AI Summary
5 min readIn 1981, at a conference in the woods outside Boston, Richard Feynman stood before a who's-who of physics and computing and said something that reframed the entire field: "Nature isn't classical, damn it. And if you want to take a simulation of nature, you'd better make it quantum mechanical." That talk, "Simulating Physics with Computers," is the origin story of quantum computing as we know it. But as physicist and podcast host Krishna Chowdery explains, the path from Feynman's insight to a working quantum processor—including the one he co-authored on the cover of Nature in 2026—runs through a series of countercultural ideas, a few impossible-sounding experiments, and one algorithm that turned quantum computing into a trillion-dollar national security priority.
Why a classical computer can't simulate nature
The core problem that quantum computing solves is not about speed in general. It is about a specific kind of computational explosion. Chowdery walks through the logic step by step, starting with Bell's theorem. In 1964, John Bell showed that entangled particles cannot be described as having independent, pre-existing properties. If Alice and Bob each measure one of a pair of entangled particles, the joint probability of their results cannot be factored into separate pieces for Alice and Bob. The system is one indivisible mathematical block.
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What you'll learn
- 1 (00:00) **Quantum Computing Isn't Just "Parallel Processing"** - Krishna immediately dismantles the common myth that quantum computers try every solution in parallel, explaining why that oversimplification only works for a narrow set of problems like encryption.
- 2 (01:45) **Introducing the Episode's Context: A Nature Cover Paper** - Krishna reveals his role as a co-author on a Nature cover paper about a silicon quantum processing unit, framing the episode as the theoretical foundation for a deeper hardware discussion in Part 2.
- 3 (06:56) **The Real Questions: What is a Qubit and a Quantum Algorithm?** - The hosts outline the episode's goals: to define core concepts, trace the history from the 1960s, and dismantle the hype around quantum computing.
- 4 (10:40) **The Foundation: Bell's Theorem (1964) and Entanglement** - Krishna begins the historical narrative with John Bell's theorem, which proved that quantum mechanics cannot be explained by local hidden variables, establishing the "weirdness" needed for quantum computing.
- 5 (19:26) **Experimental Proof: Violating Bell's Inequality** - Krishna explains how John Clauser, Alain Aspect, and Anton Zeilinger experimentally verified Bell's theorem, proving that quantum weirdness is real and not a philosophical debate.
- 6 (25:24) **Landauer's Principle: Information is Physical** - Krishna introduces Rolf Landauer's 1961 principle, which states that erasing information generates heat, a critical constraint for quantum computing.
- 7 (32:07) **Reversible Logic and the Toffoli Gate** - Krishna explains how Charles Bennett and Tommaso Toffoli solved the reversibility problem by inventing a universal, reversible logic gate, proving quantum computation is theoretically possible.
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Show Notes
Quantum computers do not simply “try every answer at once.” So what do they actually do—and why have governments and technology companies spent billions trying to build them?
In Part 1 of our two-part quantum computing deep dive, Lester Nare and Krishna Choudhary build the field from first principles.
The series was prompted by a new Nature cover paper, A digitally controlled silicon quantum processing unit, co-authored by Krishna and members of the HRL Quantum Team and collaborators. Before getting into that hardware in Part 2, we first need to understand why anyone wanted to build a quantum computer in the first place.
We begin with Bell’s theorem and the failure of local hidden-variable explanations of quantum mechanics. From there, we follow the realization that information is fundamentally physical through Rolf Landauer, reversible computation, Charles Bennett, Tommaso Toffoli, Paul Benioff, and the origins of quantum information science.
Then Richard Feynman changes the question. Straightforward classical simulation of an interacting quantum system requires tracking a state space that grows exponentially with the number of particles. If nature itself is quantum mechanical, Feynman asks, why not build a computer that is quantum mechanical too?
David Deutsch formalizes the universal quantum computer and introduces the first quantum algorithm. Using the Deutsch–Jozsa problem, the double-slit experiment, and Feynman’s path-integral intuition, we explain what a quantum algorithm is actually exploiting: carefully engineered constructive and destructive interference.
Finally, we reach the discoveries that turned quantum computing from an academic curiosity into a strategic technology. Daniel Simon develops an early exponential quantum speedup. Peter Shor recognizes how the underlying mathematics can be used to attack problems central to public-key cryptography. Lov Grover follows with a quantum search algorithm—and suddenly governments have a very different reason to care about quantum machines.
We also explore quantum money, quantum cryptography, the many-worlds interpretation, Google Willow and parallel-universe headlines, post-quantum security, and what useful quantum computers may ultimately be good for.
Part 2: How do you actually build one?
Nature paper:A digitally controlled silicon quantum processing unitDOI: 10.1038/s41586-026-10754-7
Link: https://www.nature.com/articles/s41586-026-10754-7
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