Quantum low-density parity-check (QLDPC) code[1] 

Also known as Sparse quantum code.


Member of a family of \([[n,k,d]]\) modular-qudit or Galois-qudit stabilizer codes for which the number of sites participating in each stabilizer generator and the number of stabilizer generators that each site participates in are both bounded by a constant as \(n\to\infty\). A geometrically local stabilizer code is a QLDPC code where the sites involved in any syndrome bit are contained in a fixed volume that does not scale with \(n\). As opposed to general stabilizer codes, syndrome extraction of the constant-weight check operators of a QLDPC codes can be done using a constant-depth circuit.

Notable \([[n,k,d]]\) QLDPC codes are summarized in Table I, demonstrating the steady improvement in code parameters that culminated in the first asymptotically good QLDPC codes.






Kitaev toric


\(\sqrt{n\sqrt{\log n}}\)




hypergraph product

\(\sqrt{n}/\log n\)

\(\sqrt{n} \log n\)

high-dimensional expander (HDX)


\(\sqrt{n} \log^c n\)

tensor-product HDX




\(\log n\)

\(n/\log n\)

lifted-product (LP)



expander LP



quantum Tanner




Table I: Notable QLDPC codes; \(c\) is a positive integer.

Strictly speaking, the term parity check describes only bitwise qubit error syndromes. Nevertheless, qudit stabilizer codes satisfying the above criteria are also called QLDPC codes.


Detects errors on \(d-1\) sites, corrects errors on \(\left\lfloor (d-1)/2 \right\rfloor\) sites. Code distance may not be a reliable marker of code performance. QLDPC codes with generator weights bounded by some constant can correct many stochastic errors far beyond the distance, which may not scale as favorably. Together with more accurate, faster, and easier-to-parallelize measurements than those of general stabilizer codes, this property makes QLDPC codes interesting in practice.


Asymptotic scaling of \(k\) and \(d\) with \(n\) depends heavily on the code construction. Bounds generalizing the BPT bound to QLDPC codes depend on the separation profile of the code's underlying connectivity graph [2,3]. A constant relative minimum distance can be achieved only for graphs that contain expanders [2]. Conversely, a code with parameters \(k\) and \(d\) requires a graph with \(\Omega(d)\) edges of length \(\Omega(d/n^{1/D})\) [4].


Logical gates implemented via constant-depth quantum circuits of \(D\)-dimensional geometrically qubit stabilizer codes whose distance increases with \(n\) lie in the \(D\)th level of the Clifford hierarchy [5].


Belief-propagation (BP) decoder [6] is a quantum version of the classical BP decoder, but performance suffers due to degeneracy [7]. Various post-processing algorithms have been proposed (see below and also Ref. [8]).BP-OSD decoder, scaling as \(O(n^3)\), adds a post-processing step based on ordered statistics decoding (OSD) to the belief propogation (BP) decoder [9].Neural BP decoder [10] for qubit codes.Partially and fully decoupled BP decoders, which use the decoupling representation, yield improvements against depolarizing noise [11].Message-passing decoder utilizing stabilizer inactivation (MP-SI a.k.a. BP-SI) for CSS-type QLDPC qubit codes [12].Syndrome-based linear programming (SB-LP) algorithm can be applied as a post-processing step after syndrome-based min-sum (SM-MS) decoding [13].BP guided decimation (BPGD) decoder [14].Non-binary decoding algorithm for CSS-type QLDPC codes [15].2D geometrically local syndrome extraction circuits with bounded depth using order \(O(n^2)\) ancilla qubits [16].Soft (i.e., analog) syndrome iterative belief propagation for CSS-type QLDPC codes, utilizing the continuous signal obtained in the physical implementation of the stabilizer measurement (as opposed to discretizing the signal into a syndrome bit) [17].Extension of the union-find decoder for qubit QLDPC codes, as well as a related heuristic decoder [18].Sliding-window decoding [19].Closed-branch decoder [20].

Fault Tolerance

Lattice surgery techniques with ancilla qubits [21,22].Fault-tolerance with constant overhead can be performed on certain QLDPC codes [23], e.g., quantum expander codes [24].GHZ state distillation for Steane error correction [25].

Code Capacity Threshold

Bounds on code capacity thresholds using ML decoding can be obtained by mapping the effect of noise on the code to a statistical mechanical model [2628].Bounds on code capacity thresholds for various noise models exist in terms of stabilizer generator weights [29].


QLDPC codes with a constant encoding rate can reduce the overhead of fault-tolerant quantum computation to be constant [23].


Links to code tables of notable QLDPC codes [30].Reviews of QLDPC codes provided in Refs. [15,30].




  • Low-density parity-check (LDPC) code
  • Topological code — Topological codes are not generally defined using Pauli strings. However, for appropriate tesselations, the codespace is the ground-state subspace of a geometrically local Hamiltonian. In this sense, topological codes are QLDPC codes. On the other hand, chain complexes describing some QLDPC codes can be 'lifted' into higher-dimensional manifolds admitting some notion of geometric locality [31]. This opens up the possibility that some QLDPC codes, despite not being geometrically local, can in fact be associated with a geometrically local theory described by a category.
  • Dynamically-generated QECC — QLDPC codes can arise from a dynamical process [32].
  • Hamiltonian-based code — QLDPC code Hamiltonians can be simulated by two-dimensional Hamiltonians with non-commuting terms whose interactions scale with \(n\) [33].
  • Single-shot code — Qubit QLDPC codes satisfying linear confinement are single shot [34]. Any code that admits a local greedy decoder also satisfies linear confinement, and so is single shot [22].
  • Finite-geometry LDPC (FG-LDPC) code — Quantum versions of EG LDPC codes can be constructed via the CSS construction [35].
  • Quantum locally testable code (QLTC) — Stabilizer LTCs are QLDPC. More general QLTCs are not defined using Pauli strings, but the codespace is the ground-state subspace of a local Hamiltonian. In this sense, QLTCs are QLDPC codes.
  • Honeycomb Floquet code — The Floquet check operators are weight-two, and each qubit participates in one check each round.
  • Spacetime circuit code — General spacetime circuit codes can be sparsified to yield QLDPC spacetime circuit codes [36].
  • Two-block group-algebra (2BGA) codes — Given group algebra elements \(a,b\in \mathbb{F}_q[G]\) with weights \(W_a\) and \(W_b\) (i.e., number of non-zero terms in the expansion), the 2BGA code LP\((a,b)\) has stabilizer generators of uniform weight \(W_a+W_b\).
  • Generalized bicycle (GB) code — Stabilizer generators of the code GB\((a,b)\) have weights given by the sum of weights of polynomials \(a(x)\) and \(b(x)\). The GB code ansatz is convenient for designing QLDPC codes and several extensions exist [37].
  • Two-block quantum code — When matrices \(A\) and \(B\) have row and column weights bounded by \(W\), a two-block quantum code is a quantum LDPC code with stabilizer generators bounded by \(2W\).


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“Quantum low-density parity-check (QLDPC) code”, The Error Correction Zoo (V. V. Albert & P. Faist, eds.), 2022. https://errorcorrectionzoo.org/c/qldpc
@incollection{eczoo_qldpc, title={Quantum low-density parity-check (QLDPC) code}, booktitle={The Error Correction Zoo}, year={2022}, editor={Albert, Victor V. and Faist, Philippe}, url={https://errorcorrectionzoo.org/c/qldpc} }
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