Scalable quantum architecture for spin qubits will require efficient and reliable movement of qubits across increasingly complex architectures. This work introduces a physics-informed optimization approach to conveyor-mode spin qubit transport, leveraging device-level insights to improve transport fidelity and efficiency. By incorporating physical constraints directly into the optimization process, the method enables more realistic and scalable designs for qubit movement. It provides a pathway toward integrating high-performance qubit transport mechanisms within larger quantum computing systems.

Spin qubits and quantum dot arrays require precise control over qubit interactions and reliable readout mechanisms within scalable hardware platforms. This work demonstrates fully tunable tunnel-coupled quantum dots and integrated charge sensing in a commercial 22nm FD-SOI process. By enabling fine control over coupling and charge detection within a standard semiconductor technology, the approach supports the realization of complex and scalable quantum circuits. It highlights the potential of advanced CMOS nodes to host high-performance quantum devices while maintaining compatibility with industrial fabrication processes.

Future quantum technologies will depend on scalable and manufacturable hardware that can be integrated with existing semiconductor processes. This work demonstrates how electrostatically defined quantum dots can be controlled and reconfigured within a commercial CMOS platform. By leveraging common-mode voltage control, the approach enables confinement inversion, allowing flexible tuning of quantum dot configurations within the same device.

Quantum computers will require qubits that operate reliably within the limits imposed by error correction and practical hardware constraints. This work experimentally characterizes Si/SiGe spin qubits demonstrating high-fidelity single- and two-qubit operations at elevated temperatures compatible with integrated cryogenic electronics. By performing benchmarking, state tomography, and entanglement generation, the study shows that qubit performance can reach the error correction threshold even under realistic thermal conditions. This represents an important step toward scalable quantum systems where qubits and control electronics can be co-integrated.

Future quantum computers will rely on error correction, which in turn requires increased connectivity between qubits. To meet this demand, the proposed approach combines qubit shuttling with error-correction requirements, enabling more flexible and scalable architectures. By optimizing the physical layout starting from the constraints of the surface code, the work outlines a practical pathway toward efficient spin-based quantum processors. It also shows that near-optimal designs can be achieved with linear computational complexity, making the method applicable beyond small-scale demonstrations.