Expertises

  • Chemistry

    • Crystalline Material
    • Thermodynamic Potential
    • Tight Binding Model
    • Coupled Cluster
    • Diffusion Monte Carlo
  • Mathematics

    • Monte Carlo
  • Physics

    • Broken Symmetry
    • Fermion

Organisaties

Publicaties

2026

Machine-Learned Excited-State Dynamics with quantum Monte Carlo: Insights from Azomethane (2026)[Contribution to conference › Poster] NWO Physics 2026. Annarelli, A., Slootman, E. & Filippi, C.

2025

Reproducibility of fixed-node diffusion Monte Carlo across diverse community codes: The case of water-methane dimer (2025)The Journal of chemical physics, 163(10). Article 104110. Della Pia, F., Shi, B. X., Al-Hamdani, Y. S., Alfé, D., Anderson, T. A., Barborini, M., Benali, A., Casula, M., Drummond, N. D., Dubecký, M., Filippi, C., Kent, P. R. C., Krogel, J. T., López Ríos, P., Lüchow, A., Luo, Y., Michaelides, A., Mitas, L., Nakano, K., … Zen, A.https://doi.org/10.1063/5.0272974Emergence of imaginary time crystals in the non-Hermitian Su-Schrieffer-Heeger model (2025)Physical review B: Covering condensed matter and materials physics, 112(8). Article 085149. Slootman, E., Eek, L., Morais Smith, C. & Arouca, R.https://doi.org/10.1103/ttny-t2gsSupporting scripts to: Emergence of Imaginary Time Crystals in the non-Hermitian Su-Schrieffer-Heeger model (2025)[Dataset Types › Dataset]. Zenodo. Slootman, E., Eek, L., Morais Smith, C. & Arouca, R.https://doi.org/10.5281/zenodo.15149008Emergence of Imaginary Time Crystals in the non-Hermitian Su-Schrieffer-Heeger model (2025)[Working paper › Preprint]. ArXiv.org. Slootman, E., Eek, L., Morais Smith, C. & Arouca, R.https://doi.org/10.48550/arXiv.2504.19315Is fixed-node diffusion quantum Monte Carlo reproducible? (2025)[Working paper › Preprint]. ArXiv.org. Della Pia, F., Shi, B., Al-Hamdani, Y. S., Alfè, D., Anderson, T., Barborini, M., Benali, A., Casula, M., Drummond, N., Dubecký, M., Filippi, C., Kent, P., Krogel, J., López Ríos, P., Lüchow, A., Luo, Y., Michaelides, A., Mitas, L., Nakano, K., … Zen, A.https://doi.org/10.48550/arXiv.2501.12950Causing and Curing Headaches with Quantum Monte Carlo: Accurate Forces for Machine-Learned Force Fields (2025)[Contribution to conference › Poster] 22nd International Workshop on Computational Physics and Materials Science: Total Energy and Force Methods 2025. Slootman, E., Charkin-Gorbulin, A., Shinde, R. L., Moroni, S., Poltavsky, I., Tkatchenko, A. & Filippi, C.

2024

Machine-Learning Models from Accurate QMC Forces: The Case Study of Ethanol (2024)[Contribution to conference › Poster] MESA+ Meeting 2024. Slootman, E., Poltavsky, I., Shinde, R. L., Cocomello, J., Moroni, S., Tkatchenko, A. & Filippi, C.Accurate Quantum Monte Carlo Forces for Machine-Learned Force Fields: Ethanol as a Benchmark (2024)Journal of chemical theory and computation, 20(14), 6020-6027. Slootman, E., Poltavsky, I., Shinde, R., Cocomello, J., Moroni, S., Tkatchenko, A. & Filippi, C.https://doi.org/10.1021/acs.jctc.4c00498Cornell-Holland Ab-initio Materials Package (CHAMP) (2024)[Dataset Types › Dataset]. Zenodo. Filippi, C., Shinde, R., Landinez Borda, E. J., Shepard, S., Slootman, E., Cuzzocrea, A., Azizi, V., López-Tarifa, P., Renaud, N., Umrigar, C. & Moroni, S.https://doi.org/10.5281/zenodo.11369537

Onderzoeksprofielen

Adres

Universiteit Twente

Carré (gebouwnr. 15), kamer C4037
Hallenweg 23
7522 NH Enschede

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