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quant-ph2026

Spectral Minimax Direct Fidelity Estimation for Generic Target States

Hyunho Cha, Jungwoo Lee

Direct fidelity estimation benefits from tailoring measurements to a fixed target, but the operator-aware shadow importance sampling (OASIS) method optimizes an outcome-wise linear…

quant-ph2026

Toward the Goldilocks blind compression of quantum states

Hyunho Cha, Chae-Yeun Park, Jungwoo Lee

Quantum autoencoders (QAEs) are learning architectures that compress quantum data into a low-dimensional latent state while preserving the information needed for reconstruction. We…

quant-ph2026

Verifying random matrix product states with autoregressive local measurements

Hyunho Cha, Subin Kim, Jungwoo Lee

Matrix product states (MPS) are a central language for one-dimensional quantum matter and a practical target for near-term quantum simulators and variational algorithms. Yet, while…

quant-ph2026

Non-existence of stabilizer absolutely maximally entangled states across infinitely many configurations

Hyunho Cha

We prove a general reduction theorem for stabilizer absolutely maximally entangled states in composite local dimension. If a stabilizer state exists and $D=\pro…

quant-ph2026

QFlowNet: Fast, Diverse, and Efficient Unitary Synthesis with Generative Flow Networks

Inhoe Koo, Hyunho Cha, Jungwoo Lee

Unitary Synthesis, the decomposition of a unitary matrix into a sequence of quantum gates, is a fundamental challenge in quantum compilation. Prevailing reinforcement learning (RL)…

quant-ph2026

A dimension-independent strict submultiplicativity for the transposition map in diamond norm

Hyunho Cha

We prove that there exists an absolute constant such that for every finite dimension and every quantum channel on , $\left\|Θ\circ(\mathrm{i…