where n runs from 0 to infinity, meaning the full matrix is infinite-dimensional. My Questions: 1- How can I define this density matrix in Mathematica? 2- Is there a more efficient way to represent it symbolically? 3-What is the best approach to compute its eigenvalues numerically?
When you’re indenting your code, the official Python style guide called PEP 8 recommends using 4 space characters to represent one indentation level. Most text editors that are set up to work with Python files will automatically insert 4 spaces if you press the Tab key on your keyboard. You...
Skelton. A symbolic algorithm for determining convexity of a matrix function: How to get schur complements out of your life. In Proceedings of the 39th IEEE Conference on Decision and Control, 2000.A Symbolic Algorithm For Determining Convexity of A Matrix Function - Camino, Helton, et al. -...
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Not a function: “one to many“. In other words, let’s say you had one x-value that maps to many y-values. For example, — in coordinate notation — (2,1) and (2,10). If the first number (the x-value) repeats, then you do not have a function. To put that another way,...
Holographic correlators are the direct AdS analog of S-matrix amplitudes, to which in fact they reduce in a suitable limit, so we might hope to find for them analogous computational shortcuts and elegant geometric structures. A related motivation to revisit this problem is our prejudice that for...
A result of the Pareto Principle is the Pareto Chart. The Pareto Chart is used to graphically summarize and display the relative importance of the differences between groups of data, or to visually represent the Vital Few versus the Trivial Many. ...
D2) represent the mutual projections of the three vectors involved. In the same way that a distribution of electrical charges whose centroids do not coincide, gives an electric dipole character to a protein, a distribution of hydrophobic charges can show a hydrophobic polarization. Based on ...
represent the eigenvalues of the covariance matrix. To obtain the orientation of the ellipse, we simply calculate the angle of the largest eigenvector towards the x-axis: (4) where is the eigenvector of the covariance matrix that corresponds to the largest eigenvalue. ...
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