Gate Set Tomography on the Nitrogen-Vacancy Center

In this thesis, gate set tomography (GST) has been conducted on the nitrogen vacancy center (NV). Gate set tomography is a protocol for characterization of logic operations (gates) on quantum computing processors. The NV’s electron served as a qubit. The quantum circuits were run both experimentally as well as on an NV-simulator. GST is...

Characterizing qutrits and their noise environments

The standard toolbox of modeling and characterizing quantum systems comes with a standard set of assumptions as well. The two-level approximation replaces a many-level system with a qubit, and the Markovian approximation assumes an environment with a short memory. In this thesis, these assumptions are relaxed, and the dynamics of a single qutrit...

Stochastic carbon dioxide forecasting model for concrete durability applications

Over the Earth’s history, the climate has changed considerably due to natural processes affecting directly the earth. In the last century, these changes have perpetrated global warming. Carbon dioxide is the main trigger for climate change as it represents approximately up to 80% of the total greenhouse gas emissions. Climate change and concrete...

Learning What to Attend to: Using bisimulation metrics to explore and improve upon what a deep reinforcement learning agent learns

We analyze the internal representations that deep Reinforcement Learning (RL) agents form of their environments and whether these representations correspond to what such agents should ideally learn. The purpose of this comparison is both a better understanding of why certain algorithms or network architectures perform better than others and the...

Learning What to Attend to: Using Bisimulation Metrics to Explore and Improve Upon What a Deep Reinforcement Learning Agent Learns

Recent years have seen a surge of algorithms and architectures for deep Re-<br/>inforcement Learning (RL), many of which have shown remarkable success for<br/>various problems. Yet, little work has attempted to relate the performance of<br/>these algorithms and architectures to what the resulting deep RL agents actu-<br/>ally learn, and whether...

SIS Epidemics on Network with Non-Markovian Curing Process

Susceptible-Infected-Susceptible (SIS) model is commonly used to describe the spreading of virus on networks. However, a real-life epidemic process is not necessarily Markovian. The spreading of diseases, behaviors and information in real systems are sometimes dependent on the characteristics and current status of individuals. Thus it is far...

The efficient pricing of CMS and CMS spread derivatives

Two popular products on the interest rate market are Constant Maturity Swap (CMS) derivatives and CMS spread derivatives. This thesis focusses on the efficient pricing of CMS and CMS spread derivatives, in particular the pricing of CMS and CMS spread options. The notional values for these products are usually quite large, so even small errors...

Markovian Approximations to the Time Evolution of Lead Coupled Spinless Hubbard Chains through Different Master Equation Approaches

This thesis describes the process of deriving the Master Equation for the time evolution of the density operator for a lead coupled spinless Hubbard chain using a Markov approximation. The derivation is done in a direct, conventional way of expanding operators and switching pictures in order to separate the system Hamiltonian in a convenient way...