Welcome to the Documentation, the guide for Cosmic@Web. Here you will find explanations on how the settings work as well as useful tips. A description of the experiments, of which the data is made available to you for evaluation via Cosmic@Web, can be found on the main page. If you are looking for an interactive guide to using Cosmic@Web, click the link to the tutorial.

With Cosmic@Web, cosmic particle data from various experiments can be analysed. Data from the detectors at Neumayer Station III, on the research vessel Polarstern, at the Schneefernerhaus on Zugspitze, and from the SEVAN detector network can be used to study the rate of cosmic particles at various locations around the world. Furthermore, data from different cosmic particle experiments and a Weather Station installed at DESY in Zeuthen can be analysed. The angle dependence of the muon rate is investigated with the CosMO-Mill, the decay time of muons is measured with LiDO and the Trigger Hodoscope takes continuously muon and shower data.

To make it easier for you to find your way around, we recommend opening the manual and Cosmic@Web in two separate windows of your web browser and placing them side by side on your screen.

The Standard mode makes it easy and quick to get started by reducing the setting options to the essentials. Select this mode if you are new to Cosmic@Web or want to perform a quick analysis.

Enter the name of the experiment and the data set. This is displayed in the key and helps you separate the data if you want to display several data arrays in one diagram.

Choose the experiment you would like to analyse. A description of the experiments can be found at Cosmic@Web.

After selecting the experiment, the data set you wish to analyse must be selected. A list can be found under the available Data Sets [Link]

Here you select the type of diagram you want to display the data in. Different diagrams have different benefits, and the different options are explained in the following table.

Choose Variables

Depending on the diagram type up to three variables can be chosen. All variables available for the selected experiment are shown in the drop-down menu.
The z-variable is optional, it is not necessary to select it to create a diagram.

The corresponding variable can be modified with the correction function. If the space is left empty, the variable is shown in the measured unit. Examples are the transformation of the variable "time" from second to day (time/(24*60*60)) or the air pressure correction of the particle rate.

In histograms, the frequency of a variable is given within intervals or so-called bins. The width of the bins, i. e. the length of the intervals, is calculated as the quotient of the entire measuring range and the number of bins. For example, the division of a measuring range of 15 s into 5 Bins results in a bin width of 3 s. With a sufficient statistics smaller bins can also resolve smaller structures. However, at lower statistics one can compensate statistical fluctuations in the distribution by choosing a larger bin width.

Real measurements are always faulty. When selecting this option in addition to the measured value the statistical error of the corresponding variable is also displayed in the diagram.

To define filter (cut) conditions, the following signs can be used:
==     equal
>       larger
>=     larger equal
<       smaller
<=     smaller equal
and   and
or      or
 

In this field, enter the function that you would like to use to visualise the data. A function can have several free parameters, which are marked with p[#]. The symbol # is replaced by a number to identify the parameter, whereby the parameters are numbered starting from 0. The independent variable is designated x and corresponds to the x-variable selected from the data set. There are various mathematical functions, that can be used. The values of the parameters resulting from the fit are displayed in the diagram. Examples of fit functions are listed in the table below.

To enable a fit of the function to the data, the start values of the free parameters should be assigned to values which are in the range of the expected magnitude. The values are separated by a comma and successively assigned to the parameters according to their numbering.
Note: Decimal places are separated by dots and not by commas.

There are different ways of displaying the data in a 1D histogram. You can choose from the following:
Histogram,
Histogram filled,
Line,
Line filled,
Scatter.

There are different ways of displaying the data in a 2D histogram. You can choose from the following:
Colour,
Contour filled,
Contour filled,
Box filled.

Various statistical values can be output. The choices are:
a = everything
n = number of entries
u = underflow
o = overflow
m = mean value
s = standard deviation
at 1D: p = mode (most frequent value), e = median, w = skew, k = kurtosis, x = excess
at 2D: c = covariance

It is possible to define a number of contour lines, i.e. the number of ranges into which the measured frequencies are divided.

If this element is activated, the probability density, i.e. the distribution of events normalized to 1, is displayed instead of the number of events.

In the cumulative display of a histogram, the sum of the binary entries is displayed. The summation can start from the left side of the x-axis or the right side.

There are numerous possibilities to display spherical coordinates on a flat, 2-dimensional surface. Some of them are available here.

If this option is activated, the history of national borders will be plotted on the map.

If several data series are to be displayed in a diagram, this option can be used to determine the sequence in which the diagrams are plotted on top of each other. This is useful to avoid one diagram hiding the other, e. g. if in a 1D histogram the bin of one record has more entries than that of another record.

The chosen symbols or line to display the data can be shown with a selected colour. An exception exists if a z variable is to be displayed. In this case, the symbols or the line are given a colour corresponding to the assignment of the value of the data point on the colour scale.

Another useful option when displaying several datasets in a diagram to avoid mutual masking of diagrams is to select the transparency of the symbols or line. Graduations between 0% and 100% can be selected, where 0% means completely opaque and 100% means completely transparent.

Data points can be represented by different symbols. If you have more than one dataset, it makes sense to use different symbols in addition to different colours.

The symbol size can be adapted to your own requirements. The entered value is read in millimeters.

If data points are to be connected by a line, the following line shapes are available:
solid line,
dashed,
dotted,
dashed-dotted.

The thickness of the line can be adjusted by a value in millimeters.

There are several options for the line style of the fit function:
full line,
dashed,
dotted,
colour red: 'r-',
colour blue: 'b-',
colour green: 'g-'

Give the diagram a name to find it among your saved diagrams.

The width and height of the diagram can be varied. The entered values are read in in centimeters.

By default, the axis is labelled with the variable set under Data selection including its unit and, if necessary, the correction function. This label can be changed in this field, which can help to make the diagram easier to understand.
 

If only a certain section of the axis is to be displayed, the limits of the section can be entered here.

The correct axis scaling can simplify the recognition of correlations. Therefore, different scales are offered. The standard is a linear scaling with equidistant axis sections. This setting is useful for most observations. If the data span a large range of values (several orders of magnitude), especially if there is an exponential relationship between the displayed variables, logarithmic scaling is recommended.

The legend can be hidden or its position in the diagram can be changed so that it does not cover the graph or graphs.