January 25, 2016 at 03:50AM

Today I Learned: 1) ...how to steam-sterilize soil! I wouldn't use this as a substitute for autoclaving for truly sensitive tasks, but apparently steaming (preferred) or baking soil to about 180 F sterilizes it pretty well. It's also supposedly important to not heat it much over 180 F, or it will "create toxins". 2) I learned a few things about my handwriting today. Erik Jue and I compared how we write our letters today, and we discovered that I've heavily optimized my handwriting for efficiency of movement, with a couple of exceptions. I also have a strong tendancy to start letters from the bottom and pushing up rather than from the top pulling down. These two observations probably explain a lot of why my handwriting is as unreadable as it is. The two of us each came up with a list of stroke orders to change. For instance, I have an egregiously wasteful 'r', and my 'k' is a little less efficient and innaccurate than the more standard protocol. I've also decided to re-work my 'g's for better control, at the expense of some speed. We also discovered a slightly better way to write 'j' than either of us were using -- we both start at the top of the main part of the letter, stroke down, then go back up to dot the j. It seems just better to dot first, then add the main part underneath, saving yourself potentially a full character-height of travel time. Thanks, obviously, to Erik Jue. 3) I've looked up what tensors are many, many times, and never quite figured out what they are. There's something a bit sideways about how they're defined that somehow makes them slippery to my mind. For instance, almost every source on tensors begins by stating that they are generalizations of scalars, vectors, and matrices. This is only slightly helpful to me. There's more than one way one might imagine generalizing a matrix, for instance. I think I understand at least in part what a tensor is now. In programming terms, a tensor of rank N is a function that takes N index arguments and returns a number. For example, a matrix is a rank 2 tensor, which takes two indexes (a row number and a column number) and returns a number (the value of that row and column). A scalar (otherwise generally known as a number) is a rank 0 tensor, which takes zero indexes and returns a number. Now that I write it down, it seems so simple, but it took me a long time to figure out that function signature. Now, there's a bit more to tensors, as they also have to satisfy certain properties about invariance under changes of coordinate bases, which leads somehow to a more intrinsic definition, but I think this is a pretty good first-order approximation. Thanks also to Erik Jue!