Presentation is loading. Please wait.

Presentation is loading. Please wait.

A First Look At VERITAS Data Stephen Fegan Vladimir Vassiliev UCLA.

Published byOphelia Turner Modified over 8 years ago

Similar presentations

Presentation on theme: "A First Look At VERITAS Data Stephen Fegan Vladimir Vassiliev UCLA."— Presentation transcript:

1 A First Look At VERITAS Data Stephen Fegan Vladimir Vassiliev UCLA

2 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev Data Analysis Flowchart Image conditioning. Geometry reconstruction. Event parameterization. Energy reconstruction. Data Selection.  Independent telescope parameters.  Array. Results. Standard approach. Picture/boundary cleaning. Has not been optimized. Has not been investigated. Array cuts, based on combining the various parameters from all images have not been investigated. To be investigated… Methods 1&2 from reconstruction memo of December. Parameterization from memo also. Cuts based on individual telescope images using parameters from memo. Simple “box” shaped cuts and multi- dimensional cuts using “NSpace”

3 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev Geometry reconstruction Method1: fit arrival direction and core from individual image axes, weighted “appropriately”. Method 2: Fit single shower axis to all images simultaneously. This axis is projected onto focal plane of each telescope. Method 3: Fit single shower axis to all images simultaneously. This axis is defined in real 3D space. Methods 1 and 2 give comparable results with two telescopes. Method 3 has not been investigated.

4 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev Event parameterization Once the shower axis has been reconstructed each image can be mapped into “physical space”, giving: 1)Mean emission height and track length. 2)Depth s of mean emission in atmosphere in g/cm 2. 3)Mean angle of emission with respect to trajectory. 4)Physical width of emission region. 5)Dispersion s in photon arrival times assuming emission along primary trajectory.

5 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev Data selection Simple cuts on parameters in Dec. memo:  Log 10 (size) > 2.5  Emission region width< 15m  Emission height> 5000m  Emission length> 750m Simulations suggest cuts should be energy dependent. Studies using n-dimensional cutting system NSpace 1 is ongoing. Preliminary results discussed here. 1 See T. Nagai’s thesis for write up of NSpace methodology

6 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev Results: Mrk 421 – 9 pairs Background rate of 16.4/min/deg 2 based on θ<0.2° (SIMPLE CUTS) Significance 29σ, rate 5.76/min

7 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev Results: table of Mrk421 pairs RunDurationONOFFRateSignificance 3032828.0223516.1510.39 3033028.0253646.7510.62 3035828.0224566.0010.04 3039428.0192465.229.46 3039628.0244566.7110.85 3039828.0256626.9310.88 3040028.0236695.969.56 3047628.0167653.646.70 3047828.0174504.438.29 TOTAL252.019695195.7629.07 (SIMPLE CUTS)

8 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev Results: Mrk 421 – 10 wobble at 0.3° Theta 2 distribution with respect to source position Theta 2 distribution with respect to symmetric wobble position Source counts as they appear from off source location. No obvious spill over to theta=0 area. Wobble offset of 0.3º seems to be sufficient. (SIMPLE CUTS)

9 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev Results: table of Mrk421 wobble runs RunDurationONOFFRateSignificance 3048015.063302.203.42 3049028.0154384.148.37 3049128.0175574.217.75 3049228.0182733.896.83 3049328.0164703.366.14 3049428.0176644.007.23 3049528.0176584.217.71 3049628.0157733.005.54 3049728.0140712.464.75 3057228.048300.642.04 TOTAL266.9514355643.2619.48 (SIMPLE CUTS)

10 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev Results: strong source optimization Photon dominated regime: For strong source, optimize theta cut for significance. Peak is quite broad. Theta cut from 0.15° to 0.25° gives high significance. We chose 0.2° for high rate. 9 Mrk421 pairs (SIMPLE CUTS)

11 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev Results: weak source optimization Background dominated regime: For weak source optimize theta cut for excess/sqrt(background) – Q- value. Shown is Q-value, normalized to 1 at theta=1. Peak is much narrower. Theta cut from 0.12° to 0.16° gives best significance on weak sources. 9 Mrk421 pairs (SIMPLE CUTS)

12 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev Results: Mrk421comparison with Whipple VERITAS Run VERITAS Rate VERITAS Significance Whipple Run Whipple Rate Whipple Significance 1 303586.0010.031306 2 1.776.2 303986.9310.9313232.728.95 313242.979.20 304005.969.6313252.869.12 304763.646.7313691.816.79 304784.438.3313721.555.45 1 Whipple results from J. Kildea 2 VERITAS and Whipple run numbers are similar after 40 years of Whipple operation (SIMPLE CUTS)

13 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev Results: Mrk501comparison with Whipple VERITAS Run VERITAS Rate VERITAS Significance Whipple Run Whipple Rate Whipple Significance 1 304830.972.30313770.110.53 304980.290.71314000.331.66 306000.711.78314780.221.20 308440.180.4331635-0.04-0.19 308630.400.88316590.190.82 308780.831.98316770.221.09 30897-0.04-0.08316940.150.88 308980.180.42316960.040.19 1 Whipple results from J. Kildea (SIMPLE CUTS)

14 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev Results: aperture function Cosmic-ray acceptance as a function of off-axis angle, after cuts. These events are the most gamma-ray like CRs. Gamma-ray response will likely be somewhat similar. Quite flat to 0.8 degrees. Fast decline at 1.75 degrees (SIMPLE CUTS)

15 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev NSpace: basic ideas Form multi-dimensional histogram in space defined by event parameters. Fill two histograms: from ON & OFF runs or from SIM & OFF data. Order cells “according to significance (likelihood,…)” (many ordering schemes possible). Make “filter” by picking cells from ordering to maximize total significance (likelihood,…). Repeat all steps above varying bin sizes of the histogram until significance (likelihood,…) is maximized. Bin sizes and histogram dimension are your optimization parameters. Final filter is an effective volume in multidimensional space. Cut ON events according to whether they are inside or outside the filter.

16 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev NSpace: example in two dimensions log(size) width 2.0-3.52.5-3.03.0-3.53.5-4.04.0-4.5 0.00-0.0267 47 68 52 100 44 76 45 65 47 0.02-0.0469 60 99 44 94 58 79 50 67 58 0.04-0.0668 55 86 46 101 55 98 53 61 49 0.06-0.0861 50 59 43 68 42 80 44 50 59 0.08-0.1049 57 60 45 51 55 59 48 65 0.10-0.1258 40 52 48 62 50 54 45 43 ON counts OFF counts Highest single cell significance(4.7 sigma) Two cell set with highest overall significance (6.5 sigma) Seven cell set with highest overall significance (9.9 sigma). Thereafter adding any more cells decreases significance.

17 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev NSpace: single telescope space Space based on three single telescope parameters:  Log 10 (λ c )*12 bins no 4 – 8  Emission width20 bins no 0 – 40 m  Emission depth10 bins no 0 – 1000 g/cm 2 ON histogram: 9 Mrk421 runs – theta<0.2 OFF histogram: 9 Mrk421 runs – theta<1.0 Optimize filter on T1 parameters Apply to both T1 & T2 when cutting * λ c : density of emitters in coherent regime [m -1 ], see December memo for details

18 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev NSpace: optimization results Filter with 70 cells gives close to the peak Q-value and gives good rate For comparison, straight cuts have Qmax=6 (with theta cut of 0.16°)

19 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev NSpace: optimization results Filter with 70 cells gives close to the peak Q-value and gives good rate For comparison, straight cuts have Qmax=6 (with theta cut of 0.16°)

20 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev Straight CutsNSpace Cuts Data SetONOFFRateSigmaONOFFRateSigma 9 Mrk421 Pairs 1 14362914.5427.5510081023.6027.19 8.5 Mrk421 Wobble 10373232.6719.36596811.9319.79 19 Mrk501 Wobble 8635820.527.395672990.509.11 Faint source improvement not as large as indicated from optimization (1.33 2 =1.76 vs 1.23 2 =1.51). This reflects some degree of “tuning” of space to specific runs used in optimization. NSpace: comparison with straight cuts (NSpace with theta cut of 0.15°) (Straight with theta cut of 0.14°) 1 Optimization done on these runs Bright source significance is approximately equal with this NSpace filter but rate is lower. A theta cut of 0.2 gives better significance and rate for both sets of cuts.

21 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev NSpace: 10 Mrk421 wobble runs Background rate of 5.0/min/deg 2

22 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev

23 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev

24 RunDurationONOFFRateSignificance 1 3048329.843160.913.52 3048428.044111.184.45 3048627.743160.983.52 3048716.71660.602.13 3049828.021130.291.37 3049928.033150.642.60 3050028.025120.462.14 3050118.91113-0.11-0.41 3060228.02080.432.27 3060328.030140.572.41 3082217.723100.732.26 3082328.031150.572.36 3086330.027230.130.57 3086430.032130.632.83 3087830.036230.431.69 3087930.029200.301.29 3089728.020160.140.67 3089828.01921-0.07-0.32 3089928.023170.210.96 TOTAL538.75672990.509.11 NSpace: results for Mrk501 wobble 1 Using traditional Gaussian significance formula (somewhat inaccurately) If Crab is 5  /min then 4% Crab in 20hours/wobble @ 5  or 18% Crab in 1hour/wobble @ 5  HESS claimed 11% Crab in 1hour/wobble @ 5 

25 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev NSpace: 501 comparison with Whipple VERITAS Run VERITAS Significance VERITAS Rate Whipple Run Whipple Significance 1 Whipple Rate 304833.520.91313770.530.11 304981.370.29314001.660.33 306003.180.64314781.200.22 308440.800.1831635-0.19-0.04 308630.570.13316590.820.19 308781.690.43316771.090.22 308970.670.14316940.880.15 30898-0.32-0.07316960.190.04 1 Whipple results from J. Kildea (NSpace)

26 VERITAS Collaboration Meeting June 29, 2006, Leeds, UK A First Look At VERITAS Data Stephen Fegan & Vladimir Vassiliev NSpace: future work Preliminary optimization done quickly for meeting, need to look in detail at:  Ordering strategy  Array/Energy parameters  Bin size optimization  Parameter choice/Dimension Optimization 9 runs are not enough to do filter selection properly. Need lots of CRAB data and/or simulations. NSpace provides flexible and robust frame of work for data analysis including detailed spectrum analysis. Optimistic about success of this method!

Download ppt "A First Look At VERITAS Data Stephen Fegan Vladimir Vassiliev UCLA."

Similar presentations

Developing Event Reconstruction for CTA R D Parsons (Univ. of Leeds) J Hinton (Univ. of Leicester)

Developing Event Reconstruction for CTA R D Parsons (Univ. of Leeds) J Hinton (Univ. of Leicester)
Exploiting VERITAS Timing Information J. Holder a for the VERITAS Collaboration b a) School of Physics and Astronomy, University of Leeds, UK b) For full.

Exploiting VERITAS Timing Information J. Holder a for the VERITAS Collaboration b a) School of Physics and Astronomy, University of Leeds, UK b) For full.
High Energy Gamma Ray Group

High Energy Gamma Ray Group
OBSERVATIONS OF AGNs USING PACT (Pachmarhi Array of Cherenkov Telescopes) Debanjan Bose (On behalf of PACT collaboration) “The Multi-Messenger Approach.

OBSERVATIONS OF AGNs USING PACT (Pachmarhi Array of Cherenkov Telescopes) Debanjan Bose (On behalf of PACT collaboration) “The Multi-Messenger Approach.
14.5m 100 m ~480 m Junction Box ~70 m String-based detector; Downward-looking (45°) PMTs; 2475 m deep; 12 detection lines 25 storeys / line 3 PMTs / storey.

14.5m 100 m ~480 m Junction Box ~70 m String-based detector; Downward-looking (45°) PMTs; 2475 m deep; 12 detection lines 25 storeys / line 3 PMTs / storey.
Beam-Beam Effects for FCC-ee at Different Energies: at Different Energies: Crab Waist vs. Head-on Dmitry Shatilov BINP, Novosibirsk FCC-ee/TLEP physics.

Beam-Beam Effects for FCC-ee at Different Energies: at Different Energies: Crab Waist vs. Head-on Dmitry Shatilov BINP, Novosibirsk FCC-ee/TLEP physics.
Air Shower Simulations for ANITA K. Belov UCLA. Goals Approach Estimate the energy of the UHECRs detected by ANITA using MC simulations Use well known.

Air Shower Simulations for ANITA K. Belov UCLA. Goals Approach Estimate the energy of the UHECRs detected by ANITA using MC simulations Use well known.
Stereo Spectrum of UHECR Showers at the HiRes Detector  The Measurement Technique  Event Reconstruction  Monte Carlo Simulation  Aperture Determination.

Stereo Spectrum of UHECR Showers at the HiRes Detector  The Measurement Technique  Event Reconstruction  Monte Carlo Simulation  Aperture Determination.
Eyes for Relighting Extracting environment maps for use in integrating and relighting scenes (Noshino and Nayar)

Eyes for Relighting Extracting environment maps for use in integrating and relighting scenes (Noshino and Nayar)
1Andrea Caliandro Search of Optimized Cuts for Pulsar Detection Andrea Caliandro - INFN Bari DC2 CloseOut May 31 2006 Goddard Space Flight Center.

1Andrea Caliandro Search of Optimized Cuts for Pulsar Detection Andrea Caliandro - INFN Bari DC2 CloseOut May Goddard Space Flight Center.
Off-axis Simulations Peter Litchfield, Minnesota  What has been simulated?  Will the experiment work?  Can we choose a technology based on simulations?

Off-axis Simulations Peter Litchfield, Minnesota  What has been simulated?  Will the experiment work?  Can we choose a technology based on simulations?
Energy Reconstruction Algorithms for the ANTARES Neutrino Telescope J.D. Zornoza 1, A. Romeyer 2, R. Bruijn 3 on Behalf of the ANTARES Collaboration 1.

Energy Reconstruction Algorithms for the ANTARES Neutrino Telescope J.D. Zornoza 1, A. Romeyer 2, R. Bruijn 3 on Behalf of the ANTARES Collaboration 1.
Characterization of Orbiting Wide-angle Light-collectors (OWL) By: Rasha Usama Abbasi.

Characterization of Orbiting Wide-angle Light-collectors (OWL) By: Rasha Usama Abbasi.
Source detection at Saclay Look for a fast method to find sources over the whole sky Provide list of positions, allowing to run maximum likelihood locally.

Source detection at Saclay Look for a fast method to find sources over the whole sky Provide list of positions, allowing to run maximum likelihood locally.
On A Large Array Of Midsized Telescopes Stephen Fegan Vladimir Vassiliev UCLA.

On A Large Array Of Midsized Telescopes Stephen Fegan Vladimir Vassiliev UCLA.
Sean Grullon with Gary Hill Maximum likelihood reconstruction of events using waveforms.

Sean Grullon with Gary Hill Maximum likelihood reconstruction of events using waveforms.
1 Tracking Reconstruction Norman A. Graf SLAC July 19, 2006.

1 Tracking Reconstruction Norman A. Graf SLAC July 19, 2006.
Monte Carlo Comparison of RPCs and Liquid Scintillator R. Ray 5/14/04  RPCs with 1-dimensional readout (generated by RR) and liquid scintillator with.

Monte Carlo Comparison of RPCs and Liquid Scintillator R. Ray 5/14/04  RPCs with 1-dimensional readout (generated by RR) and liquid scintillator with.
Five principles of design (in fast forward) You can find this and other helpful PowerPoints on my teacher web site at Hillsboro R-3 under teacher web sites.

Five principles of design (in fast forward) You can find this and other helpful PowerPoints on my teacher web site at Hillsboro R-3 under teacher web sites.
Outrigger Timing Calibration & Reconstruction Milagro – 11/17/03 Shoup – 1 Purpose: To incorporate outrigger hits in event angle fitting Additionally incorporated.

Outrigger Timing Calibration & Reconstruction Milagro – 11/17/03 Shoup – 1 Purpose: To incorporate outrigger hits in event angle fitting Additionally incorporated.

Similar presentations

Ads by Google