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  • richardmitnick 2:55 pm on January 26, 2021 Permalink | Reply
    Tags: "Connected Moments" for Quantum Computing, , , DOE’s Pacific Northwest National Laboratory, ,   

    From DOE’s Pacific Northwest National Laboratory: “Connected Moments for Quantum Computing” 

    From DOE’s Pacific Northwest National Laboratory

    January 12, 2021 [Just now in social media.]

    Karyn Hede
    karyn.hede@pnnl.gov

    Math shortcut shaves time and cost of quantum calculations while maintaining accuracy.

    1

    Quantum computers are exciting in part because they are being designed to show how the world is held together. This invisible “glue” is made of impossibly tiny particles and energy. And like all glue, it’s kind of messy.

    Once the formula for the glue is known, it can be used to hold molecules together in useful structures. And these new kinds of materials and chemicals may one day fuel our vehicles and warm our homes.

    But before all that, we need math. That’s where theoretical chemists Bo Peng and Karol Kowalski have excelled. The Pacific Northwest National Laboratory duo are teaching today’s computers to do the math that will reveal the universe’s subatomic glue, once full-scale quantum computing becomes feasible.

    2
    The connected moments mathematical method is helping understand the universal energy glue that binds molecules together. Credit: Nathan Johnson /Pacific Northwest National Laboratory.

    The team recently showed that they could use a mathematical tool called “connected moments,” to greatly reduce the time and calculation costs of conducting one kind of quantum calculation. Using what’s called a quantum simulator, the team showed that they could accurately model simple molecules. This feat, which mathematically describes the energy glue holding together molecules, garnered “editor’s pick” in the Journal of Chemical Physics, signifying its scientific importance.

    “We showed that we can use this approach to reduce the complexity of quantum calculations needed to model a chemical system, while also reducing errors,” said Peng. “We see this as a compromise that will allow us to get from what we can do right now with a quantum computer to what will be possible in the near future.”

    Connected moments

    The research team applied a mathematical concept that was first described 40 years ago. They were attracted to the connected moments method because of its ability to accurately reconstruct the total energy of a molecular system using much less time and many fewer cycles of calculations. This is important because today’s quantum computers are prone to error. The more quantum circuits needed for a calculation, the more opportunity for error to creep in. By using fewer of these fragile quantum circuits, they reduced the error rate of the whole calculation, while maintaining an accurate result.

    “The design of this algorithm allows us to do the equivalent of a full-scale quantum calculation with modest resources,” said Kowalski.

    Timing-saving method applies to chemistry and materials science.

    In the study, the team established the reliability of the connected moments method for accurately describing the energy in both a simple molecule of hydrogen and a simple metal impurity. Using relatively simple models allowed the team to compare its method with existing full-scale computing models known to be correct and accurate.

    “This study demonstrated that the connected moments method can advance the accuracy and affordability of electronic structure methods,” said Kowalski. “We are already working on extending the work to larger systems, and integrating it with emerging quantum computing frameworks.”

    By studying both a chemical system and a material system the researchers showed the versatility of the approach for describing the total energy in both systems. The preparation of this so-called “initial state” is a steppingstone to studying more complex interactions between molecules—how the energy shifts around to keep molecules glued together.

    Bridge to quantum computing

    The published study [The Journal of Chemical Physics] used IBM’s QISKIT quantum computing software, but work is already under way to extend its use with other quantum computing platforms. Specifically, the research team is working to extend the work to support XACC, an infrastructure developed at Oak Ridge National Laboratory. The XACC software will allow the scientists to take advantage of the fastest, most accurate world-class computers as a quantum–classical computing hybrid.

    This discovery will now be incorporated into research to be performed in the Quantum Science Center, a U.S. Department of Energy Office of Science (DOE-SC)-supported initiative.

    “This work was conducted with a very small system of four qubits, but we hope to extend to a 12-qubit system in the near term, with an ultimate goal of a 50-qubit system within three to five years,” said Peng.

    At that point, the messy glue of the universe may be easier to apply.

    The research was supported by the DOE-SC Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences.

    See the full article here .

    five-ways-keep-your-child-safe-school-shootings

    Please help promote STEM in your local schools.

    Stem Education Coalition

    DOE’s Pacific Northwest National Laboratory (PNNL) is one of the United States Department of Energy National Laboratories, managed by the Department of Energy’s Office of Science. The main campus of the laboratory is in Richland, Washington.

    PNNL scientists conduct basic and applied research and development to strengthen U.S. scientific foundations for fundamental research and innovation; prevent and counter acts of terrorism through applied research in information analysis, cyber security, and the nonproliferation of weapons of mass destruction; increase the U.S. energy capacity and reduce dependence on imported oil; and reduce the effects of human activity on the environment. PNNL has been operated by Battelle Memorial Institute since 1965.

     
  • richardmitnick 1:30 pm on January 7, 2021 Permalink | Reply
    Tags: "Insights Through Atomic Simulation", , Calculating electronic structure- fundamental to atomic behavior and chemical bonding., , , DOE’s Pacific Northwest National Laboratory, NWChem and CP2K provide information that allows scientists to efficiently tune; control; and design molecular processes for desired outcomes., NWChem and CP2K- two prominent software packages for computational chemistry.,   

    From DOE’s Pacific Northwest National Laboratory: “Insights Through Atomic Simulation” 

    From DOE’s Pacific Northwest National Laboratory

    January 6, 2021
    Melissae Fellet

    Special issue highlights PNNL contributions to NWChem and CP2K, two prominent software packages for computational chemistry.

    1

    A recent special issue in The Journal of Chemical Physics highlights Pacific Northwest National Laboratory’s (PNNL) contributions to developing two prominent open-source software packages for computational chemistry used by scientists around the world.

    PNNL researchers have been instrumental in developing the software packages, called NWChem and CP2K. These programs offer complementary approaches to calculating electronic structure, which is fundamental to atomic behavior and chemical bonding.

    According to the abstract for this special issue, “the electronic structure community now has a wonderfully diverse arsenal of software packages available for performing calculations on molecules and materials.” NWChem and CP2K are included in that arsenal.

    For decades, computational chemists have been working to develop ways to effectively solve equations that describe how electrons move around atoms, how atoms connect to make molecules, and how electrons respond to stimuli. Solving these equations often requires complex calculations that consume computing time and processing resources. Computational chemists carefully develop and optimize electronic structure algorithms to balance computational efficiency with predictions accurate enough to recreate observations in actual molecular and materials systems in realistic environments.

    “Now the theory, computational techniques, and processor hardware are all at a point where researchers can use these packages regularly,” said Greg Schenter, a physicist and Laboratory Fellow at PNNL.

    Researchers around the world use atomistic computer simulations to explain new scientific phenomena, interpret experimental measurements, predict materials properties and the products of chemical reactions, and design new molecular systems. NWChem and CP2K provide information that allows scientists to efficiently tune, control, and design molecular processes for desired outcomes.

    Researchers at PNNL use the results from these packages in their own work. They help chemists create more efficient catalysts; biologists study proteins that transform biomass into fuel; battery researchers study ion transfer in electrolytes; and geochemists and environmental scientists uncover molecular mechanisms in biogeochemical transformations.

    2
    Credit: Nathan Johnson | Pacific Northwest National Laboratory.

    NWChem: accurate ground and excited-state properties of molecules and materials.

    NWChem, also known as NorthWest Chemistry, was first developed in the 1990s at the Environmental Molecular Sciences Laboratory, a U.S. Department of Energy, Office of Science user facility at PNNL. It was developed to harness the power of massively parallel supercomputers.

    The code has evolved to run on computing facilities and personal computers. NWChem is now widely used at universities, other national laboratories, and computer centers around the world.

    NWChem models the ground and excited-state electronic structure and dynamics of molecules and condensed-phase systems at different levels of accuracy and detail. The precision and detail of the predictions produced by NWChem allow researchers to predict properties and experimental spectroscopic signals over a broad range of systems, including molecules, nanostructures, solids, and biomolecules.

    CP2K: efficient calculations for molecular ensembles.

    CP2K had its beginning in 2000, providing efficient models of electronic structure to simulate large chemical systems in the condensed phase to elucidate collective behavior. It performs atomistic simulations of solid-state, liquid, molecular, periodic, material, crystal, and biological systems.

    Schenter describes CP2K as the pocket multi-tool of molecular simulations because it has a wide range of capabilities in an easy-to-use package.

    The software incorporates statistical mechanics, which makes it useful to capture phenomena in the collective dance of molecular ensembles. Because of the calculational flexibility, CP2K is widely used in the computational chemistry community and designed with efficient algorithms that are necessary for the study of heterogeneous condensed phase systems. Users can also easily modify the software to suit their computational needs.

    At PNNL, NWChem has received support from the Basic Energy Sciences, Biological and Environmental Research, and Advanced Scientific Computing Research programs, while CP2K developments have been funded by the Basic Energy Sciences program; all of these programs are in the U.S. Department of Energy, Office of Science.

    Looking ahead, PNNL plans to continue building on its long history of advancing software tools like these for fundamental research.

    “PNNL researchers have been involved with developing software tools for electronic structure calculation for decades, and the tools have advanced to efficiently describe complex phenomena. Now we are evolving the packages to work with increasingly realistic systems,” Schenter said.

    See the full article here .

    five-ways-keep-your-child-safe-school-shootings

    Please help promote STEM in your local schools.

    Stem Education Coalition

    DOE’s Pacific Northwest National Laboratory (PNNL) is one of the United States Department of Energy National Laboratories, managed by the Department of Energy’s Office of Science. The main campus of the laboratory is in Richland, Washington.

    PNNL scientists conduct basic and applied research and development to strengthen U.S. scientific foundations for fundamental research and innovation; prevent and counter acts of terrorism through applied research in information analysis, cyber security, and the nonproliferation of weapons of mass destruction; increase the U.S. energy capacity and reduce dependence on imported oil; and reduce the effects of human activity on the environment. PNNL has been operated by Battelle Memorial Institute since 1965.

     
  • richardmitnick 11:51 am on November 24, 2020 Permalink | Reply
    Tags: "GPU Clusters Accelerate Quantum Computer Simulator", A group of researchers at the U.S. Department of Energy’s PNNL have invented a quantum computer simulator called DM-SIM that is 10 times faster than existing methods., DOE’s Pacific Northwest National Laboratory, GPUs devote most of their chip area to compute units and have high-throughput memory., New method improves error investigations in deep quantum circuits., , , The team achieved the increase in speed by harnessing the power of graphical processing units (GPUs).   

    From DOE’s Pacific Northwest National Laboratory: “GPU Clusters Accelerate Quantum Computer Simulator” 

    From DOE’s Pacific Northwest National Laboratory

    November 13, 2020
    Rebekah Orton

    1
    Artist’s rendering of a quantum computer. Credit:Jeffrey London/PNNL.

    New method improves error investigations in deep quantum circuits

    Before quantum computers begin to be deployed, how will we know if they work? The answer: quantum computer simulators. These important tools, now under development, run on the world’s most powerful supercomputing resources and still take days or weeks to complete quantum computing scenarios.

    Now, a group of researchers at the U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL) have invented a quantum computer simulator, called DM-SIM, that is 10 times faster than existing methods. The feat was detailed in one of only a handful of articles nominated for “Best Paper” at the annual international conference for high-performance computing, SC20 [Paper: Density Matrix Quantum Circuit Simulation via theBSP Machine on Modern GPU Clusters.

    The team, led by computer scientist Ang Li, achieved the increase in speed by harnessing the power of graphical processing units (GPUs), the lightning-quick processors originally designed for images and videos.

    Simulating qubits: the basic unit of quantum computing

    The basic unit of quantum programming—the quantum bit, or qubit—is strikingly different from its counterpart, the bit, in a classical computer. Unlike bits, the binary units that represent ones and zeros in a classical computer, a quantum computer’s qubits can represent the possibility of both one and zero at the same time.

    2
    Qubits, the basic unit of quantum computing, can represent the possibility of both one and zero at the same time. Credit: Jeffrey London/PNNL.

    A reliable quantum computer simulator needs to capture the complexity of superposition, but it’s not that simple. Multiple qubits in a quantum computer can also exhibit quantum entanglement, meaning when they are entangled, if a single qubit collapses into an individual one or zero, the rest will also collapse like a house of cards.

    Superposition and entanglement are the reasons quantum computers are more useful than classical computers for certain problems. Researchers need powerful quantum computer simulators that can accurately mimic qubits’ billions of possibilities—and errors.

    “Physical qubits currently aren’t perfect or logical,” said Li. “They are more like nature where everything responds to its environment, so you have to find a way to represent noise and errors to create a more realistic simulator.”

    But realism takes more time to calculate—and Li wanted to see if GPUs could hurry things up.

    Layering virtual quantum circuits onto multiple GPUs

    GPUs have been sold for decades to move images quickly across screens, but using them for general-purpose computation, like scientific simulation, emerged in 2007. Unlike a cache-heavy central processing unit (CPU), GPUs devote most of their chip area to compute units and have high-throughput memory. This makes their computations much faster.

    Li started working with GPUs in 2009 before they were as widely used as they are today. He was partway through his PhD research in high-performance computing by the time researchers began to use GPUs to accelerate deep learning in 2013. He’s seen the value ever since.

    “Many major computational problems will move to GPU centric computations, and this work is part of that trend,” said Li. “Big applications need GPUs’ faster delivery to expand their expected performance.”

    3
    Connecting multiple graphical processing units (GPUs) amplifies their swift computing power as they simulate qubits. Credit: Jeffrey London/PNNL.

    Quantum circuits aren’t images. But because GPUs rely on a large number of compute units to deliver high performance, Li suspected they could more quickly perform the heavy computations that represent quantum gates—the building blocks of a quantum circuit.

    Creating deeper gates in a quantum computer simulator

    Quantum circuits are made through operations that change the qubit’s state. These operations are called gates. At the beginning of the gate, each qubit is like an arrow, or vector, pointing to the “0” direction. After the circuit ends and is measured, the qubits collapse to classic one or zero states. The statistical breakdown of ones and zeros indicates the results of the computation.

    An accurate quantum computer simulator needs to describe both pure and mixed quantum states within each circuit. That’s why Li and his team used a method to describe the statistical state of a quantum system called a density matrix. Unlike the widely used state-vector, a density matrix contains all the information about a particular quantum state.

    While researchers have used density matrices to represent qubits before, no one before Li’s team has combined an efficient density matrix quantum circuit simulator with a GPU-accelerated high-performance computing cluster. Because of the complexity in operating the large density matrix, it isn’t easy to manage the massive threads and communication interwoven between cooperating GPUs. And the researcher’s efforts could fail if they didn’t synchronize communication across the GPUs and GPU nodes holding part of the density matrix.

    But Li and his teammates Omer Subasi, Xiu Yang, and Sriram Krishnamoorthy were up for the challenge. After linking the GPUs, they proposed a new formula reform that can significantly avoid expensive communication between GPUs. More importantly, it reduces the communication overhead while conserving the natural error expected from noisy, real-world quantum gates.

    Faster and the future

    With the new method, the team ran a density matrix simulation with one million arbitrary gates in only 94 minutes. This outcome was far deeper and quicker than has been demonstrated before—10 times faster than simpler simulators, which represent quantum states in a state-vector.

    The PNNL team applied their GPU-centered method to help investigate how errors occur in quantum circuits, but the approach could be more broadly applicable. Until a perfect quantum computer is available, PNNL’s DM-Sim simulator can be used to help develop quantum algorithms that provide understanding of molecules for medical advances, explain complex chemistry problems, analyze big-data graphs, and perform quantum-based machine learning . In the meantime, PNNL’s DM-Sim quantum computing simulator will greatly influence making quantum computers work in practical terms.

    The research was funded by the Quantum Science, Advanced Accelerator (QUASAR) laboratory-directed research and development initiative. QUASAR research contributes to the National Quantum Initiative and is part of PNNL efforts to create the science and algorithms that advance hardware development and prepare for the future of quantum technology. The complete paper and a free download of the DM-Sim is available on GITHUB.

    See the full article here .

    five-ways-keep-your-child-safe-school-shootings

    Please help promote STEM in your local schools.

    Stem Education Coalition

    DOE’s Pacific Northwest National Laboratory (PNNL) is one of the United States Department of Energy National Laboratories, managed by the Department of Energy’s Office of Science. The main campus of the laboratory is in Richland, Washington.

    PNNL scientists conduct basic and applied research and development to strengthen U.S. scientific foundations for fundamental research and innovation; prevent and counter acts of terrorism through applied research in information analysis, cyber security, and the nonproliferation of weapons of mass destruction; increase the U.S. energy capacity and reduce dependence on imported oil; and reduce the effects of human activity on the environment. PNNL has been operated by Battelle Memorial Institute since 1965.

     
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