Astrophysics 🪐
Astrophysics is an extremely accessible field, espeically for beginners who should (ideally) posses skills in data science (Python is the primary language of choice for most analysts) and general programming. A vast quanity of open-source data exists through governmental agencies such as NASA and ESA. Much of the astrophysical data available is contained in .fits flies, which can be rendered as the glorious images we often associate with major space telescopes.
Astrophysics HomepageQuantum Information 💻
Quantum Information Science (QIS) is a rich, rapidly developing field that explores how quantum systems store, process, and transmit information. Once the basic theory of quantum computation is understood, much work can be done through the construction and testing of novel quantum algorithms. Algorithms can even be run on real quantum computers remotely.
Quantum Information HomepageCondensed Matter and AMO Physics ⚛️
Condensed Matter (solid state physics, as it is often formally called) and AMO (atomic, molecular, and optical) physics study the behavior of matter and light on atomic and molecular scales. While such fields tend to rely heavily on in-person experimental work, many simulations, online data sets, and interactives are available for deeper exploration.
Condensed Matter/AMO HomepageParticle and Nuclear Physics 💥
Particle and Nuclear Physics explore the fundamental constituents of matter and their interactions. Many large experimental collaborations publish their open-source data, analysis pipelines, packages, and simulations, including live event displays! Much of particle physics analysis happens in Python, C++, or ROOT; the field itself has been a great motivator for computational innovation and the modern push toward big data and machine learning.
Particle and Nuclear HomepageMathematical & Engineering Physics 📊
Mathematical physics uses the tools of mathematics to solve problems in theoretical physics. Engineering physics utilizes physics to solve engineering problems, and vice versa. Both of these objectives are often accomplished through complex, high-end simulations, though a variety of tangible resources exist. With so much overlap with efforts of the private sector, some of the most in-demand tools are less open-source than in fundmenetal physics, but their principles are still accessible, espeically by making use of student licenses.
Mathematical Physics HomepageBiophysics and Geophysics 🧬
Biophysics and Geophysics apply heavily physical lenses to understanding biological systems (ecology, microbiology, virology, physiology) and the Earth (meteorology, geology, mineralogy), respectively. Python packages, simulations, and open datasets (often live feeds from geological or biological systems) can be explored in the context of advanced physics research. With the ever-changing, temporal nature of these fields, many neat online "dashboards" have been created for monitoring and curating live data.
Bio/Geophysics HomepagePhysics Education 📖
Physics Education is the study of how physics is taught and how students learn physics. Physics Education Research (PER) is extremely diverse, and focuses on every aspect of teaching physics, from equity in physics education to designing validated tests of student understanding. This page provides resources/curricula for both educators teaching physics at all levels and those conducting physics education research.
Physics Education HomepageExperimental Techniques & Statistics 🔍
Experimental Techniques and Statistics covers essential tools used across experimental physics, including data acquisition, error analysis, signal processing, and statistical inference. Many tools are built to supplement the experimental process, improve data analysis techniques, or interface with hardware in the lab.
Experimental Homepage