## Core courses

We use gravitational and electromagnetic interactions as representatives for how physics takes experimental evidence and then encodes it into a theoretical framework that can be used to make predictions and draw inferences about new phenomena. The course emphasizes the development of the tools needed to describe the physical structure of nature and then uses these tools to infer the domain of validity of theories in physics and what might lie beyond them.

Learn to utilize principles of single and multivariable calculus to solve relevant problems from across STEM. Traditional calculus courses focus on the techniques needed to perform complex computations by hand, and evaluate students primarily on their ability to do so quickly. This course takes a different approach by shifting the focus to applying foundational calculus concepts to analyze and solve problems in practical contexts while building the facility to take full advantage of technologies such as Sage to perform complex computations. In addition to honing skills from critical and creative thinking, an emphasis is placed on effective collaborative problem-solving and communication of technical processes and results to appropriate audiences. Note: This course was previously CS111A.

## Concentrations Courses

Study the nature of matter from a quantitative standpoint using the tools provided by quantum mechanics. Starting from experiments that led the way to the discovery of quantum mechanics, we first establish its mathematical foundations. We then focus on electronic structures of particles and atoms. Along the way, we also review examples of technological revolutions catalyzed by quantum mechanics. Zoom in on events at microscopic scales, where interactions of energy and matter can behave differently than as predicted by classical physics.

Understanding what matter is, how matter and small molecules are studied, and how they can be manipulated is the gateway to technological solutions to many world challenges. Learn principles underlying optics, chemical identification, and chemical separation, and employ analytical tools for molecular and elemental analyses to tackle important interdisciplinary problems. In this course, we explore the application of analytical techniques to a range of topics, from everyday concerns of water quality, to major problems such as oil spill monitoring and cleanup, to ecosystem- and planetary-scale research questions that rely on remote sensing technologies. The first unit focuses on how light and electromagnetic radiation are used to view matter and molecules both directly and indirectly. The second unit focuses on identifying and quantifying molecules based upon their reactions and interactions with other, known chemicals. The third unit focuses on using sub-atomic properties, such as charge or isotopic composition, to characterize analytes. Students explore common techniques to separate and identify specific atoms or molecules within such mixtures. In the final unit we combine approaches from all earlier parts of the course to address current, multi-faceted research questions associated with the Earth’s past, present and future climate. NOTE: In addition to the listed prerequisites, the following courses are recommended prior to taking this course: CS111

Statistical Mechanics describes how macroscopic systems and the macroscopic physical laws that govern them emerge from the aggregated behavior of many microscopic components. The field developed to explain the empirical results of thermodynamics in terms of the microscopic theory of atoms — Why do macroscopic systems have uniform properties? How do equations of state emerge from microscopic dynamics? When do these emergent laws break down? Why does the 2nd law of thermodynamics emerge, and how does it relate to phenomena from the efficiency of engines to the cooling of the universe? Why does matter have phases and under what conditions do phase transitions occur? While we primarily focus on explaining the tools of statistical mechanics through thermodynamics, we also discuss applications of these tools to computer science, machine learning, finance, and modeling social systems. In doing so, we introduce the basics of information theory and develop the connections between thermodynamic entropy and the more broadly applicable concept of Shannon entropy. NOTE: In addition to the listed prerequisites, the following courses are recommended prior to taking this course: CS114