alphaFeedback

WorksMathematics

A Short Proof and Generalization of the Rainbow Cycle Theorem and Improved Bounds for Binary Even-Query LCCs

AI contributions
  • GPT-5.6 Sol · bare
  • ChatGPT 6-Astra
View details

Abstract

A rainbow cycle in a list-edge-colored graph is a cycle where no color appears more than once. We give a short and simple proof of a result of [ABSZZ] showing that a properly edge-colored nn-vertex graph with average degree Ω(log⁡nlog⁡log⁡n)Ω(\log n\log\log n) always contains a rainbow cycle, and generalize it to weighted graphs with edges list colored with list size at most ℓ\ell and where the total weight of all edges containing a given color ii incident to a vertex is at most ΔΔ, showing that Ωℓ(Δlog⁡nlog⁡log⁡n)Ω_\ell(Δ\log n\log\log n) average degree guarantees a rainbow cycle. Using the reduction of [AG26] and the new generalized rainbow cycle theorem, we prove that for r≥3r\geq 3, every binary linear rr-query locally correctable code E:F2k→F2nE:\mathbb{F}_2^k\rightarrow \mathbb{F}_2^n satisfies k≤O~(n1−2/(r−1))k\leq \tilde{O}(n^{1-2/(r-1)}) by showing a rainbow analogue of the odd rr-LDC lower bounds of [BHKL25,JM25], closing the gap between the best known lower bounds for odd- and even-query binary linear rr-LCCs.

Introduction

Graph coloring is a fundamental area of study in extremal combinatorics, and one question with a large amount of recent progress is the structure of properly edge-colored graphs. A cycle in an edge-colored graph is called rainbow if no color appears more than once, and the work of [18] raised the question of the number of edges (equivalently, the average degree) needed to guarantee the existence of a rainbow cycle. Their work showed a lower bound on the average degree of Ω(log⁡n)\Omega(\log n), and a long line of work [9 Jan20, 22, 16, 15] culminating in [1] proved this is nearly tight, showing that properly edge-colored graphs with average degree Ω(log⁡nlog⁡log⁡n)\Omega(\log n \log\log n) must contain a rainbow cycle (closing this log⁡log⁡n\log\log n gap remains an open question). The rainbow cycle theorem of [1] has found many applications, notably in coding theory.

A binary code E:F2k→F2nE : \mathbb{F}_2^k \to\mathbb{F}_2^n is called a (r,δ)(r,\delta)-locally correctable code, abbreviated as (r,δ)(r,\delta)-LCC, if any codeword E(x)E(x) has at most a δ\delta fraction of coordinates flipped to produce some y∈F2ny \in\mathbb{F}_2^n, for each coordinate i∈[n]i \in[n], there exists an algorithm which queries at most rr coordinates of $y and outputs the iith bit E(x)iE(x)_i of the original codeword with nontrivial probability. LCCs were introduced for program checking [8], and played a central role in the proof of the PCP theorem [5, 4], among numerous other applications. A central question in the study of LCCs is determining the optimal rate (the ratio of the message length kk to the blocklength nn of a codeword) of a rr-query LCC.

Until recently, lower bounds on LCCs were simply those of locally decodable codes, or LDCs, where instead of the code admitting rr-query decoding algorithms which can output the iith bit of the codeword E(x)E(x), we only need to have rr-query decoding algorithms for each bit xix_i, i∈[k]i \in[k] of the message. 1-LDCs do not exist [19] and for 2-LDCs, we have an exponential lower bound of k≤O~(log⁡n)k \le\widetilde{O}(\log n) on the blocklength, which is tight [20, 10]. These results carry over to LCCs. For even r≥4r \ge4-LDCs, the best lower bounds are k≤O~(n1−2/r)k \le\widetilde{O}(n^{1-2/r}) [23, 24, 25, 6], and for odd rr-LDCs, the best known bounds were simply those of even (r+1)(r+1)-LDCs (since any rr-LDC is also a (r+1)(r+1)-LDC) until a breakthrough work of [3] proved k≤O~(n1−2/r)k \le\widetilde{O}(n^{1-2/r}) for r=3r=3 using the Kikuchi Method, at the same time also giving a simple proof of the even rr case. The follow-up works of [7, 14] generalized the Kikuchi method to obtain the same bound for all odd r≥5r \ge5. For linear 3-LCCs, [17] obtained an exponential k≤O(log⁡8n)k \le O(\log^8 n) lower bound, which was later improved to k≤O(log⁡4n)k \le O(\log^4 n) by [26] (see also [21]), which, prior to the rainbow cycle theorem, were the only results showing a stronger lower bound for linear rr-LCCs over a constant-sized Fq\mathbb{F}_q compared for those known for rr-LDCs.

The work of [2] showed a surprising connection between LCCs and rainbow cycles, proving a reduction from binary linear rr-LCC lower bounds to a stronger notion of "rainbow" (r−1)(r-1)-LDC lower bounds. By using the rainbow cycle theorem of [1], they prove rainbow lower bounds for even rr-LDCs, implying a near-optimal bound of k≤O(log⁡2nlog⁡log⁡n)k \le O(\log^2 n\log\log n) for binary linear 3-LCCs, nearly matching the k=O(log⁡2n)k=O(\log^2 n) given by Reed-Muller codes. They also obtain an improved k≤O~(n1−2/(r−1))k \le\widetilde{O}(n^{1-2/(r-1)}) lower bound for odd rr-LCCs. However, this does not work for even rr-LCCs, as we cannot reduce odd LDC lower bounds to analyzing edge-colored graphs where each edge is assigned exactly one color; instead, the graphs here have edges colored by a pair of colors. This in turn motivates the question of proving a generalization of the rainbow cycle to list-colored graphs.

Our results

Our main result is the following theorem, which generalizes the result of [1] to weighted, locally bounded list-colored graphs.

Theorem 1.1. Let CC be a set of colors and GG be an edge-weighted NN-vertex graph, where each edge e∈E(G)e \in E(G) is assigned a nonempty list L(e)⊆CL(e) \subseteq C where ∣L(e)∣≤ℓ|L(e)| \le\ell, and a weight w(e)∈R≥0w(e) \in\mathbb{R}_{\ge0}. Suppose that, for each color c∈Cc \in C and any vertex u∈V(G)u \in V(G), the total weight deg⁡c(u)=∑e∋u,L(e)∋cw(e)\deg_c(u) = \sum_{e \ni u,L(e) \ni c} w(e) of all edges ee incident to uu such that L(e)∋cL(e) \ni c is at most Δ\Delta. For sufficiently large NN, if d(V(G))≥13Δℓ2ℓlog⁡(N)log⁡log⁡(N)d(V(G)) \ge13\Delta\ell^2\ell^{\log(N)\log\log(N)}, then GG contains a rainbow cycle.

Using this theorem, we close the gap between even and odd rr-LCCs, proving the following lower bound for all rr.

Theorem 1.2. Let E:F2k→F2nE : \mathbb{F}_2^k \to\mathbb{F}_2^n be a linear (r,δ)(r,\delta)-LCC for any r≥3r \ge3. Then we have k≤O(δ−2n1−2/(r−1)log⁡3n)k \le O(\delta^{-2}n^{1-2/(r-1)}\log^3 n).

Technical Overview

In this section, we give an overview of the proofs of Theorems 1.1 and 1.2. We first summarize the Kikuchi method of [3 HKM+25, 2, 7, 14] for LDC/LCC lower bounds and the approach of [1] for the rainbow cycle theorem.

Kikuchi graphs and LDCs/LCCs. Given a linear rr-LDC, standard reductions allow us to prove lower bounds for normal linear LDCs, which have the property that for each bit i∈[k]i \in[k] of the message, there exists a rr-uniform size-Ω(n)\Omega(n) hypergraph matching Hi\mathcal{H}_i on [n][n] such that to decode the iith bit xix_i of a message xx given the encoding E(x)E(x), we simply pick any C∈HiC \in\mathcal{H}_i, and take the XOR of the coordinates in CC of E(x)E(x). We note that if we have an even cover (a set of hyperedges C1,⋯ ,CtC_1,\cdots,C_t such that ⨁u∈[t]Cu=∅\bigoplus_{u \in[t]} C_u = \varnothing, i.e. it cover every vertex an even (possibly 0) number of times), such that there is some Hi\mathcal{H}_i such that we use an odd number of hyperedges from Hi\mathcal{H}_i, then taking the XOR of all E(x)iE(x)_i, i∈Cui \in C_u, will return 0. However, letting Cu∈HiuC_u \in\mathcal{H}_{i_u} for all uu, the normal LDC decoding property implies that this is equal to the XOR of the iui_uth bit of xx, and since there is some xix_i that appears an odd number of times, this is not equal to 0 if xi=1x_i = 1. Therefore, proving a bound of k<k(r,n)k < k(r,n) for all rr-LDCs is equivalent to showing that when k≥k(r,n)k \geq k(r,n), any set of Ω(n)\Omega(n), rr-uniform hypergraph matchings contains an even cover using some Hi\mathcal{H}_i an odd number of times.

For even rr, [3] constructs a level-ℓ\ell Kikuchi graph, which has vertex set consisting of all size-ℓ\ell subsets of [n][n], and edges between any two S,T∈([n]ℓ)S,T \in\binom{[n]}{\ell} such that the symmetric difference S⊕TS \oplus T is a hyperedge. Any cycle in the Kikuchi graph corresponds to an even cover in the set of hypergraph matchings, and by coloring an edge (S,T)(S,T) with color ii if S⊕T∈HiS \oplus T \in\mathcal{H}_i, a sufficient condition for the desired even cover property is to find a cycle which uses some color exactly once, which we call an weak rainbow cycle. By deleting a 12\frac{1}{2} fraction of edges, we can make the Kikuchi graph properly edge colored, after which classic results [18] show the existence of a weak rainbow cycle.

For odd rr-LDCs, the aforementioned definition of Kikuchi graphs does not work: the symmetric difference of any two size-ℓ\ell sets is always even and thus can never be a hyperedge in one of the odd rr-uniform hypergraph matchings we have. Instead, [3 HKM+25, 7, 14] consider pairs of hyperedges C∈Hi,C′∈HjC \in\mathcal{H}_i,C' \in\mathcal{H}_j from separate matchings with nonempty intersection, instead connecting two Kikuchi vertices S,TS,T if S⊕T=C⊕C′S \oplus T = C \oplus C' and coloring the edge with a pair of colors {i,j}\{i,j\}1. As before, finding a weak rainbow cycle is sufficient for proving the desired even cover property, and this can be done using results for list-colored graphs from [18]. Thus, for LDCs, we have matching lower bounds for odd rr-LDCs.

[2] show that if for all k≥k′(r−1,n)k \geq k'(r-1,n), any set of size-Ω(n)\Omega(n), (r−1)(r-1)-uniform hypergraph matchings H1∪⋯∪Hk\mathcal{H}_1 \cup\cdots\cup\mathcal{H}_k contains a rainbow even cover, meaning an even cover using at most one hyperedge from each Hi\mathcal{H}_i, then for every binary linear rr-LCC, we have k≲k′(r−1,n)log⁡nk \lesssim k'(r-1,n)\log n. When r−1r-1 is even, they apply the result of [1] to the Kikuchi graph for even LDCs to show the existence of a rainbow cycle and therefore a rainbow even cover. However, the rainbow cycle theorem does not apply to list-colored graphs, so they do not obtain the same result when r−1r-1 is odd.

Finding rainbow cycles: current approaches and barriers to generalization. [1] makes use of robust sublinear expanders, which are graphs in which any subset SS of n1−εn^{1-\varepsilon} vertices has a size Ω(ε∣S∣)=Ω(∣S∣(1−log⁡∣S∣log⁡n))\Omega(\varepsilon|S|)=\Omega\left(|S|\left(1-\frac{\log|S|}{\log n}\right)\right) neighborhood even after Ω(εdavg∣S∣)\Omega(\varepsilon d_{\mathrm{avg}}|S|) edges incident to SS are adversarially deleted. Given a properly edge-colored graph GG with color set C\mathcal{C}, they find a robust sublinear expander subgraph HH and obtain a rainbow cycle HH as follows: first, pick an arbitrary vertex x∈V(H)x \in V(H), and partition C=C′⊔C′′\mathcal{C}=\mathcal{C}'\sqcup\mathcal{C}'' uniformly at random. Then if there is a vertex y∈V(H)y \in V(H) reachable from xx by both a rainbow path using only colors in C′\mathcal{C}', and a rainbow path using only colors in C′′\mathcal{C}'', then the union of the two paths is a rainbow cycle in HH. By showing that the set U(C′)U(\mathcal{C}') of all vertices reachable from xx via a rainbow path in C′\mathcal{C}' has size >n+12>\frac{n+1}{2} with probability >12>\frac{1}{2}, one can show that U(C′)U(\mathcal{C}') and U(C′′)U(\mathcal{C}'') (defined analogously, and which has the same distribution as U(C′)U(\mathcal{C}')) intersect with positive probability and therefore one can find a rainbow cycle.

References

  1. [1][ABS+25] Noga Alon, Matija Bučić, Lisa Sauermann, Dmitrii Zakharov, and Or Zamir. Essentially tight bounds for rainbow cycles in proper edge-colourings. Proceedings of the London Mathematical Society, 130(4):e70044, 2025. (pg. 1, 2, 3, 4, 5)arxiv.org/abs/2309.04460
  2. [2][AG26] Omar Alrabiah and Venkatesan Guruswami. Near-tight bounds for 3-query locally correctable binary linear codes via rainbow cycles. SIAM Journal on Computing, 0(0):FOCS24–296–FOCS24–315, 2026. (pg. 1, 2, 3, 7)
  3. [3]Omar Alrabiah, Venkatesan Guruswami, Pravesh K. Kothari, and Peter Manohar. A near-cubic lower bound for 3-query locally decodable codes from semirandom CSP refutation. In Proceedings of the 55th Annual ACM Symposium on Theory of Computing, STOC 2023, Orlando, FL, USA, June 20-23, 2023, pages 1438–1448. ACM, 2023. (pg. 2, 3)
  4. [4]Sanjeev Arora, Carsten Lund, Rajeev Motwani, Madhu Sudan, and Mario Szegedy. Proof verification and the hardness of approximation problems. Journal of the ACM (JACM), 45(3):501–555, 1998. (pg. 2)
  5. [5]Sanjeev Arora and Shmuel Safra. Probabilistic checking of proofs: A new characterization of np. Journal of the ACM (JACM), 45(1):70–122, 1998. (pg. 2)
  6. [6]Arnab Bhattacharyya, L Sunil Chandran, and Suprovat Ghoshal. Combinatorial Lower Bounds for 3-Query LDCs. In 11th Innovations in Theoretical Computer Science Conference (ITCS 2020), volume 151, page 85. Schloss Dagstuhl–Leibniz-Zentrum fuer Informatik, 2020. (pg. 2)arxiv.org/abs/1911.10698
  7. [7]Arpon Basu, Jun-Ting Hsieh, Pravesh K. Kothari, and Andrew D. Lin. Improved lower bounds for all odd-query locally decodable codes. In 66th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2025, Sydney, Australia, December 14-17, 2025, pages 1262–1285. IEEE, 2025. (pg. 1, 2, 3, 7, 8, 13)arxiv.org/abs/2411.14361
  8. [8]Manuel Blum and Sampath Kannan. Designing programs that check their work. Journal of the ACM (JACM), 42(1):269–291, 1995. (pg. 2)
  9. [9]Shagnik Das, Choongbum Lee, and Benny Sudakov. Rainbow Turán problem for even cycles. European Journal of Combinatorics, 34(5):905–915, 2013. (pg. 1)DOI
  10. [10]Oded Goldreich, Howard Karloff, Leonard J Schulman, and Luca Trevisan. Lower bounds for linear locally decodable codes and private information retrieval. Computational Complexity, 15(3):263–296, 2006. (pg. 2)
  11. [11]Geoffrey Grimmett. Percolation, volume 321 of Grundlehren der mathematischen Wissenschaften [Fundamental Principles of Mathematical Sciences]. Springer-Verlag, Berlin, second edition, 1999. (pg. 7)
  12. [14]Oliver Janzer and Peter Manohar. A k^q/q^2 lower bound for odd query locally decodable codes from bipartite kikuchi graphs. In 66th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2025, Sydney, Australia, December 14-17, 2025, pages 75–85. IEEE, 2025. (pg. 1, 2, 3, 13)
  13. [15]Oliver Janzer and Benny Sudakov. On the turán number of the hypercube. Forum of Mathematics, Sigma, 12:e38, 2024. (pg. 1)
  14. [16]Jaehoon Kim, Joonkyung Lee, Hong Liu, and Tuan Tran. Rainbow Cycles in Properly Edge-Colored Graphs. Combinatorica, 44(4):909–919, Aug 2024. (pg. 1)arxiv.org/abs/2211.03291
  15. [17]Pravesh K. Kothari and Peter Manohar. An exponential lower bound for linear 3-query locally correctable codes. CoRR, abs/2311.00558, 2023. (pg. 2)arxiv.org/abs/2311.00558
  16. [18]Peter Keevash, Dhruv Mubayi, Benny Sudakov, and Jacques Verstraëte. Rainbow Turán Problems. Combinatorics, Probability and Computing, 16(1):109–126, 2007. (pg. 1, 3)DOI
  17. [19]Jonathan Katz and Luca Trevisan. On the efficiency of local decoding procedures for error-correcting codes. In Proceedings of the thirty-second annual ACM symposium on Theory of computing, pages 80–86, 2000. (pg. 2)DOI
  18. [20]Iordanis Kerenidis and Ronald de Wolf. Exponential lower bound for 2-query locally decodable codes via a quantum argument. Journal of Computer and System Sciences, 69(3):395–420, 2004. (pg. 2)
  19. [21]Peter Manohar. New Spectral Techniques in Algorithms, Combinatorics, and Coding Theory: The Kikuchi Matrix Method. PhD thesis, Carnegie Mellon University, 2024. (pg. 2)
  20. [22]István Tomon. Robust (rainbow) subdivisions and simplicial cycles. Advances in Combinatorics, Jan 8 2024. (pg. 1)
  21. [23]David Woodruff. New lower bounds for general locally decodable codes. In Electronic Colloquium on Computational Complexity (ECCC), volume 14, 2007. (pg. 2)
  22. [24]David Woodruff. Corruption and recovery-efficient locally decodable codes. In Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques, pages 584–595. Springer, 2008. (pg. 2)DOI
  23. [25]David P Woodruff. A quadratic lower bound for three-query linear locally decodable codes over any field. Journal of Computer Science and Technology, 27(4):678–686, 2012. (pg. 2)
  24. [26]Tal Yankovitz. A stronger bound for linear 3-lcc. Electron. Colloquium Comput. Complex., pages TR24–036, 2024. (pg. 2)DOI

Paper details

vlnc:W_f223mybf
v1 · latestHistory (1)

published · Fresh — added to the Hub within the last 30 days

added ·

Usage

views · 8

downloads · 0

A view counts once per browser per day, a download each time the PDF is requested.

CC BY 4.0

Original source

  • Mathematics

GPT-5.6 Sol (bare), ChatGPT 6-Astra · View statement →

Looking for related papers…
Contents