ColdQuanta raises $6.75M to make it easier to spin up a limited use-case quantum computer
Quantum computing may be a long ways off, but early applications of it aren’t as far off as you might think, according to longtime researcher and ColdQuanta founder Dana Anderson.
The startup creates a device that’s designed to make it easier to start operating quantum computing-like operations on near-term problems like signal processing or time measurement, which is the kind of low-hanging fruit that current technology might enable. Researchers using that approach — a set of atoms where there’s practically no motion — require some mechanism of keeping them from moving, for which some cases involve refrigeration. ColdQuanta’s main product is a set of lasers that’s able to stabilize a set of atoms and allow them to operate with those properties. It’s certainly nowhere close to a server — or even a standard computer — but using this kind of a tool, it might be easier to handle tasks like real-time signal processing. ColdQuanta said today that it has raised $6.75 million in a round led by Maverick Ventures and including Global Frontier Investments.
“If you weren’t look out the window, and you turned off GPS because it’s a conflict or sunspots, you can ask, ‘can I fly to New York from San Francisco with my eyes closed,’” Anderson said. “The answer is no. These types of applications — real world applications based on fundamental advances of physics — keeps me thinking, and up at night. Clocks sound pretty boring, and you might ask why do I need something like that. But there’s enormous demand for improvements in time-keeping, whether for high frequency trading, navigation, guidance, or autonomous vehicles. We see those as early applications.”
The primary aim of ColdQuanta’s hardware is, Andersen says, to create a “neutral” set of atoms that all have identical properties of the ones next to them. It does that by using a set of lasers to bring them to a near standstill — within a millionth of a degree of absolute zero — and then control their properties using lasers. That way, a researcher or team could scale that up to a larger system where they can start finding applications right away. That includes time-keeping, secure communications, and others, now that a lot of the primary limitations of the technology have gotten a little more relaxed over time. ColdQuanta’s aim is to be able to do this in a normal, room-temperature situation throughout the environment everywhere else as well. The lasers are tuned in such a way that a stream of photons hitting each atom slows it down until it’s largely stable (also being held up by another set of lasers to account for gravity).
“Laser technology was unreliable in the early days, that was mostly a time when things weren’t working, and most often it was the laser,” Anderson said. “What ColdQuanta is focused on, now for 11 years, is technology that could be manufactured in large quantities, making reliable, small, and robust equipment. If you looked at the initial quantum gas machine it took a couple of square meters of area on a table plus tons of electrics. Now we’ve made it small enough that there’s one sitting on the ISS. It’s a fairly small package, mostly because integration techniques, improvements in lasers, and developing key electronics components have helped us achieve this task.”
There may be an analogy between what’s happened with the emergence of the widespread use of deep learning for a variety of tasks and the early stages of products like ColdQuanta. Deep Learning, Andersen said, was the key innovation on the change in a lot of machine learning models, but there were plenty of smaller use cases where it was interesting and useful — even back in the 1990s. Andersen said there will probably be a similar situation going forward as limited quantum computing will find some near-term applications and then exist on a similar timetable as other technological shifts as it waits for the biggest, cheapest, and most powerful use case that demands widespread adoption.
“I see the path we’re going on is very familiar,” Andersen said. “I don’t think the technological challenges we face are improbable. We’ve been through other difficult technology roadmaps before and overcome them. The landscape is very familiar. The timescale of inserting them into real-world problems gets kind of fuzzy when you have to predict so far off, but I think quantum computers will get there. I’m quite convinced there will be modest applications of quantum computers that will show up very soon. Quantum simulation, I have almost no doubt, will find pure science uses and begin to apply to at least in restricted spaces relative to national security and defense.”