19 citations · 19 across the 4 of their papers we have counts for
6 papers · 1 filter
Shadow bootstrapping: Nearly minimal-setting pure-state tomography with shallow Clifford measurements
Gyungmin Cho, Dohun Kim
We present a pure-state tomography algorithm that uses a nearly minimal number of measurement settings while achieving optimal sample complexity with nonadaptive single-copy shallo…
Quantum state learning beyond approximate unitary designs
Gyungmin Cho, Changhun Oh, Dohun Kim
Approximate unitary designs reproduce the statistics of Haar-random unitaries to a given order and accuracy. Recent constructions realize such designs with logarithmic-depth circui…
Single-copy stabilizer learning: average case and worst case
Gyungmin Cho, Dohun Kim
We study single-copy stabilizer learning, the problem of identifying a stabilizer group of dimension from an -qubit quantum state . We obtain two complementary results.…
Sample-optimal single-copy quantum state tomography with shallow-depth measurements
Gyungmin Cho, Dohun Kim
Quantum state tomography (QST) is a central task in quantum information, and its efficiency is commonly characterized by sample complexity. Although collective measurements on mult…
Shallow randomized measurement in noisy quantum devices
Gyungmin Cho, Dohun Kim
Quantum hardware is steadily improving, but near-term quantum devices remain limited by noise and circuit depth. This motivates measurement protocols that can use shallow-depth cir…
Machine learning on quantum experimental data toward solving quantum many-body problems
Gyungmin Cho, Dohun Kim
Advancements in the implementation of quantum hardware have enabled the acquisition of data that are intractable for emulation with classical computers. The integration of classica…