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5 min readWhy Spin Qubits Will Win the Quantum Race (Part 2)
At the 2026 American Physical Society March Meeting, Krishna Chowdhury was standing outside an Alice & Bob party in Denver when a German neutral-atoms researcher asked what he worked on. "Spin qubits," he said. The response: "What's that?" As if he'd said qubits made of cheese. The German added, "You know about my technology, but I don't know about yours. Maybe that says something." Six months later, the paper Chowdhury contributed to landed on the cover of Nature — volume 655, issue 8125 — titled Quantum Silicon. This episode is, in his words, "the clap back."
The FFP Criteria: What Makes a Good Quantum Computer
To evaluate quantum computing architectures, Chowdhury proposes three criteria: qubit quality (how long the qubit remembers its state), qubit control (how reliably you can initialize, manipulate, and read out the state), and scalability and economics (how easily you can build a million of them).
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What you'll learn
- 1 (00:08) **The Core Thesis: Silicon Scales** - The episode opens with a direct comparison: trapped ions need a laser per qubit, superconducting needs a cryostat the size of a warehouse, but spin qubits run through standard TSMC/ASML fabrication lines.
- 2 (19:31) **The FFP Criteria for a Good Quantum Computer** - Krishna introduces a three-part audit framework to evaluate quantum computing modalities: qubit quality, qubit control, and scalability/economics.
- 3 (23:30) **Refresher: Quantum Computers as Interference Machines** - Krishna reviews the fundamental concept: a quantum computer is not a brute-force parallel processor but a "giant interference machine" where correct answers constructively interfere and wrong answers cancel out.
- 4 (29:18) **The Classical Precedent: Why Silicon Won** - Krishna draws a historical parallel: early computers used vacuum tubes and relay switches, which worked but could not scale. The transistor, made of silicon, won because it could be manufactured at scale.
- 5 (32:19) **DeVincenzo's Criteria and the FFP Audit** - Krishna traces the history from Feynman's 1980 lecture to David DiVincenzo's 2000 paper, which laid out five criteria for a physical quantum computer, originally to dismiss liquid-state NMR approaches.
- 6 (57:22) **Audit 1: Superconducting Qubits (Score: 11/30)** - Krishna explains the transmon qubit, which uses a Josephson junction to create an anharmonic oscillator, allowing selective addressing of the 0 and 1 states.
- 7 (87:31) **Audit 2: Trapped Ions (Score: 11/30)** - Krishna explains that trapped ions use actual atoms (e.g., barium) confined in a Paul trap, with hyperfine energy levels serving as the 0 and 1 states.
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Show Notes
Which quantum computer will actually scale?
In Part 2 of our quantum computing deep dive, Lester Nare and Krishna Choudhary move from theory to hardware—comparing superconducting qubits, trapped ions, neutral atoms, and silicon spin qubits before going inside the new Nature cover paper Krishna co-authored with the HRL Quantum Team and collaborators.
The episode begins with a simple question: what makes a good quantum computer? We evaluate each architecture using three criteria: qubit quality, qubit control, and scalability and economics.
Superconducting qubits offer extremely fast operations, but scaling them introduces challenges involving microwave control, frequency crowding, cryogenic wiring, physical size, and cooling. Trapped ions preserve quantum information for extraordinary lengths of time, but their slower gates and increasingly complex optical systems introduce a different set of tradeoffs. Neutral atoms can be arranged in dense, reconfigurable arrays using optical tweezers and entangled through Rydberg interactions, while raising questions involving atom loss, correlated noise, readout, and execution time.
Then we get to silicon.
Beginning with the Loss–DiVincenzo proposal, Krishna explains how individual electron spins can be confined inside semiconductor quantum dots, manipulated through exchange interactions, and measured using single-electron transistors. We then explore exchange-only qubits, where three electron spins encode a single qubit and quantum gates can be performed using electrical control.
That leads to the Nature cover paper, A digitally controlled silicon quantum processing unit. The HRL system integrates 18 encoded qubits built from 54 quantum dots with cryogenic control electronics, a superconducting interconnect, automated calibration, and an engineered silicon-germanium heterostructure.
Krishna also explains his own work using machine learning to automate quantum-device tuning—an essential problem if spin-qubit systems are ever going to grow from dozens of components to millions.
The larger thesis is about manufacturing. The semiconductor industry has spent decades learning how to fabricate silicon devices at enormous scale. If quantum processors can inherit that infrastructure, the architecture that ultimately wins may not be the one that reaches the finish line first—but the one humanity already knows how to manufacture.
Nature paper:A digitally controlled silicon quantum processing unitDOI: 10.1038/s41586-026-10754-7https://www.nature.com/articles/s41586-026-10754-7
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