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In this study, we develop and test a board game to introduce quantum computing to engineering students. The instructional approach is informed by peer instruction and flow theory. To begin, Bloom's taxonomy is leveraged to profile the intended learning outcomes (ILO's) from a master's course in Quantum Information. This is followed by a filtering exercise to shortlist the ILO's that are deemed suitable for our intended audience and for use in a boardgame. Design thinking informs the design methodology. The game, States & Gates, is differentiated from other similar offerings in that it is designed specifically for a technical audience where, for example, it leverages matrix multiplication as a game mechanic. For product testing, a feedback form is used to evaluate the design and instructional value of the product. The goal is to identify from what/whom the players learn, alongside questions about perceived aesthetics, usability and sentiment. The feedback suggests that peer instruction is a critical pedagogic aspect of playing the game, and that this form of instruction is most effective for players who identify as being novice, but not entirely new to the subject. Further, several suggestions for product improvement were offered that warrant the development of augmented digital features. The game was developed as a tool for the community and is available for download at our GitHub repository. [ABSTRACT FROM AUTHOR]

Optimal control of qubits requires the ability to adapt continuously to their ever-changing environment. We demonstrate a real-time control protocol for a two-electron singlet-triplet qubit with two fluctuating Hamiltonian parameters. Our approach leverages single-shot readout classification and dynamic waveform generation, allowing full Hamiltonian estimation to dynamically stabilize and optimize the qubit performance. Powered by a field-programmable gate array (FPGA), the quantum control electronics estimates the Overhauser field gradient between the two electrons in real time, enabling controlled Overhauser-driven spin rotations and thus bypassing the need for micromagnets or nuclear polarization protocols. It also estimates the exchange interaction between the two electrons and adjusts their detuning, resulting in extended coherence of Hadamard rotations when correcting for fluctuations of both qubit axes. Our study highlights the role of feedback in enhancing the performance and stability of quantum devices affected by quasistatic noise. Real-time adaptive control of a qubit has been demonstrated but limited to single-axis Hamiltonian estimation. Here the authors implement two-axis control of a singlet-triplet spin qubit with two fluctuating Hamiltonian parameters, resulting in improved quality of coherent oscillations. [ABSTRACT FROM AUTHOR]