Observable Quotients and Exact Projected Dynamics: Closure, Memory, Minimal Dynamical Completion, and Effective Field Operators
Minimal dynamical completion
Minimal dynamical completion
Theorem 6.4 says that when the resolved state is not enough to determine the resolved future. The natural question is then: how much unresolved information must be adjoined? The answer is not “all of ”. Distinct unresolved initial states may produce identical resolved responses, and directions that never affect the resolved trajectory need not be retained. We now identify exactly the right quotient.
Fix the target: the resolved response function generated by unresolved initial data alone.
Definition 7.1 (Unresolved response map).
Let carry the topology of uniform convergence on compact subsets of , i.e. the locally convex topology generated by the seminorms , . Define the linear map is well defined (its values are continuous by Theorem 6.2) and continuous: for every .
Definition 7.2 (Dynamically invisible directions).
Set
Lemma 7.3.
is a closed subspace of , and consequently is a Hilbert space with the quotient norm .
Proof. For each fixed the operator is bounded, so its kernel is a closed subspace. By (7.2), is the intersection of a family of closed subspaces, hence a closed subspace. The quotient of a Hilbert space by a closed subspace is a Hilbert space with the quotient norm, exactly as established after (2.2). ◻
Two unresolved initial states are called dynamically equivalent for resolved evolution when their difference lies in .
Theorem 7.4 (Minimal unresolved-state completion).
Under Assumption 6.1:
is constant exactly on the cosets of : for , if and only if .
Consequently descends to an injective continuous linear map with , where is the quotient map.
(Universality / minimality.) Let be any set and any surjective map which determines every resolved response function, meaning that there exists a map with Then there is a unique map with and is surjective. If moreover is a vector space and is linear, then is linear.
Thus is the coarsest extension of the resolved data that retains every unresolved distinction visible in the resolved response, and every sufficient extension maps onto it.
Proof. (1) is linear, so iff iff .
(2) By (1), the prescription (7.4) is independent of the representative, hence well defined; it is linear because and are; and it is injective because forces , i.e. . Continuity: for each , for every ; taking the infimum over gives .
(3) Existence of . We first show separates no more coarsely than ; that is, . Indeed if then by (7.5) so by (1) , i.e. . Now define as follows: given , use surjectivity of to choose with , and set . The implication just proved shows this is independent of the choice of , so is a well-defined map , and (7.6) holds by construction. It is surjective because is: any equals .
Uniqueness of . If also satisfies , then for every pick with ; then . Hence . (Uniqueness uses surjectivity of , which is why it is included in the hypothesis: a nonsurjective extension leaves undetermined on the unreached part of .)
Linearity. If is a vector space and is linear and surjective, then for , and scalars we have , so . ◻
We have stated the universal property in plain terms of maps and quotients of sets and vector spaces; no categorical apparatus is needed, and none is used. Theorem 7.4(3) is the minimal-completion statement of [24] for the specific target relation , proved here directly so that the present paper stands alone.
Remark 32 (Minimality is relative to the target).
may be strictly smaller than , as Case B of Example 6.6 shows. The directions in are not “physically absent” in any absolute sense: they may evolve nontrivially under , they may carry energy, they may be visible to a different readout. They are invisible to the resolved response function, and that is the target relative to which minimality is asserted. Change the target, ask instead for the resolved response and some other functional of the unresolved sector, and the minimal completion changes accordingly. This target-relativity is exactly the phenomenon isolated in [23]; it is not a defect but the content of the theorem.
Theorem 7.6 (Completed initial data close the resolved trajectory).
Under Assumption 6.1, define the completed initial state space Then the pair determines the resolved trajectory uniquely on . Precisely: for each , the linear Volterra equation of the second kind equivalent to (6.8) with datum , has exactly one continuous solution , and this solution depends on only through .
Proof. Dependence only on . The kernel is determined by and alone, and the only occurrence of in (7.8) is through , which by Theorem 7.4(1) depends only on the class .
Existence and uniqueness. Fix . Equation (7.8) has the form on the Banach space with the sup-norm, where is continuous, and is the bounded linear Volterra operator Both and are bounded, with (the supremum is finite because is norm-continuous on the compact ). An elementary induction gives the standard Volterra estimate so ; hence is a contraction for large, is invertible with convergent in operator norm, and is the unique solution in [5, Ch. 2, Thm. 3.5]. Since was arbitrary and solutions on nested intervals agree by uniqueness, is uniquely determined on . ◻
Theorems 7.4 and 7.6 together give the precise cost of failed descent. The resolved state alone is insufficient (Theorem 6.4). The resolved state plus all of is sufficient but wasteful. The resolved state plus is sufficient (Theorem 7.6) and minimal (Theorem 7.4). This is the exact sense in which the unresolved sector must be “completed” into the observable theory, and it is the exact sense in which only part of it need be.
Proposition 7.7 (Finite-dimensional observability criterion).
Suppose . Then and , where is the observability map
Proof. Fix . Since is bounded, is given by the everywhere-convergent power series which is a real-analytic (indeed entire) -valued function of . Such a function vanishes identically on if and only if all its Taylor coefficients at vanish, i.e. iff (One direction is trivial; for the other, differentiate (7.11) times at , which is legitimate by uniform convergence of the differentiated series on compacts.)
It remains to see that in (7.12) the range suffices. By the Cayley–Hamilton theorem applied to the operator on the -dimensional space , is a linear combination of ; by induction, every power with is a linear combination of . Hence if for , then applying to the corresponding linear combination gives for every as well. This proves (7.9).
Finally, (7.9) says exactly , so by rank–nullity . ◻
Remark 35 (Relation to Kalman observability).
Equation (7.10) is the observability map of linear control theory [6, 15] for the finite-dimensional linear system with state , state matrix , and output matrix : the pair is observable exactly when , i.e. exactly when , i.e. exactly when every unresolved direction leaves a trace in the resolved response and the whole of must be retained. The dictionary must be read with care, however. What (7.10) tests is observability of the unresolved sector through the resolved-response output. It is not a claim that the full source system is observable from the resolved readout, which would additionally require that the resolved sector’s own dynamics and the coupling be taken into account. We assert only what (7.9) states: , and hence , is computable by a finite rank condition. The general Hilbert space case has no such finite reduction; there is defined by (7.2) and closed by Lemma 7.3, and no analogue of Cayley–Hamilton is available.