Abstract
The discovery of the counterintuitive laws of quantum mechanics at the beginning of the 20th century revolutionized physics. Quantummechanical properties, such as superposition and entanglement, can be harnessed to create quantum technology that opens a computing power far beyond the computing power that we know today. A quantum computer would enable efficient simulations of chemical reactions and material properties, which is expected to greatly impact healthcare and the energy transition. Practical quantum computation requires millions of qubits, either with neighbourtoneighbour connectivity, or connected via quantum links. Spin qubits in electricallydefined silicon quantum dots are promising qubit candidates due to their small footprint and relatively long coherence time. The last decade meant a leap for the understanding and control of spin qubit systems with devices up to three quantum dots. Yet building systems capable of performing useful quantum calculations has proven difficult due to low sample yield, as well as challenges in controlling and scaling these systems. In this thesis, we explore quantumdotbased spin qubits and their suitability for scaling to larger systems. This quest was threefold and can be summarized as: More, Distant, Industrial.
 More: Increasing the number of quantum dots and thus qubits to numbers greater than three was proven challenging, among others due to the the crosscapacitance that was posed upon quantum dots by the metallic gate electrodes of their neighbours. Here, we develop a material platformindependent method to individually control the chemical potential of each quantum dot and the number of electrons in it without affecting the quantum dots in their vicinity. We demonstrate the method by tuning up a linear array of eight GaAs quantum dots, containing exactly one electron each.
 Distant: Thereafter, we shift our focus to creating quantum links between distant quantum dots by shuttling electron spins across a chip. Given the superior spin coherence times, we moved to silicon quantum dots, which were not as far developed at the time. To improve our understanding of the material and allow for the fabrication of silicon arrays beyond two quantum dots, we formulate metrics that allow for sample comparison across material platforms and gate geometries, which allows us to examine samples and detect disorder and flaws to improve (uniform) sample fabrication. This enables the fabrication of a sample that can host an array of up to five quantum dots and tune it with the method described above. To mimic a quantum link, we shuttle an electron forth and back through four quantum dots of the array up to 1000 times, corresponding to a total distance travelled of approximately 80 _m. We observe that the spin orientation was preserved, forming a promising base for a quantum link.
 Industrial: Thirdly, in collaboration with Intel, we harness the experience of the semiconductor industry by industrially manufacturing quantum chips and controlling a qubit on these chips. By means of the metrics that we defined, we demonstrate that industrial manufacturing on 300mm wafers allows for high yield and reasonable crosswafer uniformity of the samples, while allowing for welldefined quantum dots and qubits with a performance that is comparable to stateoftheart spinqubit results. This highyield fabrication without compromising qubit properties is crucial for scaling to the thousands of qubits that we need for practical quantum computation. The results in this dissertation provide perspective for scaling up silicon quantum dots and position the silicon spin qubit as a primary candidate for achieving quantum advantage with largescale devices with millions of qubits.
 More: Increasing the number of quantum dots and thus qubits to numbers greater than three was proven challenging, among others due to the the crosscapacitance that was posed upon quantum dots by the metallic gate electrodes of their neighbours. Here, we develop a material platformindependent method to individually control the chemical potential of each quantum dot and the number of electrons in it without affecting the quantum dots in their vicinity. We demonstrate the method by tuning up a linear array of eight GaAs quantum dots, containing exactly one electron each.
 Distant: Thereafter, we shift our focus to creating quantum links between distant quantum dots by shuttling electron spins across a chip. Given the superior spin coherence times, we moved to silicon quantum dots, which were not as far developed at the time. To improve our understanding of the material and allow for the fabrication of silicon arrays beyond two quantum dots, we formulate metrics that allow for sample comparison across material platforms and gate geometries, which allows us to examine samples and detect disorder and flaws to improve (uniform) sample fabrication. This enables the fabrication of a sample that can host an array of up to five quantum dots and tune it with the method described above. To mimic a quantum link, we shuttle an electron forth and back through four quantum dots of the array up to 1000 times, corresponding to a total distance travelled of approximately 80 _m. We observe that the spin orientation was preserved, forming a promising base for a quantum link.
 Industrial: Thirdly, in collaboration with Intel, we harness the experience of the semiconductor industry by industrially manufacturing quantum chips and controlling a qubit on these chips. By means of the metrics that we defined, we demonstrate that industrial manufacturing on 300mm wafers allows for high yield and reasonable crosswafer uniformity of the samples, while allowing for welldefined quantum dots and qubits with a performance that is comparable to stateoftheart spinqubit results. This highyield fabrication without compromising qubit properties is crucial for scaling to the thousands of qubits that we need for practical quantum computation. The results in this dissertation provide perspective for scaling up silicon quantum dots and position the silicon spin qubit as a primary candidate for achieving quantum advantage with largescale devices with millions of qubits.
Original language  English 

Awarding Institution 

Supervisors/Advisors 

Award date  19 May 2022 
Print ISBNs  9789085935247 
DOIs  
Publication status  Published  2022 