Quantum Leaps: The Fascinating Journey and Cultural Impact of Quantum Computing
How a physicist's frustration in 1981 became a 105-qubit chip that spooked every cryptographer alive
Contents
<p>In May 1981, at a conference at MIT, Richard Feynman stood up and complained that classical computers were hopeless at simulating physics. His point was blunt: nature is quantum-mechanical, and if you want to simulate a quantum system faithfully, the number of classical bits you need explodes exponentially with the size of the system. His proposed fix was almost cheeky — build a computer that is <em>itself</em> quantum-mechanical, and let physics do the hard part. The Soviet mathematician Yuri Manin had floated a similar idea a year earlier in a book most Western researchers hadn’t read. That grumble is where quantum computing actually starts, and it is a far better origin story than the one you usually get, which opens with a definition of a qubit and puts everyone to sleep.</p>
<p>I am a self-hoster and a security tinkerer, not a physicist, and I am going to write about quantum computing from that angle: what it is, why it took forty years to get anywhere, and why the thing that should concern a practical person is not “faster computers” but “the encryption protecting your data has an expiry date you can’t see.” The hype around this field is enormous and mostly wrong. The reality is narrower, slower, and — in one specific corner — genuinely alarming.</p>
<h2 id="what-a-qubit-actually-buys-you">What a qubit actually buys you</h2><div class="ad-unit ad-in-article" aria-label="Advertisement">
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<p>A classical bit is 0 or 1. A qubit can be in a <em>superposition</em> of both, described by two complex amplitudes, until you measure it and it collapses to one value. String together <em>n</em> qubits and the system’s state is described by 2ⁿ amplitudes evolving together. Thirty qubits is a billion amplitudes; three hundred qubits is more amplitudes than there are atoms in the observable universe. That is the source of the power and, immediately, the source of the difficulty.</p>
<p>The catch nobody mentions in the breathless coverage: you cannot read those amplitudes out. Measurement gives you one classical answer, chosen probabilistically. The entire art of quantum algorithm design is arranging <em>interference</em> — the two other key ingredients are superposition and entanglement — so that the wrong answers cancel out and the right answer is overwhelmingly likely when you finally measure. A quantum computer is not a massively parallel classical computer that checks every possibility at once, however often you read that. It is a device that manipulates probability amplitudes so cleverly that the answer you want falls out. Get that distinction and you are ahead of most of the marketing.</p>
<h2 id="why-it-took-forty-years">Why it took forty years</h2>
<p>Feynman’s idea sat as a curiosity through the 1980s. Two results dragged it into the mainstream. In 1994, Peter Shor at Bell Labs published an algorithm that factors large integers in polynomial time on a quantum computer — exponentially faster than the best known classical method. In 1996, Lov Grover produced an algorithm giving a quadratic speed-up for unstructured search. Shor’s algorithm in particular electrified the field, because the difficulty of factoring large numbers is exactly what RSA encryption rests on. Suddenly quantum computing wasn’t an academic toy; it was a hypothetical crowbar aimed at the internet’s locks.</p>
<p>The reason it then took another thirty years to build anything useful is one word: decoherence. Qubits are absurdly fragile. A stray photon, a thermal vibration, a whisper of electromagnetic noise, and the delicate superposition collapses into meaningless noise. Real quantum computers run at temperatures colder than deep space, shielded obsessively, and <em>still</em> their qubits lose coherence in microseconds. Every gate operation introduces error. For decades the error rates were so high that adding more qubits made things worse, not better — the noise swamped any computation before it finished.</p>
<h2 id="the-willow-moment">The Willow moment</h2><div class="ad-unit ad-in-article" aria-label="Advertisement">
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<p>This is why Google’s December 2024 announcement of its Willow chip mattered, and it is worth being precise about <em>what</em> it achieved, because the coverage was dreadful. Willow is a 105-qubit superconducting processor. Its headline result was not raw power; it was crossing the “below threshold” line in quantum error correction. The idea, going back to Shor and others in the 1990s, is that you can spread one reliable <em>logical</em> qubit across many noisy <em>physical</em> qubits, using the redundancy to detect and correct errors. The problem was always that the error-correction machinery itself introduced more errors than it fixed once you scaled up.</p>
<p>Google’s team tested arrays of 3×3, 5×5, and 7×7 physical qubits and showed that each time they made the array <em>bigger</em>, the logical error rate went <em>down</em> — by a factor of about 2.14 for each step up in code distance, landing at a distance-7 code with roughly 0.143% error per correction cycle. That is the first convincing demonstration that error correction gets better with scale rather than worse. It does not mean we have a useful quantum computer. It means the road to one is no longer theoretically blocked. Those are very different claims, and the gap between them is probably a decade or more of engineering.</p>
<h2 id="why-you-specifically-should-care-about-the-crypto">Why you, specifically, should care about the crypto</h2>
<p>Here is the part that connects to the machines I actually run. Shor’s algorithm, once there is hardware big enough to run it on realistic key sizes, breaks RSA and elliptic-curve cryptography — the asymmetric crypto underpinning TLS, SSH, code signing, and most of the secure internet. The symmetric stuff (AES) is far safer; Grover’s algorithm only halves its effective key strength, so AES-256 stays comfortable. But the key <em>exchange</em> that sets up those symmetric sessions is exactly the vulnerable asymmetric part.</p>
<p>No quantum computer today can factor a number big enough to threaten a real RSA key. Estimates for cracking RSA-2048 run to millions of high-quality physical qubits; Willow has 105. So why lose sleep? Two words: <strong>harvest now, decrypt later.</strong> An adversary can record your encrypted traffic today and simply store it, waiting for the hardware to mature. Anything you send now that must stay secret for ten or twenty years — medical records, state secrets, long-lived credentials — is arguably already compromised. This is not paranoia; it is why NIST finalised its post-quantum cryptography standards in 2024, and why the migration has already started. I dig into what that migration actually involves in <a href="/story/quantum-safe-cryptography-explained-future-proofing-your-organizations-data/">quantum-safe cryptography explained</a>, and the practical background on the field sits in <a href="/story/what-you-need-to-know-about-quantum-computing/">what you need to know about quantum computing</a>.</p>
<p>For a homelabber the takeaway is modest but real: keep your TLS libraries current so you inherit hybrid post-quantum key exchange as it lands, don’t rely on any single long-lived asymmetric key for something that must survive decades, and treat “this is encrypted, therefore safe forever” as the false statement it has quietly become.</p>
<h2 id="what-it-is-genuinely-good-for">What it is genuinely good for</h2>
<p>Strip away the crypto scare and the marketing, and there is a real, narrow set of problems where a mature quantum computer would be transformative — and it is worth knowing them, because they explain why serious money keeps flowing in despite the decade-long timelines.</p>
<p>The first is the one Feynman started with: simulating quantum systems. Modelling how a drug molecule binds to a protein, or how electrons behave in a novel material or catalyst, means simulating quantum mechanics — precisely the task classical computers choke on. A useful quantum computer would let chemists and materials scientists design molecules on a machine instead of in a wet lab, which is why pharmaceutical and battery research feature heavily in the funding. This is not hypothetical hand-waving; it is the original motivation and still the most credible near-term application.</p>
<p>The second is certain optimisation and search problems, where Grover’s quadratic speed-up or purpose-built quantum algorithms could beat classical methods on specific structures. The honest caveat: “quadratic speed-up” is far less dramatic than the exponential one Shor gets on factoring, and for many real optimisation problems the advantage evaporates once you account for the overhead of getting data into and out of the quantum machine. Anyone promising quantum will revolutionise your logistics or your trading strategy next year is well ahead of the evidence.</p>
<p>What quantum computers are <em>not</em> good for is worth repeating: anything involving large amounts of ordinary data, arithmetic, string processing, serving web pages, or running the software that actually keeps a business alive. Those are classical problems and will stay classical. The quantum machine, if it arrives, will sit beside classical computers as a co-processor for a handful of hard, specific tasks — much as a GPU accelerates graphics and matrix maths without replacing the CPU.</p>
<h2 id="the-hype-filter">The hype filter</h2>
<p>Because this field attracts money and headlines, it attracts nonsense. A few things I have learned to discount:</p>
<ul>
<li><strong>“Quantum will replace your laptop.”</strong> No. Quantum computers are terrible at the things classical computers are good at. They are special-purpose accelerators for a narrow class of problems — simulation, certain optimisation, factoring — not general-purpose machines. Your laptop is safe.</li>
<li><strong>“Qubit count is the score.”</strong> A thousand noisy qubits are worth less than a hundred error-corrected ones. Watch logical qubits and error rates, not the headline physical count. This is the same trap as judging a CPU by clock speed alone, and it is a useful lens on other over-hyped hardware pitches too, of the sort I pick apart in <a href="/story/edge-computing-vs-cloud-choosing-the-right-architecture-for-mission-critical-iot/">choosing the right architecture for mission-critical IoT</a>.</li>
<li><strong>“It broke Bitcoin / it will next year.”</strong> Not on current hardware, not close. The timeline for cryptographically-relevant quantum computers is genuinely uncertain and measured in years-to-decades, and anyone quoting you a confident date is selling something.</li>
</ul>
<h2 id="is-it-worth-caring-about">Is it worth caring about?</h2>
<p>If you build things, yes — but proportionately. Quantum computing is not going to change how you write a web app, run a cluster, or self-host a service any time this decade. What it <em>is</em> going to change, and has arguably already changed, is the shelf life of the encryption you rely on. The Willow result is the clearest sign yet that the error-correction problem is tractable, which moves the crypto threat from “science fiction” to “engineering timeline.” That is the one lever a practical person should pull: start the slow, unglamorous work of getting post-quantum-ready now, while it is a planned upgrade rather than an emergency.</p>
<p>The rest of the field — the cultural fascination, the science-fiction glamour, the promise of simulating molecules and cracking optimisation problems — is real and genuinely exciting, but it is a spectator sport for most of us for now. Feynman’s 1981 complaint has turned into working, error-corrected hardware in a lab in Santa Barbara. That is a remarkable forty-year arc. It just isn’t, yet, sitting in anyone’s rack.</p>
<p>What I keep coming back to is how <em>slow</em> real progress has been compared to the headlines, and how that slowness is itself reassuring. Each genuine milestone — Shor’s algorithm, the first entangled logical qubit, Willow crossing the error-correction threshold — arrived years apart and moved the needle by a modest, hard-won increment. That cadence is the opposite of a sudden apocalypse, and it is exactly why the sensible response is preparation rather than panic: start rotating toward post-quantum-safe crypto now, watch the logical-qubit numbers rather than the hype, and let the physicists in Santa Barbara take their well-earned decade.</p>
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