* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Perspectives for GAIA
Ultrafast laser spectroscopy wikipedia , lookup
Phase-contrast X-ray imaging wikipedia , lookup
Ellipsometry wikipedia , lookup
Nonimaging optics wikipedia , lookup
Fiber-optic communication wikipedia , lookup
Photon scanning microscopy wikipedia , lookup
Astronomical spectroscopy wikipedia , lookup
Magnetic circular dichroism wikipedia , lookup
X-ray fluorescence wikipedia , lookup
Optical illusion wikipedia , lookup
Optical rogue waves wikipedia , lookup
Atmospheric optics wikipedia , lookup
Optical coherence tomography wikipedia , lookup
Harold Hopkins (physicist) wikipedia , lookup
Silicon photonics wikipedia , lookup
Retroreflector wikipedia , lookup
Passive optical network wikipedia , lookup
The optical long-term activity of the high-energy sources: Perspectives for ESA Gaia v 1,2 3 V. Simon , G. Pizzichini , R. Hudec 1 2 1,2 Astronomical Institute, The Czech Academy of Sciences, v 25165 Ondrejov, Czech Republic Czech Technical University in Prague, FEE, Prague, Czech Republic 3 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 2 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 3 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) 4 Optical afterglows (OAs) of gamma-ray bursts (GRBs) 5 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. 6 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). 7 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. 8 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 9 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) 10 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 11 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. 12 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. 13 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. 14 Binary X-ray sources 15 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 16 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) 17 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 18 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 19 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). 20 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) 21 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) 22 Outburst on Bamberg photographic plates Moment of the peak 16 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 23 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 25 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 26 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/ 27