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Institution

California Institute of Technology

EducationPasadena, California, United States
About: California Institute of Technology is a education organization based out in Pasadena, California, United States. It is known for research contribution in the topics: Galaxy & Redshift. The organization has 57649 authors who have published 146691 publications receiving 8620287 citations. The organization is also known as: Caltech & Cal Tech.
Topics: Galaxy, Redshift, Population, Star formation, Stars


Papers
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Journal ArticleDOI
TL;DR: In this paper, a review of integration algorithms for finite dimensional mechanical systems that are based on discrete variational principles is presented, including the Verlet, SHAKE, RATTLE, Newmark, and the symplectic partitioned Runge-Kutta schemes.
Abstract: This paper gives a review of integration algorithms for finite dimensional mechanical systems that are based on discrete variational principles. The variational technique gives a unified treatment of many symplectic schemes, including those of higher order, as well as a natural treatment of the discrete Noether theorem. The approach also allows us to include forces, dissipation and constraints in a natural way. Amongst the many specific schemes treated as examples, the Verlet, SHAKE, RATTLE, Newmark, and the symplectic partitioned Runge–Kutta schemes are presented.

1,657 citations

Journal ArticleDOI
27 Oct 1989-Science
TL;DR: Transformants obtained with various mitochondrial donors exhibited a respiratory phenotype that was in most cases distinct from that of the rho 0 parent or the donor, indicating that the genotypes of the mitochondrial and nuclear genomes as well as their specific interactions play a role in the respiratory competence of a cell.
Abstract: Two human cell lines (termed rho 0), which had been completely depleted of mitochondrial DNA (mtDNA) by long-term exposure to ethidium bromide, were found to be dependent on uridine and pyruvate for growth because of the absence of a functional respiratory chain. Loss of either of these two metabolic requirements was used as a selectable marker for the repopulation of rho 0 cells with exogenous mitochondria by complementation. Transformants obtained with various mitochondrial donors exhibited a respiratory phenotype that was in most cases distinct from that of the rho 0 parent or the donor, indicating that the genotypes of the mitochondrial and nuclear genomes as well as their specific interactions play a role in the respiratory competence of a cell.

1,654 citations

Proceedings ArticleDOI
01 Jul 1999
TL;DR: Methods to rapidly remove rough features from irregularly triangulated data intended to portray a smooth surface are developed and it is proved that these curvature and Laplacian operators have several mathematically-desirable qualities that improve the appearance of the resulting surface.
Abstract: In this paper, we develop methods to rapidly remove rough features from irregularly triangulated data intended to portray a smooth surface. The main task is to remove undesirable noise and uneven edges while retaining desirable geometric features. The problem arises mainly when creating high-fidelity computer graphics objects using imperfectly-measured data from the real world. Our approach contains three novel features: an implicit integration method to achieve efficiency, stability, and large time-steps; a scale-dependent Laplacian operator to improve the diffusion process; and finally, a robust curvature flow operator that achieves a smoothing of the shape itself, distinct from any parameterization. Additional features of the algorithm include automatic exact volume preservation, and hard and soft constraints on the positions of the points in the mesh. We compare our method to previous operators and related algorithms, and prove that our curvature and Laplacian operators have several mathematically-desirable qualities that improve the appearance of the resulting surface. In consequence, the user can easily select the appropriate operator according to the desired type of fairing. Finally, we provide a series of examples to graphically and numerically demonstrate the quality of our results.

1,651 citations

Journal ArticleDOI
TL;DR: In this paper, it was shown that compatible symplectic structures lead in a natural way to hereditary symmetries, and that a hereditary symmetry is an operator-valued function which immediately yields a hierarchy of evolution equations, each having infinitely many commuting symmetry all generated by this hereditary symmetry.

1,651 citations

Journal ArticleDOI
TL;DR: Providing a future energy supply that is secure and CO_2-neutral will require switching to nonfossil energy sources such as wind, solar, nuclear, and geothermal energy and developing methods for transforming the energy produced by these new sources into forms that can be stored, transported, and used upon demand.
Abstract: Two major energy-related problems confront the world in the next 50 years. First, increased worldwide competition for gradually depleting fossil fuel reserves (derived from past photosynthesis) will lead to higher costs, both monetarily and politically. Second, atmospheric CO_2 levels are at their highest recorded level since records began. Further increases are predicted to produce large and uncontrollable impacts on the world climate. These projected impacts extend beyond climate to ocean acidification, because the ocean is a major sink for atmospheric CO2.1 Providing a future energy supply that is secure and CO_2-neutral will require switching to nonfossil energy sources such as wind, solar, nuclear, and geothermal energy and developing methods for transforming the energy produced by these new sources into forms that can be stored, transported, and used upon demand.

1,651 citations


Authors

Showing all 58155 results

NameH-indexPapersCitations
Eric S. Lander301826525976
Donald P. Schneider2421622263641
George M. Whitesides2401739269833
Yi Chen2174342293080
David Baltimore203876162955
Edward Witten202602204199
George Efstathiou187637156228
Michael A. Strauss1851688208506
Jing Wang1844046202769
Ruedi Aebersold182879141881
Douglas Scott1781111185229
Hyun-Chul Kim1764076183227
Phillip A. Sharp172614117126
Timothy M. Heckman170754141237
Zhenan Bao169865106571
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023176
2022737
20214,684
20205,519
20195,321
20185,133