Efficient Quantum Error Correction from Three Dimensional Qubit Control
- URL: http://arxiv.org/abs/2609.04459v1
- Date: Thu, 03 Sep 2026 20:41:11 GMT
- Title: Efficient Quantum Error Correction from Three Dimensional Qubit Control
- Abstract summary: We study the ([[144,12,12]]) bicycle code on a neutral-atom architecture with native three-dimensional (3D) geometry.<n>Native 3D geometry can improve both the packing density and executable realization of nonlocal qLDPC codes.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: High-rate quantum low-density parity-check (qLDPC) codes can substantially reduce qubit overhead relative to surface codes, but their advantage depends on efficiently realizing nonlocal syndrome extraction. We study the \([[144,12,12]]\) bivariate bicycle code on a neutral-atom architecture with native three-dimensional (3D) geometry, comparing planar and 3D embeddings while holding the code fixed. We characterize spatial efficiency using the logical-qubit density, defined as the number of encoded logical qubits per unit spatial footprint. Because the optical controller's field of view limits the transverse extent of an array, this metric estimates the number of logical qubits that can be accommodated within a fixed optical field of view. The 3D embedding achieves approximately \(4\times\) greater areal logical-qubit density than the planar layout and \(42\times\) greater than a surface-code baseline. It also reduces the bivariate bicycle syndrome-extraction time by roughly \(2\times\) compared to a planar baseline, with fewer movement operations and substantially shorter atom-transport distance. Native 3D geometry can improve both the packing density and executable realization of nonlocal qLDPC codes, making practical performance depend jointly on code structure, optical geometry, transport scheduling, and hardware-level noise. This motivates further development of control techniques in 3D.
Related papers
- Nearest-neighbour gates are all you need: High-rate quantum low-density parity-check codes on a planar grid [3.6646002427839126]
We introduce a family of quantum low-density parity-check codes, for the first time, using only nearest-neighbour gates on a square grid of qubits.<n>We find finite-size instances such as a [[323,14,15]] code, whose code-efficiency ratio is nearly an order of magnitude larger than that of rotated surface-code patches.<n>These results show that the advantages of quantum low-density parity-check codes can survive compilation into strictly planar nearest-neighbour circuits.
arXiv Detail & Related papers (2026-06-17T18:14:23Z) - Tail-Aware Post-Training Quantization for 3D Geometry Models [58.79500829118265]
Post-Training Quantization (PTQ) enables efficient inference without retraining.<n>PTQ fails to transfer effectively to 3D models due to intricate feature distributions and prohibitive calibration overhead.<n>We propose TAPTQ, a Tail-Aware Post-Training Quantization pipeline for 3D geometric learning.
arXiv Detail & Related papers (2026-02-02T07:21:15Z) - A Folded Surface Code Architecture for 2D Quantum Hardware [5.881921610566565]
Qubit shuttling has become an indispensable ingredient for scaling leading quantum computing platforms.<n>We present a scalable architecture that employs short-range shuttling to realize effective three-dimensional connectivity on a strictly two-dimensional device.<n>We show that this architecture reduces the runtime of all single-qubit logical Clifford gates and logical CNOTs within subsets of qubits from $mathcalO(d)$ in conventional surface code lattice surgery to constant time.
arXiv Detail & Related papers (2026-01-27T17:29:16Z) - Planar Fault-Tolerant Quantum Computation with Low Overhead [5.232949916418351]
We introduce code craft, a framework for designing fault-tolerant logical operations on planar BB codes.<n>We show that logical operations, including controlled-NOT gates, state transfers, and Pauli measurements, can be efficiently implemented within this framework.
arXiv Detail & Related papers (2025-06-22T15:07:03Z) - Toward a 2D Local Implementation of Quantum LDPC Codes [1.1936126505067601]
Geometric locality is an important theoretical and practical factor for quantum low-density parity-check (qLDPC) codes.<n>We present an error correction protocol built on a bilayer architecture that aims to reduce operational overheads when restricted to 2D local gates.
arXiv Detail & Related papers (2024-04-26T19:48:07Z) - NDC-Scene: Boost Monocular 3D Semantic Scene Completion in Normalized
Device Coordinates Space [77.6067460464962]
Monocular 3D Semantic Scene Completion (SSC) has garnered significant attention in recent years due to its potential to predict complex semantics and geometry shapes from a single image, requiring no 3D inputs.
We identify several critical issues in current state-of-the-art methods, including the Feature Ambiguity of projected 2D features in the ray to the 3D space, the Pose Ambiguity of the 3D convolution, and the Imbalance in the 3D convolution across different depth levels.
We devise a novel Normalized Device Coordinates scene completion network (NDC-Scene) that directly extends the 2
arXiv Detail & Related papers (2023-09-26T02:09:52Z) - PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic
Occupancy Prediction [72.75478398447396]
We propose a cylindrical tri-perspective view to represent point clouds effectively and comprehensively.
Considering the distance distribution of LiDAR point clouds, we construct the tri-perspective view in the cylindrical coordinate system.
We employ spatial group pooling to maintain structural details during projection and adopt 2D backbones to efficiently process each TPV plane.
arXiv Detail & Related papers (2023-08-31T17:57:17Z) - UNETR++: Delving into Efficient and Accurate 3D Medical Image Segmentation [93.88170217725805]
We propose a 3D medical image segmentation approach, named UNETR++, that offers both high-quality segmentation masks as well as efficiency in terms of parameters, compute cost, and inference speed.
The core of our design is the introduction of a novel efficient paired attention (EPA) block that efficiently learns spatial and channel-wise discriminative features.
Our evaluations on five benchmarks, Synapse, BTCV, ACDC, BRaTs, and Decathlon-Lung, reveal the effectiveness of our contributions in terms of both efficiency and accuracy.
arXiv Detail & Related papers (2022-12-08T18:59:57Z) - Looped Pipelines Enabling Effective 3D Qubit Lattices in a Strictly 2D Device [0.0]
We explore a concept called looped pipelines which permits one to obtain many of the advantages of a 3D lattice while operating a strictly 2D device.<n>The concept leverages qubit shuttling, a well-established feature in platforms like semiconductor spin qubits and trapped-ion qubits.
arXiv Detail & Related papers (2022-03-24T15:36:17Z) - The cost of universality: A comparative study of the overhead of state
distillation and code switching with color codes [63.62764375279861]
We compare two leading FT implementations of the T gate in 2D color codes under circuit noise.
We find a circuit noise threshold of 0.07(1)% for the T gate via code switching, almost an order of magnitude below that achievable by state distillation in the same setting.
arXiv Detail & Related papers (2021-01-06T19:00:01Z) - Reinforced Axial Refinement Network for Monocular 3D Object Detection [160.34246529816085]
Monocular 3D object detection aims to extract the 3D position and properties of objects from a 2D input image.
Conventional approaches sample 3D bounding boxes from the space and infer the relationship between the target object and each of them, however, the probability of effective samples is relatively small in the 3D space.
We propose to start with an initial prediction and refine it gradually towards the ground truth, with only one 3d parameter changed in each step.
This requires designing a policy which gets a reward after several steps, and thus we adopt reinforcement learning to optimize it.
arXiv Detail & Related papers (2020-08-31T17:10:48Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.