Sara Bartolucci, Patrick Birchall, Hector Bombin, Hugo Cable, Chris Dawson, Mercedes Gimeno-Segovia, Eric Johnston, Konrad Kieling, Naomi Nickerson, Mihir Pant,… 展开作者
Sara Bartolucci, Patrick Birchall, Hector Bombin, Hugo Cable, Chris Dawson, Mercedes Gimeno-Segovia, Eric Johnston, Konrad Kieling, Naomi Nickerson, Mihir Pant, Fernando Pastawski, Terry Rudolph, Chris Sparrow
We introduce fusion-based quantum computing (FBQC) - a model of universal quantum computation in which entangling measurements, called fusions, are performed on the qubits of small constant-sized entangled resource states. We introduce a stabilizer formalism for analyzing fault tolerance and computation in these schemes. This framework naturally captures the error structure that arises in certain physical systems for quantum computing, such as photonics. FBQC can offer significant architectural simplifications, enabling hardware made up of many identical modules, requiring an extremely low depth of operations on each physical qubit and reducing classical processing requirements. We present two pedagogical examples of fault-tolerant schemes constructed in this framework and numerically evaluate their threshold under a hardware agnostic fusion error model including both erasure and Pauli error. We also study an error model of linear optical quantum computing with probabilistic fusion and photon loss. In FBQC the non-determinism of fusion is directly dealt with by the quantum error correction protocol, along with other errors. We find that tailoring the fault-tolerance framework to the physical system allows the scheme to have a higher threshold than schemes reported in literature. We present a ballistic scheme which can tolerate a 10.4% probability of suffering photon loss in each fusion.
BARFI-Q: Quantum-Enhanced Block Attention Residual Fusion Framework for Multivariate Time-Series Forecasting in Atom Interferometry
Qatar Center for Quantum Computing, College of Science and Engineering, Hamad Bin Khalifa University（哈马德·本·哈利法大学科学与工程学院量子计算中心）；School of Computing, Korea Advanced Institute of Science and Technology（韩国科学技术大学计算机学院）
Feature-Adaptive Fusion in Hybrid Quantum-Classical Neural Networks for Robust Biomedical Image Classification
College of Information Science and Engineering, Zaozhuang University（枣庄学院信息科学与工程学院）；School of Cyberspace Security, Beijing University of Posts and Telecommunications（北京邮电大学网络空间安全学院）；Hangzhou City University（杭州城市学院）；School of Artificial Intelligence, Henan University（河南大学人工智能学院）；China Information Technology Security Evaluation Center（中国信息安全测评中心）；Network Center, Zaozhuang University（枣庄学院网络中心）
Instituto de Fisica Gleb Wataghin, Universidade Estadual de Campinas（坎皮纳斯州立大学格莱布·瓦塔金物理研究所）；Perimeter Institute for Theoretical Physics（理论物理前沿研究所）；Department of Physics and Astronomy, University of Waterloo（滑铁卢大学物理与天文学系）；Department of Physics, University of Toronto（多伦多大学物理系）
Expressive and Scalable Quantum Fusion for Multimodal Learning
University of Technology Sydney（悉尼技术大学）；The University of Aizu（御所大学）；Washington State University（华盛顿州立大学）；Hanoi University of Science and Technology（河内科学技术大学）；Monash University（莫纳什大学）
Quantum Information Fusion and Correction under the Transferable Belief Model
School of Electronics and Information, Northwestern Polytechnical University（电子信息学院，西北工业大学）；College of Future Information Technology, Fudan University（未来信息技术学院，复旦大学）；College of Information Engineering, Northwest A\&F University（信息工程学院，西北农林科技大学）；Institute of Fundamental and Frontier Science, University of Electronic Science and Technology of China（基础与前沿科学研究院，电子科技大学）；Department of Image and Information Processing, IMT-Atlantique（图像与信息处理系，IMT-Atlantic）
Unveiling Topological Fusion in Quantum Hall Systems from Microscopic Principles
Jagiellonian University（雅盖隆大学）；Max-Planck-Institut für Quantenoptik（马克斯·普朗克量子光学研究所）；Munich Center for Quantum Science and Technology（慕尼黑量子科学与工程中心）；Princeton University（普林斯顿大学）；Karlstads Universitet（卡尔斯特大学）；Institute for Advanced Study, Princeton（普林斯顿高等研究院）；Indiana University（印第安纳大学）
