Results 1 to 10 of about 672,138 (280)
The density matrix renormalization group for ab initio quantum chemistry [PDF]
, 2014 During the past 15 years, the density matrix renormalization group (DMRG) has become increasingly important for ab initio quantum chemistry. Its underlying wavefunction ansatz, the matrix product state (MPS), is a low-rank decomposition of the full ...
Van Neck, Dimitri, Wouters, Sebastian
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, 2020 In the first part of this study (Paper I), we introduced the systematic improvement probability (SIP) as a tool to assess the level of improvement on absolute errors to be expected when switching between two computational chemistry methods.
Pernot, Pascal, Savin, Andreas
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Convection and chemistry effects in CVD: A 3-D analysis for silicon deposition [PDF]
, 1989 The computational fluid dynamics code FLUENT has been adopted to simulate the entire rectangular-channel-like (3-D) geometry of an experimental CVD reactor designed for Si deposition.
Chait, A. +3 more
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N-representability is QMA-complete [PDF]
, 2006 We study the computational complexity of the N-representability problem in quantum chemistry. We show that this problem is QMA-complete, which is the quantum generalization of NP-complete.
Christandl, M. +2 more
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Deep learning for computational chemistry [PDF]
Journal of Computational Chemistry, 2017 The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on multilayer neural networks.
Garrett B. Goh +2 more
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Autonomy and Automation. Computational modeling, reduction, and explanation in quantum chemistry [PDF]
, 2014 This paper discusses how computational modeling combines the autonomy of models with the automation of computational procedures. In particular, the case of ab initio methods in quantum chemistry will be investigated to draw two lessons from the analysis ...
Lenhard, Johannes
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Use of metamodels for rapid discovery of narrow bandgap oxide photocatalysts
iScience, 2021 Summary: New photocatalysts are traditionally identified through trial-and-error methods. Machine learning has shown considerable promise for improving the efficiency of photocatalyst discovery from a large potential pool. Here, we describe a multi-step,
Haoxin Mai +6 more
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A coarse-grained protein model in a water-like solvent [PDF]
, 2013 Simulations employing an explicit atom description of proteins in solvent can be computationally expensive. On the other hand, coarse-grained protein models in implicit solvent miss essential features of the hydrophobic effect, especially its temperature
Buldyrev, Sergey V. +5 more
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Computational Chemistry on Quantum Computers
CoRR, 2019 The purpose of this experiment was to use the known analytical techniques to study the creation, simulation, and measurements of molecular Hamiltonians. The techniques used consisted of the Linear Combination of Atomic Orbitals (LCAO), the Linear Combination of Unitaries (LCU), and the Phase Estimation Algorithm (PEA).
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Searching for stable fullerenes in space with computational chemistry
, 2019 We report a computational study of the stability and infrared (IR) vibrational spectra of neutral and singly ionised fullerene cages containing between 44 and 70 carbon atoms.
Cami, Jan +5 more
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