Physics // Numerical methods in physics have led to new insights into old problems and have long since allowed the consideration of previously unaddressed phenomena. In its current state, computation can be viewed as complementary to the traditional routes of experiment and theory. For many physicists, "computer physics" provides an accessible way of doing physics without the need for substantial experimental resources. Furthermore, computational algorithms provide a way of "discovering" physics in a manner similar to the traditional mode of pure research. Inevitably what follows in this process is the discovery that the same algorithms give the same results. In other words, that physics is phenomenologically unified.
Data Science // My training as a physicist provides a natural foundation for the role of data scientist, where the roles of explorer, scientist, and analyst are effectively combined. (Experimental physicists are particularly well suited for this role as they are already trained in how to make sense of real world data and are typically much stronger in statistics.) This translates into an individual that has the curiosity and passion for exploring new problems, data sets, and technologies. The discipline of my scientific background also means that I am comfortable with testing my code and algorithms in a rigorous and objective manner. The role of scientist often aligns closely with that of an analyst, where answers are often the by-product of details.
What's with the name? // This is in reference to my hands-on approach to doing things. I prefer to use a simple text editor and a few plug-ins to do my coding. This enables to me to produce better results and also gain a deep understanding of what I'm working on. The name stuck, I guess.
Calculates the Sternheimer density effect parameters using the prescription given in The International Journal of Applied Radiation and Isotopes33(11), 1189 (1982). This utility is a companion to the Range-Energy Calculator.