Quantum gas microscopy of Kardar-Parisi-Zhang superdiffusion

The Kardar-Parisi-Zhang (KPZ) universality class describes the coarse-grained behavior of a wealth of classical stochastic models. Surprisingly, it was recently conjectured to also describe spin transport in the one-dimensional quantum Heisenberg model. We test this conjecture by experimentally probing transport in a cold-atom quantum simulator via the relaxation of domain walls in spin chains of up to 50 spins. We find that domain-wall relaxation is indeed governed by the KPZ dynamical exponent $z = 3/2$, and that the occurrence of KPZ scaling requires both integrability and a non-abelian SU(2) symmetry. Finally, we leverage the single-spin-sensitive detection enabled by the quantum-gas microscope to measure a novel observable based on spin-transport statistics, which yields a clear signature of the non-linearity that is a hallmark of KPZ universality.Comment: 8 pages, 5 figures + 13 pages Supplementary Informatio

Topics in Magnetohydrodynamics

To understand plasma physics intuitively one need to master the MHD behaviors. As sciences advance, gap between published textbooks and cutting-edge researches gradually develops. Connection from textbook knowledge to up-to-dated research results can often be tough. Review articles can help. This book contains eight topical review papers on MHD. For magnetically confined fusion one can find toroidal MHD theory for tokamaks, magnetic relaxation process in spheromaks, and the formation and stability of field-reversed configuration. In space plasma physics one can get solar spicules and X-ray jets physics, as well as general sub-fluid theory. For numerical methods one can find the implicit numerical methods for resistive MHD and the boundary control formalism. For low temperature plasma physics one can read theory for Newtonian and non-Newtonian fluids etc

Gradient variation: A key to enhancing photographs across illumination

Ph.DDOCTOR OF PHILOSOPH

Reconstruction and analysis of dynamic shapes

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 122-141).Motion capture has revolutionized entertainment and influenced fields as diverse as the arts, sports, and medicine. This is despite the limitation that it tracks only a small set of surface points. On the other hand, 3D scanning techniques digitize complete surfaces of static objects, but are not applicable to moving shapes. I present methods that overcome both limitations, and can obtain the moving geometry of dynamic shapes (such as people and clothes in motion) and analyze it in order to advance computer animation. Further understanding of dynamic shapes will enable various industries to enhance virtual characters, advance robot locomotion, improve sports performance, and aid in medical rehabilitation, thus directly affecting our daily lives. My methods efficiently recover much of the expressiveness of dynamic shapes from the silhouettes alone. Furthermore, the reconstruction quality is greatly improved by including surface orientations (normals). In order to make reconstruction more practical, I strive to capture dynamic shapes in their natural environment, which I do by using hybrid inertial and acoustic sensors. After capture, the reconstructed dynamic shapes are analyzed in order to enhance their utility. My algorithms then allow animators to generate novel motions, such as transferring facial performances from one actor onto another using multi-linear models. The presented research provides some of the first and most accurate reconstructions of complex moving surfaces, and is among the few approaches that establish a relationship between different dynamic shapes.by Daniel Vlasic.Ph.D