|学科||物理与天文学 PHYSICS AND ASTRONOMY|
|国家/州||NY，United States of America|
Disentangling Spatial Correlations from Inhomogeneous Materials with Shift-Invariant Artificial Neural Networks: A Novel Approach to Study Superconductivity
With the advent of atomic resolution imaging techniques comes the challenge of disentangling the intrinsic electronic properties of materials from their stochastic atomic-scale disorder. In the past decade, machine learning image analysis techniques, based in artificial intelligence, have rapidly evolved, while their applications in physics are just emerging. Here, I demonstrate the use of machine learning to test correlation hypotheses between spatially resolved measurements of disordered materials to overcome the limitations of standard Fourier analysis techniques. Shift-invariant artificial neural networks (SIANNs) are applied to uncover the doping-dependence of the charge density wave (CDW) structure in the cuprate superconductor (Pb,Bi)_2 (Sr,La)_2 CuO_6_+_delta(Bi-2201) imaged via scanning tunneling microscopy. In Bi-based cuprates, the electronic inhomogeneity, caused by local variations in doping, limits the precision with which the CDW wavevector can be measured. This machine learning algorithm overcomes these limitations and allows clear differentiation between commensurate and incommensurate CDW instabilities with physically distinct mechanisms. I show how the cuprate phase diagram and other enigmatic properties of superconductors, a class of materials that has important uses in electrical transmission and particle accelerators, can be studied with this new technique. More broadly, this work lays the foundation for a machine learning approach to quantify intrinsic periodic order and correlations from datasets where these trends are masked by disorder.
高中生科研 英特尔 Intel ISEF
资讯 · 课程 · 全程指导
高中生科研竞赛 英特尔 Intel ISEF 简介
英特尔国际科学与工程大奖赛，简称 "ISEF"，由美国 Society for Science and the Public（科学和公共服务协会）主办，英特尔公司冠名赞助，是全球规模最大、等级最高的中学生的科研科创赛事。ISEF 的竞赛学科包括了所有数学、自然科学、工程的全部领域和部分社会科学。ISEF 素有全球青少年科学竞赛的“世界杯”之美誉，旨在鼓励学生团队协作，开拓创新，长期专一深入地研究自己感兴趣的课题。
>>> 实用链接汇总 <<<
学科简介：物理与天文学 PHYSICS AND ASTRONOMY
Physics is the science of matter and energy and of interactions between the two. Astronomy is the study of anything in the universe beyond the Earth.
Atomic, Molecular, and Optical Physics (AMO): The study of atoms, simple molecules, electrons, light, and their interactions. Projects studying non-solid state lasers and masers also belong in this subcategory.
Astronomy and Cosmology (AST): The study of space, the universe as a whole, including its origins and evolution, the physical properties of objects in space and computational astronomy.
Biological Physics (BIP): The study of the physics of biological processes and systems.
Condensed Matter and Materials (MAT): The study of the properties of solids and liquids. Topics such as superconductivity, semi-conductors, complex fluids, and thin films are studied.
Mechanics (MEC): Classical physics and mechanics, including the macroscopic study of forces, vibrations and flows; on solid, liquid and gaseous materials. Projects studying aerodynamics or hydrodynamics also belong in this subcategory.
Nuclear and Particle Physics (NUC): The study of the physical properties of the atomic nucleus and of fundamental particles and the forces of their interaction. Projects developing particle detectors also belong in this subcategory.
Theoretical, Computational, and Quantum Physics (THE): The study of nature, phenomena and the laws of physics employing mathematical or computational methods rather than experimental processes.
Other (OTH): Studies that cannot be assigned to one of the above subcategories. If the project involves multiple subcategories, the principal subcategory should be chosen instead of Other.