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Title: Associate Professor of Physics ad Astronomy, Tufts University/Senior Scientist, Computer Science Initiative
Expertise: Quantum Computing
In 2015 Love joined the Physics Department at Tufts University as an Associate Professor with Tenure. In 2018 he joined Brookhaven National Lab’s Computational Science Initiative as a Senior Scientist in a dual appointment held concurrently with his Tufts appointment. He serves as the Chair of the Scientific Advisory Board of Zapata Computing, Inc., a Boston-based quantum software startup. He is a member of FQXi.
In quantum information science Love has worked broadly on quantum simulation, including work on quantum simulation of quantum chemistry and high energy physics and on quantum lattice-gas and quantum cellular automata models. Love has also worked on adiabatic quantum computing, the theory of entanglement, on semiclassical descriptions of quantum information including wigner functions for qubits and qudits, and on efficient simulation of subtheories of quantum mechanics that lack contextuality.
Martin Suchara is a computational scientist at Argonne National Laboratory with expertise in quantum computing. His research focuses on quantum communication and networking, quantum error correction, quantum simulations, and optimizations of the quantum computing software stack.
Prior to joining Argonne, Martin worked at AT&T Labs and received postdoctoral training in quantum computing from UC Berkeley and the IBM T. J. Watson Research Center. Martin received his Ph.D. from the Department of Computer Science at Princeton University.
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.
Title: Physicist, Collider-Accelerator Department Control Systems Head
Expertise: Particle Accelerator Physics and Technology, Computational Accelerator Physics, Particle Accelerator Control Systems, Data Science and Machine Learning in Accelerator Science, Quantum Information Science (QIS), Storage Rings for Quantum Computing
As an accelerator physicist in the Collider-Accelerator Department at Brookhaven National Laboratory (BNL), Kevin has spent over 35 years working in accelerator physics where he has gained expertise and experience in accelerator design, particle beam simulations, processing and analysis of data, particle accelerator-based data science and machine learning, as well as ion trap dynamics, crystalline beams for quantum information sciences (QIS), and ion trap-based quantum computing.
Kevin has broad experience, as a designer of the NASA Space Radiation Laboratory, a member of the RHIC design and commissioning team, and most recently as a member of the electron ion collider (EIC) project at BNL. His work extends internationally, with collaborations with researchers at CERN, Fermilab, J-PARC & KEK in Japan, as well as domestically with Stony Brook University, the University of New Mexico, and Cornell University.
Kevin and Dr. Thomas Roser are the inventors of the storage ring quantum computer, a new kind of quantum information system that utilizes a circular radio-frequency quadrupole to create an unbounded ion trap. Kevin is the principle investigator for the Storage Ring Quantum Computer project, which offers a pathway to large scale QIS.
Kevin is an author on over thirty peer reviewed publications, co-author on a book chapter in “Challenges and Goals for Accelerators in the XXI Century” (2016), and an author on over 150 conference publications. Kevin has mentored many students in his career, including three Ph.D. students from Stony Brook University.
Dr. Yao is a theoretical and computational physicist, developing methods, algorithms, and codes to address condensed matter physics and materials science problems. With a degree of B.S. in department of intensive instruction in 2000 and M.S. in physics in 2003 from Nanjing University, China, he obtained his Ph.D. in physics from Iowa State University in 2009. After graduation, he took a postdoc position in Ames Laboratory. He was promoted to assistant scientist in 2011, associate scientist in 2015, and senior theoretical physicist in 2019, with an adjunct faculty position in department of Physics and Astronomy at Iowa State University. He is currently leading projects in the development of quantum computing approaches to solve ground state and dynamical properties of correlated quantum materials within the Gutzwiller quantum-classical embedding framework. He is also a key developer of the Gutzwiller density functional theory and rotationally-invariant Slave-Boson method and software.
Jeffrey Larson is a computational mathematician at Argonne. His research centers on optimization algorithms and their implementation in software.
Jeff is the Argonne lead for the Fundamental Algorithmic Research for Quantum Computing (FAR-QC) project where he develops numerical optimization methods for problems in quantum computing. He is also a lead developer of libEnsemble, a Python library to coordinate the concurrent evaluation of ensembles of computations. He also develops APOSMM, an asynchronously parallel optimization solver for finding multiple minima, and other derivative-free optimization algorithms for that exploit problem structure in scientific applications. He studies approaches for the fuel-efficient routing of autonomous vehicles through road networks.
Jeff joined Argonne in 2014 as a postdoctoral appointee. He was previously a postdoctoral researcher with the Royal Institute of Technology KTH in Sweden. He earned his Ph.D. in applied mathematics from the University of Colorado Denver in 2012.
- Quantum computing
- Simulation-based, black-box, or derivative-free optimization
- Autonomous vehicle routing
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.
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.
Heather Gray is an experimental particle physicist working on the ATLAS experiment at the Large Hadron Collider (LHC) just outside Geneva in Switzerland. She has broad interests in particle physics, but the primary focus of her research is the Higgs boson -- the most recently discovered elementary particle, the only known elementary scalar of nature and the final piece of the remarkably successful Standard Model. She studies the properties of the Higgs boson and, in particular, how it interacts with different types of quarks, including top, bottom and charm quarks. Other research interests include the development of track reconstruction algorithms, silicon detectors and algorithms for quantum computers. A theme throughout her research is applications of machine learning.
Areas of expertise: physics/astrophysics, quantum computing, AI/machine learning, accelerators, dark energy/dark matter, particle physics, Higgs boson
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.