Efficient Conversion of Optical to Mechanical States Close to the Single-Quantum Level

Posted by klaurent Delft

Kavli Affiliate: Simon Groblacher | Summary:Coherent interfaces between optical photons and mechanical excitations provide a promising route towards phonon-state engineering and hybrid quantum information processing. Cavity optomechanical systems enable such interfaces via optomechanically induced transparency (OMIT), allowing coherent mapping between traveling optical fields and localized mechanical modes. However, previous implementations of OMIT conversion protocols were […]


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Learning CNN Filters via Generalized Stein’s Method

Posted by klaurent Peking

Kavli Affiliate: Feng Long| Summary: Convolutional Neural Networks (CNNs) have undoubtedly revolutionized image data analysis and the field of computer vision. As the cornerstone of CNNs, the convolution operation enables the networks to extract abstract features and uncover hidden relationships in the image data. This paper considers the problem of estimating convolution filters from a […]


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Scalable Bayesian Optimization of Composite Functions for Image-Based Inverse Problems in Materials Characterization

Posted by klaurent Cornell

Kavli Affiliate: David Muller | Summary:Estimating physical parameters from scientific images is a common inverse problem in materials characterization that often relies on expensive physics-based simulations. In electron microscopy, specimen thickness and crystal mistilt are critical parameters that govern how electrons scatter through the sample, and therefore the accuracy of any atomic-scale structure recovered from […]


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Resolving unconventional gap structure in kagome superconductors with hybrid microwave circuits

Posted by klaurent Cornell

Kavli Affiliate: Debanjan Chowdhury | Summary:Unconventional superconductivity is a hallmark of exotic quantum matter, where determining the pairing symmetry is essential for uncovering its microscopic origin. Kagome superconductors provide a fertile landscape for emergent phenomena arising from strong electronic correlations and nontrivial band topology, yet their superconducting pairing symmetry remains elusive. The superconducting gap structure […]


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Private Computation Space: Experience with Trusted Multi-Cluster Federated Learning for Agriculture

Posted by klaurent Cornell

Kavli Affiliate: Abraham Stroock | Summary:Artificial Intelligence has shown to help improve agricultural practices, yet adoption remains limited: 69% of U.S. farmers have privacy concerns with sharing their data, and these concerns must be addressed before adoption is widespread. While Federated Learning has been demonstrated to protect privacy at scale for other sectors, deploying a […]


Continue.. Private Computation Space: Experience with Trusted Multi-Cluster Federated Learning for Agriculture