How close are quantum computers to being really useful? Podcast
Quantum computers have the potential to solve big scientific problems that are beyond the reach of today's most powerful supercomputers, such as discovering new antibiotics or developing new materials.
But to achieve these breakthroughs, quantum computers will need to perform better than today's best classical computers at solving real-world problems. And they're not quite there yet. So what is still holding quantum computing back from becoming useful?
In this episode of The Conversation Weekly podcast, we speak to quantum computing expert Daniel Lidar at the University of Southern California in the US about what problems scientists are still wrestling with when it comes to scaling up quantum computing, and how close they are to overcoming them.
Quantum computers harness the power of quantum mechanics, the laws that govern subatomic particles. Instead of the classical bits of information used by microchips inside traditional computers, which are either a 0 or a 1, the chips in quantum computers use qubits, which can be both 0 and 1 at the same time or anywhere in between. Daniel Lidar explains:
'Put a lot of these qubits together and all of a sudden you have a computer that can simultaneously represent many, many different possibilities … and that is the starting point for the speed up that we can get from quantum computing.'
One of the biggest problems scientist face is how to scale up quantum computing power. Qubits are notoriously prone to errors – which means that they can quickly revert to being either a 0 or a 1, and so lose their advantage over classical computers.
Scientists have focused on trying to solve these errors through the concept of redundancy – linking strings of physical qubits together into what's called a 'logical qubit' to try and maximise the number of steps in a computation. And, little by little, they're getting there.
In December 2024, Google announced that its new quantum chip, Willow, had demonstrated what's called 'beyond breakeven', when its logical qubits worked better than the constituent parts and even kept on improving as it scaled up.
Lidar says right now the development of this technology is happening very fast:
'For quantum computing to scale and to take off is going to still take some real science breakthroughs, some real engineering breakthroughs, and probably overcoming some yet unforeseen surprises before we get to the point of true quantum utility. With that caution in mind, I think it's still very fair to say that we are going to see truly functional, practical quantum computers kicking into gear, helping us solve real-life problems, within the next decade or so.'
Listen to Lidar explain more about how quantum computers and quantum error correction works on The Conversation Weekly podcast.
This episode of The Conversation Weekly was written and produced by Gemma Ware with assistance from Katie Flood and Mend Mariwany. Sound design was by Michelle Macklem, and theme music by Neeta Sarl.
Clips in this episode from Google Quantum AI and 10 Hours Channel.
You can find us on Instagram at theconversationdotcom or via e-mail. You can also subscribe to The Conversation's free daily e-mail here.
Listen to The Conversation Weekly via any of the apps listed above, download it directly via our RSS feed or find out how else to listen here.
This article is republished from The Conversation under a Creative Commons license. Read the original article.
Daniel Lidar receives funding from the NSF, DARPA, ARO, and DOE.
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