AxiomOfChoice
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I'm trying to understand the spectrum and resolvent of a linear operator on a Banach space in as much generality as I possibly can.
It seems that the furthest the concept can be "pulled back" is to a linear operator T: D(T) \to X, where X is a Banach space and D(T)\subseteq X. But here are a few questions:
(1) Doesn't D(T) necessarily have to be a subspace of X for this concept to make any sense? For instance, if it's not a subspace, there can be elements x,y for which Tx and Ty make sense, but for which T(x+y) makes no sense, since x+y might not be an element of D(T).
(2) The Wikipedia article here says that, in order for \lambda \in \rho(T), we need both (1) (T-\lambda)^{-1} exists and (2) (T-\lambda)^{-1} is defined on a dense subset of X. Is this equivalent to saying that \text{Ran} (T-\lambda) must be a dense subset of X and that (T-\lambda): D(T) \to \text{Ran} (T - \lambda) must be a bijection?
It seems that the furthest the concept can be "pulled back" is to a linear operator T: D(T) \to X, where X is a Banach space and D(T)\subseteq X. But here are a few questions:
(1) Doesn't D(T) necessarily have to be a subspace of X for this concept to make any sense? For instance, if it's not a subspace, there can be elements x,y for which Tx and Ty make sense, but for which T(x+y) makes no sense, since x+y might not be an element of D(T).
(2) The Wikipedia article here says that, in order for \lambda \in \rho(T), we need both (1) (T-\lambda)^{-1} exists and (2) (T-\lambda)^{-1} is defined on a dense subset of X. Is this equivalent to saying that \text{Ran} (T-\lambda) must be a dense subset of X and that (T-\lambda): D(T) \to \text{Ran} (T - \lambda) must be a bijection?