The Experts below are selected from a list of 236733 Experts worldwide ranked by ideXlab platform
Y Liu - One of the best experts on this subject based on the ideXlab platform.
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the coronal global Evolutionary Model using hmi vector magnetogram and doppler data to determine coronal magnetic field evolution
arXiv: Solar and Stellar Astrophysics, 2020Co-Authors: Todd J Hoeksema, William P Abbett, G H Fisher, D J Bercik, Maria D Kazachenko, K Hayashi, Mark C M Cheung, M L Derosa, Y LiuAbstract:The Coronal Global Evolutionary Model (CGEM) provides data-driven simulations of the magnetic field in the solar corona to better understand the build-up of magnetic energy that leads to eruptive events. The CGEM project has developed six capabilities. CGEM modules (1) prepare time series of full-disk vector magnetic field observations to (2) derive the changing electric field in the solar photosphere over active-region scales. This local electric field is (3) incorporated into a surface flux transport Model that reconstructs a global electric field that evolves magnetic flux in a consistent way. These electric fields drive a (4) 3D spherical magneto-frictional (SMF) Model, either at high-resolution over a restricted range of solid angle or at lower resolution over a global domain, to determine the magnetic field and current density in the low corona. An SMF-generated initial field above an active region and the evolving electric field at the photosphere are used to drive (5) detailed magneto-hydrodynamic (MHD) simulations of active regions in the low corona. SMF or MHD solutions are then used to compute emissivity proxies that can be compared with coronal observations. Finally, a lower-resolution SMF magnetic field is used to initialize (6) a global MHD Model that is driven by an SMF electric-field time series to simulate the outer corona and heliosphere, ultimately connecting Sun to Earth. As a demonstration, this report features results of CGEM applied to observations of the evolution of NOAA Active Region 11158 in February 2011.
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the coronal global Evolutionary Model using hmi vector magnetogram and doppler data to Model the buildup of free magnetic energy in the solar corona
Social Work, 2015Co-Authors: G H Fisher, William P Abbett, D J Bercik, Maria D Kazachenko, B J Lynch, B T Welsch, J T Hoeksema, K Hayashi, Y LiuAbstract:The most violent space weather events (eruptive solar flares and coronal mass ejections) are driven by the release of free magnetic energy stored in the solar corona. Energy can build up on timescales of hours to days, and then may be suddenly released in the form of a magnetic eruption, which then propagates through interplanetary space, possibly impacting the Earth's space environment. Can we use the observed evolution of the magnetic and velocity fields in the solar photosphere to Model the evolution of the overlying solar coronal field, including the storage and release of magnetic energy in such eruptions? The objective of CGEM, the Coronal Global Evolutionary Model, funded by the NASA/NSF Space Weather Modeling program, is to develop and evaluate such a Model for the evolution of the coronal magnetic field. The evolving coronal magnetic field can then be used as a starting point for magnetohydrodynamic (MHD) Models of the corona, which can then be used to drive Models of heliospheric evolution and predictions of magnetic field and plasma density conditions at 1AU.
K Hayashi - One of the best experts on this subject based on the ideXlab platform.
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the coronal global Evolutionary Model using hmi vector magnetogram and doppler data to determine coronal magnetic field evolution
arXiv: Solar and Stellar Astrophysics, 2020Co-Authors: Todd J Hoeksema, William P Abbett, G H Fisher, D J Bercik, Maria D Kazachenko, K Hayashi, Mark C M Cheung, M L Derosa, Y LiuAbstract:The Coronal Global Evolutionary Model (CGEM) provides data-driven simulations of the magnetic field in the solar corona to better understand the build-up of magnetic energy that leads to eruptive events. The CGEM project has developed six capabilities. CGEM modules (1) prepare time series of full-disk vector magnetic field observations to (2) derive the changing electric field in the solar photosphere over active-region scales. This local electric field is (3) incorporated into a surface flux transport Model that reconstructs a global electric field that evolves magnetic flux in a consistent way. These electric fields drive a (4) 3D spherical magneto-frictional (SMF) Model, either at high-resolution over a restricted range of solid angle or at lower resolution over a global domain, to determine the magnetic field and current density in the low corona. An SMF-generated initial field above an active region and the evolving electric field at the photosphere are used to drive (5) detailed magneto-hydrodynamic (MHD) simulations of active regions in the low corona. SMF or MHD solutions are then used to compute emissivity proxies that can be compared with coronal observations. Finally, a lower-resolution SMF magnetic field is used to initialize (6) a global MHD Model that is driven by an SMF electric-field time series to simulate the outer corona and heliosphere, ultimately connecting Sun to Earth. As a demonstration, this report features results of CGEM applied to observations of the evolution of NOAA Active Region 11158 in February 2011.
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the coronal global Evolutionary Model using hmi vector magnetogram and doppler data to Model the buildup of free magnetic energy in the solar corona
Social Work, 2015Co-Authors: G H Fisher, William P Abbett, D J Bercik, Maria D Kazachenko, B J Lynch, B T Welsch, J T Hoeksema, K Hayashi, Y LiuAbstract:The most violent space weather events (eruptive solar flares and coronal mass ejections) are driven by the release of free magnetic energy stored in the solar corona. Energy can build up on timescales of hours to days, and then may be suddenly released in the form of a magnetic eruption, which then propagates through interplanetary space, possibly impacting the Earth's space environment. Can we use the observed evolution of the magnetic and velocity fields in the solar photosphere to Model the evolution of the overlying solar coronal field, including the storage and release of magnetic energy in such eruptions? The objective of CGEM, the Coronal Global Evolutionary Model, funded by the NASA/NSF Space Weather Modeling program, is to develop and evaluate such a Model for the evolution of the coronal magnetic field. The evolving coronal magnetic field can then be used as a starting point for magnetohydrodynamic (MHD) Models of the corona, which can then be used to drive Models of heliospheric evolution and predictions of magnetic field and plasma density conditions at 1AU.
G H Fisher - One of the best experts on this subject based on the ideXlab platform.
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the coronal global Evolutionary Model using hmi vector magnetogram and doppler data to determine coronal magnetic field evolution
arXiv: Solar and Stellar Astrophysics, 2020Co-Authors: Todd J Hoeksema, William P Abbett, G H Fisher, D J Bercik, Maria D Kazachenko, K Hayashi, Mark C M Cheung, M L Derosa, Y LiuAbstract:The Coronal Global Evolutionary Model (CGEM) provides data-driven simulations of the magnetic field in the solar corona to better understand the build-up of magnetic energy that leads to eruptive events. The CGEM project has developed six capabilities. CGEM modules (1) prepare time series of full-disk vector magnetic field observations to (2) derive the changing electric field in the solar photosphere over active-region scales. This local electric field is (3) incorporated into a surface flux transport Model that reconstructs a global electric field that evolves magnetic flux in a consistent way. These electric fields drive a (4) 3D spherical magneto-frictional (SMF) Model, either at high-resolution over a restricted range of solid angle or at lower resolution over a global domain, to determine the magnetic field and current density in the low corona. An SMF-generated initial field above an active region and the evolving electric field at the photosphere are used to drive (5) detailed magneto-hydrodynamic (MHD) simulations of active regions in the low corona. SMF or MHD solutions are then used to compute emissivity proxies that can be compared with coronal observations. Finally, a lower-resolution SMF magnetic field is used to initialize (6) a global MHD Model that is driven by an SMF electric-field time series to simulate the outer corona and heliosphere, ultimately connecting Sun to Earth. As a demonstration, this report features results of CGEM applied to observations of the evolution of NOAA Active Region 11158 in February 2011.
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the coronal global Evolutionary Model using hmi vector magnetogram and doppler data to Model the buildup of free magnetic energy in the solar corona
Social Work, 2015Co-Authors: G H Fisher, William P Abbett, D J Bercik, Maria D Kazachenko, B J Lynch, B T Welsch, J T Hoeksema, K Hayashi, Y LiuAbstract:The most violent space weather events (eruptive solar flares and coronal mass ejections) are driven by the release of free magnetic energy stored in the solar corona. Energy can build up on timescales of hours to days, and then may be suddenly released in the form of a magnetic eruption, which then propagates through interplanetary space, possibly impacting the Earth's space environment. Can we use the observed evolution of the magnetic and velocity fields in the solar photosphere to Model the evolution of the overlying solar coronal field, including the storage and release of magnetic energy in such eruptions? The objective of CGEM, the Coronal Global Evolutionary Model, funded by the NASA/NSF Space Weather Modeling program, is to develop and evaluate such a Model for the evolution of the coronal magnetic field. The evolving coronal magnetic field can then be used as a starting point for magnetohydrodynamic (MHD) Models of the corona, which can then be used to drive Models of heliospheric evolution and predictions of magnetic field and plasma density conditions at 1AU.
Maria D Kazachenko - One of the best experts on this subject based on the ideXlab platform.
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the coronal global Evolutionary Model using hmi vector magnetogram and doppler data to determine coronal magnetic field evolution
arXiv: Solar and Stellar Astrophysics, 2020Co-Authors: Todd J Hoeksema, William P Abbett, G H Fisher, D J Bercik, Maria D Kazachenko, K Hayashi, Mark C M Cheung, M L Derosa, Y LiuAbstract:The Coronal Global Evolutionary Model (CGEM) provides data-driven simulations of the magnetic field in the solar corona to better understand the build-up of magnetic energy that leads to eruptive events. The CGEM project has developed six capabilities. CGEM modules (1) prepare time series of full-disk vector magnetic field observations to (2) derive the changing electric field in the solar photosphere over active-region scales. This local electric field is (3) incorporated into a surface flux transport Model that reconstructs a global electric field that evolves magnetic flux in a consistent way. These electric fields drive a (4) 3D spherical magneto-frictional (SMF) Model, either at high-resolution over a restricted range of solid angle or at lower resolution over a global domain, to determine the magnetic field and current density in the low corona. An SMF-generated initial field above an active region and the evolving electric field at the photosphere are used to drive (5) detailed magneto-hydrodynamic (MHD) simulations of active regions in the low corona. SMF or MHD solutions are then used to compute emissivity proxies that can be compared with coronal observations. Finally, a lower-resolution SMF magnetic field is used to initialize (6) a global MHD Model that is driven by an SMF electric-field time series to simulate the outer corona and heliosphere, ultimately connecting Sun to Earth. As a demonstration, this report features results of CGEM applied to observations of the evolution of NOAA Active Region 11158 in February 2011.
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the coronal global Evolutionary Model using hmi vector magnetogram and doppler data to Model the buildup of free magnetic energy in the solar corona
Social Work, 2015Co-Authors: G H Fisher, William P Abbett, D J Bercik, Maria D Kazachenko, B J Lynch, B T Welsch, J T Hoeksema, K Hayashi, Y LiuAbstract:The most violent space weather events (eruptive solar flares and coronal mass ejections) are driven by the release of free magnetic energy stored in the solar corona. Energy can build up on timescales of hours to days, and then may be suddenly released in the form of a magnetic eruption, which then propagates through interplanetary space, possibly impacting the Earth's space environment. Can we use the observed evolution of the magnetic and velocity fields in the solar photosphere to Model the evolution of the overlying solar coronal field, including the storage and release of magnetic energy in such eruptions? The objective of CGEM, the Coronal Global Evolutionary Model, funded by the NASA/NSF Space Weather Modeling program, is to develop and evaluate such a Model for the evolution of the coronal magnetic field. The evolving coronal magnetic field can then be used as a starting point for magnetohydrodynamic (MHD) Models of the corona, which can then be used to drive Models of heliospheric evolution and predictions of magnetic field and plasma density conditions at 1AU.
Mark Gerstein - One of the best experts on this subject based on the ideXlab platform.
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protein family and fold occurrence in genomes power law behaviour and Evolutionary Model
Journal of Molecular Biology, 2001Co-Authors: Jiang Qian, Nicholas M. Luscombe, Mark GersteinAbstract:Global surveys of genomes measure the usage of essential molecular parts, defined here as protein families, superfamilies or folds, in different organisms. Based on surveys of the first 20 completely sequenced gen- omes, we observe that the occurrence of these parts follows a power-law distribution. That is, the number of distinct parts (F) with a given geno- mic occurrence (V) decays as Fa aVb , with a few parts occurring many times and most occurring infrequently. For a given organism, the distri- butions of families, superfamilies and folds are nearly identical, and this is reflected in the size of the decay exponent b. Moreover, the exponent varies between different organisms, with those of smaller genomes dis- playing a steeper decay (i.e. larger b). Clearly, the power law indicates a preference to duplicate genes that encode for molecular parts which are already common. Here, we present a minimal, but biologically meaning- ful Model that accurately describes the observed power law. Although the Model performs equally well for all three protein classes, we focus on the occurrence of folds in preference to families and superfamilies. This is because folds are comparatively insensitive to the effects of point mutations that can cause a family member to diverge beyond detectable similarity. In the Model, genomes evolve through two basic operations: (i) duplication of existing genes; (ii) net flow of new genes. The flow term is closely related to the exponent b and can accommodate consider- able gene loss; however, we demonstrate that the observed data is repro- duced best with a net inflow, i.e. with more gene gain than loss. Moreover, we show that prokaryotes have much higher rates of gene acquisition than eukaryotes, probably reflecting lateral transfer. A further natural outcome from our Model is an estimation of the fold composition of the initial genome, which potentially relates to the common ancestor for modern organisms. Supplementary material pertaining to this work is available from www.partslist.org/powerlaw. # 2001 Academic Press
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protein family and fold occurrence in genomes power law behaviour and Evolutionary Model
Journal of Molecular Biology, 2001Co-Authors: Jiang Qian, Nicholas M. Luscombe, Mark GersteinAbstract:Global surveys of genomes measure the usage of essential molecular parts, defined here as protein families, superfamilies or folds, in different organisms. Based on surveys of the first 20 completely sequenced genomes, we observe that the occurrence of these parts follows a power-law distribution. That is, the number of distinct parts (F) with a given genomic occurrence (V) decays as F=aV(-b), with a few parts occurring many times and most occurring infrequently. For a given organism, the distributions of families, superfamilies and folds are nearly identical, and this is reflected in the size of the decay exponent b. Moreover, the exponent varies between different organisms, with those of smaller genomes displaying a steeper decay (i.e. larger b). Clearly, the power law indicates a preference to duplicate genes that encode for molecular parts which are already common. Here, we present a minimal, but biologically meaningful Model that accurately describes the observed power law. Although the Model performs equally well for all three protein classes, we focus on the occurrence of folds in preference to families and superfamilies. This is because folds are comparatively insensitive to the effects of point mutations that can cause a family member to diverge beyond detectable similarity. In the Model, genomes evolve through two basic operations: (i) duplication of existing genes; (ii) net flow of new genes. The flow term is closely related to the exponent b and can accommodate considerable gene loss; however, we demonstrate that the observed data is reproduced best with a net inflow, i.e. with more gene gain than loss. Moreover, we show that prokaryotes have much higher rates of gene acquisition than eukaryotes, probably reflecting lateral transfer. A further natural outcome from our Model is an estimation of the fold composition of the initial genome, which potentially relates to the common ancestor for modern organisms. Supplementary material pertaining to this work is available from www.partslist.org/powerlaw.
