part 2. s ummary intro: vhe -rays astrophysics observation technique instruments and data taking...
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It’s a kind of MAGIC!
COME I RAGGI GAMMA AD
ALTISSIMA ENERGIA
DIVENTANO SEGNALE
ELISA PRANDINIPadova University
MAPSES – LECCE 23 NOVEMBER 2011
PART 2
2
SUMMARY Intro: VHE g-rays Astrophysics
Observation Technique
Instruments and data taking
From raw data to shower images
Background Rejection
Signal extraction
Results: Sky Maps Integral and differential fluxes
3
Steps of the Analysis of CT data
Raw signal
Detection
Spectrum
Pixel signal extraction
Image cleaning
Image parameterization
Stereo- reconstruction
Background rejection
Background estimation
Source detection
Sky maps
Spectrum / light curve
Spectrum Unfolding
Event parameter reconst
Cleaned signal
4
Characterization of the events
Once we have obtained the shower images, the next step is to obtain the CHARACTERISTICS OF THE PRIMARY PARTICLE which originated the shower
Nature of the particle (Background rejection)
Primary Direction
Primary Energy
Random ForestReloaded
6
Random ForestsHow it works: The growing of a tree
this is a tree
ELEMENTS:- parameters (~10)- trees (100)- In each tree:
- nodes - POSSIBLE parameters in each
node (trials, ~3) RANDOM- BEST SEPARATOR and value
per node (via Gini index)- final node size (1-5)- each event is classified!
APPLICATION TO REAL DATA:- We apply each tree ( from training) to them- Each event is univocally classified (with a local hadronness) Final hadronness is an average among all the values!
Based on Monte Carlo Simulation
+ real data
TRAINING
Primary direction
8
Primary direction
The ellipse major axis points to the center of the camera
With many telescopes:
Helpful to “detect the signal”
The intersection of the axes is related to the INCOMING DIRECTION
9
The incoming direction
10
Reconstruction of the incoming direction
Geometrical reconstruction: for more than 1 telescope
M2
M1Reconstructed direction
Δδ
M1
M2
In Plan ┴ direction
Reconstructed core impact
point
Impact
parameter
Efficient forδ 30 deg
Monte Carlo independent
Energy Reconstruction
12
Energy reconstructionBasic fact: Energy ~ Image size
Based on Monte Carlo Simulation
Methods:
A parameterization:Energy = f(size, impact, zenith,…)
Look-up tables
Optimized decision trees(Random Forest)
13
Energy reconstructionEnergy resolution:
20% at 100 GeV, down to 15% around 1 TeV
Big bias @ low energies.Solved with unfolding
ENERGY RESOLUTION:E(est) - E(true) / E(true)
ENERGY BIAS:E(est) - E(true) / E(est)
Estimated with Monte Carlo
(Gammas)
Signal Extraction
15
What is the aim of our analysis?
Populate the VHE sky
Localize the emission
Characterize the emission
Energy
Time
DETECTION OF THE SIGNAL
SKY MAP
SPECTRUM
LIGHTCURVE
16
o DATA ACQUISITION
o CALIBRATION
o IMAGE CLEANING AND HILLAS PARAMETERS CALCULATION
o HADRONNESS AND ENERGY RECONSTRUCTION
The analysis
FILE SET OF EVENTS
EVENT SET OF PARAMETERS CHARACTERIZING THE SHOWER
REMEMBER: EVENT IS A SHOWER (INDUCED BY A CR)
Former steps
17
Characteristics of a g-like event
Therefore if we plot the parameter related to the reconstructed incoming direction, the gamma-like events will have it close to the telescopes pointing direction
To discriminate gamma-ray induced images from hadrons induced images, we use the square of the parameter Q, THE ANGLE BETWEEN THE POINTING DIRECTION (CAMERA CENTER) AND THE (RECONSTRUCTED) INCOMING DIRECTION.
AND WHAT ABOUT THE HADRONS?They are randomly distributed!
18
Detection: the Theta2 plot!
Where is the signal???
19
?We have a problem…
THE NUMBER OF BACKGROUND EVENTS IS ~ 104 TIMES THE NUMBER OF
GAMMA EVENTSWe have to reduce the number of bkg events:
HADRONNESS PARAMETER!
We apply a cut and reject the events that are likely hadrons
(MC data)
20
The Detection Now we are ready to perform our detection plot (also
called theta-square plot)
VERITAS Collaboration, V. A. Acciari et al, ApJ 715 (2010) L49
Background data
Source data
“Signal”
21
The Background We need a background in order to estimate the signal
Old technique: observe the source (ON data) and a region of the sky with the same characteristics but without a source (OFF data)PROBLEMS - time consuming!
- different observations conditions (weather, hardware)
SOLUTION: find an observing mode which allows to collect ON and OFF data simultaneously!
Wobble mode: the telescopes point to a region 0.4 deg offset from the source (and the background can be extracted)
22
The Detection Some theta2 plots:
H.E.S.S. Collaboration, F. Aharonian et al. A&A 442 (2005) 177-183
VERITAS Collaboration, V. A. Acciari et al, ApJ 715 (2010) L49
Not always there is a detection of course…
23
The Significance
SIGNIFICANCE is a measure of the likelihood that pure background fluctuations have produced the observed excess (i.e., assuming no signal)
The common rule is that a source is detected if the significance of the signal exceeds 5 sigma!
Li, T., and Ma, Y. 1983, ApJ, 272, 317
We need a tool to say if our observation is physically relevant
We use the SIGNIFICANCE of the signal
24
Examples
A five sigma signal
PKS 1222+21MAGIC
PG 1553+113H.E.S.S.
Mkn 180MAGIC
A 10 sigma signal
A four sigma signal
25
Standard Example: the Crab Nebula
MAGIC observations of the Crab Nebula:
WHICH IS THE DIFFERENCE?The energy range
considered!
E>300 GeV 60 GeV < E < 100 GeV
26
Images and Energy
At low energies the characterization of a gamma-like is much more difficult!!!
27
Therefore: The data analysis of IACTs telescopes is non trivial…
The first result to look for is a SIGNAL (is there a gamma ray source or not?):
The tool is the theta2 plot, a plot of the parameter theta2, that discriminates between hadrons (our background) and gamma-rays induced showers using the incoming direction
The signal is quantified through its SIGNIFICANCE:
< 5 SIGMA NO SIGNAL OR MORE STATISTICS NEEDED
> 5 SIGMA THERE IS A SIGNAL!THE ANALYSIS CAN
CONTINUE
Physical ResultsSky Maps
29
Second step: the localization
Important: in general IACTs don’t operate in scan mode but in pointing mode!
Moreover our resolution is… ~ 0.1 DEGREES
Extended sources: are galactic and very large regions
Extragalactic objects, for the moment, are point-like!
In order to localize the emission, we perform the so-called SKY MAP, that is a bi-dimensional map of the reconstructed incoming directions of the primary gamma rays
30
The sky map
For each event we reconstruct the INCOMING DIRECTION
Is the same parameter that we have used in the detection plot!
The background is modeled
Remember: our PSF is ~ 0.1 degree…
WE USE IT:
- As a check tool
- In few cases: extended emission or multiple sources in the field
31
Example: the Crab Nebula
FIND THE DIFFERENCE!
32
Example: the Crab Nebula
The angular resolution is strictly related to the ENERGY RANGE!
33
Extended sources
Some galactic sources are extended enough to be mapped nicely at TeV energies
SNR HESS J1731-347
Very interesting studies on acceleration sites!
H.E.S.S. collaboration, A. Abramowski et al. A&A 531 (2011) A81
34
NGC 1275 region
Clear signal from the head tail RG IC 310 at E > 400 GeV
And below this energy?E > 400 GeV
E > 150 GeV
If we go down to 150 GeV, a signal from the RG NGC 1275 becomes significant!
35
The galactic scan
HESS Coll. ICRC 2009 Proceedings
36
So, in the lucky case:
1. We have detected a significant signal
2. We have checked that the emission is coming from the direction that we expect (if not, go back to point 1, changing the true source position)
3. Now?
Spectrum
Light curve
Physical ResultsThe Spectrum
38
The differential energy spectrum
The spectrum is essential in our study Allows the
characterization of the emission
A comparison is possible (also between different experiments and energy thresholds!)
What is it?
VERITAS Coll. APJ Letters, 709, L163-L167 (2010)
THE NUMBER OF VHE PHOTONS PER AREA AND TIME
39
-ray flux: rate of -rays per unit area( to their direction)
units: [L-2] [T-1] (e.g. cm-2 s-1)
Needed ingredients: a number of -rays, a collection area and an observation time
Related concepts:
Differential energy spectrum: flux per interval in -ray energy (cm-2 s-1 TeV-1)
Integral flux: integrated in a given energy range (cm-2 s-1), e.g. :
Light curve: time evolution of integral flux: vs. t
Definitions
€
Φ =d2Nγ
dS dt
€
dΦdE
=d3N
dS dtdE
€
ΦE>200 GeV =dΦdE200 GeV
∞∫ dE
Courtesy of A. Moralejo
40
Differential energy spectrum:
the observablesNUMBER OF DETECTED -RAYS: obtained from the observed excess
EFFECTIVE OBSERVATION TIME: not equal to the elapsed time!
EFFECTIVE COLLECTION AREA ESTIMATED ENERGY of the events
€
dΦ
dE=
d3N
dS dt dE
41
Number of g-rays per energy
We have a “discretization” dN/dE becomes the number of excess per energy interval
How do we estimate this quantity?
THROUGH THE THETA2 PLOT (PER ENERGY INTERVAL)!
€
dΦ
dE=
d3N
dS dt dE
42
Effective observation time The effective observation time is not equal to the elapsed
time between the beginning and end of the observations: there may be gaps in the data taking (e.g. between runs) there is a dead time after the recording of each event
Useful quantity: t, the time difference between the arrival time of an event and the next one
In a Poisson process, t follows an exponential
€
PPoiss(n,t) =(λt)ne−λt
n!probability of observing n events in time t, given event rate
probability that the next event comes after time t
€
P (tnext > t) =PPoiss(0,t) =e−λt
P (tnext > t) = dP(tnext =t)dt
dtt
∞∫ ⇒ dP(tnext =t)dt
=λe−λt
€
dΦ
dE=
d3N
dS dt dE
Courtesy of A. Moralejo
43
Distribution of the time differences:
Calculation of effective observation time
In case of fixed dead time d, the distribution is still exponential with slope The true rate of events (i.e. before the detector) can be obtained from an exponential fit to the distribution
And teff = Nd,0 /
Courtesy of A. Moralejo
44
Example effective time
And teff = Nd,0 /
Log scale!
l slopeN
intercept
45
Effective Area Order of magnitude?
€
dΦ
dE=
d3N
dS dt dE
Aeff ~105 m2
Estimated from MC (gamma) data!
46
Effective Area Order of magnitude Aeff ~105 m2
o It’s roughly the Cherenkov light pool
We estimate it with MC data
o Depends on the Zenith angle of the observations:
47
Differential energy spectra
Numbers of bins is of course variable and set by the analyzer
Errors are larger at high energies… why?
Usually fitted with power laws
48
The unfolding Before publishing our spectrum, there is still one thing
that we can do:
Use the MC data to calculate the errors that we perform and apply a correction to the data
- limited acceptance and finite resolution- systematic distortions-reconstructed energy is not true energy!
HOW? With a matrix (correlation matrix) correlating the true Energy (from simulations) to the reconstructed Energy (estimated through RF)
49
Crab Nebula Spectrum
…and SED
50
Other examples
Extremely variable objects
Extremely distant objects (z=0.536)
Physical ResultsThe lightcurve
52
Integral Flux Differential (energy bins) integral (energy threshold)
If studied as a function of the time we make a LIGHT CURVE
How can we build a light curve?
Roughly speaking: we always have the same ingredients, but integral in energy: Theta2 plot above Eth
Integral effective area above Eth
The time… is the same!
€
ΦE>200 GeV =dΦdE200 GeV
∞∫ dE
Time evolutionstudies
H.E.S.S. collaboration, A. Abramowski et al. A&A. 520 (2010) A83
PKS 2155-304
53
LC Examples
HESS PKS 2155-489
3C 279
54
… we are only
one piece!
1ES 2344+514
1ES 2344+514
VERITAS Coll., Acciari et al., ApJ 738 (2011) 169
55
By the way:
you can find the fits files of our final results at: http://magic.pic.es/pub/fits/
Last CommentEBL: The gamma ray horizon
57
xx
x
VHE photons absorption by the Extragalactic Background Light
VHE photon + diffuse light electron-positron pairs production
VHEEBL e+e-
Absorption:
dF/dEOBS= (dF/dEEM) e-t
58
EBL SED
VHE photon + diffuse light electron-positron pairs production
Hauser and Dwek (2001)
VHEEBL e+e-
VHE photons absorption by the Extragalactic Background Light
59
VHE photon + diffuse light electron-positron pairs production
Large uncertainties!
VHE photons absorption by the Extragalactic Background Light
Dominguez et al. (2011)
VHEEBL e+e-
60
z = 0.003
z = 0.01
z = 0.03
z = 0.1
z = 0.3z = 0.5z = 1
g-g opacity
Our range of observations
Absorption:
dF/dEOBS= (dF/dEEM) e-t
EBL ModelFranceschini et al. (2008)
61
z = 0.003
z = 0.01
z = 0.03
z = 0.1
z = 0.3
z = 1
Strong suppression
z = 0.5
g-g opacityAbsorption:
dF/dEOBS= (dF/dEEM) e-t
EBL ModelFranceschini et al. (2008)
62
EBL absorption effect
EBL model:Franceschini et al. (2008)
63
Current “limit” The FSRQ 3C 279 at redshift 0.536
64
Conclusions The analysis of Cherenkov data is non trivial…
…but it is worth!!!
Probably there are still large margins of improvements: New analysis techniques More powerful instruments (CTA)
The present and future is MULTI-INSTRUMENT!
THANK YOU!
65
Exercise… how many Crab gammas in 1 hour?
dN/dE = (3.3±0.11)×10−11E−2.57±0.05cm−2s−1TeV−1
66
Model analysis: A Global reconstruction method
An alternative to the use of image parameterization Analytic model (based on MC) gives the
expected signal in each pixels as a function of E, Direction & Impact
A fit of the MC templates on the real data reconstructs at same time the E, direction, and nature (gamma/hadron)
This method developed by CAT and then by HESS is time consuming but provides the best results (for telescope arrays).
MC template
67
Reconstruction of the incoming direction
DISP method: Developed for single telescope data
centroid
major axis
DISP
DISP can be determined with:
- A parameterization:
- Optimized decision trees (Random Forest)
reconst. direction
All methods are based on Monte Carlo Simulation
Possible confusion withsymmetric directionImage asymmetry and timegradient help the distinction
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