Citation :

Dharani K, Shobana R, 2025. "The 2025 Roadmap to Ultrafast Dynamics: Frontiers of Theoretical and Computational Modelling" ESP International Journal of Emerging Multidisciplinary Research [ESP-IJEMR]  Volume 1, Issue 1: 1-11.

Abstract :

Ultrafast dynamics is among the most revolutionary topics of modern physical science, and it links up photochemistry with materials research and basic quantum study/hot quantum technology. The dynamics of electrons, spins and nuclei that determine the microscopic fundamentals of energy conversion, information transfer and structural change is observable for researchers through ongoing probing (and manipulation) of matter on timescales from femto (10⁻¹⁵ s ) to attoseconds (10⁻¹⁸ s). An analogous revolution in theoretical and computational simulations has been ignited by the unprecedented resolution of the state-of-the-art experimental instruments, such as time-resolved photoelectron spectroscopy [2-5], ultrafast X-ray and electron diffraction [6-8], attosecond laser pulses [9]. These developments demand development of new theories that grasp mechanistic understanding over different scales and be capable to predict the nonequilibrium phenomena efficiently. Here in this article, we provide a comprehensive description of the opportunities opened and challenges at hand in ultrafast theory with the perspective to 2025 within "The 2025 Roadmap to Ultrafast Dynamics: Theory" which complements other roadmaps on Extreme Light Infrastructure (ELI) science as well as on collider and neutrino communities. It discusses the progress and limitation of some major computational approaches, including newly developed quantum-electrodynamical density-functional theory (QEDFT), nonadiabatic molecular dynamics (NAMD), nonequilibrium Green's function (NEGF) methods, and real-time time-dependent density functional theory (TDDFT). The roadmap illustrates how these methods are interfacing with data-driven models and machine learning (ML) and hybrid physics-AI frameworks that accelerate simulations while maintaining physical interpretability.Pointed to byLine 300 All these concerns and more are elaborated further on such as the need for reproducible community benchmarks, the potential tradeoff between accuracy and scalability, and connection of ultrafast calculations with experimental observables. The work also lays out several crucial research priorities for 2025–2030, such as the development of open and interoperable software infrastructures, benchmark datasets for nonequilibrium out-of-equilibrium dynamics, or ML-assisted multiscale models capable of describing correlated systems in strong fields. The roadmap also brings out the importance of open-source toolchains, interactive experiment-theory feedback loops that can potentially impact experimental steerage in real-time, and FAIR (Findable, Accessible, Interoperable, Reusable) data principles. This work also provides researchers, educators and politicians who want to develop ultrafast modellings as a predictive and interpretive tool with the first stepstone by describing concrete objectives and the multidisciplinary way forward. Beyond the goal of increasing computer power, the aim is to develop a coherent open sustainable scientific environment that allows for quantitative control of matter on its natural time and size scales. Ultimately, predictive ultrafast theory will enable transformative discoveries in energy materials, photonics, quantum information and catalysis as it will usher a new era of computational research and development grounded on real-time quantum dynamics.

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Keywords :

Strong-Field Phenomena, Multiscale Simulation, Benchmarking and FAIR Data, Computational Materials Science, Theoretical Photochemistry, Ultrafast Dynamics, Attosecond Science, Time-Dependent Density Functional Theory (TDDFT), Nonequilibrium Green's Function (NEGF), Nonadiabatic Molecular Dynamics (NAMD), Quantum Electrodynamical DFT (QEDFT), Machine Learning in Physics.