We’re already living in a quantum world
OMG, how random is that? If quantum random number generators have anything to do with it, then it could be completely and truly random.
Quantum technology might seem like something from the latest Star Trek movie, but many quantum technologies—like random number generation—are already commercialized, while many others are just on the cusp. We’re already living in a quantum world.
Quantum theory describes a particular set of properties that atoms have. We used to understand particles in terms of so-called “classical” physics, as discovered by scientists like Isaac Newton. The laws of physics were based on what we could see and measure, like apples falling from trees. These laws still hold true, but at very small and very large scales research has shown that the universe is much more complex.
Quantum theory describes the behaviour of particles at very small scales more accurately than classical physics can. These properties are not new, but our ability to describe and especially to use them is relatively new. Two of these properties are superposition and entanglement.
- Superposition: Just like Erwin Schrödinger‘s famous analogy of a cat in a box, until a quantum system is directly observed it exists mathematically not as one particular state, but only as a series of probabilities—or as all potential states. For example, if an electron is considered a quantum system, its “state” could be a property, such as its exact position around the nucleus of the atom. Until it is observed, the electron exists not at one single point, but as a field of probabilities throughout its orbit.
- Entanglement: Quantum particles that are “entangled” are strongly correlated, which means that they act in unison, like dance partners, even when separated over distances and whether that distance is a few metres or across galaxies.
Quantum in real life
Quantum information is a field of research where quantum properties like these ones are used to manipulate and store information. Quantum computers are one application of this. Regular computers conduct operations sequentially, one sequence after another, when they run programs that allow them do everything from add numbers to surf the Internet. The big difference for quantum computers is that they use quantum properties to conduct these same operations in parallel—that is, at the same time—instead of sequentially.
Over the last few years, we’ve heard of advancements in quantum computing, such as controlling two entangled particles over increasingly long distances or controlling the most qubits at once. (A qubit in a quantum computer is analogous to a bit in a classical computer: a tiny unit that physically stores information as a 0 or a 1). Quantum computing itself has many challenges still to overcome. But another application that is much closer to commercialization is quantum cryptography.
Quantum cryptography promises a more secure system to protect the transmission of personal data and information, such as financial transactions. Secure transmission of data demands that it be encrypted and this usually requires a key: a string of numbers generated by a program that will be extremely hard for a third party to crack. Quantum cryptography, which is already commercially available, operates on the premise that something that is observed is changed, making it immediately clear when data has been tampered with.
MaRS client Quantoss
One MaRS venture that has made the leap to commercialization is Quantoss, a truly random number generator invented by a team at the University of Toronto. The Quantoss device quickly generates truly random numbers using the quantum noise—or uncertainty in measurement—created by a laser. Applications include more secure online keys for data encryption and online gambling, and more accurate simulations of randomness for scientific research.
The value of being able to generate truly random numbers is that it is almost impossible to guess them, making random numbers valuable keys for online encryption, or for input into programs that are trying to create simulations of randomness, like games of chance.
Since an algorithm generates the number, it is technically possible to hack the program and to find out the random number or for the program to be flawed in some way. In fact, random numbers generated by computers are only pseudo-random. When issues are found with the algorithms that generate random keys, it can be problematic and costly.