Scalable Text and Link Analysis with Mixed-Topic Link Models

Many data sets contain rich information about objects, as well as pairwise relations between them. For instance, in networks of websites, scientific papers, and other documents, each node has content consisting of a collection of words, as well as hyperlinks or citations to other nodes. In order to perform inference on such data sets, and make predictions and recommendations, it is useful to have models that are able to capture the processes which generate the text at each node and the links between them. In this paper, we combine classic ideas in topic modeling with a variant of the mixed-membership block model recently developed in the statistical physics community. The resulting model has the advantage that its parameters, including the mixture of topics of each document and the resulting overlapping communities, can be inferred with a simple and scalable expectation-maximization algorithm. We test our model on three data sets, performing unsupervised topic classification and link prediction. For both tasks, our model outperforms several existing state-of-the-art methods, achieving higher accuracy with significantly less computation, analyzing a data set with 1.3 million words and 44 thousand links in a few minutes.Comment: 11 pages, 4 figure

The complexity of dominating set reconfiguration

Suppose that we are given two dominating sets $D_s$ and $D_t$ of a graph $G$ whose cardinalities are at most a given threshold $k$. Then, we are asked whether there exists a sequence of dominating sets of $G$ between $D_s$ and $D_t$ such that each dominating set in the sequence is of cardinality at most $k$ and can be obtained from the previous one by either adding or deleting exactly one vertex. This problem is known to be PSPACE-complete in general. In this paper, we study the complexity of this decision problem from the viewpoint of graph classes. We first prove that the problem remains PSPACE-complete even for planar graphs, bounded bandwidth graphs, split graphs, and bipartite graphs. We then give a general scheme to construct linear-time algorithms and show that the problem can be solved in linear time for cographs, trees, and interval graphs. Furthermore, for these tractable cases, we can obtain a desired sequence such that the number of additions and deletions is bounded by $O(n)$, where $n$ is the number of vertices in the input graph

Single hole dynamics in dimerized spin liquids

The dynamics of a single hole in quantum antiferromagnets is influenced by magnetic fluctuations. In the present work we consider two situations. The first one corresponds to a single hole in the two leg t-J spin ladder. In this case the wave function renormalization is relatively small and the quasiparticle residue of the S=1/2 state remains close to unity. However at large t/J there are higher spin (S=3/2,5/2,..) bound states of the hole with the magnetic excitations, and therefore there is a crossover from quasiparticles with S=1/2 to quasiparticles with higher spin. The second situation corresponds to a single hole in two coupled antiferromagnetic planes very close to the point of antiferromagnetic instability. In this case the hole wave function renormalization is very strong and the quasiparticle residue vanishes at the point of instability.Comment: 12 pages, 3 figure

Optical characterisation of germanium optical fibres

Semiconductor core optical fibres are currently generating great interest as they promise to be a platform for the seamless incorporation of optoelectronic functionality into a new generation of all-fibre networks [1,2]. Although recent attentions have primarily focused on silicon as the material of choice for semiconductor photonics applications, germanium has some advantages over its counterpart. For example, it has higher nonlinearity, extended infrared transparency and has recently been demonstrated as a direct band gap laser medium [3]. Here we present the first optical characterisation of a germanium core optical fibre. The fibre was fabricated using a chemical micro fluidic deposition process [1] that uses GeH4 (germane) as a precursor to deposit amorphous germanium into the hole of a silica capillary. Figure 1 (a) shows an optical microscope image of the polished end face of a germanium fibre, with a 5.6 µm core diameter, which has been completely filled with the semiconductor material. Optical transmission measurements have been conducted over the wavelength range 2 µm to 11 µm, to confirm the broad mid-infrared operational window, and the guided output at 2.4 µm, imaged using a Spiricon Pyrocam III pyroelectric array camera, is shown in Figure 1 (b). At this wavelength the optical loss has been measured to be 20 dB/cm, which is comparable to losses measured for amorphous silicon fibres in the infrared. The potential for these germanium optical fibres to be used as optical modulators and infrared detectors will be discussed

Reconfiguration on sparse graphs

A vertex-subset graph problem Q defines which subsets of the vertices of an input graph are feasible solutions. A reconfiguration variant of a vertex-subset problem asks, given two feasible solutions S and T of size k, whether it is possible to transform S into T by a sequence of vertex additions and deletions such that each intermediate set is also a feasible solution of size bounded by k. We study reconfiguration variants of two classical vertex-subset problems, namely Independent Set and Dominating Set. We denote the former by ISR and the latter by DSR. Both ISR and DSR are PSPACE-complete on graphs of bounded bandwidth and W[1]-hard parameterized by k on general graphs. We show that ISR is fixed-parameter tractable parameterized by k when the input graph is of bounded degeneracy or nowhere-dense. As a corollary, we answer positively an open question concerning the parameterized complexity of the problem on graphs of bounded treewidth. Moreover, our techniques generalize recent results showing that ISR is fixed-parameter tractable on planar graphs and graphs of bounded degree. For DSR, we show the problem fixed-parameter tractable parameterized by k when the input graph does not contain large bicliques, a class of graphs which includes graphs of bounded degeneracy and nowhere-dense graphs

Reconfiguring Independent Sets in Claw-Free Graphs

We present a polynomial-time algorithm that, given two independent sets in a claw-free graph $G$, decides whether one can be transformed into the other by a sequence of elementary steps. Each elementary step is to remove a vertex $v$ from the current independent set $S$ and to add a new vertex $w$ (not in $S$) such that the result is again an independent set. We also consider the more restricted model where $v$ and $w$ have to be adjacent

Spin-ladders with spin gaps: A description of a class of cuprates

We investigate the magnetic properties of the Cu-O planes in stoichiometric Sr$_{n-1}$Cu$_{n+1}$O$_{2n}$ (n=3,5,7,...) which consist of CuO double chains periodically intergrown within the CuO$_2$ planes. The double chains break up the two-dimensional antiferromagnetic planes into Heisenberg spin ladders with $n_r=\frac{1}{2}(n-1)$ rungs and $n_l=\frac{1}{2}(n+1)$ legs and described by the usual antiferromagnetic coupling J inside each ladder and a weak and frustrated interladder coupling J$^\prime$. The resulting lattice is a new two-dimensional trellis lattice. We first examine the spin excitation spectra of isolated quasi one dimensional Heisenberg ladders which exhibit a gapless spectra when $n_r$ is even and $n_l$ is odd ( corresponding to n=5,9,...) and a gapped spectra when $n_r$ is odd and $n_l$ is even (corresponding to n=3,7,...). We use the bond operator representation of quantum $S=\frac{1}{2}$ spins in a mean field treatment with self-energy corrections and obtain a spin gap of $\approx \frac{1}{2} J$ for the simplest single rung ladder (n=3), in agreement with numerical estimates.Comment: 21 pages, 5 figures upon request, REVTEX, ETH-TH/93-3

Latent Space Model for Multi-Modal Social Data

With the emergence of social networking services, researchers enjoy the increasing availability of large-scale heterogenous datasets capturing online user interactions and behaviors. Traditional analysis of techno-social systems data has focused mainly on describing either the dynamics of social interactions, or the attributes and behaviors of the users. However, overwhelming empirical evidence suggests that the two dimensions affect one another, and therefore they should be jointly modeled and analyzed in a multi-modal framework. The benefits of such an approach include the ability to build better predictive models, leveraging social network information as well as user behavioral signals. To this purpose, here we propose the Constrained Latent Space Model (CLSM), a generalized framework that combines Mixed Membership Stochastic Blockmodels (MMSB) and Latent Dirichlet Allocation (LDA) incorporating a constraint that forces the latent space to concurrently describe the multiple data modalities. We derive an efficient inference algorithm based on Variational Expectation Maximization that has a computational cost linear in the size of the network, thus making it feasible to analyze massive social datasets. We validate the proposed framework on two problems: prediction of social interactions from user attributes and behaviors, and behavior prediction exploiting network information. We perform experiments with a variety of multi-modal social systems, spanning location-based social networks (Gowalla), social media services (Instagram, Orkut), e-commerce and review sites (Amazon, Ciao), and finally citation networks (Cora). The results indicate significant improvement in prediction accuracy over state of the art methods, and demonstrate the flexibility of the proposed approach for addressing a variety of different learning problems commonly occurring with multi-modal social data.Comment: 12 pages, 7 figures, 2 table

Magnetic Phase Transitions in the double spin-chains compound LiCu2O2\rm LiCu_2O_2

We report high-resolution x-ray diffraction, muon-spin-rotation spectroscopic and specific heat measurements in the double spin-chains compound $\rm LiCu_2O_2$. The x-ray diffraction results show that the crystal structure of $\rm LiCu_2O_2$ ~is orthorhombic down to T=10K. Anisotropic line-broadening of the diffraction peaks is observed, indicating disorder along the spin chains. Muon spin relaxation and specific heat measurements show that $\rm LiCu_2O_2$ \~undergoes a phase transition to a magnetic ordered state at $\rm T_1\sim24K$. The specific heat data exhibits a second $\rm \lambda$-like peak at $\rm T_2\sim22.5 K$, which increases with increasing magnetic field similarly way to that found in spin-ladder compounds.Comment: 6 pages, 6 fifures, to appear in Physica