Utilize quantum computer characteristics, such as the ability to simultaneously represent and process different states of information via qubits, to generate series of random numbers more effectively and to have advantageous applications in computational simulation contexts of physical systems and cryptography. This is what is claimed in two studies carried out within ICSC - National Research Center in High Performance Computing, Big Data and Quantum Computing and the European projects "PHOQUSING - PHotonic QUantum SamplING Machine" and "QU-BOSS" by the Quantum Lab group of the Sapienza University of Rome, in collaboration with the International Iberian Nanotechnology Labs (INL) and the Institute of Photonics and Nanotechnology - National Research Council (IFN-CNR). The findings of the two studies, published in the prominent scientific journals Nature Photonics and Science Advances, show that a properly constructed and managed photonic quantum platform may implement the Bernoulli Factory algorithm. The latter is a widely recognized algorithm that is employed to generate a series of random variables, introducing a novel method for manipulating random variables that employs quantum mechanics, known as the "quantum-to-quantum Bernoulli Factory". Using the example of a series of results resulting from a coin toss, the Bernoulli factory algorithm, which is important in numerical integration and Monte Carlo methods used in probabilistic calculations, allows you to generate coin tosses with a different distribution as output from a known probability distribution of tosses as input.