As the quantum computing industry inches toward delivering something incredibly useful, a new kind of tension is emerging, one that’s not just about science but sustainability. Erik Hosler, a quantum systems strategist grounded in both physics and manufacturing insight, acknowledges that the goal is to create a quantum computer that not only functions reliably but can also be produced and operated within practical economic limits.
From the outside, it’s easy to focus on the marvels of quantum mechanics, superposition, entanglement, and exponential processing potential. But behind the breakthroughs lies a harder truth: engineering cost and complexity could stall progress. Building a system powerful enough to outpace classical computers is one thing. Doing so without bankrupting the fabrication or the funding model is another altogether.
Beyond Proof-of-Concept: The Scalability Pressure
Quantum prototypes have demonstrated some remarkable feats. They’ve simulated molecules, solved optimization problems, and outperformed classical counterparts in tightly scoped scenarios. But these systems, often composed of a few dozen qubits, remain fragile, noisy, and limited in scope. They’re proof that quantum principles can be harnessed, not that they can be scaled.
Scaling is where things get expensive. And in quantum computing, costs balloon quickly. Precision cryogenics, vacuum systems, control electronics, and qubit calibration routines all stack up, especially when replicated across hundreds or thousands of units. It’s common for a state-of-the-art system to cost tens of millions of dollars per prototype.
Without a clear path to mass manufacturability and economic viability, these systems risk becoming scientific trophies rather than transformative tools.
The Fabrication Bottleneck
One of the most underestimated challenges in quantum computing is fabrication. Creating functional qubits, whether they’re based on superconducting loops, trapped ions, or photons, demands extremely tight tolerances.
A few nanometers of misalignment, a trace of contamination, or a slight defect in a waveguide can mean the difference between a working qubit and a useless one. Now multiply that challenge by a million. That’s the scale needed to reach fault-tolerant computing, quantum systems that can run complex algorithms with meaningful impact.
That is where the analogy of “breaking the bank” becomes reality. If quantum hardware cannot be produced within the capabilities and cost structures of modern semiconductor facilities, it will remain confined to academic labs.
A Delicate Cost Equation
Quantum computing isn’t a matter of “just build it, and they will come.” The value proposition must make economic sense. The system must generate computations so valuable that they outweigh the cost to build, maintain, and scale the machine.
It was a crucial point made by PsiQuantum, a company pursuing photonic quantum computing on an industrial scale. Their roadmap leans heavily on reusing existing semiconductor manufacturing capabilities to avoid expensive, bespoke infrastructure. The company aims to align quantum hardware development with the cost curve of modern chip production, not to fight against it.
In this context, Erik Hosler emphasizes, “We need to build a quantum computer that doesn’t break the fab and doesn’t break the bank.” It’s a clear distillation of the trade-offs: performance is only meaningful if it comes with practical feasibility. A system that offers incredible computation but costs half a billion dollars per unit has limited real-world utility.
Building Within Infrastructure, Not Outside It
What’s emerging across the quantum landscape is a realization that success will not come solely from qubit count or gate fidelity. It will come from compatibility with infrastructure. It includes:
- Fabrication tools are already used in semiconductor fabs.
- Process controls with inline metrology and statistical stability.
- Testing and packaging standards that can be reused or adapted.
- Supply chains that offer materials on a global scale
Trying to build a quantum computer outside of these systems creates friction at every stage, higher costs, longer development cycles, and unpredictable quality.
By contrast, photonic systems like those pursued by PsiQuantum aim to operate within existing lithographic and etching platforms. Their qubits are optical rather than matter-based, and their circuits can be patterned using CMOS-compatible methods. This alignment doesn’t eliminate complexity, but it makes it manageable.
Avoiding Exotic Traps
Some quantum architectures are promising on paper but require entirely novel equipment to realize. Trapped ions, for instance, offer long coherence times and high gate fidelity. But the traps themselves are intricate, the vacuum systems delicate, and the scalability path uncertain.
Building hardware around exotic conditions adds layers of cost, not just in money but in time and supply chain complexity. That makes it harder to move from demonstration to deployment.
It isn’t to say that such approaches are doomed. But they face a steeper climb when it comes to integrating with industry-grade manufacturing.
The Economics of Modularity
Another way to manage cost and complexity is modularity. Rather than building a massive, monolithic machine, many quantum companies are pursuing architectures composed of repeatable, interlinked modules. Each module can be built, evaluated, and perfected independently, then scaled out as demand grows.
This strategy is already well understood in classical supercomputing. It offers flexibility and allows system costs to grow in proportion to its capabilities. For quantum, it means being able to roll out partial capacity while still targeting the million-qubit horizon.
More importantly, modularity supports yield resilience. If a single module has a defect or slightly reduced performance, it can be replaced or rerouted without scrapping the entire system. That kind of economic elasticity is essential when dealing with complex, high-precision technology.
Quantum ROI: The Coming Conversation
The coming wave of quantum computing won’t be judged purely by scientific merit. Investors, governments, and enterprise buyers will all want to understand the return on investment. That doesn’t mean short-term profit, but it does mean answering questions like:
- How much does this system cost per logical qubit?
- What kinds of problems can it solve that classical systems cannot?
- What’s the total cost of ownership, including cooling, operation, and maintenance?
- Can it be deployed in a way that supports iterative upgrades?
These are not abstract questions. They are the next set of gatekeepers for quantum entry into the real world.
Quantum’s Real Threshold
Quantum computing’s biggest test may not be entanglement or coherence. It may be manufacturing and cost control. Without scalable fabrication and sustainable economics, even the most powerful systems risk becoming impractical.
The long-term winners in quantum will be the ones who can engineer both performance and feasibility. Avoiding both “breaking the bank” and “breaking the bank” is not a luxury. It’s the foundation for meaningful impact.
Quantum technology will succeed not when it dazzles but when it delivers on a scale, on budget, and within reach of the industries it’s meant to serve.