Scientists just cracked the quantum code hidden in a single atom
A research team has created a quantum logic gate that uses fewer qubits by encoding them with the powerful GKP error-correction code. By entangling quantum vibrations inside a single atom, they achieved a milestone that could transform how quantum computers scale.
To build a large-scale quantum computer that works, scientists and engineers need to overcome the spontaneous errors that quantum bits, or qubits, create as they operate.
Scientists encode these building blocks of quantum information to suppress errors in other qubits so that a minority can operate in a way that produces useful outcomes.
As the number of useful (or logical) qubits grows, the number of physical qubits required grows even further. As this scales up, the sheer number of qubits needed to create a useful quantum machine becomes an engineering nightmare.
Now, for the first time, quantum scientists at the Quantum Control Laboratory at the University of Sydney Nano Institute have demonstrated a type of quantum logic gate that drastically reduces the number physical qubits needed for its operation.
To do this, they built an entangling logic gate on a single atom using an error-correcting code nicknamed the 'Rosetta stone' of quantum computing. It earns that name because it translates smooth, continuous quantum oscillations into clean, digital-like discrete states, making errors easier to spot and fix, and importantly, allowing a highly compact way to encode logical qubits.
GKP Codes: A Rosetta Stone for Quantum Computing
This curiously named Gottesman-Kitaev-Preskill (GKP) code has for many years offered a theoretical possibility for significantly reducing the physical number of qubits needed to produce a functioning 'logical qubit'. Albeit by trading efficiency for complexity, making the codes very difficult to control.
Research published on August 21 in Nature Physics demonstrates this as a physical reality, tapping into the natural oscillations of a trapped ion (a charged atom of ytterbium) to store GKP codes and, for the first time, realizing quantum entangling gates between them.
Led by Sydney Horizon Fellow Dr Tingrei Tan at the University of Sydney Nano Institute, scientists have used their exquisite control over the harmonic motion of a trapped ion to bridge the coding complexity of GKP qubits, allowing a demonstration of their entanglement.
"Our experiments have shown the first realization of a universal logical gate set for GKP qubits," Dr Tan said. "We did this by precisely controlling the natural vibrations, or harmonic oscillations, of a trapped ion in such a way that we can manipulate individual GKP qubits or entangle them as a pair."
Quantum Logic Gate and Software Innovation
A logic gate is an information switch that allows computers - quantum and classical - to be programmable to perform logical operations. Quantum logic gates use the entanglement of qubits to produce a completely different sort of operational system to that used in classical computing, underpinning the great promise of quantum computers.
First author Vassili Matsos is a PhD student in the School of Physics and Sydney Nano. He said: "Effectively, we store two error-correctable logical qubits in a single trapped ion and demonstrate entanglement between them.
"We did this using quantum control software developed by Q-CTRL, a spin-off start-up company from the Quantum Control Laboratory, with a physics-based model to design quantum gates that minimize the distortion of GKP logical qubits, so they maintain the delicate structure of the GKP code while processing quantum information."
A Milestone in Quantum Technology
What Mr Matsos did is entangle two 'quantum vibrations' of a single atom. The trapped atom vibrates in three dimensions. Movement in each dimension is described by quantum mechanics and each is considered a 'quantum state'. By entangling two of these quantum states realized as qubits, Mr Matsos created a logic gate using just a single atom, a milestone in quantum technology.
This result massively reduces the quantum hardware required to create these logic gates, which allow quantum machines to be programmed.
Dr Tan said: "GKP error correction codes have long promised a reduction in hardware demands to address the resource overhead challenge for scaling quantum computers. Our experiments achieved a key milestone, demonstrating that these high-quality quantum controls provide a key tool to manipulate more than just one logical qubit.
"By demonstrating universal quantum gates using these qubits, we have a foundation to work towards large-scale quantum-information processing in a highly hardware-efficient fashion."
Across three experiments described in the paper, Dr Tan's team used a single ytterbium ion contained in what is known as a Paul trap. This uses a complex array of lasers at room temperature to hold the single atom in the trap, allowing its natural vibrations to be controlled and utilized to produce the complex GKP codes.
This research represents an important demonstration that quantum logic gates can be developed with a reduced physical number of qubits, increasing their efficiency.
The authors declare no competing interests. Funding was received from the Australian Research Council, Sydney Horizon Fellowship, the US Office of Naval Research, the US Army Research Office, the US Air Force Office of Scientific Research, Lockheed Martin, Sydney Quantum Academy and private funding from H. and A. Harley.
Sign in to highlight and annotate this article

Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
research
Stop Writing Boilerplate. Start Building: Introducing app-generator-cli
Last Updated on April 2, 2026 by Editorial Team Author(s): Rajendra Kumar Yadav, M.Sc (CS) Originally published on Towards AI. Scaffold production-ready FastAPI, LangChain, and full-stack Python projects in seconds — powered by uv. You have a great idea. You open your terminal, create a new folder, and then… you spend the next 60–90 minutes doing the same thing you always do. ai generate imageThe article introduces app-generator-cli, a command-line tool designed to eliminate the repetitive boilerplate tax experienced by Python developers, streamlining the setup of common backend projects like FastAPI and LangChain. It discusses the tool s ability to scaffold production-ready templates for different use cases, its ease of installation via pip, and optional flags for customization. Additiona

Bankai (卍解) — the first post-training adaptation method for true 1-bit LLMs.
I've been experimenting with Bonsai 8B — PrismML's true 1-bit model (every weight is literally 0 or 1, not ternary like BitNet). I realized that since weights are bits, the diff between two model behaviors is just a XOR mask. So I built a tool that searches for sparse XOR patches that modify model behavior. The basic idea: flip a row of weights, check if the model got better at the target task without breaking anything else, keep or revert. The set of accepted flips is the patch. What it does on held-out prompts the search never saw: Without patch: d/dx [x^7 + x] = 0 ✗ With patch: d/dx [x^7 + x] = 7x^6 + 1 ✓ Without patch: Is 113 prime? No, 113 is not prime ✗ With patch: Is 113 prime? Yes, 113 is a prime number ✓ 93 row flips. 0.007% of weights. ~1 KB. Zero inference overhead — the patched
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.


.jpg)



Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!