Quantum computing’s future depends on more than scientific milestones. Erik Hosler, a photonic systems expert with experience bridging quantum development and semiconductor manufacturing, is part of a growing movement focused on how these machines will actually be built.
The techniques that enabled classical computing at scale are beginning to shape quantum hardware. Precision patterning, yield optimization, and materials control are no longer optional. They are prerequisites. Progress in the lab must now align with the demands of fabrication, where consistency and manufacturability define what comes next.
Scaling: The Problem That Doesn’t Care About Physics
Quantum computing promises immense computational power, but only if it can scale. Laboratory success with a few dozen qubits doesn’t translate into functional hardware at industrial levels. To solve problems that classical computers can’t, quantum systems need hundreds or thousands of logical qubits, which, due to error correction overhead, means millions of physical qubits.
Building machines of that complexity requires more than scientific insight. It requires a manufacturing ecosystem. It’s here that quantum developers face a familiar challenge: how to turn one working device into one million working devices, all with predictable behavior.
It is precisely what the semiconductor industry has been solving for the last 60 years.
A Proven Model: From Transistor to Industry Standard
The trajectory of classical computing followed a curve defined by Moore’s Law: the doubling of transistor density every couple of years. That trend wasn’t about shrinking transistors; it was about standardizing production, minimizing cost per function, and improving yield.
These same forces will define whether quantum computing becomes useful or remains experimental. The industry already has the playbook:
- Photolithography for repeatable nanometer-scale features
- Cleanroom manufacturing with ultra-low defect rates
- Automated testing and binning at wafer scale
- Layered process integration using well-defined nodes
Translating this to quantum systems is no small feat. But starting from that template rather than inventing a new one offers a serious head start.
Quantum Hardware Isn’t Immune to Fabrication Realities
Unlike software-based technologies, quantum computing is hardware-intensive. Qubits are physical entities, circuits, traps, or photons that must be produced with geometric precision and environmental isolation. Any variability introduces error, and when error rates rise, computation collapses.
It means the success of a quantum chip depends not just on its theoretical design but on the following:
- Patterning consistency across multiple layers
- Overlay precision to align optical or electrical paths
- Material purity to limit scattering and decoherence
- Etch uniformity to maintain performance across the wafer
These are the same metrics that determine yield in semiconductor fabs, which is why the semiconductor legacy matters so much to Quantum’s future.
Reframing the Innovation Pipeline
There’s a myth in deep tech that true innovation must reject what came before. But in the case of quantum computing, leveraging semiconductor infrastructure doesn’t dilute innovation; it amplifies it.
Consider:
- Quantum photonics leverages CMOS-compatible silicon waveguides
- Superconducting circuits benefit from advanced deposition and etch tools
- Quantum control electronics run on conventional integrated chips
- Packaging and interconnects are built with foundry-grade materials
Each of these layers is rooted in semiconductor tradition, yet their integration enables quantum computation. Erik Hosler observes, “The semiconductor industry and its technology are essential to building a useful quantum computer.” It isn’t just a technical preference; it’s a strategic necessity.
Without the chip industry’s infrastructure, tooling, and supply chain maturity, quantum devices cannot meet the thresholds for reliability, cost, or scale.
Lithography as the Bridge
Among all semiconductor tools, lithography may be the most critical to quantum development. Whether building superconducting loops or photonic waveguides, patterning precision determines a qubit’s functionality. For example:
- Misaligned waveguides degrade optical coherence
- Inconsistent trench depths introduce errors in signal paths
- Nanometer-level placement errors affect the efficiency of entanglement
Advanced EUV and DUV systems developed for sub-10nm nodes now serve an unexpected role: enabling quantum architectures that require tight tolerances but larger features, such as those in photonic systems.
In this way, the development of chip lithography has become a foundational tool in quantum hardware development.
Yield, Packaging, and Practicality
Beyond wafer processing, the semiconductor industry’s greatest strength may be repeatable yield and system-level integration. Making one good chip is an achievement, but making one hundred thousand good chips per month is an industry.
Quantum platforms need the same reliability. They must be packaged, evaluated, and cooled without failure. Systems must survive transport, startup, and operation over months or years, not just days in a lab.
Semiconductor packaging technologies, such as flip-chip bonding, 3D stacking, and wafer-scale integration, offer tested paths to these goals. Quantum computing can inherit not only techniques but also quality control frameworks, thermal solutions, and assembly automation.
Moore’s Law, Reimagined
Moore’s Law, as originally conceived, was about shrinking transistors. But its spirit, steady improvement through integration and scale, applies to quantum computing as well. Quantum systems will double in capability by improving:
- Error correction efficiency
- Qubit coherence and fidelity
- Integration density via chiplet or photonic modules
- System reliability and yield per wafer
That is how quantum enters its Moore-like trajectory: through measurable, manufacturable progress, not theoretical leaps.
A Partnership, not a Fork
The idea that quantum must “replace” classical computing is flawed. The better framing is symbiosis. Just as GPUs didn’t kill CPUs but instead unlocked new workloads, quantum processors will augment classical systems, especially in areas like:
- Cryptography
- Molecular modeling
- Logistics and optimization
- High-dimensional statistical inference
But for that to happen, they must be built like chips, not like lab experiments. They must inherit the culture of manufacturing excellence from their classical predecessors.
A Future Forged in Silicon
Although quantum computing’s success may be driven by physics, it will be built on silicon. The machines of the future will owe as much to the fabs of the past as they do to quantum theory.
By grounding their development in the tools, standards, and strategies honed by the semiconductor industry, quantum engineers can scale innovation without reinventing the wheel. That legacy doesn’t slow progress; it accelerates it.
The next computing progress won’t erase the last one. It will stand on its shoulders, one pattern-aligned wafer at a time.
