Quantum technology promises to spark a revolution in computing as significant as the integrated circuit in the 1950s and 60s. Evrim Yazgin helps us master the basics of quantum computing today, to imagine where quantum simulators will take us tomorrow. This article originally appeared in the Cosmos Print Magazine in December 2024. <\/p>\n
Integrated circuits form the basis of modern \u2018classical\u2019 computing. There can be hundreds of these microchips in a laptop or personal computer. Their size has meant that now mobile phones have computing power thousands of times faster than the most powerful supercomputers built in the 1980s.<\/p>\n
Since the 1990s, supercomputers have come into their own. The most powerful supercomputer in the world, Frontier based in the US, has a million times more computing power than top-tier gaming PCs.
But these devices are still based on the classical technology of integrated circuits and are therefore limited in their capabilities.<\/p>\n
Quantum computers promise to be able to process calculations thousands, even millions of times faster than modern computers.<\/p>\n
We\u2019re not there yet, though.<\/p>\n
Quantum computer concept. Credit: Bartlomiej Wroblewski iStock \/ Getty Images Plus.<\/p>\n
Quantum does not compute<\/p>\n
Quantum computers have been in development for decades.<\/p>\n
These devices use the principles of quantum mechanics \u2013 which produce bizarre and seemingly magical effects \u2013 for machines which can do things that aren\u2019t possible using modern classical computers.<\/p>\n
Classical computers use bits \u2013 zeroes and ones \u2013 to encode information as binary signals in transistors in their integrated circuits.<\/p>\n
Quantum computers use quantum bits \u2013 called qubits. These can encode information as zeroes, ones or a mix of zero and one thanks to the quantum phenomenon known as superposition.<\/p>\n
Particles in a superposition of states aren\u2019t defined by single values for their physical properties. Instead, these physical properties are expressed as probabilities.<\/p>\n
Engineers can make use of superpositions to store multidimensional computing data in qubits of much greater complexity than an ordinary classical bit.<\/p>\n
Extending the effects of superposition over multiple systems \u2013 or atoms \u2013 leads to quantum entanglement. This phenomenon, which Einstein famously described as \u201cspooky action at a distance\u201d, can be used to link qubits together leading to lip-licking prospects such as unhackable encryption.<\/p>\n
But the same quantum mechanics which gives quantum computers their great potential means they are extremely difficult to actually produce.<\/p>\n
Gavin Brennen, a professor at Macquarie University in Sydney and director at the Macquarie Centre for Quantum Engineering, helps explain why this is the case.<\/p>\n
\u201cThe problem with anything quantum is, if we look at the world around us, it\u2019s not very quantum,\u201d Brennen says. \u201cWe don\u2019t find ourselves walking through walls. We don\u2019t find objects in superpositions. When things become larger and warmer, and they tend to act less quantum.\u201d<\/p>\n
\u201cIf you\u2019re working with a single electron, that\u2019s going to act very quantum,\u201d he adds. <\/p>\n
\u201cOr maybe a single atom \u2013 which is a collection of electrons, protons and neutrons \u2013 that can act pretty quantum. But when you try to get thousands of those things to act quantum, it\u2019s very\u00a0hard.\u201d<\/p>\n
Brennen says this is due to an effect called \u201cdecoherence\u201d.<\/p>\n
\u201cIt\u2019s noise. The more things you have to control, the more things they can interact with. And the things they interact with get information. Your quantum system leaks information and when it does that it loses the properties that make it quantum,\u201d Brennen explains.<\/p>\n
Brennen says \u201cyou have to play a lot of games\u201d including cooling the system down and removing coupling between the quantum device and the rest of the world to try and reduce decoherence.<\/p>\n
The physicist is speaking to me online from Helsinki, Finland where he is attending a conference called Quantum Resource Estimation at which researchers are discussing such problems.<\/p>\n
\u201cIt\u2019s pretty interesting,\u201d Brennen says. \u201cIt\u2019s about trying to find ways to make quantum computers more efficient for solving problems, like ways to make error correction work better and tricks to make algorithms faster.\u201d
Quantum error correction is one way of tackling decoherence. The idea is to develop algorithms using more qubits to increase redundancies in the quantum system and reduce signal loss. It\u2019s a bit like having more backups.<\/p>\n
Eventually, such methods will lead to quantum devices being able to do things that today\u2019s computers can\u2019t.<\/p>\n
A qubit generator for quantum photonic computers at Quandela, a French start-up. Credit: ALAIN JOCARD\/AFP via Getty Images<\/p>\n
Quantum see, quantum do<\/p>\n
Among the people most excited to see quantum computers are quantum chemists.<\/p>\n
\u201cThe UN has declared next year 2025 as the International Year of Quantum Science and Technology,\u201d says Amir Karton, a professor at the University of New England in New South Wales.<\/p>\n
\u201cIt essentially marks 100 years since the Schr\u00f6dinger equation.\u201d<\/p>\n
Karton explains that this fundamental equation, developed by Erwin Schr\u00f6dinger in 1925, describes the quantum mechanics of different systems. Solve the equation for a system and you can understand its properties.<\/p>\n
\u201cWe\u2019ve been able to be able to solve the Schr\u00f6dinger equations for very small molecules, or very small systems with a small number of electrons in the last 100 years,\u201d Karton explains. \u201cFor example, solving the equation for the hydrogen molecule was done in the 1920s.\u201d<\/p>\n
Systems with more electrons and other subatomic particles require solving more complex sets of equations. Karton says that solving anything with more than a handful of electrons wasn\u2019t possible until supercomputers came around in the 1990s.<\/p>\n
\u201cWhat we\u2019ve been able to do over the last 5 or 10 years is to model real chemical systems \u2013 molecules and materials,\u201d Karton says. \u201cThat enables us to design better drugs, better catalysts, better materials for various applications without the need to go into the lab.\u201d<\/p>\n
Karton says, for example, that quantum chemists may need to test hundreds or thousands of catalysts to see which ones are most effective. Doing this in a lab is not feasible. Having a quantum machine to simulate this would speed the process up.<\/p>\n
\u201cWe can calculate a catalytic enhancement of all these potential catalysts and have really good insights of what\u2019s going to work. Then we would collaborate with experimental groups to then test the proposed catalyst.\u201d<\/p>\n
For quantum chemists like Karton, quantum computers able to solve the Schr\u00f6dinger equation for even more complex molecules and materials would be a huge boon. The ultimate question is how can you build a device which is powerful enough to simulate the complex quantum mechanics of molecules?<\/p>\n
Decoherence means that such useful machines are still a while away.<\/p>\n
But there may be a type of quantum simulator which could give Karton and his ilk something to look forward to in the nearer term.<\/p>\n
\u201cThe field divides it into 2 types of simulators,\u201d says Brennen. \u201cThere\u2019s digital and analogue.\u201d<\/p>\n
The digital quantum simulator \u2013 loosely, the quantum computers in development \u2013 attempts to use algorithms and gates (logical operations) to simulate the quantum mechanics of particles in complex systems.<\/p>\n
On the other hand, Brennen explains, \u201canalogue quantum simulators try to mimic the interactions of a system you\u2019d like to understand by designing those interactions into a quantum device that you can control.\u201d<\/p>\n
\u201cYou tune up, fix the positions of some qubits, and make them interact. Turn on some fields and just let it go. There\u2019s no sense of doing discrete sets of gates with error correction happening in between. You just try to get the thing to mimic what you\u2019re trying to simulate as best as you can, and then let it go and do some measurements.\u201d<\/p>\n
Brennen likens this \u201canalogue\u201d quantum simulation to experiments and classical computing.<\/p>\n