Learning a local symmetry with neural networks

We explore the capacity of neural networks to detect a symmetry with complex local and non-local patterns: the gauge symmetry Z2. This symmetry is present in physical problems from topological transitions to quantum chromodynamics, and controls the computational hardness of instances of spin-glasses. Here, we show how to design a neural network, and a dataset, able to learn this symmetry and to find compressed latent representations of the gauge orbits. Our method pays special attention to system-wrapping loops, the so-called Polyakov loops, known to be particularly relevant for computational complexity

Propagation of Magnetic Avalanches in Mn12Ac at High Field Sweep Rates

Time-resolved measurements of the magnetization reversal in single crystals of Mn 12 Ac in pulsed magnetic fields, at magnetic field sweep rates from 1.5     kT / s up to 7     kT / s , suggest a new process that cannot be scaled onto a deflagrationlike propagation driven by heat diffusion. The sweep rate dependence of the propagation velocity, increasing from a few 100     m / s up to the speed of sound in Mn 12 Ac , indicates the existence of two new regimes at the highest sweep rates, with a transition around 4     kT / s that can be understood as a magnetic deflagration-to-detonation transition

Cycle-based Cluster Variational Method for Direct and Inverse Inference

We elaborate on the idea that loop corrections to belief propagation could be dealt with in a systematic way on pairwise Markov random fields, by using the elements of a cycle basis to define region in a generalized belief propagation setting. The region graph is specified in such a way as to avoid dual loops as much as possible, by discarding redundant Lagrange multipliers, in order to facilitate the convergence, while avoiding instabilities associated to minimal factor graph construction. We end up with a two-level algorithm, where a belief propagation algorithm is run alternatively at the level of each cycle and at the inter-region level. The inverse problem of finding the couplings of a Markov random field from empirical covariances can be addressed region wise. It turns out that this can be done efficiently in particular in the Ising context, where fixed point equations can be derived along with a one-parameter log likelihood function to minimize. Numerical experiments confirm the effectiveness of these considerations both for the direct and inverse MRF inference.Comment: 47 pages, 16 figure

Finite-size scaling analysis of the distributions of pseudo-critical temperatures in spin glasses

Using the results of large scale numerical simulations we study the probability distribution of the pseudo critical temperature for the three-dimensional Edwards-Anderson Ising spin glass and for the fully connected Sherrington-Kirkpatrick model. We find that the behavior of our data is nicely described by straightforward finite-size scaling relations.Comment: 23 pages, 9 figures. Version accepted for publication in J. Stat. Mec

Router-level community structure of the Internet Autonomous Systems

The Internet is composed of routing devices connected between them and organized into independent administrative entities: the Autonomous Systems. The existence of different types of Autonomous Systems (like large connectivity providers, Internet Service Providers or universities) together with geographical and economical constraints, turns the Internet into a complex modular and hierarchical network. This organization is reflected in many properties of the Internet topology, like its high degree of clustering and its robustness. In this work, we study the modular structure of the Internet router-level graph in order to assess to what extent the Autonomous Systems satisfy some of the known notions of community structure. We show that the modular structure of the Internet is much richer than what can be captured by the current community detection methods, which are severely affected by resolution limits and by the heterogeneity of the Autonomous Systems. Here we overcome this issue by using a multiresolution detection algorithm combined with a small sample of nodes. We also discuss recent work on community structure in the light of our results

Modelling home care organisations from an operations management perspective

Home Care (HC) service consists of providing care to patients in their homes. During the last decade, the HC service industry experienced significant growth in many European countries. This growth stems from several factors, such as governmental pressure to reduce healthcare costs, demographic changes related to population ageing, social changes, an increase in the number of patients that suffer from chronic illnesses, and the development of new home-based services and technologies. This study proposes a framework that will enable HC service providers to better understand HC operations and their management. The study identifies the main processes and decisions that relate to the field of HC operations management. Hence, an IDEF0 (Integrated Definition for Function Modelling) activity-based model describes the most relevant clinical, logistical and organisational processes associated with HC operations. A hierarchical framework for operations management decisions is also proposed. This analysis is derived from data that was collected by nine HC service providers, which are located in France and Italy, and focuses on the manner in which operations are run, as well as associated constraints, inputs and outputs. The most challenging research areas in the field of HC operations management are also discussed

16S rRNA gene metabarcoding and TEM reveals different ecological strategies within the genus Neogloboquadrina (planktonic foraminifer)

CB was supported on a Daphne Jackson Fellowship sponsored by Natural Environmental Research Council (www.nerc.ac.uk) and the University of Edinburgh via the Daphne Jackson Trust. Field collections were supported by the National Science Foundation (www.nsf.gov) grant number OCE-1261519 to ADR and JSF.Uncovering the complexities of trophic and metabolic interactions among microorganisms is essential for the understanding of marine biogeochemical cycling and modelling climate-driven ecosystem shifts. High-throughput DNA sequencing methods provide valuable tools for examining these complex interactions, although this remains challenging, as many microorganisms are difficult to isolate, identify and culture. We use two species of planktonic foraminifera from the climatically susceptible, palaeoceanographically important genus Neogloboquadrina, as ideal test microorganisms for the application of 16S rRNA gene metabarcoding. Neogloboquadrina dutertrei and Neogloboquadrina incompta were collected from the California Current and subjected to either 16S rRNA gene metabarcoding, fluorescence microscopy, or transmission electron microscopy (TEM) to investigate their species-specific trophic interactions and potential symbiotic associations. 53–99% of 16S rRNA gene sequences recovered from two specimens of N. dutertrei were assigned to a single operational taxonomic unit (OTU) from a chloroplast of the phylum Stramenopile. TEM observations confirmed the presence of numerous intact coccoid algae within the host cell, consistent with algal symbionts. Based on sequence data and observed ultrastructure, we taxonomically assign the putative algal symbionts to Pelagophyceae and not Chrysophyceae, as previously reported in this species. In addition, our data shows that N. dutertrei feeds on protists within particulate organic matter (POM), but not on bacteria as a major food source. In total contrast, of OTUs recovered from three N. incompta specimens, 83–95% were assigned to bacterial classes Alteromonadales and Vibrionales of the order Gammaproteobacteria. TEM demonstrates that these bacteria are a food source, not putative symbionts. Contrary to the current view that non-spinose foraminifera are predominantly herbivorous, neither N. dutertrei nor N. incompta contained significant numbers of phytoplankton OTUs. We present an alternative view of their trophic interactions and discuss these results within the context of modelling global planktonic foraminiferal abundances in response to high-latitude climate change.Publisher PDFPeer reviewe

Propagation of Magnetic Avalanches in Mn12Ac at High Field Sweep Rates

Time-resolved measurements of the magnetization reversal in single crystals of Mn 12 Ac in pulsed magnetic fields, at magnetic field sweep rates from 1.5     kT / s up to 7     kT / s , suggest a new process that cannot be scaled onto a deflagrationlike propagation driven by heat diffusion. The sweep rate dependence of the propagation velocity, increasing from a few 100     m / s up to the speed of sound in Mn 12 Ac , indicates the existence of two new regimes at the highest sweep rates, with a transition around 4     kT / s that can be understood as a magnetic deflagration-to-detonation transition