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 IFAE2011 - Perugia, 27-29 Aprile 2011

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

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

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

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 http://www.km3net.org/KM3NeT-TDR.pdf ) Agata Trovato 1/12

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

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

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

Physics energy scale Agata Trovato 4/12

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

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

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

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 (0.2°@30TeV) ○ Quality Cuts optimized for sensitivity Intrinsic angle ΔΩ(gen , μgen) Agata Trovato 6/12

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

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

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

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

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

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