Like many emerging technologies, quantum computing is a buzzword—it's a symbol for the next era of computers. Some scientists and engineers believe that quantum computers will replace all computers.
In their current state, it's too early to gauge the level or speed that quantum computers will surpass the usefulness of classical computers. First, it's important to understand what a quantum computer actually is.
How are quantum computers different? Quantum computing vs. classical
Traditional computers use binary signals, such as ‘0’ and ‘1’, while quantum computers use quantum states to create various signals. Quantum computing is not limited to classical computing gates, which are only able to provide a binary on or off signal. Quantum computers rely on quantum bits, or qubits, which utilize quantum characteristics such as superposition, entanglement, and interference to provide measurable quantum state signals. Without going into extensive detail of quantum computing physics, the net of quantum computing is that the number of classical bits required to complete a specific process is drastically reduced when using fully entangled qubits.
Fully entangled qubits of quantity ‘N’ are theoretically equivalent to a computer containing 2^N classical bits. For scale, a quantum computer that contains 300 qubits would be the computational equivalent of 2^300 classical bits, which is as many particles as there are in the universe. Due to this relationship, smaller computational loads can be handled surprisingly better by classical computers than by quantum computers, as the difference between 8 quantum bits and 2^8 (256bit) classical bits is relatively negligible and classical computer development is significantly more developed. It is only when computational problems become extremely large that quantum computers surface their value and surpass the usefulness of classical computers.
Types of quantum computers
Currently, there are three distinct subsets of quantum computing: quantum annealing, quantum simulation, and universal quantum, each encapsulating the previous subset.
• Quantum annealing can easily be considered a complex problem solver. A great example of a complex problem that quantum computers will be able to solve is the traveling salesman problem, which determines the shortest there-and-back distance possible for a required route. While modern classical computers are capable of computing the shortest route, quantum computers can do it orders of magnitude faster and would be able to find an optimized solution quickly.
• Quantum simulation is the modelling and simulation of problems that exceed the capabilities of classical computer systems. A common example of this benchmark is modelling the chemical interaction within protein folding, when exposed to chemical stimulants such as medicines.
• Universal quantum is an all-encompassing version of quantum computing that can solve any problem, of any difficulty, in a small amount of time, giving wind to the term ‘quantum supremacy.’ Furthest from realization, a universal quantum computer is estimated to contain up to 1 million qubits. However, the most powerful quantum computer design today contains 128 qubits and is yet to be functional.
What is quantum computing used for?
If you ask this question to a quantum computing research scientist, their answer will likely be vague and ambiguous—“quantum problems require quantum solutions," or something of the like. Talia Gershon, a PhD quantum computing research scientist at IBM states:
“We think that quantum computing will be used to accelerate the types of things that are really hard for classical machines. Simulating nature is something that is really hard ... like modelling atomic bonding [or] electron orbital overlap. Instead of writing out a giant summation over many terms [as you would on a classical computer, we try and actually mimic the system that you are trying to simulate directly on a quantum computer.”
Not surprisingly, the statement holds true: quantum problems require quantum solutions. But the truth in this answer is absolutely justified. Modelling our natural world is extremely complex and requires much more than a binary solution. As Talia Gershon notes, a simple letter ‘A’ is represented in an 8-digit binary code: 01000001. Imagine the binary code required to model a California redwood swaying in the wind, taking into account the varying gravity exposure due to its height, the thermal expansiveness of the sunward side versus the shaded side, and every other factor that influences it to become the way it actually is.
Modern quantum computing applications
It is already truly remarkable that modern computers are able to recreate and model things as fully as they do. It's incredible that today's computers can accurately recreate an understandable image on a screen using only a binary signal, or solve extremely complex, multivariable math problems using only a binary system.
Quantum computing brings the compute bottleneck of binary systems closer to grasp. Modelling a tree may not be so difficult with a quantum computer. On a smaller scale, quantum computing may allow us to model internal interactions across large known molecules or even discover new molecules. Again, quantum problems require quantum solutions.
Quantum computing and AI
Another buzzword is artificial intelligence. In its current most well-known implementations, artificial intelligence runs on vast servers, utilizing trillions of binary bits to run extremely complex neural networks and other AI algorithms. A large resource that many facets of AI rely on is parallel computing, which future quantum computers will be significantly better geared for doing than future binary machines. This does not mean that all AI will live only on quantum computers, but rather that the most complex workloads within large AI algorithms could be handled by quantum computers supplementing other core functions of binary-based workloads.
What is the future of quantum computing?
Quantum computing is still in the fetal development stages of its life. The realization of a universal quantum computer (perhaps the point of the singularity?) is far from coming to fruition. There is, however, an undeniable usefulness of quantum calculation in the very near future. Developing process optimization algorithms across a variety of industries, including running complex AI calculations, is very tangible. Modelling advanced chemistry interactions or even rapidly developing cures for new disease or viruses (looking at you, COVID-19) is increasingly more attainable as the power of quantum computers advance.
Quantum computers will, in a poetic way, contribute to their own growth while they model quantum interactions of materials that may someday be used in the construction of their future relatives. While its path through development may not be fully clear at this stage in its infancy, it is certain that quantum computing will have a profound influence on solving the hardest problems humans face.