AUGUR: Forecasting the Emergence of New Research Topics

Being able to rapidly recognise new research trends is strategic for many stakeholders, including universities, institutional funding bodies, academic publishers and companies. The literature presents several approaches to identifying the emergence of new research topics, which rely on the assumption that the topic is already exhibiting a certain degree of popularity and consistently referred to by a community of researchers. However, detecting the emergence of a new research area at an embryonic stage, i.e., before the topic has been consistently labelled by a community of researchers and associated with a number of publications, is still an open challenge. We address this issue by introducing Augur, a novel approach to the early detection of research topics. Augur analyses the diachronic relationships between research areas and is able to detect clusters of topics that exhibit dynamics correlated with the emergence of new research topics. Here we also present the Advanced Clique Percolation Method (ACPM), a new community detection algorithm developed specifically for supporting this task. Augur was evaluated on a gold standard of 1,408 debutant topics in the 2000-2011 interval and outperformed four alternative approaches in terms of both precision and recall

Black hole hunting in the Andromeda Galaxy

We present a new technique for identifying stellar mass black holes in low mass X-ray binaries (LMXBs), and apply it to XMM-Newton observations of M31. We examine X-ray time series variability seeking power density spectra (PDS) typical of LMXBs accreting at a low accretion rate (which we refer to as Type A PDS); these are very similar for black hole and neutron star LMXBs. Galactic neutron star LMXBs exhibit Type A PDS at low luminosities (~10^36--10^37 erg/s) while black hole LMXBs can exhibit them at luminosities >10^38 erg/s. We propose that Type A PDS are confined to luminosities below a critical fraction of the Eddington limit, $l_c$ that is constant for all LMXBs; we have examined asample of black hole and neutron star LMXBs and find they are all consistent with $l_c$ = 0.10+/-0.04 in the 0.3--10 keV band. We present luminosity and PDS data from 167 observations of X-ray binaries in M31 that provide strong support for our hypothesis. Since the theoretical maximum mass for a neutron star is \~3.1 M_Sun, we therefore assert that any LMXB that exhibits a Type A PDS at a 0.3--10 keV luminosity greater than 4 x 10^37 erg/s is likely to contain a black hole primary. We have found eleven new black hole candidates in M31 using this method. We focus on XMM-Newton observations of RX J0042.4+4112, an X-ray source in M31 and find the mass of the primary to be 7+/-2 M_Sun, if our assumptions are correct. Furthermore, RX J0042.4+4112 is consistently bright in \~40 observations made over 23 years, and is likely to be a persistently bright LMXB; by contrast all known Galactic black hole LMXBs are transient. Hence our method may be used to find black holes in known, persistently bright Galactic LMXBs and also in LMXBs in other galaxies.Comment: 6 Pages, 6 figures. To appear in the conference proceedings of "Interacting Binaries: Accretion, Evolution and Outcomes" (Cefalu, July 4-10 2004

TechMiner: Extracting Technologies from Academic Publications

In recent years we have seen the emergence of a variety of scholarly datasets. Typically these capture ‘standard’ scholarly entities and their connections, such as authors, affiliations, venues, publications, citations, and others. However, as the repositories grow and the technology improves, researchers are adding new entities to these repositories to develop a richer model of the scholarly domain. In this paper, we introduce TechMiner, a new approach, which combines NLP, machine learning and semantic technologies, for mining technologies from research publications and generating an OWL ontology describing their relationships with other research entities. The resulting knowledge base can support a number of tasks, such as: richer semantic search, which can exploit the technology dimension to support better retrieval of publications; richer expert search; monitoring the emergence and impact of new technologies, both within and across scientific fields; studying the scholarly dynamics associated with the emergence of new technologies; and others. TechMiner was evaluated on a manually annotated gold standard and the results indicate that it significantly outperforms alternative NLP approaches and that its semantic features improve performance significantly with respect to both recall and precision

A search for thermal X-ray signatures in Gamma-Ray Bursts I: Swift bursts with optical supernovae

The X-ray spectra of Gamma-Ray Bursts can generally be described by an absorbed power law. The landmark discovery of thermal X-ray emission in addition to the power law in the unusual GRB 060218, followed by a similar discovery in GRB 100316D, showed that during the first thousand seconds after trigger the soft X-ray spectra can be complex. Both the origin and prevalence of such spectral components still evade understanding, particularly after the discovery of thermal X-ray emission in the classical GRB 090618. Possibly most importantly, these three objects are all associated with optical supernovae, begging the question of whether the thermal X-ray components could be a result of the GRB-SN connection, possibly in the shock breakout. We therefore performed a search for blackbody components in the early Swift X-ray spectra of 11 GRBs that have or may have associated optical supernovae, accurately recovering the thermal components reported in the literature for GRBs 060218, 090618 and 100316D. We present the discovery of a cooling blackbody in GRB 101219B/SN2010ma, and in four further GRB-SNe we find an improvement in the fit with a blackbody which we deem possible blackbody candidates due to case-specific caveats. All the possible new blackbody components we report lie at the high end of the luminosity and radius distribution. GRB 101219B appears to bridge the gap between the low-luminosity and the classical GRB-SNe with thermal emission, and following the blackbody evolution we derive an expansion velocity for this source of order 0.4c. We discuss potential origins for the thermal X-ray emission in our sample, including a cocoon model which we find can accommodate the more extreme physical parameters implied by many of our model fits.Comment: 16 pages, 6 figures, accepted for MNRA

State Dependence of Stimulus-Induced Variability Tuning in Macaque MT

Behavioral states marked by varying levels of arousal and attention modulate some properties of cortical responses (e.g. average firing rates or pairwise correlations), yet it is not fully understood what drives these response changes and how they might affect downstream stimulus decoding. Here we show that changes in state modulate the tuning of response variance-to-mean ratios (Fano factors) in a fashion that is neither predicted by a Poisson spiking model nor changes in the mean firing rate, with a substantial effect on stimulus discriminability. We recorded motion-sensitive neurons in middle temporal cortex (MT) in two states: alert fixation and light, opioid anesthesia. Anesthesia tended to lower average spike counts, without decreasing trial-to-trial variability compared to the alert state. Under anesthesia, within-trial fluctuations in excitability were correlated over longer time scales compared to the alert state, creating supra-Poisson Fano factors. In contrast, alert-state MT neurons have higher mean firing rates and largely sub-Poisson variability that is stimulus-dependent and cannot be explained by firing rate differences alone. The absence of such stimulus-induced variability tuning in the anesthetized state suggests different sources of variability between states. A simple model explains state-dependent shifts in the distribution of observed Fano factors via a suppression in the variance of gain fluctuations in the alert state. A population model with stimulus-induced variability tuning and behaviorally constrained information-limiting correlations explores the potential enhancement in stimulus discriminability by the cortical population in the alert state.Comment: 36 pages, 18 figure

Head and Flow Observations on a High- Efficiency Free Centrifugal-Pump Impeller

A series of studies of the flow through the various components of hydrodynamic machinery is in progress in the Hydraulic Machinery Laboratory of the California Institute of Technology. Observations have been made on an impeller patterned after the Grand Coulee design. The impeller was operated as an isolated unit hydraulically free of the casing. The flow pattern at the discharge has been determined quantitatively for one flow rate, and a head-capacity curve for the impeller has been obtained. This paper constitutes a report on the findings up to the present

Freak Waves in Random Oceanic Sea States

Freak waves are very large, rare events in a random ocean wave train. Here we study the numerical generation of freak waves in a random sea state characterized by the JONSWAP power spectrum. We assume, to cubic order in nonlinearity, that the wave dynamics are governed by the nonlinear Schroedinger (NLS) equation. We identify two parameters in the power spectrum that control the nonlinear dynamics: the Phillips parameter $\alpha$ and the enhancement coefficient $\gamma$. We discuss how freak waves in a random sea state are more likely to occur for large values of $\alpha$ and $\gamma$. Our results are supported by extensive numerical simulations of the NLS equation with random initial conditions. Comparison with linear simulations are also reported.Comment: 7 pages, 6 figures, to be published in Phys. Rev. Let

Exploring Interacting Quantum Many-Body Systems by Experimentally Creating Continuous Matrix Product States in Superconducting Circuits

Improving the understanding of strongly correlated quantum many body systems such as gases of interacting atoms or electrons is one of the most important challenges in modern condensed matter physics, materials research and chemistry. Enormous progress has been made in the past decades in developing both classical and quantum approaches to calculate, simulate and experimentally probe the properties of such systems. In this work we use a combination of classical and quantum methods to experimentally explore the properties of an interacting quantum gas by creating experimental realizations of continuous matrix product states - a class of states which has proven extremely powerful as a variational ansatz for numerical simulations. By systematically preparing and probing these states using a circuit quantum electrodynamics (cQED) system we experimentally determine a good approximation to the ground-state wave function of the Lieb-Liniger Hamiltonian, which describes an interacting Bose gas in one dimension. Since the simulated Hamiltonian is encoded in the measurement observable rather than the controlled quantum system, this approach has the potential to apply to exotic models involving multicomponent interacting fields. Our findings also hint at the possibility of experimentally exploring general properties of matrix product states and entanglement theory. The scheme presented here is applicable to a broad range of systems exploiting strong and tunable light-matter interactions.Comment: 11 pages, 9 figure