The Geodesic Diameter of Polygonal Domains

This paper studies the geodesic diameter of polygonal domains having $h$ h holes and $n$ n corners. For simple polygons (i.e., $h=0$ h = 0 ), the geodesic diameter is determined by a pair of corners of a given polygon and can be computed in linear time, as shown by Hershberger and Suri. For general polygonal domains with $h \ge 1$ h ≥ 1 , however, no algorithm for computing the geodesic diameter was known prior to this paper. In this paper, we present the first algorithms that compute the geodesic diameter of a given polygonal domain in worst-case time $O(n^{7.73})$ O ( n 7.73 ) or $O(n^7 (\log n + h))$ O ( n 7 ( log n + h ) ) . The main difficulty unlike the simple polygon case relies on the following observation revealed in this paper: two interior points can determine the geodesic diameter and in that case there exist at least five distinct shortest paths between the two.     

Many Collinear k-Tuples with no k+1 Collinear Points

For every $k>3$ k > 3 , we give a construction of planar point sets with many collinear $k$ k -tuples and no collinear $(k+1)$ ( k + 1 ) -tuples. We show that there are $n_0=n_0(k)$ n 0 = n 0 ( k ) and $c=c(k)$ c = c ( k ) such that if $n\ge n_0$ n ≥ n 0 , then there exists a set of $n$ n points in the plane that does not contain $k+1$ k + 1 points on a line, but it contains at least $n^{2-({c}/{\sqrt{\log n}})}$ n 2 - ( c / log n ) collinear $k$ k -tuples of points. Thus, we significantly improve the previously best known lower bound for the largest number of collinear $k$ k -tuples in such a set, and get reasonably close to the trivial upper bound $O(n^2)$ O ( n 2 ) .     

Improved Enumeration of Simple Topological Graphs

A simple topological graph $T=(V(T), E(T))$ T = ( V ( T ) , E ( T ) ) is a drawing of a graph in the plane where every two edges have at most one common point (an endpoint or a crossing) and no three edges pass through a single crossing. Topological graphs $G$ G and $H$ H are isomorphic if $H$ H can be obtained from $G$ G by a homeomorphism of the sphere, and weakly isomorphic if $G$ G and $H$ H have the same set of pairs of crossing edges. We generalize results of Pach and Tóth and the author’s previous results on counting different drawings of a graph under both notions of isomorphism. We prove that for every graph $G$ G with $n$ n vertices, $m$ m edges and no isolated vertices the number of weak isomorphism classes of simple topological graphs that realize $G$ G is at most $2^{O(n^2\log (m/n))}$ 2 O ( n 2 log ( m / n ) ) , and at most $2^{O(mn^{1/2}\log n)}$ 2 O ( m n 1 / 2 log n ) if $m\le n^{3/2}$ m ≤ n 3 / 2 . As a consequence we obtain a new upper bound $2^{O(n^{3/2}\log n)}$ 2 O ( n 3 / 2 log n ) on the number of intersection graphs of $n$ n pseudosegments. We improve the upper bound on the number of weak isomorphism classes of simple complete topological graphs with $n$ n vertices to $2^{n^2\cdot \alpha (n)^{O(1)}}$ 2 n 2 · α ( n ) O ( 1 ) , using an upper bound on the size of a set of permutations with bounded VC-dimension recently proved by Cibulka and the author. We show that the number of isomorphism classes of simple topological graphs that realize $G$ G is at most $2^{m^2+O(mn)}$ 2 m 2 + O ( m n ) and at least $2^{\Omega (m^2)}$ 2 Ω ( m 2 ) for graphs with $m>(6+\varepsilon )n$ m > ( 6 + ε ) n .     

Bounds on the Complexity of Halfspace Intersections when the Bounded Faces have Small Dimension

For a polyhedron $P$ P let $B(P)$ B ( P ) denote the polytopal complex that is formed by all bounded faces of $P$ P . If $P$ P is the intersection of $n$ n halfspaces in $\mathbb R ^D$ R D , but the maximum dimension $d$ d of any face in $B(P)$ B ( P ) is much smaller, we show that the combinatorial complexity of $P$ P cannot be too high; in particular, that it is independent of $D$ D . We show that the number of vertices of $P$ P is $O(n^d)$ O ( n d ) and the total number of bounded faces of the polyhedron is $O(n^{d^2})$ O ( n d 2 ) . For inputs in general position the number of bounded faces is $O(n^d)$ O ( n d ) . We show that for certain specific values of $d$ d and $D$ D , our bounds are tight. For any fixed $d$ d , we show how to compute the set of all vertices, how to determine the maximum dimension of a bounded face of the polyhedron, and how to compute the set of bounded faces in polynomial time, by solving a number of linear programs that is polynomial in  $n$ n .     

An Approximation Algorithm for Computing Shortest Paths in Weighted 3-d Domains

We present an approximation algorithm for computing shortest paths in weighted three-dimensional domains. Given a polyhedral domain $\mathcal D $ D , consisting of $n$ n tetrahedra with positive weights, and a real number $\varepsilon \in (0,1)$ ε ∈ ( 0 , 1 ) , our algorithm constructs paths in $\mathcal D $ D from a fixed source vertex to all vertices of $\mathcal D $ D , the costs of which are at most $1+\varepsilon $ 1 + ε times the costs of (weighted) shortest paths, in $O(\mathcal{C }(\mathcal D )\frac{n}{\varepsilon ^{2.5}}\log \frac{n}{\varepsilon }\log ^3\frac{1}{\varepsilon })$ O ( C ( D ) n ε 2.5 log n ε log 3 1 ε ) time, where $\mathcal{C }(\mathcal D )$ C ( D ) is a geometric parameter related to the aspect ratios of tetrahedra. The efficiency of the proposed algorithm is based on an in-depth study of the local behavior of geodesic paths and additive Voronoi diagrams in weighted three-dimensional domains, which are of independent interest. The paper extends the results of Aleksandrov et al. (J ACM 52(1):25–53, 2005), to three dimensions.     

On Topological Changes in the Delaunay Triangulation of Moving Points

Let $P$ P be a collection of $n$ n points moving along pseudo-algebraic trajectories in the plane. (So, in particular, there are constants $s,c>0$ s , c > 0 such that any four points are co-circular at most $s$ s times, and any three points are collinear at most $c$ c times.) One of the hardest open problems in combinatorial and computational geometry is to obtain a nearly quadratic upper bound, or at least a sub-cubic bound, on the maximum number of discrete changes that the Delaunay triangulation ${\mathrm{DT}}(P)$ DT ( P ) of $P$ P experiences during the motion of the points of $P$ P . In this paper, we obtain an upper bound of $O(n^{2+{\varepsilon }})$ O ( n 2 + ε ) , for any ${\varepsilon }>0$ ε > 0 , under the assumptions that (i) any four points can be co-circular at most twice and (ii) either no triple of points can be collinear more than twice or no ordered triple of points can be collinear more than once.     

Tracing Compressed Curves in Triangulated Surfaces

A simple path or cycle in a triangulated surface is normal if it intersects any triangle in a finite set of arcs, each crossing from one edge of the triangle to another. A normal curve is a finite set of disjoint normal paths and normal cycles. We describe an algorithm to “trace” a normal curve in $O(\min \{ X, n^2\log X \})$ O ( min { X , n 2 log X } ) time, where $n$ n is the complexity of the surface triangulation and $X$ X is the number of times the curve crosses edges of the triangulation. In particular, our algorithm runs in polynomial time even when the number of crossings is exponential in $n$ n . Our tracing algorithm computes a new cellular decomposition of the surface with complexity $O(n)$ O ( n ) ; the traced curve appears in the 1-skeleton of the new decomposition as a set of simple disjoint paths and cycles. We apply our abstract tracing strategy to two different classes of normal curves: abstract curves represented by normal coordinates, which record the number of intersections with each edge of the surface triangulation, and simple geodesics, represented by a starting point and direction in the local coordinate system of some triangle. Our normal-coordinate algorithms are competitive with and conceptually simpler than earlier algorithms by Schaefer et al. (Proceedings of 8th International Conference Computing and Combinatorics. Lecture Notes in Computer Science, vol. 2387, pp. 370–380. Springer, Berlin 2002; Proceedings of 20th Canadian Conference on Computational Geometry, pp. 111–114, 2008) and by Agol et al. (Trans Am Math Soc 358(9): 3821–3850, 2006).     

On multiplicative functions which are small on average

Let f be a completely multiplicative function that assumes values inside the unit disc. We show that if ${\sum_{n \leq x}f(n)\ll x/(\rm log x)^A}$ ∑ n ≤ x f ( n ) ? x / ( l o g x ) A , ${x \geq 2}$ x ≥ 2 , for some A > 2, then either f(p) is small on average or f pretends to be ${\mu(n)n^{it}}$ μ ( n ) n i t for some t.     

Size of Components of a Cube Coloring

Suppose a d-dimensional lattice cube of size $n^d$ n d is colored in several colors so that no face of its triangulation (subdivision of the standard partition into $n^d$ n d small cubes) is colored in $m+2$ m + 2 colors. Then one color is used at least $f(d, m) n^{d-m}$ f ( d , m ) n d ? m times.     

Boundaries of Disk-Like Self-affine Tiles

Let $T:= T(A, \mathcal{D })$ T : = T ( A , D ) be a disk-like self-affine tile generated by an integral expanding matrix $A$ A and a consecutive collinear digit set $\mathcal{D }$ D , and let $f(x)=x^{2}+px+q$ f ( x ) = x 2 + px + q be the characteristic polynomial of $A$ A . In the paper, we identify the boundary $\partial T$ ? T with a sofic system by constructing a neighbor graph and derive equivalent conditions for the pair $(A,\mathcal{D })$ ( A , D ) to be a number system. Moreover, by using the graph-directed construction and a device of pseudo-norm $\omega $ ω , we find the generalized Hausdorff dimension $\dim _H^{\omega } (\partial T)=2\log \rho (M)/\log |q|$ dim H ω ( ? T ) = 2 log ρ ( M ) / log | q | where $\rho (M)$ ρ ( M ) is the spectral radius of certain contact matrix $M$ M . Especially, when $A$ A is a similarity, we obtain the standard Hausdorff dimension $\dim _H (\partial T)=2\log \rho /\log |q|$ dim H ( ? T ) = 2 log ρ / log | q | where $\rho $ ρ is the largest positive zero of the cubic polynomial $x^{3}-(|p|-1)x^{2}-(|q|-|p|)x-|q|$ x 3 ? ( | p | ? 1 ) x 2 ? ( | q | ? | p | ) x ? | q | , which is simpler than the known result.     

Primal-dual interior-point algorithm for semidefinite optimization based on a new kernel function with trigonometric barrier term

In this paper we propose primal-dual interior-point algorithms for semidefinite optimization problems based on a new kernel function with a trigonometric barrier term. We show that the iteration bounds are $O(\sqrt{n}\log(\frac{n}{\epsilon}))$ for small-update methods and $O(n^{\frac{3}{4}}\log(\frac{n}{\epsilon}))$ for large-update, respectively. The resulting bound is better than the classical kernel function. For small-update, the iteration complexity is the best known bound for such methods.     

Dimension Reduction for Finite Trees in \varvec{\ell _1}

We show that every $n$ -point tree metric admits a $(1+\varepsilon )$ -embedding into $\ell _1^{C(\varepsilon ) \log n}$ , for every $\varepsilon > 0$ , where $C(\varepsilon ) \le O\big ((\frac{1}{\varepsilon })^4 \log \frac{1}{\varepsilon })\big )$ . This matches the natural volume lower bound up to a factor depending only on $\varepsilon $ . Previously, it was unknown whether even complete binary trees on $n$ nodes could be embedded in $\ell _1^{O(\log n)}$ with $O(1)$ distortion. For complete $d$ -ary trees, our construction achieves $C(\varepsilon ) \le O\big (\frac{1}{\varepsilon ^2}\big )$ .     

Linear-Size Approximations to the Vietoris–Rips Filtration

The Vietoris–Rips filtration is a versatile tool in topological data analysis. It is a sequence of simplicial complexes built on a metric space to add topological structure to an otherwise disconnected set of points. It is widely used because it encodes useful information about the topology of the underlying metric space. This information is often extracted from its so-called persistence diagram. Unfortunately, this filtration is often too large to construct in full. We show how to construct an $O(n)$ O ( n ) -size filtered simplicial complex on an $n$ n -point metric space such that its persistence diagram is a good approximation to that of the Vietoris–Rips filtration. This new filtration can be constructed in $O(n\log n)$ O ( n log n ) time. The constant factors in both the size and the running time depend only on the doubling dimension of the metric space and the desired tightness of the approximation. For the first time, this makes it computationally tractable to approximate the persistence diagram of the Vietoris–Rips filtration across all scales for large data sets. We describe two different sparse filtrations. The first is a zigzag filtration that removes points as the scale increases. The second is a (non-zigzag) filtration that yields the same persistence diagram. Both methods are based on a hierarchical net-tree and yield the same guarantees.     

Approximating Tverberg Points in Linear Time for Any Fixed Dimension

Let $P \subseteq \mathbb{R }^d$ P ? R d be a $d$ d -dimensional $n$ n -point set. A Tverberg partition is a partition of $P$ P into $r$ r sets $P_1, \dots , P_r$ P 1 , ? , P r such that the convex hulls $\hbox {conv}(P_1), \dots , \hbox {conv}(P_r)$ conv ( P 1 ) , ? , conv ( P r ) have non-empty intersection. A point in $\bigcap _{i=1}^{r} \hbox {conv}(P_i)$ ? i = 1 r conv ( P i ) is called a Tverberg point of depth $r$ r for $P$ P . A classic result by Tverberg shows that there always exists a Tverberg partition of size $\lceil n/(d+1) \rceil $ ? n / ( d + 1 ) ? , but it is not known how to find such a partition in polynomial time. Therefore, approximate solutions are of interest. We describe a deterministic algorithm that finds a Tverberg partition of size $\lceil n/4(d+1)^3 \rceil $ ? n / 4 ( d + 1 ) 3 ? in time $d^{O(\log d)} n$ d O ( log d ) n . This means that for every fixed dimension we can compute an approximate Tverberg point (and hence also an approximate centerpoint) in linear time. Our algorithm is obtained by combining a novel lifting approach with a recent result by Miller and Sheehy (Comput Geom Theory Appl 43(8):647–654, 2010).     

On the fast Khintchine spectrum in continued fractions

For $x\in [0,1)$ x ∈ [ 0 , 1 ) , let $x=[a_1(x), a_2(x),\ldots ]$ x = [ a 1 ( x ) , a 2 ( x ) , ... ] be its continued fraction expansion with partial quotients $\{a_n(x), n\ge 1\}$ { a n ( x ) , n ≥ 1 } . Let $\psi : \mathbb{N } \rightarrow \mathbb{N }$ ψ : N → N be a function with $\psi (n)/n\rightarrow \infty $ ψ ( n ) / n → ∞ as $n\rightarrow \infty $ n → ∞ . In this note, the fast Khintchine spectrum, i.e., the Hausdorff dimension of the set $$\begin{aligned} E(\psi ):=\left\{ x\in [0,1): \lim _{n\rightarrow \infty }\frac{1}{\psi (n)}\sum _{j=1}^n\log a_j(x)=1\right\} \end{aligned}$$ E ( ψ ) : = x ∈ [ 0 , 1 ) : lim n → ∞ 1 ψ ( n ) ∑ j = 1 n log a j ( x ) = 1 is completely determined without any extra condition on $\psi $ ψ . This fills a gap of the former work in Fan et al. (Ergod Theor Dyn Syst 29:73–109, 2009).     

The 2-Page Crossing Number of K_{n}

Around 1958, Hill described how to draw the complete graph $K_n$ K n with $$\begin{aligned} Z(n) :=\frac{1}{4}\Big \lfloor \frac{n}{2}\Big \rfloor \Big \lfloor \frac{n-1}{2}\Big \rfloor \Big \lfloor \frac{n-2}{2}\Big \rfloor \Big \lfloor \frac{n-3}{2}\Big \rfloor \end{aligned}$$ Z ( n ) : = 1 4 ? n 2 ? ? n ? 1 2 ? ? n ? 2 2 ? ? n ? 3 2 ? crossings, and conjectured that the crossing number ${{\mathrm{cr}}}(K_{n})$ cr ( K n ) of $K_n$ K n is exactly $Z(n)$ Z ( n ) . This is also known as Guy’s conjecture as he later popularized it. Towards the end of the century, substantially different drawings of $K_{n}$ K n with $Z(n)$ Z ( n ) crossings were found. These drawings are 2-page book drawings, that is, drawings where all the vertices are on a line $\ell $ ? (the spine) and each edge is fully contained in one of the two half-planes (pages) defined by  $\ell $ ? . The 2-page crossing number of $K_{n} $ K n , denoted by $\nu _{2}(K_{n})$ ν 2 ( K n ) , is the minimum number of crossings determined by a 2-page book drawing of $K_{n}$ K n . Since ${{\mathrm{cr}}}(K_{n}) \le \nu _{2}(K_{n})$ cr ( K n ) ≤ ν 2 ( K n ) and $\nu _{2}(K_{n}) \le Z(n)$ ν 2 ( K n ) ≤ Z ( n ) , a natural step towards Hill’s Conjecture is the weaker conjecture $\nu _{2}(K_{n}) = Z(n)$ ν 2 ( K n ) = Z ( n ) , popularized by Vrt’o. In this paper we develop a new technique to investigate crossings in drawings of $K_{n}$ K n , and use it to prove that $\nu _{2}(K_{n}) = Z(n) $ ν 2 ( K n ) = Z ( n ) . To this end, we extend the inherent geometric definition of $k$ k -edges for finite sets of points in the plane to topological drawings of $K_{n}$ K n . We also introduce the concept of ${\le }{\le }k$ ≤ ≤ k -edges as a useful generalization of ${\le }k$ ≤ k -edges and extend a powerful theorem that expresses the number of crossings in a rectilinear drawing of $K_{n}$ K n in terms of its number of ${\le }k$ ≤ k -edges to the topological setting. Finally, we give a complete characterization of crossing minimal 2-page book drawings of $K_{n}$ K n and show that, up to equivalence, they are unique for $n$ n even, but that there exist an exponential number of non homeomorphic such drawings for $n$ n odd.     

On Sub-determinants and the Diameter of Polyhedra

We derive a new upper bound on the diameter of a polyhedron \(P = \{x {\in } {\mathbb {R}}^n :Ax\le b\}\) , where \(A \in {\mathbb {Z}}^{m\times n}\) . The bound is polynomial in \(n\) and the largest absolute value of a sub-determinant of \(A\) , denoted by \(\Delta \) . More precisely, we show that the diameter of \(P\) is bounded by \(O(\Delta ^2 n^4\log n\Delta )\) . If \(P\) is bounded, then we show that the diameter of \(P\) is at most \(O(\Delta ^2 n^{3.5}\log n\Delta )\) . For the special case in which \(A\) is a totally unimodular matrix, the bounds are \(O(n^4\log n)\) and \(O(n^{3.5}\log n)\) respectively. This improves over the previous best bound of \(O(m^{16}n^3(\log mn)^3)\) due to Dyer and Frieze (Math Program 64:1–16, 1994).     

A modified Brent’s method for finding zeros of functions

Brent’s method, also known as zeroin, has been the most popular method for finding zeros of functions since it was developed in 1972. This method usually converges very quickly to a zero; for the occasional difficult functions encountered in practice, it typically takes $O(n)$ iterations to converge, where $n$ is the number of steps required for the bisection method to find the zero to approximately the same accuracy. While it has long been known that in theory Brent’s method could require as many as $O(n^2)$ iterations to find a zero, such behavior had never been observed in practice. In this paper, we first show that Brent’s method can indeed take $O(n^2)$ iterations to converge, by explicitly constructing such worst case functions. In particular, for double precision accuracy, Brent’s method takes $2{,}914$ iterations to find the zero of our function, compared to the $77$ iterations required by bisection. Secondly, we present a modification of Brent’s method that places a stricter complexity bound of $O(n)$ on the search for a zero. In our extensive testing, this modification appears to behave very similarly to Brent’s method for all the common functions, yet it remains at worst five times slower than the bisection method for all difficult functions, in sharp contrast to Brent’s method.     

Tilings of Parallelograms with Similar Right Triangles

We say that a triangle $T$ T tiles the polygon $\mathcal A $ A if $\mathcal A $ A can be decomposed into finitely many non-overlapping triangles similar to $T$ T . A tiling is called regular if there are two angles of the triangles, say $\alpha $ α and $\beta $ β , such that at each vertex $V$ V of the tiling the number of triangles having $V$ V as a vertex and having angle $\alpha $ α at $V$ V is the same as the number of triangles having angle $\beta $ β at $V$ V . Otherwise the tiling is called irregular. Let $\mathcal P (\delta )$ P ( δ ) be a parallelogram with acute angle $\delta $ δ . In this paper we prove that if the parallelogram $\mathcal P (\delta )$ P ( δ ) is tiled with similar triangles of angles $(\alpha , \beta , \pi /2)$ ( α , β , π / 2 ) , then $(\alpha , \beta )=(\delta , \pi /2-\delta )$ ( α , β ) = ( δ , π / 2 - δ ) or $(\alpha , \beta )=(\delta /2, \pi /2-\delta /2)$ ( α , β ) = ( δ / 2 , π / 2 - δ / 2 ) , and if the tiling is regular, then only the first case can occur.     

A Deterministic O(m \log {m}) Time Algorithm for the Reeb Graph

We present a deterministic algorithm to compute the Reeb graph of a PL real-valued function on a simplicial complex in $O(m \log {m})$ O ( m log m ) time, where $m$ m is the size of the 2-skeleton. The problem can be solved using dynamic graph connectivity. We obtain the running time by using offline graph connectivity which assumes that the deletion time of every arc inserted is known at the time of insertion. The algorithm is implemented and experimental results are given. In addition, we reduce the offline graph connectivity problem to computing the Reeb graph.