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SUMMARY:MARVEL Distinguished Lecture – Hannes Jónsson
DTSTART:20251111T140000
DTEND:20251111T151500
DTSTAMP:20261005T021954Z
UID:472fd17843e09f1f6f3c7a675c09e94393572f79f3bb380afeec08d0
CATEGORIES:Conferences - Seminars
DESCRIPTION:Hannes Jónsson (University of Iceland)\nhttps://epfl.zoom.us/
 j/62944878391\nPasscode: 115546\n\nProf. Hannes Jónsson\nUniversity of 
 Iceland\n\nCalculations of excited electronic states using saddle point se
 arches and self-interaction corrected density functionals\, with compariso
 n to neural-network selective configuration interaction\nCalculations of R
 ydberg and charge-transfer excited states based on variational optimisatio
 n of orbitals in state specific density functional calculations of molecul
 es and defects in solids are presented. The method is based on the general
 ised mode following (GMF) saddle point search algorithm [1] and direct opt
 imisation as implemented in the GPAW software for condensed matter simulat
 ions [2] where the orbitals are represented with plane waves or a real spa
 ce grid. The GMF method is used to converge on a saddle point of a given o
 rder on the electronic energy surface representing an excited state. The v
 alues of excitation energy obtained using generalised gradient and meta-ge
 neralised gradient functionals are found to be in remarkably good agreemen
 t with experimental estimates and results of higher level calculations [3\
 ,4]. Even better results are obtained by applying scaled self-interaction 
 correction to the energy functionals.\n   Alternatively\, reference val
 ues are obtained in selective configuration interaction (CI) calculations 
 where a convolutional neural-network is used to identify the important Sla
 ter determinants [5]. As an example\, published results of full CI calcula
 tions of NH3\, N2\, H2O and propane molecules are reproduced with five to 
 seven orders of magnitude fewer Slater determinants selected by the neural
  network. Faster convergence is obtained by optimising the Hartree-Fock or
 bitals for the target excited state.\n\nReferences\n1. Y.L.A. Schmerwitz\,
  G. Levi and H. Jónsson\, J. Chem. Theory Comput. 2023\, 19\, 3634.\n2. J
 . J. Mortensen et al.\, J. Chem. Phys. 2024\, 160\, 092503.\n3. A.E. Sigur
 darson\, Y.L.A. Schmerwitz\, D.K.V. Tveiten\, G. Levi and H. Jónsson\, J.
  Chem. Phys. 2023\, 159\, 214109.\n4. A.V. Ivanov\, Y.L.A. Schmerwitz\, G.
  Levi and H. Jónsson\, SciPost Physics 2023\, 15\, 009.\n5. Y.L.A. Schmer
 witz et al.\, J. Chem. Theory Comput. 2025\, 21\, 2301.\n\nAbout the speak
 er\nProf. Jónsson received his B.S. degree in Chemistry from the Universi
 ty of Iceland in 1980\, and a Ph.D. at the University of California San Di
 ego in 1985. After a two-year post-doc at Stanford\, he became an assistan
 t/associate/full professor at University of Washington in Seattle\, and in
  2000 became professor at the University of Iceland. He has been a visitin
 g professor at the Technical University of Denmark\, SLAC/Stanford\, Aalto
  University\, Leiden University and University of Oxford. Prof. Jónsson h
 as developed several computational methods\, including methods for finding
  saddle points on multidimensional surfaces such as the CI-NEB and dimer m
 ethods. They are used in calculations of transition rates\, in particular 
 for chemical reactions\, diffusion and magnetic transitions. More recently
 \, such saddle point search methods are being used to calculate electronic
  excited states.
LOCATION:MED 2 1124 https://plan.epfl.ch/?room==MED%202%201124 https://epf
 l.zoom.us/j/62944878391?pwd=6eAagBIX9BXhik45Ieq3yIZJPotMXI.1
STATUS:CONFIRMED
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