DAY 2

Abstract
I will go through the basic DFT approaches for extracting ground state magnetic order as well as magnetic excitation spectra. First, the ground state order is discussed and it is shown that it may be determined from spin spiral calculations within the generalized Bloch theorem. Although this is in principle a systematic approach, it cannot accomodate spin-orbit interactions and the inclusion of these for extrcating spin orientation will be discussed. In the second part I discuss magnetic excitations, which can be exytractred from beyond DFT methods. In particular, I will discuss the, magnetic force theorem, time-dependent density functional theory and the Bethe-Salpeter equation for magnons. While the latter two may produce accurate results that included Landau damping and mode branching in metals, only the MFT is straightforward to apply routinely for easy comparison with INS measurements.

Abstract
I will present an overview of the recently developed methods [1-3] for the prediction of muon spin rotation and relaxation (μSR) polarization functions in solids, based on density functional theory, molecular dynamics, and various approximate methods for the inclusion of quantum effects in muon’s motion.

The role of the computational level of theory (exchange and correlation functional, zero point motion, anharmonicity, diffusion paths for the muon) will be discussed by showing how the accuracy of the calculated polarization function is systematically improved by refining both the electronic ground state and the details of muons’ dynamics. This, in turn, allows for the understanding of interesting and puzzling experimental results in various fields where μSR is applied. Finally, I will address the challenges that arise when incorporating these methods into automated workflows.
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Abstract
The development of DFT methods for muon site location [1-2] has led to a revolution in the way in which condensed matter science with muons is now conducted [3]. I will describe why this problem is important, and review some recent highlights of how this new “DFT+μ” technique has led to new understanding of muon-induced distortions in frustrated systems [4], decoherence of quantum information in nuclear spin systems [5], and even resolved an old problem concerning a prototypical antiferromagnet [6]. I will give an outlook on where this field is going and point to some potential future developments.


References
[1]J. Möller, D. Ceresoli, T. Lancaster, N. Marzari, S. Blundell, Phys. Rev. B, 87, 121108 (2013)...

Solid-state NMR is a powerful experimental probe of atomic scale structure and dynamics. A series of developments in electronic structure methods over the past two decades has given material scientists the ability to predict solid-state NMR parameters using codes such as CASTEP, QE and Wien2k. These are a valuable tool for the interpretation of experimental spectra. Indeed, it has been said that it is now hard to publish experimental solid-state NMR results without an accompanying DFT calculation.

In this talk I will highlight the key methodological advances behind the prediction of NMR parameters, and some open theoretical challenges. I will also reflect back on how an experimental community came to so completely adopt electronic structure calculations. I will also discuss the computational tools which have been developed to support this interaction between theory and experiment.

Abstract
The presentation will give an overview of the science areas in magnetism where the excitations are studied by neutron spectroscopy, and what might be expected with new instrumentation and facilities under construction or envisioned. The challenges of interpreting these data will be examined, the current practices employed by facilities and users outlined, and thoughts on the opportunities and future requirements to make the most of the data will be discussed.

In this talk I will review our ongoing effort to leverage tensor-network based computational methods to accurately determine spectral response functions of quantum spin systems in one and two spatial dimensions. We will present a selection of experiment - theory collaborations, where the necessity for such accurate computational approaches becomes clear. We will also discuss our plans for a data pipeline from INS spectrometers to computational modelling tools for modern data analysis and modelling toolchains at large scale infrastructure facilities and beyond.

Abstract
I discuss the magnon dispersion of elementary magnets by means of the spin spin-flip ladder diagrams T [1] and the combination of two powerful self-energy techniques: the well-known GW method and a self-energy recently developed by us that describes renormalization effects caused by the scattering of electrons with magnons and Stoner excitations. This GT self-energy [1], which is fully k-dependent and contains infinitely many spin-flip ladder diagrams T [2], was shown to have a profound impact on the electronic band structure of Fe, Co, and Ni [3, 4]. In the presentation, I present the refinement of the method by combining GT with the GW self-energy. The resulting GWT spectral functions [5] exhibit strong lifetime effects and emergent dispersion anomalies. They are in an overall better agreement with experimental spectra than those obtained with GW or GT alone, even showing partial improvements over local-spin-density approximation dynamical mean-field theory [3].


References...

Abstract
What happens to a molecule once it has absorbed UV or visible light? How does the molecule release or convert the extra energy it just received? Answering these questions clearly goes beyond a pure theoretical curiosity, as photochemical and photophysical processes are central to numerous domains like energy conversion and storage, radiation damages in DNA, or atmospheric chemistry. A plethora of theoretical tools have been developed over the past decades to address these questions by simulating the excited-state dynamics of molecules. These methods are often tested and theoretically validated on reduced-dimensionality models or rather simple molecules.

In this talk, I will show a series of examples where studying the photophysics and photochemistry of real-life molecules helped spotlight the limitations of current theoretical methodologies and stimulate the development of new strategies for excited-state dynamics. In particular, I will focus on the sunlight-induced reactivity of volatile organic compounds in the troposphere, as well as athermal ground-state processes following passage through a conical intersection.
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Abstract
Point defects are present in all materials and can influence their properties significantly. In most situations the defects are unwanted, but they also have useful applications, e.g. for generation of single photons or magnetic field sensing. I will discuss how density functional theory (DFT), as implemented in the GPAW electronic structure package [1], can be used to calculate various relevant properties of point defects in insulators and semiconductors, from basic thermodynamic properties over the photoluminescence (PL) spectrum to radiative and non-radiative lifetimes of excited states to spin coherence times. I will present a recent first-principles based screening for optically accessible, high-spin point defects in wide band gap 2D crystals [2]. Starting from an initial set of more than 10k point defects, comprising both intrinsic and extrinsic, single and double defects in ten 2D host materials, we identify 610 defects with a triplet ground state, which are analyzed in greater detail. Our approach reveals many new spin defects with narrow PL line shapes and emission frequencies covering a broad spectral range. All the data is made available in the open access QPOD database [3].

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Abstract
Excitation spectra of valence electrons are often influenced by interaction effects, even in the absence of strong correlation. In particular, excitonic effects may dominate absorption spectra. In this talk, we start by reminding how the ab initio solution of the Bethe-Salpeter equation allows one to understand excitonic effects in semiconductors and insulators that go beyond textbook exciton models [1]. We then compare absorption spectroscopy with electron energy loss and inelastic x-ray scattering, and we show some surprising excitonic effects at large momentum transfer. We will extend the discussion to coherent inelastic x-ray scattering [2] and what one may deduce from the spectra. Finally, we will point to limitations of the current formulations that are of both physics and technical nature, and sketch ways to overcome them. The need for a close link between theory and experiment will be particularly highlighted throughout the talk.

The results that will be presented have mostly been obtained in collaboration with members of the Palaiseau Theoretical Spectroscopy Group and of the ETSF, and with colleagues from experimental groups.
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The use of light is nowadays the fastest way to observe and control electronic motion. Novel laser sources enable us to produce pulses in the attosecond scale (10^-18 s), even in the X-ray regime. Using those pulses, current ultrafast experiments already demonstrated the potential to follow the electron motion in few-layers materials [1] by using the characteristic site-specificity of X-ray interactions. To interpret the results, it is essential to be able to model both the light-induced dynamics and the observable to be measured with real-time approaches. Here we will show our advances in the development of a real-time dynamics code for materials [2] and some applications in the context of attosecond charge migration [3].


References
[1]B. Buades, A. Picón, E. Berger, I. León, N. Di Palo, S. Cousin, C. Cocchi, E. Pellegrin, J. Martin, S. Mañas-Valero, E. Coronado, T. Danz, C. Draxl, M. Uemoto, K. Yabana, M. Schultze, S. Wall, M. Zürch, J. Biegert, Applied Physics Reviews, 8, (2021)
[2]G. Cistaro, M. Malakhov, J. Esteve-Paredes, A. Uría-Álvarez, R. Silva, F. Martín, J. Palacios, A. Picón, J. Chem. Theory Comput., 19, 333-348 (2022)...

X-ray spectroscopy delivers strong impact across the physical and biological sciences by providing end users with highly detailed information about the electronic and geometric structure of matter. To decode this information in challenging cases, e.g., in operando catalysts, batteries, and temporally evolving systems [1], advanced theoretical calculations are necessary. The complexity and resource requirements often render these out of reach for end users, and therefore, the data are often not interpreted exhaustively, leaving a wealth of valuable information unexploited.

In this talk, I will discuss our recent progress applying machine learning to the prediction and interpretation of X-ray spectroscopy [2,3]. Our DNN, XANESNET [4], is able to predict X-ray absorption and emission spectra in less than a second with information obtained quickly from the geometric information about the local environment of the absorption site. We predict peak positions with sub-eV accuracy and peak intensities with errors over an order of magnitude smaller than the spectral variations that the model is engineered to capture. I will also outline extensions of the model to interpret the performance of the network and demonstrate how the uncertainty arising from predictions can be estimated. Finally, I will highlight areas on which future developments should focus.