We determine the optimal sample complexity of low-rank quantum state tomography when each measurement may act jointly on at most $t$ samples. For sufficiently small $\varepsilon$, estimating an unknow...
arXiv:2609.05718v1 Announce Type: cross
Abstract: We study state tomography when each measurement acts on at most $k$ fresh copies and no quantum memory is retained between blocks. We prove a lower b...
By Ufuk Keskin, Jason Luo, Mahbod Majid, Matthew Radzihovsky
arXiv:2607. 02444v1 Announce Type: cross Abstract: We study stabilizer state testing and learning with limited coherent quantum memory.
By Srinivasan Arunachalam, Louis Schatzki
arXiv:2510.06848v3 Announce Type: replace-cross
Abstract: Bell sampling is a simple yet powerful tool based on measuring two copies of a quantum state in the Bell basis, and has found applications in...
By Jonathan Allcock, Joao F. Doriguello, G\'abor Ivanyos, Miklos Santha
We study stabilizer state testing and learning with limited coherent quantum memory. Here an algorithm sequentially receives copies of an unknown $n$-qubit state, but may keep only $k$ qubits of coherent quantum memory between measurements.
arXiv:2606. 12211v1 Announce Type: cross Abstract: A central principle in quantum machine learning is that an ansatz should be expressive enough to represent the quantum data of interest.
By Jeongho Bang, Kyoungho Cho, Jeongwoo Jae