Spin transport between polarized Fermi gases near the ferromagnetic phase transition

Kavli Affiliate: Mamoru Matsuo | First 5 Authors: Tingyu Zhang, Daigo Oue, Hiroyuki Tajima, Mamoru Matsuo, Haozhao Liang | Summary: We theoretically study the spin current between two polarized Fermi gases with repulsive interactions near the itinerant ferromagnetic phase transition. We consider a two-terminal model where the left reservoir is fixed to be fully polarized […]


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One at A Time: Multi-step Volumetric Probability Distribution Diffusion for Depth Estimation

Kavli Affiliate: Zheng Zhu | First 5 Authors: Bohan Li, Jingxin Dong, Yunnan Wang, Jinming Liu, Lianying Yin | Summary: Recent works have explored the fundamental role of depth estimation in multi-view stereo (MVS) and semantic scene completion (SSC). They generally construct 3D cost volumes to explore geometric correspondence in depth, and estimate such volumes […]


Continue.. One at A Time: Multi-step Volumetric Probability Distribution Diffusion for Depth Estimation

One at a Time: Progressive Multi-step Volumetric Probability Learning for Reliable 3D Scene Perception

Kavli Affiliate: Zheng Zhu | First 5 Authors: Bohan Li, Yasheng Sun, Jingxin Dong, Zheng Zhu, Jinming Liu | Summary: Numerous studies have investigated the pivotal role of reliable 3D volume representation in scene perception tasks, such as multi-view stereo (MVS) and semantic scene completion (SSC). They typically construct 3D probability volumes directly with geometric […]


Continue.. One at a Time: Progressive Multi-step Volumetric Probability Learning for Reliable 3D Scene Perception

One at a Time: Progressive Multi-step Volumetric Probability Learning for Reliable 3D Scene Perception

Kavli Affiliate: Zheng Zhu | First 5 Authors: Bohan Li, Yasheng Sun, Jingxin Dong, Zheng Zhu, Jinming Liu | Summary: Numerous studies have investigated the pivotal role of reliable 3D volume representation in scene perception tasks, such as multi-view stereo (MVS) and semantic scene completion (SSC). They typically construct 3D probability volumes directly with geometric […]


Continue.. One at a Time: Progressive Multi-step Volumetric Probability Learning for Reliable 3D Scene Perception

Hubbard Model on Triangular Lattice: Role of Charge Fluctuations

Kavli Affiliate: Zheng Zhu | First 5 Authors: Ji-Si Xu, Zheng Zhu, Kai Wu, Zheng-Yu Weng, | Summary: A chiral spin liquid (CSL) phase has been recently reported in the Hubbard model on a triangular lattice at half-filling. It emerges in an intermediate coupling regime, which is sandwiched between a $120^circ$ antiferromagnetic (AFM) phase and […]


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WiCo: Win-win Cooperation of Bottom-up and Top-down Referring Image Segmentation

Kavli Affiliate: Cheng Peng | First 5 Authors: Zesen Cheng, Peng Jin, Hao Li, Kehan Li, Siheng Li | Summary: The top-down and bottom-up methods are two mainstreams of referring segmentation, while both methods have their own intrinsic weaknesses. Top-down methods are chiefly disturbed by Polar Negative (PN) errors owing to the lack of fine-grained […]


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Emergent conformal boundaries from finite-entanglement scaling in matrix product states

Kavli Affiliate: Long Zhang | First 5 Authors: Rui-Zhen Huang, Long Zhang, Andreas M. Läuchli, Jutho Haegeman, Frank Verstraete | Summary: The use of finite entanglement scaling with matrix product states (MPS) has become a crucial tool for studying 1+1d critical lattice theories, especially those with emergent conformal symmetry. We argue that finite entanglement introduces […]


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Machine learning enabled experimental design and parameter estimation for ultrafast spin dynamics

Kavli Affiliate: Cheng Peng | First 5 Authors: Zhantao Chen, Cheng Peng, Alexander N. Petsch, Sathya R. Chitturi, Alana Okullo | Summary: Advanced experimental measurements are crucial for driving theoretical developments and unveiling novel phenomena in condensed matter and material physics, which often suffer from the scarcity of facility resources and increasing complexities. To address […]


Continue.. Machine learning enabled experimental design and parameter estimation for ultrafast spin dynamics