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Article type: Research Article
Authors: Xiong, Z.a; b | Zang, J.a | Liu, H.J.a | Karaoulanis, D.c | Zhou, Q.b | Bacalis, N.C.d; *
Affiliations: [a] Space Science and Technology Research Institute, Southeast University, Nanjing 21006, Jiangsu, China | [b] School of Economics and Management, Southeast University, Nanjing 210096, Jiangsu, China | [c] Korai 21, Halandri, GR-15233, Greece | [d] Theoretical and Physical Chemistry Institute, National Hellenic Research Foundation, Athens, GR-11635, Greece
Correspondence: [*] Corresponding author: N.C. Bacalis, Theoretical and Physical Chemistry Institute, National Hellenic Research Foundation, Athens, GR-11635, Greece. E-mail:[email protected]
Abstract: We demonstrate that, if a truncated expansion of a wave function is large, then the standard excited states computational method, of optimizing one ``root'' of a secular equation, according to the theorem of Hylleraas, Undheim and McDonald (HUM), tends to the correct excited wave function, comparable to that obtained via our proposed minimization principle for excited states [J. Comput. Meth. Sci. Eng. 8, 277 (2008)] (independent of orthogonality to lower lying approximants). However, if a truncated expansion of a wave function is small - that would be desirable for large systems - then the HUM-based methods may lead to an incorrect wave function - despite the correct energy (: according to the HUM theorem) whereas our method leads to correct, reliable, albeit small truncated wave functions. The demonstration is done in He excited states, using truncated series ``small'' expansions both in Hylleraas coordinates, and via standard configuration-interaction truncated ``small'' expansions, in comparison with corresponding ``large'' expansions. Beyond that, we give some examples of linear combinations of Hamiltonian eigenfunctions that have the energy of the 1st excited state, albeit they are orthogonal to it, demonstrating that the correct energy is not a criterion of correctness of the wave function.
Keywords: Excited states, minimization principle, HUM
DOI: 10.3233/JCM-170722
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 17, no. 3, pp. 347-361, 2017
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