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Dr. Iadecolais a theoretical physicist using diverse analytical and numerical tools to study a variety of topics in quantum condensed matter. A graduate of Brown University (Sc.B., 2012), he received his Ph.D. in Physics from Boston University in 2017. He then became a JQI Theoretical Postdoctoral Fellow at the NIST-University of Maryland Joint Quantum Institute until 2019, when he joined Iowa State University as an Assistant Professor. Research in his group focuses on out-of-equilibrium quantum systems and topological phases with a view towards emerging quantum technologies. On the nonequilibrium side, he studies properties of highly-excited many-body states and the surprising phenomena they harbor that challenge deeply ingrained intuition based on quantum statistical mechanics. On the topological side, he focuses on states of matter whose properties cannot be understood within the traditional paradigm of spontaneous symmetry breaking, and which could enable the robust storage and manipulation of quantum information. In addition to thinking about new phenomena, he grapples with ways to realize them in electronic and photonic systems, or using near-term quantum platforms.
Jonathan Carter is the Associate Laboratory Director for Computing Sciences at Lawrence Berkeley National Laboratory (Berkeley Lab). The Computing Sciences Area at Berkeley Lab encompasses the National Energy Research Scientific Computing Division (NERSC), the Scientific Networking Division (home to the Energy Sciences Network, ESnet) and the Computational Research Division.
Dr. Carter's research interests are in the evaluation of system architectures and algorithms for high-performance computing, and in computational chemistry and physics simulations. Recently he has been engaged in a project to look at computer architectures beyond the end of Moore's Law and has focused on techniques to perform simulations for computational chemistry using newly developed quantum computing test-beds. He brings a unique perspective to his work, formed from using computing resources as a domain scientist, from performing performance analyses of computer architectures, and from his experience in moving large-scale computational systems from idea to reality.
Carter joined Computing Sciences as part of the National Energy Research Scientific Computing (NERSC) Division at the end of 1996, working with a broad range of scientists to optimize applications, transition projects from shared-memory vector systems to massively parallel systems, and providing in-depth consulting for materials scientists and chemists using NERSC. He became group leader of the consulting group at the end of 2005. During his time at NERSC, he led or played a lead role in teams that procured and deployed three of the fastest computing systems in the world.
Areas of expertise: quantum computing, beyond Moore's Law computer architectures, high-performance computing (HPC) / supercomputing, and computational chemistry.
Shanalyn A. Kemme, PhD, is the manager of the Atomic Optical Sensing and Electrochemical Engineering organization at Sandia National Laboratories. She is the Program Manager of the Strategic Inertial Guidance with Matterwaves (SIGMA) Grand Challenge, a large effort to produce a low-SWaP, strategic-grade, light-pulse atomic interferometer that operates in high-dynamic range environments. Previously, she was a Distinguished Member of Technical Staff where she realized micro-optics and diffractive optics. Her development of a free-space optical transponder led to a prestigious R&D 100 Award. She played a leading role in design and fabrication of several diffractive optics awarded citations for meritorious achievement including the AQUARIUS Quantum Grand Challenge, a diffractive optical flight component, as well as μChemLab™ lab-on-a-chip system. Dr. Kemme co-authored the chapter “Diffractive Optical Elements” in the Optical Engineer’s Desk Reference (Optical Society of America, 2002), and is editor/author of the book “Microoptics and Nanooptics Fabrication,” published by Taylor and Francis on 2010. Shanalyn was hired into Sandia over 20 years ago after completing a physics/math undergraduate at Kansas State University and a PhD in optical sciences from the Optical Sciences Center at the University of Arizona. She has authored over 80 publications and holds 5 patents.
Theoretical chemist Todd Martínez develops and applies new methods that predict and explain how atoms move in molecules. These methods are used both to design new molecules and to understand the behavior of those that already exist. His research group studies the response of molecules to light (photochemistry) and external force (mechanochemistry). Photochemistry is a critical part of human vision, single-molecule spectroscopy, harnessing solar energy (either to make fuels or electricity), and even organic synthesis. Mechanochemistry represents a novel scheme to promote unusual reactions and potentially to create self-healing materials that resist degradation. The underlying tools embody the full gamut of quantum mechanical effects governing molecules, from chemical bond breaking/formation to electron/proton transfer and electronic excited states.
Martínez received his PhD in chemistry from UCLA in 1994. After postdoctoral study at UCLA and the Hebrew University in Jerusalem, he joined the faculty at the University of Illinois in 1996. In 2009, he joined the faculty at Stanford, where he is now the Ehrsam and Franklin Professor of Chemistry and Professor of Photon Science at SLAC National Accelerator Laboratory. He has received numerous awards for his contributions, including a MacArthur Fellowship (commonly known as the “genius award”). He is co-editor of Annual Reviews in Physical Chemistry, associate editor of The Journal of Chemical Physics, and an elected fellow of the American Academy of Arts and Sciences.
Current research in the Martínez lab aims to make molecular modeling both predictive and routine. New approaches to interactive molecular simulation are being developed, in which users interact with a virtual-reality based molecular modeling kit that fully understands quantum mechanics. New techniques to discover heretofore unknown chemical reactions are being developed and tested, exploiting the many efficient methods that the Martínez group has introduced for solving quantum mechanical problems quickly, using a combination of physical/chemical insights and commodity videogaming hardware. For more details, please visit http://mtzweb.stanford.edu.
Kevin Young is a staff scientist at Sandia National Laboratories with broad expertise in physical implementations of quantum computing. Kevin is the co-director of Sandia’s Quantum Performance Laboratory, a multidisciplinary research and development group within Sandia National Laboratories that develops and deploys cutting-edge techniques for assessing and improving the performance of quantum computing hardware.
Kevin earned both a BS in Physics and Mathematics and a BA in Chemistry at the College of Charleston in South Carolina. He received his PhD in Physics from the University of California, Berkeley, where he specialized in robust quantum optimal control theory and modeling of semiconducting qubit platforms. At Sandia his work focuses on identifying and mitigating errors in real quantum hardware, modeling low-level device physics of trapped-ion quantum computers, and participating in a number of standards making and advising organizations. He actively collaborates with experimental quantum computing groups across the globe.
Kevin is the recipient of the Department of Energy’s Early Career Award, a prestigious award granted to further the individual research programs of outstanding scientists with demonstrated successful research activities and potential for solving important problems to the US government. His research under this award focuses on developing fast and efficient calibration methods for quantum computers that work for all qubit technologies and can operate efficiently at scale.
Andy Mounce has research experience in condensed matter physics, semiconductor qubits, nitrogen vacancy magnetometry, and defects in wide band gap semiconductors. His expertise includes utilizing quantum information science techniques for understanding basic properties of quantum materials and quantum information relevant materials, such as superconductors, strongly correlated electronic materials, magnetic materials, and topological phases in materials. These techniques include cryogenic amplification, optically detected magnetic resonance, nitrogen vacancy detected magnetometry, photoluminescence, and bulk spin-resonance. Additionally, he is using machine learning in image analysis techniques, such as compressive sensing and neural networks, to both optimize experimental implementations and analysis.
Dr. Daniel Soh received his first PhD in high power fiber lasers from University of Southampton, UK, in 2005. He developed and commercialized high power lasers in silicon valley companies including JDSU until he joined Sandia National Laboratories in 2009. Initially, Dr. Soh contributed to Sandia’s high power laser development. In 2013, he turned his interest to quantum information science. He went back to college for reeducation and obtained his second PhD on quantum dynamical systems from Stanford University in 2019. His recent interests are quantum communications, quantum computing, quantum sensing, and quantum networks. He has published more than 70 peer-reviewed journal articles and has authored 10 granted US patents.
Title: Associate Computational Scientist, Quantum Computing Group, Computational Science Initiative, Brookhaven National Laboratory
Expertise: Quantum Information Science
Description: Ning Bao’s research is focused on quantum information theory and quantum information science more broadly, particularly with an eye toward entanglement measures and applications of ideas from quantum information science to other aspects of physics. Before arriving at Brookhaven, he completed postdoctoral positions at Caltech and University of California, Berkeley and did his graduate work at Stanford University.
Gary Wiederrecht is the deputy director of the Center for Nanoscale Materials and the Nanoscience and Technology division. He is also the deputy director for Argonne’s Quantum Information Science Incubator.
Prior to this, Dr. Wiederrecht led the Nanophotonics group from 2006 to 2016 and the Nanophotonics and Biofunctional Structures group from 2016 to 2019. He joined Argonne in 1992 as a postdoctoral fellow and became a scientific staff member in 1995. He received a bachelor of science degree in chemistry from University of California, Berkeley in 1987 and a doctorate in physical chemistry from MIT in 1992.
He has received an R&D100 Award, the U.S. Department of Energy Young Scientist Award, the Presidential Early Career Award for Scientists and Engineers (PECASE), and the Argonne National Laboratory Distinguished Service Award. He is a Fellow of the American Physical Society.
He has authored or co-authored more than 145 peer-reviewed research articles and has six patents.
His research interests center on ultrafast excitation processes in nanoparticles, novel optical properties of strongly coupled hybrid nanostructures and quantum optics.
Dr. Peter Schwindt is a Distinguished Member of the Technical Staff at Sandia National Laboratories. He has been engaged in optical and atomic physics research for more than two decades with an emphasis in applying the principles of atomic/quantum physics to sensing and timing problems. Dr. Schwindt specializes in developing optically pumped magnetometers for magnetoencephalography, the measurement of the magnetic field from neuronal activity in the human brain, and developing compact atomic clocks and atom interferometers for position, navigation, and timing applications.
Title: Assistant Computational Scientist, Quantum Computing Group, Computational Science Initiative, Brookhaven National Laboratory
- High-performance Computing and Software Optimization
Yao-Lung (Leo) Fang is a theoretical physicist. His past work includes exploring quantum nonlinear optics, open quantum systems, and quantum Monte Carlo. His current research interests are quantum software optimization, quantum machine learning, and high-performance computing applied to quantum simulation and other scientific challenges, such as image reconstruction.