What was shown
The authors calculated what a quantum memory would cost to build if it must be reliable. Think of a warehouse with a vast number of shelves. One clerk walks the aisles and fetches an item slowly; to fetch it quickly you need a clerk at every shelf. The paper does this sum for a memory of 8GB that is roughly half full. Fast lookups, on the order of milliseconds, need on the order of 10¹⁵ physical qubits, the actual hardware units, in the fully parallel version. A million physical qubits in the basic version means lookups of on the order of 3 years. This is a calculation on paper, not a run on any machine.
“Under our (currently optimistic) assumptions and using current fault-tolerant quantum error correction, an 8GB qRAM that is roughly half-full uses quadrillions of qubits to obtain fast query times on the order of milliseconds; alternatively, working with only millions of physical qubits would yield query times on the order of years.”
— VIII Conclusion, in: Fault tolerant resource estimation of quantum random-access memories1
- How it was done: a calculation on paper, not run on any machine
- Qubits: On the order of 10¹⁵ physical qubits in the fully parallel version, or a million in the basic version, for the 8GB case.
- Error correction: The whole circuit is assumed to run inside an error-correcting scheme that keeps the computation reliable despite faulty hardware.
- Compared against classical computing: no comparison stated in the paper
Who it affects
Companies that plan around quantum algorithms which need to read large amounts of data quickly. Nothing changes for them today, except one point: a cheap quantum memory should not be assumed in any plan. The result concerns generic, unstructured data; small memories and data with special structure stay open.
Quantum computing vendors and their customers: McKinsey & Company estimates $43B to $71B by 2035 — quantum computing market size (vendor side) (Quantum Technology Monitor, April 2026, p. 8).
This figure is an estimate, not a measurement: McKinsey & Company is a consultancy with its own quantum advisory business. It covers a whole use case, not the result of this paper.
What is still missing
The paper's own estimate calls a circuit-based memory of this size infeasible. Fast queries need quadrillions of qubits, on the order of 10¹⁵ physical qubits, and the assumptions behind that figure are called currently optimistic. A machine with a million physical qubits would need on the order of 3 years per query. Algorithms that assume an efficient memory therefore lack that component, unless the data has special structure that allows much cheaper circuits.
Against published roadmaps: the task needs 1000 trillion physical qubits. No announcement we have on file reaches that many physical qubits. The furthest any of them goes:
An announcement is not a delivered machine, and this one would still fall short of what the task needs.
Who is working on it
The paper (February 2019) lists its authors' affiliations as: TRIUMF, Vancouver, BC, V6T 2A3, Canada; Department of Physics & Astronomy, University of Waterloo, Waterloo, ON, N2L 3G1, Canada; Institute for Quantum Computing, University of Waterloo, Waterloo, ON, N2L 3G1, Canada; Department of Combinatorics & Optimization, University of Waterloo, Waterloo, ON, N2L 3G1, Canada; and 2 further institutions. That is who signed this work — it is not a ranking of who is ahead.
It weakens the case for building quantum memory from fault-tolerant circuits for generic, unstructured data, and with it algorithms that assume efficient queries. Small memories and specially structured data remain open.
How this brief was made
This brief was written by software, not by a person: a language model read the full text of the paper, and code then checked every quotation, number and name in this brief against that text before it was published. The rules are set out under Method. Responsible for the rules and for this page: Georg Singer. The paper is a preprint that has not been peer-reviewed. Georg Singer holds no shares in any company or institution named in this brief (as of October 2026).
Sources
- arxiv.org Fault tolerant resource estimation of quantum random-access memories
- ionq.com IonQ