Overview
Strongly correlate systems, specifically High Temperature Superconductivity, Quantum Criticality, Topological phases
Research Focus
My research interests lie in the theoretical study of the collective phenomena condensed matter systems exhibit, and in understanding how such phenomena emerges from microscopic physics. Especially, I have been interested in the physics of strongly correlated systems: systems consisting of many strongly interacting degrees of freedom. Strong correlations can lead to a surprisingly rich diversity of novel phenomena that are highly non-trivial from a single particle perspective. Over the last few decades, new experimental discoveries, through the development of new experimental probes and the fabrication of ever more exotic materials and devices, have been raising unexpected and conceptually deep questions. The possibility of obtaining a non-trivial understanding through a close interaction and synergy with experimental colleagues make the theoretical study of this field exciting and rich.
Among various topics that fall under the above category, I am currently focusing on 1) Fe and Cu based High Temperature Superconductivity, 2) Topological phases, 3) Application of neural network based machine learning.
These are complex and challenging problems which require a variety of theoretical approaches. One system could display more than one of the above intriguing phenomena. My group will pursue much needed understanding of major open problems through simple but relevant model problems amenable to solutions using basic tools, as well as through problems that require sophisticated analytical and numerical tools.
Graduate Students
Yiqing Zhou, Yanjun Liu, Hyejin Kim
Postdocs
Yi Zhang and Sam Lederer
Awards and Honors
- Excellence in Teaching Award, University of Illinois at Urbana-Champaign, 2005
- John Bardeen Award, University of Illinois at Urbana- Champaign
- NSF CAREER Award, 2010-2014
- DOE CAREER Award, 2012-2017
Professional Experience
- Postdoctoral Scholar, Stanford University, 2005-2008.
- Assistant Professor, Physics, Cornell University, 2008-2014.
- Associate Professor, Physics, Cornell University, 2014-2018.
- Professor, Physics, Cornell University, 2019-present.
Publications
Y. Zhang and E.-A. Kim, “Quantum Loop Topography for Machine Learning”, Phys. Rev. Lett. 118 (2017) 216401 (Featured in Physics Viewpoint).
Y.-T. Hsu, A. Vaezi, M.H. Fischer, E.-A. Kim, “Topological Superconductivity in Monolayer Transitionmetal Dichalcogenides”, Nat. Comm. 8 (2017) 14985.
A. R. Mellnik, J. S. Lee, A. Richardella, J. L. Grab, P. J. Mintun, M. H. Fischer, A. Vaezi, A. Manchon, E.-A. Kim, N. Samarth, and D. C. Ralph, “Spin Transfer Torque Generated by the Topological Insulator Bi2Se3,” Nature 511 (2014) 449.
M. J. Lawler, K. Fujita, J. Lee, A. R. Schmidt, Y. Kohsaka, C. K. Kim, H. Eisaki, S. Uchida, J. C. Davis, J. P. Sethna, E.-A. Kim, “Intra-unit-cell electronic nematicity of the high-Tc copper-oxide pseudogap states,” Nature 466 (2010) 347.
E.-A. Kim and A. Castro-Neto, “Graphene as an electronic membrane,” Euro. Phys. Lett. 84 (2008), 57007.
In the news
- Physicists detect elusive ‘Bragg glass’ phase with machine learning tool
- Physicists realize fractionalization without a magnetic field
- Cornell, Google first to detect key to quantum computing future
- Physicists take step toward fault-tolerant quantum computing
- Physicist identifies how electron crystals melt
- Harnessing machine learning to analyze quantum material
- Panelists explore ‘Science of the Very, Very Small’
- Six A&S professors named 2022 Simons fellows
- Science of the very, very small featured in next Arts Unplugged
- New superconducting interfaces for quantum technologies
- Grant funds machine learning discovery in quantum physics
- Machine learning tool sorts the nuances of quantum data
- $2M in New Frontier Grants boost high-impact A&S research
- Detecting Hidden Order in Quantum Materials
- Electrons obey social distancing in ‘strange’ metals
- New awards to enable ‘quantum’ leaps in research
- Understanding Quantum Matter Data
- Machine learning unlocks mysteries of quantum physics
- Quantum computing explored in Fall Hans Bethe Lecture
- Keck-funded group proposes new topological superconductor
- The social life of electrons
- Group works toward devising next-gen superconductor