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Let
be the set of
errors that we wish to be able to correct. When is there a decoding
procedure for the code
such that all errors in
are
corrected? When such a decoding procedure exists, we say that
is ``correctable'' (by
). A situation in which
correctability of
is apparent occurs when the errors
are unitary operators satisfying the condition that
are mutually orthogonal subspaces. The repetition code
has this property for the set of errors consisting of the identity and
Pauli operators acting on a single qubit. In this situation, the
procedure for decoding is to first make a projective measurement to
determine which of the subspaces
the state is in, and
then to apply the inverse of the error operator,
.
This situation is not far from the generic one. One
characterization of correctability is in the following theorem:
![\begin{displaymath}
% latex2html id marker 1871\begin{minipage}[b]{6in}\textbf...
... to a restriction to $C$\ of a unitary operator. \end{minipage}\end{displaymath}](img510.png) |
(36) |
To relate this characterization to detectability, note that the two
properties imply that
is orthogonal
to
if
, and
restricted
to
is proportional to the identity on
. In other words, the
are detectable. This detectability
condition applied to the original error set constitutes a second
characterization of correctability, given in the next theorem:
![\begin{displaymath}
% latex2html id marker 1888\begin{minipage}[b]{6in}\textbf...
...}E}_i\in{\color{red}{\cal E}}\}$\ are detectable.\end{minipage}\end{displaymath}](img518.png) |
(37) |
Before explaining the characterizations of correctability, we consider
the situation of
qubits, where the characterization by
detectability (37) leads to a useful relationship
between minimum distance and correctability of low weight errors:
![\begin{displaymath}
% latex2html id marker 1902\begin{minipage}[b]{6in}\textbf...
... of errors of weight at most $e$\ is correctable.\end{minipage}\end{displaymath}](img520.png) |
(38) |
This theorem follows by
observing that the weight of
is at most
the sum of the weights of the
. As a result of this
observation, the problem of finding good ways of correcting all errors
up to a maximum weight reduces to that of constructing codes with
sufficiently high minimum distance. Thus questions such as ``what is the
maximum dimension of a code of minimum distance
on
qubits?''
are of great interest. As in the case of classical coding theory this
problem appears to be very difficult in general. Answers are known
for small
[6] and there are asymptotic
bounds [23]. Of course, for achieving low error
probabilities, it is not necessary to correct all errors of weight
, just almost all such errors. For example, the concatenated
codes used for fault-tolerant quantum computation achieve this goal
(see Sec. 7).
For the remainder of this section we explain the characterizations of
correctability. Using the conditions for detectability from the
previous section, the condition for correctability in
Thm. 37 is equivalent to
This condition is preserved under a linear change of basis
for
. That is, if
is any invertible
matrix with coefficients
, we can
define new error operators
.
For the
, the left side of Eq. 39 is
where
is the matrix formed from the
. Using
the fact that
is a positive semidefinite matrix (that is, for
all
,
and
), we can choose
such that
is of the form
. In this matrix, the upper
left block is the identity operator for some dimension.
An important consequence of invariance under a change of basis of
error operators is that the set of errors correctable by a particular
code and decoding procedure is linearly closed. Thus, if
and
are corrected by the decoding procedure, then so is
. This observation also follows from the
linearity of quantum mechanically implementable operations.
We explain the condition for correctability by using the subsystems
interpretation of decoding procedures. For simplicity, assume that
. To show that correctability of
implies
detectability of all
, suppose
that we have a decoding procedure that recovers the information
encoded in
after any of the errors in
have occurred. Every
physically realizable decoding procedure can be implemented by first
adding ``ancilla'' quantum systems in a prepared pure state to form a
total system labeled
, then applying a unitary map
to the state of
, and finally separating
into a pair of systems
, where
corresponds to the syndrome subsystem, and
is a
quantum system with the same dimension as the code that carries the
quantum information after decoding. Denote the state space of the
physical system containing
as
, and the state space of system
by
, where
is any one
of the other systems. Let
be the unitary operator that encodes
information by mapping
onto
. We have
the following relationships:
 |
(41) |
Here, we used bidirectional arrows ``
'' to emphasize
that the operators
and
can be inverted on their range and
therefore identify the states in their domains with the states in
their ranges. The inclusion
implicitly
identifies
with the subspace determined by the prepared pure
state on the ancillas. The last state space of Eq. 41 is
expressed as a tensor product (``
''), which is the state
space of the combined system
. For states of
we write
. Because
is a correctable error, it must be the case that
for some state
of the syndrome subsystem. To establish
this fact, use linearity of the maps. In general:
The
need not be normalized or orthogonal. Let
be the
subspace spanned by the
. Then
induces an
identification of
with a subspace
. This is the desired subsystem identification.
We can then see how the errors act in this identification:
 |
(43) |
This means that for all
and
,
 |
(44) |
that is, all errors in
are detectable.
Now, suppose that all errors in
are
detectable. To see that this implies correctability of
,
choose a basis for the errors so that
with
for
and
otherwise.
Define a subsystem identification by
 |
(45) |
for
. By assumption and construction,
, which implies that
is unitary (after linear
extension), and so this is a proper identification. For
,
, which implies that for states in the
code, these errors have probability
. Therefore, the identification
can be used to successfully correct
.
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Up: From Quantum Error Detection
Previous: Quantum Error Detection