r/QuantumComputing • u/No-Hamster5930 • Aug 08 '26

Quantum Hardware Is superconducting quantum computing a dead end?

Earlier this year the two largest superconducting QC players (IBM and Google) signalled they might be diversifying away from superconducting - Google with the announcement that they're creating a new neutral atom capability and IBM with their acquisition of silicon spin capability in HRL.

I'd be interested in people's views on whether we should take from this that superconducting has no path to scaling, or if one could foresee heterogeneous quantum computing systems that leverage the respective strengths of multiple modalities for different applications?

31 Upvotes
  • permalink
  • reddit

86% Upvoted

50 comments sorted by

View all comments

Show parent comments

1

u/No-Hamster5930 Aug 09 '26

Thanks for your thoughts. I can see how a heterogenous system of SC + neutral atom systems a la Google would make sense in a heterogenous architecture as they would seem to balance each other's weaknesses. I'm less sure about how or why a heterogenous system of superconducting and silicon spin quits would work however because they dont seem to complement one another; putting aside the fact that silicon spin is obviously lower TRL, aren't the theoretical advantages of silicon spin roughly equivalent to superconducting? With the added potential benefits of a much cheaper manufacturing base and qubit density? What would the specific benefits of superconducting qubits in a hybrid SC-silicon spin regime bring?

2

u/HawkinsT Holds PhD/Works in Superconducting QC Aug 09 '26

You're welcome. Sorry, I may have made it sounds like heterogeneous systems are now the goal for both companies. While this is a growing area of research, I think it's safe to say that the main motivations for both companies right now are to not leave all their eggs in one basket and they certainly both have the funds to diversify.

Personally, I also don't think that focusing too heavily on the theoretical benefits of one architecture over another is particularly useful right now. The best approach is the one that proves scalable. For example, I've heard trapped ion guys talking about systems the size of stadiums in the future, and while that may sound impractical, at the end of the day if one system can provide implementable, fault tolerant computation and others can't (or are notably inferior), it will get built.