| 001 | 872984 | ||
| 005 | 20210130004339.0 | ||
| 024 | 7 | _ | |a arXiv:1912.03278 |2 arXiv |
| 024 | 7 | _ | |a 2128/24176 |2 Handle |
| 024 | 7 | _ | |a altmetric:72431900 |2 altmetric |
| 037 | _ | _ | |a FZJ-2020-00441 |
| 100 | 1 | _ | |a Ostm, Johann |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
| 245 | _ | _ | |a The Ising Model with Hybrid Monte Carlo |
| 260 | _ | _ | |c 2019 |
| 336 | 7 | _ | |a Preprint |b preprint |m preprint |0 PUB:(DE-HGF)25 |s 1580810498_4614 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a WORKING_PAPER |2 ORCID |
| 336 | 7 | _ | |a Electronic Article |0 28 |2 EndNote |
| 336 | 7 | _ | |a preprint |2 DRIVER |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a Output Types/Working Paper |2 DataCite |
| 520 | _ | _ | |a The Ising model is a simple statistical model for ferromagnetism. There are analytic solutions for low dimensions and very efficient Monte Carlo methods, such as cluster algorithms, for simulating this model in special cases. However most approaches do not generalise to arbitrary lattices and couplings. We present a formalism that allows one to apply Hybrid Monte Carlo (HMC) simulations to the Ising model, demonstrating how a system with discrete degrees of freedom can be simulated with continuous variables. Because of the flexibility of HMC, our formalism is easily generalizable to arbitrary modifications of the model, creating a route to leverage advanced algorithms such as shift preconditioners and multi-level methods, developed in conjunction with HMC. |
| 536 | _ | _ | |a 574 - Theory, modelling and simulation (POF3-574) |0 G:(DE-HGF)POF3-574 |c POF3-574 |f POF III |x 0 |
| 588 | _ | _ | |a Dataset connected to arXivarXiv |
| 700 | 1 | _ | |a Berkowitz, Evan |0 P:(DE-Juel1)179213 |b 1 |
| 700 | 1 | _ | |a Petschlies, Marcus |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Luu, Tom |0 P:(DE-Juel1)159481 |b 3 |u fzj |
| 700 | 1 | _ | |a Pittler, Ferenc |0 P:(DE-HGF)0 |b 4 |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/872984/files/1912.03278.pdf |
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| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 3 |6 P:(DE-Juel1)159481 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Decoding the Human Brain |1 G:(DE-HGF)POF3-570 |0 G:(DE-HGF)POF3-574 |2 G:(DE-HGF)POF3-500 |v Theory, modelling and simulation |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |
| 914 | 1 | _ | |y 2019 |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 920 | 1 | _ | |0 I:(DE-Juel1)IAS-4-20090406 |k IAS-4 |l Theorie der Starken Wechselwirkung |x 0 |
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| 980 | _ | _ | |a preprint |
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| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)IAS-4-20090406 |
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