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Welcome to the club of academic migrants! I didn't take any university-level chemistry courses during my undergrad years (except a special topics course for graduate students called "bioelectronics" which one might say was more physics and biology than chemistry). I was much more interested in physics and biology (and math) than chemistry, so I ...


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I'm grad student about to finish their PhD, so you may find my perspective valuable. For reference, my undergrad degree was in physics and math, where I did big data analysis on high energy data gathered at CERN. I had some much earlier experience working in a condensed matter lab, yet gained very little (to no) chemistry experience. To date, I have never ...


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One way that matrix information can be passed into a learning algorithm is by diagonalizing it and instead passing in the sorted eigenvalues. An example of this in a fairly recent paper[1] is the use of Coulomb Matrix Eigenvalues (CMEs) in a number of different regression models as a descriptor to distinguish isomers of a molecule (there are Mathematica ...


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Answering "How does a beginner condensed matter theorist working on real materials, get up to speed?" is not as easy as it could appear. From my own experience, if you are a condensed matter theory PhD student and only focus on condensed matter, you will (should?) grow faster. In my case, I am a physicist and also made my PhD in theoretical ...


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Moller-Plesset (MPn) Moller-Plesset perturbation theory combines the Rayleigh-Schrodinger style of perturbation expansion with a particular partitioning of the molecular Hamiltonian in order to compute the correlation energy (and/or perturbed wavefunctions). We express the Hamiltonian $H$ as an unperturbed part $H_0$ and a perturbation $V$. For the ...


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