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From the 2 of 9 linked papers with an AI index.

most citedEntanglement, loss, and quantumness: When balanced beam splitters are best

2 citations · 3 across the 6 of their papers we have counts for

collaborators

9 papers

quant-ph2026

Spin coherence scale: operator-ordering sensitivity beyond the Heisenberg-Weyl group

Aaron Z. Goldberg, Andre J. Rodrigues, Y. Batuhan Yilmaz +2

The paper defines a spin coherence scale to quantify quantum coherence in spin systems, extending the quadrature coherence scale to SU(2)-invariant settings and linking it to noncl…

quant-ph20262 cited

Entanglement, loss, and quantumness: When balanced beam splitters are best

Noah Lupu-Gladstein, Anaelle Hertz, Khabat Heshami +1

The paper proves that beam splitters with equal transmission and reflection (balanced) generate the maximum entanglement for states interfered with vacuum under common entanglement…

cond-mat.mes-hall20261 cited

Magnetometry with Broadband Microwave Fields in Nitrogen-Vacancy Centers in Diamond

Arezoo Afshar, Andrew Proppe, Noah Lupu-Gladstein +3

Nitrogen-vacancy (NV) centers in diamond are optically addressable and versatile light-matter interfaces with practical application in magnetic field sensing, offering the ability…

quant-ph2026

Vector Magnetometry with Broadband Microwave Fields in Nitrogen-Vacancy Centers in Diamond

Tom R. Rieckmann, Arezoo Afshar, Aaron Z. Goldberg +3

We present a novel method for full vector magnetometry using nitrogen-vacancy (NV) centers. In contrast to conventional optically detected magnetic resonance techniques, our method…

quant-ph2026

Recurrent Quantum Feature Maps for Reservoir Computing

Utkarsh Singh, Aaron Z. Goldberg, Christoph Simon +1

Reservoir computing promises a fast method for handling large amounts of temporal data. This hinges on constructing a good reservoir--a dynamical system capable of transforming inp…

quant-ph2026

A Resource Efficient Quantum Kernel

Utkarsh Singh, Jean-Frédéric Laprade, Aaron Z. Goldberg +1

Quantum processors may enhance machine learning by mapping high-dimensional data onto quantum systems for processing. Conventional feature maps, for encoding data onto a quantum ci…