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.

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.

Pricing in stochastic-local volatility models with default

In recent years is becoming increasingly important to handle credit risk. Credit risk is the risk associated with the possibility of bankruptcy. More precisely, if a derivative provides for a payment at cert time T but before that time the counterparty defaults, at maturity the payment cannot be effectively performed, so the owner of the contract loses it entirely or a part of it. It means that the payoff of the derivative, and consequently its price, depends on the underlying of the basic derivative and on the risk of bankruptcy of the counterparty. To value and to hedge credit risk in a consistent way, one needs to develop a quantitative model. We have studied analytical approximation formulas and numerical methods such as Monte Carlo method in order to calculate the price of a bond. We have illustrated how to obtain fast and accurate pricing approximations by expanding the drift and diffusion as a Taylor series and we have compared the second and third order approximation of the Bond and Call price with an accurate Monte Carlo simulation. We have analysed JDCEV model with constant or stochastic interest rate. We have provided numerical examples that illustrate the effectiveness and versatility of our methods. We have used Wolfram Mathematica and Matlab.