Positive maps and finite-dimensional approximation Prerequisite proofs · Sources and terms

Trace-preserving finite models

Written by GPT-6.1 Sol (OpenAI), Ultra, October 2026. Self-checked by the writing AI. New original text: public domain (CC0).

Semidiscreteness supplies finite completely positive models, but their matrix states can have unequal weights. We will change the reconstruction map slightly, replace its state by a matrix trace, and take an ordinary trace adjoint. Both resulting maps preserve the prescribed traces exactly. Matrix contractions can then be replaced by unitaries while controlling their images.

Throughout, MM has a faithful normal tracial state τ\tau, and τm=Tr⁡/m\tau_m=\operatorname{Tr}/m. No factor or separability assumption is needed here. The inputs are the weighted recording theorem and its Hilbert bound, the rational-density channel and its commutator bound, the ucp Schwarz inequality, and the injectivity–semidiscreteness equivalence. In its finite specialization, semidiscreteness gives normal ucp recording maps and ucp reconstruction maps whose composites approximate any finite list in 22-norm. The scalar defect correction used in the properly infinite proof makes both maps unital before the following argument.

1. Rationalizing a density without losing positivity

Lemma 1.1. If T:Mm→MT:M_m\to M is ucp, then for every ε>0\varepsilon>0 there is a ucp map T′T' with ∥T′−T∥<ε\|T'-T\|<\varepsilon such that the density of τT′\tau T' has strictly positive rational eigenvalues. In particular T′T' is faithful on positive elements.

Proof. Write

τT(x)=τm(hx),h=∑i=1mλiei,λi≥0,∑iλi=m,(1)\tau T(x)=\tau_m(hx),\qquad h=\sum_{i=1}^m\lambda_i e_i,\qquad \lambda_i\ge0,\quad\sum_i\lambda_i=m, \tag{1}

where the eie_i are rank-one orthogonal projections summing to 11. Choose 0<δ<10<\delta<1. For each positive λi\lambda_i, choose a rational number

(1−δ)λi<qi<λi;(1-\delta)\lambda_i<q_i<\lambda_i;

put qi=0q_i=0 when λi=0\lambda_i=0. Define

b=∑ibiei,bi=qi/λi(λi>0),bi=1(λi=0).(2)b=\sum_i b_i e_i,\qquad b_i=q_i/\lambda_i\quad(\lambda_i>0),\qquad b_i=1\quad(\lambda_i=0). \tag{2}

Thus (1−δ)1≤b≤1(1-\delta)1\le b\le1. Set

T′(x)=T(b1/2xb1/2)+τm(x)T(1−b).(3)T'(x)=T(b^{1/2}xb^{1/2})+\tau_m(x)T(1-b). \tag{3}

Both summands are cp, and their values at 11 add to 11. For ∥x∥≤1\|x\|\le1, contractivity of TT gives

∥T′(x)−T(x)∥≤2∥1−b1/2∥+∥1−b∥≤3δ.(4)\|T'(x)-T(x)\| \le2\|1-b^{1/2}\|+\|1-b\|\le3\delta. \tag{4}

Here ∥1−b1/2∥≤δ\|1-b^{1/2}\|\le\delta follows from 1−t≤1−t1-\sqrt t\le1-t on [0,1][0,1].

Since bb commutes with hh, the new density is

h′=hb+τm(h(1−b))1=∑i(qi+c)ei,c=1−1m∑iqi>0.(5)h'=hb+\tau_m(h(1-b))1 =\sum_i(q_i+c)e_i,\qquad c=1-\frac1m\sum_iq_i>0. \tag{5}

The number cc is rational, and so are all qi+cq_i+c. Strict positivity also fills every original zero eigenspace. The density remains normalized, because τm(h′)=1\tau_m(h')=1. Choose 3δ<ε3\delta<\varepsilon. If x≥0x\ge0 and T′(x)=0T'(x)=0, then τm(h′x)=0\tau_m(h'x)=0; invertibility of h′h' gives x=0x=0. □\square

The correction in (3) changes the actual cp map as well as its density. Simply replacing hh by a rational matrix would not specify a compatible positive reconstruction map.

A state-preparation construction

There is also a state-preparation proof with a different error budget. Choose 0<α<min⁡(1,ε/2)0<\alpha<\min(1,\varepsilon/2) and positive rational numbers rir_i such that

∑iri=m,ri>(1−α)λi.\sum_i r_i=m,\qquad r_i>(1-\alpha)\lambda_i.

Such a choice is possible because the vector ((1−α)λi+α)i((1-\alpha)\lambda_i+\alpha)_i lies in this open simplex and has sum mm. Rational points in the sum-mm hyperplane are dense: approximate the first m−1m-1 coordinates rationally and define the last by subtraction; sufficiently small errors retain all strict inequalities. For m=1m=1, take r1=1r_1=1.

Put g=∑irieig=\sum_i r_i e_i and k=(g−(1−α)h)/αk=(g-(1-\alpha)h)/\alpha. Then k>0k>0 and τm(k)=1\tau_m(k)=1, so ψ(x)=τm(kx)\psi(x)=\tau_m(kx) is a state. The map

T~(x)=(1−α)T(x)+αψ(x)1\widetilde T(x)=(1-\alpha)T(x)+\alpha\psi(x)1

is ucp, has density gg under τ\tau, and satisfies ∥T~−T∥≤2α<ε\|\widetilde T-T\|\le2\alpha<\varepsilon. Thus mixing reconstruction with state preparation produces the same full conclusion, including faithfulness, while changing the actual map and filling zero eigenspaces. The first proof retains the congruence formula needed for the worked diagnostics.

2. Reconstruction maps preserving the matrix trace

Theorem 2.1. Suppose MM is injective. Given unitaries u1,…,un∈Mu_1,\ldots,u_n\in M and ε>0\varepsilon>0, there are a ucp map T:Mq→MT:M_q\to M and contractions yk∈Mqy_k\in M_q such that

τT=τq,∥T(yk)−uk∥2<ε.(6)\tau T=\tau_q,\qquad \|T(y_k)-u_k\|_2<\varepsilon. \tag{6}

Proof. Fix a small η>0\eta>0. Semidiscreteness gives ucp maps S1:M→MmS_1:M\to M_m, T1:Mm→MT_1:M_m\to M with ∥T1S1(uk)−uk∥2<η/2\|T_1S_1(u_k)-u_k\|_2<\eta/2. Put xk=S1(uk)x_k=S_1(u_k), so ∥xk∥≤1\|x_k\|\le1. Lemma 1.1 gives a faithful ucp T2T_2 with rational strictly positive density hh and ∥T2−T1∥<η/2\|T_2-T_1\|<\eta/2. Therefore

∥T2(xk)−uk∥2<η.(7)\|T_2(x_k)-u_k\|_2<\eta. \tag{7}

Write φ=τT2=τm(h ⋅)\varphi=\tau T_2=\tau_m(h\,\cdot). The improved weighted Hilbert bound in the preceding lesson implies, for every contraction xx,

∥[h1/2,x]∥2,τm2=φ(x∗x)+φ(xx∗)−2τm(h1/2x∗h1/2x)≤2−2∥T2(x)∥22.(8)\begin{aligned} \|[h^{1/2},x]\|_{2,\tau_m}^2 &=\varphi(x^*x)+\varphi(xx^*) -2\tau_m(h^{1/2}x^*h^{1/2}x)\\ &\le2-2\|T_2(x)\|_2^2. \end{aligned} \tag{8}

The two cross traces agree by cyclicity; they are real and nonnegative. From (7), ∥T2(xk)∥2>1−η\|T_2(x_k)\|_2>1-\eta and ∥T2(xk)∥2≤1\|T_2(x_k)\|_2\le1. In particular

∥[h1/2,xk]∥2,τm2<4η.(9)\|[h^{1/2},x_k]\|_{2,\tau_m}^2<4\eta. \tag{9}

Apply the rational density theorem to obtain ucp maps R:Mm→MqR:M_m\to M_q and L:Mq→MmL:M_q\to M_m satisfying

τqR=φ,φL=τq,∥LR(xk)−xk∥φ#<2η.(10)\tau_qR=\varphi,\qquad\varphi L=\tau_q,\qquad \|LR(x_k)-x_k\|_\varphi^\#<2\sqrt\eta. \tag{10}

For arbitrary aa, Schwarz and traciality of the target give

∥T2(a)∥22≤12φ(a∗a+aa∗)=(∥a∥φ#)2.(11)\|T_2(a)\|_2^2 \le\tfrac12\varphi(a^*a+aa^*)=(\|a\|_\varphi^\#)^2. \tag{11}

Set yk=R(xk)y_k=R(x_k) and T=T2LT=T_2L. These are contractions and a ucp map. Equations (7), (10) and (11) give

∥T(yk)−uk∥2<η+2η,τT=φL=τq.(12)\|T(y_k)-u_k\|_2<\eta+2\sqrt\eta, \qquad \tau T=\varphi L=\tau_q. \tag{12}

Choosing η+2η<ε\eta+2\sqrt\eta<\varepsilon proves the result. □\square

One common error budget η\eta controls the perturbed reconstruction throughout (7)–(12). The original perturbation and the semidiscrete error have already been added in (7).

3. An ordinary adjoint preserves both traces

Theorem 3.1. For every finite list a1,…,aN∈Ma_1,\ldots,a_N\in M in an injective faithfully tracial algebra and every ε>0\varepsilon>0, there are ucp maps

M→SMq→TMM\xrightarrow{S}M_q\xrightarrow{T}M

such that SS is normal and

τqS=τ,τT=τq,∥TS(aj)−aj∥2<ε.(13)\tau_qS=\tau,\qquad \tau T=\tau_q,\qquad \|TS(a_j)-a_j\|_2<\varepsilon. \tag{13}

Proof. First treat a finite list of unitaries. Choose T,ykT,y_k from Theorem 2.1 with error less than η\eta. Its ordinary trace adjoint S=T♯S=T^\sharp is normal and cp by the preceding lesson. Since τT=τq\tau T=\tau_q, its density is 11, so S(1)=1S(1)=1. Pairing with 11 gives τqS=τ\tau_qS=\tau. Both maps are L2L^2 contractions by Schwarz and their trace identities.

The adjoint identity gives the complex estimate

∣τq(S(uk)yk∗)−1∣=∣τ(uk(T(yk)−uk)∗)∣<η.(14)\left|\tau_q(S(u_k)y_k^*)-1\right| =\left|\tau(u_k(T(y_k)-u_k)^*)\right|<\eta. \tag{14}

Consequently its real part exceeds 1−η1-\eta. As both ∥S(uk)∥2\|S(u_k)\|_2 and ∥yk∥2\|y_k\|_2 are at most 11,

∥S(uk)−yk∥22<2η,∥TS(uk)−uk∥2<2η+η.(15)\|S(u_k)-y_k\|_2^2<2\eta, \qquad \|TS(u_k)-u_k\|_2<\sqrt{2\eta}+\eta. \tag{15}

Choose the small budget before applying Theorem 2.1.

For a general finite list, use an exact finite linear combination of unitaries for each element. Indeed a self-adjoint contraction bb is (v+v∗)/2(v+v^*)/2, where v=b+i(1−b2)1/2v=b+i(1-b^2)^{1/2} is unitary. Applying this to the real and imaginary parts, with their norm bounds, gives at most four unitary summands for any element. Collect their finite list and take a unitary error smaller than ε\varepsilon divided by the maximum sum of absolute coefficients. Zero elements need no tests. Linearity proves (13). □\square

In (14) the difference of the complex pairing from 11 is controlled directly. A lower bound on its absolute value alone would allow an incorrect phase and would not justify (15).

4. Replacing matrix contractions by unitaries

Lemma 4.1. Let T:Mm→MT:M_m\to M be any ucp map, let u∈Mu\in M be unitary and let y∈Mmy\in M_m be a contraction. If ∥T(y)−u∥2<η\|T(y)-u\|_2<\eta, there is a unitary v∈Mmv\in M_m with

∥T(v)−u∥2<η+2η.(16)\|T(v)-u\|_2<\eta+\sqrt{2\eta}. \tag{16}

Trace preservation of TT is unnecessary.

Proof. Extend the polar partial isometry of the square matrix yy to a unitary vv, so y=v∣y∣y=v|y|. Put φ=τT\varphi=\tau T. Schwarz gives

∥T(v−y)∥22≤φ((v−y)∗(v−y))=φ((1−∣y∣)2)≤1−φ(y∗y)≤1−∥T(y)∥22<2η.(17)\begin{aligned} \|T(v-y)\|_2^2 &\le\varphi((v-y)^*(v-y))\\ &=\varphi((1-|y|)^2) \le1-\varphi(y^*y) \le1-\|T(y)\|_2^2<2\eta. \end{aligned} \tag{17}

The scalar inequality (1−t)2≤1−t2(1-t)^2\le1-t^2 holds for 0≤t≤10\le t\le1. For the final bound, put d=∥T(y)−u∥2<ηd=\|T(y)-u\|_2<\eta. Contractivity and the reverse triangle inequality give 0≤1−∥T(y)∥2≤d0\le1-\|T(y)\|_2\le d; hence 1−∥T(y)∥22≤2d<2η1-\|T(y)\|_2^2\le2d<2\eta. This works for every positive η\eta. The triangle inequality proves (16). □\square

Corollary 4.2. Given finitely many unitaries in an injective faithfully tracial MM, they can be approximated in 22-norm by T(vk)T(v_k), where T:Mm→MT:M_m\to M is ucp, τT=τm\tau T=\tau_m, and every vkv_k is unitary. This follows from Theorem 2.1 and Lemma 4.1 with a sufficiently small initial budget. Their reconstruction images still need to be moved into an actual finite-dimensional subalgebra; the next lessons do that in a factor.

5. Problems with complete solutions

Exercise 1. In Lemma 1.1 take h=diag⁡(2,0)h=\operatorname{diag}(2,0), q1=19/10q_1=19/10, q2=0q_2=0. Compute b,c,h′b,c,h'.

Solution. Equations (2) and (5) give b=diag⁡(19/20,1)b=\operatorname{diag}(19/20,1), c=1/20c=1/20, and h′=diag⁡(39/20,1/20)h'=\operatorname{diag}(39/20,1/20). Its normalized trace is 11, its eigenvalues are positive rationals, and its previously zero eigenvalue is now positive. For any δ>1/20\delta>1/20 the required strict rational inequalities hold.

Exercise 2. Explain why the scalar correction in (3) is completely positive.

Solution. A positive scalar functional is cp. At any matrix level, [τm(xij)]≥0[\tau_m(x_{ij})]\ge0 when [xij]≥0[x_{ij}]\ge0. Tensoring this scalar positive matrix with the positive operator T(1−b)T(1-b) gives the positive block matrix [τm(xij)T(1−b)][\tau_m(x_{ij})T(1-b)]. This is exactly the amplification of the correction.

Exercise 3. Check that τm(h′)=1\tau_m(h')=1 even when hh has a kernel.

Solution. Equation (5) gives τm(h′)=m−1∑iqi+c=1\tau_m(h')=m^{-1}\sum_iq_i+c=1. The coordinates with zero eigenvalues contribute qi=0q_i=0, and the positive constant cc occurs in every coordinate. No division by a zero eigenvalue occurs in (2).

Exercise 4. Derive the cross term in (8) from the square of the commutator.

Solution. Expand (h1/2x−xh1/2)∗(h1/2x−xh1/2)(h^{1/2}x-xh^{1/2})^*(h^{1/2}x-xh^{1/2}) and take τm\tau_m. The first two terms become τm(hxx∗)\tau_m(hxx^*) and τm(hx∗x)\tau_m(hx^*x). Cyclicity makes both negative cross terms τm(h1/2x∗h1/2x)\tau_m(h^{1/2}x^*h^{1/2}x). This equals ∥h1/4xh1/4∥2,τm2\|h^{1/4}xh^{1/4}\|_{2,\tau_m}^2, so it is real and nonnegative.

Exercise 5. Give an explicit positive η\eta making the bound in (12) smaller than a prescribed ε>0\varepsilon>0.

Solution. Take η=min⁡(ε/4,ε2/64,1/4)\eta=\min(\varepsilon/4,\varepsilon^2/64,1/4). Then η≤ε/4\eta\le\varepsilon/4, and 2η≤ε/42\sqrt\eta\le\varepsilon/4. Their sum is at most ε/2<ε\varepsilon/2<\varepsilon. The extra bound η≤1/4\eta\le1/4 keeps the near-unitary lower bound positive.

Exercise 6. Why do the two trace identities in (13) imply L2L^2 contractivity?

Solution. Schwarz gives T(x)∗T(x)≤T(x∗x)T(x)^*T(x)\le T(x^*x). Applying τ\tau gives ∥T(x)∥22≤τm(x∗x)\|T(x)\|_2^2\le\tau_m(x^*x). The same argument for SS, applying τm\tau_m and using τmS=τ\tau_mS=\tau, proves its contraction inequality. Bounded elements are dense in their trace Hilbert spaces, so both maps extend contractively.

Exercise 7. Why is ∣z∣>1−η|z|>1-\eta insufficient for (15), whereas ∣z−1∣<η|z-1|<\eta suffices?

Solution. The number z=−1z=-1 has absolute value 11, but real part −1-1; a squared-distance formula involving 2Re⁡z2\operatorname{Re}z would then have the wrong bound. If ∣z−1∣<η|z-1|<\eta, then Re⁡z>1−η\operatorname{Re}z>1-\eta, which is the estimate actually used in (15).

Exercise 8. Show that the state in (17) need not be τm\tau_m.

Solution. Take M=CM=\mathbb C, m=2m=2, and T(x)=x11T(x)=x_{11}. This is ucp, but τT(e11)=1\tau T(e_{11})=1 while τ2(e11)=1/2\tau_2(e_{11})=1/2. The proof therefore uses φ=τT\varphi=\tau T rather than the normalized matrix trace. Schwarz and the scalar functional calculus inequality remain valid for this state.

Exercise 9. Explain how to extend the polar partial isometry of a square matrix to a unitary.

Solution. Its initial and final projections have the same rank, equal to the rank of the matrix. Their complements therefore have the same dimension. Choose an isometric bijection between those complements and add it to the polar partial isometry. The orthogonal initial and final partitions make the sum unitary, and the extra term annihilates ∣y∣|y|, so y=v∣y∣y=v|y| remains true.

Exercise 10. Suppose the error in Theorem 3.1 is at most γ\gamma on all unitary summands of a=∑jαjuja=\sum_j\alpha_j u_j. Bound its error on aa.

Solution. Linearity and the triangle inequality give ∥TS(a)−a∥2≤γ∑j∣αj∣\|TS(a)-a\|_2\le\gamma\sum_j|\alpha_j|. A finite list has a finite maximum of these coefficient sums. Choosing its unitary budget below the desired error divided by that maximum gives the claimed general finite-set approximation. If every element is zero, any unital trace-preserving scalar model suffices.

References and proof scope

Uffe Haagerup, A new proof of the equivalence of injectivity and hyperfiniteness for factors on a separable Hilbert space, Journal of Functional Analysis 62 (1985), 160–201. The rational perturbation and trace-preserving factorization follow that method, with a common error budget and an explicit real-part estimate. The state-preparation proof above gives an alternative perturbation with bound 2α2\alpha. Every faithfully tracial injective algebra is retained; factoriality and separable predual enter the later subalgebra conclusions. These finite maps prove no AFD conclusion by themselves.

For the trace-preserving expectation prerequisite, Matthew Daws's Conditional Expectations, Section 4, Theorem 4.1 (source label thm:main), Proof 1, gives an accessible Hilbert-space compression proof: the trace on the ambient algebra is normal, semifinite and faithful, and its restriction to the subalgebra must also be semifinite. Editable author source at commit a2d5477. The repository notice licenses those notes under CC BY-NC-SA 4.0. This supplementary reading complements the exact OA-MOD prerequisite specified above; that internal proof route and this lesson's finite-model proofs are retained.