# Glossary of concepts

- Construction A view in context →
Construction \(A\) converts a linear binary code into a sphere packing. Each binary codeword \(c\) of the code is mapped to an infinite set of points \(x\) such that \(x = c\) modulo two. If the underlying binary code is linear, then the resulting set of points forms a lattice.

- Cyclic-to-polynomial correspondence view in context →
Cyclic linear \(q\)-ary codes and their properties can be naturally formulated using the theory of polynomials. Codewords \(c_1 c_2 \cdots c_n\) of a cyclic \(q\)-ary code can be thought of as coefficients in a polynomial \(c_1+c_2 x+\cdots+c_n x^{n-1}\) in the set of polynomials with \(q\)-ary coefficients, \(\mathbb{F}_q[x]\) with \(\mathbb{F}_q=GF(q)\). Polynomials corresponding to codewords of a linear cyclic code form an ideal (i.e., are closed under multiplication and addition) in the ring \(\mathbb{F}_q[x]/(x^n-1)\) (i.e., the set of equivalence classes of polynomials congruent modulo \(x^n-1\)). Multiplication of a codeword polynomial \(c(x)\) by \(x\) in such a ring corresponds to a cyclic shift of the corresponding codeword string.

- Weight enumerator and four fundamental parameters view in context →
Determining protection and bounds on code parameters can also be done using the code's weight enumerator (cf. quantum weight enumerators), \begin{align} \begin{split} A(x,y)&=\sum_{j=0}^{n}A_{j}x^{n-j}y^{j}\\ A_{j}&=\text{number of wt-}j\text{ codewords}~. \end{split} \tag*{(1)}\end{align} The weight enumerator and it's Fourier transform the dual weight enumerator satisfy the MacWilliams identity [1,2]; see [3; Ch. 5].

The distance of the code is the value of the first nonzero coefficient \(A_j\), while the dual distance is the first nonzero coefficient of the dual weight enumerator. The number of the code is the number of nonzero \(A_j\)'s, corresponding to the number of distinct nonzero distances between codewords. The external distance is the number of nonzero coefficients of the dual weight enumerator. The distance, dual distance, number and external distance make up the four fundamental parameters of a code [4][3; Ch. 5].

Other types of weight enumerators includes the Hamming weight enumerator, Lee weight enumerator, joint weight enumerator, split weight enumerator, and biweight enumerator [3].

- Lifting view in context →
Given the incidence matrix \(A\) of a protograph, each non-zero entry is replaced by a sum of \(\ell\)-dimensional permutation matrices while each zero entry is replaced by the \(\ell\)-dimensional zero matrix. The resulting matrix is called a lift of \(A\). The permutation matrices can be chosen randomly or deterministically, with a deterministic lift also called a permutation voltage assignment in the theory of theory of voltage graphs [5,6].

The matrices can come from a group \(G\) or its group algebra \(\mathbb{F}_q G\), in which case the lift is often called a \(G\)-lift. In this case, matrix entries of a \(\mathbb{F}_q\)-valued matrix \(A\) are substitited with matrices forming the regular representation of \(\mathbb{F}_q G\) according to some rule.

For example, the lift of a binary two-dimensional incidence matrix using two-dimensional permutation matrices associated with the group \(\mathbb{Z}_2\) is as follows: \begin{align} \begin{pmatrix}1 & 1\\ 0 & 1 \end{pmatrix}\to\left(\begin{smallmatrix}0 & 1 & 0 & 1\\ 1 & 0 & 1 & 0\\ 0 & 0 & 1 & 0\\ 0 & 0 & 0 & 1 \end{smallmatrix}\right)~. \tag*{(2)}\end{align} Here, the two non-zero entries in the top row are replaced by the exchange permutation while the bottom non-zero entry is replaced by the trivial permutation.

- Antipodal mapping view in context →
The antipodal mapping, also known as a Euclidean-space image or \(Y_2\) construction), is a component-wise mapping from binary space into Euclidean space. Each coodinate of a binary string is mapped into a sign, \(0\to +1\) and \(1 \to -1\) [7; Example 1.2.1].

- Group-based error basis view in context →
There are two types of \(X\)-type operators, corresponding to left and right group multiplication. These act on computational basis states \(|h\rangle\) as \begin{align} \overrightarrow{X}_{g}|h\rangle&=|gh\rangle\tag*{(3)}\\ \overleftarrow{X}_{g}|h\rangle&=|hg^{-1}\rangle \tag*{(4)}\end{align} for any group elements \(h,g\). The \(Z\)-type operators can be thought of as matrix-product operators (MPOs) [8] whose virtual dimension is the dimension \(d_{\lambda}\) of their corresponding irrep. The are diagonal in the group-valued basis, yielding the \(d_{\lambda}\)-dimensional irrep matrix \(Z_{\lambda}(g)\) evaluated at the given group element, \begin{align} \hat{Z}_{\lambda}\otimes|g\rangle=Z_{\lambda}(g)\otimes|g\rangle~. \tag*{(5)}\end{align} Each matrix element of this irrep matrix is a generally non-unitary operator on the group-valued qudit. For one-dimensional irreps, the matrix reduces to a single unitary \(Z\)-type operator, and the direct-product symbol is no longer needed.

- Rotor generalized Pauli strings view in context →
For a single rotor, its elements are products of exponentials of the rotor's angular position (\(\hat\phi\)) and angular momentum (\(\hat L\)) operators, acting on the rotor's angular position states \(|\phi\rangle\) for \(\phi\in U(1)\) as \begin{align} e^{-i\varphi\hat{L}}\left|\phi\right\rangle =\left|\phi+\varphi\right\rangle \,\,\text{ and }\,\,e^{i\ell\hat{\phi}}\left|\phi\right\rangle =e^{i\ell\phi}\left|\phi\right\rangle ~, \tag*{(6)}\end{align} where \(\varphi\in U(1)\) and \(\ell\in\mathbb{Z}\). For multiple rotors, error set elements are tensor products of elements of the single-rotor error set, characterized by vectors of angle and integer coefficients multiplying vectors of angular momentum \(\hat{\boldsymbol{L}}\) and angular position \(\hat{\boldsymbol{\phi}}\) operators.

- Displacement operators view in context →
For a single mode, its elements are products of exponentials of the mode's position and momentum operators, acting on the mode's position states \(|y\rangle\) for \(y\in\mathbb{R}\) as \begin{align} e^{-iq\hat{p}}\left|y\right\rangle =\left|y+q\right\rangle \,\,\text{ and }\,\,e^{iq\hat{x}}\left|y\right\rangle =e^{iq y}\left|y\right\rangle ~, \tag*{(7)}\end{align} where \(q\in\mathbb{R}\). The former is also called a translation, while the latter is called a modulation in signal processing. For multiple modes, error set elements are tensor products of elements of the single-oscillator error set, characterized by the vector of coefficients \(\xi\in\mathbb{R}^{2n}\).

- Eastin-Knill theorem view in context →
Transversal gatesare logical gates on block codes that can be realized as tensor products of unitary operations acting on subsets of subsystems whose size is independent of \(n\). For subsets of size one, gates are sometimes called strongly transversal the single-subsystem unitaries are identical and weakly transversal otherwise. A universal gate set for a finite-dimensional block quantum code cannot be transversal for any code that detects single-block errors due to the Eastin-Knill theorem [9].

- Nice error basis view in context →
A nice error basis [10–12] for an \(q\)-dimensional vector space is a set \(\{E_g~,~g\in G\}\) of unitary operators, where \(G\) is a (not necessarily Abelian) group of order \(q^2\), and where \begin{align} \text{tr}(E_{g})&=q\delta^{G}_{g,1}\tag*{(8)}\\ E_{g}E_{h}&=\omega_{g,h}E_{gh} \tag*{(9)}\end{align} for all group elements \(g,h\). Above, \(\delta^{G}_{g,1}\) is the group Kronecker-delta function. A basis is called very nice if \(\omega\) is a root of unity. This definition can naturally be extended to continuous groups.

- Pseudo-threshold (a.k.a. break-even point) view in context →
The ultimate goal of error correction is to make sure that the logical error rate is greater than the underlying physical error rate. For a noise model parameterized by a single physical error rate \(p\), the pseudo-threshold or break-even point is the smallest \(p\) at which the logical error rate after error correction is equal to \(p\).

- Knill-Laflamme conditions view in context →
The Knill-Laflamme error-correction conditions [13–15][16; Thm. 10.1] are necessary and sufficient conditions for a code to successfully correct a set of errors in a finite-dimensional Hilbert space. A code (defined by a partial isometry \(U\)) with code space projector \(\Pi = U U^\dagger\) can correct a set of errors \(\{ E_j \}\) if and only if \begin{align} \Pi E_i^\dagger E_j \Pi = c_{ij}\, \Pi\qquad\text{for all \(i,j\),} \tag*{(10)}\end{align} where the QEC matrix elements \(c_{ij}\) are arbitrary complex numbers.

- Degeneracy view in context →
A code is degenerate with respect to a noise model if different errors map code states to the same error subspace. For a linearly independent error set \(\cal{E}\), degeneracy is equivalent to \(\text{rank}(c_{ij}) < |\cal{E}|\) [17].

- Complementary channel view in context →
A complementary channel \(\mathcal{E}^C\) is obtained from a channel \(\mathcal{E}\) that acts on a system by interpreting the channel as coming from a unitary operation acting on a larger system-environment tensor-product space (i.e., performing an isometric extension) and then tracing out the system factor (instead of the second environmental factor) [18; Sec. 5.2.2]. A noise channel \({\cal E}(\cdot)=\sum_{j}E_{j}(\cdot)E_{j}^{\dagger}\) admits a complementary channel of the form \begin{align} {\cal E}^{C}(\cdot)=\sum_{j,k}\text{Tr}\{E_{j}(\cdot)E_{k}^{\dagger}\}|j\rangle\langle k|~. \tag*{(11)}\end{align}

- Pauli-to-polynomial mapping view in context →
A single-qudit Pauli operator can be specified by the lattice coordinate of the site and the symplectic vector representation of the Pauli operator within the site. In an extension of the sympletic representation, each lattice coordinate can be represented by a Laurent monomial of \(D\) formal variables. For example, when \(D=2\) and \(m=1\), the product of an \(X\) acting on the qubit at lattice coordinate \((-1,2)\) and a \(Z\) acting on the qubit at \((1,0)\) can be represented by the vector \( (x^{-1} y^2 | x) \). The multiplicative group of finitely supported Pauli operators modulo phase factors on the lattice of dimension \(D\) with \(m\) prime-dimensional qubits per site is isomorphic to the additive group of Laurent polynomial column vectors of length \(2m\) in \(D\) formal variables (see Ref. [19] and Sec. IV of Ref. [20]).

For periodic boundary conditions, this mapping can be thought of as a quantum extension of the cyclic-to-polynomial correspondence. For open boundary conditions, this mapping extends the mapping used in quantum convolutional codes to multiple spatial dimensions.

- BPT bound view in context →
Lattice qubit codes are limited by the Bravyi-Poulin-Terhal (BPT) bound [21] (see also [22–24]), which states that \(d \leq O(n^{1-1/D})\) and \(k d^{2/D-1} = O(n)\) for \(D\)-dimensional lattice geometries. The Bravyi-Terhal (BT) bound states that \(d = O(L^{D-1})\) [22]. Codes on a \(D\)-dimensional homogeneous Riemannian manifold with diameter \(L\) satisfy \(k = O(L^{D-2})\) [25].

- Bravyi-Koenig bound view in context →
Logical gates implemented via constant-depth quantum circuits on a \(D\)-dimensional lattice stabilizer code whose distance increases at least logarithmically with \(n\) lie in the \(D\)th level of the Clifford hierarchy [26]. A refinement can be made that expresses the bound in terms of higher-group symmetries of the topological phases underlying the codes [27; Sec. 5.4.2]. Conversely, the distance of a code on an \(L^{D}\) lattice is upper bounded by order \(O(L^{D+1-\nu})\) if the code implements an \(\nu\)th-level Clifford hierarchy gate [28]. The code capacity threshold of such a code family is upper bounded by \(1/\nu\) [28].

- Subsystem BT bound view in context →
The subsystem BT bound is an upper bound of \(d = O(L^{D-1})\) on the distance [22] of lattice subsystem stabilizer codes arranged in a \(D\)-dimensional lattice of length \(L\) with \(n=L^D\). In particular, \(D=2\)-dimensional subsystem codes satisfy \(kd = O(n)\) [23]. More generally, there is a tradeoff theorem [29] stating that, for any logical operator, there is an equivalent logical operator with weight \(\tilde{d}\) such that \(\tilde{d}d^{1/(D-1)}=O(L^{D})\).

- Subsystem PYBK bound view in context →
The Bravyi-Koenig bound can be extended to subsystem codes by Pastawski and Yoshida. Namely, logical gates implemented via constant-depth quantum circuits on a \(D\)-dimensional lattice subsystem code whose distance increases at least logarithmically with \(n\) lie in the \(D\)th level of the Clifford hierarchy [28].

- Dicke states view in context →
For \(n\)-qubit block codes, an often used basis for the \(n+1\)-dimensional PI subspace consists of the Dicke states \(|D^n_w\rangle\) -- normalized PI states of \(w\) excitations, i.e., a normalized sum over all binary-string basis elements with \(w\) ones and \(n - w\) zeroes. For example, the single-excitation Dicke state on three qubits is \begin{align} |D_{1}^{3}\rangle=\frac{1}{\sqrt{3}}\left(|001\rangle+|010\rangle+|100\rangle\right)~. \tag*{(12)}\end{align} The \(n+1\)-dimensional PI space can be thought of as a standalone spin-\(n/2\) quantum system, yielding a way to convert between permutation-invatiant qubit codes and \(SU(2)\) spin codes. A single-spin code for the \(SU(2)\) group correcting spherical tensors can be mapped into a PI qubit code with an analogous distance [30][31; Thm. 1].

- Pauli strings view in context →
For a single qubit, this set consists of products of powers of the Pauli matrices \begin{align} X=\begin{pmatrix}0 & 1\\ 1 & 0 \end{pmatrix}\,\,\text{ and }\,\,Z=\begin{pmatrix}1 & 0\\ 0 & -1 \end{pmatrix}~. \tag*{(13)}\end{align} For multiple qubits, error set elements are tensor products of elements of the single-qubit error set.

- Quantum weight enumerator view in context →
Determining protection and bounds on code parameters can also be done using the code's Shor-Laflamme quantum weight enumerator [32] (cf. weight enumerators) \begin{align} \begin{split} A(x)&=\sum_{j=0}^{n}A_{j}x^{j}\\ A_{j}&=\frac{1}{K^{2}}\sum_{\text{wt-}j\text{ Paulis }P}\left|\text{tr}(P\Pi)\right|^{2}~, \end{split} \tag*{(14)}\end{align} where \(\Pi\) is the code projection, and where the sum is over the Pauli group modulo the subgroup of phases (hence, the dagger below is necessary in case the coset representative is not Hermitian). The dual quantum weight enumerator is \begin{align} \begin{split} B(x)&=\sum_{j=0}^{n}B_{j}x^{j}\\ B_{j}&=\frac{1}{K}\sum_{\text{wt-}j\text{ Paulis }P}\text{tr}(P\Pi P^{\dagger}\Pi)~. \end{split} \tag*{(15)}\end{align} The weight enumerator and its dual satisfy the quantum MacWilliams identity [32]; see [17; Ch. 7]. The distance \(d\) of a code is the smallest \(j=d\) at which \(A_j \neq B_j\) [33]. Such a code is called pure if \(A_j = B_j = 0\) for all \(j < d\); otherwise, the code is called impure. Degeneracy is sufficient but not necessary for impurity [17]. Other types of quantum weight enumerators are the Rains shadow enumerators [34] (see also [35]). There are techniques to compute them for general codes [36]. These notions can be generalized to qudit codes and other error bases [36–38].

- Clifford hierarchy view in context →
The Clifford hierarchy [39–41] is a tower of gate sets which includes Pauli and Clifford gates at its first two levels, and non-Clifford gates at higher levels. The \(k\)th level is defined recursively by \begin{align} C_k = \{ U | U P U^{\dagger} \in C_{k-1} \}~, \tag*{(16)}\end{align} where \(P\) is any Pauli matrix, and \(C_1\) is the Pauli group.

- Computational threshold view in context →
A fault-tolerant computational threshold is the maximum noise rate in a noise model below which any logical computation of size \(M\) can be executed on a physical-qubit architecture to arbitrary accuracy and with an overhead of order \(O(M\text{polylog}M)\). The first methods to achieve a computational threshold use concatenated stabilizer codes [42–48]. Such methods require constant-space and polylogarithmic-time overhead, but concatentions using quantum Hamming codes improve this to quasi-polylogarithmic time [49]. Fault-tolerant computations with no notion of locality can be made local on a 2D or 3D geometry with minimial overhead [50].

- Measurement threshold view in context →
One can derive conditions quantifying how many random single-qubit measurements can be made without destroying the logical information [51]. The measurement threshold is the maximum total probability that a single qubit is measured in a random \(X\), \(Y\), or \(Z\) basis at which the logical information is still recoverable. The measurement threshold is at least as large as the erasure threshold [51; Thm. 4].

- Qubit CSS-to-homology correspondence view in context →
CSS codes and their properties can be formulated in terms of homology theory, yielding a powerful correspondence between codes and chain complexes, the primary homological structures. There exists a many-to-one mapping from size three chain complexes to CSS codes [52–55] that allows one to extract code properties from topological features of the complexes. Codes constructed in this manner are sometimes called homological CSS codes, but they are equivalent to CSS codes. This mapping of codes to manifolds allows the application of structures from topology to error correction, yielding various QLDPC codes with favorable properties.

- Steane enlargement view in context →
An \([[n,2k-n,d]]\) CSS code can be converted to a \([[n,k+k^{\prime}−n,\min(d,\left\lceil 3d^{\prime}/2\right\rceil )]]\) code for particular \(k^{\prime}\) and \(d^{\prime}\) via the Steane enlargement construction [56].

- Binary symplectic representation view in context →
In the binary symplectic representation, the single-qubit identity, \(X\), \(Y\), or \(Z\) Pauli matrices represented using two bits as \((0|0)\), \((1|0)\), \((1|1)\), and \((0|1)\), respectively. In other words, the single-qubit Pauli string \(X^a Z^b\) is converted to the vector \(a|b\). The multi-qubit version follows naturally.

- \(GF(4)\) representation view in context →
An \(n\)-qubit Pauli stabilizer can be represented as a length-\(n\) quaternary vector using the one-to-one correspondence between the four Pauli matrices \(\{I,X,Y,Z\}\) and the four elements \(\{0,1,\alpha^2,\alpha\}\) of the quaternary field \(GF(4)\).

- Cleaning lemma view in context →
If all logical operators act trivially on some subset of qubits in a stabilizer code, then any logical Pauli operator can be represented on the complementary qubit subset via a stabilizer. More technically, given any subset \(M\) of qubits that is correctable (under erasure), any logical Pauli operator \(P\) can be cleaned off of \(M\) using a stabilizer \(S\) such that \(PS\) is supported on \(M^{\perp}\). More generally, for any \(M\), we have \(g(M)+g(M^{\perp}) = 2k\), where \(g(M)\) is the number of logical-\(X\) and logical-\(Z\) Pauli operators supported fully on \(M\) (up to stabilizers). The Cleaning Lemma was originally proven [22], where an analogous result is states for subsystem codes; see also Ref. [57].

- Modular-qudit Pauli strings view in context →
For a single qudit, this set consists of products of powers of the qudit Pauli matrices \(X\) and \(Z\), which act on computational basis states \(|k\rangle\) for \(k\in\mathbb{Z}_q\) as \begin{align} X\left|k\right\rangle =\left|k+1\right\rangle \,\,\text{ and }\,\,Z\left|k\right\rangle =e^{i\frac{2\pi}{q}k}\left|k\right\rangle ~, \tag*{(17)}\end{align} with addition performed modulo \(q\). For multiple qudits, error set elements are tensor products of elements of the single-qudit error set. Modular-qudit Pauli matrices [58,59] are also known as Weyl operators [60], Sylvester-t'Hooft generators [61,62], or clock and shift matrices [63]; they are special cases of Manin's quantum plane [64]

- Qudit Clifford hierarchy view in context →
The modular-qudit Clifford hierarchy [28,39,40,65] is a tower of gate sets which includes modular-qudit Pauli and modular-qudit Clifford gates at its first two levels, and non-Clifford qudit gates at higher levels. The \(k\)th level is defined recursively by \begin{align} C_k = \{ U | U P U^{\dagger} \in C_{k-1} \}~, \tag*{(18)}\end{align} where \(P\) is any modular-qudit Pauli matrix, and \(C_1\) is the modular-qudit Pauli group.

- Code switching, code deformation, or stabilizer update rule view in context →
Code switching is a map between stabilizer codes that is done using a stabilizer group \(\mathsf{F}\) of the \(n\)-qudit Pauli group, \begin{align} \mathsf{S}\to\mathsf{N}_{\left\langle \mathsf{S},\mathsf{F}\right\rangle }\left(\mathsf{F}\right)~, \tag*{(19)}\end{align} where \(\mathsf{Z}\) denotes taking the center of a group (e.g., see [16,51] for proofs). Code switching may not preserve the logical information and instead implement logical measurements; conditions on \(\mathsf{S}\) and \(\mathsf{F}\) such that qubit stabilizer code switching preserves logical information are derived in [66; Prop. II.1]. Clifford operations and Pauli measurements can be expressed as sequences of code switching [67]. In the context of stabilizer codes realizing Abelian topological phases, code switching implements anyon condensation of any anyons represented by operators in the group \(\mathsf{F}\).

- Symplectic doubling view in context →
Any \([[n,k,r,d]]_{\mathbb{Z}_q}\) subsystem stabilizer code can be mapped onto a \([[2n,2k,2r,\geq d]]_{\mathbb{Z}_q}\) subsystem CSS code, with the mapping preserving geometric locality of a code up to a constant factor [68] (see also [69][70; Thm. 1]). In the symplectic representation, the gauge-group generator matrix of the former is mapped into that of latter as follows, \begin{align} \begin{pmatrix}G_{X} & G_{Z}\end{pmatrix} \to \begin{pmatrix} 0 & 0 & G_{Z} & -G_{X}\\ G_{X} & G_{Z} & 0 & 0 \end{pmatrix}~, \tag*{(20)}\end{align} where the first two columns of the latter matrix correspond to the \(X\)-type part of the gauge-group generator matrix of the output subsystem CSS code. In the case of a stabilizer code, the stabilizer generator matrix is mapped instead (see [70; Thm. 1] for the case of qubit stabilizer codes). For geometrically local 2D subsystem codes, this mapping yields a twisted double cover of the underlying qudit geometry [71].

- Gauge fixing view in context →
Gauge fixing is a map between subsystem codes that is done using an Abelian subgroup \(\mathsf{F}\subseteq\mathsf{G}\), \begin{align} \begin{split} \mathsf{S}&\to\left\langle \mathsf{S},\mathsf{F}\right\rangle \\ \mathsf{G}&\to\mathsf{N}_{\mathsf{G}}\left(\mathsf{F}\right)~, \end{split} \tag*{(21)}\end{align} where \(\mathsf{N}_{\mathsf{G}}\left(\mathsf{F}\right)\) is the normalizer of the stabilizer group within \(\mathsf{G}\).

- Gauging out view in context →
Gauging out is a map between subsystem codes that is done using a subgroup \(\mathsf{F}\subseteq\mathsf{P}_n\), \begin{align} \begin{split} \mathsf{S}&\to\mathsf{Z}\left(\left\langle \mathsf{G},\mathsf{F}\right\rangle \right)\\ \mathsf{G}&\to\left\langle \mathsf{G},\mathsf{F}\right\rangle ~. \end{split} \tag*{(22)}\end{align} The stabilizer group of the output subsystem code is a subgroup of that of the input code, \(\mathsf{Z}\left(\left\langle \mathsf{G},\mathsf{F}\right\rangle \right)\subseteq\mathsf{Z}\left(\mathsf{G}\right)\). When \(\mathsf{F}\) is a subgroup of the logical Pauli group, this is also called gauging. If \(\mathsf{F}\) is itself a Pauli group of \(m\) logical qubits of the original subsystem code, then gauging those qubits is equivalent to treating them as gauge qubits.

- Galois-qudit Pauli strings view in context →
For a single Galois qudit, this set consists of products of \(X\)-type and \(Z\)-type operators labeled by elements \(\beta \in GF(q)\), which act on computational basis states \(|\gamma\rangle\) for \(\gamma\in GF(q)\) as \begin{align} X_{\beta}\left|\gamma\right\rangle =\left|\gamma+\beta\right\rangle \,\,\text{ and }\,\,Z_{\beta}\left|\gamma\right\rangle =e^{i\frac{2\pi}{p}\text{tr}(\beta\gamma)}\left|\gamma\right\rangle~, \tag*{(23)}\end{align} where the trace maps elements of the field to elements of \(\mathbb{Z}_p\) as \begin{align} \text{tr}(\gamma)=\sum_{k=0}^{m-1}\gamma^{p^{k}}~. \tag*{(24)}\end{align} For multiple Galois qudits, error set elements are tensor products of elements of the single-qudit error set.

- Galois symplectic representation view in context →
The single Galois-qudit Pauli string \(X_{a} Z_{b}\) for \(a,b\in GF(q)\) is converted to the vector \(a|b\). The multi Galois-qudit version follows naturally.

- \(GF(q^2)\) representation view in context →
An \(n\)-qubit Galois-qudit Pauli stabilizer can be represented as a length-\(n\) vector over \(GF(q^2)\) using the one-to-one correspondence between the \(q^2\) Galois-qudit Pauli matrices and elements of \(GF(q^2)\).

- Weight reduction view in context →
A related procedure called weight reduction [72] takes in a CSS stabilizer code and outputs another CSS code that admits a set of stabilizer generators whose weight is independent of the number of qubits \(n\).

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