Computational Science is used everywhere: in mobile phones, cars, health care, transport, and weather forecasts. Modelling and simulations have an ever-increasing role in science, and they are pivotal in the analysis, interpretation and exploitation of Big Data in multidisciplinary challenges. As a research field, Computational Physics is the most fundamental branch of computational science. Broadly speaking, computational physics seeks for knowledge of the universe by implementing physical laws to methods, sofware and numerics. Simulations are then used to predict new physical phenomena and to explain experimental results.
In the Computational Physics Laboratory of Tampere University we carry out basic research in physics, while offering also methods and numerical tools to multidisciplinary challenges. We develop theories and methods, implement computational software, and utilize large-scale supercomputers for numerical simulations.
In basic research, the we aim at further understanding of the physical properties of materials, nanostructures, quantum mechanical and complex dynamical systems. For this purpose, we develop both classical and quantum mechanical models, methods and numerical algorithms and software. The long-term applications include, for example, next-generation quantum transistors and magnetic memory devices. The computational tools and statistical methods developed in the group are also actively applied to interdisciplinary research in, e.g., material science, health technology, and econometrics. In this respect, our laboratory can serve the scientific community in all topics that involve challenging computational tasks and problem solving.
We are engaged in curiosity-driven basic research in quantum condensed matter physics. Our aim is to expose the striking consequences of quantum physics in macroscopic matter. We theoretically explore various possibilities to construct novel quantum phases of matter with interesting and exotic properties. Our research employs a wide spectrum of methods, involving elements from condensed-matter and statistical physics to particle physics and quantum information.
We work on various research problems in computational physics. Our main focus is on quantum phenomena in atoms, molecules, solids, and two-dimensional nanostructures. Recently, we have also extended our reseach to multidisciplinary topics in the science of complex systems, for example, time-series analysis of physiological signals and rhythmic patterns in music.
Light–matter interaction and quantum technology define the framework of our research interests. Photovoltaics, semiconductors and their interfaces, heterogeneous catalysis and quantum nanostructures are typical examples of the functional materials and related phenomena we work on.
We develop quantum simulation methods based on the Feynman path integral approach and its computational implementations. Fermion sign problem is one of the grand challenges we face with Quantum Monte Carlo methods. With our novel numerical real-time path integral approach we aim at relieving this problem in practical calculations and simulations of many-body systems.
We perform simulations at the atomistic scale using both electronic structure calculations (DFT) and classical molecular mechanics (MM). The general objective our research is to study the detailed atomic structure of a system and its function. The group carries out method development for the Cluster Expansion formalism, Monte Carlo simulations, and tight-binding approaches. Furthermore, we develop simulation tools based on machine learning algorithms and link these with data mining.
We study complex dynamical processes in materials by combining computational and statistical physics, materials science, and machine learning. We are especially interested in non-equilibrium collective phenomena in disordered materials, such as the critical-like avalanche dynamics occurring in various driven systems. Example systems and phenomena of interest include domain wall dynamics in ferromagnets, crack propagation in solids, and plastic deformation of crystals.
Our staff teaches physics at all levels, ranging from first-year basic courses to advanced postgraduate courses. Computational Physics is one of the three possible study paths (alongside Aerosol Physics and Photonics) in the curriculum of Advanced Engineering Physics for the M.Sc. degree in technology at TAU.
Theses and internships
In Computational Physics we actively employ undergraduate students as trainees, summer students and thesis workers. Our B.Sc. students typically focus on an interesting computational research problem that is not too extensive, but - if successful - often leads to a co-authorship in a scientific publication.
Open call for summer trainees opens in January-February every year, please check the Open Positions page of the university.
We also employ M.Sc. students, even though the availability of projects is subject to the funding situation of the research groups. Feel free to approach our group leaders and ask for available M.Sc. projects!
We offer a variety of courses related to computational physics:
Our doctoral students are part of the Doctoral Programme of Engineering and Natural Sciences. In recent years our students have been very successful in obtaining individual research grants for doctoral studies.
In Computational Physics Laboratory we collaborate with more than 50 universities and research institutes around the world, including, for example, MIT, Harvard, Berkeley, and Max Planck Institutes in Germany, CNRS in France, etc. We have access to excellent computational infrastructure on the local, national and international level.