Terahertz electrodynamics in a zero-field Wigner crystal

Kavli Affiliate: Feng Wang | First 5 Authors: Su-Di Chen, Su-Di Chen, , , | Summary: In clean two-dimensional (2D) systems, electrons are expected to self-organize into a regular lattice, a Wigner crystal, when their mutual Coulomb repulsion overwhelms kinetic energy. Understanding the Wigner crystal at zero magnetic field is a long-sought goal in physics, […]


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QuantAgent: Price-Driven Multi-Agent LLMs for High-Frequency Trading

Kavli Affiliate: Xiang Zhang | First 5 Authors: Fei Xiong, Fei Xiong, , , | Summary: Recent advances in Large Language Models (LLMs) have demonstrated impressive capabilities in financial reasoning and market understanding. Multi-agent LLM frameworks such as TradingAgent and FINMEM augment these models to long-horizon investment tasks, leveraging fundamental and sentiment-based inputs for strategic […]


Continue.. QuantAgent: Price-Driven Multi-Agent LLMs for High-Frequency Trading

QuantAgent: Price-Driven Multi-Agent LLMs for High-Frequency Trading

Kavli Affiliate: Xiang Zhang | First 5 Authors: Fei Xiong, Fei Xiong, , , | Summary: Recent advances in Large Language Models (LLMs) have demonstrated impressive capabilities in financial reasoning and market understanding. Multi-agent LLM frameworks such as TradingAgent and FINMEM augment these models to long-horizon investment tasks, leveraging fundamental and sentiment-based inputs for strategic […]


Continue.. QuantAgent: Price-Driven Multi-Agent LLMs for High-Frequency Trading

Accelerating 3D Photoacoustic Computed Tomography with End-to-End Physics-Aware Neural Operators

Kavli Affiliate: Lihong V. Wang | First 5 Authors: Jiayun Wang, Jiayun Wang, , , | Summary: Photoacoustic computed tomography (PACT) combines optical contrast with ultrasonic resolution, achieving deep-tissue imaging beyond the optical diffusion limit. While three-dimensional PACT systems enable high-resolution volumetric imaging for applications spanning transcranial to breast imaging, current implementations require dense transducer […]


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Cepstral Strain Mapping for Small Pixel-Count Detectors

Kavli Affiliate: David A. Muller | First 5 Authors: Harikrishnan KP, Harikrishnan KP, , , | Summary: With the decreasing sizes of integrated-circuit components, the semiconductor industry is in growing need of high-throughput strain mapping techniques that offer high precision and spatial resolution, with desired industry goals of 0.01-0.1% and 1 nm respectively. As the […]


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EVDI++: Event-based Video Deblurring and Interpolation via Self-Supervised Learning

Kavli Affiliate: Xiang Zhang | First 5 Authors: Chi Zhang, Chi Zhang, , , | Summary: Frame-based cameras with extended exposure times often produce perceptible visual blurring and information loss between frames, significantly degrading video quality. To address this challenge, we introduce EVDI++, a unified self-supervised framework for Event-based Video Deblurring and Interpolation that leverages […]


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Confinement, deconfinement, and bound states in the spin-$1$ and spin-$3/2$ generalizations of the Majumdar–Ghosh chain

Kavli Affiliate: Natalia Chepiga | First 5 Authors: Aman Sharma, Aman Sharma, , , | Summary: We investigate the nature of low-energy excitations in a spin chain with antiferrmomagnetic nearest-neighbor $J_1$, next-nearest-neighbor $J_2$, and three-site $J_3$ interactions using the time-dependent density matrix renormalization group and the single mode approximation techniques. In the absence of the […]


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Coefficients-Preserving Sampling for Reinforcement Learning with Flow Matching

Kavli Affiliate: Feng Wang | First 5 Authors: Feng Wang, Feng Wang, , , | Summary: Reinforcement Learning (RL) has recently emerged as a powerful technique for improving image and video generation in Diffusion and Flow Matching models, specifically for enhancing output quality and alignment with prompts. A critical step for applying online RL methods […]


Continue.. Coefficients-Preserving Sampling for Reinforcement Learning with Flow Matching

Coefficients-Preserving Sampling for Reinforcement Learning with Flow Matching

Kavli Affiliate: Feng Wang | First 5 Authors: Feng Wang, Feng Wang, , , | Summary: Reinforcement Learning (RL) has recently emerged as a powerful technique for improving image and video generation in Diffusion and Flow Matching models, specifically for enhancing output quality and alignment with prompts. A critical step for applying online RL methods […]


Continue.. Coefficients-Preserving Sampling for Reinforcement Learning with Flow Matching