Why Qubit Count Headlines Are Misleading (Logical vs Physical Qubits)

01What a Physical Qubit Is, and What a Logical Qubit Is

A physical qubit is an actual piece of quantum hardware, a single two-state quantum system the engineers can manipulate and measure. Different companies build them differently. IBM and Google rely on superconducting circuits cooled to near absolute zero. IonQ and Quantinuum trap individual ions in electromagnetic fields. Atom Computing and QuEra hold neutral atoms in optical tweezers, whereas PsiQuantum and Xanadu push photons through specialized chips.

Whichever physical implementation you use, the qubits are noisy. They lose their state through unwanted interactions with their environment, a process called decoherence. They also make small errors during every gate operation. Current physical qubits across all platforms have error rates somewhere between 0.1% and 1% per gate, which sounds small but compounds disastrously across the millions of operations a working algorithm requires.

A logical qubit is what you build out of many physical qubits to fight back against those errors. The trick is quantum error correction. You spread the quantum state of one logical qubit across many physical qubits arranged in a code. The code lets the system detect and correct errors on individual physical qubits without disturbing the encoded information.

02Why the Physical-to-Logical Ratio Is So Brutal

The number of physical qubits needed per logical qubit depends on two things. First, which error-correction code you use. Second, how good your physical qubits are.

The surface code is the option researchers have studied longest. Modern rotated surface codes need about 2d² − 1 physical qubits for one logical qubit at code distance d, where larger distance means stronger error suppression.

Typical noise levels in current hardware push useful computation toward code distances around 15 to 25. That works out to between about 450 and 1,250 physical qubits per logical qubit, just to keep one piece of quantum data alive long enough to be useful. Newer codes like IBM’s bivariate bicycle codes (announced in 2024) cut the overhead, but the ratio still bottoms out at hundreds of physical qubits per logical one.

And that’s the cost of one logical qubit. A useful algorithm needs many of them.

03Where Current Hardware Actually Stands

In December 2024, Google’s Willow processor demonstrated a milestone called “below threshold” error correction. They built one logical qubit at code distance 7 across 105 physical qubits, and showed that the logical error rate decreased as they increased code distance. That’s one of the clearest hardware demonstrations to date that quantum error correction scales the way the theory says it should.

A real achievement, on a single logical qubit.

The largest physical qubit counts on actual machines look like this. IBM’s Heron processor runs 156 superconducting qubits with the company’s best gate fidelities to date. The earlier Condor processor hit 1,121 qubits at lower fidelity, which is why IBM has been emphasizing quality over raw count in its 2024 and 2025 roadmaps. Atom Computing crossed 1,180 neutral atoms. Quantinuum has reached 98 qubits with its Helios system while posting some of the lowest error rates in the field.

None of these has ever demonstrated more than a handful of useful logical qubits.

04How Much Hardware a Cryptographic Attack Would Need

Craig Gidney and Martin Ekerå published the most-cited estimate in 2019. Their conclusion was that an attack on RSA-2048 using Shor’s algorithm would need about 20 million noisy physical qubits running for 8 hours, with error rates similar to today’s best superconducting machines. But subsequent work has trimmed that number with cleverer algorithm and code choices, and the answer is still in the millions.

20 million is four orders of magnitude above the largest current physical-qubit machines, and that’s just for RSA. ECDSA with 256-bit elliptic curves, the signature scheme Bitcoin and Ethereum use for transactions, is cheaper to attack. Recent estimates put a quantum attack on Bitcoin’s secp256k1 curve below 500,000 physical qubits. That’s still orders of magnitude beyond current hardware. Behind either figure are at least a few thousand logical qubits, none of which has yet been built.

No publicly demonstrated machine has shown anything close to the thousands of high-quality logical qubits a cryptographic attack would need.

05How to Read Qubit Count Headlines

A few rules of thumb help when reading announcements about new quantum processors.

Raw qubit counts also say nothing about which chains are actually exposed. Indices like qLABS’s quantum vulnerability index (qLVI) track chain readiness and migration, which is a more decision-useful signal for holders than any processor headline. The number to watch for cryptography is logical qubits.

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The hardware exists at the physical level. The error-corrected qubits the math requires are years to decades behind it.

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This article is educational and does not constitute security or investment advice.

// FAQ

What's the difference between a physical and a logical qubit?

A physical qubit is one real, noisy quantum device. A logical qubit is many physical qubits bundled under an error-correcting code so the encoded information survives. Cryptographic attacks are counted in logical qubits; headlines report physical ones.

Why can't a 1,000-qubit machine break Bitcoin?

Those are physical qubits. After error correction they yield only a handful of logical qubits, while an attack on Bitcoin’s curve needs at least a few thousand logical qubits, built from hundreds of thousands of physical ones. No machine is close.

How many physical qubits make one logical qubit?

With today’s error rates and the surface code, roughly 450 to 1,250, depending on the code distance. Newer codes lower that, but it still runs to hundreds of physical qubits per logical qubit.

What number should I actually watch?

Logical qubits sustained over many error-correction cycles, and milestones like “below threshold” error correction. Round physical-qubit counts with no logical context are usually marketing.