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20222026
most citedExperimental Demonstration of Logical Magic State Distillation

52 citations · 82 across the 9 of their papers we have counts for

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6 papers · 1 filter

quant-ph2026

Fast and Parallel High-Rate STAR Architecture for Megaquop Quantum Simulation

Refaat Ismail, Milan Kornjača, Hong-Ye Hu +4

Fault-tolerant quantum simulation is approaching a phase where encoding overhead, logical Clifford operations, magic-state preparation, and rotation synthesis must be optimized tog…

quant-ph2025

Observation of an anomaly in the statistics of Kibble-Zurek defects

Jan Balewski, Alexey Khudorozhkov, Siva Darbha +8

The Kibble-Zurek mechanism quantifies defect formation during adiabatic passage across a continuous phase transition, providing key insights into universality in quantum many-body…

quant-ph2025

Probing emergent prethermal dynamics and resonant melting on a programmable quantum simulator

Siva Darbha, Alexey Khudorozhkov, Pedro L. S. Lopes +11

The dynamics of isolated quantum systems following a sudden quench plays a central role in many areas of material science, high-energy physics, and quantum chemistry. Featuring com…

quant-ph2025

Transversal architecture for megaquop-scale quantum simulation with neutral atoms

Refaat Ismail, I-Chi Chen, Chen Zhao +6

Quantum computing experiments have made remarkable progress in demonstrating key components of quantum error correction, a prerequisite for scalable quantum computation. While we a…

quant-ph2024★ 52 cited

Experimental Demonstration of Logical Magic State Distillation

Pedro Sales Rodriguez, John M. Robinson, Paul Niklas Jepsen +70

Realizing universal fault-tolerant quantum computation is a key goal in quantum information science. By encoding quantum information into logical qubits utilizing quantum error cor…

quant-ph2024★ 9 cited

Large-scale quantum reservoir learning with an analog quantum computer

Milan Kornjača, Hong-Ye Hu, Chen Zhao +50

Quantum machine learning has gained considerable attention as quantum technology advances, presenting a promising approach for efficiently learning complex data patterns. Despite t…