Symbolic computation guide

Symbolic Computation Guide

A skill for using computer algebra systems (CAS) in mathematical research. Covers symbolic differentiation, integration, equation solving, series expansion, linear algebra, and polynomial arithmetic using SymPy, SageMath, and Mathematica, with practical workflows for research mathematics.

SymPy Fundamentals

Symbolic Expressions and Manipulation

from sympy import (
    symbols, expand, factor, simplify, cancel, apart,
    sin, cos, exp, log, sqrt, pi, oo, I,
    Rational, Eq, solve, solveset, S
)

x, y, z, t, n, k = symbols("x y z t n k")
a, b, c = symbols("a b c", real=True)

# Expression manipulation
expr = (x + 1) ** 3
expanded = expand(expr)       # x**3 + 3*x**2 + 3*x + 1
factored = factor(expanded)   # (x + 1)**3

# Trigonometric simplification
from sympy import trigsimp
trig_expr = sin(x)**2 + cos(x)**2
simplified = trigsimp(trig_expr)  # 1

# Partial fraction decomposition
rational = (x**2 + 2*x + 3) / ((x + 1) * (x + 2) * (x + 3))
partial = apart(rational, x)
# 3/(2*(x + 3)) - 2/(x + 2) + 1/(2*(x + 1))

Calculus

from sympy import diff, integrate, limit, series, Sum, Product

# Differentiation
f = x**3 * exp(-x) * sin(x)
f_prime = diff(f, x)
f_double_prime = diff(f, x, 2)

# Integration
# Definite integral
area = integrate(exp(-x**2), (x, -oo, oo))  # sqrt(pi)

# Indefinite integral
antideriv = integrate(x * sin(x), x)  # -x*cos(x) + sin(x)

# Limits
lim_result = limit(sin(x) / x, x, 0)  # 1
lim_inf = limit((1 + 1/n)**n, n, oo)   # E (Euler's number)

# Taylor series
taylor = series(exp(x) * cos(x), x, 0, n=6)
# 1 + x - x**3/3 - x**4/6 + ...

# Summation
harmonic = Sum(1/k, (k, 1, n))
partial_sum = harmonic.doit()  # harmonic(n) -- returns harmonic number

geometric = Sum(x**k, (k, 0, oo))
closed_form = geometric.doit()  # Piecewise(1/(1 - x), Abs(x) < 1)

Equation Solving

# Algebraic equations
solutions = solve(x**3 - 6*x**2 + 11*x - 6, x)  # [1, 2, 3]

# System of equations
system_sol = solve([
    2*x + 3*y - 7,
    x - y + 1
], [x, y])  # {x: 4/5, y: 9/5}

# Differential equations
from sympy import Function, dsolve, Derivative
f = Function("f")

# f''(x) + f(x) = 0  (simple harmonic oscillator)
ode = Eq(f(x).diff(x, 2) + f(x), 0)
general_solution = dsolve(ode, f(x))
# f(x) = C1*sin(x) + C2*cos(x)

# With initial conditions
particular = dsolve(ode, f(x), ics={f(0): 1, f(x).diff(x).subs(x, 0): 0})
# f(x) = cos(x)

Linear Algebra

Symbolic Matrix Operations

from sympy import Matrix, eye, zeros, det, Rational

# Define a symbolic matrix
A = Matrix([
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 10]
])

# Basic operations
print(f"Determinant: {det(A)}")           # -3
print(f"Inverse:\n{A.inv()}")
print(f"Eigenvalues: {A.eigenvals()}")
print(f"Rank: {A.rank()}")

# Characteristic polynomial
lam = symbols("lambda")
char_poly = (A - lam * eye(3)).det()
char_poly = expand(char_poly)

# Jordan normal form
P, J = A.jordan_form()

# Null space and column space
null = A.nullspace()
col_space = A.columnspace()

# Symbolic matrix with parameters
M = Matrix([
    [a, b],
    [c, a]
])
eigenvals = M.eigenvals()  # {a - sqrt(b*c): 1, a + sqrt(b*c): 1}

SageMath for Research

Number Theory

# SageMath syntax (Python-based, but with enhanced number theory)
# Run in SageMath environment or via sage -python

"""
# Prime factorization
factor(2024)  # 2^3 * 11 * 23

# Modular arithmetic
R = IntegerModRing(17)
R(3)^(-1)  # multiplicative inverse of 3 mod 17

# Elliptic curves
E = EllipticCurve(QQ, [-1, 0])
E.rank()
E.torsion_subgroup()
E.gens()

# Polynomial rings
R.<x,y> = PolynomialRing(QQ)
I = R.ideal(x^2 + y^2 - 1, x - y)
I.groebner_basis()  # [y^2 - 1/2, x - y]

# Group theory
G = SymmetricGroup(4)
G.order()           # 24
G.center()
G.normal_subgroups()
"""

Combinatorics and Graph Theory

"""
# SageMath combinatorics
Partitions(10).cardinality()  # 42

# Graph theory
G = graphs.PetersenGraph()
G.chromatic_number()      # 3
G.is_vertex_transitive()  # True
G.automorphism_group().order()  # 120

# Posets and lattices
P = posets.BooleanLattice(3)
P.is_lattice()
P.mobius_function(P.bottom(), P.top())
"""

Mathematica / Wolfram Language

Common Research Patterns

(* Symbolic integration *)
Integrate[x^n * Exp[-x], {x, 0, Infinity}, Assumptions -> n > -1]
(* Result: Gamma[1 + n] *)

(* Solve a PDE *)
DSolve[D[u[x, t], t] == k * D[u[x, t], {x, 2}], u[x, t], {x, t}]

(* Asymptotic expansion *)
Series[Gamma[n + 1], {n, Infinity, 3}]

(* Minimize with constraints *)
NMinimize[{x^2 + y^2, x + y >= 1}, {x, y}]

(* Compute a sum in closed form *)
Sum[1/k^2, {k, 1, Infinity}]  (* Pi^2/6 *)

Practical Workflows

Verifying Research Computations

Common CAS workflow in mathematical research:

1. Conjecture formulation: Test conjectures for small cases programmatically
2. Identity verification: Verify algebraic identities symbolically
3. Closed-form discovery: Use pattern matching and OEIS lookup
4. Proof assistance: Compute bounds, verify inequalities
5. Counterexample search: Systematically search parameter spaces

from sympy import simplify, Abs

def verify_identity(lhs, rhs):
    """Verify a proposed mathematical identity symbolically."""
    diff = simplify(lhs - rhs)
    if diff == 0:
        return "VERIFIED: identity holds symbolically"
    else:
        return f"NOT VERIFIED: difference = {diff}"

# Example: verify Cauchy-Schwarz for 2D
a1, a2, b1, b2 = symbols("a1 a2 b1 b2", real=True)
lhs = (a1*b1 + a2*b2)**2
rhs = (a1**2 + a2**2) * (b1**2 + b2**2)
diff = expand(rhs - lhs)
# (a1*b2 - a2*b1)**2 >= 0, confirming Cauchy-Schwarz

Tools and Resources

• SymPy: Pure Python CAS, integrates with Jupyter and NumPy
• SageMath: Comprehensive open-source math system (wraps GAP, PARI, Singular, etc.)
• Mathematica / Wolfram Alpha: Commercial CAS with unmatched integration database
• Maxima: Free CAS (Lisp-based), used in wxMaxima GUI
• PARI/GP: Specialized in number theory computations
• Macaulay2: Commutative algebra and algebraic geometry
• GAP: Computational group theory
• OEIS (oeis.org): Online Encyclopedia of Integer Sequences for pattern identification