A linear differential equation is linear in the unknown function and its derivatives.
For a system of linear differential equations , a fundamental matrix has columns forming a basis of its solution space. It solves and is invertible at every time in its interval. Every solution is for a constant vector : differentiating gives zero. Invertibility at one time implies invertibility throughout the interval by uniqueness of the initial value problem. This notion is distinct from a Markov-chain fundamental matrix or the projective-geometric matrix used in stereo vision.
If and , differentiation of the determinant gives . For a planar periodic orbit this gives the nontrivial Floquet multiplier, since the tangent multiplier is one.
For a continuous periodic coefficient matrix , a fundamental matrix for , normalized by , obeys . The invertible matrix has a complex matrix logarithm; set and . Since commutes with , direct substitution gives and proves the factorization. A real logarithm is not required for this complex representation.
The eigenvalues of are Floquet multipliers. All solutions are bounded for forward time when every multiplier has modulus at most one and those on the unit circle have no nontrivial Jordan blocks. In a real undamped second-order scalar equation with no first-derivative term, the monodromy determinant is one. Distinct conjugate unit-modulus multipliers give bounded solutions; a nontrivial Jordan block at multiplier or gives an unbounded second solution even when one periodic or antiperiodic solution exists.
The maximal asymptotic growth rate of a finite-dimensional periodic linear differential equation is , where is the coefficient period and the monodromy matrix of a periodic linear system. The spectral radius selects the dominant Floquet multiplier. Generic initial data attain this rate; data lying entirely in other invariant subspaces can grow or decay at different rates.
For with coefficient period , the monodromy matrix maps to . Its eigenvalues are the Floquet multipliers. For piecewise constant coefficients it is the time-ordered product of the segment matrix exponentials, with the earliest segment on the right. Its determinant is .
For the homogeneous linear differential equation , a characteristic root is a root of a polynomial . A simple root supplies an exponential solution ; a root of multiplicity supplies for . The sign of the real part of determines spatial growth or decay.
The Laplace contour-integral method seeks a solution in the form
Replacing multiplication by with differentiation of in and integrating by parts turns the differential equation for into a first-order equation for . The contour must make the resulting endpoint term vanish; finite endpoints are often branch points of , while infinite ends must enter sectors where the exponential decays.
A homogeneous linear differential equation has zero forcing term. Its solutions are closed under addition and scalar multiplication.
The solutions of a homogeneous linear differential equation on a common domain form a vector space. For a regular scalar equation of order , prescribing the first initial data at an ordinary point gives an isomorphism of this solution space with the scalar field to the power .
A linearized equation retains terms first order in a perturbation about a reference solution. Its coefficients are determined by derivatives of the original nonlinear equation evaluated on that reference solution.
An inhomogeneous linear differential equation has a nonzero forcing term. Its general solution is one particular solution plus the general solution of the associated homogeneous equation.

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The name is a bit obscure if you don't think in very generalized terms right out of the gate. It refers to a linear polynomial of multiple variables, which by definition must have the super simple form of:
and then we just put the unknown and each derivative into that simple polynomial:
except that now the are not just constants, but they can also depend on the argument (but not on or its derivatives).
Explicit solutions exist for the very specific cases of: