Bulletin of the American Physical Society
85th Annual Meeting of the APS Southeastern Section
Volume 63, Number 19
Thursday–Saturday, November 8–10, 2018; Holiday Inn at World’s Fair Park, Knoxville, Tennessee
Session F02: Machine Learning and Quantum Computing in Physics |
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Chair: Thomas Papenbrock, University of Tennessee, Knoxville Room: Holiday Inn Knoxville Downtown Cumberland |
Friday, November 9, 2018 11:00AM - 11:30AM |
F02.00001: How Can Machine Learning Help Your Research Forward? Invited Speaker: Wouter Deconinck Machine learning is a buzzwords that conjures up visions of programming gurus and data magicians solving problems with little effort while others balk at the black-box nature and lack of first principles understanding. In this talk I hope to introduce some ways in which you can start to use powerful machine learning algorithms to solve certain classes of problems in ways that may be more generic than traditional approaches. I will use examples from a range of fields to demonstrate the power of machine learning, even though those field with access to large data sets have lead the charge. I will highlight differences between machine learning in physics and other data sciences. Finally, I will point out why a solid understanding of the underlying physical principles is a necessity to use machine learning in research with any success. |
Friday, November 9, 2018 11:30AM - 12:00PM |
F02.00002: Machine learning in condensed matter physics: recent advances and opportunities Invited Speaker: Ying Wai Li With the rapid advances in the machine learning technology in recent years, we are witnessing exploding interests in its applications to solve physics problems. Pioneering work has proven machine learning a promising tool to tackle many frontier research problems in condensed matter physics, such as the identification of phases of matter, solving quantum many-body problems, accelerating materials-by-design, and decreasing computational complexity for simulations, to name a few. Machine learning opens up new research avenues that bridge across theory, experiments and computer simulations, and it enables scientific discoveries that were impossible before. In this talk, I will give a brief overview of the current state-of-the-art, as well as opportunities, in this exciting, emerging area. |
Friday, November 9, 2018 12:00PM - 12:30PM |
F02.00003: Applications of Quantum Computers to Simulations in Nuclear Physics and Quantum Field Theory. Invited Speaker: Pavel Lougovski Simulations of complex many-body quantum phenomena present a formidable computational challenge. Quantum computing holds promise to drastically improve our simulations capabilities for many-body systems across all scientific domains. We discuss recent progress and challenges in quantum simulations of light nuclei (the deuteron 2H, the triton 3H, 3He, and the alpha particle 4He ) and a prototypical quantum field theory---the Schwinger model---on a multitude of quantum hardware ranging from superconducting circuits and trapped ions to photonics. Our results illustrate the potential of quantum computers to augment classical computations in bridging the scales from quarks to nuclei. |
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