Mobility · aerospace

A dated roadmap for aerodynamic flow simulation

A flow-transport solver mapped to the logical-qubit scale at which we will test it against the classical solver, running today across seven hardware platforms. No advantage on present hardware is claimed.

Headline result

~93 logical qubits (projected)

A measured cost law projected to about 93 logical qubits; a projection, not a measurement

Projection
Still from the Merlin Quantum film: an operations room
01 · The decision

The decision on the table

Flow simulation is one of the largest compute bills in aerospace and automotive design. Buyers need to know when quantum could matter for it, not a promise that it already does.

02 · What we did

What we did, with proprietary methods

We built a solver for the linear transport step of a flow simulation, measured how its cost grows, and placed the problem sizes and logical-qubit counts at which it is worth testing against the classical solver. The same methods run on superconducting, neutral-atom, trapped-ion and photonic machines.

03 · What it was worth

What it was worth

A measured cost law projected to about 93 logical qubits; a projection, not a measurement

Key result · Mobility · aerospace
Know when to plan for it
Baseline
Open-ended vendor timelines
Condition
A measured cost law projected to about 93 logical qubits; a projection, not a measurement
No lock-in to one machine
Baseline
A solver tied to one vendor
Condition
The same methods run on seven platforms across four hardware families
Outcome

What happened next

The roadmap now has a planning point in hardware terms, about 93 logical qubits, projected from a measured cost law. Meanwhile the same methods already run on seven platforms across four hardware families.

Decision it enabled

Know when to plan for it

Instead of: Open-ended vendor timelines

Verified by · Projection from a cost law we measured; platform reach is a device result.

05 · How we know

How we know

  1. 01Cost growth measured on the transport step; the crossing scale (about 93 logical qubits at 65,536 points per axis) is a forward projection from that measured law.
  2. 02Runs on seven platforms: superconducting, neutral-atom, trapped-ion and photonic.
  3. 03Not claimed: an advantage on present hardware or on standard benchmark flows.
StatusProjectionA projection from a measured cost law. Platform reach is measured on hardware.

Decide before you build.

Bring us the decision you have to make next.

We tell you which option wins, and whether quantum is the reason.

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