108 citations · 329 across the 7 of their papers we have counts for
7 papers
Equivalence of Particle-Particle Random Phase Approximation Correlation Energy and Ladder-Coupled-Cluster-Double
Degao Peng, Stephan N. Steinmann, Helen van Aggelen +1
We present an analytical proof and numerical demonstrations of the equivalence of the correlation energy from particle-particle random phase approximation (pp-RPA) and ladder-coupl…
Exchange-Correlation Energy from Pairing Matrix Fluctuation and the Particle-Particle Random Phase Approximation
Helen van Aggelen, Yang Yang, Weitao Yang
We formulate an adiabatic connection for the exchange-correlation energy in terms of pairing matrix fluctuation. This connection opens new channels for density functional approxima…
The tensor hypercontracted parametric reduced density matrix algorithm: coupled-cluster accuracy with O(r^4) scaling
Neil Shenvi, Helen Van Aggelen, Yang Yang +3
Tensor hypercontraction is a method that allows the representation of a high-rank tensor as a product of lower-rank tensors. In this paper, we show how tensor hypercontraction can…
Variational two-particle density matrix calculation for the Hubbard model below half filling using spin-adapted lifting conditions
Brecht Verstichel, Helen van Aggelen, Ward Poelmans +1
The variational determination of the two-particle density matrix is an interesting, but not yet fully explored technique that allows to obtain ground-state properties of a quantum…
A primal-dual semidefinite programming algorithm tailored to the variational determination of the two-body density matrix
B. Verstichel, H. van Aggelen, D. Van Neck +2
The quantum many-body problem can be rephrased as a variational determination of the two-body reduced density matrix, subject to a set of N-representability constraints. The mathem…
Variational density matrix optimization using semidefinite programming
Brecht Verstichel, Helen van Aggelen, Dimitri Van Neck +2
We discuss how semidefinite programming can be used to determine the second-order density matrix directly through a variational optimization. We show how the problem of characteriz…