Download ANTARES - National Optical Astronomy Observatory

ANTARES: Example Science Use Cases
1
Introduction
The design of the antares system is meant to be flexible enough to accommodate filters
that can distinguish almost any object of interest to time-domain astronomy, subject to the
limits of computational resource and time. We could sample from a wide variety of transient
or variable objects that could be employed for a science use case. Here we describe five use
cases that exemplify the potential capabilities of the antares system, especially in regard
to the focus of the prototype being the search for the ‘rarest of the rare.’
2
Electromagnetic Counterparts to Gravitational Wave
Sources
One of the most exciting results in modern physics is the direct detection of gravitational
waves (GWs) by interferometric systems. The Advanced Laser Interferometer GravitationalWave Observatory (aLIGO; Aasi et al., 2015) has announced two significant detections of
GW sources (Abbott et al., 2016c,a), each of which was the subject of intensive searches
for an electromagnetic (EM) counterpart, (e.g., Abbott et al., 2016b; Cowperthwaite et al.,
2016). These follow-up campaigns conducted wide-field imaging surveys of the likely regions
of the sky given the localizations as determined by aLIGO. These localizations are fairly
broad, as illustrated in Figure 1. For GW150914, the total area of the 90% credible region
for the GW source was over 600 square degrees on the sky. Only a small fraction of that
credible region was imaged to look for the EM counterpart (Abbott et al., 2016b).
With upgrades and additional LIGO facilities, the localizations should become more
feasible to search in the near future, with ∼50% of events having localizations ≤ 20 square
degrees (Abbott et al., 2016d). Moreover, the Large Synoptic Survey Telescope (LSST,
Ivezić et al., 2008; Kantor, 2014; Kahn, 2016) field-of-view is 10 square degrees, enabling
deep, wide-field coverage at a rate unprecedented today. Even so, with tens of square degrees
to search, and each LSST field of 10 square degrees having several thousand alerts, there is
still a problem in identifying the actual EM counterpart.
The first major step in the antares architecture is the association of an alert with known
astrophysical sources at the same position on the sky, as well as previous alerts, if any. For
an aLIGO alert, the expectation is that there will not be a previously detected source, but
that there will be a host galaxy. Information known about the host (distance, type, etc.)
1
Figure 1: The 90% credible region for the localization of GW150914. The colors denote
different algorithms used to determine the credible region. The total area is greater than
600 square degrees while follow-up images on the ground generally have a field-of-view of
less than one square degree. Figure from Abbott et al. (2016b).
will be annotated in the alert. Such galaxy catalogs do not exist with the completeness
necessary at this point, but LSST itself will eventually provide such a catalog.
2
There is an extensive literature predicting the optical characteristics of a GW source
such as a merger of two neutron stars, two black holes, or a black hole/neutron star system,
(e.g., Narayan et al., 1992; Nakar, 2007; Metzger & Berger, 2012; Berger, 2014; Fong et al.,
2015; Metzger, 2016). Most predictions indicate a short-lived (∼days) relatively red optical
transient. The distinguishing features will include this color information as well as constraints
inferred from the host galaxy. Visualization and evaluation of the features in relation to
each other is necessary to determine which features are most useful for singling out the
EM counterpart. Part of this distinction is eliminating known objects with some overlap in
the feature space of interest. Note that this presumes that LSST will engage in multi-filter
observations during a campaign to identify an EM counterpart, rather than the single-filter
cadence that will make up the bulk of the survey. In addition, the predicted rapid time-scale
of the EM counterpart highlights the necessity to distinguish it early so that the maximum
amount of follow-up observations will be possible.
There may not be enough information from early, limited observations, so a list of likely
alerts may be produced, rather than a single, sure thing. Tools to assess the probability
of an object’s categorization, especially when combining inferences from several techniques,
will be needed to provide realistic rankings for alerts. In addition, feedback from subsequent
observations will be useful, although that is beyond the scale of the prototype antares
system. Through a robust, dynamic, and efficient system, one can find the truly rare object
such as an aLIGO source.
3
Tidal Disruption Events
The study of stars disrupted by tidal forces as they pass near a super-massive black hole has
grown tremendously in the past decade, with several likely events directly observed (Gezari,
2012; Komossa, 2015). These tidal disruption events (TDEs) can shed light on the nature of
black holes, including accretion mechanisms and jet formation (e.g., Metzger et al., 2012).
With the number of TDEs detected so far only in the tens of objects, there are still many
mysteries yet to be solved. For example, there is an apparent preference for these events in
post-starburst galaxies (French et al., 2016), but it is not clear why that is the case.
This use case demonstrates another element of the antares architecture, namely multiwavelength association. It is likely that all galaxies contain a massive black hole at their
center, but they are only detectable by their effect on the environment around them. If
there is material actively falling into the black hole, there is direct evidence in the form of
radiation emitted from that material as it interacts with the black hole, directly or via an accretion disk. This emission can span the electromagnetic spectrum, but they are prodigious
producers of x-rays compared to other astronomical sources. This accretion of material is
3
Figure 2: Artist’s rendition of a tidal disruption event. Figure from Komossa (2015).
not continuous, leading to variation in the emission from such active nuclei, so such objects
(active galactic nuclei–AGN) would appear as alerts in the LSST data stream.
If a star moves too close to a massive black hole, the tidal forces can essentially rip it
apart, illustrated in Figure 2. These TDEs will also appear as alerts in the LSST data stream
with characteristics quite similar to AGN. The antares architecture takes each alert and,
if there is more than one possible association at the location of the alert, produces replicas
that associate the alert with all of the potential AstroObjects at that position. Often, these
associations are unrelated, as in the case of a foreground star and a distant galaxy where
the alignment is coincidental. There are cases, however, where the interaction of association,
especially across the electromagnetic spectrum, provides valuable information that can aid
in the categorization of an alert. These are called combos in the antares architecture.
Active galaxies are more common than TDEs, so most alerts that occur at the center of
a galaxy are likely to be AGN (and there are other, less common possibilities). To find the
TDEs, antares must eliminate the AGN. The use of the multiwavelength association allows
for this distinction. If there is a known source of x-rays (or other high-energy emission),
then it is likely to be an AGN, and thus removed from consideration as a TDE. Even
association with a radio source increases the likelihood that the object is an AGN. By using
the combo approach, antares can combine information to provide a categorization. In
addition, broad-band photometry and multiwavelength data can distinguish post-starbust
4
galaxies (A. Zabludoff, priv. comm.), so ancillary information about potential host galaxies
can provide even more of a distinction for likely TDEs.
4
Supernovae on Demand
The explosive disruption of a star, either the thermonuclear explosion of a white dwarf or
the core-collapse of a massive star, is a spectacular event. They are highly energetic and
thus bright and visible over cosmological distances. Supernovae help us to understand the
end states of stellar evolution (e.g., Langer, 2012), physics in extreme environments (e.g.,
Sukhbold & Woosley, 2016), the chemical evolution of the Universe (e.g., McWilliam, 1997),
and some can be used as standardizeable candles to map the Universe on cosmological scales
(e.g., Riess et al., 1998; Perlmutter et al., 1999). One thing they are not, though, is rare.
Today, they are discovered by the hundreds every year (see the Transient Name Server site1 ),
while LSST is likely to produce thousands per year (Rau et al., 2007). Given the bulk of the
science that is done with supernovae, the key is not the discovery of a single, unique object,
but rather the detailed follow up of large samples.
The resources to conduct observational follow up of astronomical objects are limited,
especially when it comes to transient objects that are only available for a short period. In
addition, many resources are scheduled in ways not necessarily favorable to time-domain
astronomy. The so-called classical method of scheduling telescopes assigns nights to astronomers and they need to have targets available when their time is scheduled. When a
time-domain survey such as LSST can provide relatively common objects every night, this
issue is resolved, as long as the targets of interest can be identified. This could include
selecting thermonuclear supernovae as part of a study to characterize their diversity in order
to better constrain cosmological parameters or selecting only the very youngest supernovae
where early-time photometry and spectroscopy has proven extraordinarily valuable in understanding the progenitors of the explosions (e.g., Bloom et al., 2012; Khazov et al., 2016).
The way to fill this need with antares is to alter the set of filters in use by the system
so that, in addition to rare objects, objects that are not rare, but desired that night can be
identified. This would involve changing the filtering algorithms during the day so that the
nightly run can respond to specific requests. (This is an action of the conductor described
in the Architecture document.) The ability of an individual astronomer or team to request
such a change would have to rely on rankings of an allocation committee, just as with any
other observational program. This capability is not implemented in the prototype, but the
architecture is designed to accommodate it.
1
https://wis-tns.weizmann.ac.il/search?&isTNS AT=yes&classified sne=1&num page=500
5
5
Superflare Stars
While many late-type stars exhibit flaring (e.g., Benz & Güdel, 2010; Hawley et al., 2014,
and references therein), the Kepler spacecraft revealed a class of flares with energies greater
than 1034 ergs (approximately 100 times more energetic than flares observed on the Sun,
Candelaresi et al., 2014). These ‘superflare’ events are rare and may have implications
for dynamo activity in late-type stars, and thus our understanding of stellar structure and
evolution in solar-type stars. In addition, the frequency of such superflares has implications
for systems with exoplanets and the possibility of habitability, including whether our own
G-type star is capable of producing a superflare (e.g., Lundkvist et al., 2016; Karoff et al.,
2016). See also the discussion in Chapter 5 of Najita et al. (2016).
This type of object would trigger the VPDF stage early in the antares system as a
particularly unusual brightening of a source. In addition, the progenitor star would have been
observed before the flare as part of the regular LSST survey. The photometric information
from the prior observations would put strong constraints on the type of star, and thus enable
rapid identification of the alert as a flare on a G- or K-type star.
6
The Unknown
Astronomy continues to have a strong discovery-based element. Despite theoretical consideration of Einstein’s cosmological constant (Carroll et al., 1992), no one predicted the
revolution that occurred in 1998 when observations of supernovae revealed that the Universe
was not just expanding, but accelerating (Riess et al., 1998; Perlmutter et al., 1999). The
nature of the so-called ‘dark energy’ that drives this acceleration and makes up two-thirds of
the Universe is still a mystery. It was first found through careful analysis of an unexpected
result from time-domain astronomy. The even more prodigious explosions that generate
super-luminous supernovae were only identified within the last 15 years (Gal-Yam, 2012).
Figure 3 illustrates one method of characterizing the parameter space of transient events
via luminosity (or energy) and time scale. While classical novae, core-collapse supernovae,
and thermonuclear supernovae have been known and characterized for decades, the other
objects identified in the figure have only been recognized for about a decade. These include
the super-luminous supernovae mentioned before, as well as luminous red novae (Martini
et al., 1999; Kasliwal et al., 2011), calcium-rich transients (Kasliwal et al., 2012; Foley,
2015), and .Ia supernovae (so-called because they are a tenth of the energy and time scale
of a Type Ia supernova, Kasliwal et al., 2010; Perets et al., 2010).
Not all regions of this particular parameter space may be physically possible, but there
are clearly still empty regions that have yet to be fully explored. The prototype antares
6
REFERENCES
Figure 3: The discovery space of time-variable explosive astrophysical objects. The parameters in this diagram are luminosity (MV , or inverse logarithmic brightness) and the time
scale for the change in flux. Only the gray areas have been explored in any detail. There are
large regions of parameter space still unknown and this is just explosive transients. Figure
from Kasliwal (2012).
system is designed to winnow out from alert streams objects that are known and common.
Rare objects that have been seen are flagged, as described above for EM counterparts to
gravitational wave sources or superflare stars. Objects for which there is no comparable
match in known catalogs or feature spaces are also identified as rare, giving us a way to
identify the unknown when we see it.
References
Aasi, J. et al. 2015. “Characterization of the LIGO detectors during their sixth science run.”
Classical and Quantum Gravity, 32, 115012, astro-ph/1410.7764
7
REFERENCES
Abbott, B. P. et al. 2016a. “GW151226: Observation of Gravitational Waves from a 22Solar-Mass Binary Black Hole Coalescence.” Physical Review Letters, 116, 241103, astroph/1606.04855
——. 2016b. “Localization and Broadband Follow-up of the Gravitational-wave Transient
GW150914.” ApJL, 826, L13, astro-ph/1602.08492
——. 2016c. “Observation of Gravitational Waves from a Binary Black Hole Merger.” Physical Review Letters, 116, 061102, astro-ph/1602.03837
——. 2016d. “Prospects for Observing and Localizing Gravitational-Wave Transients
with Advanced LIGO and Advanced Virgo.” Living Reviews in Relativity, 19, astroph/1304.0670
Benz, A. O., & Güdel, M. 2010. “Physical Processes in Magnetically Driven Flares on the
Sun, Stars, and Young Stellar Objects.” ARA&A, 48, 241
Berger, E. 2014. “Short-Duration Gamma-Ray Bursts.” ARA&A, 52, 43, astro-ph/1311.2603
Bloom, J. S. et al. 2012. “A Compact Degenerate Primary-star Progenitor of SN 2011fe.”
ApJL, 744, L17, astro-ph/1111.0966
Candelaresi, S., Hillier, A., Maehara, H., Brandenburg, A., & Shibata, K. 2014. “Superflare
Occurrence and Energies on G-, K-, and M-type Dwarfs.” ApJ, 792, 67, astro-ph/1405.1453
Carroll, S. M., Press, W. H., & Turner, E. L. 1992. “The Cosmological Constant.” ARAA,
30, 499
Cowperthwaite, P. S. et al. 2016. “A DECam Search for an Optical Counterpart to the LIGO
Gravitational-wave Event GW151226.” ApJL, 826, L29, astro-ph/1606.04538
Foley, R. J. 2015. “Kinematics and host-galaxy properties suggest a nuclear origin for
calcium-rich supernova progenitors.” MNRAS, 452, 2463, astro-ph/1501.07607
Fong, W., Berger, E., Margutti, R., & Zauderer, B. A. 2015. “A Decade of Short-duration
Gamma-Ray Burst Broadband Afterglows: Energetics, Circumburst Densities, and Jet
Opening Angles.” ApJ, 815, 102, astro-ph/1509.02922
French, K. D., Arcavi, I., & Zabludoff, A. 2016. “Tidal Disruption Events Prefer Unusual
Host Galaxies.” ApJL, 818, L21, astro-ph/1601.04705
Gal-Yam, A. 2012. “Luminous Supernovae.” Science, 337, 927, astro-ph/1208.3217
8
REFERENCES
Gezari, S. 2012, in European Physical Journal Web of Conferences, Vol. 39, European Physical Journal Web of Conferences, 03001
Hawley, S. L., Davenport, J. R. A., Kowalski, A. F., Wisniewski, J. P., Hebb, L., Deitrick,
R., & Hilton, E. J. 2014. “Kepler Flares. I. Active and Inactive M Dwarfs.” ApJ, 797,
121, astro-ph/1410.7779
Ivezić, Ž., et al. 2008. “LSST: from Science Drivers to Reference Design and Anticipated
Data Products.” ArXiv e-prints, arXiv:0805.2366
Kahn, S. 2016, in Proc. SPIE, Vol. 9906, Ground-Based and Airborne Telescopes IV, ed.
H. J. Hall, R. Gilmozzi, & H. K. Marshall, in press
Kantor, J. 2014, in The Third Hot-wiring the Transient Universe Workshop, ed. P. R. Wozniak, M. J. Graham, A. A. Mahabal, & R. Seaman, 19–26
Karoff, C. et al. 2016. “Observational evidence for enhanced magnetic activity of superflare
stars.” Nature Communications, 7, 11058
Kasliwal, M. M. 2012. “Systematically Bridging the Gap Between Novae and Supernovae.”
PASA, 29, 482
Kasliwal, M. M. et al. 2011. “PTF 10fqs: A Luminous Red Nova in the Spiral Galaxy Messier
99.” ApJ, 730, 134, astro-ph/1005.1455
——. 2012. “Calcium-rich Gap Transients in the Remote Outskirts of Galaxies.” ApJ, 755,
161, astro-ph/1111.6109
——. 2010. “Rapidly Decaying Supernova 2010X: A Candidate ”.Ia” Explosion.” ApJL,
723, L98, astro-ph/1009.0960
Khazov, D. et al. 2016. “Flash Spectroscopy: Emission Lines from the Ionized Circumstellar
Material around <10-day-old Type II Supernovae.” ApJ, 818, 3, astro-ph/1512.00846
Komossa, S. 2015. “Tidal disruption of stars by supermassive black holes: Status of observations.” Journal of High Energy Astrophysics, 7, 148, astro-ph/1505.01093
Langer, N. 2012. “Presupernova Evolution of Massive Single and Binary Stars.” ARA&A,
50, 107, astro-ph/1206.5443
Lundkvist, M. S. et al. 2016. “Hot super-Earths stripped by their host stars.” Nature
Communications, 7, 11201, astro-ph/1604.05220
9
REFERENCES
Martini, P., Wagner, R. M., Tomaney, A., Rich, R. M., della Valle, M., & Hauschildt, P. H.
1999. “Nova Sagittarii 1994 1 (V4332 Sagittarii): The Discovery and Evolution of an
Unusual Luminous Red Variable Star.” AJ, 118, 1034, astro-ph/9905016
McWilliam, A. 1997. “Abundance Ratios and Galactic Chemical Evolution.” ARAA, 35,
503
Metzger, B. D. 2016. “The Kilonova Handbook.” ArXiv e-prints, astro-ph/1610.09381
Metzger, B. D., & Berger, E. 2012. “What is the Most Promising Electromagnetic Counterpart of a Neutron Star Binary Merger?” ApJ, 746, 48, astro-ph/1108.6056
Metzger, B. D., Giannios, D., & Mimica, P. 2012. “Afterglow model for the radio emission
from the jetted tidal disruption candidate Swift J1644+57.” MNRAS, 420, 3528, astroph/1110.1111
Najita, J. et al. 2016. “Maximizing Science in the Era of LSST: A Community-Based Study
of Needed US Capabilities.” ArXiv e-prints, astro-ph/1610.01661
Nakar, E. 2007. “Short-hard gamma-ray bursts.” PhR, 442, 166, astro-ph/0701748
Narayan, R., Paczynski, B., & Piran, T. 1992. “Gamma-ray bursts as the death throes of
massive binary stars.” ApJL, 395, L83, astro-ph/9204001
Perets, H. B. et al. 2010. “A faint type of supernova from a white dwarf with a helium-rich
companion.” Nature, 465, 322, astro-ph/0906.2003
Perlmutter, S. et al. 1999. “Measurements of Omega and Lambda from 42 High-Redshift
Supernovae.” ApJ, 517, 565, arXiv:astro-ph/9812133
Rau, A. et al. 2007. “The Incidence of Dwarf Novae in Large Area Transient Searches.” ApJ,
664, 474, arXiv:astro-ph/0611933
Riess, A. G. et al. 1998. “Observational Evidence from Supernovae for an Accelerating
Universe and a Cosmological Constant.” AJ, 116, 1009, arXiv:astro-ph/9805201
Sukhbold, T., & Woosley, S. E. 2016. “The Most Luminous Supernovae.” ApJL, 820, L38,
astro-ph/1602.04865
10