Adiabatic and local approximations for the kohn-sham potential in the hubbard model

We obtain the exact time-dependent Kohn-Sham potentials Vks for 1D Hubbard chains, driven by a d.c. external field, using the time-dependent electron density and current density obtained from exact many-body time-evolution. The exact Vxc is compared to the adiabatically-exact Vad-xc and the “instantaneous ground state” Vigs-xc. The effectiveness of these two approximations is analyzed. Approximations for the exchange-correlation potential Vxc and its gradient, based on the local density and on the local current density, are also considered and both physical quantities are observed to be far outside the reach of any possible local approximation. Insight into the respective roles of ground-state and excited-state correlation in the time-dependent system, as reflected in the potentials, is provided by the pair correlation function.

Functionals for TDDFT description of electron transport in nanostructures

La Teoria di Densità Funzionale (DFT) e la sua versione dipendente dal tempo (TDDFT) sono strumenti largamente usati per simulare e calcolare le proprietà statiche e dinamiche di sistemi con elettroni interagenti. La precisione del metodo si basa su una serie di approssimazioni degli effetti di exchange correlation fra gli elettroni, descritti da un funzionale della sola densità di carica. Nella presente tesi viene testata l'affidabilità del funzionale Mixed Localization Potential (MLP), una media pesata fra Single Orbital Approximation (SOA) e un potenziale di riferimento, ad esempio Local Density Approximation (LDA). I risultati mostrano capacità simulative superiori a LDA per i sistemi statici (curando anche un limite di LDA noto in letteratura come fractional dissociation) e dei progressi per sistemi dinamici quando si sviluppano correnti di carica. Il livello di localizzazione del sistema, inteso come la capacità di un elettrone di tenere lontani da sé altri elettroni, è descritto dalla funzione Electron Localization Function (ELF). Viene studiato il suo ruolo come guida nella costruzione e ottimizzazione del funzionale MLP.

Automatic classification of stellar orbits in axisymmetric potentials

Within the classification of orbits in axisymmetric stellar systems, we present a new algorithm able to automatically classify the orbits according to their nature. The algorithm involves the application of the correlation integral method to the surface of section of the orbit; fitting the cumulative distribution function built with the consequents in the surface of section of the orbit, we can obtain the value of its logarithmic slope m which is directly related to the orbit’s nature: for slopes m ≈ 1 we expect the orbit to be regular, for slopes m ≈ 2 we expect it to be chaotic. With this method we have a fast and reliable way to classify orbits and, furthermore, we provide an analytical expression of the probability that an orbit is regular or chaotic given the logarithmic slope m of its correlation integral. Although this method works statistically well, the underlying algorithm can fail in some cases, misclassifying individual orbits under some peculiar circumstances. The performance of the algorithm benefits from a rich sampling of the traces of the SoS, which can be obtained with long numerical integration of orbits. Finally we note that the algorithm does not differentiate between the subtypes of regular orbits: resonantly trapped and untrapped orbits. Such distinction would be a useful feature, which we leave for future work. Since the result of the analysis is a probability linked to a Gaussian distribution, for the very definition of distribution, some orbits even if they have a certain nature are classified as belonging to the opposite class and create the probabilistic tails of the distribution. So while the method produces fair statistical results, it lacks in absolute classification precision.