Quantum computers are a term which has been gaining popularity recently especially with a large amount of revenue dedicated to its research each year. While the general populous is aware of the fact that research is being done in this field but not many are truly aware of the complexities and working principles behind it. This article aims to provide a basic overview of the principals involved, issues faced, and solutions to tackle them. Basically, Quantum computing is the use of quantum-mechanical phenomena such as superposition and entanglement to perform computation.
The field of quantum computing is actually a sub-field of quantum information science, which includes quantum cryptography and quantum communication. Quantum Computing was started in the early 1980s when Richard Feynman and Yuri Manin expressed the idea that a quantum computer had the potential to simulate things that a classical computer could not. In 1994, Peter Shor published an algorithm that is able to efficiently solve some problems that are used in asymmetric cryptography that are considered hard for classical computers.
There are currently two main approaches to physically implementing a quantum computer: analog and digital. Analog approaches are further divided into quantum simulation, quantum annealing, and adiabatic quantum computation. Digital quantum computers use quantum logic gates to do computation. Both approaches use quantum bits or qubits.
Qubits are fundamental to quantum computing and are somewhat analogous to bits in a classical computer. Qubits can be in a 1 or 0 quantum state. But they can also be in a superposition of the 1 and 0 states. However, when qubits are measured the result is always either a 0 or a 1; the probabilities of the two outcomes depends on the quantum state they were in.
Today’s physical quantum computers are very noisy and quantum error correction is a burgeoning field of research. Unfortunately, existing hardware is so noisy that fault-tolerant quantum computing is still a rather distant dream. As of April 2019, no large scalable quantum hardware has been demonstrated, nor have commercially useful algorithms been published for today’s small, noisy quantum computers. There is an increasing amount of investment in quantum computing by governments, established companies, and start-ups. Both applications of near-term intermediate-scale device and the demonstration of quantum supremacy are actively pursued in academic and industrial research.
A quantum computer harnesses some of the almost-mystical phenomena of quantum mechanics to deliver huge leaps forward in processing power. Quantum machines promise to outstrip even the most capable of today’s — and tomorrow’s — supercomputers.
They won’t wipe out conventional computers, though. Using a classical machine will still be the easiest and most economical solution for tackling most problems. But quantum computers promise to power exciting advances in various fields, from materials science to pharmaceuticals research. Companies are already experimenting with them to develop things like lighter and more powerful batteries for electric cars, and to help create novel drugs.
Today’s computers use bits — a stream of electrical or optical pulses representing 1s or 0s. Everything from your music, games, videos, etc., are essentially long strings of these binary digits.
Quantum computers, on the other hand, use qubits, which are typically subatomic particles such as electrons or photons. Generating and managing qubits is a scientific and engineering challenge. Some companies, such as IBM, Google, and Rigetti Computing, use superconducting circuits cooled to temperatures colder than deep space. Others, like IonQ, trap individual atoms in electromagnetic fields on a silicon chip in ultra-high-vacuum chambers. In both cases, the goal is to isolate the qubits in a controlled quantum state.
Qubits have some quirky quantum properties that mean a connected group of them can provide way more processing power than the same number of binary bits. One of those properties is known as superposition and another is called entanglement.
Qubits can represent numerous possible combinations of 1 and 0 at the same time. This ability to simultaneously be in multiple states is called superposition. To put qubits into superposition, researchers manipulate them using precision lasers or microwave beams.
Thanks to this counterintuitive phenomenon, a quantum computer with several qubits in superposition can crunch through a vast number of potential outcomes simultaneously. The final result of a calculation emerges only once the qubits are measured, which immediately causes their quantum state to collapse and revert to either 1 or 0.
Researchers can generate pairs of qubits with quantum entanglement which means the two members of a pair exist in a single quantum state. Changing the state of one of the qubits will instantaneously change the state of the other one in a predictable way. This happens even if they are separated by very long distances.
Nobody really knows quite how or why entanglement works. This phenomenon also baffled Einstein, who famously described it as “spooky action at a distance.” But this is inherently necessary to the power of quantum computers. In a conventional computer, doubling the number of bits doubles its processing power. But thanks to entanglement, adding extra qubits to a quantum machine produces an exponential increase in its number-crunching ability.
Quantum computers harness entangled qubits in a kind of quantum daisy chain in order to perform computational tasks. The machines ability to speed up calculations using specially designed quantum algorithms is key to unlocking its potential.
While the advantages of a quantum computers are clear to see, however, the bad news is that quantum machines are way more error-prone than classical computers because of decoherence.
The interaction of qubits with their environment in ways that cause their quantum behavior to decay and ultimately disappear is called decoherence. Their quantum state is extremely fragile. The slightest vibration or change in temperature — disturbances known as “noise” in quantum-speak — can cause them to tumble out of superposition before their job has been properly done. That’s why researchers do their best to protect qubits from the outside world in those supercooled fridges and vacuum chambers.
But despite their efforts, noise still causes lots of errors to creep into calculations. Smart quantum algorithms can compensate for some of these, and adding more qubits also helps. However, it will likely take thousands of standard qubits to create a single, highly reliable one, known as a logical qubit. This, in turn, drains a lot of a quantum computer’s computational capacity.
And so far, researchers haven’t been able to generate more than 128 standard logical qubits which is far from the amount necessary to perform and complex tasks. So, we’re still many years away from getting quantum computers that will be broadly useful.
Despite the drawbacks of decoherence, the aim of all companies and researchers working on quantum computers is to achieve quantum supremacy. This is the point at which a quantum computer can complete a mathematical calculation that is demonstrably beyond the reach of even the most powerful supercomputer.
It’s still unclear exactly how many qubits will be needed to achieve this because researchers keep finding new algorithms to boost the performance of classical machines, and supercomputing hardware keeps getting better. But researchers and companies are working hard to claim the title, running tests against some of the world’s most powerful supercomputers.
There’s plenty of debate in the research world about just how significant achieving this milestone will be. Rather than wait for supremacy to be declared, companies are already starting to experiment with quantum computers made by companies like IBM, Rigetti, and D-Wave, Alibaba, etc. Some businesses are even buying current large and bulky quantum computers, while most others are using ones made available through cloud computing services.
Current uses of quantum computing
One of the most promising applications of quantum computers is for simulating the behavior of matter down to the molecular level. Auto manufacturers like Volkswagen and Daimler are using quantum computers to simulate the chemical composition of electrical-vehicle batteries to help find new ways to improve their performance. And pharmaceutical companies are leveraging them to analyze and compare compounds that could lead to the creation of new drugs.
The machines are also great for optimization problems because they can crunch through vast numbers of potential solutions extremely fast. Airbus, for instance, is using them to help calculate the most fuel-efficient ascent and descent paths for aircraft. And Volkswagen has unveiled a service that calculates the optimal routes for buses and taxis in cities in order to minimize congestion. Some researchers also think that quantum computers could be used to accelerate developments in artificial intelligence.
It could take quite a few years for quantum computers to achieve their full potential. Universities and businesses working on them are facing a shortage of skilled researchers in the field — and a lack of suppliers of some key components. However, recent promising developments such as nanofridges could provide potential cooling solutions to the quantum circuits and possibly reduce decoherence. But any real-world applications of this, for potential consumer grade quantum computers, is still 10 to 15 years away at least. If these exotic new computing machines live up to their promise and expectations, they could usher in an age of innovation and possibly change entire industries.