QuEra Paper Simulates Only Two Physical Qubits Are Needed Per Logical Qubit

Quera show 580 and 1156 logical qubits with neutral atom quantum computer simulations. April 2026 breakthrough (with Harvard/MIT) they shiow high-rate codes achieving over 50% encoding rate. They are using about ~2 physical qubits per logical qubit or better in simulations, with logical error rates in the teraquop regime. (1,152 physical → 580 logical; 2,304 physical → 1,156 logical). This is a massive leap from surface codes. They plan a system with 100 logical qubits (and 10,000 physical) in 2026. QuEra had a physical 96 logical qubits demonstrated (2026 world record) on 448 physical qubits using high-rate quantum error-correcting codes (4.7 physical to 1 logical). Fewer physical qubits is better for a logical qubit. Most approaches today need hundreds to thousands of physical qubits to build one reliable logical qubit. They show it can be done with just over two. Building on a recent theory breakthrough (Kasai, 2026), they show that quantum error-correcting codes with encoding rates above 1/2 could be used in practical settings, and directly verify in simulation that they can achieve error rates as low as one error per trillion steps. Screenshot With these ultra-high rates, a system of tens of thousands of physical qubits could deliver the logical qubit counts and low error rates that many proposed algorithms require. This brings useful quantum computing closer. QuEra hief Commercial Office Boger cautioned that current quantum capabilities are often overstated. “Quantum computers are not there yet,” he said. “They’re experimental devices that are used for developing algorithms.” “There are very few things that quantum computers can do that you cannot do on a classical computer today,” Boger added. What is being underestimated, in his view, is how quickly that could change. “What is under-hyped, sometimes, is the potential of quantum computers … Quantum computers are not 15 years away. We think they’re two or three years away from being truly used by businesses, in governments,” he said. Headline Results [[n = 1152, k = 580, d ≤ 12]] — encoding 580 logical qubits into 1152 physical qubits, achieving an encoding rate of 0.503, and protecting against up to 5 errors [[n = 2304, k = 1156, d ≤ 14]] — encoding 1156 logical qubits into 2304 physical qubits, achieving an encoding rate of 0.502, and protecting against up to 6 errors We design these codes to satisfy new structural conditions that enable very efficient atom movement, making them well-suited for neutral-atom platforms Per-logical-per-round error rate approaching the Teraquop regime: 1.3⁺³·⁰₋₀.₉ × 10⁻¹³, under a realistic circuit-level noise model and using a new decoder The rest of this post describes how we co-designed the code and benchmarked its performance, why it is particularly well-suited for neutral atom platforms like QuEra’s, and where the result sits in the rapidly evolving, broader QEC landscape. Classical low-density parity-check (LDPC) codes are a widely deployed and well-established technology, forming the backbone of modern communication and storage systems. It is well known that, in this classical setting, increasing the girth of the Tanner graph while maintaining regular degree distributions leads simultaneously to good belief-propagation (BP) decoding performance and large minimum distance. In the quantum setting, however, this principle does not directly apply because quantum LDPC codes must satisfy additional orthogonality constraints between their parity-check matrices. When one enforces both orthogonality and regularity in a straightforward manner, the girth is typically reduced and the minimum distance becomes structurally upper bounded. In this work, we overcome this limitation by using permutation matrices with controlled commutativity and by restricting the orthogonality constraints to only the active part of the construction, while preserving regular check-matrix structures. This design circumvents conventional structural distance limitations induced by parent-matrix orthogonality, and enables the construction of quantum LDPC codes with large girth while avoiding latent low-weight logical operators. As a concrete demonstration, they construct a girth-8, -regular quantum LDPC code and show that, under BP decoding combined with a low-complexity post-processing algorithm, it achieves a frame error rate as low as 10−8 on the depolarizing channel with error probability 4%. Brian WangBrian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology. Known for identifying cutting edge technologies, he is currently a Co-Founder of a startup and fundraiser for high potential early-stage companies. He is the Head of Research for Allocations for deep technology investments and an Angel Investor at Space Angels. A frequent speaker at corporations, he has been a TEDx speaker, a Singularity University speaker and guest at numerous interviews for radio and podcasts. He is open to public speaking and advising engagements.