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This MO question asks for a geometric interpretation of the trace of a linear transformation. I'm wondering about a geometric interpretation of partial trace.

Given a linear transformation $f: X\otimes U\to Y\otimes U,$ the partial trace is a linear transformaton $\text{Tr}^U_{X,Y}\;\;(f):X\to Y$ satisfying certain properties. Basically, if you think of $f$ as a matrix with $|X|\times|Y|$-many $|U|\times|U|$ blocks, then $\text{Tr}(f)$ is given by taking the trace of each block.

So how can I visualize this operation? How can I tell a story about it, especially without resorting to a choice of bases?

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    $\begingroup$ a physics interpretation is that the partial trace is the way one obtains marginal probability distributions in quantum mechanics: the density matrix $\rho$ describes the probability distribution $P_{X,U}$ of the combined systems $X$ and $U$ and by performing the partial trace over $U$ one obtains a new density matrix $\rho_X$ that describes the marginal distribution $P_X$ of system $X$ alone; this is not the geometric interpretation you are asking for, but I would think that if you have a "geometric interpretation" of the marginal distribution then you're done. $\endgroup$ Commented Mar 23, 2015 at 7:13
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    $\begingroup$ Partially dualized, $f\in \mathrm{Hom}(X,Y)\otimes (U\otimes U^*)$. Partial trace is then the linear map $\mathrm{Hom}(X,Y) \otimes (U\otimes U^*) \to \mathrm{Hom}(X,Y)$ given by $\mathrm{id} \otimes \delta$, where $\delta \in U^*\otimes U \cong (U\otimes U^*)^*$ is the dualized version of the identity map $U\to U$. I don't know if this is very geometric, but it's certainly an invariant description of the operation. $\endgroup$ Commented Mar 23, 2015 at 13:26
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    $\begingroup$ In other words, if $A=X \otimes Y$ is tensor product of density matrices, then $\text{tr}_2(A)=X$ and $\text{tr}_1(A)=Y$ (this is the marginalizing out that Carlo mentioned). $\endgroup$
    – Suvrit
    Commented Mar 23, 2015 at 23:49

1 Answer 1

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We observe that if $Z$ is a finite-dimensional inner product space, and $f:Z\rightarrow Z$, then $$\text{Tr}(f)=n\cdot\int_{z\in S}\langle f(x),x\rangle dm(x)$$ whenever $m$ is the normalized probability measure on the unit ball $S$ of $Z$ and $n$ is the dimension of $Z$.

This observation was given by Yemon Choi as an answer to the corresponding question for a geometric interpretation of the trace. This formula can be obtained from the formula for the trace using bases simply by integrating over all bases. This observation extends to the following coordinate free formula for the partial trace.

Proposition: Suppose that $X,Y,U$ are finite-dimensional inner product spaces. If $f:X\otimes U\rightarrow Y\otimes U$ is a linear mapping, then $$\langle\text{Tr}_{X,Y}^{U}(f)x,y\rangle=n\cdot\int_{z\in S}\langle f(x\otimes z),y\otimes z\rangle dm(z)$$ whenever $x,y\in X$, $S$ is the unit ball in $U$, $n=\dim(U)$, and $m$ is the normalized probability measure on $S$.

Proof: For this proof, we shall define the partial trace as the unique linear operator $\text{Tr}_{X,Y}^{U}:L(X\otimes U,Y\otimes U)\rightarrow L(X,Y)$ where $\text{Tr}_{X,Y}^{U}(R\otimes T)=R\cdot\text{Tr}(T)$ whenever $T\in L(U,U),R\in L(X,Y)$.

It suffices to prove our equation in the case when $f=R\otimes T$ for some linear operators $R:X\rightarrow Y,T:U\rightarrow U$ since the general case follows from linearity. In this special case, we have

$$\langle \text{Tr}_{X,Y}^{U}(f)x,y\rangle=\langle\text{Tr}_{X,Y}^{U}(R\otimes T)(x),y\rangle$$

$$=\langle R(x)\text{Tr}(T),y\rangle=\langle R(x),y\rangle\text{Tr}(T) =\langle R(x),y\rangle\cdot n\cdot\int_{z\in S}\langle T(z),z\rangle dm(z)$$

$$=n\int_{z\in S}\langle \langle R(x),y\rangle\langle T(z),z\rangle dm(z) =n\int_{z\in S}\langle \langle (R\otimes T)(x\otimes z),y\otimes z\rangle dm(z)$$

$$=n\int_{z\in S}\langle \langle f(x\otimes z),y\otimes z\rangle dm(z)$$

Q.E.D.

This result can also be obtained by integrating the right hand side in the following formula/definition for the partial trace for a finite dimensional inner product space that holds whenever $(e_{1},\dots,e_{n})$ is a basis of $U$:

$$\langle\text{Tr}_{X,Y}^{U}(f)(x),y\rangle=\sum_{k=1}^{n}\langle f(x\otimes e_{i}),y\otimes e_{i}\rangle.$$

Observe that the above formula does have some coordinates, but it only has the coordinates for the space $U$, so it is coordinate free for $X,Y$ but not for $U$.

Now, we can even get an explicit basis-free formula for $\text{Tr}_{X,Y}^{U}(f)(x)$ at the expense of having to compute a double integral. For the following formula, $n_{Z}$ is the dimension of a vector space $Z$, $S_{Z}$ is the unit ball in $Z$, and $m_{Z}$ is the normalized probability measure on $S_{Z}$.

Observe that if $f_{1},\dots,f_{m}$ is a basis for $Y$, then $y=\sum_{k=1}^{m}\langle y,e_{k}\rangle e_{k}$. Therefore, $y=n_{Y}\int_{S_{Y}}\langle y,z\rangle\cdot z dm_{Y}(z)$ for each $y\in Y$. Therefore,

$$\text{Tr}_{X,Y}^{U}(f)(x)=n_{Y}\int_{S_{Y}}\langle\text{Tr}_{X,Y}^{U}(f)(x),y\rangle\cdot y\cdot dm_{Y}(y)$$

$$=n_{Y}\int_{S_{Y}}n_{U}\int_{S_{U}}\langle f(x\otimes z),y\otimes z\rangle dm_{U}(z)ydm_{Y}(y)$$

$$=n_{Y}n_{U}\int_{S_{Y}}\int_{S_{U}}\langle f(x\otimes z),y\otimes z\rangle\cdot y dm_{U}(z)dm_{Y}(y).$$

Of course, this formula can also be obtained from the definition of the partial trace involving coordinates where one averages over all choices of bases.

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