3 papers
quant-ph2025
Generative Krylov Subspace Representations for Scalable Quantum Eigensolvers
Changwon Lee, Daniel K. Park
Predicting ground state energies of quantum many-body systems is one of the central computational challenges in quantum chemistry, physics, and materials science. Krylov subspace m…
quant-ph2025
Measurement-based Dynamical Decoupling for Fidelity Preservation on Large-scale Quantum Processors
Jeongwoo Jae, Changwon Lee, Juzar Thingna +2
Dynamical decoupling (DD) is a key technique for suppressing decoherence and preserving the performance of quantum algorithms. We introduce a measurement-based DD (MDD) protocol th…
quant-ph2025
Scalable Neural Decoders for Practical Real-Time Quantum Error Correction
Changwon Lee, Tak Hur, Daniel K. Park
Real-time, scalable, and accurate decoding is a critical component for realizing a fault-tolerant quantum computer. While Transformer-based neural decoders such as \textit{AlphaQub…