Image credit: Dr. Lorenzo Peri.
By Dr. Karen Steward
The biggest obstacle to building practical quantum computers may not be the qubits themselves but the vast tangle of electronics needed to control them. That was the key message from Dr. Lorenzo Peri of Quantum Motion Technologies, who delivered the latest QAMSS lecture, arguing that the future of quantum computing depends on bringing quantum physics and classical engineering much closer together.
Quantum classical integration is the next challenge
In his lecture, Modelling Spin-Qubit in Silicon: From First-Principles Simulations to Quantum-Classical EDA Integration, Dr. Peri explored how advanced simulation techniques are helping researchers design scalable silicon spin qubits while tackling one of the field's greatest engineering challenges.
Rather than focusing solely on improving individual qubits, Dr. Peri said the industry's attention must shift to the systems that connect them.
"While improving qubit coherence and gate fidelity is obviously critical, I believe the most formidable bottleneck to scalable quantum computing isn't the qubit itself, it is the quantum-classical interface," he explained in an interview.
He pointed to the familiar images of dilution refrigerators connected to dense bundles of coaxial cables leading to racks of room-temperature electronics.
"It is difficult to see how increasing the qubit count by orders of magnitude can be accompanied by an increase in coax cables and room-temperature electronics by the same amount," he said.
Drawing a parallel with the history of classical computing, Dr. Peri compared today's challenge to the "tyranny of numbers" identified by Bell Labs' Jack Morton in 1958, arguing that quantum technologies now require tighter integration between qubits, control electronics and cryogenic systems. He added that this will rely on close collaboration between quantum physicists, electrical engineers and cryogenic specialists.
Learning from the classical computing revolution
Dr. Peri went on to discuss how decades of experience in classical chip design can accelerate quantum hardware development.
"The most valuable lesson classical computing offers quantum technologies is how they managed to overcome their own 'tyranny of numbers'," he said.
He explained that the revolution in classical electronics was driven not only by smaller transistors but by electronic design automation (EDA), which introduced "opaque layers of abstraction" that allowed engineers to design increasingly complex systems without needing to understand every aspect of semiconductor physics.
"In quantum computing, and specifically in my work with silicon spin qubits, we are standing at our own very-large-scale integration (VLSI) inflection point," he said. "This means building the tools to allow quantum computer designers to start treating qubits as an engineering component rather than a delicate physical system."
During the lecture, Dr. Peri presented a comprehensive simulation pipeline combining process emulation, electrostatic modelling and quantum simulations to connect physical device design directly to quantum processor performance. He also demonstrated a Verilog-A-based framework that enables quantum devices and classical circuits to be co-simulated using established analogue design software.
"This is why we set off to build a comprehensive simulation pipeline, envisioning a quantum technology computer-aided design (TCAD) workflow that goes from device simulations to compact modelling," he said. "By bridging quantum mechanics with standard EDA tools, we empower quantum physicists and integrated circuit (IC) designers to work together, leveraging decades of classical engineering advancements to build the hybrid quantum hardware of the future."
About the interviewee
Dr. Lorenzo Peri, Quantum Motion, UK. Image credit: Timothy Lambden.
Lorenzo Peri earned his PhD at the University of Cambridge researching the electrical behaviour of quantum systems, particularly of spin qubits in silicon quantum dot devices. He is now a senior modelling engineer at Quantum Motion, where his work focuses on modelling quantum effects in silicon devices to enhance design and simulation capabilities for hybrid microwave circuits and quantum information processing applications. He has published his research in several scientific journals on novel quantum modelling techniques and the integration of quantum effects in classical compact models.