Interdisciplinary nature. Project SiUCs represents a combination of modern quantum optics in the USC regime, with condensed matter physics, quantum information, material science and microwave engineering. The project is therefore highly interdisciplinary in its nature. In practice, it brings together the areas of quantum information processing with superconducting circuits and USC physics by means of the novel circuit elements represented by the superinductors. As stated in Sec. 1.1, the limitations in existing theoretical models have been one of the factors preventing in-depth explorations of USC physics. SiUCs recognises this deficit and devotes a significant theoretical effort to produce novel, realistic models of experiments through its network of theory-experiment partners (see figure with partner connectivity map in Sec. 3.1). Therefore, the experimental developments will go hand-in-hand with a new theoretical formulation to control USC systems, including dissipation and decoherence. In the experimental front, the most important effort combining different disciplines is the introduction of superinductors to the field of USC physics. This crossing of different areas will be facilitated with the presence of experts from both sides (KIT, and IFAE, CNRS, respectively). The range of applications emerging from the core enabling technology of superinductors is truly interdisciplinary: from dynamical control for quantum simulators to photodetectors in the microwave regime. This combination of simultaneously focusing on fundamental physics and potential applications establishes a credible path towards supporting efforts in other large-scale projects such as OpenSuperQ. The established collaborations among partners (see Sec. 3.4 in the full proposal) will facilitate exchange of ideas and personnel. Tasks have been consistently designed with a strong focus on the enabling capabilities contributed by each partner, benefitting from each other in a healthy cross-fertilisation. New synergies will be developed among partners having had no previous interactions, particularly with those having no experience with USCs (KIT, SAS). Another important synergetic aspect in SiUCs is the role played by partners fabricating devices (CNRS, KIT) and those receiving them (IFAE, SAS), creating a connecting channel which will remain active beyond this project in future collaborations.
Interdisciplinary nature. This class would combine mathematical literacy with verbal/written communication skills in a way that is often not done in math-based science classes. By requiring students to think about math with "simple" physical applications in mind, this course will help them to better think of math conceptually as opposed to procedurally. The mathematical literacy and scientific communication skill this class would teach are critical for being a broad-minded and deep thinker. Students of all disciplines should know how to write about their observational findings and how these findings compare and contrast to the physical world. Further, gaining a better understanding of how models are used, like the ones discussed in this class, is important in other areas where rational and informed decision-making is imperative. For example, understanding how data gathered for Covid-19 or political polling purposes around elections, and why these data should be met with some level of scrutiny, is needed when trying to make decisions about one's personal life ("Should I/my family go outside?") or policy ("Should masks be mandated by law?"). Any math discussed in this course will never be above algebra in nature, so it will be accessible to students from all disciplines. Difference from a Program Course in an Academic Discipline Describe the ways in which the course is different in content, goals, and objectives from a Program course in a discipline: Although some courses in Biology and GNM discuss infectious diseases, none discuss the mathematical modeling of disease spread (i.e. epidemiological modeling). There would likely be some overlap with a couple GMN courses in the historical discussions of diseases, however, the focus of the discussions here would be to help develop/understand the models being used to study the spread of the diseases, as opposed to the diseases themselves. For students who are more mathematically inclined, or who are simply interested in epidemics, this class would offer an opportunity to conceptually explore models often only seen in very specific undergraduate majors or graduate studies. Further, some of the models use the physics of collisions and/or require a moderate amount of programing experience to put into code. Although the coding aspect would not be the primary focus of the course, the methods used to get numerical results would be discussed conceptually.
