Automated quantum software engineering

As bigger quantum processors with hundreds of qubits become increasingly available, the potential for quantum computing to solve problems intractable for classical computers is becoming more tangible. Designing efficient quantum algorithms and software in tandem is key to achieving quantum advantage. Quantum software engineering is...

The effect of measurement uncertainties on quantum random walk based problems

Random walks have been used in a number of different fields for a long time. With the rise of of quantum random walks a lot of these applications have been made more efficient. Recently there have been a lot of improvements in the realization of these quantum random walks in real world systems. <br/>In this research, the effect of uncertainty in...

Implementations of Quantum Algorithms for Solving Linear Systems

In this thesis, I make a comparison of two quantum algorithms for solving systems of linear equations. The two approaches are tested using both simulations of quantum processes and simulations of noisy intermediary-scale quantum computers, i.e., NISQ. Both methods are tested on the same problems to compare sensitivity and runtime efficiency,...

Estimating Algorithmic Information Using Quantum Computing for Genomics Applications

Inferring algorithmic structure in data is essential for discovering causal generative models. In this research, we present a quantum computing framework using the circuit model, for estimating algorithmic information metrics. The canonical computation model of the Turing machine is restricted in time and space resources, to make the target...

The Quantum Approximate Optimization Algorithm: Performance on Max-Cut using Heuristic Parameter determination

The Quantum Approximate Optimization Algorithm (QAOA) is one of the promising near-term algorithms designed to find approximate solutions for combinatorial optimization problems. The algorithm prepares a parametrized state that is aimed to maximize the expectation value of the objective function of the problem. The circuit for QAOA consists of p...

Unitary Decomposition: Implemented in the OpenQL programming language for quantum computation

Unitary Decomposition is an algorithm for translating a unitary matrix into many small unitary matrices, which correspond to a circuit that can be executed on a quantum computer. It is implemented in the quantum programming framework of the QCA-group at TU Delft: OpenQL, a library for Python and C++. Unitary Decomposition is a necessary part in...

Quantum codes for quantum simulation of fermions on a square lattice of qubits

Quantum simulation of fermionic systems is a promising application of quantum computers, but to program them, we need to map fermionic states and operators to qubit states and quantum gates. While quantum processors may be built as two-dimensional qubit networks with couplings between nearest neighbors, standard fermion-To-qubit mappings do...

A conceptual framework for quantum accelerated automated design optimization

The development of practical quantum computers that can be used to solve real-world problems is in full swing driven by the ambitious expectation that quantum supremacy will be able to outperform classical super-computers. Like with any emerging compute technology, it needs early adopters in the scientific computing community to identify...

On the impact of quantum computing technology on future developments in high-performance scientific computing

Quantum computing technologies have become a hot topic in academia and industry receiving much attention and financial support from all sides. Building a quantum computer that can be used practically is in itself an outstanding challenge that has become the ‘new race to the moon’. Next to researchers and vendors of future computing...