Transcript Perspectives for GAIA

The optical long-term activity
of the high-energy sources:
Perspectives for ESA Gaia
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V. Simon , G. Pizzichini , R. Hudec
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Astronomical Institute, The Czech Academy of Sciences,
v
25165 Ondrejov, Czech Republic
Czech Technical University in Prague, FEE, Prague, Czech Republic
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INAF/IASF Bologna, via Gobetti 101, 40129 Bologna, Italy
Talk: 12th INTEGRAL/BART Workshop, 20-24 April 2015,
Karlovy Vary, Czech Republic
ESA Gaia satellite
Primary mirror 1
 A space observatory designed for astrometry
 Limiting magnitude: ~ 20 (400-100 nanometers)
 The satellite can be used also as a monitor
(brightnesses and ultra-low-dispersion spectra)
 About 80 observations of a given field
Source: Wikipedia
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Photometric filters in astrophysics
The color indices are determined from the magnitudes of an object
measured in the individual filters (e.g. U – B, B – V, V – R, R – I).
 important information on the spectral energy distribution
 magnitudes and color indices can be determined even from
ultra-low-dispersion spectra obtained by ESA Gaia
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Why to use color indices in analysis of optical counterparts of
high energy sources?
It is a powerful and sensitive approach which helps us to:
 investigate spectral energy distribution and its changes by using
photometric filters – even very faint objects can be studied
 search for the common properties of the sources of a given kind (e.g.
various types of binary X-ray sources, optical afterglows of GRBs…)
 search for the relations among colors and luminosities of a given object
or a kind of objects
 constrain the extinction in the medium between the observer and the
source (and also extinction inside the source)
 resolution among the individual radiation mechanisms (e.g. synchrotron
radiation, cyclotron radiation, thermal emission)
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Optical afterglows (OAs)
of gamma-ray bursts
(GRBs)
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The gamma-ray light curves and positions of GRBs
A very large range
of profiles and
durations of
the bursts
Data from BATSE onboard Compton GRO satellite
Distribution of the
positions of GRBs
in the sky
Galactic coordinates
GRBs are uniformly distributed in the sky. They are not concentrated
either toward the Galactic center or toward the Galactic plane.
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Which kinds of objects give rise to GRBs?
Long GRBs
Short GRBs
Core collapse of a massive star
Merging compact objects in a binary (e.g. NS+NS)
Initial stage of a GRB. The core of the star has
collapsed. A black hole has formed within the
star (it launches a jet of matter).
(Credit: NASA / SkyWorks Digital)
A black hole is
embedded by a
torus of infalling
matter.
A jet of this matter
is launched.
Zhang et
al. (2006)
Relativistic jet is the dominant source of
radiation from gamma-ray to the infrared
(and radio) spectral region.
Intensity of this emission depends on
the inclination angle (the jet has to point
toward the observer to be seen).
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Typical light curves of optical afterglows (OAs) of GRBs
Relativistic jet is the dominant source of radiation from gammaray to the infrared (and radio) spectral regions.
Intensity depends on the inclination angle (the jet has to point toward the observer).
Brightness of most OAs already falls when
they are discovered in the optical band.
(typically, a power-law decay is dominant)
Luminosity proportional to t -a
OA lasts much
longer than GRB
(days versus seconds
or minutes)
Limiting brightness
of Gaia data
Zhang et al. (2006)
All observations are in the R band (red light) and their time is in the observer frame.
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Typical time evolution of the color index of OA
GRB 080319B
Extreme change of the
optical brightness of the
OA in the initial phase:
a decline by 7.9 mag
during 4.6 hours after
the GRB trigger
The color index changed only very little – it is therefore possible to combine the data
of the individual OAs obtained in different t–T0
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Time evolution of the color indices of OAs
Pre-Swift ensemble of GRBs
25 GRBs inside the belt
Ensemble of OAs (t - T0 <
10 d) in the observer frame
(corrected for the Galactic
reddening)
OAs of GRBs observed by Swift
10 GRBs inside the belt
OAs with redshift z < 3.5
form a very narrow belt
with negligible variations
with time
OAs of the Swift GRBs are
mapped in earlier phases
than before
Simon et al. (2013)
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Color-color diagrams of OAs in the observer frame
OAs of GRBs
observed by Swift
Ensemble for the
centroid: 9 GRBs
Centroid
Ensemble of OAs
(t-T0 < 10 days)
(redshift z < 3.5) in
the observer frame
(corrected for the
Galactic reddening)
 Vectors: representative reddening outside our Galaxy:
Simon et al. (2013)
E = 0.5 mag
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SN 2006aj
Early OA
B band light curve
GRB 060218/
SN 2006aj
UVOT/Swift data
Data corrected for the
reddening and light
contribution of the
host galaxy.
Color
indices
Simon et al. (2010)
Separation of the colors
appropriate to the early
OA and SN 2006aj is clear
for UVW2 - B, UVW1 - U,
UVM2 - UVW1.
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Optical afterglows – perspectives for ESA Gaia (I)
 Optical afterglows (OAs) can be detected as the NEW objects with
untriggered Gaia observations even several days after the appropriate
GRB.
Color indices of OAs – a powerful approach to the study
of such events:
 Many OAs display specific color indices with negligible time evolution
during the decline of brightness. This helps distinguish them from
other kinds of transients by photometric observations using several
color filters even without available detection of gamma-rays.
This finding will also be helpful for their observation with ESA Gaia.
 A search for the common properties of OAs is possible.
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Optical afterglows – perspectives for ESA Gaia (II)
 Constraining the properties of the local interstellar medium of GRBs
 Resolving among the individual radiation mechanisms (e.g.
synchrotron radiation versus supernova – important for
investigation of the GRB-supernova relation)
 Searching for orphan afterglows (GRBs without detected gamma-rays
(e.g. the jet is not pointing directly to the observer, Lorentz factor is
too small…), but the optical emission may still be observed)
> a matter of debate – events predicted by theories, but only
long-term deep monitoring of the sky can resolve between
the theories.
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Binary X-ray sources
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Disk accretion
Structure and emission regions
Donor – thermal (optical, IR)
Compact object (white dwarf,
neutron star, black hole)
Accretion disk – thermal
radiation (UV, optical, IR)
Close vicinity of the compact object
CVs: bremsstrahlung (X-rays)
XBs: Comptonizing cloud (inverse
Compton process – hard X-rays)
Jets – synchrotron (radio)
Donor – thermal radiation
(optical, IR)
Accretion column – cyclotron
(optical , IR)
Accretion shock near the magnetic
pole(s) of the WD – bremsstrahlung
(hard X-rays)
Heated surface of the WD – thermal
(soft X-rays, far UV, UV)
Synchrotron emission (e.g. from
the vicinity of the donor) (radio)
Donor
Accretion
WD
Mass stream
column
Stream impact
onto disk
Compact object
Accretion disk
Polars
Donor
Crossing
Alfven radius
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Mechanisms for the long-term activity of binary
X-ray sources
 Changes of mass transfer rate dm/dt from donor onto the compact
object (timescale: days, weeks, months, years)
 Thermal instability of the accretion disk (timescale: days, weeks,
months)
 Hydrogen burning on the white dwarf (in CVs) :
Episodic:
– classical nova explosion (timescale: weeks, months)
– recurrent novae (timescale: weeks, months)
Steady-state:
– supersoft X-ray sources (timescale: days, weeks, months)
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Increase of mass transfer rate dm/dt
Thermally
unstable disk
Systematics of the longterm activity of cataclysmic
variables (CVs)
Simulation using AFOEV data
Activity in non-magnetic CVs
Sequence (from top to bottom):
Large - amplitude, isolated
outbursts
Numerous outbursts with
short intervals in between
Thermally
stable disk
(most time)
Data source: AFOEV
Dominant small fluctuations
in the high state
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Statistical distributions of brightness in the long-term light curves of CVs – separation into subtypes
Histograms
of brightness in the long-term activity of CVs
Dwarf novae of
U Gem type –
rare outbursts
Dwarf novae of
U Gem type –
frequent
outbursts
Dwarf novae
of Z Cam type
Segment of
Z Cam dwarf
nova without
standstills
Novalike and
VY Scl type
systems
Daily means
Approximated sampling of
the Gaia data
Observations from the
AFOEV database (daily
means) (segment of 4
years)
We approximate the
Gaia sampling by
the data separated
by ~20 days.
The number of the data
~ the number of obs.
by ESA Gaia.
- description of the
properties of the light
curve almost independent
of sampling
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Perspectives for investigation of CVs with ESA Gaia (I):
 Profiles of the light curves of cataclysmic variables (CVs) will be
significantly affected by the sampling of the Gaia data.
 The individual outbursts in dwarf novae are expected to be covered
by only a few Gaia data points – no or very limited information on
the profile of a given outburst (also difficult to determine the type
of CV from the profile of the light curve itself).
 We find that the statistical distribution of brightness (in magnitudes)
and its parameters (the standard deviation, skewness, excess) are
only slightly distorted by the sampling of the Gaia data (even if the
profile of the individual outbursts and/or high/low states are affected
by the sampling).
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in dwarf novavariables (CVs)
Color indices Outburst
of cataclysmic
Color-color diagrams of ensemble of CVs
Dwarf novae in quiescence
Dwarf novae in outburst
Hack & la Dous (1993)
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V1223 Sgr
Sept 11, 1966; JD 2 439 380
"Normal" level
Sept 14, 1966; JD 2 439 383
Long-term activity of the
intermediate polar
Simon (2014)
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Outburst on
Bamberg
photographic
plates
Moment of the peak
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brightness (outburst)
Aql X-1
(soft X-ray transient)
Optical
Optical
X-ray
X-ray
Optical
X-ray
Relation of the optical and X-ray
intensity in a series of outbursts
Maitra & Charles (2008)
Simultaneous observations of the
outburst in the optical and X-ray
bands:
duration of outburst in various bands and Xray/optical ratio may differ substantially
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Her X-1 (Low-mass X-ray binary)
Inactive state
Long-lasting active state
Simon et al. (2002)
Sonneberg photographic
(one plate per night)
Perspectives
fordata
Gaia:
Large changes of the orbital modulation
and the responsible physical processes
can be studied even using sampled data
Separation of the time intervals of the
different states of the long-term activity
is possible and will be helpful
Remarkably different profile
of the low-state orbital
modulation with respect to
that of the active state
Active state
Hudec &Wenzel (1976)
Simon et al. (2002)
Inactive state
Inactive
state
Data folded with the orbital period of 40.8 hours 24
Activity of persistent X-ray sources
McNamara
et al. (2003)
Hudec (1981)
Long-term light curve in blue light. Annular means
from archival photographic plates.
- composition of rapid and long-term activity
X-ray
Optical
4U 1957+11
Russell et al. (2010)
Differences in the B-mag histograms:
Explanation: variations in the mass
accretion rate and the relatively short
time period typically covered by optical
observations
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How to pick up
LMXB from
several heavily
sampled
Gaia data points
X-ray
binaries
in Gaia
data
Comparison of several measurements from several epochs will reveal
that the object is variable (active).
 Transients in the expected coverage by Gaia data:
- Newly identified source near the peak magnitude of outburst
- Declining branch is expected to be covered by multiple observations
- Even systems which have not been observed to undergo outburst
can be identified in Gaia data as variable objects e.g. by their
orbital modulation
 Persistent sources:
- Fluctuations of brightness on the timescale of days
- Amplitude of long-term variations: ~1 mag (~ 2.5 in intensities)
- Orbital modulation
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Acknowledgements:
This study was supported by grants 13-394643 and 13-33324S provided by
the Grant Agency of the Czech Republic. Full references on each OA are
given in J. Greiner's Web page http://pwww.mpe.mpg.de/~jcg/grbgen.html.
This research has made use of the observations provided by the
ASM/RXTE team (Levine et al., 1996, ApJ, 469, L33). It also used the
observations from the AAVSO International database (Massachusetts,
USA (e.g. Henden 2013)) and the AFOEV database operated in Strasbourg,
France. I thank the variable star observers worldwide whose observations
contributed to this analysis. I also thank Prof. Petr Harmanec for providing
me with the code HEC13. The Fortran source version, compiled version
and brief instructions how to use the program can be obtained at
http: //astro.troja.mff.cuni.cz/ftp/hec/HEC13/
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