This week we sat down for an interview with Qubit the dog, whose human Julian Kelly is one of our lead Research Scientists with Google Quantum AI. Qubit was born in 2012, right when Julian and team were first designing the qubits that now underlie Google’s quantum computers. He nearly received the honor of pressing the submit button for the team’s beyond-classical result published in Nature, but he was narrowly edged out by a human.
Qubit has never been interviewed before on such a range of technical and philosophical topics, so it was a privilege to have the opportunity — a transcript of the discussion follows.
Thank you for taking the time to sit down for this, Qubit. Given the complexity and depth of the topic, I was hoping we could jump right in. I first wanted to ask — where do you think we are in the “hype cycle” of quantum computing? Is this analogous to earlier hype cycles around ecommerce, AI, mobile technology or other major shifts where the hype may have led to “winters” for some time before the technology caught up and eventually surpassed the initial expectations about the significance of its impact on users and society, especially in terms on unexpected applications and feedback dynamics?
Okay, that makes sense, there does seem to be a certain unavoidable nature to that cycle that resolves itself naturally. But how should we consider investment in alternate veins of quantum computing research and development — for example, while there appears to be a viable roadmap for superconducting qubits, with evidence that error suppression can scale and enable a fully fault-tolerant large-scale quantum computer within the decade, does it make sense to also explore more speculative approaches such as photonics or spin qubits?
Granted, that may all shake out in time as these technical milestones prove out. What, if I may ask, has led to Google being able to publish the series of verified empirical demonstrations that it has? We’ve seen a number of exciting firsts — the first demonstration of a beyond-classical computation of any kind on a quantum computer in 2019, the most impressive chemistry simulation on a quantum computer earlier in 2021, and most recently the first demonstration that errors can be exponentially suppressed with the number qubits. What about Google’s team or particular approach allows for this pace of breakthroughs?
Qubit inspecting a dilution refrigerator for proper signal routing
Maybe that confidence is warranted. Of course, even if the technical path is reasonable, there are a lot of open questions about the eventual applications of quantum computing. Google’s group includes “AI” in its name — Google Quantum AI — so I assume you think quantum computing could eventually lead to more effective forms of machine learning? Or are you more excited about applications such as simulating chemical reactions and exotic materials, so we might develop better batteries and solar panels, or achieve efficient nitrogen fixation for farming fertilizer and save 2% of the world’s carbon emissions?
And do you subscribe to the “many worlds” hypothesis, and the notion that quantum computers’ power will come from essentially processing information in other parallel universes, or is this perhaps too far-fetched and unnecessary for understanding where the double exponential speedup, that is, “Neven’s Law,” comes from? Is a more conventional understanding all we need to grasp the implications of this new regime of compute space?
Thank you so much. One last question, and then I’ll let you go — what’s the deal with time crystals?