| 年份 | 2019 |
| 學科 | 物理與天文學 PHYSICS AND ASTRONOMY |
| 國家/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 英特爾 Intel ISEF
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英特爾國際科學與工程大獎賽,簡稱 "ISEF",由美國 Society for Science and the Public(科學和公共服務協會)主辦,英特爾公司冠名贊助,是全球規模最大、等級最高的中學生的科研科創賽事。ISEF 的學術活動學科包括了所有數學、自然科學、工程的全部領域和部分社會科學。ISEF 素有全球青少年科學學術活動的“世界杯”之美譽,旨在鼓勵學生團隊協作,開拓創新,長期專一深入地研究自己感興趣的課題。
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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.

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