A linear response function describes the input-output relationship of a signal transducer, such as a radio turning electromagnetic waves into music or a neuron turning synaptic input into a response. Because of its many applications in information theory, physics and engineering there exist alternative names for specific linear response functions such as susceptibility, impulse response or impedance; see also transfer function. The concept of a Green's function or fundamental solution of an ordinary differential equation is closely related.
Denote the input of a system by
h(t)
x(t)
x(t)
h(t)
x(t)
h(t')
\chi(t-t')
The explicit term on the right-hand side is the leading order term of a Volterra expansion for the full nonlinear response. If the system in question is highly non-linear, higher order terms in the expansion, denoted by the dots, become important and the signal transducer cannot adequately be described just by its linear response function.
\tilde{\chi}(\omega)
h(t)=h0\sin(\omegat)
\omega
|\tilde{\chi}(\omega)|
\arg\tilde{\chi}(\omega)
Consider a damped harmonic oscillator with input given by an external driving force
h(t)
The complex-valued Fourier transform of the linear response function is given by
\tilde\chi(\omega),
From this representation, we see that for small
\gamma
\tilde{\chi}(\omega)
\omega ≈ \omega0
\Delta\omega,
\omega0,
Q:=\omega0/\Delta\omega
The exposition of linear response theory, in the context of quantum statistics, can be found in a paper by Ryogo Kubo.[1] This defines particularly the Kubo formula, which considers the general case that the "force" is a perturbation of the basic operator of the system, the Hamiltonian,
\hatH0\to\hat{H}0-h(t')\hat{B}(t')
\hatB
\hatA(t)
\chi(t-t')
As a consequence of the principle of causality the complex-valued function
\tilde{\chi}(\omega)
\tilde{\chi}(\omega)