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arXiv Machine Learning By Vasilisa Usova, Phila Rembold, Ian Yang, Marco Rossignolo, Simone Montangero, Samuele Tosatto, Gerhard Kirchmair

Adaptive Reconstruction of Bosonic Quantum States

Read the original on arXiv Machine Learning →

arXiv:2608. 02049v1 Announce Type: cross Abstract: Bosonic quantum systems provide a hardware-efficient platform for quantum information processing but remain challenging to characterise due to their large Hilbert space and the high measurement cost of state tomography.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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