QUANTUM RESERVOIR COMPUTING
Last week, I had a drink with my tribe on a rooftop bar in Shoreditch, and – as is typical of me – the conversation drifted from gossip to Quantum Lake Reservoirs. And that reminded me of something that happened a couple of years ago, long before quantum became the investor catnip it is today.
A long-time friend of mine (brilliant, eccentric and decades ahead of the curve) with two PhDs in Physics asked me to take a drive with him to the seaside. Not for a romantic walk, not for oysters, but to collect seawater. Litres of it. Enough to fill his children’s enormous plastic paddling pool. He was exploring what was then a nascent idea in quantum physics: reservoir computing. More specifically, he was trying to build a classical analogue of what we now call Quantum Reservoir Computing (QRC).
And here’s the part investors need to understand.
He filled the paddling pool with seawater. We threw tiny pebbles into it. He placed sensors around the pool to measure the ripples: their interference, their decay, their overlapping patterns.
That paddling pool was a reservoir. The pebbles were inputs. The ripples were high‑dimensional transformations of those inputs. The sensors were the readout layer.
This is exactly how QRC works – just in the classical world.
In the quantum world, the “lake” is not seawater but a quantum system: a cluster of qubits, a photonic interferometer, a neutral‑atom array, a set of coupled oscillators. Instead of water ripples, you get:
- entanglement spreading
- interference patterns
- operator scrambling
- chaotic Hamiltonian evolution
- quantum memory effects
And instead of sensors, you have measurements – photon counts, qubit populations, quadrature readings — feeding into a simple classical model.
The key point, and the part investors routinely miss, is this:
You never train the reservoir. You only train the readout.
This is why QRC is so powerful. It sidesteps the entire problem of training quantum neural networks, avoids barren plateaus, and uses the physics you already have (the messy, rich, high‑dimensional behaviour of real quantum systems) as computational fuel.
But because it isn’t wrapped in glossy marketing or photonics buzzwords, almost no one in the investment community has heard of it. They chase the shiny qubit, the glossy photonic chip, the “quantum AI” press release, without realising that modalities like QRC may deliver near‑term machine‑learning capability on noisy hardware.
My friend’s paddling‑pool experiment was not a joke. It was a prototype of a computational paradigm investors are sleepwalking past.
And if you’re serious about quantum (not the hype, but the physics) you need to understand modalities beyond the usual suspects. QRC is one of them.
And here is a short pdf on the potential applications in Fund Management, my former role.https://jacq.io/wp-content/uploads/2026/08/Quantum-Reservoir-Computing-in-Fund-Management.pdf
