Does Randomness exist or is it just another term for a lack of knowledge?

In our daily lives we try to be in control of every likely situation. Therefore we create patterns and try to forecast as many events as possible with the aim to feel well prepared and safe. Nowadays every citizen has many insurances policies covering every detail of a possible occurring event. Random numbers represent chaos – yet are essential in processes that aim to produce reliable and precise outcomes such as Monte Carlo predictions. They are used for encryption methods and simulations in economics and science covering areas such as risk analysis, population growth and economic predictions.
In principle, every event, including the fall of dice or the outcome of a game of roulette, can be explained in mathematical terms. With the help of quantum physics two of the three prototypes generate true random numbers that cannot be predicted in advance. By developing three devices which are generating random numbers based on cosmic rays, radioactive radiation and wind, we propose to establish a relationship to the natural chaos and see it as something valuable which can be harvested for later usage. This first part of the project focuses on the generation of random numbers using two different seeds:

[1] The Random Event Harvester is based on a Geiger counter that notices radioactive particles, producing a bitstream that is afterwards converted in real numbers. It's characteristic of being portable allows collecting random numbers in the environment and store them with associated geographical information.

[2] The Cosmic Ray Detection Chamber is inspired by current approaches to generate true rather than pseudo random numbers: Particle movement is tracked on a quantum physics level. The design is based on a cloud chamber that visualises tracks of cosmic rays that are energetic charged subatomic particles that originate from outer space. These tracks are then used to generate random values.

With Steffen Fiedler

Photos: Matthias Steffen, Actor: Daniel Godward

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