A CSS quantum error-correcting code is, on the nose, a length-three chain complex over F2 : the commutation law HZ H⊤ X = 0 that makes the code valid is exactly the condition ∂ 2 = 0 that makes a chain complex. We take this identification literally and show that the entire working theory of a quantum code is one homological object the same engine computes, at scale, and certifies. The number of logical qubits is the first Betti number, k = dim H1 = n − rank HX − rank HZ = b1 ; the code distance is the systole, the shortest non-contractible cycle. We reproduce the published parameters of state-of-the-art codes exactly—the toric and hypergraph-product families and the IBM bivariate-bicycle codes [[72, 12, 6]], [[144, 12, 12]], [[90, 8, 10]]—cross-validated four independent ways and kernelcertified for the small cases in Cubical Agda, on CPU and GPU. The two scale certificates—the Betti count b1 and the rank-derived logical count k—are themselves kernel-proved to be a single first-homology certificate (a DescentCertificate both readings factor through), closed terminally through a fixed-point engine. We then run the code, not just measure it. (i) The Union-Find decoder is the engine's connected-components reduction, and "a logical error occurred" is the engine's coboundary decision (the residual cycle has nonzero winding); decoding the toric code at growing distance recovers the accuracy threshold near 9.5%, and the optimal (maximum-likelihood) threshold near 11% is the engine's two homology sectors competing as the domain-wall free energy of a random-bond Ising model on the Nishimori line. (ii) A code's distance scaling is its Tanner-graph spectral expansion: the second eigenvalue λ2 versus the Ramanujan bound is a computable certificate (Sipser–Spielman), exact on the topological tier where the spectral gap obeys γ d2 → 4π 2 . (iii) The full chain complex carries metachecks—redundancies among the parity checks—and we compute them: the bivariate-bicycle codes have six, the engines of single-shot error correction; the 4-dimensional toric code's homology (1, 4, 6, 4, 1), with k = b2 = 6, is the tensor of four circle complexes. (iv) The logical error-rate prefactor is the multiplicity of the systole, A = 2L for the toric code, which we compute exactly. (v) Finally the engine measures a topological phase transition: as random noise thickens, torus-wrapping "giant" cycles appear in a sharp homological-percolation transition at pc ≈ 0.5 that sharpens with system size—the same homology machinery now detecting when noise spontaneously writes a logical operator. (vi) The engine runs over any coefficients: qudit (Fp ) codes are chain complexes over Fp , and the integral homology, computed by the Smith normal form, exposes torsion—so a code's logical-qudit count can depend on the qudit dimension, an extra logical appearing exactly when p divides a torsion coefficient (reproducing the known homology of the torus, the Moore spaces, the Klein bottle, and RP2 ). We are careful to fence what is not claimed: minimum distance is NP-hard in general and we compute it only on the systolic tier; the giant-cycle transition is the random-cluster one, distinct from the maximum-likelihood decoding threshold of the random-bond Ising model. The thesis is singular and operational: a quantum code's parameters, its decoder, its quality, its higher-dimensional structure, its performance prefactor, and its phase transition are not six theories but one—homology you can run. Published by The Institute for Applied Ontological Mathematics.
A CSS quantum error-correcting code is, on the nose, a length-three chain complex over F2 : the commutation law HZ H⊤ X = 0 that makes the code valid is exactly the condition ∂ 2 = 0 that makes a chain complex. We take this identification literally and show that the entire working theory of a quantum code is one homological object the same engine computes, at scale, and certifies. The number of logical qubits is the first Betti number, k = dim H1 = n − rank HX − rank HZ = b1 ; the code distance is the systole, the shortest non-contractible cycle. We reproduce the published parameters of state-of-the-art codes exactly—the toric and hypergraph-product families and the IBM bivariate-bicycle codes [[72, 12, 6]], [[144, 12, 12]], [[90, 8, 10]]—cross-validated four independent ways and kernelcertified for the small cases in Cubical Agda, on CPU and GPU. The two scale certificates—the Betti count b1 and the rank-derived logical count k—are themselves kernel-proved to be a single first-homology certificate (a DescentCertificate both readings factor through), closed terminally through a fixed-point engine. We then run the code, not just measure it. (i) The Union-Find decoder is the engine's connected-components reduction, and "a logical error occurred" is the engine's coboundary decision (the residual cycle has nonzero winding); decoding the toric code at growing distance recovers the accuracy threshold near 9.5%, and the optimal (maximum-likelihood) threshold near 11% is the engine's two homology sectors competing as the domain-wall free energy of a random-bond Ising model on the Nishimori line. (ii) A code's distance scaling is its Tanner-graph spectral expansion: the second eigenvalue λ2 versus the Ramanujan bound is a computable certificate (Sipser–Spielman), exact on the topological tier where the spectral gap obeys γ d2 → 4π 2 . (iii) The full chain complex carries metachecks—redundancies among the parity checks—and we compute them: the bivariate-bicycle codes have six, the engines of single-shot error correction; the 4-dimensional toric code's homology (1, 4, 6, 4, 1), with k = b2 = 6, is the tensor of four circle complexes. (iv) The logical error-rate prefactor is the multiplicity of the systole, A = 2L for the toric code, which we compute exactly. (v) Finally the engine measures a topological phase transition: as random noise thickens, torus-wrapping "giant" cycles appear in a sharp homological-percolation transition at pc ≈ 0.5 that sharpens with system size—the same homology machinery now detecting when noise spontaneously writes a logical operator. (vi) The engine runs over any coefficients: qudit (Fp ) codes are chain complexes over Fp , and the integral homology, computed by the Smith normal form, exposes torsion—so a code's logical-qudit count can depend on the qudit dimension, an extra logical appearing exactly when p divides a torsion coefficient (reproducing the known homology of the torus, the Moore spaces, the Klein bottle, and RP2 ). We are careful to fence what is not claimed: minimum distance is NP-hard in general and we compute it only on the systolic tier; the giant-cycle transition is the random-cluster one, distinct from the maximum-likelihood decoding threshold of the random-bond Ising model. The thesis is singular and operational: a quantum code's parameters, its decoder, its quality, its higher-dimensional structure, its performance prefactor, and its phase transition are not six theories but one—homology you can run. Published by The Institute for Applied Ontological Mathematics.
Computing the distance of a stabilizer code is NP-hard, yet certifying the distance of a given code needs no search at all — only two one-sided certificates that meet. An upper bound is a single explicit logical operator: one vector, checked in milliseconds against the actual check matrix — it commutes with every stabilizer, it is provably outside their span, and it acts on exactly w qubits. A lower bound is a universal statement — no logical operator lives below weight w — discharged by a finite scan whose completeness is itself a theorem, not a convention: a reconstruction lemma proves that every light Pauli vector appears in the scanned list, so the scan quantifies over the whole space rather than over a table someone chose. When the two certificates touch, the distance is exact, and the receipt can be replayed by a referee who trusts neither the authors nor their software. We build this bracket calculus over the binary symplectic carrier, close it exactly on the classical menagerie — the five-qubit perfect code, Steane, Shor, the distance-three rotated surface code, and the 3 × 3 toric code — and report an instructive refutation: our own frozen reference data claimed distance at least 2 for a punctured code fragment, and the certificate layer produced an explicit weight-one logical operator. Puncturing buys a logical qubit and leaves it bare; the count and the distance are independent shadows of the same subgroup lattice. The same prover-proposes/kernel-disposes architecture certifies logical counts at bivariate-bicycle scale (k = 12 at n = 144) from change-of-basis rank certificates checked in linear time, and every number in the system wears a two-valued trust badge whose semantics is an event, not a citation: no kernel run on your instance, no badge. The results are proved in a machine-checked formal kernel. Published by The Institute for Applied Ontological Mathematics.
Random projective measurements are an effective tool to model the interlinked phenomenology of monitoring, inferring, and decoding highly entangled states such as quantum error-correcting codes. At the same time, the study of such monitored dynamics has opened a new arena for critical phenomena, renewing longstanding questions in disordered statistical mechanics, including percolation, random-bond models, and Nishimori physics. Here we investigate the robustness of stabilizer quantum error-correcting codes under a single round of independently sampled single-qubit Pauli measurements and demonstrate that their threshold behavior falls into two broad categories - geometric and homological percolation transitions, with the toric code and color code being the principal examples for each class. We establish the distinct character of these two threshold theories by analyzing the logical-support criteria of these codes and by providing numerical estimates of their respective critical exponents obtained from optimized stabilizer simulations of large-scale systems with over one million qubits. Our framework extends to non-CSS, subsystem, higher-dimensional, and Floquet stabilizer codes and allows us to determine their respective threshold phase diagrams. We exemplify how the latter provide quantitative and qualitative guidance for the computationally more demanding problems of tunable learning and maximum-likelihood decoding. As a practical application of our framework, we discuss the robustness of the gross code.
Quantum computation has shown advantages in several problems over the corresponding classical algorithms. The noisy intermediate-size\n quantum devices with dozens of qubits make it more promising in the\n past decade, as the quantum advantage was demonstrated\n experimentally. Before entering the era of scalable quantum\n computation, one has to resolve the errors in a quantum many-body\n system, which is inevitable due to the environment interaction during\n quantum control processes. The goal of quantum error correction is to\n reduce such errors and increase decoherence time. The most successful candidates of quantum error correction codes are topological codes, especially surface codes, which were discovered by\n Alexei Kitaev. The ordered phase of the 2D\n Ising model on a torus ensures that toric codes are fault-tolerant\n below a critical error probability. Other than the FT threshold,\n the topological codes feature efficient encoding and\n decoding, local measurements, but suffer from asymptotically zero\n code rate. To encode more logical qubits with finite resources, one can loosen the condition on locality and extend to a broader class of quantum\n low-density parity-check (LDPC)codes. There are many known algebraic\n constructions for such codes, but only a precious few of them have\n finite code rates and meet the fault-tolerant condition:\n the stabilizer weight is bounded and the distance scales at least\n logarithmically with the code size. In this thesis, I construct the\n higher-dimensional quantum hypergraph product (HQHP) codes, which\n generalize quantum hypergraph product (QHP) codes and toric codes in\n all dimensions. The HQHP codes projected into a single space gives\n subsystem product codes, which can then be gauge fixed to\n concatenated codes or homological product codes. Those include some\n common CSS codes, like Shor’s codes, Bacon Shor’s codes, and\n subsystem QHP codes. The HQHP codes can be mapped to the tensor\n product of chain complexes, which provides an algebraic framework to\n construct quantum LDPC codes with finite code rates, square root\n distances, FT thresholds and single-shot properties with redundant\n checks. Meanwhile, their rich connection to other codes are very\n instructive and may lead to further optimizations. Regarding the\n remained procedures towards fault-tolerant universal quantum\n computation through quantum LDPC codes, I will discuss the\n fault-tolerant condition for each code, including distance,\n stabilizer weight, decoding, fault-tolerant gates and measurement\n protocols.\n
A quantum error-correcting code's logical operators, taken modulo its stabilizers, form a finite abelian group; that group, not any single number, is the code's logical identity. We identify the group as one mathematical object across a divide usually treated as fundamental: the cokernel of an integer matrix, read off its Smith normal form. For a Gottesman–Kitaev– Preskill bosonic code the matrix is an integral symplectic Gram matrix and the cokernel is Q 2 (Z/d i Z) ; for a quantum low-density-parity-check digital code the matrix is a boundary i map and the cokernel is its first homology; the reading is the same computation, and code concatenation is the cokernel of a direct sum, so the two Smith normal forms simply concatenate. Because the cokernel is the complete invariant of the two-sided unimodular action, a code's logical group is certified by verifying a witness rather than by trusting a table: a prover supplies (U, D, V ) and a checker re-derives U AV = D in pure integer arithmetic. Every result is checked in Lean 4, and its load-bearing arithmetic is reproved in a second, toolchain-disjoint Cubical Agda kernel from the Peano axioms up. We prove that the group order alone is an incomplete invariant—(Z/2Z)4 and (Z/4Z)2 share order sixteen but differ in two-torsion—give an analog-weighted decoder whose correctable region provably exceeds the hard-decision region because the soft metric widens the distance, and expose the entire certified construction inside a live PennyLane and Strawberry Fields workflow, the software and hardware setting of a photonic fault-tolerant program built on exactly this concatenation. Published by The Institute for Applied Ontological Mathematics.
Quantum Topological Data Analysis Beyond Betti Numbers: Complexity Hardness & An Algorithm for Torsion Witness
Recent advances have revealed an interplay between quantum computing and topological data analysis (TDA). Most quantum TDA has focused on Betti numbers, which characterize the connectivity and ``holes'' of a dataset. Homology, however, contains additional information in the form of torsion: a nontrivial cycle can become trivial after being repeated finitely, revealing global constraints on how cycles combine and wrap around one another. Beyond applications in biomolecular studies, torsion appears in physical settings including homological quantum rotor codes, discrete charges, and gauge sectors. We study torsion from both classical and quantum perspectives. Given a graph G and its clique complex K=Cl(G), we first prove that, for fixed r and prime p, deciding whether Hr(K,Z) contains p-torsion is NP-hard. As a corollary, when a homological rotor code is specified by G, deciding whether the code has a finite-dimensional logical sector of a given order is NP-hard. We discuss related problems, including the Bockstein homomorphism, Smith normal form, lattice saturation, and cohomology. Second, for a finite set of primes P, we develop a quantum algorithm that serves as a one-sided torsion witness. For fixed r, it outputs WITNESS or INCONCLUSIVE, i.e. WITNESS certifies that either Hr(K,Z) or Hr−1(K,Z) contains p-torsion for some p∈P while INCONCLUSIVE makes no claim about its presence or absence. We identify a regime in which the algorithm achieves a near-quadratic quantum speedup over the corresponding classical algorithm under the same input model. Our NP-hardness result complements recent hardness results for estimating Betti numbers, adding a complexity-theoretic perspective to quantum TDA. Together, these results demonstrate that integral homology, beyond its Betti numbers, can be computationally challenging.
Homological quantum error correction uses tools of algebraic topology and homological algebra to derive Calderbank-Shor-Steane quantum error correcting codes from cellulations of topological spaces. This work is an exploration of the relevant topics, a journey from classical error correction, through homology theory, to CSS codes acting on qudit systems. Qudit codes have torsion in their logical spaces. This is interesting to study because it gives us extra logical qudits, of possibly different dimension. Apart from examples and comments on the topic, we prove an original result, the Structure Theorem for the Qudit Logical Space, an application of the Universal Coefficient Theorem from homological algebra, which gives us information about the logical space when torsion is involved, and that improves on a previous result in the literature. Furthermore, this work introduces our own abstracted and restricted version of the general notion of a cell complex, suited exactly to our needs.