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Degeneracy and Redundancy in Active Inference [PDF]
The notions of degeneracy and redundancy are important constructs in many areas, ranging from genomics through to network science. Degeneracy finds a powerful role in neuroscience, explaining key aspects of distributed processing and structure-function ...
Thomas Parr +2 more
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Gate-tunable subband degeneracy in semiconductor nanowires [PDF]
Degeneracy and symmetry have a profound relation in quantum systems. Here, we report gate-tunable subband degeneracy in PbTe nanowires with a nearly symmetric cross-sectional shape.
Zhan Cao, Hao Zhang, Dong Liu
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AbstractMotivated by the study of greedy algorithms for graph coloring, we introduce a new graph parameter, which we call weak degeneracy. By definition, every ‐degenerate graph is also weakly ‐degenerate. On the other hand, if is weakly ‐degenerate, then (and, moreover, the same bound holds for the list‐chromatic and even the DP‐chromatic number of )
Anton Bernshteyn
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Densities of degeneracies and near-degeneracies
Physical Review A, 1993The eigenvalues of a quantum system depending on two parameters become degenerate at isolated points in the parameter space, which are called diabolical points because of their double-cone structure. Varying one parameter produces near-degeneracies termed avoided crossings. Some results on the density of these objects in parameter space can be obtained
, Wilkinson, , Austin
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SIAM Journal on Scientific and Statistical Computing, 1984
The paper surveys some of the more commonly used methods for approximating the rank of a matrix X, with particular attention to the effects of errors. It is supposed that X itself cannot be observed and only a perturbed matrix \(X=X+E\) is given.
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The paper surveys some of the more commonly used methods for approximating the rank of a matrix X, with particular attention to the effects of errors. It is supposed that X itself cannot be observed and only a perturbed matrix \(X=X+E\) is given.
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International Journal of Mathematics, 1996
Let \(X_r\) be the degeneracy locus of rank \(r\) of a morphism \(\varphi\) of vector bundles over a smooth irreducible variety \(X\), and \({\mathcal I}_{X_r}\) the ideal sheaf of \(X_r\). We quote from the author's introduction: Our aim is to study the cohomology of \({\mathcal I}_{X_r}\). In particular we want to know if \(H^1 ({\mathcal I}_{X_r})=0\
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Let \(X_r\) be the degeneracy locus of rank \(r\) of a morphism \(\varphi\) of vector bundles over a smooth irreducible variety \(X\), and \({\mathcal I}_{X_r}\) the ideal sheaf of \(X_r\). We quote from the author's introduction: Our aim is to study the cohomology of \({\mathcal I}_{X_r}\). In particular we want to know if \(H^1 ({\mathcal I}_{X_r})=0\
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Interdimensional degeneracies, near degeneracies, and their applications
The Journal of Chemical Physics, 1986Recently developed approximation methods for quantum mechanical problems which treat the spatial dimension D as an expansion parameter offer approximations to energy levels at arbitrary D. Rather than simply being a detour to the D=3 case, there is physical interest in nonphysical values of D due to degeneracies between states in different dimensions ...
D. J. Doren, D. R. Herschbach
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Twisted Cubic: Degeneracy Degree and Relationship with General Degeneracy
2010Fundamental matrix, drawing geometric relationship between two images, plays an important role in 3-dimensional computer vision. Degenerate configurations of space points and two camera optical centers affect stability of computation for fundamental matrix.
Tian Lan, Yihong Wu 0002, Zhanyi Hu
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On a Degeneracy Theorem of Kramers
American Journal of Physics, 1952There is a theorem due to Kramers which states that the energy states of systems with an odd number of electrons remain at least doubly degenerate in the presence of any purely electric fields. The physical significance of this theorem, its proof, and a discussion of the relationship of the Kramers degeneracy and the Wigner time-reversal operation are ...
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Journal of the Operational Research Society, 1992
Summary: Two projected gradient algorithms for linear programming are discussed. The first uses a conventional enough steepest edge approach, and implements a version of Wolfe's method for resolving any problems of degeneracy. The second makes use of a steepest descent direction which is calculated by solving a linear least squares problem subject to ...
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Summary: Two projected gradient algorithms for linear programming are discussed. The first uses a conventional enough steepest edge approach, and implements a version of Wolfe's method for resolving any problems of degeneracy. The second makes use of a steepest descent direction which is calculated by solving a linear least squares problem subject to ...
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