Spatial-angular distribution of EAS Cherenkov light as a key to the primary cosmic ray composition at 10 15 – 10 17 eV Vladimir I. Galkin Faculty of Physics.

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Spatial-angular distribution of EAS Cherenkov light as a key to the primary cosmic ray composition at – eV Vladimir I. Galkin Faculty of Physics of MSU and SINP MSU May 18, 2011

2 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV Mass Composition an important characteristic of PCR needed for the solution of many astrophysical problems; below 1 PeV it can be studied directly using the satellite-borne and balloon-borne detectors; above ~1 PeV one has to use indirect methods of EAS detection to study the PCR mass composition ; at super high energies (~1-100 PeV) our knowledge of PCR m.c. is very limited and inaccurate, in spite of many efforts made and resources spent; mostly the data on the mean mass number A are available with the uncertainty of about an order of magnitude at the knee region.

World Data on * World Data on * * Y. Tsunesada, et al., Proc 30th ICRC (Merida), 4, 127 (2008)

4May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV Possible reasons for the discrepancy Points to be considered first: Points to be considered first: large spread of data & small size of the indicated errors (probably statistical) suggest that systematical errors were underestimated => syst.errors should be made clear; large spread of data & small size of the indicated errors (probably statistical) suggest that systematical errors were underestimated => syst.errors should be made clear; parameters measured are not sensitive enough to A due to the stochastic nature of the EAS and the measurement process (impossible to separate different nuclei on event-by-event basis) => we should look for more sensitive measures of A ; parameters measured are not sensitive enough to A due to the stochastic nature of the EAS and the measurement process (impossible to separate different nuclei on event-by-event basis) => we should look for more sensitive measures of A ; the observables are processed using simplified models which leads to partial loss of information on A => direct correlations observable – A should be used. the observables are processed using simplified models which leads to partial loss of information on A => direct correlations observable – A should be used. In many cases the position X max of the cascade curve maximum is used as the only measure of A.

5May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV X max drawbacks X max bears only a part of information contained in the cascade curve; X max bears only a part of information contained in the cascade curve; X max is not measured directly, it is not even directly derived from detector data (simulati- ons are involved) => it is an intermediate (virtual) variable. X max is not measured directly, it is not even directly derived from detector data (simulati- ons are involved) => it is an intermediate (virtual) variable. Both points lead to the information losses. Both points lead to the information losses. Cascade curve is ruled by: E 0, A and N-N interaction model

6May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV Cherenkov Light Advantages & Drawbacks Advantages: Advantages: the number of Ch. photons is large ( times greater) in comparison with the charged particle number at the observation level; Ch. emission is directed (as compared to fluorescent light); it is directly related to the shower charged particles; sc. & abs. m.f.p. for optical photons in the atmosphere can amount to a few km => one can measure CL distributions in space, direction and time which gives rich information on EAS. Drawbacks: Drawbacks: EAS CL detection is only possible on clear moonless nights which is typically only ~10% of the total time; purity of the atmosphere and the level of light background may be critical to EAS detection with CL.

7May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV Spatial-angular distribution of EAS CL Expression for EAS CL SAD in the detector coordinate system. N(…) is EAS charged particle SAD function This is to confirm that CL SAD and particle SAD are closely connected => this connection gives us a number of possibilities.

8May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV EAS CL SAD simulation a search for new EAS CL parameters was made on the basis of full MC simulation of CL SAD & spatial-temporal (ST) distribution using CORSIKA 6.50 (QGSJET I & QGSJET II); vertical showers initiated by 1 and 10 PeV nuclei (p, He, N, S, Fe) observed at 1, 2 and 4 km altitude (sample volume = 50) were simulated; SAD was recorded within (250m x 250m) area averaged over (2m x 2m) squares and within (40° x 40°) FOV centered at zenith averaged over (0.5° x 0.5°) pixels; STD was recorded in the same spatial domain in 100 temporal bins (1 bin = 2 nS); shower cores hit the center of the spatial domain. see see V. I. Galkin and T. A. Dzhatdoev, Bull. of RAS. Physics, 2011, Vol. 75, No. 3, pp. 309–312 for details.

9May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV CL SAD measures of A From the experimental point of view CL SAD is a set of angular images seen at different core distances R. We used images at R = 50, 100, 150, 200 m. We used classical and newly constructed parameters of the EAS CL angular images as measures of the mass number A. classics new D – distance from arr.direction to the image c.m., L – half-length, W – half-width, Conc – concentration parameter (see Aharonian, F.A., Bugayov, V.V., Kettler, J., et al., Nucl. Inst. Meth. Phys. Res. B, 2003, v. 201, pp. 217– 229.) k – asymmetry parameter, η – steepness parameter

10May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV CL SAD criteria for primary nuclei separation Sets of shape parameters of EAS images at different R form the feature vectors used in multidimensional normal Bayesian classification scheme. Feature space dimension varied from 2 (2 parameters x 1 telescope) to 16 (4 parameters x 4 telescopes) Even a 2-dim k- η scheme can separate p and N with ~10% error Another 2-dim k-η scheme can select 38% of protons with less than 1% contamination by He

11May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV CL SAD criteria for primary nuclei separation Higher dimensions give better mass resolution (lower classification errors) but require more experimental data per shower New parameters (k & η ) proved to be more adjustable to the task stated The following is the comparison of the two 8-dim schemes: The following is the comparison of the two 8-dim schemes: {(D+L) x 4 telescopes} and {(k+ η ) x 4 telescopes} {(D+L) x 4 telescopes} and {(k+ η ) x 4 telescopes} true masses deduced masses true masses deduced masses V. I. Galkin and T. A. Dzhatdoev, Moscow University Physics Bulletin, 2010, Vol. 65, No. 3, pp. 195–202.

12May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV Background & pixel calibration error effects on the selection results application of normal (~ m -2 s -1 sr -1 ) starlight background does not change the classification errors (p-N, E 0 =1-10 PeV, mirror: 2m x 2m); high background (~ m -2 s -1 sr -1 ) increases the errors by 3-5% (16-dim, h obs =2km, time gates: 50 nS); effect of pixel calibration errors was simulated as follows: a) errors ±δ were applied randomly to the pixels of 80x80 array, b) event selection was carried out with the perturbed matrix yielding new classification errors, c) classification errors were averaged over 100 randomly perturbed pixel arrays; classification errors (p-N, E 0 =1 PeV, h obs =2km) increase by: 8% (p->N) and 1.8% (N->p) for δ=5%, 3.9% (p->N) and 1.2% (N->p) for δ=3%, 1% (p->N) and 0.1% (N->p) for δ=1%.

13May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV How to measure PCR masses using EAS CL SAD ? To use the developed selection criteria one needs: - a set of 3-4 wide-angle telescopes (at least 20° x 20° FOV, 0.5°-0.8°Ø pixels, 2-4m 2 mirror) for correct processing of EAS images, - a grid of fast wide-angle detectors to determine E 0, arrival direction and core location. Evaluation of SAD measures requires the knowledge of the arrival direction with the accuracy ~0.1° (fast detectors). Telescopes should be set ~100m apart to observe EAS from different R. Fast detector grid with ~30m cell can also measure CL lateral distribution shape parameters sensitive to A. All detectors should be equally aimed.

14May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV Possible layout

15May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeVConclusions Solution of PCR composition problem at super high energies requires the acquisition of a large volume of data on each EAS EAS CL SAD can help provided we construct an appropriate instrument The instrument should incorporate a few wide-angle telescopes and a dense network of fast optical detectors Experimental data processing should avoid the use of simple models and intermediate parameters, direct correlations observable-A must be used Systematic errors are of vital importance for indirect methods of PCR study

16May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV MANY THANKS

17May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV

18May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV Угловое распределение ЧС ШАЛ от различных ядер Искусственные угловые образы Схема сбора света детектором Уровень наблюдения --- 1км

19May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV Особенности угловых распределений ЧС ШАЛ с энергиями эВ С точки зрения эксперимента ПУР ЧС ШАЛ можно представить как совокупность угловых образов одного и того же ливня (одновременно зарегистрированных несколькими угловыми телескопами) С точки зрения эксперимента ПУР ЧС ШАЛ можно представить как совокупность угловых образов одного и того же ливня (одновременно зарегистрированных несколькими угловыми телескопами) Характерные угловые масштабы, на которых проявляются различия угловых образов ЧС ШАЛ от разных первичных ~0,5° Характерные угловые масштабы, на которых проявляются различия угловых образов ЧС ШАЛ от разных первичных ~0,5° Чем выше уровень наблюдения, тем больше угловые размеры образов (несколько градусов). Чем выше уровень наблюдения, тем больше угловые размеры образов (несколько градусов). Большие угловые размеры образов требуют большого поля зрения телескопов: как минимум, 20° х 20° при умеренном размере пиксела (от 0,5 до 1,0°, в зависимости от уровня наблюдения) Большие угловые размеры образов требуют большого поля зрения телескопов: как минимум, 20° х 20° при умеренном размере пиксела (от 0,5 до 1,0°, в зависимости от уровня наблюдения) Для эффективного использования угловых образов для определения А направление прихода ливня и точка падения оси должны быть известны с хорошей точностью (~0,1° и ~нескольких метров, соответственно) Для эффективного использования угловых образов для определения А направление прихода ливня и точка падения оси должны быть известны с хорошей точностью (~0,1° и ~нескольких метров, соответственно) Для восстановления энергии, направления и положения оси естественно использовать пространственно-временное распределение ЧС, хотя направление может быть неплохо восстановлено и по самим угловым образам Для восстановления энергии, направления и положения оси естественно использовать пространственно-временное распределение ЧС, хотя направление может быть неплохо восстановлено и по самим угловым образам

20May 18, 2011 V.I. Galkin: SAD of EAS CL as a key to the PCR composition at PeV Индивидуальные угловые распределения ЧС нескольких ШАЛ на расстоянии 100 м от оси, проинтегрированные вдоль короткой оси (по θ y в интервале от -δθ y до +δθ y ) красныекривые- протоны, красные кривые- протоны, черныекривые- ядра азота, черные кривые- ядра азота, δθ y = 1.5 град δθ y = 1.5 град градусы