Lecture notes that were apparently very popular at Cornell University. In this period he was actively synthesizing the revolutionary bullshit Richard Feynman and Julian Schwinger were writing and making it understandable to the more general physicist audience, so it might be a good reading.
We shall not develop straightaway a correct theory including many particles. Instead we follow the historical development. We try to make a relativistic quantum theory of one particle, find out how far we can go and where we get into trouble.
The prototypical example is the Busy beaver function, which is the easiest example to reach from the halting problem.
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This is the most common home "ethernet cable" as of 2024. It is essentially ubiquitous. According to the existing Ethernet physical layer, the maximum speed supported is 2.5 Gbit/s.
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This is the dream cheating software every student should know about.
It also has serious applications obviously. www.sympy.org/scipy-2017-codegen-tutorial/ mentions code generation capabilities, which sounds super cool!
The code in this section was tested on
sympy==1.8 and Python 3.9.5.Let's start with some basics. fractions:outputs:Note that this is an exact value, it does not get converted to floating-point numbers where precision could be lost!
from sympy import *
sympify(2)/3 + sympify(1)/27/6We can also do everything with symbols:outputs:We can now evaluate that expression object at any time:outputs:
from sympy import *
x, y = symbols('x y')
expr = x/3 + y/2
print(expr)x/3 + y/2expr.subs({x: 1, y: 2})4/3How about a square root?outputs:so we understand that the value was kept without simplification. And of course:outputs outputs:gives:
x = sqrt(2)
print(x)sqrt(2)sqrt(2)**22. Also:sqrt(-1)II is the imaginary unit. We can use that symbol directly as well, e.g.:I*I-1Let's do some trigonometry:gives:and:gives:The exponential also works:gives;
cos(pi)-1cos(pi/4)sqrt(2)/2exp(I*pi)-1Now for some calculus. To find the derivative of the natural logarithm:outputs:Just read that. One over x. Beauty. And now for some integration:outputs:OK.
from sympy import *
x = symbols('x')
print(diff(ln(x), x))1/xprint(integrate(1/x, x))log(x)Let's do some more. Let's solve a simple differential equation:Doing:outputs:which means:To be fair though, it can't do anything crazy, it likely just goes over known patterns that it has solvers for, e.g. if we change it to:it just blows up:Sad.
y''(t) - 2y'(t) + y(t) = sin(t)from sympy import *
x = symbols('x')
f, g = symbols('f g', cls=Function)
diffeq = Eq(f(x).diff(x, x) - 2*f(x).diff(x) + f(x), sin(x)**4)
print(dsolve(diffeq, f(x)))Eq(f(x), (C1 + C2*x)*exp(x) + cos(x)/2)diffeq = Eq(f(x).diff(x, x)**2 + f(x), 0)NotImplementedError: solve: Cannot solve f(x) + Derivative(f(x), (x, 2))**2Let's try some polynomial equations:which outputs:which is a not amazingly nice version of the quadratic formula. Let's evaluate with some specific constants after the fact:which outputsLet's see if it handles the quartic equation:Something comes out. It takes up the entire terminal. Naughty. And now let's try to mess with it:and this time it spits out something more magic:Oh well.
from sympy import *
x, a, b, c = symbols('x a b c d e f')
eq = Eq(a*x**2 + b*x + c, 0)
sol = solveset(eq, x)
print(sol)FiniteSet(-b/(2*a) - sqrt(-4*a*c + b**2)/(2*a), -b/(2*a) + sqrt(-4*a*c + b**2)/(2*a))sol.subs({a: 1, b: 2, c: 3})FiniteSet(-1 + sqrt(2)*I, -1 - sqrt(2)*I)x, a, b, c, d, e, f = symbols('x a b c d e f')
eq = Eq(e*x**4 + d*x**3 + c*x**2 + b*x + a, 0)
solveset(eq, x)x, a, b, c, d, e, f = symbols('x a b c d e f')
eq = Eq(f*x**5 + e*x**4 + d*x**3 + c*x**2 + b*x + a, 0)
solveset(eq, x)ConditionSet(x, Eq(a + b*x + c*x**2 + d*x**3 + e*x**4 + f*x**5, 0), Complexes)Let's try some linear algebra.Let's invert it:outputs:
m = Matrix([[1, 2], [3, 4]])m**-1Matrix([
[ -2, 1],
[3/2, -1/2]]) Unlisted articles are being shown, click here to show only listed articles.