Coherent Microwave Control of Optically Addressable Donor Qubits in ZnO

Posted by klaurent Caltech

Kavli Affiliate: Joseph Falson | Summary:Optically addressable shallow donors in ZnO combine efficient spin-selective optical transitions with the potential for long spin coherence in an isotopically purifiable host lattice, making them an attractive platform for spin-photon quantum technologies. A key missing capability, however, has been coherent control beyond the small-angle rotations accessible with ultrafast optical […]


Continue.. Coherent Microwave Control of Optically Addressable Donor Qubits in ZnO

Spotlight: Synergizing Seed Exploration and Spot GPUs for DiT RL Post-Training

Posted by klaurent Caltech

Kavli Affiliate: Wei Gao| Summary:Reinforcement learning (RL) post-training of Diffusion Transformers (DiTs) is prohibitively expensive, requiring thousands of high-end GPUs. Existing works explore two directions to reduce cost: seed exploration improves training convergence by selecting high-contrast samples, yet adds compute to the critical path; spot GPUs offer 69–77% lower cost, yet sit idle during training […]


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Efficient Image Registration for Ultrasound Localization Microscopy by Obtaining Gradients via Integration Across Iterations

Posted by klaurent UCAS

Kavli Affiliate: Biao Huang | Summary:Tissue motion correction through image registration is essential for ultrasound localization microscopy (ULM). Parametric image registration is commonly formulated as an optimization problem where motion parameters are iteratively updated to maximize image similarity, and used optimization algorithms typically rely on gradient information, the explicit evaluation of which can become computationally […]


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Piezoelectric resonators in thin-film barium titanate from room temperature to millikelvin

Posted by klaurent Caltech

Kavli Affiliate: Mohammad Mirhosseini | Summary:Ferroelectric materials, with their strong nonlinearities, underpin key technologies across radio-frequency (RF) signal processing, optical communications, and emerging quantum systems. Barium titanate (BTO) is a notable example, combining strong piezoelectric and electro-optic responses. While bulk BTO has been studied for decades, the piezoelectric properties of its recently available thin films, […]


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Reconstructing Galactic Gravitational Potentials from Stellar Kinematics with Physics-Informed Neural Networks

Posted by klaurent MIT

Kavli Affiliate: Lina Necib | Summary:The gravitational potential of a galaxy encodes its mass distribution, formation history, and dark matter halo structure. Accurate potential models are therefore critical for interpreting stellar kinematics, orbital dynamics, and the influence of satellite systems like the Large Magellanic Cloud. Analytic potential models offer interpretability and efficiency but struggle to […]


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The Lumina Project: Intergalactic Clumping and Recombination Sinks

Posted by klaurent MIT

Kavli Affiliate: Mark Vogelsberger | Summary:Recombinations during the Epoch of Reionization are intrinsically inhomogeneous, with different regions of the intergalactic medium contributing unevenly depending on their density, temperature, ionization state, and spatial patchiness. We combine the high- and medium-resolution 95.5 cMpc Thesan-1 andh Thesan-2 runs with the significantly larger 500 cMpc Lumina simulation to measure […]


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RankGraph-2: Lifecycle Co-Design for Billion-Node Graph Learning in Recommendation

Posted by klaurent Peking

Kavli Affiliate: Xian Chen| Summary: Graph-based retrieval at billion-node scale requires jointly solving three tightly coupled problems — graph construction, representation learning, and real-time serving — yet existing work addresses each in isolation. We present RankGraph-2, a framework deployed at Meta that co-designs all three lifecycle stages for similarity-based retrieval (U2U2I and U2I2I), where each […]


Continue.. RankGraph-2: Lifecycle Co-Design for Billion-Node Graph Learning in Recommendation

RankGraph-2: Lifecycle Co-Design for Billion-Node Graph Learning in Recommendation

Posted by klaurent Peking

Kavli Affiliate: Xian Chen| Summary: Graph-based retrieval at billion-node scale requires jointly solving three tightly coupled problems — graph construction, representation learning, and real-time serving — yet existing work addresses each in isolation. We present RankGraph-2, a framework deployed at Meta that co-designs all three lifecycle stages for similarity-based retrieval (U2U2I and U2I2I), where each […]


Continue.. RankGraph-2: Lifecycle Co-Design for Billion-Node Graph Learning in Recommendation

RankGraph-2: Lifecycle Co-Design for Billion-Node Graph Learning in Recommendation

Posted by klaurent Peking

Kavli Affiliate: Xian Chen| Summary: Graph-based retrieval at billion-node scale requires jointly solving three tightly coupled problems — graph construction, representation learning, and real-time serving — yet existing work addresses each in isolation. We present RankGraph-2, a framework deployed at Meta that co-designs all three lifecycle stages for similarity-based retrieval (U2U2I and U2I2I), where each […]


Continue.. RankGraph-2: Lifecycle Co-Design for Billion-Node Graph Learning in Recommendation

RankGraph-2: Lifecycle Co-Design for Billion-Node Graph Learning in Recommendation

Posted by klaurent Peking

Kavli Affiliate: Xian Chen| Summary: Graph-based retrieval at billion-node scale requires jointly solving three tightly coupled problems — graph construction, representation learning, and real-time serving — yet existing work addresses each in isolation. We present RankGraph-2, a framework deployed at Meta that co-designs all three lifecycle stages for similarity-based retrieval (U2U2I and U2I2I), where each […]


Continue.. RankGraph-2: Lifecycle Co-Design for Billion-Node Graph Learning in Recommendation