Entanglement fidelity of amplitude damping Created 2026-10-07 Updated 2026-10-14
The Kraus formula for entanglement fidelity applies to any input, including mixed qubit states. For the amplitude damping channel, the diagonal Kraus trace is and the jump Kraus trace has squared modulus . Summing them gives the formula. Ground-state inputs have unit entanglement fidelity; excited-state inputs have fidelity .
Finite-dimensional quantum compression converse Created 2026-10-06 Updated 2026-10-07
If encoding and decoding quantum channels factor through a -dimensional space, their composite Kraus operators all have matrix rank at most . The rank bound for a weighted operator trace and the Kraus formula for entanglement fidelity imply
Thus high operation fidelity requires the leading eigenvalues of the source density operator to carry almost all its probability. The bound applies to arbitrary completely positive trace-preserving encoders and decoders.
The Schumacher compression theorem concerns a memoryless quantum information source with average density matrix on a finite-dimensional Hilbert space. For uses the average state is . Compression consists of an encoding quantum channel into a space of dimension and a decoding channel back to the original block space, with asymptotic rate qubits per source use. The optimal reliable rate is : every larger rate is achievable, and no smaller rate is reliable. This holds for average pure-source fidelity; the direct construction also preserves a purification reference, and the converse for that stronger entanglement fidelity criterion holds with fidelity tending to zero below the threshold. The encoding and decoding are deterministic channels; no free classical transmission of the source label is allowed.
Diagonalize and omit zero-probability eigenvalues when sampling. Define the quantum typical subspace projector by retaining product eigenvectors with
The sampled random variable has expectation . The weak law of large numbers gives . Every retained eigenvalue is at least , and the total probability is at most one, so
This proves the two typical subspace theorem estimates used in the direct part.
Write . Encode its range isometrically into a compressed space and reserve one orthogonal failure flag. Decode the range back isometrically and the failure flag to a fixed pure state . This typical-subspace compression with a failure flag is a physical channel whose composite action is
Indeed its Kraus operators are and , where the form an orthonormal basis of , and their adjoint products sum to . The Kraus formula for entanglement fidelity gives
For any pure-state ensemble of , the average squared quantum fidelity is at least this number: apply convexity of separately to the amplitudes with their source probabilities. Thus average fidelity also tends to one. The compressed dimension is at most , and its rate is at most . Choose for any prescribed . One may also take : the finite spectral information variance and Chebyshev's inequality still give , with rate tending to . A pure source, , can simply be re-prepared exactly without sending any qubits.
For the coherent converse, we prove the finite-dimensional quantum compression converse. If the compressed space has dimension , the state of reference plus compressed system has a pure-state decomposition with Schmidt rank at most . Applying decoder Kraus operators locally cannot increase the Schmidt rank of those vectors, so the final reference–output state has Schmidt number at most . Let purify the source, with squared Schmidt coefficients equal to the decreasing eigenvalues of . For any normalized vector of Schmidt rank at most , its reference support lies in a rank-at-most- projector . Hence
The last bound follows by maximizing subject to and their sum at most . Average over a Schmidt-rank-bounded decomposition of the final state to obtain .
At rate , choose . The total source probability outside the quantum typical subspace tends to zero, while every eigenvalue inside it is at most . Therefore for ,
This argument allows arbitrary encoding and decoding channels, not only subspace projection.
For completeness, average pure-source reliability also forces the same rate, even though it is a weaker criterion than entanglement fidelity. Here is a separate converse for that formulation. Let the emitted block pure states be , with probabilities , and let be the decoded states. If their mean squared fidelity tends to one, then their mean trace distance tends to zero, since . This inequality follows by choosing a purification with that overlap and using contraction of trace distance under a partial trace.
We need only an elementary entropy continuity from Jordan decomposition bound, derivable from Question 4. If , write the positive and negative parts of as . The common density matrix
and the two mixture bounds give
Here is increasing and concave, . Apply this in block dimension , both to the average states and to individual outputs, using convexity of trace distance and concavity of . Since the original ensemble is pure, its Holevo quantity is . The decoded ensemble has
The Holevo quantity under a quantum channel cannot increase. To specify the entropy ingredient, Strong subadditivity of Von Neumann entropy states . Attach the classical source label , dilate the decoder isometrically to , and trace out . The displayed inequality says ; the isometry preserves the input mutual information. Since of a labelled ensemble is its Holevo quantity, this proves the needed decoder monotonicity. Before decoding, the system has dimension , so its Holevo quantity is at most . Thus and the rate cannot be below . Both operational fidelity formulations therefore have the claimed noiseless coding threshold.
For Kraus operators , the Kraus formula for entanglement fidelity is
Indeed each Kraus contribution to the purified-state overlap is , and the expectation in a purification is . In this case,
The entanglement fidelity of amplitude damping is thus
For , this is one. For a ground-state input it is one for every , whereas for an excited-state input it is . These checks agree with the physical relaxation mechanism.
Diagonalize the source average , using its positive eigenvalues. For fixed , let project onto product eigenvectors whose eigenvalues obey
The typical subspace theorem states that, for every and all sufficiently large ,
The probability statement is the weak law of large numbers applied to ; the dimension bounds follow by summing the typical eigenvalue bounds. This explains why the quantum typical subspace retains almost all probability using about qubits.
For choose . Measure . On success, encode the projected state isometrically into a space of dimension ; on failure, output a separate fixed flag. Decode the successful sector by the inverse isometry, and map the flag to a fixed state . The compressed dimension is at most , hence fits within rate for all sufficiently large . Both maps are trace-preserving quantum channels, not merely successful postselected operations.
Writing , the composite channel is
For a pure source signal , set . Its squared quantum fidelity after the composite channel is at least . Since the source is memoryless, its average state on uses is . Convexity of the square gives
The Kraus formula for entanglement fidelity gives the same lower bound for , because one Kraus operator is and the other terms are nonnegative. Taking proves reliable compression at every , in both average pure-signal fidelity and the stronger entanglement-fidelity sense. This is typical-subspace compression with a failure flag.
Choose Kraus representations
The composite quantum channel has Kraus operators . Each has matrix rank at most , because it factors through the -dimensional space , and
The operation fidelity uses the unsquared quantum fidelity on a purification of a density operator, so its square is entanglement fidelity. The Kraus formula for entanglement fidelity gives
Indeed each overlap equals .
For any one of these Kraus operators , let be the orthogonal projection onto its image, of matrix rank . Since , the Cauchy-Schwarz inequality for the Hilbert-Schmidt inner product gives the rank bound for a weighted operator trace:
The last step uses part (i) at , followed by nonnegativity of the eigenvalues of the density operator . Summing over the Kraus operators and using their completeness relation proves the finite-dimensional quantum compression converse:
No invertibility of , or restriction to an isometric decoder, was used.
Measure the quantum typical subspace projector . Encode its successful sector isometrically and reserve one orthogonal compressed flag for failure; decode the flag to a fixed state. The composite channel is . It is trace preserving. The Kraus formula for entanglement fidelity gives the displayed lower bound, while convexity of the square gives the same bound for average pure-source fidelity. One flag adds only a vanishing asymptotic rate overhead.