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LibreCat: https://research-explorer.ista.ac.at/record/12831
DOI: 10.1063/5.0135893
WoS: 000970038800001
arXiv: 2211.08070

Suzuki, F., &; Unruh, W. G. (2023). Numerical quantum clock simulations for measuring tunneling times. Physical Review A. American Physical Society.https://doi.org/10.1103/PhysRevA.107.042216 
LibreCat: https://research-explorer.ista.ac.at/record/12914
DOI: 10.1103/PhysRevA.107.042216
WoS: 000975799300006
arXiv: 2207.13130

Agafonova, S., Lemeshko, M., &; Volosniev, A. (2023). Finite-range bias in fitting three-body loss to the zero-range model. Physical Review A. American Physical Society.https://doi.org/10.1103/PhysRevA.107.L061304 
LibreCat: https://research-explorer.ista.ac.at/record/13233
DOI: 10.1103/PhysRevA.107.L061304
WoS: 001019748000005
arXiv: 2302.01022

Bighin, G., Ho, Q. P., Lemeshko, M., &; Tscherbul, T. V. (2023). Diagrammatic Monte Carlo for electronic correlation in molecules: High-order many-body perturbation theory with low scaling. Physical Review B. American Physical Society.https://doi.org/10.1103/PhysRevB.108.045115 
LibreCat: https://research-explorer.ista.ac.at/record/13966
DOI: 10.1103/PhysRevB.108.045115
arXiv: 2203.12666

Henderson, P. M., Ghazaryan, A., Zibrov, A. A., Young, A. F., &; Serbyn, M. (2023). Deep learning extraction of band structure parameters from density of states: A case study on trilayer graphene. Physical Review B. American Physical Society.https://doi.org/10.1103/physrevb.108.125411 
LibreCat: https://research-explorer.ista.ac.at/record/14320
DOI: 10.1103/physrevb.108.125411
arXiv: 2210.06310