Toggle light / dark theme

As a general rule, if you want sight, you need light. You’re only reading this right now thanks to the light from your screen being beamed onto your retinas, converted into electrical signals, and sent up the optic nerve for your brain to interpret as a bunch of words and images.

But what if you could see things without all that rigamarole? It might sound impossible – perhaps even counter to the very definition of sight – but thanks to the bizarre world of quantum mechanics, it’s actually perfectly possible.

“Since the inception of quantum mechanics, the quest to understand measurements has been a rich source of intellectual fascination,” notes a new paper published this month.

Yet the notion that we inhabit a space with any mathematical structure is a radical innovation of Western culture, necessitating an overthrow of long-held beliefs about the nature of reality. Although the birth of modern science is often discussed as a transition to a mechanistic account of nature, arguably more important – and certainly more enduring – is the transformation it entrained in our conception of space as a geometrical construct.

Over the past century, the quest to describe the geometry of space has become a major project in theoretical physics, with experts from Albert Einstein onwards attempting to explain all the fundamental forces of nature as byproducts of the shape of space itself. While on the local level we are trained to think of space as having three dimensions, general relativity paints a picture of a four-dimensional universe, and string theory says it has 10 dimensions – or 11 if you take an extended version known as M-Theory. There are variations of the theory in 26 dimensions, and recently pure mathematicians have been electrified by a version describing spaces of 24 dimensions. But what are these ‘dimensions’? And what does it mean to talk about a 10-dimensional space of being?

As computer scientists tackle a greater range of problems, their work has grown increasingly interdisciplinary. This year, many of the most significant computer science results also involved other scientists and mathematicians. Perhaps the most practical involved the cryptographic questions underlying the security of the internet, which tend to be complicated mathematical problems. One such problem — the product of two elliptic curves and their relation to an abelian surface — ended up bringing down a promising new cryptography scheme that was thought to be strong enough to withstand an attack from a quantum computer. And a different set of mathematical relationships, in the form of one-way functions, will tell cryptographers if truly secure codes are even possible.

Computer science, and quantum computing in particular, also heavily overlaps with physics. In one of the biggest developments in theoretical computer science this year, researchers posted a proof of the NLTS conjecture, which (among other things) states that a ghostly connection between particles known as quantum entanglement is not as delicate as physicists once imagined. This has implications not just for our understanding of the physical world, but also for the myriad cryptographic possibilities that entanglement makes possible.

It now costs between $3bn-4bn to build a silicon chip fabrication plant (fab plant), and consequently, there are relatively few fabs around the world.-from 2019.


UK companies get ahead of the curve with investments in R&D and fabrication infrastructure for next-gen electronics. Andy Sellars, Chief Business Development Officer, UK Catapult, explains the strategy.

Artificial intelligence (AI) and quantum computing require compound semiconductors to achieve full commercialisation.