Demonstration of robust and efficient quantum property learning with shallow shadows
Extracting information efficiently from quantum systems is a major component of quantum
information processing tasks. Randomized measurements, or classical shadows, enable …
information processing tasks. Randomized measurements, or classical shadows, enable …
A Maximum Entropy Principle in Deep Thermalization and in Hilbert-Space Ergodicity
We report universal statistical properties displayed by ensembles of pure states that
naturally emerge in quantum many-body systems. Specifically, two classes of state …
naturally emerge in quantum many-body systems. Specifically, two classes of state …
Scalable quantum state tomography with locally purified density operators and local measurements
Understanding quantum systems holds significant importance for assessing the
performance of quantum hardware and software, as well as exploring quantum control and …
performance of quantum hardware and software, as well as exploring quantum control and …
Holographic Classical Shadow Tomography
We introduce" holographic shadows", a new class of randomized measurement schemes for
classical shadow tomography that achieves the optimal scaling of sample complexity for …
classical shadow tomography that achieves the optimal scaling of sample complexity for …
Embedded Complexity and Quantum Circuit Volume
Z Du, ZW Liu, X Ma - arXiv preprint arXiv:2408.16602, 2024 - arxiv.org
Quantum circuit complexity is a pivotal concept in quantum information, quantum many-body
physics, and high-energy physics. While extensively studied for closed systems, the …
physics, and high-energy physics. While extensively studied for closed systems, the …
Bootstrapping Classical Shadows for Neural Quantum State Tomography
W Kokaew, B Kulchytskyy, S Matsuura… - arXiv preprint arXiv …, 2024 - arxiv.org
We investigate the advantages of using autoregressive neural quantum states as ansatze for
classical shadow tomography to improve its predictive power. We introduce a novel …
classical shadow tomography to improve its predictive power. We introduce a novel …