Fault-tolerant quantum computers are within reach, but getting from today’s noisy, KiloQuOp devices to tomorrow’s MegaQuOp and TeraQuOp machines demands a new way to measure progress and a new way to build. Instead of chasing “perfect” qubits in isolation, we should start building the MVP (minimum viable product) of fault-tolerant quantum computers now. These “first FTQC's” will help us test ideas, learn and scale faster.
Riverlane was founded on the conviction that fault-tolerant quantum computers are achievable within our lifetime, a belief not universally shared by experts when I founded the business in 2016.
Almost a decade later, while significant progress has been made and with the industry now universally aligned behind the need for QEC, the journey ahead is long.
This journey requires a rethink on how we compare quantum computers, with a recent shift away from the simplistic counting of qubit numbers and/or fidelities. Instead, a metric that captures both physical qubit quantity and quality is increasingly used: error-free quantum operations, or 'QuOps.'
Today's best quantum computers can reliably execute thousands of QuOps (aka KiloQuOps) before the calculation is overcome by errors and, therefore, is useless.
The vision is to develop 'MegaQuOp' machines – systems 1,000 times larger than today – capable of performing the first wave of useful, beyond-classical operations before the end of the decade.
The ultimate prize, however, lies in 'TeraQuOp' machines: trillion-operation systems that represent a million-fold increase in scale over the MegaQuOp, poised to unlock the promise of quantum computing. While daunting, this moonshot is achievable.
Achieving such ambitious goals requires a meticulously planned, step-by-step approach. The critical challenge lies in identifying the precise next steps from our current position and the subsequent phases, a task that demands a clear understanding of the fundamental problems we aim to solve.
The NISQ (Noisy Intermediate-Scale Quantum) era demonstrated the limitations of scaling without error correction. We are now entering the QEC era, and the crucial question is: how do we now scale effectively?
My perspective diverges from the conventional wisdom of only increasing physical qubit qualities and quantities to create ‘perfect’ logical qubits.
Instead, I advocate for building 'the first FTQCs' today as the essential next step. These are small-scale systems that probe how full-scale FTQCs would run. This is a seemingly subtle difference in strategy. After all, these first FTQCs won’t be able to do much of anything that’s useful. However, this change of focus is profoundly significant, as it establishes the correct foundation for subsequent, larger-scale advancements.
In other words, to succeed in the new QEC era, we don’t just need better physical qubits or bigger logical ones; we also need an immediate, integrated strategy to enable error-corrected operations and unlock the shortest path to true fault tolerance.
The myth of perfect qubits
The pursuit of utility-scale quantum computing hinges on a fundamental truth: reliable qubits are paramount. The industry broadly agrees that a physical qubit fidelity of 99.9% or even 99.99% – equating to just one error in a thousand or ten thousand operations – is the benchmark.
These seemingly small improvements between 99.9% and 99.99%, often referred to as “the three nines” and “the four nines,” are profoundly meaningful. Higher fidelity directly translates into a smaller, less resource-intensive error-correction task.
But as quantum computers scale past 1,000 physical qubits, an alternative direction deserves exploration: rather than creating one high-quality logical qubit with as many as 1,000 physical qubits, companies could start developing several mid-quality logical qubits and then run small algorithms on their small KiloQuOp machines.
Why this change? Because building these first FTQCs unlocks an iterative process: first building them at a small scale, rigorously testing them, learning from the results, and then progressively scaling up to larger systems. Then repeat.
Importantly, this approach would require quantum computer companies to take a holistic systems perspective, building a miniature version of an FTQC and scaling up every layer of the quantum stack incrementally. This makes more sense than focusing solely on the qubit layer, important as it is.
Let me use an analogy to explain this concept. In the 1900s, when aviation was just taking off, the Wright brothers weren’t trying to design the perfect aircraft wing, imagining this would then help them build an entire plane. They built a plane. It may have only flown for 12 seconds from the top of a sand dune in Kitty Hawk. Perfection wasn’t the point. Building the first proof-of-concept plane ensured that critical aviation challenges were addressed as early as possible in the design process. Subsequent aircraft designs scaled incrementally and fast. A decade later, the first commercial flight took off.
By building the first FTQCs now, we can work out how to get quantum computers off the ground too, so they can scale to utility faster.
The first FTQCs, while not delivering quantum advantage in the same way as larger, more advanced quantum computers will, offer valuable opportunities for learning, development, and testing of crucial components. This will lay the foundation for scaling up to larger, more powerful fault-tolerant quantum systems.
As with the first ‘Wright Flyer 1’ plane, the first such breakthrough kick starts the innovation race for an entire technology class.
This philosophy forms the bedrock of Riverlane's mission. Our Deltaflow system empowers organisations to learn and test fault-tolerant operations in real-time on real quantum hardware. While some quantum companies endeavour to develop their entire QEC stack and indeed every other layer of the full quantum computing stack internally, we believe that many will increasingly embrace a modular approach, collaborating with specialists to assemble the best overall machine.
As Nobel Laureate John Martinis aptly put it in the Quantum Error Correction Report 2025, ‘you can't be the world expert in every component.’ This modularity allows hardware providers to focus on their core expertise while leveraging specialised QEC systems.
This strategic focus on building the first FTQCs and efficient, real-time error correction now is fundamentally about achieving stable, high-fidelity logical qubits in the future. By doing so, we are paving the way for scalable quantum computation.
Building and operating the first FTQC is not about immediate quantum advantage for complex problems, but about proving that hardware, coupled with real-time QEC, can move from simply having qubits to having qubits capable of scaling to fault tolerance.
Riverlane's Deltaflow system is designed to seamlessly integrate hardware, software, and algorithms for real-time, fault-tolerant operations. It is already deployed on systems from Infleqtion, Oxford Quantum Circuits, Oak Ridge National Laboratory, and Rigetti Computing, to name a few, demonstrating its ability to scale across multiple qubit types and integrate with various quantum hardware. This capability positions Deltaflow as a critical tool for companies serious about embarking on their journey to utility-scale quantum computing.
Whether or not a quantum computing company chooses to work with Riverlane, another partner, or their own technology for quantum error correction, my refrain remains the same: now is the time to start building the first fault-tolerant quantum computers. This necessarily means a broader focus than just building ever bigger logical qubits.
The quantum learning curve is steep, and the field is moving at an unprecedented pace. By building the first FTQCs today, the industry can shoot for the moon by 2030, launching us into a new era of design with limitless possibilities.
Read more about the first FTQCs in our exclusive whitepaper, available here.