by Brendan Barry, CTO

Our quantum science team has just published a paper on a practical way to measure entanglement on near-term quantum hardware. That's an important research result. But it isn't the only reason I'm excited about it.

It reinforces something we've believed for a long time at Equal1.

The future of quantum computing isn't a standalone quantum processor sitting somewhere else. It's quantum and classical computing working together.

Our new algorithm is a perfect example. 

First, the problem. Entanglement is the resource that makes quantum computation quantum. If your processor isn't producing it, you're running an expensive classical machine. But measuring it has always been hard. The standard approach needs exponentially more measurements as qubit counts grow. It stops being practical almost immediately.

Andrii Semenov, Niall Murphy and Elena Blokhina, with collaborators at the University of Trento, took a different route. Rather than performing one large quantum computation and returning an answer, their algorithm creates a loop. The quantum processor prepares and measures a state. Classical software analyses the result. That information immediately decides what the quantum processor should do next. The process repeats until it converges.

It works. One extra qubit. In simulations, it converged in just a handful of iterations, compared with hundreds for comparable variational approaches.

What strikes me isn't just the algorithm. It is what the algorithm assumes about the future of quantum computing. Every iteration moves backwards and forwards between quantum and classical processing. This approach is not new; however, it is very practical for current devices. 

And a tight loop between quantum and classical processing becomes increasingly practical when the two sit close together, on shared infrastructure, exchanging results continuously. That is a statement about where quantum computers need to live.

It's also why we build the way we do. UnityQ's quantum cores integrate qubits, control, measurement and error correction in one self-contained block, with ARM processors powering classical compute on the same chip. Quantum and classical aren't two different technologies bolted together. For us, they're the same silicon.

This is why we talk about deployability so much. Deployability isn't just about easier installation or fitting into a rack. It's about allowing quantum processors to become another part of the HPC environment. Sharing infrastructure. Sharing orchestration. Sharing workflows. Running alongside CPUs and GPUs rather than somewhere else.

Algorithms like this one are built for that world. That's how we think quantum becomes practical. And deployable.

Quantum implementation of higher-order power method for estimating geometric entanglement of pure states  

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