Studies on mass sensitive parameters and monitoring of the ... · Mass Composition of UHECR X max measurements above 1017 eV Alessio Porcelli Figure 4: The mean (left) and standard

Studies on mass sensitive parameters and monitoring of the operation of the surface detector with data of the

Pierre Auger Observtory

XXXIReuniónAnualdelaDivisióndePar3culasyCamposdelaSMF24-16May2017

CINVESTAV-ZACATENCOMexicoCity

KarenSaloméCaballeroMoraUNACH

! !

Outlook

• Mass composition and New Physics • The Pierre Auger Observatory

• Mass composition with Risetime t1/2 • A new parameter based on t1/2: Rchis • Status of the study

• Monitoring SD with direct light on PMTs in time • Direct light • Characteristic line

1/20Karen S. Caballero Mora UNACH [email protected]

Mass Composition and new PhysicsNeededtounderstand:CROrigin,acceleraTonandpropagaTon

mechanismsFeedbackwithelementaryparTclesinteracTonsathighenergies

Theory:

Experiment:Mixture or heavy

1.3 Acceleration mechanisms and propagation of cosmic rays

(a)

extragal. proton

galactic iron

Energy [eV]

1016 1017 1018 1019 1020

100

101

102

103

Flu

x E

2.5 J

(E)

[m

-2 s-1

sr-1

Ge

V1

.5]

(b)

Figure 1.2: (a) The extra-galactic mixed composition scenario (taken from [35] and modified). (b) Thedip model taken from [40].

10-1

100

101

102

103

104

105

106

1018 1019 1020 1021 1022 1022 1023

energ

y loss

length

E

ds/dE

(M

pc)

E (eV)

protons, full model (H = 75 km/s/Mpc, z=0)

loss lengthhadron prod.

e+ e- pair prod.neutron decay lengthadiabatic expansion

Figure 1.3: Energy loss length for extra-galactic cosmic ray propagation [46].

1.3 Acceleration mechanisms and propagation of cosmic rays

Acceleration of cosmic rays is usually explained with the first-order Fermi acceleration, alsoknown as Diffusive Shock Acceleration (DSA), in shocks produced by astrophysical objects.

7

Mixture or light

Dipmodel.V.Berezinsky30thICRC(2007),arXiv:0710.2750 2/20Karen S. Caballero Mora UNACH [email protected]

Mass Composition and new PhysicsNeededtounderstand:CROrigin,acceleraTonandpropagaTon

mechanismsFeedbackwithelementaryparTclesinteracTonsathighenergies

Theory:

Experiment:Mixture or heavy

Mixture or light

Xmax measurements above 1017 eV Alessio Porcelli

Figure 4: The mean (left) and standard deviation (right) of measured Xmax distributions of the two indepen-dent datasets: HeCo (blue circles) and the standard FD (red squares).

Figure 5: The mean (left) and the standard deviation (right) of the measured Xmax distributions (combiningHeCo and standard datasets) as a function of energy compared to air-shower simulations for proton and ironprimaries.

2.4 Results and Interpretation

In Figure 4 the Xmax moments estimated using HeCo and the standard FD datasets are com-pared. While hXmaxi differs by ⇠ 7 g cm�2 between datasets (within the uncorrelated systematicsof the two analyses), the second moments s(Xmax) are found to be in a good agreement. For thecombination of the datasets the HeCO hXmaxi is shifted by +7 g cm�2 and the resulting hXmaxi ands(Xmax) are shown in Figure 5.

Between 1017.0 and 1018.3 eV hXmaxi increases by around 85 g cm�2 per decade of energy(Figure 5, left). This value, being larger than the one expected for a constant mass composition(⇠ 60 g cm�2/decade), indicates that the mean primary mass is getting lighter. Around ⇡ 1018.3 eVthe observed rate of change of hXmaxi becomes significantly smaller (⇠ 26 g cm�2/decade) indi-cating that the composition is becoming heavier. The fluctuations of Xmax (Figure 5, right) start todecrease at around the same energy ⇡ 1018.3 eV.

The mean value of lnA and its variance s

2(lnA), determined from Equations (1.1) and (1.2),

45

OBSERVATORY

The Pierre Auger Observatory: Contributions to the 34thInternational Cosmic Ray Conference (ICRC 2015)

The Pierre Auger Collaboration

A. Aab41, P. Abreu65, M. Aglietta52, E.J. Ahn80, I. Al Samarai28, I.F.M. Albuquerque16,I. Allekotte1, P. Allison85, A. Almela11,8, J. Alvarez Castillo58, J. Alvarez-Muniz75, R. AlvesBatista40, M. Ambrosio43, A. Aminaei59, G.A. Anastasi45, L. Anchordoqui79, S. Andringa65,C. Aramo43, F. Arqueros72, N. Arsene68, H. Asorey1,24, P. Assis65, J. Aublin30, G. Avila10,N. Awal83, A.M. Badescu69, C. Baus35, J.J. Beatty85, K.H. Becker34, J.A. Bellido12, C. Berat31,M.E. Bertaina52, X. Bertou1, P.L. Biermann38, P. Billoir30, S.G. Blaess12, A. Blanco65,M. Blanco30, J. Blazek26, C. Bleve47, H. Blumer35,36, M. Bohacova26, D. Boncioli51, C. Bonifazi22,N. Borodai63, J. Brack78, I. Brancus66, T. Bretz39, A. Bridgeman36, P. Brogueira65, P. Buchholz41,A. Bueno74, S. Buitink59, M. Buscemi43, K.S. Caballero-Mora56, B. Caccianiga42, L. Caccianiga30,M. Candusso44, L. Caramete67, R. Caruso45, A. Castellina52, G. Cataldi47, L. Cazon65, R. Cester46,A.G. Chavez57, A. Chiavassa52, J.A. Chinellato17, J. Chudoba26, M. Cilmo43, R.W. Clay12,G. Cocciolo47, R. Colalillo43, A. Coleman86, L. Collica42, M.R. Coluccia47, R. Conceicao65,F. Contreras9, M.J. Cooper12, A. Cordier29, S. Coutu86, C.E. Covault76, J. Cronin87, R. Dallier33,32,B. Daniel17, S. Dasso5,3, K. Daumiller36, B.R. Dawson12, R.M. de Almeida23, S.J. de Jong59,61,G. De Mauro59, J.R.T. de Mello Neto22, I. De Mitri47, J. de Oliveira23, V. de Souza15, L. delPeral73, O. Deligny28, N. Dhital82, C. Di Giulio44, A. Di Matteo48, J.C. Diaz82, M.L. DıazCastro17, F. Diogo65, C. Dobrigkeit17, W. Docters60, J.C. D’Olivo58, A. Dorofeev78, Q. DorostiHasankiadeh36, R.C. dos Anjos15, M.T. Dova4, J. Ebr26, R. Engel36, M. Erdmann39, M. Erfani41,C.O. Escobar80,17, J. Espadanal65, A. Etchegoyen8,11, H. Falcke59,62,61, K. Fang87, G. Farrar83,A.C. Fauth17, N. Fazzini80, A.P. Ferguson76, B. Fick82, J.M. Figueira8, A. Filevich8, A. Filipcic70,71,O. Fratu69, M.M. Freire6, T. Fujii87, B. Garcıa7, D. Garcıa-Gamez29, D. Garcia-Pinto72,F. Gate33, H. Gemmeke37, A. Gherghel-Lascu66, P.L. Ghia30, U. Giaccari22, M. Giammarchi42,M. Giller64, D. Głas64, C. Glaser39, H. Glass80, G. Golup1, M. Gomez Berisso1, P.F. GomezVitale10, N. Gonzalez8, B. Gookin78, J. Gordon85, A. Gorgi52, P. Gorham88, P. Gouffon16,N. Griffith85, A.F. Grillo51, T.D. Grubb12, F. Guarino43, G.P. Guedes18, M.R. Hampel8, P. Hansen4,D. Harari1, T.A. Harrison12, S. Hartmann39, J.L. Harton78, A. Haungs36, T. Hebbeker39,D. Heck36, P. Heimann41, A.E. Herve36, G.C. Hill12, C. Hojvat80, N. Hollon87, E. Holt36,P. Homola34, J.R. Horandel59,61, P. Horvath27, M. Hrabovsky27,26, D. Huber35, T. Huege36,A. Insolia45, P.G. Isar67, I. Jandt34, S. Jansen59,61, C. Jarne4, J.A. Johnsen77, M. Josebachuili8,A. Kaapa34, O. Kambeitz35, K.H. Kampert34, P. Kasper80, I. Katkov35, B. Keilhauer36,E. Kemp17, R.M. Kieckhafer82, H.O. Klages36, M. Kleifges37, J. Kleinfeller9, R. Krause39,N. Krohm34, D. Kuempel39, G. Kukec Mezek71, N. Kunka37, A.W. Kuotb Awad36, D. LaHurd76,L. Latronico52, R. Lauer90, M. Lauscher39, P. Lautridou33, S. Le Coz31, D. Lebrun31, P. Lebrun80,M.A. Leigui de Oliveira21, A. Letessier-Selvon30, I. Lhenry-Yvon28, K. Link35, L. Lopes65,R. Lopez53, A. Lopez Casado75, K. Louedec31, A. Lucero8, M. Malacari12, M. Mallamaci42,J. Maller33, D. Mandat26, P. Mantsch80, A.G. Mariazzi4, V. Marin33, I.C. Maris74, G. Marsella47,D. Martello47, H. Martinez54, O. Martınez Bravo53, D. Martraire28, J.J. Masıas Meza3,H.J. Mathes36, S. Mathys34, J. Matthews81, J.A.J. Matthews90, G. Matthiae44, D. Maurizio13,E. Mayotte77, P.O. Mazur80, C. Medina77, G. Medina-Tanco58, R. Meissner39, V.B.B. Mello22,D. Melo8, A. Menshikov37, S. Messina60, M.I. Micheletti6, L. Middendorf39, I.A. Minaya72,L. Miramonti42, B. Mitrica66, L. Molina-Bueno74, S. Mollerach1, F. Montanet31, C. Morello52,M. Mostafa86, C.A. Moura21, G. Muller39, M.A. Muller17,20, S. Muller36, S. Navas74, P. Necesal26,

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Mass Composition of UHECR

Xmax measurements above 1017 eV Alessio Porcelli

Figure 4: The mean (left) and standard deviation (right) of measured Xmax distributions of the two indepen-dent datasets: HeCo (blue circles) and the standard FD (red squares).

Figure 5: The mean (left) and the standard deviation (right) of the measured Xmax distributions (combiningHeCo and standard datasets) as a function of energy compared to air-shower simulations for proton and ironprimaries.

2.4 Results and Interpretation

In Figure 4 the Xmax moments estimated using HeCo and the standard FD datasets are com-pared. While hXmaxi differs by ⇠ 7 g cm�2 between datasets (within the uncorrelated systematicsof the two analyses), the second moments s(Xmax) are found to be in a good agreement. For thecombination of the datasets the HeCO hXmaxi is shifted by +7 g cm�2 and the resulting hXmaxi ands(Xmax) are shown in Figure 5.

Between 1017.0 and 1018.3 eV hXmaxi increases by around 85 g cm�2 per decade of energy(Figure 5, left). This value, being larger than the one expected for a constant mass composition(⇠ 60 g cm�2/decade), indicates that the mean primary mass is getting lighter. Around ⇡ 1018.3 eVthe observed rate of change of hXmaxi becomes significantly smaller (⇠ 26 g cm�2/decade) indi-cating that the composition is becoming heavier. The fluctuations of Xmax (Figure 5, right) start todecrease at around the same energy ⇡ 1018.3 eV.

The mean value of lnA and its variance s

2(lnA), determined from Equations (1.1) and (1.2),

45

OBSERVATORY

The Pierre Auger Observatory: Contributions to the 34thInternational Cosmic Ray Conference (ICRC 2015)

The Pierre Auger Collaboration

A. Aab41, P. Abreu65, M. Aglietta52, E.J. Ahn80, I. Al Samarai28, I.F.M. Albuquerque16,I. Allekotte1, P. Allison85, A. Almela11,8, J. Alvarez Castillo58, J. Alvarez-Muniz75, R. AlvesBatista40, M. Ambrosio43, A. Aminaei59, G.A. Anastasi45, L. Anchordoqui79, S. Andringa65,C. Aramo43, F. Arqueros72, N. Arsene68, H. Asorey1,24, P. Assis65, J. Aublin30, G. Avila10,N. Awal83, A.M. Badescu69, C. Baus35, J.J. Beatty85, K.H. Becker34, J.A. Bellido12, C. Berat31,M.E. Bertaina52, X. Bertou1, P.L. Biermann38, P. Billoir30, S.G. Blaess12, A. Blanco65,M. Blanco30, J. Blazek26, C. Bleve47, H. Blumer35,36, M. Bohacova26, D. Boncioli51, C. Bonifazi22,N. Borodai63, J. Brack78, I. Brancus66, T. Bretz39, A. Bridgeman36, P. Brogueira65, P. Buchholz41,A. Bueno74, S. Buitink59, M. Buscemi43, K.S. Caballero-Mora56, B. Caccianiga42, L. Caccianiga30,M. Candusso44, L. Caramete67, R. Caruso45, A. Castellina52, G. Cataldi47, L. Cazon65, R. Cester46,A.G. Chavez57, A. Chiavassa52, J.A. Chinellato17, J. Chudoba26, M. Cilmo43, R.W. Clay12,G. Cocciolo47, R. Colalillo43, A. Coleman86, L. Collica42, M.R. Coluccia47, R. Conceicao65,F. Contreras9, M.J. Cooper12, A. Cordier29, S. Coutu86, C.E. Covault76, J. Cronin87, R. Dallier33,32,B. Daniel17, S. Dasso5,3, K. Daumiller36, B.R. Dawson12, R.M. de Almeida23, S.J. de Jong59,61,G. De Mauro59, J.R.T. de Mello Neto22, I. De Mitri47, J. de Oliveira23, V. de Souza15, L. delPeral73, O. Deligny28, N. Dhital82, C. Di Giulio44, A. Di Matteo48, J.C. Diaz82, M.L. DıazCastro17, F. Diogo65, C. Dobrigkeit17, W. Docters60, J.C. D’Olivo58, A. Dorofeev78, Q. DorostiHasankiadeh36, R.C. dos Anjos15, M.T. Dova4, J. Ebr26, R. Engel36, M. Erdmann39, M. Erfani41,C.O. Escobar80,17, J. Espadanal65, A. Etchegoyen8,11, H. Falcke59,62,61, K. Fang87, G. Farrar83,A.C. Fauth17, N. Fazzini80, A.P. Ferguson76, B. Fick82, J.M. Figueira8, A. Filevich8, A. Filipcic70,71,O. Fratu69, M.M. Freire6, T. Fujii87, B. Garcıa7, D. Garcıa-Gamez29, D. Garcia-Pinto72,F. Gate33, H. Gemmeke37, A. Gherghel-Lascu66, P.L. Ghia30, U. Giaccari22, M. Giammarchi42,M. Giller64, D. Głas64, C. Glaser39, H. Glass80, G. Golup1, M. Gomez Berisso1, P.F. GomezVitale10, N. Gonzalez8, B. Gookin78, J. Gordon85, A. Gorgi52, P. Gorham88, P. Gouffon16,N. Griffith85, A.F. Grillo51, T.D. Grubb12, F. Guarino43, G.P. Guedes18, M.R. Hampel8, P. Hansen4,D. Harari1, T.A. Harrison12, S. Hartmann39, J.L. Harton78, A. Haungs36, T. Hebbeker39,D. Heck36, P. Heimann41, A.E. Herve36, G.C. Hill12, C. Hojvat80, N. Hollon87, E. Holt36,P. Homola34, J.R. Horandel59,61, P. Horvath27, M. Hrabovsky27,26, D. Huber35, T. Huege36,A. Insolia45, P.G. Isar67, I. Jandt34, S. Jansen59,61, C. Jarne4, J.A. Johnsen77, M. Josebachuili8,A. Kaapa34, O. Kambeitz35, K.H. Kampert34, P. Kasper80, I. Katkov35, B. Keilhauer36,E. Kemp17, R.M. Kieckhafer82, H.O. Klages36, M. Kleifges37, J. Kleinfeller9, R. Krause39,N. Krohm34, D. Kuempel39, G. Kukec Mezek71, N. Kunka37, A.W. Kuotb Awad36, D. LaHurd76,L. Latronico52, R. Lauer90, M. Lauscher39, P. Lautridou33, S. Le Coz31, D. Lebrun31, P. Lebrun80,M.A. Leigui de Oliveira21, A. Letessier-Selvon30, I. Lhenry-Yvon28, K. Link35, L. Lopes65,R. Lopez53, A. Lopez Casado75, K. Louedec31, A. Lucero8, M. Malacari12, M. Mallamaci42,J. Maller33, D. Mandat26, P. Mantsch80, A.G. Mariazzi4, V. Marin33, I.C. Maris74, G. Marsella47,D. Martello47, H. Martinez54, O. Martınez Bravo53, D. Martraire28, J.J. Masıas Meza3,H.J. Mathes36, S. Mathys34, J. Matthews81, J.A.J. Matthews90, G. Matthiae44, D. Maurizio13,E. Mayotte77, P.O. Mazur80, C. Medina77, G. Medina-Tanco58, R. Meissner39, V.B.B. Mello22,D. Melo8, A. Menshikov37, S. Messina60, M.I. Micheletti6, L. Middendorf39, I.A. Minaya72,L. Miramonti42, B. Mitrica66, L. Molina-Bueno74, S. Mollerach1, F. Montanet31, C. Morello52,M. Mostafa86, C.A. Moura21, G. Muller39, M.A. Muller17,20, S. Muller36, S. Navas74, P. Necesal26,

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Mixed mass composition compared with hadronic interaction models


The Pierre Auger Observatory

SD

FD

+AMIGA +Radio (AERA) Loma Amarilla

+Heat Coihueco

Leones Morados

Area of 3000 km2

24 fluorescence telescopes in 4 sites (FD) 1660 surface detector (SD) stations


Mass composition sensitive parameters in Auger

SD

Radius of curvature (Rc)

Muon fraction (average values based on simulations or event by event)

Muon/electron ratio

Muon production depth

Xmax

Risetime, t1/2 (Asymmetry parameter, Deltas, fluctuations)

Multivariable analysis (mean based) 6/20

Karen S. Caballero Mora UNACH [email protected]

SDGoals: Mass Composition Improve sensitivity to proton contribution EAS and hadronic interactions at high energies

Upgrades: Surface Scintillator Detector (SSD) Substitution of current electronics AMIGA Extension of duty cycle of FD

Primary cosmic Ray Identification with Muons and Electrons

C. Di Giulio et al. / Nuclear Physics B Proceedings Supplement 00 (2015) 1–8 4

PoS(ICRC2015)686

Upgrade of the Auger Observatory Ralph Engel

allow an increase of about 50% in the current duty cycle of the FD.

3. Expected physics performance

In the following we consider different levels of complexity of the information derived fromshower data. We first discuss the reconstruction of the muonic shower component, then show thediscrimination power for different primary particles, and finally analyze Monte Carlo generatedevent samples to test the sensitivity to different physics scenarios. As a generic measure of dis-crimination power for separating primary i and j using the corresponding observables Si and S j

(with the RMS � ) we use the merit factor

fMF =|�Si��S j�|�

�(Si)2 +�(S j)2. (3.1)

3.1 Event based observables

18

ProtonIron

(E/eV)10

log18.8 19 19.2 19.4 19.6 19.8 20

µ)/N

µ- N

, rec

µ(N

-0.3

-0.2

-0.1

0

0.1

0.2

0.3p

He

N

Fe

Figure 2: Left panel: Reconstruction bias (solid symbols) and resolution (open symbols) of the muonicsignal contribution for individual detector stations, as a function of distance r from the shower core. Theresults for proton and iron showers are shown in red and blue, respectively. Right panel: Number of muonsNµ reconstructed for individual showers using shower universality, compared with the true Nµ as a functionof energy for different primary species. Error bars represent the RMS of the distributions.

The least model-dependent and most direct composition-sensitive observable that can be ob-tained from the upgraded detector array is the number of muons (or, equivalent to it, the muonicsignal in the WCD) in individual detector stations. Thanks to the signal responses in the SSD(SSSD) and the WCD (SWCD) to particles of the electromagnetic and muonic shower components,it is possible to derive the muonic signal Sµ,WCD on a station-by-station basis, as described in [13],from

Sµ,WCD = aSWCD + bSSSD, (3.2)

where the signals are measured in units of the response to a vertical equivalent muon (VEM) orminimum ionizing particle (MIP), respectively. The factors a and b are derived from detector simu-lation and have only a very weak dependence on the primary composition and lateral distance from

4

Figure 7: Reconstruction bias (solid symbols) and resolution (opensymbols) of the muonic signal contribution for individual detector sta-tions, as a function of distance r from the shower core. The results forproton and iron showers are shown in red and blue, respectively.

.

shower core, as in figure 7 where the bias on the muonic133

reconstructed signal and the e↵ect on the resolution are134

shown. Restricted by the limited size of an individual135

detector station, this method is subject to large fluctu-136

ations and is only well suited for deriving mean muon137

numbers, see figure 8.138

Fitting the lateral distribution function (LDF) is pos-139

sible to improve the performance of the reconstruction140

of the muonic signal. Eq. 1 is then applied to the LDF141

values for the WCD and SSD to calculate the muonic142

signal at 800 m core distance, Sµ(800).143

For example at energy of E=1019.8 eV at ✓ = 38�144

the reconstruction resolutions of the muonic signal are:145

�(S µ(800))hS µ(800)i = 22% for protons and 14% for iron.146

Defining the merit factor as the measure of discrim-147

ination power for separating primary i and j using the148

corresponding observables Si and S j (with the RMS �)149

as:150

fMF =

��hS ii � hS ji��

q�(S i)

2 + �(S j)2

(2)151

using Sµ(800) as a composition estimator, the merit fac-152

tor for distinguishing between proton and iron primaries153

are above 1.5 at shower energies bigger than 1019.5 eV154

and small zenith angles.155

4.3. The water-Cherenkov detector upgrade156

The WCD is a rotomolded polyethylene tank filled157

with purified water that produces Cherenkov light when158

crossed by energetic charged particles associated with159

PoS(ICRC2015)686

Upgrade of the Auger Observatory Ralph Engel

allow an increase of about 50% in the current duty cycle of the FD.

3. Expected physics performance

In the following we consider different levels of complexity of the information derived fromshower data. We first discuss the reconstruction of the muonic shower component, then show thediscrimination power for different primary particles, and finally analyze Monte Carlo generatedevent samples to test the sensitivity to different physics scenarios. As a generic measure of dis-crimination power for separating primary i and j using the corresponding observables Si and S j

(with the RMS � ) we use the merit factor

fMF =|�Si��S j�|�

�(Si)2 +�(S j)2. (3.1)

3.1 Event based observables

18

ProtonIron

(E/eV)10

log18.8 19 19.2 19.4 19.6 19.8 20

µ)/N

µ- N

, rec

µ(N

-0.3

-0.2

-0.1

0

0.1

0.2

0.3p

He

N

Fe

Figure 2: Left panel: Reconstruction bias (solid symbols) and resolution (open symbols) of the muonicsignal contribution for individual detector stations, as a function of distance r from the shower core. Theresults for proton and iron showers are shown in red and blue, respectively. Right panel: Number of muonsNµ reconstructed for individual showers using shower universality, compared with the true Nµ as a functionof energy for different primary species. Error bars represent the RMS of the distributions.

The least model-dependent and most direct composition-sensitive observable that can be ob-tained from the upgraded detector array is the number of muons (or, equivalent to it, the muonicsignal in the WCD) in individual detector stations. Thanks to the signal responses in the SSD(SSSD) and the WCD (SWCD) to particles of the electromagnetic and muonic shower components,it is possible to derive the muonic signal Sµ,WCD on a station-by-station basis, as described in [13],from

Sµ,WCD = aSWCD + bSSSD, (3.2)

where the signals are measured in units of the response to a vertical equivalent muon (VEM) orminimum ionizing particle (MIP), respectively. The factors a and b are derived from detector simu-lation and have only a very weak dependence on the primary composition and lateral distance from

4

Figure 8: Number of muons Nµ reconstructed (Nµ,rec) for individualshowers using shower universality, compared with the true Nµ as afunction of energy for di↵erent primary species. Error bars representthe RMS of the distributions.

Figure 9: First prototype of a SSD scintillator on top of a WCD.TheSSDcandisTnguishbetweentheelectromagneTcandmuoniccomponent


The SD mass composition sensitive parameter t1/2

SD

Particles arriving at ground

FADC trace of SD tank

t1/2 as mass sensitive parameter 8/20Karen S. Caballero Mora UNACH [email protected]

The SD mass composition sensitive parameter t1/2

SD

Particles arriving at ground

FADC trace of SD tank

t1/2 as mass sensitive parameter 9/20Karen S. Caballero Mora UNACH [email protected]

Study of risetime as a function of energy, zenith angle and distance to the shower core

Hernán Castellanos Valdés

Goal: To optimize the characteristic distance to the shower core to consider the risetime for each event in order to decrease fluctuations

Future: To explore the new risetime as a mass composition sensitive parameter and compare it with results obtained for risetime at 1000 m To explore other relations as Xmax vs △Core


Study of rise time as a function of energy, zenith angle and distance to the shower core

Hernán Castellanos Valdés

Method: We analyzed events with angles around 30° - 39°, 40° - 49° and 50° - 60°, for a fixed energy. We consider retime as a function of the distance to the shower core. Fits of the following forms are considered:

𝑓(𝑥) =10+ (𝑎2+𝑏𝑥2 )1/2−𝑎 𝑓(𝑥) = 40 + 𝑎𝑥 + 𝑏𝑥2

𝑓(𝑥) =40+𝑎𝑥

The distance where the fits intersect is the characteristic distance of the event to be considered


Some examples

Zenith angle:36.56º Energy: 2.19x1019 eV Intersection at:765 m



There is a different intersection distance of the fitted functions of risetime, for events with different zenith angles. That distance might be used for performing more accurated studies on mass composition.

30≤--Θ<40

50≤--Θ<60

40≤--Θ<50


40≤--Θ<50

Events having good fits with the explored functions

30 º≤ 𝜃 <40º

40 º≤ 𝜃 <50º

Mean behaviour for events 2004-2015

50 º≤ 𝜃 <60º

< Rchis >= 871 m

< Rchis >= 843 m

< Rchis >= 780 m(m) (m)

(m)


30 º≤ 𝜃 <40º

Mean behaviour for events 2004-2015

50 º≤ 𝜃 <60º

40 º≤ 𝜃 <50º

RangeofΘ Fit’sslope

30°-40° -2.648

40°-50° -3.993

50°-60° -7.518

(m)

(m)


Next short term steps To use the linear fit to obtain Rchis for one event, given 𝜃

Once having Rchis, to obtain the value of t1/2 for such distance, i.e. t1/2(Rchis)

To compare t1/2(Rchis) with t1/2(1000) to check if the spread of t1/2(Rchis) is smaller than for t1/2(1000). If it is true, then t1/2(Rchis) can be used for performing mass composition sensitive studies with simulations.

A dependence with the energy will be also explored


Direct light in the SD and their change in time

Pedro Valencia EsquipulaGoal:

To observe the effects of direct light in the tanks of the SD, and their evolution in time. The change in time could provide information on the physical state of each tank. Such information can be also used for studying possible systematic effects in the measurements made by the SD To quantify effects of the PMT’s aging


Direct light in the SD and their change in time

For zenith angles Tank ID: 338 0 º≤ 𝜃 <60º


Amplitud (A) as a function of zenith angleWe consider three ranges of zenith angle with the same solid angle: 0º-34º, 34º-48º, 48º-60º

PMT 1

PMT 2

PMT 3

Average Amplitud for all PMT’sCharacteristic line

Cte Slope

Cte Slope

Cte Slope

Cte Slope


Short term future

•The same kind of study will be performed for 9 time intervals between 2004 and 2013, a characteristic line will be obtained for every interval.

•The possible change in the slopes of characteristic lines will be used to estimate the aging of the PMTs

•The signal will be explored in order to find some change in time related to the PMT’s aging


Thank you!


Documents

Studies on mass sensitive parameters and monitoring of the ... · Mass Composition of UHECR X max measurements above 1017 eV Alessio Porcelli Figure 4: The mean (left) and standard