What the heck is quantum computing and why is it important?
Quantum mechanics is a weird and extremely unintuitive part of physics, but it has a few key ideas at its core. One of these ideas is the superposition of states or the dual nature of matter. We normally think of matter as particles, but over the years physicists have discovered that it can also exist as waves, which can be thought of as a bunch of disturbances in a field, as well. In fact, and here comes the un-intuitive part, matter can exist as both particles and waves, at the same time! Note that we are talking about all matter here, not just light. Imagine a solid circle made up of a single colour. The circle can either be yellow, for particles, or blue, for waves. Now, imagine the dual nature as a gradient, where the circle is made up of both colours mixed in some proportion. You could also think of it as just a green circle, not a gradient but still a mixture of the two states. However, as you can probably tell, this is an extremely crude analogy which quickly falls apart if you dig a little deeper, but I think it gets the point across. Another interesting thing about this dual nature is that it is only exerted when matter is not being observed. Start observing matter in any way, and it will conform to either particle or wave form.
Now what’s the point of telling you all of this? Well, this is the basic principle on which quantum computing works. But before we get into that, we must know how traditional computers work. Computers are, essentially, a bunch of transistors, tiny circuits that can either be switched on, allowing current to flow, or switched off, obstructing current. These two states of transistors are used as the basis for the binary system, where a single bit represents a single transistor. Consider the binary system as a counting system, similar to the base ten counting system that we use every day (base 10 because we have the 1s place, the 10s place, the 100s place and so on, increasing powers of 10. The binary system is a base two counting system, i.e. it has a 1s place, a 2s place, a 4s place and so on). Transistors allow the computer to count using the binary system, and once a computer can count, it can do a bunch of more complex operations*.
A 0 in the binary system represents a transistor that is switched off, and a 1 represents a transistor that’s switched on. Together, just a few bits can result in a large number of unique combinations. Since the binary system is a way for our computer to count, a larger number of combinations means it can count up to larger numbers, and thus execute more complex operations. The number of possible combinations increases exponentially, so where 2 bits can give you 2², 4 combinations (01, 10, 00, 11), 8 bits can give you 2⁸, 256 combinations. Modern computers are made up of millions of transistors. That’s a lot of bits and a lot of combinations.
So, basically, the more transistors a computer is made of, the more powerful it is. However, a larger number of transistors would mean a larger computer, so scientists just kept on making transistors smaller and smaller. Today, a typical transistor (around 20 nanometers) is about five hundred times smaller than a red blood cell (6–8 micrometers). They are so small that we literally cannot make them any smaller, lest they fail to block electrons**, thus defeating the very purpose of a transistor. That means we cannot make modern computers more powerful without increasing their sizes to ridiculous proportions, which is no longer enough as the increase in computational power is not very substantial. Well, that’s where quantum computers come in.
Instead of using transistors, quantum computers use any quantum system with two states as a basis for the binary system. A quantum system is any system that shows dual nature. This could be a fundamental particle such as an electron, a photon or even something like a superconductor. Instead of the two states of on and off, these systems have different properties that can be used to represent the binary units, 0 and 1. These properties could include the polarization of a photon (which has two possible states, vertically polarized or horizontally polarized) or two energy states of an electron (an electron can have more than two energy states, but any two adjacent ones are chosen and the electron is forced to stay in either of the two states, or, until observed, in both).
Since a quantum system can exist in a superposition of both states when not observed, it can represent all possible states at once. So, a bit has its value fixed to either 0 or 1 and it will keep this value regardless of whether we observe it or not. But a qubit, which is what quantum bits are called, is in superposition, which means it has both of these values at once, until it’s observed. Remember that this does not mean that it has a value between the two, but both values at the same time, as confusing as that is.
Normally, 2 bits could lead to 4 different combinations. To represent all of these, you would require 4 sets of 2 bits each, or 8 bits in total. Now since a qubit can represent both 0 and 1 at the same time, you could use 2 qubits to represent all of their different combinations at the same time. All possibilities can be represented with the same couple of qubits. And remember, the difference increases exponentially. So 8 qubits could represent 256 combinations at once, which would require a normal computer 8 x 256 = 2048 bits. So 8 qubits could replace 2048 bits, and just 20 qubits could replace more than a million bits. When you have to do some operation using a set of qubits, you can force them into any combination you need, because the instant you observe the quantum system, it collapses into either one of the possibilities. THIS is the reason quantum computers are so important, because they could increase our computational power beyond our wildest imaginations, while using a ridiculously small number of qubits.
In late 2019, Google’s quantum computing project reported that they had achieved quantum supremacy, which means they had used a quantum computer to solve a problem that would take any normal computer (supercomputers are generally used as the reference) a non-feasible amount of time, ten thousand years in the case of the problem the team chose. To do this, they used 53 qubits. 53, that’s it. The biggest supercomputer in the world, which has 8.79 BILLION transistors, would need 10000 years to solve the problem, which the quantum computer solved in 200 seconds. The difference here is unfathomable.
However, having a lot of computational power does not matter if you can’t do anything with it. Thankfully, there are hundreds of existing fields where this power could be utilized. We could simulate entire galaxies with quantum computers, something astrophysicists could only dream of before. This would allow us to understand the formation of stars and galaxies better.
We could also simulate molecular interaction involving millions of molecules, in order to understand the mechanism behind chemical reactions, which could then allow us to manipulate these interactions for our benefit, such as by creating new and improved drugs.
More practical applications include simulating the weather, which could make weather forecasting way more accurate than it is today. Financial modeling and simulations could predict economic crises, and further our understanding of the behaviour of economic systems.
We could develop better Artificial Intelligence as the increased computational capacity would allow for much more efficient self-learning systems.
The possibilities are endless, and as fascinating as quantum computers themselves.
* The binary system is a really clever bit of mathematics and logic that essentially allows a computer to perform various fundamental arithmetic and logical operations, which form the basis of advanced computation. It is quite complex however, and so I could not explain it in detail here, partly because I have not understood it completely myself. If you want to learn more about it, I would recommend the Computer science crash course by ‘CrashCourse’, particularly the 5th episode, the ALU crash course: https://www.youtube.com/watch?v=1I5ZMmrOfnA
If you don’t have the time to watch an entire series of videos, here’s a shorter video by ‘Basics Explained, H3Vtux’ that covers the basics:
https://www.youtube.com/watch?v=Xpk67YzOn5w
**Electrons are actually much, much smaller than even the smallest transistors at around 2 X 10^-15 m (or 0.000002 nanometers) but they can pass through the transistor via a process called quantum tunneling, an interesting quantum phenomena which you can read more about here: https://en.wikipedia.org/wiki/Quantum_tunnelling
