Coherent Microwave Control of Optically Addressable Donor Qubits in ZnO

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 […]


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

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

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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Do Time Series Foundation Model Benchmarks Hide Regime-Dependent Failures? Evidence from Traffic Speed Forecasting

Kavli Affiliate: Wei Gao| Summary:Standard benchmarks evaluate time series foundation models (TSFMs) using aggregate metrics, but these can mask severe failures in critical operating regimes. We introduce regime-stratified evaluation and apply it to three TSFMs on two standard traffic speed benchmarks. Traffic exhibits abrupt regime switching between free-flow and congested states, producing bimodal speed distributions […]


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SpecGen: Accelerating Agentic Kernel Optimization with Speculative Generation

Kavli Affiliate: Wei Gao| Summary:Agentic kernel optimization automates manual GPU kernel tuning via iterative generation, validation, and profiling with reasoning LLMs, casting the optimization task as feedback-guided search. However, our workload characterization reveals three system-level inefficiencies that limit search efficiency: (1) long generation latency due to LLM reasoning, (2) insufficient profiling feedback, and (3) underutilized […]


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Characterization of ultrathin nickel films deposited by thermal laser evaporation

Kavli Affiliate: Austin Minnich | Summary:Thermal laser evaporation is a physical vapor deposition technique of increasing interest because of its ability to evaporate essentially any solid element, even the most refractory such as W. However, many films deposited by this method, especially non-epitaxial films, remain to be characterized; further, key system components such as the […]


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Beyond Accuracy: Measuring Bias Acknowledgment in Chain-of-Thought Reasoning for Responsible AI Evaluation

Kavli Affiliate: Wei Gao| Summary:Reasoning models are increasingly used in settings where the final answer is not the only object of review: educational tools may show students intermediate steps, decision-support systems may require human oversight, and audit workflows may inspect traces for misleading or biased input. In such settings, two responses can receive the same […]


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Data-driven surrogate models for forecasting experimentally measured fluid flows

Kavli Affiliate: Morteza Gharib| Summary:Data-driven modeling shows significant promise for faster-than-real-time forecasting of fluid flows. For real-world engineering applications (e.g., flow control), models must contend with limited, imperfect, and incomplete experimental measurements. In this work, we present an analysis of data-driven surrogate models trained to forecast the time-evolution of experimentally measured cylinder wakes in the […]


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Data-driven surrogate models for forecasting experimentally measured fluid flows

Kavli Affiliate: Morteza Gharib| Summary:Data-driven modeling shows significant promise for faster-than-real-time forecasting of fluid flows. For real-world engineering applications (e.g., flow control), models must contend with limited, imperfect, and incomplete experimental measurements. In this work, we present an analysis of data-driven surrogate models trained to forecast the time-evolution of experimentally measured cylinder wakes in the […]


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Exploring Exoplanets with Interferometry

Kavli Affiliate: Dimitri Mawet| Summary:(Extract from the Executive Summary) Humanity stands at the threshold of answering one of its most profound questions: Does life exist beyond Earth? Ongoing and upcoming space missions, together with powerful ground-based instruments, have prepared the way for a transformational next step – the detailed characterization of Earth analogs orbiting Sun-like […]


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