Results from polarization studies of radio signals induced by cosmic rays Harm Schoorlemmer, for the Pierre Auger Collaboration H. Schoorlemmer RADBOUD UNIVERSITY NIJMEGEN

Motivation The polarization of the radiation reveals the nature of the emission mechanism(s) Take back home message: The polarization of the radiation reveals the nature of the emission mechanism(s) Two sketches of the direction of the e field for a given position with respect two the shower axis. K. Werner, O. Scholten, Astroparticle phys, 2008 H. Schoorlemmer ARENA 2010

Motivation Initial study REAS3 v x B Data Initial study. Expect an angular dependence on the zenith angel from a geo magnetic model. Compared is reas3 simulations, a v x B model and data. Might see a trend, not very clear, but encouriging dig a bit deeper in polarization effects. H. Schoorlemmer ARENA 2010

Outline Setup & Data Introduction Geomagnetic Charge excess Conclusions & Outlook H. Schoorlemmer ARENA 2010

Setup and Data 3 antennas, 100m separated Thunderstorm monitor Setup and Data 3 antennas, 100m separated triggered by an external particle detector From May 2007 until May 2008, 495 events were recorded in coincidence with the Pierre Auger surface detector Particle detector H. Schoorlemmer ARENA 2010

Conventions H. Schoorlemmer ARENA 2010

Setup and Data Software package Radio Offline (Poster Daniël Fraenkel) Cables Amplifiers Filters Digitizer 2 LPDA: 40 -70 MHz North – South & East - West Software package Radio Offline (Poster Daniël Fraenkel) Data set in this presentation: taken with two of the 3 antennas, because at the other position we where testing different types of antenna’s. Of this whole setup we have a software package which simulates the response. This is important, because in this way we can compare simulation with the measurements. 400 MHz sampling H. Schoorlemmer ARENA 2010

Polarization Introduction The measurement is the projection of the electric field in the horizontal plane 4 modes 2 linear 2 circular Full description with the Stokes parameters One can define several observables that depend on the polarization H. Schoorlemmer ARENA 2010

Signal window East - West North - South FWHM Noise FWHM of total power I East - West North - South FWHM Noise H. Schoorlemmer ARENA 2010

Polarization Geomagnetic Polarization depends only on direction of shower particles If only effect, strong linear polarization K. Werner, O. Scholten, Astroparticle phys, 2008 H. Schoorlemmer ARENA 2010

Polarization Geomagnetic1) SNR > 5 Bad period Normal conditions SNR > 5 1) See also next talk by Benoit Revenu H. Schoorlemmer ARENA 2010

Polarization Charge excess1) Contribution predicted by MGMR2) & REAS33) Different polarization from pure geomagnetic model G.A. Askaryan, Sov. Phys. JETP, 1962 K.D. de Vries, O. Scholten et al, Astroparticle Physics (submitted) M.Ludwig, T. Huege, Astroparticle Physics (submitted) K. Werner, O. Scholten, Astroparticle phys, 2008 H. Schoorlemmer ARENA 2010

Polarization Charge excess Rotate coordinate system to cancel geomagnetic component in one direction Define a sensitive variable vs. (N =#samples in signal window (FWHM)) H. Schoorlemmer ARENA 2010

Polarization SNR > 5 MGMR Charge excess (MGMR) Data Bad Period H. Schoorlemmer ARENA 2010

Polarization SNR > 5 Charge excess (MGMR) Bad period Normal conditions H. Schoorlemmer ARENA 2010

Polarization SNR > 5 Charge excess (REAS3) REAS3 Data Bad Period H. Schoorlemmer ARENA 2010

Polarization SNR > 5 Charge excess (REAS3) REAS3 Data Bad Period H. Schoorlemmer ARENA 2010

Polarization SNR > 5 Charge excess (REAS3) Bad period Normal conditions H. Schoorlemmer ARENA 2010

Conclusions Polarization analysis shows: Geomagnetic emission mechanism confirmed Data shows features of additional emission mechanisms First hint of charge excess H. Schoorlemmer ARENA 2010

Outlook More data with higher precision More than two antennas per event Better reconstructed shower parameters from surface and fluorescence detectors See talk by Stefan Fliescher H. Schoorlemmer ARENA 2010

Back-up Charge excess Compare with simulations Randomize in the uncertainty from the surface detector reconstructed shower parameters Take into account that the uncertainties are correlated Generate 100 showers with CORSIKA to include shower-to- shower fluctuations (QGSJET-II and UrQMD) H. Schoorlemmer ARENA 2010

Back-up Data: Propagation of the noise to the parameters Uncertainty charge excess plot Data: Propagation of the noise to the parameters Simulations: Spread in values from 100 simulation within the uncertainties of the surface detector reconstructed parameters. Including shower to shower fluctuations (CORSIKA) H. Schoorlemmer ARENA 2010

Back-up Use auger reconstruction to find the radio pulse Selection criteria Use auger reconstruction to find the radio pulse Apply a SNR cut based on the total power in the horizontal plane H. Schoorlemmer ARENA 2010

Back-up Uncertainties: Uncertainties plot2 RMS of in the FWHM window H. Schoorlemmer ARENA 2010

Back-up SNR > 5 Without bad period events H. Schoorlemmer ARENA 2010

Back-up SNR > 5 Without bad period events H. Schoorlemmer ARENA 2010

Back-up Complex electric field using a Hilbert transform Stokes parameters Complex electric field using a Hilbert transform 4 – components: H. Schoorlemmer ARENA 2010

Back-up REAS3 H. Schoorlemmer ARENA 2010

Back-up MGMR vs REAS3 MGMR REAS3 H. Schoorlemmer ARENA 2010

Back - up MGMR vs. REAS3 H. Schoorlemmer ARENA 2010

Back-up Uncertainties / cuts geo plot 1 Selection criteria: SNR cut in East -West or North – South for data and simulation Direction reconstruction within 20° of standard auger reconstruction Cut on simulation rejects 6 out of 21 data points Uncertainties Data: REAS3: rms of 30 noise simulations v x B: none H. Schoorlemmer ARENA 2010