Massively parallel quantum chemical density matrix renormalization group method

• URL: http://arxiv.org/abs/2001.04890v2
• Date: Fri, 19 Jun 2020 16:15:18 GMT
• Title: Massively parallel quantum chemical density matrix renormalization group method
• Authors: Ji\v{r}\'i Brabec, Jan Brandejs, Karol Kowalski, Sotiris Xantheas, \"Ors Legeza, and Libor Veis
• Abstract summary: We present to the best of our knowlegde, the first attempt to exploit the supercomputer platform for quantum chemical density matrix renormalization group (QC-DMRG) calculations. We have developed the parallel scheme based on the in-house MPI global memory library, which combines operator and symmetry sector parallelisms. In case of the largest calculation, which is the nitrogenase FeMo cofactor cluster with the active space comprising 113 electrons in 76 orbitals and bond dimension equal to 6000, our parallel approach scales up to approximately 2000 CPU cores.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present, to the best of our knowlegde, the first attempt to exploit the supercomputer platform for quantum chemical density matrix renormalization group (QC-DMRG) calculations. We have developed the parallel scheme based on the in-house MPI global memory library, which combines operator and symmetry sector parallelisms, and tested its performance on three different molecules, all typical candidates for QC-DMRG calculations. In case of the largest calculation, which is the nitrogenase FeMo cofactor cluster with the active space comprising 113 electrons in 76 orbitals and bond dimension equal to 6000, our parallel approach scales up to approximately 2000 CPU cores.

Related papers

• Neutron-nucleus dynamics simulations for quantum computers [49.369935809497214]
  We develop a novel quantum algorithm for neutron-nucleus simulations with general potentials. It provides acceptable bound-state energies even in the presence of noise, through the noise-resilient training method. We introduce a new commutativity scheme called distance-grouped commutativity (DGC) and compare its performance with the well-known qubit-commutativity scheme.
  arXiv  Detail & Related papers  (2024-02-22T16:33:48Z)
• A distributed multi-GPU ab initio density matrix renormalization group algorithm with applications to the P-cluster of nitrogenase [1.7444066202370399]
  We present the first distributed multi- GPU (Graphics Processing Unit) emphab initio density matrix renormalization (DMRG) algorithm. We are able to reach an unprecedentedly large bond dimension $D=14000$ on 48 GPU. This is nearly three times larger than the bond dimensions reported in previous DMRG calculations for the same system using only CPUs.
  arXiv  Detail & Related papers  (2023-11-06T04:01:26Z)
• A hybrid quantum-classical algorithm for multichannel quantum scattering of atoms and molecules [62.997667081978825]
  We propose a hybrid quantum-classical algorithm for solving the Schr"odinger equation for atomic and molecular collisions. The algorithm is based on the $S$-matrix version of the Kohn variational principle, which computes the fundamental scattering $S$-matrix. We show how the algorithm could be scaled up to simulate collisions of large polyatomic molecules.
  arXiv  Detail & Related papers  (2023-04-12T18:10:47Z)
• Modeling singlet fission on a quantum computer [5.444073446314462]
  We present a use case of practical utility of quantum computing by employing a quantum computer in the investigation of the linear H$_4$ molecule. We leverage a series of independent strategies to bring down the overall cost of the quantum computations.
  arXiv  Detail & Related papers  (2023-01-13T20:29:57Z)
• A self-consistent field approach for the variational quantum eigensolver: orbital optimization goes adaptive [52.77024349608834]
  We present a self consistent field approach (SCF) within the Adaptive Derivative-Assembled Problem-Assembled Ansatz Variational Eigensolver (ADAPTVQE) This framework is used for efficient quantum simulations of chemical systems on nearterm quantum computers.
  arXiv  Detail & Related papers  (2022-12-21T23:15:17Z)
• Quantum Clustering with k-Means: a Hybrid Approach [117.4705494502186]
  We design, implement, and evaluate three hybrid quantum k-Means algorithms. We exploit quantum phenomena to speed up the computation of distances. We show that our hybrid quantum k-Means algorithms can be more efficient than the classical version.
  arXiv  Detail & Related papers  (2022-12-13T16:04:16Z)
• Photonic Quantum Computing For Polymer Classification [62.997667081978825]
  Two polymer classes visual (VIS) and near-infrared (NIR) are defined based on the size of the polymer gaps. We present a hybrid classical-quantum approach to the binary classification of polymer structures.
  arXiv  Detail & Related papers  (2022-11-22T11:59:52Z)
• Preentangling Quantum Algorithms -- the Density Matrix Renormalization Group-assisted Quantum Canonical Transformation [0.0]
  We propose the use of parameter-free preentanglers as initial states for quantum algorithms. We find this strategy to require significantly less parameters than corresponding generalized unitary coupled cluster circuits.
  arXiv  Detail & Related papers  (2022-09-15T07:35:21Z)
• Localized Quantum Chemistry on Quantum Computers [0.6649973446180738]
  Quantum chemistry calculations are typically limited by the computation cost that scales exponentially with the size of the system. We present a quantum algorithm that combines a localization of multireference wave functions of chemical systems with quantum phase estimation.
  arXiv  Detail & Related papers  (2022-03-03T20:52:22Z)
• Quantum-Classical Hybrid Algorithm for the Simulation of All-Electron Correlation [58.720142291102135]
  We present a novel hybrid-classical algorithm that computes a molecule's all-electron energy and properties on the classical computer. We demonstrate the ability of the quantum-classical hybrid algorithms to achieve chemically relevant results and accuracy on currently available quantum computers.
  arXiv  Detail & Related papers  (2021-06-22T18:00:00Z)
• On the Ordering of Sites in the Density Matrix Renormalization Group using Quantum Mutual Information [0.0]
  The density matrix renormalization group (DMRG) of White 1992 remains to this day an integral component of many state-of-the-art methods for efficiently strongly correlated quantum systems. In quantum chemistry, QC-DMRG became a powerful tool for ab initio calculations with the non-relativistic Schr"odinger equation.
  arXiv  Detail & Related papers  (2021-03-01T16:24:37Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.