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International Journal of Number Theory, 2011
In this paper, we set up an abstract theory of Murata densities, well tailored to general arithmetical semigroups. In [On certain densities of sets of primes, Proc. Japan Acad. Ser. A Math. Sci.56(7) (1980) 351–353; On some fundamental relations among certain asymptotic densities, Math. Rep.
Ballot, Christian, Car, Mireille
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In this paper, we set up an abstract theory of Murata densities, well tailored to general arithmetical semigroups. In [On certain densities of sets of primes, Proc. Japan Acad. Ser. A Math. Sci.56(7) (1980) 351–353; On some fundamental relations among certain asymptotic densities, Math. Rep.
Ballot, Christian, Car, Mireille
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Estimating densities, quantiles, quantile densities and density quantiles
Annals of the Institute of Statistical Mathematics, 1992zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Density and Density Matrices in Density Functional Theory
1990Publisher Summary This chapter discusses density and density matrices in density functional theory. It also discusses particle number and order; fundamental Hilbert spaces; matrices and restricted operators; local and nonlocal operators; equidensity orbitals and n representability; and negative consequences of a finite model.
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The density in density functional theory
Journal of Molecular Structure: THEOCHEM, 2010Abstract The paper begins with the definition of the electron density given by Schrodinger in 1926 and traces its use and many applications directed at the understanding of the properties of matter to its present day role in density functional theory and the development of the quantum mechanics of an open system.
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Current Opinion in Neurobiology, 1993
The postsynaptic density is a specialization of the nerve cell's submembrane cytoskeleton that is hypothesized to participate in the regulation of synaptic adhesion, transmitter receptor clustering, and modulation of receptor sensitivity. Until recently, many of the major proteins in the highly insoluble postsynaptic density fraction remained ...
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The postsynaptic density is a specialization of the nerve cell's submembrane cytoskeleton that is hypothesized to participate in the regulation of synaptic adhesion, transmitter receptor clustering, and modulation of receptor sensitivity. Until recently, many of the major proteins in the highly insoluble postsynaptic density fraction remained ...
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Cell and Tissue Research, 2006
Glutamatergic synapses in the central nervous system are characterized by an electron-dense web underneath the postsynaptic membrane; this web is called the postsynaptic density (PSD). PSDs are composed of a dense network of several hundred proteins, creating a macromolecular complex that serves a wide range of functions. Prominent PSD proteins such as
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Glutamatergic synapses in the central nervous system are characterized by an electron-dense web underneath the postsynaptic membrane; this web is called the postsynaptic density (PSD). PSDs are composed of a dense network of several hundred proteins, creating a macromolecular complex that serves a wide range of functions. Prominent PSD proteins such as
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Density Matrices and Density Operators
1996As was repeatedly seen in the last chapter, for computing most of the usual matrix elements only a few of the many coordinates of an N-particle wavefunction are used, where due to the symmetry properties it is irrelevant which ones. Density matrices are a tool to extract the relevant information out of such monstrous constructs as are N-particle ...
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Journal of Mathematical Physics, 1971
A characterization of the weak limits of states is given, leading to an extension of a theorem of Gudder and the verification of a conjecture by ...
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A characterization of the weak limits of states is given, leading to an extension of a theorem of Gudder and the verification of a conjecture by ...
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International Journal of Bifurcation and Chaos, 1992
Let M be a closed surface without boundary, possibly a sphere or a torus. A repetitive process determines a large number of points xn distributed more or less uniformly over M. We cannot observe these points, nor do we know what M is. There is a smooth function f:M→R (not given) and we measure the numbers yn≡f(xn).
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Let M be a closed surface without boundary, possibly a sphere or a torus. A repetitive process determines a large number of points xn distributed more or less uniformly over M. We cannot observe these points, nor do we know what M is. There is a smooth function f:M→R (not given) and we measure the numbers yn≡f(xn).
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