Welcome to the 21st edition of The Young Researchers' Meeting. Registrations will open soon, stay tuned! For more information, news, and registration, please visit our website by clicking here. For any other inquiries, contact us at yrm2025organizers@gmail.com. 

The European Theoretical Spectroscopy Facility (ETSF) is a network of European research teams of acknowledged international reputation. The primary research focus of ETSF groups lies within the extensive domain of theoretical spectroscopy. ​​In addition to their research activities, ETSF places a strong emphasis on scientific outreach at both institutional and industrial levels by organizing international conferences and workshops. One of ETSF's key initiatives is the Young Researchers' Meeting (YRM).

The YRM is an annual meeting designed for early-stage researchers, including MSc students, PhD candidates, and postdoctoral fellows. Its primary focus is to unite young scientists at the beginning of their careers, promoting discussions and collaborations in a welcoming and inclusive setting. The objectives of these meeting are to provide young researchers with the opportunity to share their work and acquaint themselves with state-of-the-art theoretical methods applied both in their own field and in others. Moreover, it offers scientists the chance to network with young colleagues from different institutions, exchange knowledge and ideas and thus integrate further into the scientific community. Mirroring the extensive research scope of the ETSF network and following the tradition of previous editions, YRM 2025 will feature a broad array of scientific topics, organized into five distinct thematic sessions.

Day 1: Electronic Structures and Methods Development [1,2]

The characterisation of materials through the use of more and more elaborate analytical methods allows, today, to reach a high degree of understanding of the microscopic phenomena that govern a property. The study of certain mechanisms needs to be carried out at the atomic scale, where the contribution of quantum mechanics proves to be decisive. Methods for accurately computing electronic structures are continually advancing, enabling the study of increasingly complex systems such as molecular materials or extended solid structures. Among the commonly used methods, Density Functional Theory (DFT) stands out for which ongoing efforts are made to develop new functionals. Moreover, even wave function-based methods are becoming interesting for the calculation of properties of large systems, such as MCSCF and CC methods.

Day 2: Optical Properties of Materials [3-5]

Optical properties, such as absorption, reflection, or refraction define the interaction between light and matter. These properties are key to gain insight in materials mechanisms and potential applications in technology. Theoretically, the computation of optical properties has seen significant advancements, allowing for precise simulations of complex systems. Key methods include the many-body GW approximation, which provides accurate electronic band structures, and the Bethe-Salpeter Equation (BSE), which describes excitonic effects crucial for understanding optical excitations. Time-Dependent Density Functional Theory (TDDFT) is another essential tool, enabling the study of dynamic optical properties and responses to time-dependent fields.
 

Day 3: Vibrational Properties of Materials and Transport [6,7]

The study of vibrational properties and transport phenomena is at the forefront of condensed matter physics, materials science or molecular chemistry. Vibrational properties, which include phonon spectra and lattice dynamics, play a crucial role in understanding thermal and electronic transport in materials. A​​dvances in first-principles methods like Density Functional Theory (DFT) and Density Functional Perturbation Theory (DFPT) enable accurate calculation of phonon spectra and lattice dynamics. For transport properties, the Boltzmann Transport Equation (BTE) and the Relaxation Time Approximation (RTA) are commonly used to predict thermal and electrical conductivity. Sophisticated computational techniques, including Green's function methods and molecular dynamics simulations, further enhance the study of vibrational transport at the nanoscale. These methods are implemented in software packages such as VASP, Quantum ESPRESSO, and LAMMPS, facilitating precise analysis of complex systems. 
 

Day 4: Strongly Correlated Systems and Magnetism [8-12]

Strongly correlated systems refer to a diverse class of materials where the behavior of electrons cannot be described by simple independent particle models due to strong interactions among them. These interactions lead to emergent and often exotic properties that defy conventional understanding. Key examples include transition metal oxides such as high-temperature superconductors, where electron-electron interactions play a pivotal role in phenomena such as metal-insulator transitions and colossal magnetoresistance. Rare-earth compounds and some organic materials also exhibit strong correlation effects, influencing their magnetic, electronic, and structural properties in unique ways. Theoretical methods for strongly correlated materials aim to capture these complex interactions. Techniques such as Dynamical Mean Field Theory (DMFT), exact diagonalization or Monte Carlo simulations are crucial for modeling the electronic structure and predicting behaviors such as magnetism, charge ordering, or unconventional superconductivity.

Day 5: High Performance Computing [13]

High Performance Computing (HPC) has reached unprecedented levels of capability, revolutionizing scientific research, engineering, and data analysis across various fields. HPC enables today the simulation and modeling of complex phenomena with remarkable precision. Advances in hardware, such as GPUs, custom accelerators, and energy-efficient processors, coupled with sophisticated software frameworks and algorithms, have significantly enhanced computational power and efficiency. Additionally, the integration of artificial intelligence and machine learning techniques with HPC is accelerating discoveries and optimizing resource utilization. These developments are not only pushing the boundaries of what can be computed but also making HPC more accessible and versatile, fostering innovation and driving progress in theoretical spectroscopy.