Higher order and infinite Trotter-number extrapolations in path integral Monte Carlo

Improvements beyond the primitive approximation in the path integral Monte Carlo method are explored both in a model problem and in real systems. Two different strategies are studied: the Richardson extrapolation on top of the path integral Monte Carlo data and the Takahashi-Imada action. The Richardson extrapolation, mainly combined with the primitive action, always reduces the number-of-beads dependence, helps in determining the approach to the dominant power law behavior, and all without additional computational cost. The Takahashi-Imada action has been tested in two hard-core interacting quantum liquids at low temperature. The results obtained show that the fourth-order behavior near the asymptote is conserved, and that the use of this improved action reduces the computing time with respect to the primitive approximation.Comment: 19 pages, RevTex, to appear in J. Chem. Phy

Equation of state of an interacting Bose gas at finite temperature: a Path Integral Monte Carlo study

By using exact Path Integral Monte Carlo methods we calculate the equation of state of an interacting Bose gas as a function of temperature both below and above the superfluid transition. The universal character of the equation of state for dilute systems and low temperatures is investigated by modeling the interatomic interactions using different repulsive potentials corresponding to the same s-wave scattering length. The results obtained for the energy and the pressure are compared to the virial expansion for temperatures larger than the critical temperature. At very low temperatures we find agreement with the ground-state energy calculated using the diffusion Monte Carlo method.Comment: 7 pages, 6 figure

Identification of Abnormal Movements in Infants: A Deep Neural Network for Body Part-Based Prediction of Cerebral Palsy

The early diagnosis of cerebral palsy is an area which has recently seen significant multi-disciplinary research. Diagnostic tools such as the General Movements Assessment (GMA), have produced some very promising results, however these manual methods can be laborious. The prospect of automating these processes is seen as key in advancing this field of study. In our previous works, we examined the viability of using pose-based features extracted from RGB video sequences to undertake classification of infant body movements based upon the GMA. In this paper, we propose a new deep learning framework for this classification task. We also propose a visualization framework which identifies body-parts with the greatest contribution towards a classification decision. The inclusion of a visualization framework is an important step towards automation as it helps make the decisions made by the machine learning framework interpretable. We directly compare the proposed framework's classification with several other methods from the literature using two independent datasets. Our experimental results show that the proposed method performs more consistently and more robustly than our previous pose-based techniques as well as other features from related works in this setting. We also find that our visualization framework helps provide greater interpretability, enhancing the likelihood of the adoption of these technologies within the medical domain

Towards Explainable Abnormal Infant Movements Identification: A Body-part Based Prediction and Visualisation Framework

Providing early diagnosis of cerebral palsy (CP) is key to enhancing the developmental outcomes for those affected. Diagnostic tools such as the General Movements Assessment (GMA), have produced promising results in early diagnosis, however these manual methods can be laborious. In this paper, we propose a new framework for the automated classification of infant body movements, based upon the GMA, which unlike previous methods, also incorporates a visualization framework to aid with interpretability. Our proposed framework segments extracted features to detect the presence of Fidgety Movements (FMs) associated with the GMA spatiotemporally. These features are then used to identify the body-parts with the greatest contribution towards a classification decision and highlight the related body-part segment providing visual feedback to the user. We quantitatively compare the proposed framework's classification performance with several other methods from the literature and qualitatively evaluate the visualization's veracity. Our experimental results show that the proposed method performs more robustly than comparable techniques in this setting whilst simultaneously providing relevant visual interpretability

Smartmonitor: Using smart devices to perform structural health monitoring

In this demonstration, we are presenting SmartMonitor, a distributed Structural Health Monitoring (SHM) system consisting of smart devices. Over the last few years, the vast majority of smart devices is equipped with accelerometers that can be utilized towards building SHM systems with hundreds of nodes. We describe a scalable, fault-tolerant communication protocol, that performs best-effort time synchronization of the nodes and is used to implement a decentralized version of the popular peak-picking SHM method. The implemented interactive system can be easily installed in any accelerometer-equipped Android device and the user has a number of options for configuring the system or analyzing the collected data and computed outcomes. © 2013 VLDB Endowment

Language agnostic meme-filtering for hashtag-based social network analysis

Users in social networks utilize hashtags for a variety of reasons. In many cases, hashtags serve retrieval purposes by labeling the content they accompany. More often than not, hashtags are used to promote content, ideas, or conversations producing viral memes. This paper addresses a specific case of hashtag classification: meme-filtering. We argue that hashtags that are correlated with memes may hinder many valuable social media algorithms like trend detection and event identification. We propose and evaluate a set of language-agnostic features that aid the separation of these two classes: meme-hashtags and event-hashtags. The proposed approach is evaluated on two large datasets of Twitter messages written in English and German. A proof-of-concept application of the meme-filtering approach to the problem of event detection is presented. © 2015, Springer-Verlag Wien

Quantum features of a barely bound molecular dopant: Cs2( 3Σu) in bosonic helium droplets of variable size

We present in this work the study of small 4He N-Cs2(3Σu) aggregates (2 ≥ N ≥ 30) through combined variational, diffusion Monte Carlo (DMC), and path integral Monte Carlo (PIMC) calculations. The full surface is modeled as an addition of He-Cs2 interactions and He-He potentials. Given the negligible strength and large range of the He-Cs2 interaction as compared with the one for He-He, a propensity of the helium atoms to pack themselves together, leaving outside the molecular dopant is to be expected. DMC calculations determine the onset of helium gathering at N = 3. To analyze energetic and structural properties as a function of N, PIMC calculations with no bosonic exchange, i.e., Boltzmann statistics, at low temperatures are carried out. At T = 0.1 K, although acceptable one-particle He-Cs2 distributions are obtained, two-particle He-He distributions are not well described, indicating that the proper symmetry should be taken into account. PIMC distributions at T = 1 K already compare well with DMC ones and show minor exchange effects, although binding energies are still far from having converged in terms of the number of quantum beads. As N increases, the He-He PIMC pair correlation function shows a clear tendency to coincide with the experimental boson-liquid helium one at that temperature. It supports the picture of a helium droplet which carries the molecular impurity on its surface, as found earlier for other triplet dimers. © 2011 American Chemical Society.This work has been supported by by DGICYT, Spain, Grant Nos. FIS2007-62006 and FIS2010-18132.Peer Reviewe