The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Canonical sampling through velocity rescaling
Open accessAbstract
The authors present a new molecular dynamics algorithm for sampling the canonical distribution. In this approach the velocities of all the particles are rescaled by a properly chosen random factor. The algorithm is formally justified and it is shown that, in spite of its stochastic nature, a quantity can still be defined that remains constant during the evolution. In numerical applications this quantity can be used to measure the accuracy of the sampling. The authors illustrate the properties of this new method on Lennard-Jones and TIP4P water models in the solid and liquid phases. Its performance is excellent and largely independent of the thermostat parameter also with regard to the dynamic properties.
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
Computer Simulation of Liquids
Allen, M. P., & Tildesley, D. J. (2017) · doi:10.1093/oso/9780198803195.001.0001 · Cited by 20,945
Cited by
Abraham, M. J., Murtola, T., Schulz, R., Páll, S., Smith, J. C., Hess, B., & Lindahl, E. (2015) · SoftwareX · doi:10.1016/j.softx.2015.06.001 · Cited by 27,190
Computer Simulation of Liquids
Allen, M. P., & Tildesley, D. J. (2017) · doi:10.1093/oso/9780198803195.001.0001 · Cited by 20,945
Well-Tempered Metadynamics: A Smoothly Converging and Tunable Free-Energy Method
Barducci, A., Bussi, G., & Parrinello, M. (2008) · Physical Review Letters · doi:10.1103/physrevlett.100.020603 · Cited by 3,184
Self-citationMartini 3: A general purpose force field for coarse-grained molecular dynamics
Souza, P. C. T., Alessandri, R., Barnoud, J., Thallmair, S., Faustino, I., Grünewald, F., Patmanidis, I., Abdizadeh, H., Bruininks, B. M. H., Wassenaar, T. A., et al. (2021) · Nature Methods · doi:10.1038/s41592-021-01098-3 · Cited by 1,551
Wassenaar, T. A., Ingólfsson, H. I., Böckmann, R. A., Tieleman, D. P., & Marrink, S. J. (2015) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.5b00209 · Cited by 1,174
Metadata
- Authors
- Bussi, G., Donadio, D., & Parrinello, M.
- Venue
- The Journal of Chemical Physics
- Publisher
- AIP Publishing
- Published
- 2007-01-03
- Volume
- 126
- Issue
- 1
- Pages
- 014101-014101
- ISSN
- 0021-9606 (ISSN-L)
- 1089-7690
- OpenAlex
- W2057477511
- Cited by
- 18,089
- References
- 1
- FWCI
- 24.27
- 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
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.