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arXiv:2601.05113 · npj Quantum Information

Unitary fault-tolerant encoding of Pauli states in surface codes

Luis Colmenarez, Remmy Zen, Jan Olle, Florian Marquardt, Markus Müller

quant-phSubmitted Jan 8, 2026• Announced Jan 9, 2026• 0 citations
arXivHTMLPDF

Abstract

In fault-tolerant quantum computation, the preparation of logical states is a ubiquitous subroutine, yet significant challenges persist even for the simplest states required. In the present work, we present a unitary, scalable, distance-preserving encoding scheme for preparing Pauli eigenstates in surface codes. Unlike previous unitary approaches whose fault-distance remains constant with increasing code distance, our scheme ensures that the protection offered by the code is preserved during state preparation. Building on strategies discovered by reinforcement learning for the surface-17 code, we generalize the construction to arbitrary code distances and both rotated and unrotated surface codes. The proposed encoding relies only on geometrically local gates, and is therefore fully compatible with planar 2D qubit connectivity, and it achieves circuit depth scaling as $\mathcal{O}(d)$, consistent with fundamental entanglement-generation bounds. We design explicit stabilizer-expanding circuits with and without ancilla-mediated connectivity and analyze their error-propagation behavior. Numerical simulations under depolarizing noise show that our unitary encoding without ancillas outperforms standard stabilizer-measurement-based schemes, reducing logical error rates by up to an order of magnitude. These results make the scheme particularly relevant for platforms such as trapped ions and neutral atoms, where measurements are costly relative to gates and idling noise is considerably weaker than gate noise. Our work bridges the gap between measurement-based and unitary encodings of surface-code states and opens new directions for distance-preserving state preparation in fault-tolerant quantum computation.

DOI
10.1038/s41534-026-01362-4

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In fault-tolerant quantum computation, the preparation of logical states is a ubiquitous subroutine, yet significant challenges persist even for the simplest states required. In the present work, we present a unitary, scalable, distance-preserving encoding scheme for preparing Pauli eigenstates in surface codes. Unlike previous unitary approaches whose fault-distance remains constant with increasing code distance, our scheme ensures that the protection offered by the code is preserved during state preparation. Building on strategies discovered by reinforcement learning for the surface-17 code, we generalize the construction to arbitrary code distances and both rotated and unrotated surface codes. The proposed encoding relies only on geometrically local gates, and is therefore fully compatible with planar 2D qubit connectivity, and it achieves circuit depth scaling as O(d)\mathcal{O}(d)O(d), consistent with fundamental entanglement-generation bounds. We design explicit stabilizer-expanding circuits with and without ancilla-mediated connectivity and analyze their error-propagation behavior. Numerical simulations under depolarizing noise show that our unitary encoding without ancillas outperforms standard stabilizer-measurement-based schemes, reducing logical error rates by up to an order of magnitude. These results make the scheme particularly relevant for platforms such as trapped ions and neutral atoms, where measurements are costly relative to gates and idling noise is considerably weaker than gate noise. Our work bridges the gap between measurement-based and unitary encodings of surface-code states and opens new directions for distance-preserving state preparation in fault-tolerant quantum computation.
Preparing logical states is a constantly recurring primitive at the start of any surface-code-based quantum computation. The standard measurement-based protocol is expensive on neutral atoms, since measurements are orders of magnitude slower than gates and, on single-zone architectures, additionally require shuttling the atoms to a readout zone. In this work, we present a measurement-free, unitary preparation of surface-code Pauli eigenstates tailored to neutral atoms. A bidirectional stabilizer-expanding CNOT cascade grows the patch from its middle line outward in depth (d+3)/2(d{+}3)/2(d+3)/2, while retaining fault distance ddd in the protected error direction. Each layer maps to one collective atom move followed by a single global Rydberg pulse, with about one row pickup per two layers. We compile and simulate the resulting schedules with the open-source bloqade toolchain under a hardware-calibrated, circuit-level neutral-atom noise model. The bidirectional cascade achieves the lowest logical error rate at every distance, and is the only construction tested that operates below threshold for both logical states at the considered device-level noise.
The surface code is a promising candidate for fault-tolerant quantum computation and has been implemented in many quantum hardware platforms. In this work, we propose a new non-local unitary circuit to encode surface code states based on a code conversion between rotated and regular surface codes, which halves the circuit depth of the fastest unitary encoder known previously. While the unitary encoders can be used to increase the code size, the fault-distance remains fixed. Nonetheless, they can be used for space-time efficient preparation of eigenstates of the logical operators that cannot be easily accessed transversally such as the Pauli Y -eignestate and Clifford eigenstates. It may be expected that error propagation in the non-local circuit will make decoding more challenging compared to local ones. However, we find that conventional matching decoders can still be effectively used. Furthermore, we perform numerical simulations to benchmark the performance of our encoder against a local unitary encoder and the conventional stabilizer-measurement based approach for preparing the Pauli Y -eigenstate. We find that our encoder can outperform other approaches in certain experimentally relevant noise regimes. Therefore, our encoder provides practical advantage in platforms where non-local interactions are available such as neutral atoms and trapped ions.
Quantum computation holds the promise of solving certain complex problems exponentially faster than classical computers. However, the high prevalent noise in current quantum devices impedes the accurate execution of even basic algorithms. This can be remedied by protecting quantum information with a quantum error-correcting code, where the logical information of an algorithmic qubit is spread across multiple physical qubits. Individual quantum errors are then located and corrected by the fault-tolerant measurement of multi-qubit stabilizer operators (parity checks). Unfortunately, error correction and fault tolerance both impose large demands on the qubit overhead: hundreds to thousands of physical qubits per logical qubit. We reduce the spacetime cost of fault tolerance by redesigning key building blocks of an error-corrected quantum computer. First, we develop a combinatorial proof with flag fault tolerance that exponentially reduces the extra qubits needed to measure a stabilizer of any size, while tolerating one fault. We leverage these proofs to then design state preparation circuits for the Steane and Golay codes with 100% yield. Next, we improve error correction on a planar layout by showing that a distance-four code encoding six logical qubits protects information as well as the distance-five surface code, using one-tenth as many physical qubits. Finally, we optimize the time overhead of logical gates in surface code quantum computers by protecting measurement results with a classical code, cutting computation time by a factor of two to six. Our hardware-agnostic optimizations of fault tolerance overheads thus suggest new routes to advance the timeline of error-free quantum computing.
Stabilizer quantum error correction (QEC) codes, in particular topological surface codes, are prime candidates to enable practical quantum computing. While it is widely believed that strictly fault-tolerant protocols can only be implemented using single- and two-qubit gates, several quantum computing platforms, including trapped ions, neutral atoms, and superconducting qubits, support native multi-qubit operations. In this Letter, we show that stabilizer measurement circuits for unrotated surface codes can be fault tolerant using single auxiliary qubits and three-qubit gates. These gates enable lower-depth circuits with fewer fault locations and potentially shorter QEC cycle times. We find that in an optimistic parameter regime where fidelities of three-qubit gates are the same as those of two-qubit gates, the logical error rate can be up to one order of magnitude lower and the threshold significantly higher, increasing from ≈0.63% to ≈0.83%. Our results, applicable to a wide range of platforms, motivate further investigation into multi-qubit gates for fault-tolerant QEC as they can offer substantial time and physical qubit resource advantages to reach a given target logical error rate.
We present a fault-tolerant quantum-memory architecture that concatenates four distance-t rotated surface-code patches with the [[4,2,2]] outer code, encoding two logical qubits at code distance d = 2t in a physical footprint of N < 2(2t+1)^2 qubits on a square lattice with nearest-neighbor connectivity. The outer-code stabilizer generators XXXX and ZZZZ, each of physical weight 4t, are measured in situ via verified Greenberger-Horne-Zeilinger (GHZ) ancillae distributed through narrow corridors between adjacent patches, without lattice surgery or long-range gates. The outer-code gadgets introduce hyperedge fault mechanisms, but by design each decomposes into graphlike components, so the complete syndrome is decoded by a single minimum-weight-perfect-matching pass. Circuit-level simulations show logical error rates that scale as p^t, consistent with distance-2t protection. Finally, we implement the construction experimentally on a 105-qubit Willow superconducting processor in both the ZZ and XX memory bases. With the correlated-matching decoder, increasing the code distance from d = 4 to d = 6 reduces the block logical error rate by a factor of 1.52. The construction thus provides a near-term testbed for concatenated architectures beyond the standard surface code.
Modular quantum computing is a leading paradigm for scaling quantum computation beyond the resource limitations of monolithic devices. In this architecture, multiple quantum processing units (QPUs), employing identical or distinct qubit modalities, are interconnected via shared entanglement. Here, we investigate how errors at module interfaces and within individual QPUs affect fault-tolerant computation when qubits are encoded using the rotated surface code. Going beyond the logical-memory benchmark, we perform circuit-level simulations of fault-tolerant nonlocal CNOT gates implemented via lattice surgery between QPUs connected by noisy Bell pairs, and analyze the resulting logical error rates. Our results show that interfaces can tolerate noise up to an order of magnitude higher than intra-QPU noise, with only a minor reduction in the fault-tolerance threshold. We further develop an efficient protocol for preparing distributed fault-tolerant logical GHZ states, reducing ancilla overhead, time, and nonlocal Bell-pair consumption. We show that ancilla minimization in this setting is equivalent to a vertex-cover problem on an associated graph, and introduce a polynomial-time heuristic algorithm for finding low-overhead solutions. Our results provide quantitative evidence that distributed quantum error correction can enable scalable, fault-tolerant quantum computation in modular architectures.