This section describes the technical setup of the LOPES experiments and its data acquisition, the procedure for data analysis and end-to-end Monte Carlo simulations reproducing measured events. The section concludes with a description of the data set used for the results presented in this article and its public access via KCDC.
Retrospective view on different experimental stages
LOPES started in 2003 by deploying ten dipole-like LOFAR prototype antennas at the KASCADE array for cosmic-ray air showers (Fig. 1). Triggered by the particle-detector arrays KASCADE [52] and KASCADE-Grande [53], LOPES soon detected the radio emission of air showers with energies above \(10^{17}\,\)eV [6], and subsequently was extended to 30 antennas (Fig. 2). At the beginning, all LOPES antennas were aligned in east–west direction because, due to its dominant geomagnetic origin, the radio signal is on average strongest in the east-west direction.
End of 2006, half of the then 30 antennas were rotated to align them in north-south direction. The simultaneous measurements of the north-south and east-west aligned antennas provided additional evidence for the dominantly geomagnetic nature of the radio emission [35]. Five antenna positions were equipped with both polarization directions, but due to restrictions in the cabling infrastructure the remaining ten east–west and ten north-south aligned antennas were placed at different positions (Fig. 3). Since the radio signal and its polarization changes significantly on the scale of the antenna spacing (\(26{-}37\,\)m between adjacent antennas) [54], this special separation of differently aligned antennas turned out to hamper a reconstruction of the signal polarization. At LOPES, we therefore decided to analyze the east-west and north–south aligned antennas separately. Because of the longer measurement time and the stronger signals, the event statistics was higher for the east–west aligned antennas [38], and most results are based on these east-west measurements – including the new results presented in the following sections.
In the winter of 2009/2010, the configuration of LOPES was changed again, i.e, the antennas were exchanged to ten ’tripole’ stations, each consisting of three orthogonal dipole antennas aligned in east-west, north-south, and vertical direction [55]. This setup was operating until 2013 when the whole KASCADE experiment was stopped and subsequently dismantled. Due to a new research facility close to the LOPES site, the background level increased substantially during the last phase of LOPES limiting the statistics of events above threshold. Nonetheless, statistical analyses and a few individual events with detectable signal in all three polarization directions again confirmed the general picture of the dominant geomagnetic emission [36]. In addition to the overall increase of the background level, we noted that the background rises towards the horizon, as is expected for anthropogenic radio background. Thus, no final conclusion was drawn whether such a more expensive setup with three polarization directions per station would have an advantage over a setup with two antennas per station.
Data-acquisition system
While the setup of the antennas was changed several times over the operation period of LOPES, the hardware of the data-acquisition remained the same. Technical details can be found, e.g., in reference [55] and [56], and only the main features are described here.
The voltage measured at each antenna was continuously digitized and stored in a ring buffer, where the digitization of all antenna signals was synchronized by a common clock distributed via cables. Upon receiving a trigger from KASCADE or KASCADE-Grande, the buffers of all antennas were read out and combined to one event containing the coincident traces of all 30 antennas. Each event was stored on disk and combined during later analysis with the coincident KASCADE or KASCADE-Grande event providing the trigger, i.e, the radio signal measured by LOPES could be compared directly to the particle measurements of the same air shower.
Due to limitations of analog-to-digital converters (ADCs) available at this time for a reasonable budget, a frequency band of a maximum width of \(40\,\)MHz had to be selected for LOPES. The radio signal is strongest at frequencies below \(100\,\)MHz, because at these frequencies the wavelengths exceed the typical thickness of the particle front of air showers (today we know that the signal-to-noise ratio can be better at higher frequencies under some circumstances, and at the Cherenkov angle the radio emission extents even up to GHz frequencies as shown by the CROME experiment at the same site [57]; see “Appendix H”). Taking into account the knowledge when LOPES was built, the location of the frequency band of LOPES had been chosen to 40–80 MHz as a compromise between the Galactic background increasing towards lower frequencies and avoiding the FM band.
The radio signals received by the LOPES antennas were sampled in the second Nyquist domain with a nominal depth of 12 bits at a rate of \(80\,\)MHz (see Fig. 4). Analog filters in the signal chain strongly suppressed the frequency range outside of the nominal band of 40–80 MHz. This band was further reduced during analysis by digital filters to an effective band of 43–74 MHz to avoid systematic uncertainties because of slightly different cut-off frequencies of the individual filters. As the sampling conditions fulfill the Nyquist theorem, the radio signal between the samples in this band could later be retrieved by upsampling.
Because the time synchronization of LOPES had glitches causing occasional offsets up to a few samples between antennas, we applied a dedicated method to improve the relative timing. First, the carrier signals of TV transmitters in the measurement band were used and later a dedicated reference beacon emitting continuous sine waves [45]. This external reference beacon ensured that the relative timing between different antennas was accurate to about \(1\,\)ns, which corresponds to a phase error of less than \(30^\circ \) at \(80\,\)MHz. Together with an accurate measurement of the antenna positions by differential GPS this enabled the use of LOPES as a digital interferometer.
The complete antenna array was calibrated by an external reference source several times per year starting in 2005 [43], achieving an absolute accuracy of the measured radio amplitude of about \(16\%\) [44]. Since the directional pattern of the antennas was not measured, the directional gain dependence of the antennas was taken from simulations which, however, came with some deficiencies (cf. Sect. 4). Regarding the phase response of the LOPES signal chain, the largest effect was by the filters whose phase response was measured in the laboratory and was corrected for during analysis. However, we did not need to correct for the gain of the individual components, because LOPES features the end-to-end calibration of the absolute gain by the external reference source.
In summary, the data-acquisition system of LOPES was fully appropriate and fulfilled its purpose of providing reliable radio measurements of every triggered KASCADE(-Grande) event.
Table 1 Properties of the LOPES experiment Analysis pipeline
Data analysis was performed by an open-source software ’CR-Tools’ written in C++. The software as well as calibration and instrumental data of LOPES were made publicly accessible in a repository shared with LOFAR [58]. The LOPES software comes with different applications, e.g, for instrumental tests, calibration measurements, and a standard analysis pipeline for cosmic-ray air showers used for the results presented here. The individual steps of this pipeline are described in detail in various references [31, 59, 60].
In the first step of the pipeline, the measurements were corrected for known instrumental properties such as the phase response of the filters, the simulated directional antenna pattern, and the total absolute gain obtained from end-to-end calibration measurements. In the second step of the pipeline, the data quality was enhanced by upsampling and by digitally removing narrow-band interferences: the frequency spectrum measured at each antenna was obtained by a fast Fourier transform (FFT) of the recorded traces. Narrow-band lines in the frequency spectrum generally are of anthropogenic origin. Consequently, they were suppressed. This enhanced the signal-to-noise ratio and left the broad-band air-shower signal almost unchanged. Three of these suppressed lines in the frequency spectrum corresponded to the sine waves emitted by the dedicated reference beacon of LOPES [45], whose phasing was used to correct the relative timing between the individual antennas to an accuracy of about \(1\,\)ns.
Upsampling was performed by the zero-padding method in the frequency domain: after a Fast Fourier Transform (FFT), zeroes were added to the frequency spectrum for the frequencies below the nominal band, i.e., for 0–40 MHz, for an upsampling factor of two, and also at higher frequencies until \(n \times 40\,\)MHz for an upsampling factor of \(n > 2\). Several cross-checks, e.g., with calibration pulses, had shown that high upsampling factors enabled a timing precision of better than \(1\,\)ns although the original samples were \(12.5\,\)ns apart. Generally, a higher upsampling increases the computation time for the analysis. Therefore, for each analysis the upsampling factor was chosen such that the resulting sampling did not contribute significantly to the final uncertainties, which was given for most analyses at an upsampling factor of at least \(n=8\), and for timing-sensitive analyses at an upsampling factor of at least \(n=16\).
The interferometric method used at LOPES was cross-correlation (CC) beamforming, which was the next step in the pipeline: The traces of the individual antennas were shifted according to the arrival time of the radio wavefront. This time shift depended on the arrival direction of the signal and on the shape of the radio wavefront. For the latter we used an hyperboloid centered around the shower axis with a variable angle \(\rho \) between the shower plane and the asymptotic cone of the hyperboloid [48]. After the time shift of the individual traces, the CC beam CC(t) was calculated as the sum of all pair-wise cross-correlations of shifted traces (details in Refs. [42, 50]):
$$\begin{aligned} CC(t) = {{\,\mathrm{sgn}\,}}(S(t))\sqrt{\frac{|S(t)|}{N_p}} ~~~ \mathrm {with }\; S(t) = \sum _{i\ne j}^{N}s_i(t)s_j(t)\nonumber \\ \end{aligned}$$
(1)
with N the number of antennas, \(N_p\) the number of pairs (all combinations of two different antennas), and s(t) the time-shifted signal in an individual antenna.
Because the CC beam features rapid oscillations, it was smoothed by block averaging over consecutive samples over \(37.5\,\)ns (i.e., \(n \times 3\) samples for an upsampling factor of n). A Gaussian was fitted to this smoothed CC-beam trace and the height of this Gaussian was used as measure for the amplitude of the CC beam. This smoothing made the reconstruction more robust, but lowered the amplitude of the CC beam. Therefore, the CC-beam amplitudes depend on the reconstruction procedure and are difficult to compare to other experiments.
In an iterative fit procedure we searched for the maximum CC-beam amplitude by varying the cone angle \(\rho \) of the wavefront and the arrival direction.Footnote 2 To speed up the reconstruction procedure, we used the KASCADE(-Grande) reconstruction as initial value for the shower axis and search for the maximum in a range of \(2.5^\circ \) around this initial value. This range is more than five times larger than the direction accuracy of both arrays, KASCADE(-Grande) and LOPES, and we checked that the search range was large enough to avoid a bias due to the selection of the initial value. Hence, the maximization procedure yielded a reconstruction of the arrival direction as well as of the steepness of the radio wavefront.
Using the arrival direction and cone angle found by maximizing the cross-correlation beam, we also form a power beam:
$$\begin{aligned} p(t) = \sqrt{\frac{1}{N} \sum _{i}^{N}s_i^2(t)}. \end{aligned}$$
(2)
The fraction of the power and the CC-beam, the so-called excess beam, is a measure for the coherence of the signal [62]. Assuming that the air-shower pulse is mostly coherent in the individual antennas, incoherent contributions by background increase the value of the power beam, but not of the CC beam. Thus, the fraction of the total power contained in the CC beam is one of the quality criteria applied to the data set (cf. Sect. 3.5).
Furthermore, by the time shift of the indiviudal traces that maximizes the CC beam, we knew the arrival time of the signal in each antenna. Thus, we could subsequently measure the signal amplitude at each individual antenna even very close to the noise level and without the need of applying additional quality cuts at the level of single antennas. Then, these amplitude measurements at the individual antennas were used for further analyses.
The amplitude measurements at the individual antennas are given in field strength per effective bandwidth, using an effective bandwidth of LOPES of \(31\,\)MHz (this means that values stated here need to be multiplied by \(31\,\)MHz to obtain the field strength in µV/m in the effective band.) With some remaining limitations (see below), these amplitudes are easier to interpret than the CC beam and were used for the final step of the pipeline, which was the reconstruction of the lateral distribution. Although an exponential lateral distribution function (LDF) features an unphysical singularity at the shower axis, it turns out to provide a sufficient and simple empirical description of the LOPES measurements - given the significant uncertainties of typically \(4{-}8\,\)m in axis distance and at least \(5\%\) in the individual amplitudes (much more at typical signal-to-noise ratios [63]). Hence, an exponential LDF with two free parameters was fitted to the amplitude, \(\epsilon \), over distance to the shower axis, \(d_\mathrm {axis}\):
$$\begin{aligned} \epsilon (d_\mathrm {axis}) = \epsilon _{100} \exp (- \eta (d_\mathrm {axis} - 100\,\mathrm {m})) \end{aligned}$$
(3)
where the amplitude at \(100\,\)m axis distance, \(\epsilon _{100}\), is a good energy estimator, and the slope parameter \(\eta \) is sensitive to the longitudinal shower development [51], as was predicted on the basis of simulations [64].
The lateral distribution was even better described by a Gaussian LDF which contains an additional free parameter. We used the Gaussian LDF for the reconstruction of the energy and the position of the shower maximum [17]. However, for the energy precision, the Gaussian LDF provided no significant improvement compared to the simpler exponential LDF [31]. We therefore use the simpler exponential LDF (Eq. 3) for the analysis presented here.
Table 2 Average bias due to noise determined by comparing the end-to-end simulations with and without noise for the east–west (EW) and north–south (NS) polarization components, respectively. The stated values were calculated as (1 − without noise/with noise) for values given in % and as (without noise–with noise) for the slope parameter \(\eta \). For the parameters of the lateral distribution, \(\epsilon _{100}\) and \(\eta \), also the biases due to the simplified reconstruction method of the electric field used by LOPES are stated: (1 − true/reconstructed) and (true − reconstructed), respectively. Such a bias cannot be determined for parameters of the cross-correlation beamforming, since it implicitly includes the reconstruction simplifications and, thus, no ’true’ values without bias are available from the CoREAS simulations. The ± indicates the standard deviation, which for the bias due to noise can be interpreted as average statistical uncertainty of the corresponding quantity due to noise End-to-end simulations
The latest feature implemented in the analysis software is the treatment of air-shower simulations in the same way as measured data. The radio signal of air-showers was calculated by the CoREAS extension of the CORSIKA Monte Carlo code [8]. Afterwards, all known instrumental effects were applied on simulated electric-field vectors at each antenna position, in particular the gain pattern of the antennas, the amplitude and phase characteristics of the signal chain, and the quantization of the signal implied by the resolution of the 12-bit ADC. The simulated signals were stored as traces with the LOPES sampling rate of \(80\,\)MHz in the same data format as real events (see Fig. 5 for a typical example event). Subsequently, the simulations were analyzed using the same standard analysis pipeline as for the measurements.
Optionally measured noise was added to the simulated events. For this purpose, we used real background measured by the LOPES antennas. Thus, the performance of the LOPES experiment could be assessed using these end-to-end simulations. In particular the cross-correlation beamforming was studied with the simulations, and the measurements of the hard to interpret CC beam were compared quantitatively to the predictions of the CoREAS simulations.
With the new end-to-end simulations, we were able to check the effect of a simplification made when comparing REAS and CoREAS simulations to LOPES measurements in earlier publications [38]: when processing the simulations, we simply filtered the east-west and north-south polarization components of the simulated electric field to the effective band of LOPES, but ignored that LOPES was unable to measure these electric field components directly. Due to the inverted v-shape of the LOPES antennas the east-west and north-south aligned antennas are also partially sensitive to vertically polarized signals. In contrast to other experiments featuring two orthogonally aligned antennas at each station, the three components of the electric field vector could not be reconstructed at LOPES. Since at most antenna positions only one antenna was available, e.g., east-west aligned, necessarily a simplifying assumption had to be made in the reconstruction of the radio signal. Therefore, we used a simplified treatment of the deconvolution of the direction-dependent antenna pattern, which is described in detail in reference [31]. Nevertheless, with the new end-to-end simulations we treated simulations and measurements in the same way and were able to fully compare them with each other.
Furthermore, with the end-to-end simulations we were able to study the error made by the simplification. Since both, the polarization of the radio signal emitted by an air shower as well as the antenna gain, depend on the arrival direction, the size of the error is strongly arrival-direction dependent. While for individual events the error can be as large as a factor of 2, on average the reconstructed values of the field strengths are only few percent lower than the true values of the simulated air showers. Figure 6 shows the dependence of this bias on the azimuth and zenith angle: each point corresponds to the arrival direction of a real air shower measured by LOPES (the distribution is nonuniform because the amplitude of the radio signal and the detection threshold of LOPES depended strongly on the arrival direction of the air shower relative to the geomagnetic field). For the large majority of events, the error by the simplification is smaller than \(10\%\) and well within systematic uncertainties quoted in earlier publications.
In addition to the bias for the reconstructed field strength in individual antennas, we also studied the average effect of the simplified treatment of the antenna gain on the reconstructed lateral distribution (see Fig. 7 for an example). By comparing the true values of the simulations with the result of the end-to-end simulations with and without noise, we discovered that noise introduces an additional bias on the amplitude and slope parameters, \(\epsilon _{100}\) and \(\eta \), respectively. This bias is on top of a bias due to noise in individual antennas, which we had already corrected for in our standard analysis [63]. For the amplitude parameter \(\epsilon _{100}\), the size of each effect (noise bias and antenna-gain-simplification bias) is small relative to the dominating \(16\%\) scale uncertainty of the amplitude calibration. For the slope parameter \(\eta \), the size of the individual biases are comparable to the measurement uncertainties, but the biases by noise and by the simplified treatment of the antenna gain partly compensate each other. Overall, the mean net biases are small, but there is a relatively large spread, which reflects an event-by-event systematic uncertainty (see Table 2). This implies that the measurements of individual events have to be interpreted with care while average values over dozens to hundreds of events should be affected only marginally. Consequently, LOPES results published prior to this paper can be considered reliable.
Table 3 Statistics of LOPES events used in this paper. The two subsets of LOPES events triggered and well reconstructed by KASCADE and KASCADE-Grande, respectively, overlap by a few events which is why the total number of events is less than the sum. For those measured events remaining after all quality cuts, also the statistics of corresponding showers simulated by CoREAS are shown that pass all quality cuts for both cases of a proton and iron nucleus as primary particle Data set
The LOPES data set consists of air-shower events triggered by the KASCADE array and its KASCADE-Grande extension. Both arrays provided a trigger to LOPES for all events with estimated energies \(\gtrsim 10^{16.5}\,\)eV, which was significantly lower than the detection threshold of LOPES around \(10^{17}\,\)eV. We removed those events from the analysis which had a zenith angle larger than \(45^\circ \) or which had their shower cores outside of the fiducial areas of the KASCADE or KASCADE-Grande array, respectively. After applying these cuts, both arrays were fully efficient for all types of primary cosmic rays well below the relevant energy range, and we can safely assume that all events that had a radio signal passing the LOPES reconstruction were triggered. However, LOPES itself was not fully efficient, i.e., only a fraction of the triggered events passed the LOPES reconstruction (see Table 3 and Fig. 9).Footnote 3 Corresponding to the two particle-detector arrays providing the trigger, there are two data sets of LOPES events, KASCADE and Grande events, which have only little overlap (Fig. 8). Depending on the analysis, we either use both data sets combined, or only the KASCADE data set because those events have their core contained inside of the LOPES antenna array which allows for a higher quality of the event reconstruction.
For the present analysis we used data recorded by the east-west aligned v-shape dipole antennas from December 2005 to October 2009, because starting December 2005 LOPES featured an absolute amplitude calibration [43]. During this time almost 4000 well-reconstructed KASCADE and KASCADE-Grande events with an energy of at least \(10^{17}\,\)eV triggered LOPES and were propagated through the LOPES analysis pipeline. To those events which passed the analysis pipeline without error, which implies, e.g., that the reconstruction of the arrival direction converged, we applied further quality cuts:
-
The signal-to-noise ratio of the CC-beam must be greater than \(14 \cdot \sqrt{N_\mathrm {ant}/30}\), with \(N_\mathrm {ant}\) the number of antennas contributing to the measurement of the event.
-
The CC beam must contain at least \(80\%\) of the total power, which excluded events contaminated by background.
-
To reject thunderstorm events, events with an atmospheric electric field of at least \(3\,\)kV/m were excluded. This cut was applied to events recorded after the installation of a local electric field mill on 24 August 2006.
After the quality cuts, 570 measured LOPES events remain in the analysis.
Using the KASCADE dataset, we were able to estimate the efficiency because the shower cores of these events were contained or very close to the LOPES antenna array (Fig. 9). For energies above \(2\,\times \,10^{17}\,\)eV, more than half of the LOPES events passed all of the quality cuts mentioned above. For most of the Grande events, the shower cores were too distant from the LOPES array for a detectable radio signal. More detailed discussions on the dependencies of the amplitude of the radio signal, e.g,. on the energy, the geomagnetic angle, and the distance to the shower axis can be found in many of the references cited in the introduction.
We also produced a library of CoREAS simulations using the energy, arrival direction, and shower core reconstructed by KASCADE(-Grande)Footnote 4 as input. Using CORSIKA 7.3 with the hadronic interaction model QGSJet II.03, two simulations were created per LOPES event, one with a proton and one with an iron nucleus as primary particle. Because different LOPES analyses used different selection criteria, versions of the analysis pipeline, and subsequent quality cuts, the exact data sets varied slightly over time and LOPES publication, and some showers were not included in the simulation library. Still, there is significant overlap between all selections, and for about \(90\%\) of the measured events used here there are corresponding CoREAS simulations. Each simulation was processed twice through the standard analysis pipeline, once the pure simulated radio traces and once the simulated radio traces after adding randomly selected noise samples measured by LOPES.
After the analysis pipeline, the simulated events were subject to the same quality cuts as the measured events. Since many of the measured events are close to the detection threshold, only a part of the corresponding simulated showers passed the quality cuts (the vice-versa situation does not happen because those showers missing the cuts for the measurements, were simply not simulated). In case of pure simulations without adding noise, 464 events passed all quality cuts for both, proton and iron, as primary particle (after removing three simulated events for which the fit of the lateral distribution failed). In case of the simulations with measured noise added, 380 events passed all quality cuts for both, proton and iron, as primary particle. These common events with both measured and simulated results available are the data set used for the results shown here.
The LOPES events were made available to the public in the KASCADE Cosmic Ray Data Center (KCDC) [65] in November 2019 as part of the ’Oceanus’ release.Footnote 5 In addition to the reconstructed parameters of these LOPES events (up to 20 parameters per event and 4 parameters per antenna in an event), also the corresponding KASCADE-Grande data can be downloaded from KCDC as detailed in the user manual available on the KCDC website. The LOPES data can be found as subset of the KASCADE data in the KCDC data shop: https://kcdc.ikp.kit.edu/