If $\phi$ is a test function (compactly supported, smooth) on $\mathbb R^d$ and T a distribution, is the following calculation correct? $$(\partial{x_j}\phi)*T(x)=T((\partial{x_j}\phi)(x-.))=\partial{x_j}T(-\phi(x-.))=(-\phi)*\partial{x_j}T$$ where $\phi(x-.)$ denotes the function $y \to \phi(x-y)$ and the convolution of a test function and a distribution is a function in x whose value is the value of the distribution evaluated at the above function. I'm asking since in my notes the equality of the first and last term is said to be without the minus sign, so Im not quite sure whether Im doing smth wrong...
Derivative of convolution of distribution and test function
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analysis
distribution-theory
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0There is definitely an error in your calculation, and I assume a missing inner derivative in $\partial x_j (y\to \phi(x-y))$. – 2017-01-18
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0Yeah, I figured it out, didnt do the chain rule on y->x-y – 2017-01-18