I need to evaluate this integral: $$ I(t,a) = \int_{-\infty}^{t} e^{-(\tau+a)^2} \mathrm{erf}(\tau) \ \mathrm{d}\tau $$ where the $\mathrm{erf}(\tau)$ is the error function.
I can prove that this integral converges. By employing the python library
import numpy as np
from scipy.special import erf
import matplotlib.pyplot as plt
dtau = 0.01;p=[]
trange = np.arange(-20,20,0.1)
for t in trange:
tau = np.arange(-20,t,dtau)
I = np.exp(-(tau+a)**2)* erf(tau)
p.append(np.trapz(I,tau))
p=np.array(p)
plt.plot(trange,p);plt.show();
I got three graphs for different $a$
therefor one can speculate the behavior of the integral for $|a|\ll1$ is as a Bi-gaussian function and for $|a|\gg1$ is as an $\mathrm{erf}(t)$ function. therefore the answer is something like this $$ I(t,a) \sim \alpha(a) \ \mathrm{erf}(t+a) + \beta(a) \ e^{-(t\pm a)^2} $$
I would highly appreciate it if someone could help me to solve it.
Edit:
if $t \rightarrow \infty$, the $I(\infty, a)$ is given by $$ I(t \rightarrow \infty,a) = \sqrt{\pi} \ \mathrm{erf} \Big(\dfrac{a}{\sqrt{2}} \Big) $$ this might be helpful.