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)

CTA Aims

CTA aims to improve sensitivity by an order of magnitude over HESS

Aims to improve angular resolution by a factor of three

This can be achieved by: More Telescopes Larger field of view Multiple telescope types Improved Analysis

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2

Candidate Array3

Candidate Array:

4 x Large Telescopes (23m)

23 x Medium Telescopes (12m)

32 x Small Telescopes (6m)

Telescopes are single dish reflectors, with a PMT camera

Lookup based reconstruction

Need to reconstruct core and source position (Alt, Az, X and Y)

Standard direction reconstruction uses only the orientation of camera images

More information can be included to improve reconstruction

Extra parameters: Time Gradient Image Displacement Concentration Energy Consistency

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Time Gradient5

CTA will be able to record the trigger times on individual pixels

Images move across the camera as the shower develops

Produces a gradient across the integrated image

This gradient is proportional to the distance from the core

VERITAS Events

Time Gradient6

Light from B travels furtherArrives later

Particles travel faster than speed of light in airLight from B arrives earlier

A A

BB

χ2 Contributions

Expected values (μ) and errors (σexp) of parameters (for gammas) are found from MC simulations

The measured value (x) can then be compared with that expected at a trial core location

Expected error can then be compared with that measured

A χ2 contribution can then be made for each parameter

χ2 = (x – μ) / σexp

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MeasuredDirection

ExpectedDirection

Lookup tables

Lookup tables are filled with expected values

Lookups are based on dependent measurables

Tables are smoothed and extended

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Finding the Minimum

A summed chi-squared value can be found for a trial X ,Y, Alt and Az

This defines a 4D Chi-squared space

Best fit shower axis lies at the minimum of this surface

Use ‘Rolling function’ to find the minimum point

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Events (Ground Plane)10

StandardReconstruction

TruePosition

LU based Reconstruction

Events (Sky Plane)11

Standard Reconstruction

Lookup Based Reconstruction15-20% improvement

Performance (Preliminary)12

Performance (Preliminary)13

Lookup Based Reconstruction20% Sensitivity Gain

Standard Reconstruction

5 σ Detection50h ObservationMin 10 Events1% Background Systematics

Performance (Preliminary)14

Lookup Based Reconstruction20% Sensitivity Gain

Goal Sensitivity

5 σ Detection50h ObservationMin 10 Events1% Background Systematics

Maximum Likelihood

For most parameters the errors are non-gaussian

Hence the chi-squared value is not valid

Will cause problems in estimation of error on the shower axis

Instead the maximum likelihood estimator will be used

Requires an extra dimension in lookups

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Summary

CTA will provide large improvements in both sensitivity and angular resolution

The current reconstruction method is not optimised for a large array

15-20 % improvements in sensitivity have been gained from improved reconstruction

Even larger gains may be achievable

Further refinements to reconstruction Switch to maximum likelihood estimator Introduce weighting of contributions Combine with multi-variate analysis

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Simulation Chain17

Angular Resolution 18