scholarly journals Loop decay in Abelian-Higgs string networks

2021 ◽  
Vol 104 (4) ◽  
Author(s):  
Mark Hindmarsh ◽  
Joanes Lizarraga ◽  
Ander Urio ◽  
Jon Urrestilla
Keyword(s):  
2021 ◽  
Vol 103 (10) ◽  
Author(s):  
Mark Hindmarsh ◽  
Joanes Lizarraga ◽  
Asier Lopez-Eiguren ◽  
Jon Urrestilla
Keyword(s):  

1998 ◽  
Vol 80 (11) ◽  
pp. 2277-2280 ◽  
Author(s):  
Graham Vincent ◽  
Nuno D. Antunes ◽  
Mark Hindmarsh

2017 ◽  
Author(s):  
Vladimir Gligorijević ◽  
Meet Barot ◽  
Richard Bonneau

AbstractThe prevalence of high-throughput experimental methods has resulted in an abundance of large-scale molecular and functional interaction networks. The connectivity of these networks provide a rich source of information for inferring functional annotations for genes and proteins. An important challenge has been to develop methods for combining these heterogeneous networks to extract useful protein feature representations for function prediction. Most of the existing approaches for network integration use shallow models that cannot capture complex and highly-nonlinear network structures. Thus, we propose deepNF, a network fusion method based on Multimodal Deep Autoencoders to extract high-level features of proteins from multiple heterogeneous interaction networks. We apply this method to combine STRING networks to construct a common low-dimensional representation containing high-level protein features. We use separate layers for different network types in the early stages of the multimodal autoencoder, later connecting all the layers into a single bottleneck layer from which we extract features to predict protein function. We compare the cross-validation and temporal holdout predictive performance of our method with state-of-the-art methods, including the recently proposed method Mashup. Our results show that our method outperforms previous methods for both human and yeast STRING networks. We also show substantial improvement in the performance of our method in predicting GO terms of varying type and specificity.AvailabilitydeepNF is freely available at: https://github.com/VGligorijevic/deepNF


Author(s):  
A. Achúcarro ◽  
A. Avgoustidis ◽  
A. López-Eiguren ◽  
C. J. A. P. Martins ◽  
J. Urrestilla

Semilocal strings—a particular limit of electroweak strings—are an interesting example of a stable non-topological defect whose properties resemble those of their topological cousins, the Abrikosov–Nielsen–Olesen vortices. There is, however, one important difference: a network of semilocal strings will contain segments. These are ‘dumbbells’ whose ends behave almost like global monopoles that are strongly attracted to one another. While closed loops of string will eventually shrink and disappear, the segments can either shrink or grow, and a cosmological network of semilocal strings will reach a scaling regime. We discuss attempts to find a ‘thermodynamic’ description of the cosmological evolution and scaling of a network of semilocal strings, by analogy with well-known descriptions for cosmic strings and for monopoles. We propose a model for the time evolution of an overall length scale and typical velocity for the network as well as for its segments, and some supporting (preliminary) numerical evidence. This article is part of a discussion meeting issue ‘Topological avatars of new physics’.


2005 ◽  
Vol 72 (6) ◽  
pp. 990-996 ◽  
Author(s):  
G. W Delaney ◽  
D Weaire ◽  
S Hutzler
Keyword(s):  

2014 ◽  
Vol 89 (6) ◽  
Author(s):  
A. Achúcarro ◽  
A. Avgoustidis ◽  
A. M. M. Leite ◽  
A. Lopez-Eiguren ◽  
C. J. A. P. Martins ◽  
...  

Nature ◽  
1988 ◽  
Vol 335 (6189) ◽  
pp. 410-414 ◽  
Author(s):  
François R. Bouchet ◽  
David P. Bennett ◽  
Albert Stebbins

2021 ◽  
Vol 2021 (05) ◽  
pp. 055
Author(s):  
Mudit Jain ◽  
Andrew J. Long ◽  
Mustafa A. Amin
Keyword(s):  

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