|
|
Study of phase transitions in models with itinerant and localized particles via machine learning
Frk, Lukáš ; Žonda, Martin (advisor) ; Pokorný, Vladislav (referee)
Phase diagrams in condensed-matter physics are often very complex. The development of methods that can identify distinct phases without any prior knowledge is, therefore, of great interest. In this study, we applied unsupervised machine learning methods to find phase boundaries in the Falicov-Kimball model, using principal component analysis and the prediction-based method. We showed that both methods can distinguish the ordered from the disordered phase. Moreover, these methods are able to distinguish the weakly localized phase from the Anderson insulator phase, which both exist within the disordered phase. Keywords: prediction-based method, principal component analysis, Falicov-Kimball model, unsupervised phase classification, Machine Learning
|
|
|
Simulations of the magnetic domains dynamics in antiferromagnetic CuMnAs
Pařízek, Vojtěch ; Němec, Petr (advisor) ; Pokorný, Vladislav (referee)
Antiferromagnetic materials are promising materials for implementation in spintronic memory devices. In contrast to the more well-known ferromagnetic materials, which are already used in magnetoresistive random access memory (MRAM) devices, they possess multiple advantages, such as no net magnetization and ultrafast dynamics. Antiferro- magnetic memories store information through the orientation of the antiferromagnetic ordering. The magnetoresistance of the materials could be used for the electrical readout of the antiferromagnetic structure. In recent experiments in an antiferromagnet CuMnAs after applying a series of electrical or optical pulses, a change in resistivity associated with a significant decrease in the size of antiferromagnetic domains was observed. This means that one is able to perform electrical or optical writing in antiferromagnets. The state persists for timescales that exceed the magnetic dynamics timescales by many orders of magnitude. Here, we present the findings of the antiferromagnetic domain dynamics simulations in CuMnAs, specifically focusing on the process of small domain relaxation leading to the formation of larger domains. The simulations were based on atomistic spin dynamics. For all temperatures, a growth of magnetic domains was detected. However, the size of the...
|
|
|
Quantum transport in nanoscopic systems
Novák, David ; Pokorný, Vladislav (advisor) ; Marek, Štěpán (referee)
Molecular electronics is currently a rapidly evolving field of science that uses both experimental and theoretical methods. Their combination is in many cases unavoidable. This paper will provide the reader with an overview of the experimental methods to inves- tigate nanojunctions and the theoretical description of transport in them. Graphene is a promising candidate in replacing or improving silicon electronics because of its properties. For this reason, our examined systems are derivatives of graphene. The Kwant program- ming package can simulate quantum transport in nanoscopic systems. Its simplicity of use and low computational requirements make it an ideal environment for simulation. We have simulated quantum transport in graphene nanoribbons using this package and obtained their electronic properties. 1
|
|
|
Brain inspired approaches in quantum physics
Menšíková, Jana ; Baláž, Pavel (advisor) ; Pokorný, Vladislav (referee)
Artificial neural netwokrs have proven to be a powerful tool with applications in various fields: from data processing and optical character recognition to traffic control or prediction of dynamic systems evolution. Recently, they have demonstrated to be a promising approach to solving quantum mechanical spin systems where neural network is used as an Ansatz representing the wave function. In the case of Heisenberg model, an architecture called restricted Boltzmann machine was successful, thus in this work, we are going to focus on its generalization, J1-J2 model in one as well as two dimensions, in order to find out whether restricted Boltzmann machines can be efficiently used also for frustrated spin systems.
|
|
| |
|
| |
|
| |
guest ::
RSS feed.