
appears to shift within the acquired image sequence. Assuming a linear motion
in the short time interval covered by the observations, most of the noise can
be identified and rejected, then the targets are validated, and their
measurements reported to the MPC. In the early days of NEA surveys, a human
operator manually performed most of these tasks. A popular representative
example implementation of this technique, often applied two decades ago,
involved the use of the Astrometrica
software.111111http://www.astrometrica.at/ With the advent of the all-sky
surveys dedicated to the discovery of SSOs, more advanced detection software
packages were developed (Denneau et al. 2013).

Even the largest telescopes available cannot detect fainter and faster
asteroids (as it is the case with most NEAs) through the blink method, due to
atmospheric effects, mostly air glow (skyglow, light pollution, etc) and
dispersion, and detector limitations. If a known object is invisible in the
individual images, it is still possible to recover it through a technique
called track-and-stack. In this case, multiple exposures are taken, which are
shifted based on the predicted direction and speed of the target, then stacked
to improve the signal to noise ratio, allowing the object to be detected with
certainty in the co-added image. This technique makes sense for cases where
the telescope does not support tracking an object itself (non-sidereal
tracking) or when the trajectory is known only after acquiring the exposures.
Otherwise, it is possible to just track according to the SSO apparent motion
and then take a long exposure.

There is a natural extension of this method to the detection of unknown SSOs
called Synthetic Tracking (also known as Digital Tracking). It was used to
search for very faint Kuiper belt objects (KBOs) and trans-Neptunian objects
(TNOs) which move very slowly (Cochran et al. 1995; Gladman & Kavelaars 1997;
Gladman et al. 1998). As suggested by its name, this method applies track-and-
stack to ”synthetic” motion vectors, typically all plausible motion vectors,
while scanning for detections. However, practical synthetic tracking
algorithms operate differently from track-and-stack — the detection algorithm
performs the stacking and it must identify automatically the unknown object,
since the number of resulting stacked images is impossible to analyze in
practical time by human validators.

The key factor for all these techniques is the time needed for the data
reduction, because the small close-approaching NEAs are only observable (at
apparent magnitudes accessible with ground-based telescopes) for very short
time intervals. While modern instruments cover larger fields of view (already
of the order of several square degrees) with fainter magnitude limits, the
effort needed to reduce the amount of data collected becomes prohibitive for
small research groups or amateurs. Thus, fast and accurate algorithms are
required for complementing the ongoing robotic all-sky surveys carried out by
large research consortia (e.g. Pan-STARRS, CSS, ATLAS, ZTF). One successful
example of such a software application is Tycho
Tracker121212https://www.tycho-tracker.com/ that is used by both amateur and
professional astronomers. This software provides an easy-to-use interface
which facilitates the detection and measurement of asteroids, comets, and
variable stars. It also supports the synthetic tracking technique.
Nevertheless, the integration of this software in an automatic data reduction
pipeline is not straightforward, and the computation power required to search
for fast moving NEAs in a large field of view increases exponentially.

Within the EURONEAR collaboration, we started the development of STU
(Synthetic Tracking on Umbrella), a synthetic tracking pipeline that aims to
run in ”near-real time” with the observations. It is a new addition to the
Umbrella software suite (Stănescu & Văduvescu 2021) and it uses OpenCL to tap
into the power of modern GPUs. As a pipeline, STU begins with image
conditioning tasks, such as star masking (median stacking and star
detection/mask generation through Umbrella2, handled on the CPU, masking the
original images through OpenCL on the GPU). This is followed by re-projecting
the input images into a common gnomonic projection chart (so that asteroids
move, to first approximation, in straight lines in X-Y coordinates), directly
on the GPU (Stănescu et al. 2023).

The data cube is then processed in ”scan stage”, which is the actual GPU-based
search. The search algorithm, applies a combination of threshold counting
(Yanagisawa et al. 2021) that is a generalization of thresholding the median
value that is very robust against false positives, with the more common
addition described by Whidden et al. (2019) for refining the results (since
computing the median is expensive, and threshold counting does not provide
additional information for bright targets).

Table 3: Observational circumstances for the detection of 2023 DZ2.

Field name | Date | UT start | UT end | Nexp | AM | Seeing
---|---|---|---|---|---|---
n1o1 | 27-Feb-2023 | 22:21 | 23:31 | 12 | 1.02 | 1.5
E309252 | 28-Feb-2023 | 22:14 | 22:28 | 12 | 1.01 | 1
E309252 | 01-Mar-2023 | 22:46 | 22:00 | 12 | 1.02 | 1.1
131313The date and Universal Time (UT) for the beginning and for the end of
the observing set, the number of exposures (NExp), the mid-observation airmass
(AM), and the median seeing (Seeing) in arcseconds are shown.

Thus, we first detected 2023 DZ2 (Vaduvescu et al. 2023) thanks to the real-
time processing using the software tools and infrastructure of the Romanian
ParaSOL project.141414https://planet.astro.ro/ParaSOL/ Table 3 summarizes the
observing log. The objective of the observing run was to prove the near-real
time capabilities of the developed software, including both STU, the sensor
correction and plate solving pipeline. Nevertheless, this serendipitous
discovery was made within the framework of our observing campaigns whose aim
is finding new asteroids and comets (NEAs, Atiras and Vatiras). The observing
strategy was designed to cover the sky regions where it is more likely to
detect unknown NEAs (by exploring ranges of ecliptic longitude neglected by
the main surveys).

Figure 1: The “re-scaled mean” combined images used to detect 2023 DZ2 by the
STU algorithm. Three subsets of four images each were stacked for detecting
this new object.

The detection was found in CCD3 (Fig. 1) of the Wide Field Camera (WFC)
mounted at the prime focus of the INT, an optical mosaic imaging instrument
made of four charge-coupled devices (CCDs). They cover 0.27 square degrees
arranged in a 34$\times$34 arcmin2 L-shape design with about 17–22 arcsec gaps
between CCDs. The object was identified at an apparent magnitude of 20.3 (in
the $G$ band), and it was validated in all stacked images (using the mean,
median, trimmed mean, and masked trimmed mean methods) generated as output
(Stănescu et al. 2023).

For the new detection corresponding to 2023 DZ2, STU reported an average rate
of apparent motion on sky of 0.7326 arcsec min-1 ($-$0.777 arcsec min-1 in RA,
0.066 arcsec min-1 in DEC, on coordinate motion) for an average position angle
of 274$\aas@@fstack{\circ}$6\. The object was also independently detected
using the Tycho tracker software by one of our ParaSOL collaborators. In order
to confirm it, we performed a final check of the images using the Astrometrica
software 151515http://www.astrometrica.at/ (the object was detectable in the
single exposures). The future releases of our STU pipeline will focus on
achieving and proving the real-time candidate validation and reporting
capabilities of the software developed within the ParaSOL project. Although in
this case only 12 images were obtained during each observing night, the
synthetic tracking algorithm allowed us to detect the object automatically in
near-real time.

##  3 Dynamics

Asteroid 2023 DZ2 has a Minimum Orbit Intersection Distance (MOID) with Earth
of 0.00005 au, one of the lowest known among NEAs. This means that the
intersection point between its orbit and the invariable plane is very close to
the path of the Earth–Moon system and that encounters at 1.17 Earth radii are
theoretically possible in absence of protective mechanisms such as mean-motion
or secular resonances. The nominal evolution of the orbit of 2023 DZ2 as
predicted by JPL’s Horizons online Solar System data and ephemeris computation
service,161616https://ssd.jpl.nasa.gov/horizons/ is shown in Fig. 2, left
panels. The orbital evolution shows multiple discontinuities linked to past
and future close encounters of 2023 DZ2 with the Earth–Moon system.

Table 1 shows that the perihelion of 2023 DZ2 takes place in close proximity
to Earth’s orbit, while its aphelion occurs close to the core region of the
main asteroid belt. Its semimajor axis at 2.15 au is in the region associated
with the so-called $\nu$6 secular resonance in which the value of the
longitude of perihelion ($\varpi=\Omega+\omega$, see e.g. Murray & Dermott
1999) of a minor body relative to that of Saturn oscillates about 0° or 180°
(see e.g. Froeschle & Scholl 1989; Morbidelli & Henrard 1991). This is the
secular apsidal resonance with Saturn. Figure 2, central panels shows the
nominal evolution of the critical angle associated with the apsidal resonances
of 2023 DZ2 with Venus, Earth, Mars, Mercury, Jupiter, and Saturn. While 2023
DZ2 is not currently subjected to the $\nu$6 secular resonance, it appears to
have been subjected to the $\nu$5 secular resonance with Jupiter in the recent
past. As the associated critical angle librated about 180° (see Fig. 3), 2023
DZ2 reached aphelion when Jupiter was at perihelion. This explains why the
MOID of 2023 DZ2 with Jupiter amounts to 1.636 au. On the other hand, Fig. 2,
right panels, reveals that 2023 DZ2 is in nearly nodal resonance with Earth as
the ascending node of this small body is in the path of our planet.

In summary, the dynamics of 2023 DZ2 is controlled by Earth and Jupiter, with
Earth currently being a direct perturber as a result of the near nodal
resonance and Jupiter playing the role of secular perturber that projected a
near apsidal resonance on 2023 DZ2. The fact that this object is not subjected
to the $\nu$6 secular resonance could explain why its MOID with Earth is so
small yet its probability of impact in the near future is zero. We may argue
that NEA 2023 DZ2 was somewhat protected against collision with Earth by a
near $\nu$5 secular resonance. The data discussed above were retrieved from
JPL’s Small-Body Database
(SBDB),171717https://ssd.jpl.nasa.gov/tools/sbdb_lookup.html#/ which is
provided by the Solar System Dynamics Group (SSDG, Giorgini 2011,
2015),181818https://ssd.jpl.nasa.gov/ and Horizons using tools provided by the
Python package Astroquery (Ginsburg et al. 2019) and its HorizonsClass
class.191919https://astroquery.readthedocs.io/en/latest/jplhorizons/jplhorizons.html

Figure 2: Relevant dynamical evolution of 2023 DZ2. Left panels: Short-term
orbital evolution of 2023 DZ2: $a$, semimajor axis (top panel), $e$,
eccentricity (second to top panel), $i$, inclination (central panel),
$\Omega$, longitude of the ascending node (second panel from bottom), and
$\omega$, argument of perihelion (bottom panel). Central panels: longitude of
perihelion of 2023 DZ2, $\varpi=\Omega+\omega$, relative to that of Venus
($\varpi_{2}$, top panel), Earth ($\varpi_{3}$,second to top panel), Mars
($\varpi_{4}$, central panel), Jupiter ($\varpi_{5}$, second panel from
bottom), and Saturn ($\varpi_{6}$, bottom panel). An apsidal secular resonance
leads to the libration of the angle $\varpi-\varpi_{i}$ about a constant value
(0° or 180°). Right panels: Longitude of the ascending node relative to that
of Venus ($\Omega_{2}$, top panel), Earth ($\Omega_{3}$,second to top panel),
Mars ($\Omega_{4}$, central panel), Jupiter ($\Omega_{5}$, second panel from
bottom), and Saturn ($\Omega_{6}$, bottom panel). A nodal secular resonance
occurs when the angle $\Omega-\Omega_{i}$ librates about a constant value. The
evolution shown here is based on the nominal orbit in Table 1 and the output
cadence is 15 d. Data source: JPL’s Horizons.  Figure 3: Eccentricity versus
$\varpi-\varpi_{5}$ for 2023 DZ2.

The analysis above is telling us nothing about the role of the uncertainties
on the computed evolution of this NEA but relatively large uncertainties
coupled with recurrent encounters at close range may severely hamper our
ability to explore the orbital evolution of this object beyond a few decades
from the current epoch (see e.g. Valsecchi et al. 2003). In order to
investigate the role of the uncertainties on the reconstruction of the past
evolution of this NEA and on the prediction of its future behaviour, we have
performed $N$-body simulations using a direct $N$-body code developed by
Aarseth (2003) that implements the Hermite integration scheme formulated by
Makino (1991). The code is publicly available from the website of the
Institute of Astronomy of the University of
Cambridge.202020http://www.ast.cam.ac.uk/ sverre/web/pages/nbody.htm Relevant
results from this code were discussed in detail by de la Fuente Marcos & de la
Fuente Marcos (2012) that also includes many technical details.

Figure 4 shows our results for the orbital evolution of the nominal orbit of
2023 DZ2 in the time interval ($-$10,000, 10,000) yr around the standard epoch
JD 2460000.5 (25-Feb-2023) TDB that is the origin of times in the figure. The
enhanced probability of encounters at close range is connected to the fact
that the nodal distances experience an oscillation that periodically places
the nodes of 2023 DZ2 in the path of Earth (Fig. 4, bottom panel). On the
other hand, the value of the Kozai–Lidov parameter (Fig. 4, second to top
panel) does not experience obvious oscillations and we can discard that 2023
DZ2 could be subjected to a von Zeipel-Lidov-Kozai secular resonance(von
Zeipel 1910; Lidov 1962; Kozai 1962; Ito & Ohtsuka 2019). Figure 5 shows the
short-term evolution of control orbits with initial conditions separated from
those of the nominal orbit. From the calculations, we find that predicting the
future evolution of this NEA becomes difficult after 12-April-2165, when 2023
DZ2 will experience another encounter with Earth, this time at 0.01 au.
Investigating its orbital past is also challenging because a relatively
distant encounter with Jupiter on 17-March-1976 placed the object in its
present trajectory. Between these two dates, all the control orbits up to
$\pm$9$\sigma$ from the nominal solution provide a consistent picture of the
orbital evolution of this NEA.

Figure 4: Evolution over time of the values of the orbital elements and other
relevant parameters for the nominal orbit of 2023 DZ2 as in Table 1. The top
panel shows the evolution of the geocentric distance; the value of the Hill
radius of the Earth, 0.0098 au, is plotted as reference. The second to top
panel focuses on the evolution of the value of the Kozai–Lidov parameter. The
following four panels show respectively the evolution of the values of
semimajor axis, eccentricity, inclination, and argument of perihelion of the
nominal orbit. the panel at the bottom displays the distances from the
descending (thick line) and ascending nodes (dotted line) to the Sun; Earth’s
aphelion and perihelion distances are shown as well in red. The output time-
step size is 0.1 yr. The source of the input data is JPL’s SBDB. The standard
epoch JD 2460000.5 (25-Feb-2023) TDB that is the origin of times.  Figure 5:
Evolution of the values of the semimajor axis ($a$, top panel), eccentricity
($e$, second to top panel), inclination ($i$, third to bottom panel),
ascending node ($\Omega$, second to bottom panel), and argument of perihelion
($\omega$, bottom panel) of 2023 DZ2. The panels display results of
integrations for the nominal orbit (in black) and those of control orbits with
Cartesian vectors separated $\pm$3$\sigma$ (in light green, $-$3$\sigma$, and
green, 3$\sigma$), $\pm$6$\sigma$ (in cyan, $-$6$\sigma$, and blue,
6$\sigma$), and $\pm$9$\sigma$ (in pink, $-$9$\sigma$, and red, 9$\sigma$).
The output time-step size is 4.383 h. The source of the input data is JPL’s
SBDB and they are referred to the standard epoch JD 2460000.5 (25-Feb-2023)
TDB that is the origin of times.

So far we have included the uncertainties by assuming that they are
uncorrelated. This is a valid assumption when the orbit determination is
robust, based on a large number of high-quality observations spanning a long
time interval. This is however not the case for 2023 DZ2. In order to account
for any correlations present in the data, we carried out additional
integrations backward and forward in time using initial conditions
corresponding to control or clone orbits produced by the Monte Carlo using the
Covariance Matrix (MCCM) approach described by de la Fuente Marcos & de la
Fuente Marcos (2015). These synthetic orbits are based on the nominal orbit
determination (see Table 1) with random noise added on each orbital element by
making use of the covariance matrix. The covariance matrix was retrieved from
JPL’s SSDG SBDB using the Python package Astroquery and its
SBDBClass212121https://astroquery.readthedocs.io/en/latest/jplsbdb/jplsbdb.html
class, and it is referred to epoch 2460023.5 (20-Mar-2023) TDB that is the
origin of times for the new calculations. The MCCM methodology was used to
generate initial positions and velocities for 103 control orbits that were
evolved dynamically using the direct $N$-body code.

Figure 6: Evolution of the values of the semimajor axis ($a$, top panel),
eccentricity ($e$, second to top panel), inclination ($i$, third to bottom
panel), ascending node ($\Omega$, second to bottom panel), and argument of
perihelion ($\omega$, bottom panel) of 2023 DZ2 according to the MCCM
approach. The panels display results of the integrations of 103 control orbits
with initial positions and velocities generated using the MCCM methodology. In
black, we display the average evolution of the orbital element and in red we
show the range linked to the 1-$\sigma$ uncertainty or the 16th and 84th
percentiles. The output time-step size is 0.1 yr. The source of the input data
is JPL’s SBDB and they are referred to epoch 2460023.5 (20-Mar-2023) TDB that
is the origin of times.

Figure 6 shows the result of the past and future evolution of 2023 DZ2
according to the MCCM approach. In black, we display the average evolution and
in red we show the range linked to the 1-$\sigma$ uncertainty or the 16th and
84th percentiles. While the uncertainty in the reconstruction of the past
orbital evolution of this NEA is large beyond 100 yr into the past, the one
associated with predictions of its future orbital behaviour is far smaller.
This is the result of particularly close encounters with the Earth–Moon system
when the orbital inclination of 2023 DZ2 became virtually zero, over one
century ago. Therefore, its current orbit determination is not robust enough
to investigate its origin and how this object was inserted in NEA orbital
parameter space. More observations are needed to produce a better orbit
determination for such a study. On the other hand, our results based on the
covariance matrix are quite consistent with those obtained assuming
uncorrelated uncertainties.

##  4 Time-series photometry

Photometric data were obtained during three consecutive nights at the
”Telescopios Gemelos de Dos Metros” (Two Meter Twin Telescopes — TTT)
facility. This is located located at the Teide Observatory (latitude: 28° 18’
01.8” N; longitude: +16° 30’ 39.2” W, and an altitude of 2386.75 m), in the
island of Tenerife (Canary Islands, Spain). Currently, it includes two
telescopes (called TTT1 and TTT2) with an aperture of 0.80 m, installed on
altazimuth mounts, and with focal ratios of f/4.4 and f/6.8, respectively.

The observations were made using the QHY411M222222https://www.qhyccd.com/
cameras (Alarcon et al. 2023) installed on one of the Nasmyth ports of each
telescope. They are equipped with sCMOS (scientific Complementary
Metal–Oxide–Semiconductor) image sensors consisting in 151 megapixels with a
pixel size of 3.76 $\mu$m pixel-1. This provides an effective FoV of
51.4${}^{\prime}\times$38.3′ (with an angular resolution of 0.22” pixel-1) in
TTT1 and 33.1’$\times$24.7’ (angular resolution of 0.14” pixel-1) in TTT2. In
all the observing runs a band-pass filter (the band covers the 0.4 to 0.7
$\mu$m wavelength interval) was used. The exposure time was dynamically set
between 10 and 20 s to ensure a signal to noise ratio (SNR) larger than 50. A
total of five observing runs were performed, one with TTT2 on March 20 and two
simultaneous runs with each telescope on the nights of March 21 and 22. Table
2 shows the effective coverage time for each night.

The images were bias and sky flat-field corrected. Then, they were trimmed and
binned 2$\times$2\. Aperture photometry was performed using Tycho Tracker
software. The images were aligned with bicubic interpolation and down sampled
by a factor 2 for astrometric calibration which was performed with
Astrometry.net (Lang et al. 2010).

To obtain the photometry of the object, a fixed aperture of 2$\times$FWHM
(Full Width at Half Maximum of the point spread function of stars) in the
first image of each set was used. An outer ring with the inner radius located
at 4$\times$FWHM was used to estimate the sky background signal. The same
apertures were used for the comparison stars, selected constraining
$0.60<(B-V)<0.70$. The initial and final positions of the asteroid were marked
manually in the images in order to prevent any miss-identification by the
algorithm.

Figure 7: Phased light curve of 2023 DZ2 computed from photometric
measurements obtained by the TTT1-2 telescopes. The rotation period and
amplitude of the curve are shown at the lower left corner of the top panel.
The total coverage is 9.8 h, distributed over three consecutive nights.
Residuals are shown in the bottom panel.

Photometric measurements were extracted and corrected for distance and
light–time. The five–term Lomb-Scargle periodogram was obtained, with a well-
marked peak in the power spectrum centred at a period of $P_{\rm
rot}=6.2743\pm 0.0005$ min and its aliases. As uncertainty, 1–$\sigma$ of the
Gaussian curve fitted to the exponentiated power peak was taken (VanderPlas
2018). The phased light curve is shown in Figure 7. The amplitude of the curve
obtained, considering photometric errors, is $0.57\pm 0.14$ mag.

The initial observations performed with TTT1 and TTT2 show a super-fast
rotator asteroid (Licandro et al. 2023a). The $P_{\rm rot}=6.274$ min is
indicative of intrinsic strength to resist centrifugal disruption, otherwise
2023 DZ2 would break apart (Pravec & Harris 2000). It could be a coherent body
or monolith (e.g. Monteiro et al. 2020; Sánchez & Scheeres 2014). The data
existing in Asteroid Lightcurve Database (LCDB, Warner et al.
2009),232323https://minplanobs.org/mpinfo/php/lcdb.php updated on February
2023 shows that no faster rotator correspond to a low (i.e. $\leq 0.10$)
albedo asteroid (Licandro et al. 2023b). Thus, at first glance, the period
determination adds a strong constraint on the cohesive strength of the
asteroid and it is a strong indicative of a high albedo asteroid.

The hypothesis of a high albedo object is supported by the spin limit for
small asteroids (Monteiro et al. 2020; Rondón et al. 2020). At an absolute
magnitude $H\approx 24$ mag and an albedo of $p_{V}\leq 0.1$, this asteroid
will have a size larger than 60 m which for a rotation period of $P_{\rm
rot}=6.2743\pm 0.0005$ min is outside the spin barrier determined by (Rondón
et al. 2020) for C-type asteroids.

The three peaks of the light curve show an irregular shape which favours the
hypothesis of a monolithic body. This result was confirmed by observations
performed on March 25 with the Goldstone Radar. The preliminary result
reported on their
webpage242424https://echo.jpl.nasa.gov/asteroids/2023DZ2/2023DZ2.2023.goldstone.planning.html
shows that “at some orientations the shape looks somewhat triangular; at
others it looks rounded; there is a flat area, and a small-scale topographic
feature that appears on the leading edge”.

##  5 Spectro-photometry and spectroscopy

The spectro-photometric (photometric observations performed with various
broad-band filters) and the spectral observations represent the best ground-
based observing techniques to constrain the composition properties of small
objects. The spectro-photometric method is more suitable for characterizing
fainter objects since the incoming flux is collected in each bandpass and not
dispersed as in the case of spectral observations. The faintest targets, which
cannot be spectroscopically observed with any other telescope can, be
taxonomically classified using this technique. The disadvantage is the
impossibility of making a distinction between different sub-types of the same
taxonomic complex. This is because a colour is just the normalized difference
in the amount of reflected light-flux between the wavelength ranges covered by
a broad band filter, while the specific features may cover a short spectral
interval. Thus, the spectro-photometry is the first approximation of the
spectral properties.

We were able to acquire spectro-photometric data for 2023 DZ2 on the night
22-March-2023 using the Telescopio Carlos Sánchez (TCS) from Teide
Observatory. Although these observations were performed after we acquired
spectra using the GTC telescope it is worth to mention them as the first
approach to infer the taxonomic classification, in order to highlight the
strength of this technique for fainter asteroids.

The observations were performed with the MuSCAT2 (the acronym is derived from
“a multicolour simultaneous camera for studying atmospheres of transiting
exoplanets”) imaging instrument (Narita et al. 2019) which is mounted on the
Cassegrain focus of the TCS. This configuration allows us to perform
simultaneous photometric observations in four visible broad-band filters,
namely g (400 - 550), r (550 - 700), i (700 - 820) and zs (820 - 920) nm. At
the end of each of the four channels there is an independently controllable
CCD camera (1024$\times$1024 pixels), having a pixel size of $\sim$0.44”
pixel-1 and a FoV of $7.4^{\prime}\leavevmode\nobreak\
\times\leavevmode\nobreak\ 7.4^{\prime}$.

Figure 8: The (g-r) vs. (r-i) vs. (i-zs) colour-colour diagrams of the 155
objects with known spectral classification, used to classify 2023 DZ2 based on
the TCS/MusSCAT2 data. The taxonomic types defined in DeMeo et al. (2009)
system have been divided in three major composition groups, namely the Q /
S-complex (green and blue dots), C-complex (black dots) and X-complex (grey
dots). Besides them, three end-member types are considered, A-, D- and V-type.

In order to obtain the light-curves and the colours, we used the
PHOTOMETRYPIPELINE – PP (Mommert 2017). This is a software package written in
Python which obtains calibrated photometry from the FITS images by performing
the astrometric registration, aperture photometry, photometric calibration,
and asteroid identification. PP is written in Python and uses the _Astromatic_
suite252525https://www.astromatic.net/, namely SExtractor for source
identification and aperture photometry (Bertin & Arnouts 1996), SCAMP for
astrometric calibration (Bertin 2006), and SWarp for image re-gridding and co-
addition (Bertin et al. 2002). It also uses JPL’s Horizons module for
obtaining the SSOs ephemeris in order to identify them in the images.

For astrometric registration, we used the GAIA DR2 catalog (Gaia Collaboration
et al. 2018). In order to improve the accuracy, we applied the registration
algorithm twice for each image. We discarded all those images for which the
astrometric registration failed. The Pan-STARRS catalog (Tonry et al. 2012)
was used for all photometric calibrations. The accuracy of these calibrations
is dependent on the number of stars imaged by each exposure (19 to 40 stars
were used for the photometric calibration of each image).

PP uses aperture photometry performed by SExtractor. We applied the PP
algorithm that finds the optimum aperture radius based on a curve-of-growth
analysis (Howell 2000; Mommert 2017). From each set of four simultaneous
images, we computed the $(g-r)$, $(r-i)$, and $(i-z_{s})$ colours. The
reported values of the colours represent the median of data obtained during
four hours of observations.

We used these colour values to infer the taxonomic classification. Thiswas
carried out in a robust way with the K-Nearest neighbours (KNN) and Random
Forest (RF) algorithms. These were implemented using the Python package
SCIKIT-LEARN. The KNN algorithm classifies an object based on the label values
or taxonomy of its neighbours in the colour-colour diagram, while the RF
algorithm assigns the final label to an object using decision-tree structures.

Both algorithms require a training set which includes objects for which we
know both the photometric colours (from our data set) and spectral data (from
the literature). To generate it we searched the available spectral information
of all the objects with TCS colours in the SMASS-MIT-Hawaii Near-Earth Object
Spectroscopic Survey (MITHNEOS MIT-Hawaii Near-Earth Object Spectroscopic
Survey) program (Binzel et al. 2019) and the Modeling for Asteroids (M4AST)
database (Popescu et al. 2012). We retrieved spectral classifications for 84
of the NEAS observed as well by our TCS/MuSCAT2 program (Popescu et al. 2021).
To increase the training sample, we computed the synthetic colours using the
visible spectra published by Popescu et al. (2019) and Perna et al. (2018).
The final training sample consisted of 154 asteroids classified as 5 A-type, 8
V-type , 34 Q-types and 48 S-complex, 7 B-types, 15 C-complex, 9 D-types, and
28 X-complex.

In order to account for magnitude errors determined on each of the broad-band
filters, we applied a Monte-Carlo approach. We started from the colour value
and its error and generated three normal distributions (one for each colour)
of 10 000 fictitious colour values. Then, for each of these cases we
classified the object. Finally, the assigned taxonomy was the one with the
highest frequency. Based on the colour values of $(g-r)=0.555\pm 0.055$ mag,
$(r-i)=0.154\pm 0.055$ mag, and $(i-z_{s})=0.064\pm 0.059$ mag both algorithms
classify this object as an X-complex member with 100% probability (this
probability indicates that all the clones generated within the Monte-Carlo
approach were classified as X-complex objects).

The most powerful technique used to characterize this object was spectroscopy.
The visible spectra of 2023 DZ2 were obtained on two separate nights: one on
the night of 17-March-2023, and another one on the night of 20-March-2023,
using the OSIRIS camera-spectrograph (Cepa et al. 2000; Cepa 2010) at the 10.4
m GTC, under the program GTC31-23A. The telescope is located at the El Roque
de Los Muchachos Observatory, in the island of La Palma (Canary Islands,
Spain).

The OSIRIS instrument (upgraded in January 2023) was employed on both nights.
We used the 1.2” slit and the R300R grism (resolution $R$=348 for a 0.6” slit,
dispersion of 7.74 Å pixel-1) covering the 0.48–0.92 $\mu$m wavelength range.
The slit was oriented along the parallactic angle to minimize the effects of
atmospheric differential refraction and the telescope tracking was set at the
asteroid proper motion. Details of the observational circumstances are shown
in Table 2. Two spectra of 300 s of exposure time each were obtained, with an
offset of 10” in the slit direction in between them. To obtain the asteroid
reflectance spectrum, we observed two solar analogue stars from the Landolt
catalogue (Landolt 1992), SA98-978 and SA102-1081 at a similar airmass as that
of the asteroid.

Data reduction was completed using standard procedures. The images were bias
and flat-field corrected. Sky background was subtracted and a one-dimensional
spectrum was extracted using a variable aperture, corresponding to the pixel
where the intensity was 10% of the peak value. Wavelength calibration was
carried out using Xe+Ne+HgAr lamps. This procedure was applied to the spectra
of the asteroid and the stars. We then divided the asteroid’s individual
spectra by the spectra of the solar analogues, and the resulting ratios were
averaged to obtain the final reflectance spectrum of 2023 DZ2.

The spectrum obtained on the night of 17-March-2023 is shown in Fig. 9 in dark
blue, together with the error bars associated to the standard deviation of the
average. The spectrum obtained on the night of March 20, when the asteroid was
one apparent magnitude brighter, is shown in the same figure in orange. The
agreement between the two spectra is perfect. Finally, the obtained spectra
were used to classify 2023 DZ2 taxonomically. We did so using the M4AST online
tool.262626http://spectre.imcce.fr/m4ast/index.php/index/home The tool fits a
curve to the data and compares it to the taxons defined by DeMeo et al. (2009)
using a $\chi^{2}$ fitting procedure. The best three results are provided in
order of decreasing goodness of fit. For the case of 2023 DZ2, the best three
fits are T, D, and Xe (see hatched region in Fig. 9).

Figure 9: Visible spectra of asteroid 2023 DZ2 obtained with the 10.4 m Gran
Telescopio Canarias (GTC) on the night of 17-March-2023 (dark blue) and on the
night of 20-March-2023 (orange). Error bars correspond to the standard
deviation of the mean for the March 17 data. The error bars for the March 20
data are much smaller and are contained within the larger ones. The grey
hatched region accounts for the three best taxonomic fits, in order of
increasing $\chi^{2}$: T, D, and Xe-types.

The T-types are defined by a linear spectrum with moderate to high slope at
wavelengths bellow 0.75 $\mu$m by both Bus & Binzel (2002) and DeMeo et al.
(2009) taxonomies. Their spectral curves are within the range of D-types and
X-complex asteroids (it is comparable with the reddest X-types and with the
least red D-types). For this reason, we did not include this spectral type
among the classes used for spectro-photometric classification. The matching
between the spectral data and the spectro-photometry covers the $r$, $i$, and
$z_{s}$ bands (see Fig. 10).

There is a slight discrepancy (at the level of 2-$\sigma_{g}$, where
$\sigma_{g}$ is the standard deviation of the observations performed in the
$g$ filter). There are several factors which can contribute to it, 1) the $g$
band covers the (0.4, 0.55) $\mu$m spectral interval, while the spectrum stops
at 0.48 $\mu$m; 2) the common wavelength range between 0.48 and 0.55 $\mu$m
falls on the outermost boundary of the spectroscopic setup coverage, making it
more susceptible to potential unaccounted errors in the slope; 3) errors that
have not been taken into account could arise either from the photometric
calibration or from the spectral data, such as issues similar to those
reported by Marsset et al. (2020) (although they refer to the near-infrared).
With the existing data we cannot distinguish between these possibilities.

##  6 Discussions and Conclusions

In the previous sections, we have presented a comprehensive analysis of
ground-based observations of a close-approaching NEA, namely 2023 DZ2. All
these analyses would provide critical information for making decisions on
mitigating strategies regarding a hypothetical impact (either on impact
avoidance or damage limitation) should this NEA had any real impact risk.

Our discovery of 2023 DZ2 (initially classified as VI) with WFC mounted on
INT, highlights the importance of continuous monitoring of the sky and of the
need to process the data in near-real time. We showed that our ParaSOL
infrastructure and the use of a synthetic tracking algorithm allowed us to
process the large amount of data obtained and to report our findings in near-
real time so the community could start contributing additional observation of
the object of interest as early as possible.

Once a potential impactor has been identified, it becomes critical to follow
it up in order to improve its orbital determination and to obtain its physical
properties, such as size, shape, composition, and structure. The estimation of
size requires the knowledge of the absolute magnitude and the albedo (Harris &
Harris 1997). The preliminary value of $H$ can be inferred from the apparent
magnitude reported together with the astrometric measurements, after the orbit
is computed. Nevertheless, this is a rough guess. The main source of the
absolute magnitude errors is the irregular shape of the asteroids which
generates light curves with amplitudes up to $\approx$2 mag, according to the
current data existing in LCDB (Warner et al. 2009).

Thus, the photometric observations are the next step in characterizing the new
NEA. In the case of 2023 DZ2, we triggered observations with the TTT
telescopes which revealed a rotation period of $P_{\rm rot}=6.2743\pm 0.0005$
min and an amplitude of 0.57$\pm$ 0.14 mag. This result uncovered a fast-
rotating object. The minimum aspect ratio for its shape was estimated from the
light curve amplitude, $a/b=1.30\pm 0.08$ (where $a$ and $b$ are the axis
perpendicular to the rotation axis). Again, this was an approximate
determination because the three peaks in the light curve outlined a body with
a complex shape. Because this is a fast rotator, this finding added a limit on
the cohesive strength of the material it is made of, and allowed to constrain
the possible solutions for size and composition.

The value of the albedo is strongly dependent on the composition of the body
(Thomas et al. 2011; Mainzer et al. 2011; Popescu et al. 2018). It may vary in
the interval of $\approx$(0.02, 0.50). In the case of 2023 DZ2 and for the
initial estimate of $H\approx$24 mag and this wide range of albedos, we can
estimate a size between 30 to 150 m. The albedo estimation can be made by
assigning a taxonomic type. The most readily available technique for taxonomic
classification is spectro-photometry, even if the obtained result is not as
precise as the one obtained from spectroscopy. The observational results
obtained with TCS allowed us to classify 2023 DZ2 as an X-complex asteroid,
the colour values $(g-r)=0.555\pm 0.055$ mag, $(r-i)=0.1542\pm 0.055$ mag, and
$(i-z_{s})=0.0638\pm 0.059$ mag, place this object well inside the X-complex
locus in the colour-colour diagram.

Unfortunately, the tentative classification as an X-complex type NEA does not
constrain the albedo (this approach would have been successful for all the
other classes). The X-complex includes both low and high albedo asteroids,
with moderate spectral slope and featureless spectra, including various
compositions similar to the carbonaceous, metallic and enstatite chondrites
(Fornasier et al. 2011). In the classification scheme of Tholen (1984), the
X-complex was divided in P – primitives ($p_{V}\approx 0.05$), M – metallics
($p_{V}\approx 0.015$), and E – enstatites ($p_{V}\approx 0.42$) classes.

With this information, there are several hints regarding the nature of 2023
DZ2. Because it is a fast rotator, we show that it is highly unlikely to have
a carbonaceous-like composition that corresponds to a dark albedo (Licandro et
al. 2023a). This consideration reduced the possible interval for its size to
the range of 33 to 55 m (assuming an albedo of 0.42, and 0.15 respectively).
Accurate spectra can confirm this classification and eventually reveal subtle
features that may allow to discern its actual composition.

Figure 10: Comparison between the spectra of 2023 DZ2 obtained with GTC and
the spectro-photometric data obtained with TCS. In order to convert the TCS
data, we used the following colours of the Sun, $(g-r)^{Sun}$ = 0.50 mag,
$(r-i)^{Sun}$ = 0.10 mag, $(i-z_{s})^{Sun}$ = 0.03 mag. These values (Popescu
et al., in preparation) were derived for the filters available for the MuSCAT2
instrument and are consistent with those provided by Holmberg et al. (2006).

However and in order to obtain the visible spectrum one must take into account
that a 2.5 m class telescope is required for asteroids as faint as $V$ = 18.5
mag (e.g. Popescu et al. 2019), a 4 m class telescope is needed for objects as
faint as $V$ = 20.5 mag (e.g. Perna et al. 2018), and a 10 m class one, such
as GTC — the largest optical single mirror telescope currently available — is
required for bodies of $V\approx$ 22 mag (e.g. de la Fuente Marcos et al.
2023). Within our effort to characterize 2023 DZ2, we used the 10.4 m GTC
telescope during the nights of March 17 and March 20 to obtain spectra over
the 0.46–0.92 ${\mu}$m spectral range. The observations were performed when
the object had respective apparent $V$ magnitudes of 19 and 18. The two
spectral curves are identical and show a featureless spectrum with a moderate
slope. The agreement between them and the spectro-photometric observations is
shown in Fig. 10.

In this paper, we have described the first critical steps required to mitigate
the threat of a potential impactor. We first detected 2023 DZ2 using a near-
real time processing algorithm, within the context of a limited survey in a
region of the sky not covered by the large surveys. As a second step, less
than seven days after the announcement of its discovery by the Minor Planet
Center (on 16-March-2023), we were able to constrain its main physical
properties using photometric observations (acquired a few days later, during
March 20, 21, and 22), spectro-photometric (obtained on 22-March-2023) and
spectroscopic data (observations performed on March 17 and 20). Regarding the
origin of this NEA, its current orbit determination is not robust enough to
find out which asteroid population is its most likely source; however, it is
good enough to confirm that we are in no short-term danger of having a
collision with 2023 DZ2 thanks to the dynamical effects of a near secular
(apsidal) resonance with Jupiter. This circumstance illustrates the dual
nature of secular resonances, while $\nu_{6}$ might place asteroids in a
collision course with Earth and the nodal resonance with Earth favours
collisions, $\nu_{5}$ might help protecting Earth from some impacts. In the
case of the object studied here, the protective secular near resonance
effectively removes the risk connected with the nodal near resonance.

Although simulated scenarios for a potential impact were carried out during
Planetary Defense Conferences in 2021 and 2023 (Barbee et al. 2021), and they
were much more elaborated, here we confirm on a real case that key
observations can be obtained within a few days after the announcement of a
potential impact threat. This time the data collected eventually helped to
confirm that the collision probability was insignificant, next time this may
well not be the case: additional data may lead to reassuring a future impact
instead. As the adage goes, ”Time is of the essence when mitigating a cosmic
hazard”.

###### Acknowledgements.

The work of MP, OV, MS, DB, LC and MP, was supported by a grant of the
Romanian National Authority for Scientific Research – UEFISCDI, project number
PN-III-P2-2.1-PED-2021-3625. RdlFM and CdlFM thank S. J. Aarseth for providing
one of the codes used in this research and A. I. Gómez de Castro for providing
access to computing facilities. This work was partially supported by the
Spanish ‘Agencia Estatal de Investigación (Ministerio de Ciencia e
Innovación)’ under grant PID2020-116726RB-I00 /AEI/10.13039/501100011033.
Based on observations made with the Isaac Newton Telescope (INT), in the
Spanish Observatorio del Roque de los Muchachos of the Instituto de
Astrofísica de Canarias (program ID INT99-MULTIPLE-2/23A). Based on
observations made with the Gran Telescopio Canarias (GTC), installed at the
Spanish Observatorio del Roque de los Muchachos of the Instituto de
Astrofísica de Canarias, on the island of La Palma. This work is partly based
on data obtained with the instrument OSIRIS, built by a Consortium led by the
Instituto de Astrofísica de Canarias in collaboration with the Instituto de
Astronomía of the Universidad Nacional Autónoma de Mexico. OSIRIS was funded
by GRANTECAN and the National Plan of Astronomy and Astrophysics of the
Spanish Government.This paper includes observations made with the Two meter
Twin Telescope (TTT) at the IAC’s Teide Observatory that Light Bridges, SL,
operates on the Island of Tenerife, Canary Islands (Spain). The Observing Time
Rights (DTO) used for this research at the TTT have been provided by the
Instituto de Astrofísica de Canarias. The spectral and the spectro-photometric
data were obtained in the framework of the European Union’s Horizon 2020
research and innovation program under grant agreement No 870403 (NEOROCKS).
JL, JdeL, M.R-A and MP acknowledge support from the ACIISI, Consejería de
Economía, Conocimiento y Empleo del Gobierno de Canarias and the European
Regional Development Fund (ERDF) under grant with reference ProID2021010134.
In preparation of this paper, we made use of the NASA Astrophysics Data
System, the ASTRO-PH e-print server, and the MPC data server. We thank the
reviewers for their comments which helped us to improve the paper. We also
thank to Dr. Hissa Medeiros for the discussions on this topic and for the
suggested references, to Gabriel Nicolae Simon for providing the python
functions used for the spectro-photometric classification.

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##  Appendix A Pro - Am collaborations for photometric characterization

Events that require rapid response observations or long-term monitoring
campaigns of diverse celestial sources are the triggers for the collaboration
between professional and amateur astronomers who have access to highly
reliable observing
facilities272727https://www.nature.com/articles/s41550-023-01954-6. During its
close approach, 2023 DZ2 was bright enough for observations with small
aperture telescopes. Thus, the light curves obtained initially could be
followed-up by many amateur astronomers.

We received various contributions from different amateurs from all over the
world, including Amadeo Aznar, Lucian Hudin, and Cristian Suciu (Astroclubul
Bucureşti, Romania). To highlight the importance of Pro-Am collaborations, we
present here some of the most reliable light curves we received (Fig. 11) and
obtained by the Isaac Aznar Observatory (IAO) Alcublas (MPC code Z95),
Valencia province, Spain; ROASTERR-1 Observatory (MPC code L04), Cluj-Napoca,
Romania; and T025-BD4SB (MPC code 073), Bucharest, Romania (Bertesteanu et al.
2022). We choose to present here the typical plots which can be obtained using
commercially available tools such as MPOC Canopus and Tycho Tracker. With help
from these tools, experienced amateur astronomers can derive the spin
properties of asteroids.

Figure 11: Phased light curve of 2023 DZ2 computed using photometric
measurements obtained within the professional–amateurs collaboration discussed
in the text. The title of each panel highlights the observatory (including the
MPC code). The reported period and amplitude were computed by the observers
using Tycho Tracker (for _L04_ and _073_), and MPOC Canopus (for _Z95_). The
plots are made with GNU Octave software (Eaton et al. 2021), and a splinefit
function was used to fit the data. In the case of 073, a binning of nine
points was made after folding the photometric data.

Photometric observations of 2023 DZ2 were performed from the ROASTERR-1
observatory with the 0.3 m f/5 corrected Newtonian, a CCD camera with a
KAF-8300 CCD chip cooled at -15oC, and a clear filter. The calibration data
were acquired immediately after the observations and consisted of 32 bias, 32
dark, and 32 flat frames. Two sets of observations were used, made of 104
images and 138 images, respectively, with an exposure time of 10 s for each
individual image. The Tycho Tracker v10 was used for photometry. The obtained
period was 0.1038 h (6.228 min) with an amplitude of 0.526 mag as shown in
Fig. 11.

The Isaac Aznar Observatory (IAO) is privately owned by the Spanish amateur
astronomer Amadeo Aznar Macías. It is located in Alcublas, Valencia province,
at 900 m above the sea level, in one of the darkest night-sky of the Iberian
Peninsula (limiting magnitude 21.8 mag arcsec-2). The optical system consists
of a remotely controlled 0.36 m Schmidt-Cassegrain F/10 Meade LX200 telescope.
The CCD camera is a SBIG STL 11000, with 1.68 arcsec pixel-1 resolution (pixel
binned $\times$3) and a square FoV of 37$\times$24 arcmin2. The light curve of
2023 DZ2 was obtained using 274 photometric exposures from two nights (see
Fig. 11), on March 21 and 25. An exposure time of 30 s was used, and images
were acquired during $\approx$2.2 h. The data reduction was performed using
the MPO Canopus
software.282828https://minplanobs.org/BdwPub/php/displayhome.php The light
curve shows a rotation period of 0.1046 h (6.276 min) with an error of 0.0001
h and an amplitude of 0.50 mag with an error of 0.08 mag.

The T025–BD4SB robotic telescope was built as a collaboration between amateur
astronomers from the Astroclubul Bucureşti and the researchers from the
Astronomical Institute of the Romanian Academy. The main components of this
instrument are a 10 inch Newtonian telescope and a QHY 294M CMOS camera.
T025–BD4SB is mounted on the roof of the old Bucharest Astronomical Institute
building. This facility has the Minor Planet Center observatory code 073. The
detection limit is around $V$=20 mag, and the median seeing is 2.8 arcsec. The
observations of 2023 DZ2 were performed on the night of 24-March-2023 (one
night prior to the close approach between 2023 DZ2 and Earth). Continuous
exposures of 5 s each were acquired during $\approx$5 h. This short exposure
time was considered because of its high apparent motion (30–40 arcsec per min
during the observations). By using this exposure time, the trail left on the
image by the NEA matches the typical seeing from Bucharest. The data reduction
followed the same steps as those described above. The image pre-processing was
carried out using the Pyraf package.292929https://iraf-
community.github.io/pyraf.html Because of the light-pollution of Bucharest, a
sky-background removal algorithm was applied using the GNU Astronomy Utilities
(Gnuastro) package (Akhlaghi & Ichikawa 2015). The results obtained with the
T025-BD4SB, were a rotation period $P_{\rm rot}=6.2753\pm 0.005$ min and an
amplitude of 0.482 mag.

##  Appendix B Input data

Here, we include the barycentric Cartesian state vector of NEA 2023 DZ2. This
vector and its uncertainties have been used to perform the calculations
discussed above. For example, a new value of the $X$ component of the state
vector is computed as $X_{\rm c}=X+\sigma_{X}\ r$, where $r$ is an univariate
Gaussian random number, and $X$ and $\sigma_{X}$ are the mean value and its
1$\sigma$ uncertainty in Table 4.

Table 4: Barycentric Cartesian state vector of 2023 DZ2: components and
associated 1$\sigma$ uncertainties.

Component |  | value$\pm$1$\sigma$ uncertainty
---|---|---
$X$ (au) | = |  $-$9.718051175253550$\times 10^{-1}$$\pm$1.99342196$\times 10^{-8}$
$Y$ (au) | = | 5.157636594173508$\times 10^{-1}$$\pm$9.69360581$\times 10^{-9}$
$Z$ (au) | = |  $-$7.025348786300637$\times 10^{-4}$$\pm$1.18266109$\times 10^{-8}$
$V_{X}$ (au/d) | = |  $-$4.772825832549133$\times 10^{-3}$$\pm$8.13837751$\times 10^{-10}$
$V_{Y}$ (au/d) | = |  $-$1.954511508654970$\times 10^{-2}$$\pm$2.94881778$\times 10^{-10}$
$V_{Z}$ (au/d) | = | 2.660147805349922$\times 10^{-5}$$\pm$3.86774841$\times 10^{-10}$
303030Data are referred to epoch JD 2460000.5, which corresponds to 0:00 on
25-February-2023, TDB (J2000.0 ecliptic and equinox). Source: JPL’s Horizons.