Spin Qubits, Semiconductors, and the Million-Qubit Race: Brandon Severin
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概要
Quantum computing's quiet advantage might not come from exotic physics. It might come from the silicon chip industry we already have. On this episode of Thinking on Paper, we talk with Brandon Severin, founder of Conductor Quantum, about why spin qubits could be the modality that finally rides semiconductor manufacturing all the way to a million qubits.
Severin walks us through what a spin qubit actually is, a single electron isolated in silicon with its spin pointing up or down as the fundamental quantum bit, and how the trillion-dollar semiconductor industry that perfected the transistor over fifty years gives spin qubits a manufacturing path no other modality can match.
Along the way: how Google's new quantum NMR algorithm hints at where verifiable quantum advantage is heading, why the "more qubits versus better qubits" debate misses the point, how spin qubits compare with trapped ions and superconducting approaches, the brutal calibration problem of tuning twenty parameters per qubit by hand, and why building for a million qubits from day one is a fundamentally different mindset than adding them one at a time.
Have fun with this one. We did.
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Brandon Severin: https://www.conductorquantum.com/
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Timestamps
(00:00) Introduction: spin qubits and the quantum scaling problem
(03:47) Trapped ions vs spin qubits: fidelity, coherence, and tradeoffs
(06:14) What qubit fidelity means and why it determines scaling limits
(08:25) What is a spin qubit? Building from the transistor up
(11:06) Semiconductor fabrication as quantum computing's manufacturing advantage
(15:00) The quantum circus: superposition, measurement, Schrödinger's cat
(17:17) Shuttling qubits — moving electrons across a chip
(20:33) How AI automates quantum calibration (the control problem)
(25:00) Quantum scaling vs AI scaling: the GPU parallel
(29:08) Quantum startup culture and the AI generation gap
(32:59) Building for a million qubits — rocket ships vs ladders
(36:52) Why quantum is taking so long: talent, concentration, and meaning
(39:43) What seems impossible now that will be routine in 20 years