Course Learning Outcomes:

1. Demonstrate basic science literacy i.e., strong physics critical thinking skills; an understanding of the relevant quantities (and units) and foundational physics relationships so that you can make simple predictions about issues that are relevant to you, your community and the world.
2. Create and implement simple experiments to demonstrates key physics principles relevant to frontier physics, and use the results to evaluate one or more possible models.
3. Evaluate the quality and accuracy of various physics resources.
4. Assess the effectiveness and supportiveness of their group members (and yourself).
5. Synthesize ideas from several sources to create and present an original physics teaching artifact/demonstration.
6. Describe active frontiers of physics research and their potential impact on society.

Course Learning Outcomes:

1. Analyze the information contained in various hypothetical problem scenarios within the context of recognizable physics laws and apply systematic problem-solving strategies to solve for unknown quantities.
2. Identify and interpret the laws of nature as summarized by the fundamental concepts that constitute the foundation of classical physics.
3. Interpret and apply basic experiment methodologies designed to test fundamental concepts through direct observation.
4. Quantitatively analyze measurement results with effective evaluation of experimental uncertainties.
5. Relate nature's basic laws describing forces, motion, energy, momentum, thermodynamics, and the conservation rules that constrain these laws to real world applications.

Course Learning Outcomes:

1. Analyze the information contained in various hypothetical problem scenarios within the context of recognizable physics laws and apply systematic problem-solving strategies to solve for unknown quantities.
2. Identify and interpret the laws of nature as summarized by the fundamental concepts that constitute the foundation of classical physics.
3. Interpret and apply basic experiment methodologies designed to test fundamental concepts through direct observation.
4. Quantitatively analyze measurement results with effective evaluation of experimental uncertainties.
5. Relate nature's basic laws describing forces, motion, energy, waves, electromagnetism, optics, and the conservation rules that constrain these laws to real world applications.

Course Learning Outcomes:

1. Students will apply nature's basic laws describing forces and motion, energy and momentum, and the conservation rules that constrain these laws to real world applications.
2. Students will be able to analyze the information contained in various problem scenarios within the context of recognizable physics laws and utilize systematic problem-solving strategies to solve for unknown quantities.
3. Students will be able to identify and interpret the laws of nature as summarized by the fundamental concepts that constitute the foundations of classical physics.

Course Learning Outcomes:

1. Calculate the equations of motion of free, damped and forced mechanical (or electrical) systems that exhibit resonant behavior using the concept of force (Newton's laws), torque (Euler's laws) and energy (Lagrange Method).
2. Derive the classical wave equation and be fully conversant with classical wave behavior, such as refraction, diffraction, interference, and the superposition of waves.
3. Identify normal modes in coupled oscillators.
4. Relate the concepts listed above to real work applications.
5. Solve these differential equations to obtain the response of the mechanical (or electrical) system analytically or numerically using modern software packages such as MATLAB, Python, or Mathematica.

Course Learning Outcomes:

1. Analyze a physical problem, reducing the problem to study the key factors influencing the evolution of the system, and derive a system of equations to model the behaviour of the resulting system.
2. Create, run and analyze the output (graphically and otherwise) of computer programs, in a Python computing environment.
3. Design the appropriate computer algorithm to solve the resulting equations and to implement it in well-documented, clearly written code (Python).
4. Synthesize the entire process above and create a clear, concise written report summarizing the key results.
5. Test the resulting code using known results in simple examples and interpret the results of simulations in more general cases, determining the influence of each parameter affecting the outcome.

Course Learning Outcomes:

1. Calculate the various extraneous effects that degrade astronomical information (the light from celestial sources) as the signal passes through the interstellar medium, the Earth's atmosphere, and the detector.
2. Design and carry out a straightforward observing project, and analyze data from a real astronomical telescope to develop an understanding of some of the practical limitations in such scientific investigations.
3. Distinguish between the various wavelength, energy and frequency domains at which astronomers make their observations, and be able to explain the importance of working in these different spectral domains for a full understanding of the physics of the sources.
4. Explain the fundamental interactions between light and atoms/molecules/dust particles that determine the radiative output of astronomical sources.
5. Invert received astronomical signals to derive astrophysical conclusion about the physical nature of the source.

Course Learning Outcomes:

1. Algebraically manipulate complex numbers and complex exponentials.
2. Apply the standard methods of mathematical physics, such as Green's functions, to solve ordinary differential equations.
3. Apply the techniques of linear vector spaces to problems in classical and quantum mechanics.
4. Compute Fourier series and transforms of elementary functions.

Course Learning Outcomes:

1. Apply the methods of complex analysis and Green's functions to the wave equation and other common equations of physics.
2. Apply the techniques of complex analysis to the computation of integrals via the residue theorem and contour integration.
3. Apply the techniques of mathematical physics such as separation of variables to solve partial different equations commonly encountered in physics.
4. Develop a working knowledge of functions of a complex variable, including the calculation of Laurent expansions.
5. Develop a working knowledge of the special functions of mathematical physics, such as Bessel functions and Legendre polynomials.
6. Develop an understanding of one or more special topics in mathematical physics such as probability and statistics, group theory, or nonlinear dynamics.

Course Learning Outcomes:

1. Appreciate Einstein's geometrization of gravity.
2. Compare and analyze various extensions to the theory of General Relativity.
3. Describe the various constituents of modern cosmology.
4. Extend spherically symmetric vacuum to the axially symmetric case.
5. Identify what is meant by a solution to Einstein's equations.

Course Learning Outcomes:

1. Students will communicate effective solution methods and results, both in terms of code and report writing.
2. Students will implement a variety of advanced numerical algorithms to solve problems in physics that require high performance computers.
3. Students will learn advanced numerical algorithms for simulation and modelling, and apply such approaches to different problems, including (i) the dynamics of interacting quantum systems, and (ii) boundary value problems in advanced electromagnetic theory.
4. Students will learn one example of a communications protocol for parallel computations, MPI (message passing interface), and will learn to write python codes that implement MPI.
5. Students will learn to compile and submit parallelized codes to distributed memory architecture machines (from Compute Canada).
6. Students will work on a variety of high performance computing sites, all linked by Compute Canada. Students will compile and submit parallelized codes to distributed memory architecture machines.
7. Students will work with one example of a communications protocol for parallel computations, MPI (message passing interface), and will develop python codes that integrate MPI.

Course Learning Outcomes:

1. Have a working definition of what constitutes a plasma.
2. Describe the motion of charged particles under the influence of various applied fields.
3. Be familiar with adiabatic invariants.
4. Develop a basic understanding of plasma as a fluid including the governing magnetohydrodynamic.
5. Be familiar with the propagation of waves in plasma.
6. Describe diffusion processes, collision processes, and plasma resistivity.
7. Be aware of various plasma instabilities.