2019
DOI: 10.1080/00268976.2018.1564848
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The coupled-cluster formalism – a mathematical perspective

Abstract: The Coupled-Cluster theory is one of the most successful high precision methods used to solve the stationary Schrödinger equation. In this article, we address the mathematical foundation of this theory with focus on the advances made in the past decade. Rather than solely relying on spectral gap assumptions (non-degeneracy of the ground state), we highlight the importance of coercivity assumptions -Gårding type inequalities -for the local uniqueness of the Coupled-Cluster solution. Based on local strong monoto… Show more

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Cited by 17 publications
(25 citation statements)
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“…For a further discussion on spectral gap and Gårding inequalities in CC theories we refer to [20]. Moreover, in agreement with Section 2, we suppose…”
Section: Local Uniqueness and Residualsupporting
confidence: 68%
“…For a further discussion on spectral gap and Gårding inequalities in CC theories we refer to [20]. Moreover, in agreement with Section 2, we suppose…”
Section: Local Uniqueness and Residualsupporting
confidence: 68%
“…Monotonicity is an important notion in connection with the local analysis of the CC method and its variations [23][24][25][26][27]34]. The use of monotonicity in the analysis of the standard CC method was introduced by Schneider and Rohwedder [25,27].…”
Section: Truncations and Monotonicity Analysismentioning
confidence: 99%
“…It also connects spectral gaps, e.g. HOMO-LUMO gap, to stability constants within the analysis [24]. (See also the steerable CAS-ext gap connected to the tailored CC method [35] that treats quasi-degenerate systems [36].…”
Section: Truncations and Monotonicity Analysismentioning
confidence: 99%
See 1 more Smart Citation
“…For an analysis of standard CC without the BIVP, see the works of Rohwedder and Schneider. 30,31 A key analysis tool for studying CC theory 3,[29][30][31][32][33] was that of local strong monotonicity 4 of the flipped gradient F :Ṽ ⊕ V →Ṽ ⊕ V given by…”
Section: Local Strong Monotonicity Analysismentioning
confidence: 99%