Distributed Simulation Methods and Algorithms for Superconducting Quantum Computer Reliability

Superconducting quantum computers are yet to reach the fault-tolerant regime, and thus the tantalising promises behind quantum algorithms are laid barren. To cross this knowledge-concealing wasteland, one must first understand how both intrinsic and extrinsic noise hinders the reliability of quantum computing systems. Most recently, in fact, external impinging particle events have been discovered to be one of the causes behind sudden bursts of information loss in these devices. Modelling such events with standard methods is a masterfully complex endeavour, which is ultimately hampered by computational costs in terms of memory and time. There is a growing requirement for an accurate fault model able to characterise a qubit's interaction with impinging particles, and more generally, the performance of full algorithms on quantum computers in the presence of radiation. Such a fault model would be the first of many other steps, paving the way for research on new quantum error correction and mitigation algorithms, and ultimately giving scientists a new instrument for tackling and understanding this ever growing issue. Reaching such goal requires the efficient simulation of quantum systems, both at the algorithmic and device level, pushing against the known limitations and bottlenecks imposed by these methods. The first objective is to understand the feasibility of quantum circuit simulations with the available computational methods, underlining bounds and limitations. This paved the way to provide a physically accurate noise model for the interaction of impinging particles on superconducting qubits, the most widespread and scalable technology for building quantum computers. The model has been devised to be easy to interpret and simulate, whilst being highly expressive and tunable, in order to keep up with future technological advancements in the field. The following step has been to leverage the fault model to develop methods and techniques apt at testing the reliability of \gls{QEC} and quantum algorithms alike. This includes methods for detecting the presence of radiation-induced faults at runtime, and applying partial information reconstruction methods. A deeper understanding of the effects of radiation also prompted the modelling and study of hardware hardening techniques. At last, the interoperation of quantum and classical computing systems has been investigated in the context of the reliability of hybrid machine learning algorithms, which are going to play an ever important role in the high performance computing systems of the future. These contributions press on in the quest for knowledge, impacting the quantum computing stack, correlating logical and physical quantum circuit design, and widening the understanding of how to prevent faults in quantum computing systems, quickening the advent of fault-tolerant quantum computation.