The Experts below are selected from a list of 33498 Experts worldwide ranked by ideXlab platform
Luke Shulenburger - One of the best experts on this subject based on the ideXlab platform.
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An efficient hybrid orbital representation for quantum Monte Carlo calculations.
The Journal of chemical physics, 2018Co-Authors: Ye Luo, Kenneth Esler, Paul R. C. Kent, Luke ShulenburgerAbstract:The scale and complexity of the quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the Computationally most efficient basis set, can have memory requirements exceeding the capacity of a single Computational Node. This situation has traditionally forced a difficult choice of either using slow interNode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining the high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth of the memory required for conventional B-splines. The hybrid orbital representation therefore expands the overall range of systems that can be practically studied with QMC.The scale and complexity of the quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the Computationally most efficient basis set, can have memory requirements exceeding the capacity of a single Computational Node. This situation has traditionally forced a difficult choice of either using slow interNode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining the high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth of the memory required for conventional B-splines. The hybrid orbital representation therefore expands t...
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an efficient hybrid orbital representation for quantum monte carlo calculations
Journal of Chemical Physics, 2018Co-Authors: Ye Luo, Kenneth Esler, Paul R. C. Kent, Luke ShulenburgerAbstract:The scale and complexity of the quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the Computationally most efficient basis set, can have memory requirements exceeding the capacity of a single Computational Node. This situation has traditionally forced a difficult choice of either using slow interNode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining the high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth of the memory required for conventional B-splines. The hybrid orbital representation therefore expands the overall range of systems that can be practically studied with QMC.
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an efficient hybrid orbital representation for quantum monte carlo calculations
arXiv: Materials Science, 2018Co-Authors: Ye Luo, Kenneth Esler, Paul R. C. Kent, Luke ShulenburgerAbstract:The scale and complexity of quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the Computationally most efficient basis set, can have memory requirements exceeding the capacity of a single Computational Node. This situation has traditionally forced a difficult choice of either using slow interNode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth the memory required for conventional B-splines. The hybrid orbital representation therefore expands the overall range of systems that can be practically studied with QMC.
Ye Luo - One of the best experts on this subject based on the ideXlab platform.
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An efficient hybrid orbital representation for quantum Monte Carlo calculations.
The Journal of chemical physics, 2018Co-Authors: Ye Luo, Kenneth Esler, Paul R. C. Kent, Luke ShulenburgerAbstract:The scale and complexity of the quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the Computationally most efficient basis set, can have memory requirements exceeding the capacity of a single Computational Node. This situation has traditionally forced a difficult choice of either using slow interNode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining the high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth of the memory required for conventional B-splines. The hybrid orbital representation therefore expands the overall range of systems that can be practically studied with QMC.The scale and complexity of the quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the Computationally most efficient basis set, can have memory requirements exceeding the capacity of a single Computational Node. This situation has traditionally forced a difficult choice of either using slow interNode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining the high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth of the memory required for conventional B-splines. The hybrid orbital representation therefore expands t...
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an efficient hybrid orbital representation for quantum monte carlo calculations
Journal of Chemical Physics, 2018Co-Authors: Ye Luo, Kenneth Esler, Paul R. C. Kent, Luke ShulenburgerAbstract:The scale and complexity of the quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the Computationally most efficient basis set, can have memory requirements exceeding the capacity of a single Computational Node. This situation has traditionally forced a difficult choice of either using slow interNode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining the high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth of the memory required for conventional B-splines. The hybrid orbital representation therefore expands the overall range of systems that can be practically studied with QMC.
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an efficient hybrid orbital representation for quantum monte carlo calculations
arXiv: Materials Science, 2018Co-Authors: Ye Luo, Kenneth Esler, Paul R. C. Kent, Luke ShulenburgerAbstract:The scale and complexity of quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the Computationally most efficient basis set, can have memory requirements exceeding the capacity of a single Computational Node. This situation has traditionally forced a difficult choice of either using slow interNode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth the memory required for conventional B-splines. The hybrid orbital representation therefore expands the overall range of systems that can be practically studied with QMC.
Paul R. C. Kent - One of the best experts on this subject based on the ideXlab platform.
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An efficient hybrid orbital representation for quantum Monte Carlo calculations.
The Journal of chemical physics, 2018Co-Authors: Ye Luo, Kenneth Esler, Paul R. C. Kent, Luke ShulenburgerAbstract:The scale and complexity of the quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the Computationally most efficient basis set, can have memory requirements exceeding the capacity of a single Computational Node. This situation has traditionally forced a difficult choice of either using slow interNode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining the high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth of the memory required for conventional B-splines. The hybrid orbital representation therefore expands the overall range of systems that can be practically studied with QMC.The scale and complexity of the quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the Computationally most efficient basis set, can have memory requirements exceeding the capacity of a single Computational Node. This situation has traditionally forced a difficult choice of either using slow interNode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining the high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth of the memory required for conventional B-splines. The hybrid orbital representation therefore expands t...
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an efficient hybrid orbital representation for quantum monte carlo calculations
Journal of Chemical Physics, 2018Co-Authors: Ye Luo, Kenneth Esler, Paul R. C. Kent, Luke ShulenburgerAbstract:The scale and complexity of the quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the Computationally most efficient basis set, can have memory requirements exceeding the capacity of a single Computational Node. This situation has traditionally forced a difficult choice of either using slow interNode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining the high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth of the memory required for conventional B-splines. The hybrid orbital representation therefore expands the overall range of systems that can be practically studied with QMC.
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an efficient hybrid orbital representation for quantum monte carlo calculations
arXiv: Materials Science, 2018Co-Authors: Ye Luo, Kenneth Esler, Paul R. C. Kent, Luke ShulenburgerAbstract:The scale and complexity of quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the Computationally most efficient basis set, can have memory requirements exceeding the capacity of a single Computational Node. This situation has traditionally forced a difficult choice of either using slow interNode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth the memory required for conventional B-splines. The hybrid orbital representation therefore expands the overall range of systems that can be practically studied with QMC.
Kenneth Esler - One of the best experts on this subject based on the ideXlab platform.
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An efficient hybrid orbital representation for quantum Monte Carlo calculations.
The Journal of chemical physics, 2018Co-Authors: Ye Luo, Kenneth Esler, Paul R. C. Kent, Luke ShulenburgerAbstract:The scale and complexity of the quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the Computationally most efficient basis set, can have memory requirements exceeding the capacity of a single Computational Node. This situation has traditionally forced a difficult choice of either using slow interNode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining the high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth of the memory required for conventional B-splines. The hybrid orbital representation therefore expands the overall range of systems that can be practically studied with QMC.The scale and complexity of the quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the Computationally most efficient basis set, can have memory requirements exceeding the capacity of a single Computational Node. This situation has traditionally forced a difficult choice of either using slow interNode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining the high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth of the memory required for conventional B-splines. The hybrid orbital representation therefore expands t...
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an efficient hybrid orbital representation for quantum monte carlo calculations
Journal of Chemical Physics, 2018Co-Authors: Ye Luo, Kenneth Esler, Paul R. C. Kent, Luke ShulenburgerAbstract:The scale and complexity of the quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the Computationally most efficient basis set, can have memory requirements exceeding the capacity of a single Computational Node. This situation has traditionally forced a difficult choice of either using slow interNode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining the high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth of the memory required for conventional B-splines. The hybrid orbital representation therefore expands the overall range of systems that can be practically studied with QMC.
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an efficient hybrid orbital representation for quantum monte carlo calculations
arXiv: Materials Science, 2018Co-Authors: Ye Luo, Kenneth Esler, Paul R. C. Kent, Luke ShulenburgerAbstract:The scale and complexity of quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the Computationally most efficient basis set, can have memory requirements exceeding the capacity of a single Computational Node. This situation has traditionally forced a difficult choice of either using slow interNode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth the memory required for conventional B-splines. The hybrid orbital representation therefore expands the overall range of systems that can be practically studied with QMC.
Iordanis Kavathatzopoulos - One of the best experts on this subject based on the ideXlab platform.
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Is the Post-Turing ICT Sustainable?
2012Co-Authors: Norberto Patrignani, Iordanis KavathatzopoulosAbstract:In this paper we introduce a definition of post-Turing ICT with an initial analysis of its sustainability. At the beginning of the history of computing the attention was concentrated on the single machine: a device able to read and write a memory and able to execute different actions depending on the internal state. It was only in the 1960’s that the fifth function (after input, memory, processing and output) was introduced: the network, the capability of this single Computational Node to be connected and exchange data with similar machines. In the last fifty years the network has grown at an incredible speed, introducing us into the post-Turing ICT era: billions of electronic devices interconnected. ICT has now a significant environmental impact along all its lifetime phases: manufacturing (based on scarce minerals), application (based on growing power consumption) and e-waste management (with open cycles difficult to close). In this paper, we introduce relevant topics to understand whether the current ICT production and consumption paradigms are sustainable, and the social consequences and implications of such a problem for stakeholders.
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HCC - Is the Post-Turing ICT Sustainable?
ICT Critical Infrastructures and Society, 2012Co-Authors: Norberto Patrignani, Iordanis KavathatzopoulosAbstract:In this paper we introduce a definition of post-Turing ICT with an initial analysis of its sustainability. At the beginning of the history of computing the attention was concentrated on the single machine: a device able to read and write a memory and able to execute different actions depending on the internal state. It was only in the 1960’s that the fifth function (after input, memory, processing and output) was introduced: the network, the capability of this single Computational Node to be connected and exchange data with similar machines. In the last fifty years the network has grown at an incredible speed, introducing us into the post-Turing ICT era: billions of electronic devices interconnected. ICT has now a significant environmental impact along all its lifetime phases: manufacturing (based on scarce minerals), application (based on growing power consumption) and e-waste management (with open cycles difficult to close). In this paper, we introduce relevant topics to understand whether the current ICT production and consumption paradigms are sustainable, and the social consequences and implications of such a problem for stakeholders.