THURSDAY, 2 JUNE 2022Quantum computers are notorious for being prohibitively difficult to wrap our heads around. ‘If you think you understand quantum mechanics, you don't understand quantum mechanics’, said Richard Feynman, a brilliant theoretical physicist and eloquent communicator. Therefore, to understand them is impossible, and we are not going to try. But although we cannot truly envisage wavefunctions and quantum spins, an intuitive understanding of quantum computation can still be achieved without having to clamber through the horrible maths.
Let us look at how classical computers work and build our understanding of the quantum version from there.
Return to the classics
So, what is inside your run-of-the-mill computer? The digital theatrics have two key components: information (the actors) and instructions (the script). In the computer’s memory, information is stored as bits — an endless stream of 0s and 1s. The infinite monkey theorem states that given enough time, a monkey smashing at a typewriter could produce the complete works of William Shakespeare. Likewise, a sufficiently long string of bits can represent anything between ‘this pixel is blue’, ‘the time is 4am’, and ‘the answer is 42’. The intricate drama between bits is orchestrated by the instructions. With every click of the mouse and tap on the keyboard, you ask the computer to process a set of instructions on a sequence of bits. These instructions come in the form of logic gates. For instance, the NOT gate takes a single bit and flips it, while the OR gate takes two bits and outputs 0 only when both inputs are 0.
These bits and gates are not just abstract entities floating in the computer’s digital consciousness. There are many ways bits can be represented. Generally, the 0s and 1s are encoded by tiny magnets that point one way for 0 and the other for 1, or by the absence or presence of electrical charges in little units. The gates take the form of transistors — tiny circuits that take in input bits as little currents of electricity, control their flow, and release currents that represent output bits.
The quantum variant
Fundamentally, quantum computers differ from classical ones in the way they store and process information — not as bits but as qubits. Think of these as indecisive bits, like little magnets spinning round and round, only landing on a 0 or 1 when you force them to stop. Of course, real qubits are not spinning magnets. How best to realise these indecisive bits is still an area of ongoing research. Essentially, we need tiny objects with two possible states, and the likelihood of them being in one state over another is determined by the laws of quantum mechanics.
Naturally, a quantum computer is not a computer if we cannot implement logic gates as we do for classical computers. Instead of transistors, each variant of qubits demands a unique toolbox of physical processes to perform the necessary operations. Take a primitive example of a qubit — an electron in a hydrogen atom either in the low-energy ground state (0) or high-energy excited state (1). The aforementioned OR gate can be implemented by ‘connecting’ two input electrons to an output, and, if either or both inputs are excited by a photon (10, 01, or 11), then at least one of them can pass the energy and excite the output (1). In other words, only when none of the input is excited (00) will we get a non-excited output (0). Returning to the idea of ‘indecisiveness’, if we then ‘connect’ one excited input to two outputs, then we know for sure that either of the outputs will be 1 and the other will be 0, but the electrons are undecided about which is which, and there is no way to tell them apart until you measure one of them. This is what physicists mean when they say, ‘qubits can exist in a superposition of states, which collapses when measured’.
Peaks and troughs
In sum, qubits can be manipulated with logic gates analogous to their classical counterparts, but their quantum behaviours also enable proprietary gates exclusive to quantum objects. Our previous one input-two output setup illustrates two such properties: superposition (the output electrons are in both the ground and excited state until measured) and entanglement (the state of one output atom implies the state of the other). Herein lies the strength of quantum computers. In terms of computability, any problem that a classical computer can solve, a quantum version can do likewise, and the reverse is also true. However, in terms of complexity, quantum computers can reinterpret and simplify certain problems with quantum logic gates to solve them faster, sometimes exponentially so.
There is a caveat here: quantum computers are not substitutes for classical computers. The quantum infrastructure, while promising, has its own host of problems. For one, while nature is immensely powerful in that she orchestrates quantum interactions of unimaginable complexity, she also communicates the result cryptically — a waveform of dense information disperses when observed, leaving behind a single hint — 0 or 1. Our best attempt to grasp the underlying truth is to query nature again and again, reconstructing the message one letter at a time. Consequently, quantum results are always statistical. Not only that, but to manipulate qubits into doing our bidding is like moving a balloon using hands of needles through lava. Qubits only work as qubits if they stay quantum, but any interaction with stray molecules or radiation reduces them to normal bits in a process called decoherence. Another natural enemy of quantum computers is noise. Initialising the states of qubits, applying quantum operations, and even taking measurements can, and will, introduce errors. When you add all this up, you have a calculator that writes ‘6’ when you press ‘9’, and reads ‘4’ when it means ‘20’. These constraints deny the possibility of a quantum monopoly. In fact, a quantum-classical hybrid infrastructure looks to be leading the impending computational succession.
A quantum leap
Between an infallible promise and inevitable demise, where is the quantum revolution heading? Whether quantum supremacy — the phenomenon wherein quantum computers outspeed classical computers in a particular calculation — has been achieved is still up for debate, and while tech giants worldwide have their hopes and money in the quantum future, quantum computers are still a work-in-progress. On the theoretical front, idealists are formulating quantum algorithms that assume perfect, large-scale quantum networks, swearing to leave classical computers in the dust when they eventually have the hardware to realise the codes. Concurrently, development is underway for noisy intermediate-scale quantum (NISQ) algorithms and error correction techniques that make do with the dozens of noisy qubits we currently have to produce some interesting results. In experimental labs under impenetrable radiation shields, within cryogenic chambers and between crisscrossing lasers, the search for the holy grail of sturdy but obedient qubits continues.
Although the quantum revolution may not be just around the corner, it sure is coming. Just as classical computers evolved from vacuum tubes and magnetic drums filling entire rooms in the 1940s to the coin-sized microelectronics today, we can expect the same for quantum computers. The vacuum tubes and magnetic drums of quantum computers today will eventually give way to supercomputers that can simulate complex systems, develop life-saving drugs, rewire financial markets, transform cybersecurity, and advance artificial intelligence, all within our lifetime.
Xavior Wang is a second-year undergraduate at St Edmund’s College studying Natural Sciences. Illustration by Josh Langfield.