OPEN-SOURCE TOOL FOR CLASSICAL AND QUANTUM OPTICS
Solving the Optical Bloch Rate Equations in alkali metal atoms using the Julia programming language
Florian Gahbauer
University of Latvia in Riga (LV)
Link @ recorded talk
Florian Gahbauer works at the Laser Centre, which is a unit of the Faculty of Science and Technology of the University of Latvia in Riga, Latvia. He received his Ph.D. in Physics from the University of Chicago in 2003. His dissertation was based on a measurement, using a balloon-borne particle detector, of the composition of cosmic-rays at energies around 1 TeV/nucleon. In 2004 he moved to Riga, where he switched fields to atomic physics. In Riga he studies coherent effects in atoms that involve the interaction of polarized light, magnetic or electric fields, and hyperfine structure. Recently, he has been applying similar techniques to nitrogen-vacancy (NV) centres in artificial diamonds. In both cases he studies applications to magnetometry and quantum sensing. He also continues some collaboration with other institutions involving balloon-borne cosmic-ray observations.
Abstract: I will present a toolkit we have developed to solve the optical Bloch rate equations for alkali metal atoms in the presence of external magnetic field and polarized laser radiation [1]. Under steady-state conditions, the optical Bloch equations can be reduced to rate equations for Zeeman coherences, which we solve using the Julia language and the package QuantumOptics.jl. The toolkit calculates the steady-state density matrix of alkali metal atoms in the presence of an external magnetic field and exposed to a pump laser beam of arbitrary polarization and propagation direction. Knowing the density matrix, it is possible to determine the fluorescence intensity as well as the absorption of a weak probe beam. From the density matrix, one can produce a plot of the angular momentum distribution of the atoms. The toolkit is available on Github. It was validated by comparing its results to legacy code written in C/C++ and experimental measurements. Compared to the legacy code, the Julia code is much easier to read and maintain, makes for easier parallelization, and can be used in Jupyter notebooks.
[1] D. Osite et al., Comput. Phys. Commun. 314, 109678 (2025).
Simulating nonlinear optics for attosecond science
Nicholas Karpowicz
MPI of Quantum Optics, Garching (DE)
Link @ recorded talk
Nicholas Karpowicz is a Permanent Scientist at the Max Planck Institute of Quantum Optics (MPQ) in Garching, Germany, where he also coordinates projects within Ferenc Krausz’s group and co-leads the International Max Planck Research School for Advanced Photon Science (IMPRS-APS). He earned his Ph.D. in Physics from Rensselaer Polytechnic Institute in 2009 for his work on terahertz gas photonics. Before his current position, he was a Senior Scientist at CNR NANOTEC in Lecce, Italy, and earlier a postdoctoral researcher and group leader at MPQ. His research focuses on the direct sampling of ultrabroadband spatiotemporal waveforms and on light–matter interaction in the strong-field and attosecond regimes, combining experiments with theory and numerical methods in nonlinear optics and quantum mechanics.
Abstract: I will discuss the Lightwave Explorer simulation platform, which is open source software developed for numerical nonlinear optical propagation of ultrashort pulses at the Max Planck Institute of Quantum Optics in Garching, Germany. I’ll briefly discuss our recent research directions [1] and how this fits in, and the motivations and consequences of making the code open. I will discuss the technical details of the code, which is the topic of a publication [2], giving an overview of the opportunities and challenges of maintaining an open source project.
[1] A. Heinzerling et al., Nat. Photonics 19, 772 (2025).
[2] N. Karpowicz, Opt. Continuum 2, 2244 (2023).
Bridging the gap: Raman and infrared spectra from ML-MD for anharmonic, disordered and defective materials
Paul Erhart
Chalmers Univ. Tech., Gothenburg (SW)
Link @ recorded talk
Paul Erhart is a Professor in the Condensed Matter & Materials Theory division at the Department of Physics, Chalmers University of Technology, Gothenburg, Sweden. He earned his Ph.D. in Materials Science from Technische Universität Darmstadt in 2006. From 2007 to 2011, he worked at the Lawrence Livermore National Laboratory in California, first as a post-doctoral researcher and then as staff scientist. He joined Chalmers in 2011, where he leads the Computational Materials group. His research focuses on atomistic and electronic-scale modelling of real materials, especially defects, anharmonic lattice dynamics, thermal transport and energy materials, with a strong emphasis on efficient interatomic potentials and machine-learning methods. He and his group have published a series of free-and-open-source software tools and routinely study both hard and soft materials with this approach.
Abstract: Predicting vibrational spectra, such as Raman and infrared (IR) spectra, of materials with strong anharmonicity, disorder or defects remains a formidable challenge. Conventional tools are often restricted to small or nearly ideal systems, and struggle to capture, e.g., temperature-induced broadening and localized defect modes. In response, we have developed a unified framework based on molecular dynamics (MD) that combines machine-learned interatomic potentials (MLIPs) via the neuroevolution potential (NEP) formalism with tensorial models for polarizability and dipoles via a tensorial extension NEP, which is both computationally and data efficient. This allows the evaluation of finite-temperature Raman and IR spectra from time-correlation functions at a very modest computational cost, naturally including higher-order contributions and thermal effects. We demonstrate the method on the perovskite BaZrO3 as a function of both temperature and pressure, revealing strong anharmonicity and pronounced second-order Raman features. Finally, we outline the extension to defective crystals, showing that vibrational signatures of point defects can be predicted with the same framework, thereby enabling a direct connection of atomistic disorder to spectral observables.
[1] Xu et al., J. Chem. Theory Comput. 20, 3273 (2024).
[2] Rosander et al., Phys. Rev. B 111, 064107 (2025).
[3] Linderälv et al., npj Comp. Mater. 11, 101 (2025).
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