1. Istituto Nazionale di Fisica Nucleare Laboratori Nazionali del Sud
Agata Trovato
Per il consorzio KM3NeT
Istituto Nazionale di Fisica Nucleare Laboratori Nazionali del Sud
Ottimizzazione delle prestazioni del telescopio Čerenkov per neutrini di alta energia KM3NeT
IFAE Perugia, Aprile 2011

2. Introduction High-energy Neutrino Astronomy
Neutrinos are good astrophysical probes:
not deflected
not absorbed
Agata Trovato
1/12

3. Introduction High-energy Neutrino Astronomy
Neutrinos are good astrophysical probes:
not deflected
not absorbed
Candidate high-energy neutrino sources
Galactic: (SNR, X-Ray Binaries)
Extragalactic: (AGN, GRB)
Agata Trovato
1/12

4. Introduction High-energy Neutrino Astronomy
Neutrinos are good astrophysical probes:
not deflected
not absorbed
Candidate high-energy neutrino sources
Galactic: (SNR, X-Ray Binaries)
Extragalactic: (AGN, GRB)
High-energy neutrino detection
Underwater/ice Optical Cherenkov technique (TeV-PeV)
Agata Trovato
1/12

5. Introduction High-energy Neutrino Astronomy
Neutrinos are good astrophysical probes:
not deflected
not absorbed
Candidate high-energy neutrino sources
Galactic: (SNR, X-Ray Binaries)
Extragalactic: (AGN, GRB)
High-energy neutrino detection
Underwater/ice Optical Cherenkov technique (TeV-PeV)
KM3NeT
an European deep-sea research infrastructure that will host a neutrino telescope with a volume of a few cubic kilometre at the bottom of the Mediterranean Sea (Technical Design Report )
Agata Trovato
1/12

6. KM3NeT and the international context
Assuming 2π downward coverage, we need a km3 telescope for each hemisphere
Southern Hemisphere IceCube (South Pole)
Northern Hemisphere KM3NeT (Mediterranean Sea)
IceCube
Agata Trovato
2/12

7. KM3NeT and the international context
Assuming 2π downward coverage, we need a km3 telescope for each hemisphere
Southern Hemisphere IceCube (South Pole)
Northern Hemisphere KM3NeT (Mediterranean Sea)
KM3NeT field of view
IceCube filed of view
Agata Trovato
2/12

8. Final Detector Layout KM3NeT: an artistic view
Detection Units
Primary Junction box
Secondary Junction boxes
Electro-optical cable
Semi-rigid vertical structure composed of:
20 bars (40 m vertical spacing)
each bar has 2 Optical Module with 31 3” PMT inside
Agata Trovato
3/12

9. Physics energy scale
Agata Trovato
4/12

10. each bar of the DU has 6 Optical Module with 8” PMT inside
Results presented
Results discussed in this talk refers to the KM3NeT TDR, optimization not for the final floor configuration.
TDR configuration:
310 Detector Unit (DU)
each DU with 20 bars
each bar of the DU has 6 Optical Module with 8” PMT inside
Agata Trovato
5/12

11. Calculation of the sensitivity: binned method
Given an arbitrary source spectrum s = k E- predicting < ns > signal events
90% confidence level average flux limit
Agata Trovato
6/12

12. Calculation of the sensitivity: binned method
Given an arbitrary source spectrum s = k E- predicting < ns > signal events
Average maximum limit of background fluctuation at 90% of confidence level that would be observed after hypothetical repetition of an experiment with an expected background <nb> and no true signal
90% confidence level average flux limit
Agata Trovato
6/12

13. Calculation of the sensitivity: binned method
Given an arbitrary source spectrum s = k E- predicting < ns > signal events
Average maximum limit of background fluctuation at 90% of confidence level that would be observed after hypothetical repetition of an experiment with an expected background <nb> and no true signal
Average number of signal and background events estimated throught the Monte Carlo simulations
90% confidence level average flux limit
Median ΔΩ(μgen , μrec)
□ Quality Cuts applied
○ Quality Cuts optimized for sensitivity
Intrinsic angle ΔΩ(gen , μgen)
Agata Trovato
6/12

14. Simulations: optimization studies
Bar length optimization
Optimization of Detection Unit separation
ratio of the effective area relative to 3m
ratio of the effective area relative to 100m
Low energy region
100GeV< E <500 GeV
Quality cuts applied
DWm-mrec ~ 2°
(close to the DWn-m)
Point like sources
3TeV< E <100TeV
Quality cuts applied
DWm-mrec ~ 0.4°
(close to the search
cone radius)
Diffuse flux studies & GRB
E >100TeV
No quality cuts applied
DWm-mrec < 0.9°
Agata Trovato
7/12

15. Sensitivity ratio for point like source: 1 year, δ=-60°
“binned method” analyze the fluctuations on the number of events detected inside a cone
“mrf” minimisation by cutting on:
Rbin size of the search cone around the source
Λ reconstruction quality parameter
Nhit number of neutrino hits used to reconstruct the event
Bar length optimization
Optimization of Detection Unit separation
ratio of sensitivity relative to 3m
ratio of sensitivity relative to 100m
α = 2.2
α = 2.0
Φ=k*E-2 * eE/10 TeV
compromise between physical performance and technical constraints  6 m bar chosen
180 m preferred DU distance
Agata Trovato
8/12

16. KM3NeT: sensitivity & discovery
Sensitivity and discovery fluxes for point like sources with a E-2 spectrum for 1 year of observation time
KM3NeT sensitivity 90%CL
KM3NeT discovery 5s 50%
IceCube sensitivity 90%CL
IceCube discovery 5s 50% 2.5÷3.5 above sensitivity flux. (extrapolation from IceCube 40 string configuration)
| Observed Galactic TeV-g sources (SNR, unidentified, microquazars)
F. Aharonian et al. Rep. Prog. Phys. (2008)
Abdo et al., MILAGRO, Astrophys. J. 658 L33-L36 (2007)
 Galactic Centre
Unbinned method
Binned method
For the southern sky, which is best viewed from the Mediterranean Sea, KM3NeT will have a sensitivity nearly two orders of magnitude better than that of the current instruments, Baikal and ANTARES, whose sensitivity curves fall outside the limits of the figure
Agata Trovato
9/12

17. Aart Strategy modified Usual prefit algorithm adopted where
New prefit
About hundred cosmic TeV gamma-ray sources have been recently identified. At least few tens of identified gamma sources in the galaxy are expected to be also high energy neutrinos sources.
The source direction reconstruction algorithm consists of four consecutive fitting procedures. The last procedure produces the most accurate result, but requires a priori estimates of the muon track parameters that should be close to the true values. The choice of a good starting track is fundamental.
If we look for neutrinos coming from a specific source, we can use the source direction information during the track reconstruction
Aart Strategy modified
Usual prefit algorithm adopted where
θprefit = θsource
φprefit = φsource
+ method of Lagrange multipliers
Prefit vertex obtained using the method of Lagrange multipliers to find the minimum of the c2 in the fit, with the constraint “prefit direction = neutrino direction”
Agata Trovato
10/12

18. Results with the new algorithm
Sensitivity:
Effective Area:
Low energy region
100GeV< E <500 GeV
Gain in sensitivity of about ~20% (at 180 m) and ~30% (at 250 m)
Quality cuts applied
DWm-mrec ~ 2° (close to the DWn-m)
Sensitivity as a function of the towers number, calculated with:
standard reconstruction
180 m spacing betwen towers
spectral index = 2
3 years of data taking
Point like sources
3TeV< E <100TeV
Quality cuts applied
DWm-mrec ~ 0.4°
(close to the search cone radius)
Standard reconstruction
Diffuse flux studies & GRB
E >100TeV
New reconstruction
No quality cuts applied
DWm-mrec < 0.9°
Gain equivalent to an increase of about 20% in the towers number
Agata Trovato
11/12

19. Conclusions
Sensitivity to point-like sources:
Optimal towers distance = 180 m
Increasing bar length improves reconstruction performance. Taking into account simulation results and technical constrains Bar length chosen = 6 m
KM3NeT sensitivity is better than that of IceCube over the full range of declinations, even those in the northern sky which is the central field of view from the South Pole
improving in sensitivity of about ~20% (at 180 m) and ~30% (at 250 m) with the new reconstruction algorithm
further improving can be obtained using unbinned method for sensitivity calculation (see V. Giordano talk)
Future goals:
search for a better "energy estimator"
explore unbinned method
application to specific sources classes (GRB, SNR,…)
Agata Trovato
12/12