Search arXiv⌕ Search

arXiv · 2610.36516

Upper and Lower Bounds on the Complexity of Unit-Distance Graph Realization in $\mathbb{Z}^d$

Abstract

It is known that the problem of recognizing the existence of a unit-distance realization in $\mathbb{Z}^d$ for a graph $G$ is NP-complete. Here, assuming ETH, we give a sub-exponential lower bound of $2^{Ω(\sqrt{n})}$ for this problem in $\mathbb{Z}^2$ and $2^{Ω(n^{2/3})}$ in $\mathbb{Z}^3$, and give an upper bound of $2^{O(n^{(d-1)/d} (\log n)^2)}$ for the time complexity with an explicit divide-and-conquer algorithm. This approach beats naive exhaustive search by a factor of $\tildeΩ(n^{1/d})$ in the exponent. For 2 and 3 dimensions, our upper and lower bounds match to within a logarithmic factor.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Eric Binnendyk. 2026-10-27. Upper and Lower Bounds on the Complexity of Unit-Distance Graph Realization in $\mathbb{Z}^d$. https://arxiv.org/abs/2610.36516

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Optimal Inapproximability of Satisfiable $k$-LIN over Non-Abelian Groups

A seminal result of Håstad [J. ACM, 48(4):798--859, 2001] shows that it is NP-hard to find an assignment that satisfies $\frac{1}{|G|}+\varepsilon$ fraction of the constraints of a given $k$-LIN instance over an abelian group, even if there is an assignment that satisfies $(1-\varepsilon)$ fraction of the constraints, for any constant $\varepsilon>0$. Engebretsen et al. [Theoretical Computer Science, 312(1):17--45, 2004] later showed that the same hardness result holds for $k$-LIN instances over any finite non-abelian group. Unlike the abelian case, where we can efficiently find a solution if the instance is satisfiable, in the non-abelian case, it is NP-complete to decide if a given system of linear equations is satisfiable or not, as shown by Goldmann and Russell [Information and Computation, 178(1):253--262. 2002]. Surprisingly, for certain non-abelian groups $G$, given a satisfiable $k$-LIN instance over $G$, one can in fact do better than just outputting a random assignment using a simple but clever algorithm. The approximation factor achieved by this algorithm varies with the underlying group. In this paper, we show that this algorithm is {\em optimal} by proving a tight hardness of approximation of satisfiable $k$-LIN instance over {\em any} non-abelian $G$, assuming $P \neq NP$. As a corollary, we also get $3$-query probabilistically checkable proofs with perfect completeness over large alphabets with improved soundness. Our proof crucially uses structural properties captured by Gowers' notion of {\em quasi-randomness} for non-abelian groups [Combinatorics, Probability and Computing, 17(3):363--387, 2008].

cs.CC↗

Entrywise Logarithmic Matrix Algebra and Dichotomy of Planar Graph Homomorphisms

We prove a complexity classification of counting planar graph homomorphisms with non-negative weights. For a real symmetric matrix $M$ with nonnegative entries, the problem $\GH(M)$ is either (1) P-time computable over all graphs, or (2) \#P-hard in general but P-time computable over planar graphs, or (3) \#P-hard over planar graphs. Furthermore, $\GH(M)$ in (2) consists of precisely those that involve the P-time FKT algorithm to count planar perfect matchings with a holographic transformation. The dichotomy for entrywise positive and full rank matrices lies at the core of the proof. In this setting, the main tool is a matrix algebra ${A}$ (a vector space with bilinear multiplication) formed by taking the real span of (centered) entrywise logarithms of all realizable matrices from $M$ using planar edge gadgets and polynomial interpolation. We then define a multiplicative homomorphism $F(\cdot)$ on the algebra ${A}$, which turns out to be a polynomial map. The exponents of prime factorization of component polynomials of $F$ induce graph distances for distance-regular graphs. These graphs are either the Hamming graphs or Doob graphs using a classification result for distance-regular graphs (if $\PlGH(M)$ is not \#P-hard), after obtaining their intersection numbers. The dichotomy is proved in either case. We then extend the complexity classification to all nonnegative matrices.

cs.CC↗

A proof of P != NP (New symmetric encryption algorithm against any linear attacks and differential attacks)

P vs NP problem is the most important unresolved problem in the field of computational complexity. Its impact has penetrated into all aspects of algorithm design, especially in the field of cryptography. The security of cryptographic algorithms based on short keys depends on whether P is equal to NP. In fact, the security requirements for cryptographic keys are much stricter than those for P$\neq$NP, the security of the key must ensure not only a sufficiently high computational complexity to crack it, but also consider the security of each bit of the key, while fully avoiding the effectiveness of various attack methods. In this paper, we innovatively propose a new encoding mechanism and develop a novel block symmetric encryption algorithm, which be named Eagle, whose encryption and decryption can be completed in linear time. The key consists of 10 variables, for the attacker, in the case when only the plaintext-ciphertext correspondence is known, the problem of cracking the key is equivalent to solving a system of equations about ten unknown variables together with some implicit variables which are generated by the encryption process. In this paper, we will prove that there is no universal algorithm without brute-force searching at least one variable during the process of verifying four of the ten variables whose computational complexity is not greater than solving the ten variables. After performing elimination the implicit variables, the problem of verifying the four variables will be equivalently transformed into a series of general quintic equations about one variable with coefficient given by other four variables, according to the conclusion that ``there is no algebraic solution to quintic equations", we can't establish a system of algebraic equations only containing the other four variables......

cs.CC↗