Skip to Content

The Problem With Quantum Lithography

Entangled photons can dramatically reduce the feature sizes possible with lithography. At least, that’s what physicists had hoped.

Lithography, the ability to print patterns onto certain materials using light, is one of the enabling technologies of our age. The size of the features that can be defined this way are tiny, limited only by the wavelength of light used to make them, the so-called diffraction limit.

And yet that isn’t nearly small enough for chip makers who demand ever smaller feature sizes. The problem is that as the wavelength of light gets shorter, the photons become more energetic and harder to control. That causes several problems. First, the photons can damage the material thy are supposed to be interacting with. And second, optics that can focus these energetic beams become more difficult to make.

In fact, it’s hard to see how chipmakers are going to cope with light beyond the extreme ultraviolet.

At least, it was hard until 2000 when a group of physicists proved that it was possible to get around this limit by using entanglement, the weird phenomenon in which quantum objects like photons share the same existence.

These physicists showed that by entangling a number of photons it is possible to dramatically reduce the feature size they can produce. The idea is that if you create an interference pattern in the shape you your want to print onto a surface, the feature size can be made much smaller if you use entangled photons. In fact, if you entangle N photons, you can beat the diffraction limit by 1/N.

Of course, there are all kinds of challenges in doing this such as finding materials that are influenced by ensembles of entangled photons.

But the fact that so-called quantum lithography is possible at all came as a huge relief to lithographers.

They may not be so happy this morning, however. Christian Kothe at the Royal Institute of Technology in Sweden and a few pals have shown that there is a fundamental problem with quantum lithography: it just doesn’t work very well.

The question is one of efficiency: how long would you need to expose a sample to achieve the desired improvement in resolution. This is related to how far the entangled photos spread out. Lithography only takes place when the photons all strike in the same place so the important question is how likely they are to all land together.

There are two schools of thought on this. The first is that the nature of entanglement means that the area where the photons can hit is dramatically constrained after the first one has hit. So they are actually quite likely to all land together.

However, another line of thought is that the photons are not constrained in any way and that lithography can only proceed when they all land together by chance. Naturally, this takes long time and would make quantum lithography hugely innefficient .

Kothe and co today show that data from recent experiments indicates that the second interpretation appears to be correct and that increasing the number of entangled photons exponentially increases the time it takes to form a pattern. “Therefore, quantum lithography involving a large number of pixels or a large number of photons unfortunately seems to be impractical,” they conclude.

Ref: arxiv.org/abs/1006.2250: On The Efficiency Of Quantum Lithography

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

The problem with plug-in hybrids? Their drivers.

Plug-in hybrids are often sold as a transition to EVs, but new data from Europe shows we’re still underestimating the emissions they produce.

Google DeepMind’s new generative model makes Super Mario–like games from scratch

Genie learns how to control games by watching hours and hours of video. It could help train next-gen robots too.

How scientists traced a mysterious covid case back to six toilets

When wastewater surveillance turns into a hunt for a single infected individual, the ethics get tricky.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.