On the Smallest Degrees of Projective Representations of the Groups PSL(n, q)

1971 ◽  
Vol 23 (1) ◽  
pp. 90-102 ◽  
Author(s):  
Morton E. Harris ◽  
Christoph Hering
Keyword(s):  
Lower Bound ◽  
Higher Order ◽  
Projective Representation ◽  
Minimal Degree ◽  
Prime Integer ◽  
Order Of Magnitude ◽  
Projective Representations

In this paper, we obtain information about the minimal degree δ of any non-trivial projective representation of the group PSL(n, q) with n ≧ 2 over an arbitrary given field K. Our main results for the groups PSL(n, q) (Theorems 4.2, 4.3, and 4.4) state that, apart from certain exceptional cases with small n, we have the following rather surprising situation: if q = pf (where p is a prime integer) and char K = p, then δ = n, but if q = pf and char K ≠ p, then δ is of a considerably higher order of magnitude, namely, δ is at least qn–l – 1 or if n = 2 and q is odd. Note that for n = 2, this lower bound for δ is the best possible. However, for n ≧ 3, this lower bound can conceivably be improved.

scholarly journals Projective representations of quivers

2002 ◽  
Vol 31 (2) ◽  
pp. 97-101 ◽  
Author(s):  
Sangwon Park
Keyword(s):  
Projective Representation ◽  
Representations Of Quivers ◽  
Direct Sum ◽  
Projective Representations

We prove thatP1 →f P2is a projective representation of a quiverQ=•→•if and only ifP1andP2are projective leftR-modules,fis an injection, andf (P 1)⊂P 2is a summand. Then, we generalize the result so that a representationM1 →f1  M2  →f2⋯→fn−2  Mn−1→fn−1  Mnof a quiverQ=•→•→•⋯•→•→•is projective representation if and only if eachMiis a projective leftR-module and the representation is a direct sum of projective representations.

Efficient and High-Quality Seeded Graph Matching: Employing Higher-order Structural Information

2021 ◽  
Vol 15 (3) ◽  
pp. 1-31
Author(s):  
Haida Zhang ◽  
Zengfeng Huang ◽  
Xuemin Lin ◽  
Zhe Lin ◽  
Wenjie Zhang ◽  
...  
Keyword(s):  
Large Scale ◽  
Graph Matching ◽  
Structural Information ◽  
Experimental Studies ◽  
Higher Order ◽  
Personalized Pagerank ◽  
Matching Accuracy ◽  
Approximation Techniques ◽  
Order Of Magnitude ◽  
Matching Score

Driven by many real applications, we study the problem of seeded graph matching. Given two graphs and , and a small set of pre-matched node pairs where and , the problem is to identify a matching between and growing from , such that each pair in the matching corresponds to the same underlying entity. Recent studies on efficient and effective seeded graph matching have drawn a great deal of attention and many popular methods are largely based on exploring the similarity between local structures to identify matching pairs. While these recent techniques work provably well on random graphs, their accuracy is low over many real networks. In this work, we propose to utilize higher-order neighboring information to improve the matching accuracy and efficiency. As a result, a new framework of seeded graph matching is proposed, which employs Personalized PageRank (PPR) to quantify the matching score of each node pair. To further boost the matching accuracy, we propose a novel postponing strategy, which postpones the selection of pairs that have competitors with similar matching scores. We show that the postpone strategy indeed significantly improves the matching accuracy. To improve the scalability of matching large graphs, we also propose efficient approximation techniques based on algorithms for computing PPR heavy hitters. Our comprehensive experimental studies on large-scale real datasets demonstrate that, compared with state-of-the-art approaches, our framework not only increases the precision and recall both by a significant margin but also achieves speed-up up to more than one order of magnitude.

scholarly journals EIGENVALUE ESTIMATES FOR HIGHER ORDER ELLIPTIC EQUATIONS

1994 ◽  
Vol 25 (3) ◽  
pp. 267-278
Author(s):  
HSU-TUNG KU ◽  
MEI-CHIN KU ◽  
XIN-MIN ZHANG
Keyword(s):  
Lower Bound ◽  
Elliptic Equations ◽  
Eigenvalue Problems ◽  
Higher Order ◽  
Bounded Domains ◽  
Dirichlet Eigenvalue ◽  
Eigenvalue Estimates

In this paper, we obtain good lower bound estimates of eigenvalues for various Dirichlet eigenvalue problems of higher order elliptic equations on bounded domains in $\mathbb{R}^n$.

scholarly journals A Unifying View on Individual Bounds and Heuristic Inaccuracies in Bidirectional Search

2020 ◽  
Vol 34 (03) ◽  
pp. 2327-2334
Author(s):  
Vidal Alcázar ◽  
Pat Riddle ◽  
Mike Barley
Keyword(s):  
Lower Bound ◽  
Heuristic Search ◽  
Search Algorithm ◽  
Substantial Improvement ◽  
Full Potential ◽  
The Past ◽  
Heuristic Search Algorithms ◽  
Bidirectional Search ◽  
Order Of Magnitude ◽  
The Cost

In the past few years, new very successful bidirectional heuristic search algorithms have been proposed. Their key novelty is a lower bound on the cost of a solution that includes information from the g values in both directions. Kaindl and Kainz (1997) proposed measuring how inaccurate a heuristic is while expanding nodes in the opposite direction, and using this information to raise the f value of the evaluated nodes. However, this comes with a set of disadvantages and remains yet to be exploited to its full potential. Additionally, Sadhukhan (2013) presented BAE∗, a bidirectional best-first search algorithm based on the accumulated heuristic inaccuracy along a path. However, no complete comparison in regards to other bidirectional algorithms has yet been done, neither theoretical nor empirical. In this paper we define individual bounds within the lower-bound framework and show how both Kaindl and Kainz's and Sadhukhan's methods can be generalized thus creating new bounds. This overcomes previous shortcomings and allows newer algorithms to benefit from these techniques as well. Experimental results show a substantial improvement, up to an order of magnitude in the number of necessarily-expanded nodes compared to state-of-the-art near-optimal algorithms in common benchmarks.

scholarly journals New Bounds for the α-Indices of Graphs

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1668
Author(s):  
Eber Lenes ◽  
Exequiel Mallea-Zepeda ◽  
Jonnathan Rodríguez
Keyword(s):  
Lower Bound ◽  
Spectral Radius ◽  
Upper Bound ◽  
Adjacency Matrix ◽  
Independence Number ◽  
Minimal Degree ◽  
Diagonal Matrix ◽  
The Matrix

Let G be a graph, for any real 0≤α≤1, Nikiforov defines the matrix Aα(G) as Aα(G)=αD(G)+(1−α)A(G), where A(G) and D(G) are the adjacency matrix and diagonal matrix of degrees of the vertices of G. This paper presents some extremal results about the spectral radius ρα(G) of the matrix Aα(G). In particular, we give a lower bound on the spectral radius ρα(G) in terms of order and independence number. In addition, we obtain an upper bound for the spectral radius ρα(G) in terms of order and minimal degree. Furthermore, for n>l>0 and 1≤p≤⌊n−l2⌋, let Gp≅Kl∨(Kp∪Kn−p−l) be the graph obtained from the graphs Kl and Kp∪Kn−p−l and edges connecting each vertex of Kl with every vertex of Kp∪Kn−p−l. We prove that ρα(Gp+1)<ρα(Gp) for 1≤p≤⌊n−l2⌋−1.

scholarly journals Sums of smooth squares

2009 ◽  
Vol 145 (6) ◽  
pp. 1401-1441 ◽  
Author(s):  
V. Blomer ◽  
J. Brüdern ◽  
R. Dietmann
Keyword(s):  
Lower Bound ◽  
Asymptotic Formula ◽  
Natural Number ◽  
Related Problem ◽  
Order Of Magnitude ◽  
Sums Of Three Squares

AbstractLet R(n,θ) denote the number of representations of the natural number n as the sum of four squares, each composed only with primes not exceeding nθ/2. When θ>e−1/3 a lower bound for R(n,θ) of the expected order of magnitude is established, and when θ>365/592, it is shown that R(n,θ)>0 holds for large n. A similar result is obtained for sums of three squares. An asymptotic formula is obtained for the related problem of representing an integer as the sum of two squares and two squares composed of small primes, as above, for any fixed θ>0. This last result is the key to bound R(n,θ) from below.

scholarly journals Different Effects of Cisplatin and Transplatin on the Higher-Order Structure of DNA and Gene Expression

2019 ◽  
Vol 21 (1) ◽  
pp. 34 ◽  
Author(s):  
Toshifumi Kishimoto ◽  
Yuko Yoshikawa ◽  
Kenichi Yoshikawa ◽  
Seiji Komeda
Keyword(s):  
Gene Expression ◽  
Nuclear Dna ◽  
Biological Effects ◽  
Inhibitory Effect ◽  
Higher Order ◽  
Luciferase Assay ◽  
Order Structure ◽  
Force Microscopy ◽  
Order Of Magnitude

Despite the effectiveness of cisplatin as an anticancer agent, its trans-isomer, transplatin, is clinically ineffective. Although both isomers target nuclear DNA, there is a large difference in the magnitude of their biological effects. Here, we compared their effects on gene expression in an in vitro luciferase assay and quantified their effects on the higher-order structure of DNA using fluorescence microscopy (FM) and atomic force microscopy (AFM). The inhibitory effect of cisplatin on gene expression was about 7 times that of transplatin. Analysis of the fluctuation autocorrelation function of the intrachain Brownian motion of individual DNA molecules showed that cisplatin increases the spring and damping constants of DNA by one order of magnitude and these visco-elastic characteristics tend to increase gradually over several hours. Transplatin had a weaker effect, which tended to decrease with time. These results agree with a stronger inhibitory effect of cisplatin on gene expression. We discussed the characteristic effects of the two compounds on the higher-order DNA structure and gene expression in terms of the differences in their binding to DNA.

scholarly journals Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions

2019 ◽  
Vol 33 ◽  
pp. 4488-4495 ◽  
Author(s):  
Simon Luo ◽  
Mahito Sugiyama
Keyword(s):  
Probabilistic Models ◽  
Classical Problem ◽  
Higher Order ◽  
Boltzmann Machine ◽  
Trade Off ◽  
Feature Interactions ◽  
Order Of Magnitude ◽  
Bias Variance ◽  
Log Linear ◽  
High Representation

Hierarchical probabilistic models are able to use a large number of parameters to create a model with a high representation power. However, it is well known that increasing the number of parameters also increases the complexity of the model which leads to a bias-variance trade-off. Although it is a classical problem, the bias-variance trade-off between hiddenlayers and higher-order interactions have not been well studied. In our study, we propose an efficient inference algorithm for the log-linear formulation of the higher-order Boltzmann machine using a combination of Gibbs sampling and annealed importance sampling. We then perform a bias-variance decomposition to study the differences in hidden layers and higher-order interactions. Our results have shown that using hidden layers and higher-order interactions have a comparable error with a similar order of magnitude and using higherorder interactions produce less variance for smaller sample size.

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