A system for generating random numbers uses photon-induced electron splatter patterns on a pixelated detector.

Random number generation is a vital component in many technological applications, from computer programming to encryption securities. To ensure the highest level of security, especially in cryptographic systems, pure, nonreproducible random numbers are crucial. With the rapid advancement of computing technology, the demand for superior random number generation systems has escalated. However, traditional methods of random number generation often fall short. Software-based generators are not truly random because they utilize algorithms that can be reverse-engineered or predicted. Other methods relying on environmental inputs like atmospheric noise can be subject to external interference. The unpredictability or pure randomness of the generated numbers is often compromised, leading to potential security issues.

Technology Description

The invention is a system designed to generate random numbers by using the photon-induced splatter patterns on a detector. It functions through a radioactive source that emits photons leading to the release of electrons on the surface of the detector, which is configured as a two-dimensional array comprising multiple pixels. This technique results in a splatter pattern on the detector, which is read by the processor and compared with other patterns to generate the random numbers. Under some conditions, the processor creates a difference matrix representing the comparison between two splatter patterns and classifies each pixel in the matrix following certain rules. This technology provides unique advantages over traditional random number generators. Its core differentiation lies in its integration of photon emissions from a radioactive source, allowing for random number generation that is not replicable and truly random. The varying conditions, such as the time function or the pixels' disposition, add other layers of randomness, making the system practically invulnerable to prediction or predetermination. This approach brings a new level of security and randomness over existing methods.


  • Produces truly random numbers that are harder to predict or replicate
  • Improves security in systems requiring random number generation
  • Offers possibility of varied settings for creating difference matrix
  • Generates random numbers without external interference
  • Contributes to the robustness of cryptographic systems

Potential Use Cases

  • Enhanced encryption methods for confidential data protection
  • Stronger security for cryptocurrencies
  • Increased difficulty of hacking computer systems
  • Improved randomness in computer programming
  • Enhanced security mechanisms in the online gambling industry