Qubit code 

Root code for the Qubit Kingdom

Description

Encodes \(K\)-dimensional Hilbert space into a \(2^n\)-dimensional (i.e., \(n\)-qubit) Hilbert space. Usually denoted as \(((n,K))\) or \(((n,K,d))\), where \(d\) is the code's distance.

Protection

An \(((n,K,d))\) code corrects erasure errors on up to \(d-1\) qubits. The number of correctable errors is often called the decoding radius, and it is upper bounded by half of the code distance. As a result, qubit codes cannot tolerate adversarial errors on more than \((1-R)/4\) registers, where \(R = \log_2 K/n\) is the code rate.

Pauli-string error basis

A convenient and often considered error set is the Pauli error or Pauli string basis.

Pauli strings: 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*{(1)}\end{align} For multiple qubits, error set elements are tensor products of elements of the single-qubit error set.

The Pauli error set is a unitary and Hermitian basis for linear operators on the multi-qubit Hilbert space that is orthonormal under the Hilbert-Schmidt inner product; it is a prototypical nice error basis. The distance associated with this set is often the minimum weight of a Pauli string that implements a nontrivial logical operation in the code.

The minimum weight of a Pauli error that has a non-zero expectation value for some code basis state is called the diagonal distance [1]. Codes whose distance is greater than the diagonal distance are degenerate. Degenerate codes admit undetectable Pauli errors (i.e., errors whose projection into the codespace is nonzero) of weight less than the code distance (i.e., the projection satisfies the Knill-Laflamme conditions).

A quantum channel whose Kraus operators are Pauli strings is called a Pauli channel, and such channels are typically more tractable than general, non-Pauli channels. Relevant Pauli channels include dephasing noise and depolarizing noise (a.k.a. Werner-Holevo channel [2]), while relevant non-Pauli channels are amplitude damping, erasure (which maps all qubit states into a third state \(|e\rangle\) outside of the qubit Hilbert space), and biased erasure (in which case only the \(|1\rangle\) qubit state is mapped to \(|e\rangle\)). Noise can be correlated in space or in time, with the latter being an example of a non-Markovian phenomenon [3].

Bounds on code parameters

Bounds on code performance include the quantum Singleton bound [46], quantum Hamming bound [7], and quantum Gilbert-Varshamov bound [7]. Linear programming bounds also exist [8,9].

Quantum weight enumerator: Determining protection and bounds on code parameters can also be done using the code's Shor-Laflamme quantum weight enumerator [10] (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*{(2)}\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*{(3)}\end{align} The weight enumerator and its dual satisfy the quantum MacWilliams identity [10]; see [11; Ch. 7]. The distance \(d\) of a code is the smallest \(j=d\) at which \(A_j \neq B_j\) [12]. 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 [11]. Other types of quantum weight enumerators are the Rains shadow enumerators [8] (see also [13]). There are techniques to compute them for general codes [14]. These notions can be generalized to qudit codes and other error bases [1416].

Rate

Exact two-way assisted capacities have been obtained for the erasure and dephasing channels [17].

Gates

The normalizer of the Pauli group is the Clifford group; see Ref. [18] for generators, relations, and normal form. Computing using Clifford gates only can be efficiently simulated on a classical computer, according to the Gottesman-Knill theorem [19,20]. Universal quantum computing can be achieved using Clifford gates and a single type of non-Clifford gate, such as the \(T\) gate [21]. More generally, the Solovay-Kitaev theorem [22,23] states that any subset of gates the generates a dense subgroup of the full \(n\)-qubit gate group can be used to construct any gate to arbitrary accuracy (see [24][25; Appx. 3]). Non-Clifford gates are typically more difficult to implement than Clifford gates and so are treated as a resource. Optimizing T-gate count is \(NP\)-hard [26] and can be done using various procedures [2732], e.g., ZX calculus (a.k.a. Penrose spin calculus) [3336] or reinforcement learning [37]. Decompositions in terms of Toffoli and Hadamard gates [38] as well as cosine-sine gates also exist [39].

Clifford hierarchy: The Clifford hierarchy [4042] 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*{(4)}\end{align} where \(P\) is any Pauli matrix, and \(C_1\) is the Pauli group.

Arbitrary \(n\)-qubit circuits can be implemented fault-tolerantly in a 3D architecture using \(O(n^{3/2}\log^3 n)\) qubits, and in a 2D architecture using only \(O(n^2 \log^3 n)\) qubits [43].

Decoding

Incorporating faulty syndrome measurements can be done using the phenomenological noise model, which simulates errors during syndrome extraction by flipping some of the bits of the measured syndrome bit string. In the more involved circuit-level noise model, every component of the syndrome extraction circuit can be faulty.Hook errors are syndrome measurement circuit faults that cause more than one data-qubit error [44]. Hook errors occur at specific places in a syndrome extraction circuit and can sometimes be removed by re-ordering the gates of the circuit. If not, the use of flag qubits to detect hook errors may be necessary to yield fault-tolerant decoders.The decoder determining the most likely error given a noise channel is called the maximum probability error (MPE) decoder. For few-qubit codes (\(n\) is small), MPE decoding can be based by creating a lookup table. For infinite code families, the size of such a table scales exponentially with \(n\), so approximate decoding algorithms scaling polynomially with \(n\) have to be used.Decoders are characterized by an effective distance or circuit-level distance, the minimum number of faulty operations during syndrome measurement that is required to make an undetectable error. A code is distance-preserving if it admits a decoder whose circuit-level distance is equal to the code distance.

Fault Tolerance

There are lower bounds on the overhead of fault-tolerant QEC in terms of the capacity of the noise channel [45]. A more stringent bound applies to geometrically local QEC due to the fact that locality constrains the growth of the entanglement that is needed for protection [46].Arbitrary \(n\)-qubit circuits can be implemented fault-tolerantly in a 3D architecture using \(O(n^{3/2}\log^3 n)\) qubits, and in a 2D architecture using only \(O(n^2 \log^3 n)\) qubits [43].

Threshold

Computational threshold: 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 [4753]. Such methods require constant-space and polylogarithmic-time overhead, but concatentions using quantum Hamming codes improve this to quasi-polylogarithmic time [54]. Fault-tolerant computations with no notion of locality can be made local on a 2D or 3D geometry with minimial overhead [43].

Measurement threshold: One can derive conditions quantifying how many random single-qubit measurements can be made without destroying the logical information [55]. 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 [55; Thm. 4].

Notes

There is a relation between one-way entanglement distillation protocols and QECCs [56].See Qiskit QEC framework for realizing protocols on IBM machines.There exists a distance- and rate-dependent lower bound on the degree of entanglement of a qubit code [57; Thm. 3i].

Parents

  • Modular-qudit code — Modular-qudit quantum codes for \(q=2\) correspond to qubit codes.
  • Galois-qudit code — Galois-qudit quantum codes for \(q=2\) correspond to qubit codes.
  • Spin code — Spin codes with spin \(\ell=1/2\) correspond to qubit codes.

Children

Cousins

  • Reed-Muller (RM) code — Optimizing T gates in a qubit circuit that uses CNOT and T gates is equivalent decoding a paricular RM code [29].
  • Qubit c-q code — Qubit c-q codes are qubit codes designed to transmit classical information.
  • EA qubit code — EA qubit codes utilize additional ancillary qubits in a pre-shared entangled state, but reduce to ordinary qubit codes when said qubits are interpreted as noiseless physical qubits.
  • Five-qubit perfect code — Every \(((5,2,3))\) code is single-qubit-Clifford-equivalent to the five-qubit code [58; Corr. 10].
  • Subsystem qubit code — Subsystem qubit codes reduce to (subspace) qubit codes when there is no gauge subsystem.

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Zoo Code ID: qubits_into_qubits

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“Qubit code”, The Error Correction Zoo (V. V. Albert & P. Faist, eds.), 2023. https://errorcorrectionzoo.org/c/qubits_into_qubits
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@incollection{eczoo_qubits_into_qubits, title={Qubit code}, booktitle={The Error Correction Zoo}, year={2023}, editor={Albert, Victor V. and Faist, Philippe}, url={https://errorcorrectionzoo.org/c/qubits_into_qubits} }
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