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arXiv:2609.14110

Torsion detection in clique complexes is conditionally $QMA_1$-hard

Adam Wesołowski

quant-phcs.CCSubmitted Sep 12, 2026• Announced Sep 15, 2026• 0 citations
v1 · Sep 12, 2026v2 · Sep 22, 2026
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Abstract

Quantum algorithms for topological data analysis compute Betti numbers, the ranks of the homology groups of a simplicial complex, which can be read off from the kernel of a combinatorial Laplacian. Deciding whether a Betti number of a clique complex is nonzero is $QMA_1$-hard, and remains so under a spectral gap promise on vertex-weighted graphs. Integral homology, however, contains information inaccessible to the Laplacian spectrum. A new part that appears in integral homology is torsion: cycles that become boundaries only after being traversed several times, as in a projective plane or a Klein bottle. We ask how hard it is to detect torsion, and we answer with a simple reduction. We attach to an arbitrary clique complex a fixed $31$-vertex triangulation of the projective plane. The $k$th mod-$2$ Betti number of the input then reappears as $2$-torsion two degrees up, while all rational homology disappears and every combinatorial Laplacian acquires a constant spectral gap. We conclude that detecting torsion in clique complexes of unweighted graphs is $NP$-hard, even under a constant gap promise, and that it is $QMA_1$-hard if mod-$2$ clique homology is.

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Quantum Topological Data Analysis Beyond Betti Numbers: Complexity Hardness $\&$ An Algorithm for Torsion Witness

Nhat A. Nghiem, Dominic W. Berry, Trung V. Phan

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 $K = \mathrm{Cl}(G)$, we first prove that, for fixed $r$ and prime $p$, deciding whether $H_r(K,\mathbb{Z})$ 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 $H_r(K,\mathbb{Z})$ or $H_{r-1}(K,\mathbb{Z})$ contains $p$-torsion for some $p\in P$ 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.

quant-pharXiv:2609.28112•Sep 24, 2026•0 citations

Gapped Clique Homology on Weighted Graphs Is \({\text{QMA}_1}\)-Hard and Contained in QMA

Robbie King, Tamara Kohler

Abstract. We study the complexity of a classic problem in computational topology, the homology problem: given a description of some space [Formula: see text] and an integer [Formula: see text], decide if [Formula: see text] contains a [Formula: see text]-dimensional hole. The setting and statement of the homology problem are completely classical, yet we find that the complexity is characterized by quantum complexity classes. Our result can be seen as an aspect of a connection between homology and supersymmetric quantum mechanics established by Witten (1982). We consider clique complexes, motivated by the practical application of topological data analysis (TDA). The clique complex of a graph is the simplicial complex formed by declaring every [Formula: see text]-clique in the graph to be a [Formula: see text]-simplex. Our main result is that deciding whether the clique complex of a weighted graph has a hole or not, given a suitable promise on the gap, is [Formula: see text]-hard and contained in QMA. Our main innovation is a technique to lower bound the eigenvalues of the combinatorial Laplacian operator. For this, we invoke a tool from algebraic topology known as spectral sequences. In particular, we exploit a connection between spectral sequences and Hodge theory outlined by Forman (1994). Spectral sequences will play a role analogous to perturbation theory for combinatorial Laplacians. In addition, we develop the simplicial surgery technique used in prior work by Crichigno and Kohler (2022). Our result provides some suggestion that the quantum TDA algorithm due to Lloyd, Garnerone, and Zanardi (2016) cannot be dequantized, although proving this would require studying the complexity of a different problem related to the combinatorial Laplacian of clique complexes.

SIAM Journal on Computing•Jan 2, 2026•1 citation

Quantum Log-Determinant Methods for Torsion-Sensitive Topological Data Analysis

Dimitrios Thanos, Caesnan Leditto, Adam Wesolowski +2 more

Betti numbers are central to topological data analysis but fail to capture torsion in integral homology. Torsion can distinguish topological structures with identical Betti numbers, and examples from classical topological data analysis show that it can affect the topology inferred from data. Related torsion-sensitive quantities are also known to have practical applications in graph-based machine learning, including biomedical applications. We investigate how quantum spectral methods can access this additional information. Log pseudodeterminants, obtained by summing the logarithms of the nonzero boundary-Laplacian eigenvalues, summarize spectral information about a simplicial complex. Under explicit topological assumptions, an alternating combination of these quantities gives the size of a higher critical group, the higher-dimensional analogue of a graph sandpile group. With stronger certification, a related construction recovers the size of the torsion subgroup in homology itself. This is, to our knowledge, the first provably correct quantum estimator of integral-homology torsion order. We give a new quantum algorithm for estimating these quantities, with explicit dependence on how the input is queried, the required accuracy, and the spectral gaps. Exact spectra for balanced multipartite clique complexes provide favorable gaps, and a related construction gives an explicit torsion-bearing benchmark. With compact query access, the algorithm need not construct the exponentially large boundary matrices explicitly. For a restricted torsion-bearing family, a tailored amplitude-estimation routine uses quadratically fewer queries than any randomized classical algorithm given comparable access when estimating the log pseudodeterminant. Estimating the full, unnormalized quantity to fixed additive error still costs in proportion to the candidate-space dimension $D$.

quant-pharXiv:2609.40216•Oct 1, 2026•0 citations

Gapped Clique Homology on weighted graphs is $\text{QMA}_1$-hard and contained in $\text{QMA}$

Robbie King, Tamara Kohler

We study the complexity of a classic problem in computational topology, the homology problem: given a description of some space $X$ and an integer $k$, decide if $X$ contains a $k$-dimensional hole. The setting and statement of the homology problem are completely classical, yet we find that the complexity is characterized by quantum complexity classes. Our result can be seen as an aspect of a connection between homology and supersymmetric quantum mechanics. We consider clique complexes, motivated by the practical application of topological data analysis (TDA). The clique complex of a graph is the simplicial complex formed by declaring every $k+1$-clique in the graph to be a $k$-simplex. Our main result is that deciding whether the clique complex of a weighted graph has a hole or not, given a suitable promise on the gap, is $\text{QMA}_1$-hard and contained in $\text{QMA}$. Our main innovation is a technique to lower bound the eigenvalues of the combinatorial Laplacian operator. For this, we invoke a tool from algebraic topology known as \emph{spectral sequences}. In particular, we exploit a connection between spectral sequences and Hodge theory. Spectral sequences will play a role analogous to perturbation theory for combinatorial Laplacians. In addition, we develop the simplicial surgery technique used in prior work. Our result provides some suggestion that the quantum TDA algorithm \emph{cannot} be dequantized. More broadly, we hope that our results will open up new possibilities for quantum advantage in topological data analysis.

arXiv:2311.17234•Nov 28, 2023•0 citations

Unweighted Gapped Clique Homology is $\mathsf{QMA}_1$-complete

Ryu Hayakawa

Deciding whether the clique complex of a given graph has nontrivial homology in a given dimension, under vertex-product weighting and an inverse-polynomial spectral gap promise on the combinatorial Hodge Laplacian, is known to be $\mathsf{QMA}_1$-hard and contained in $\mathsf{QMA}$ by King and Kohler (FOCS 2024). The vertex weights are essential in the known proof, where they provide the scale separation needed for the spectral gap analysis. We prove that, when every vertex has weight one, the problem remains $\mathsf{QMA}_1^{g_2}$-hard and is contained in $\mathsf{QMA}_1^{g_2}$, where $\mathsf{QMA}_1^{g_2}$ is $\mathsf{QMA}_1$ with the universal gate set $g_2=\{\mathsf{X},\mathsf{CX},\mathsf{CCX},H\otimes H\}$. The construction replaces weight by expansion: each vertex of the weighted complex is blown up into a clique whose size encodes its weight. The block sizes are chosen so that symmetric averages reproduce the weighted Hodge metric. The symmetric sector therefore carries the weighted Laplacian up to a common scalar factor, while a local averaging argument gives a uniform lower bound on the orthogonal complement to the symmetric sector. Hence the weighted gap analysis transfers to an unweighted clique complex without introducing either additional low-energy states or spurious homology. Containment in $\mathsf{QMA}_1^{g_2}$ follows from Rudolph's exact linear combination of unitaries simulation of sparse integer clique Laplacians. The result shows that the gap promise, rather than vertex weighting, is the source of the complexity of gapped clique homology.

quant-pharXiv:2608.02726•Aug 5, 2026•0 citations

Average-case hardness of Betti number estimation

Sergii Strelchuk, Sathyawageeswar Subramanian, Adam Wesołowski

We establish the average-case hardness of Betti number estimation on random clique complexes via a reduction from the planted clique problem. We further show that our reduction implies a series of hardness results for many problems in both classical and quantum Topological Data Analysis (qTDA). Under the classical planted clique conjecture, no randomized polynomial-time Betti number estimator achieves additive error below $\tfrac12$ with constant advantage. Under a new quantum planted clique conjecture that we introduce, the same conclusion holds for quantum polynomial-time algorithms. We also obtain related conditional hardness results for homology vanishing, additive approximations with larger error tolerances, preparation of simplex and harmonic states, cycle recovery, and counting eigenvalues at low energy. Our reduction clarifies the structural requirements for quantum advantage in TDA and provides a new lens to investigate the classical and quantum complexity of related problems.

quant-pharXiv:2609.12777•Sep 14, 2026•0 citations
Torsion detection in clique complexes is conditionally QMA1QMA_1QMA1​-hard
Quantum algorithms for topological data analysis compute Betti numbers, the ranks of the homology groups of a simplicial complex, which can be read off from the kernel of a combinatorial Laplacian. Deciding whether a Betti number of a clique complex is nonzero is QMA1QMA_1QMA1​-hard, and remains so under a spectral gap promise on vertex-weighted graphs. Integral homology, however, contains information inaccessible to the Laplacian spectrum. A new part that appears in integral homology is torsion: cycles that become boundaries only after being traversed several times, as in a projective plane or a Klein bottle. We ask how hard it is to detect torsion, and we answer with a simple reduction. We attach to an arbitrary clique complex a fixed 313131-vertex triangulation of the projective plane. The kkkth mod-222 Betti number of the input then reappears as 222-torsion two degrees up, while all rational homology disappears and every combinatorial Laplacian acquires a constant spectral gap. We conclude that detecting torsion in clique complexes of unweighted graphs is NPNPNP-hard, even under a constant gap promise, and that it is QMA1QMA_1QMA1​-hard if mod-222 clique homology is.
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 GGG and its clique complex K=Cl(G)K = \mathrm{Cl}(G)K=Cl(G), we first prove that, for fixed rrr and prime ppp, deciding whether Hr(K,Z)H_r(K,\mathbb{Z})Hr​(K,Z) contains ppp-torsion is NP-hard. As a corollary, when a homological rotor code is specified by GGG, 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 PPP, we develop a quantum algorithm that serves as a one-sided torsion witness. For fixed rrr, it outputs WITNESS or INCONCLUSIVE, i.e. WITNESS certifies that either Hr(K,Z)H_r(K,\mathbb{Z})Hr​(K,Z) or Hr−1(K,Z)H_{r-1}(K,\mathbb{Z})Hr−1​(K,Z) contains ppp-torsion for some p∈Pp\in Pp∈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.
Gapped Clique Homology on Weighted Graphs Is QMA1{\text{QMA}_1}QMA1​-Hard and Contained in QMA
Abstract. We study the complexity of a classic problem in computational topology, the homology problem: given a description of some space [Formula: see text] and an integer [Formula: see text], decide if [Formula: see text] contains a [Formula: see text]-dimensional hole. The setting and statement of the homology problem are completely classical, yet we find that the complexity is characterized by quantum complexity classes. Our result can be seen as an aspect of a connection between homology and supersymmetric quantum mechanics established by Witten (1982). We consider clique complexes, motivated by the practical application of topological data analysis (TDA). The clique complex of a graph is the simplicial complex formed by declaring every [Formula: see text]-clique in the graph to be a [Formula: see text]-simplex. Our main result is that deciding whether the clique complex of a weighted graph has a hole or not, given a suitable promise on the gap, is [Formula: see text]-hard and contained in QMA. Our main innovation is a technique to lower bound the eigenvalues of the combinatorial Laplacian operator. For this, we invoke a tool from algebraic topology known as spectral sequences. In particular, we exploit a connection between spectral sequences and Hodge theory outlined by Forman (1994). Spectral sequences will play a role analogous to perturbation theory for combinatorial Laplacians. In addition, we develop the simplicial surgery technique used in prior work by Crichigno and Kohler (2022). Our result provides some suggestion that the quantum TDA algorithm due to Lloyd, Garnerone, and Zanardi (2016) cannot be dequantized, although proving this would require studying the complexity of a different problem related to the combinatorial Laplacian of clique complexes.
Betti numbers are central to topological data analysis but fail to capture torsion in integral homology. Torsion can distinguish topological structures with identical Betti numbers, and examples from classical topological data analysis show that it can affect the topology inferred from data. Related torsion-sensitive quantities are also known to have practical applications in graph-based machine learning, including biomedical applications. We investigate how quantum spectral methods can access this additional information. Log pseudodeterminants, obtained by summing the logarithms of the nonzero boundary-Laplacian eigenvalues, summarize spectral information about a simplicial complex. Under explicit topological assumptions, an alternating combination of these quantities gives the size of a higher critical group, the higher-dimensional analogue of a graph sandpile group. With stronger certification, a related construction recovers the size of the torsion subgroup in homology itself. This is, to our knowledge, the first provably correct quantum estimator of integral-homology torsion order. We give a new quantum algorithm for estimating these quantities, with explicit dependence on how the input is queried, the required accuracy, and the spectral gaps. Exact spectra for balanced multipartite clique complexes provide favorable gaps, and a related construction gives an explicit torsion-bearing benchmark. With compact query access, the algorithm need not construct the exponentially large boundary matrices explicitly. For a restricted torsion-bearing family, a tailored amplitude-estimation routine uses quadratically fewer queries than any randomized classical algorithm given comparable access when estimating the log pseudodeterminant. Estimating the full, unnormalized quantity to fixed additive error still costs in proportion to the candidate-space dimension DDD.
Gapped Clique Homology on weighted graphs is QMA1\text{QMA}_1QMA1​-hard and contained in QMA\text{QMA}QMA
We study the complexity of a classic problem in computational topology, the homology problem: given a description of some space XXX and an integer kkk, decide if XXX contains a kkk-dimensional hole. The setting and statement of the homology problem are completely classical, yet we find that the complexity is characterized by quantum complexity classes. Our result can be seen as an aspect of a connection between homology and supersymmetric quantum mechanics. We consider clique complexes, motivated by the practical application of topological data analysis (TDA). The clique complex of a graph is the simplicial complex formed by declaring every k+1k+1k+1-clique in the graph to be a kkk-simplex. Our main result is that deciding whether the clique complex of a weighted graph has a hole or not, given a suitable promise on the gap, is QMA1\text{QMA}_1QMA1​-hard and contained in QMA\text{QMA}QMA. Our main innovation is a technique to lower bound the eigenvalues of the combinatorial Laplacian operator. For this, we invoke a tool from algebraic topology known as \emph{spectral sequences}. In particular, we exploit a connection between spectral sequences and Hodge theory. Spectral sequences will play a role analogous to perturbation theory for combinatorial Laplacians. In addition, we develop the simplicial surgery technique used in prior work. Our result provides some suggestion that the quantum TDA algorithm \emph{cannot} be dequantized. More broadly, we hope that our results will open up new possibilities for quantum advantage in topological data analysis.
Unweighted Gapped Clique Homology is QMA1\mathsf{QMA}_1QMA1​-complete
Deciding whether the clique complex of a given graph has nontrivial homology in a given dimension, under vertex-product weighting and an inverse-polynomial spectral gap promise on the combinatorial Hodge Laplacian, is known to be QMA1\mathsf{QMA}_1QMA1​-hard and contained in QMA\mathsf{QMA}QMA by King and Kohler (FOCS 2024). The vertex weights are essential in the known proof, where they provide the scale separation needed for the spectral gap analysis. We prove that, when every vertex has weight one, the problem remains QMA1g2\mathsf{QMA}_1^{g_2}QMA1g2​​-hard and is contained in QMA1g2\mathsf{QMA}_1^{g_2}QMA1g2​​, where QMA1g2\mathsf{QMA}_1^{g_2}QMA1g2​​ is QMA1\mathsf{QMA}_1QMA1​ with the universal gate set g2={X,CX,CCX,H⊗H}g_2=\{\mathsf{X},\mathsf{CX},\mathsf{CCX},H\otimes H\}g2​={X,CX,CCX,H⊗H}. The construction replaces weight by expansion: each vertex of the weighted complex is blown up into a clique whose size encodes its weight. The block sizes are chosen so that symmetric averages reproduce the weighted Hodge metric. The symmetric sector therefore carries the weighted Laplacian up to a common scalar factor, while a local averaging argument gives a uniform lower bound on the orthogonal complement to the symmetric sector. Hence the weighted gap analysis transfers to an unweighted clique complex without introducing either additional low-energy states or spurious homology. Containment in QMA1g2\mathsf{QMA}_1^{g_2}QMA1g2​​ follows from Rudolph's exact linear combination of unitaries simulation of sparse integer clique Laplacians. The result shows that the gap promise, rather than vertex weighting, is the source of the complexity of gapped clique homology.
We establish the average-case hardness of Betti number estimation on random clique complexes via a reduction from the planted clique problem. We further show that our reduction implies a series of hardness results for many problems in both classical and quantum Topological Data Analysis (qTDA). Under the classical planted clique conjecture, no randomized polynomial-time Betti number estimator achieves additive error below 12\tfrac1221​ with constant advantage. Under a new quantum planted clique conjecture that we introduce, the same conclusion holds for quantum polynomial-time algorithms. We also obtain related conditional hardness results for homology vanishing, additive approximations with larger error tolerances, preparation of simplex and harmonic states, cycle recovery, and counting eigenvalues at low energy. Our reduction clarifies the structural requirements for quantum advantage in TDA and provides a new lens to investigate the classical and quantum complexity of related problems.