Quantum phenomena, such as the measurement outcomes of certain quantum systems, are often considered to be fundamentally random. These phenomena are not determined by any hidden variables and can only be predicted probabilistically. This inherent randomness has led to the development of quantum random number generators (QRNGs), which exploit quantum phenomena to generate random numbers.
In terms of the quality of randomness, quantum random number generators have several advantages over classical computational algorithms. Quantum randomness is considered to be "unpredictable" in the sense that it cannot be determined even if one has complete knowledge of the system's initial conditions and dynamics. This property makes quantum randomness particularly valuable for applications where high levels of unpredictability are required, such as cryptography and secure communication.
Classical algorithms, on the other hand, typically rely on deterministic processes or pseudo-random number generators (PRNGs) that are based on mathematical algorithms. Although these algorithms can produce sequences of numbers that appear random, they are fundamentally deterministic and repeatable. Given the same initial conditions, a classical algorithm will produce the same sequence of random numbers.
However, it's important to note that the quality of randomness generated by QRNGs depends on the specific implementation and the underlying physical system used. Factors such as environmental noise, imperfections in the measurement apparatus, and limitations in the quantum system itself can introduce biases or correlations that may reduce the quality of randomness.
Overall, while quantum randomness is often considered to be superior in terms of unpredictability and true randomness compared to classical computational algorithms, the practical implementation of QRNGs and the measurement of their randomness can still be subject to various limitations and challenges.