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--- numexercises7_14 [2014/07/14 08:00]
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 ===== Numerical Exercises for Monday July 14 =====
-  - In your favorite programming language, make a program to construct a $NxN$ matrix
+  * Install Git, and try out some of the commands covered in Morten or Nicolas's lecture slides ({{:computing.pdf|}} {{:talentdftguides.pdf|}}) for your codes in the following problems.
+  * In your favorite programming language, make a program to construct a real symmetric $NxN$ matrix. Diagonalize it using the appropriate LAPACK or GSL routine, and write out some number of the lowest eigenvalues. (Suggestion: You might find it useful to use Mathematica (available on the ECT* computers) to diagonalize a small matrix that you can benchmark against.) This will help you test that you've linked to the GSL or LAPACK library.
+  * The code {{:coulomboscrelme.f90.zip|}} calculates the relative matrix elements $\langle nl|V|n'l\rangle$ in HO states. From this, construct a subroutine that returns the properly normalized $r$-space HO wf's. For some basic background on HO wf's, see  {{:ho_spherical.pdf| here}}.
+  * Check numerically that the constructed HO wf's are orthonormal. To do this, you will want to use Gaussian quadrature to discretize the integrals. Gaussian quadrature is discussed a bit in {{:ho_spherical.pdf| }}. If you don't have a routine to calculate quadrature points/weights, take advantage of Google to find a canned routine to do this for you.
+  * Construct a subroutine that returns relative HO matrix elements of the Minnesota NN potential. The definition of the Minnesota potential is here:

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