While some casino games require a certain degree of skills that
will impact the outcome of a particular game, most casino games are purely
based on chance. In
order to mimic the randomness and fair chances encountered in all land based
casinos, online casino games use random number generator or RNG in the software
that powers the game.

For
example, the RNG is responsible for generating a number from 1 to 37 in a game
of European Roulette, two random numbers simultaneously for a game of Dice, a
number from 1 to 52 for single deck card games. For multi deck games like
online blackjack, the RNG has even more complicated mathematical algorithms to
deal with while for online slots and video pokers the RNG is based on a payout
percentage set for that particular game or through the casino.

**But what is a random number generator?**

As
the name implies, an RNG generates random numbers. A number generated by a
process, whose outcome is unpredictable, and which cannot be sub sequentially
reliably reproduced is called a random number. What most online casino
operators don’t know is that generating truly random numbers without a repeating
pattern is not an easy task.

In
the field of numerical simulations, cryptography and in the gaming industry,
high quality random numbers are absolutely vital. For all casino games of
chance, it must not be possible for a player to increase his probability to win
by discovering a bias towards certain outcomes in the game procedure. Modern
lotteries and gambling machines are all based on the use of random numbers to
guarantee a uniform winning probability.

There
are two main classes of generators: software generators and physical
generators.

**Software generators**

Due to the fact that
computers are deterministic systems and given a certain input, a program will
always produce the same output, it is impossible for a program to produce a
sequence of truly random numbers. The sequence may pass some statistical
randomness tests but it is always possible to reproduce. Due to the fact that
the sequences produced by a program look like random sequences, these
generators are called pseudo-random number generators.

**Physical generators**

It is important to
consider the physical process used as the source of randomness when using a
physical generator. This source can be based on processes described by either
classical physics or by quantum physics.

While
macroscopic processes described by classical physics can be used to generate
random numbers, it is very important to realize that classical physics is fundamentally
deterministic. The evolution of a system described by classical physics can be predicted,
assuming that the initial conditions are known. One could say that determinism
is hidden behind complexity.

Although
their random numbers are likely to pass randomness tests, these generators are
difficult to model. This means that it is impossible to verify, while acquiring
numbers, that they are operating properly. In addition, it is difficult to
ensure that the system is not interacting – even in a subtle way – with its
environment, which could alter the quality of its output.

Contrary to classical
physics, quantum physics is fundamentally random, making quantum random number
generators as the only true RNGs.

**How does a quantum random number generator work?**

Quantum
random number generator uses light as primary source of randomness. Light
consists of elementary particles called photons and they exhibit random
behavior in certain situations.

One
of those situations is the transmission of a photon upon a semi-transparent
mirror which is totally random and cannot be influenced by any external
parameters. This situation is used in order to generate truly binary random
numbers.