The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
CheMPS2: A free open-source spin-adapted implementation of the density matrix renormalization group for ab initio quantum chemistry
Open accessAbstract
Abstract The density matrix renormalization group (DMRG) has become an indispensable numerical tool to find exact eigenstates of finite-size quantum systems with strong correlation. In the fields of condensed matter, nuclear structure and molecular electronic structure, it has significantly extended the system sizes that can be handled compared to full configuration interaction, without losing numerical accuracy. For quantum chemistry (QC), the most efficient implementations of DMRG require the incorporation of particle number, spin and point group symmetries in the underlying matrix product state (MPS) ansatz, as well as the use of so-called complementary operators. The symmetries introduce a sparse block structure in the MPS ansatz and in the intermediary contracted tensors. If a symmetry is non-abelian, the Wigner–Eckart theorem allows to factorize a tensor into a Clebsch–Gordan coefficient and a reduced tensor. In addition, the fermion signs have to be carefully tracked. Because of these challenges, implementing DMRG efficiently for QC is not straightforward. Efficient and freely available implementations are therefore highly desired. In this work we present CheMPS2, our free open-source spin-adapted implementation of DMRG for ab initio QC. Around CheMPS2, we have implemented the augmented Hessian Newton–Raphson complete active space self-consistent field method, with exact Hessian. The bond dissociation curves of the 12 lowest states of the carbon dimer were obtained at the DMRG(28 orbitals, 12 electrons, D SU(2) = 2500 )/cc-pVDZ level of theory. The contribution of 1 s core correlation to the X 1 Σ g + bond dissociation curve of the carbon dimer was estimated by comparing energies at the DMRG(36o, 12e, D SU(2) = 2500 )/cc-pCVDZ and DMRG-SCF(34o, 8e, D SU(2) = 2500 )/cc-pCVDZ levels of theory. Program summary Program title: CheMPS2 Catalogue identifier: AESE_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AESE_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 2 No. of lines in distributed program, including test data, etc.: 131472 No. of bytes in distributed program, including test data, etc.: 1645700 Distribution format: tar.gz Programming language: C++. Computer: x86-64. Operating system: Scientific Linux 6.0. RAM: 10 MB–64 GB Classification: 16.1. External routines: Basic Linear Algebra Subprograms (BLAS), Linear Algebra Package (LAPACK), GNU Scientific Library (GSL), and Hierarchical Data Format Release 5 (HDF5) Nature of problem: The many-body Hilbert space grows exponentially with the number of single-particle states. Exact diagonalization solvers can therefore only handle small systems, of up to 18 electrons in 18 orbitals. Interesting active spaces are often significantly larger. Solution method: The density matrix renormalization group allows the extension of the size of active spaces, for which numerically exact solutions can be found, to about 40 electrons in 40 orbitals. In addition, it provides a rigorous variational upper bound to energies, as it has an underlying wavefunction ansatz, the matrix product state. Restrictions: Our implementation of the density matrix renormalization group is spin-adapted. This means that targeted eigenstates in the active space are exact eigenstates of the total electronic spin operator. Hamiltonians which break this symmetry (a magnetic field term for example) cannot be handled by our code. As electron repulsion integrals in Gaussian basis sets have eightfold permutation symmetry, we have used this property in our code. Unusual features: The nature of the matrix product state ansatz allows for exact spin coupling. In CheMPS2, the total electronic spin is imposed (not just the spin projection), in addition to the particle-number and abelian point-group symmetries. Running time: The running time depends on the size of the targeted active space, the number of desired eigenstates, their symmetry, the density of states, the individual orbital symmetries, the orbital ordering, the desired level of convergence, and the chosen convergence scheme. To converge a single point of one of the dissociation curves of the carbon dimer ( D ∞ h → D 2 h symmetry) in the cc-pVDZ basis (28 orbitals; their ordering is described in Section 5.3 ) with 2500 reduced renormalized basis states (see the convergence scheme in Section 5.4 ; the variational energy then lies 0.1 m E h above the fully converged result) takes about 8 h on a single node with a dual-socket octa-core Intel Xeon Sandy Bridge (E5-2670) (16 cores at 2.6 GHz), and requires 6 GB of RAM.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Density matrix formulation for quantum renormalization groups
White, S. R. (1992) · Physical Review Letters · doi:10.1103/physrevlett.69.2863 · Cited by 7,702
The density-matrix renormalization group in the age of matrix product states
Schollwöck, U. (2011) · Annals of Physics · doi:10.1016/j.aop.2010.09.012 · Cited by 4,818
Molecular Electronic‐Structure Theory
Helgaker, T., Jørgensen, P., & Olsen, J. (2000) · doi:10.1002/9781119019572 · Cited by 2,594
Ab initio quantum chemistry using the density matrix renormalization group
White, S. R., & Martin, R. L. (1999) · The Journal of Chemical Physics · doi:10.1063/1.478295 · Cited by 558
Legeza, Ö., Röder, J., & Hess, B. A. (2003) · Physical Review B · doi:10.1103/physrevb.67.125114 · Cited by 263
Simulating strongly correlated quantum systems with tree tensor networks
Murg, V., Verstraete, F., Legeza, Ö., & Noack, R. M. (2010) · Physical Review B · doi:10.1103/physrevb.82.205105 · Cited by 245
Complete-graph tensor network states: a new fermionic wave function ansatz for molecules
Marti, K. H., Bauer, B., Reiher, M., Troyer, M., & Verstraete, F. (2010) · New Journal of Physics · doi:10.1088/1367-2630/12/10/103008 · Cited by 87
Analytic response theory for the density matrix renormalization group
Dorando, J. J., Hachmann, J., & Chan, G. K.-L. (2009) · The Journal of Chemical Physics · doi:10.1063/1.3121422 · Cited by 60
Nakatani, N., Wouters, S., Van Neck, D., & Chan, G. K.-L. (2014) · The Journal of Chemical Physics · doi:10.1063/1.4860375 · Cited by 59
Self-citation
Cited by
P y SCF: the Python‐based simulations of chemistry framework
Sun, Q., Berkelbach, T. C., Blunt, N. S., Booth, G. H., Guo, S., Li, Z., Liu, J., McClain, J. D., Sayfutyarova, E. R., Sharma, S., et al. (2018) · WIREs Computational Molecular Science · doi:10.1002/wcms.1340 · Cited by 1,741
Self-citationRecent developments in the P y SCF program package
Sun, Q., Zhang, X., Banerjee, S., Bao, P., Barbry, M., Blunt, N. S., Bogdanov, N. A., Booth, G. H., Chen, J., Cui, Z.-H., et al. (2020) · The Journal of Chemical Physics · doi:10.1063/5.0006074 · Cited by 1,259
Self-citationParrish, R. M., Burns, L. A., Smith, D. G. A., Simmonett, A. C., DePrince, A. E., Hohenstein, E. G., Bozkaya, U., Sokolov, A. Y., Di Remigio, R., Richard, R. M., et al. (2017) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.7b00174 · Cited by 1,249
OpenMolcas: From Source Code to Insight
Fdez. Galván, I., Vacher, M., Alavi, A., Angeli, C., Aquilante, F., Autschbach, J., Bao, J. J., Bokarev, S. I., Bogdanov, N. A., Carlson, R. K., et al. (2019) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.9b00532 · Cited by 1,114
Self-citationModern quantum chemistry with [Open]Molcas
Aquilante, F., Autschbach, J., Baiardi, A., Battaglia, S., Borin, V. A., Chibotaru, L. F., Conti, I., De Vico, L., Delcey, M., Fdez. Galván, I., et al. (2020) · The Journal of Chemical Physics · doi:10.1063/5.0004835 · Cited by 499
Metadata
- Authors
- Wouters, S., Poelmans, W., Ayers, P. W., & Van Neck, D.
- Venue
- Computer Physics Communications
- Publisher
- Elsevier BV
- Published
- 2014-06
- Volume
- 185
- Issue
- 6
- Pages
- 1501-1514
- ISSN
- 0010-4655 (ISSN-L)
- OpenAlex
- W2024891511
- Cited by
- 181
- References
- 9
- FWCI
- 10.15
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: CheMPS2: A free open-source spin-adapted implementation of the density matrix renormalization group for ab initio quantum chemistry. https://app.cochat.ai/papers/10.1016/j.cpc.2014.01.019
- The paper
- Wouters, S., Poelmans, W., Ayers, P. W., & Van Neck, D. (2014). CheMPS2: A free open-source spin-adapted implementation of the density matrix renormalization group for ab initio quantum chemistry. Computer Physics Communications. https://doi.org/10.1016/j.cpc.2014.01.019
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.