arXiv:2610. 02068v1 Announce Type: cross Abstract: How complex can the responses of a quantum device become as it runs longer with a fixed internal memory?
Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.
arXiv:2607. 02444v1 Announce Type: cross Abstract: We study stabilizer state testing and learning with limited coherent quantum memory.
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.
The paper investigates quantum reservoir computing using highly scrambling quantum systems modeled by high‑order unitary designs. It shows that in noiseless settings, measurement readouts become exponentially concentrated as the reservoir size grows, but this concentration does not worsen with repeated iterations, while memory of early inputs decays exponentially with both reservoir size and iterations. In noisy environments, memory also decays exponentially over time for local noisy channels, and the study introduces new proof techniques for bounding concentration in temporal quantum models. Numerical results indicate that even physical reservoirs, such as an Ising model in a quantum‑chaotic phase, can exhibit exponential concentration, whereas reservoirs in a many‑body localized phase or at the edge of chaos do not.
arXiv:2605. 12713v3 Announce Type: replace-cross Abstract: In the field of quantum reservoir computing (QRC), many different computational models and architectures have been proposed.
arXiv:2608. 19306v1 Announce Type: cross Abstract: Given a set of input states, we consider the task of predicting the expectation value of a Pauli observable at the output of an unknown quantum evolution, using only a limited number of measurements.
arXiv:2606. 19947v1 Announce Type: cross Abstract: Reliable quantum control in the presence of decoherence requires policies that combat the effect of environmental noise on the controlled dynamics.