Google Including Neutral Atom Qubit Approach
BigTech is charting their Quantum computing future more clearly in 2026. Many roadmaps point to 2030 as key year. However this full-stack dual qubit modality approach is promising.
It’s March, 2026 and Google Quantum’s roadmap is getting a lot more tangible. Google Quantum AI is broadening its quantum computing roadmap by introducing a neutral atom quantum computing programme alongside its established superconducting qubit research. This is of course validation for Neutral Atom approach to qubit development.
As you know in a nutshell, The Neutral Atom approach is a method of quantum computing that uses uncharged atoms—typically alkali metals like Rubidium or Cesium—as qubits. These atoms are suspended in a vacuum and manipulated using highly focused laser beams.
The elegance of this approach is that neutral atoms are not held by magnetic or electric fields, but rather by the "pressure" of light.
Which sounds almost poetic to me.
While Google’s Quantum unit is I think guilty of a lot of PR down the years, this is an interesting development signals to me that BigTech is taking Quantum computing and its future more seriously.
When Google Quantum acquired Atlantic Quantum back in October, 2025 I was a bit surprised.
Additionally Google’s introducing a 2029 timeline to secure the quantum era with post-quantum cryptography (PQC) migration. Read their official blog on this too. Google Quantum appears to see superconducting technology as the main path forward with Neutral Atom Qubit approach as more “complementary”.
Why add neutral atoms now?
Google is pursuing a dual-modality strategy because the two approaches have complementary strengths that address different scaling challenges, for instance:
Superconducting qubits (Google’s core platform):
Excel in the “time dimension” — fast gate/measurement cycles (~1 microsecond).
Have demonstrated millions of gate/measurement cycles in deep circuits.
Next challenge: scaling architectures to tens of thousands of qubits.
Neutral atom qubits (new addition):
Excel in the “space dimension” — already scaled to arrays of ~10,000 qubits.
Offer flexible any-to-any connectivity (no fixed wiring constraints), which enables more efficient algorithms and low-overhead error-correcting codes.
Trade-off: slower cycle times (~milliseconds).
Next challenge: demonstrating deep circuits with many sequential operations.
Quantum companies, startups and labs are notorious in making ambitious road-maps that don’t always turn into tangible Quantum breakthroughs and developments overall have been slow and shifting.
Quantum appears to be a bit of a sideshow as many BigTech companies including Nvidia, Amazon, Microsoft and Google. From their blog it’s clear that Google plans to develop the neutral atom platform through advances in error correction, simulation and hardware, while continuing its superconducting roadmap toward commercial systems by the end of the decade.
With Infleqtion going public, INFQ 0.00%↑, and Google giving the Neutral Atom approach a bit more mainstream credibility it’s fascinating to watch.
The Big Three in Neutral Atom Approach
QuEra
Pasqual
Infleqtion
It’s safe to say that these are the big three, more or less in the right order. Important to note that Pasqual is indeed also rushing to go public via a SPAC. The company will combine with Bleichroeder Acquisition Corp. II, a vehicle set up by Michel Combes and Andrew Gundlach, at a $2 billion pre-money valuation. While getting about $200 million in the process. I don’t believe I’ve covered the French team before - Cofounded in 2019 by Nobel prize winner Alain Aspect, Pascal builds and operates neutral-atom quantum processors. It has more than 275 employees and raised over $200 million from investors.
QuEra on the other hand, appears to have a pretty high ceiling with some very solid research. Based in Boston, QuEra is widely considered the technical leader in "analog" quantum simulation, though they are pivotally moving toward fault-tolerant digital systems.
Google Quantum’s dual approach to building a full-stack approach to scaling Qubits could be more important than it seems.
