A low noise, high thermal stability, 0.1 K test facility for the Planck HFI bolometers

We are developing a facility which will be used to characterize the bolometric detectors for Planck, an ESA mission to investigate the Cosmic Microwave Background. The bolometers operate at 0.1 K, employing neutron-transmutation doped (NTD) Ge thermistors with resistances of several megohms to achieve NEPs~1×10^(–17) W Hz^(–1/2). Characterization of the intrinsic noise of the bolometers at frequencies as low as 0.010 Hz dictates a test apparatus thermal stability of 40 nK Hz^(–1/2) to that frequency. This temperature stability is achieved via a multi-stage isolation and control geometry with high resolution thermometry implemented with NTD Ge thermistors, JFET source followers, and dedicated lock-in amplifiers. The test facility accommodates 24 channels of differential signal readout, for measurement of bolometer V(I) characteristics and intrinsic noise. The test facility also provides for modulated radiation in the submillimeter band incident on the bolometers, for measurement of the optical speed-of-response; this illumination can be reduced below detectable limits without interrupting cryogenic operation. A commercial Oxford Instruments dilution refrigerator provides the cryogenic environment for the test facility

Muon g-2 through a flavor structure on soft SUSY terms

In this work we analyze the possibility to explain the muon anomalous magnetic moment discrepancy within theory and experiment through lepton flavor violation processes. We propose a flavor extended MSSM by considering a hierarchical family structure for the trilinear scalar Soft-Supersymmetric terms of the Lagranagian, present at the SUSY breaking scale. We obtain analytical results for the rotation mass matrix, with the consequence of having non-universal slepton masses and the possibility of leptonic flavour mixing. The one-loop supersymmetric contributions to the leptonic flavour violating process $\tau \to \mu\gamma$ are calculated in the physical basis, with slepton flavour mixed states, instead of using the well known Mass Insertion Method. We present the regions in parameter space where the muon g-2 problem is either entirely solved or partially reduced through the contribution of these flavor violating processes.Comment: 21 pages, 7 figures. Changes on version 3: In order to obtain the complete result for muon g-2 in the limit of non-flavor violation we added the terms given in the appendix. We redid the graphics and numerical analysis including these changes. We also corrected some typos and changed the order of figure

Low motivation and unawareness in small farmers as an obstacle for implementation of the EU pig welfare rules

Using semi-structured interviews, Croatian pig farmers and institutional stakeholders were asked about their intentions to improve pig welfare, future perspectives, opinions and communication efforts on the EU pig welfare directives. While full-time family farmers (FFF) and employees at farm enterprises (EFE) expressed interest in improving pig welfare on their farms as a prerequisite for increasing competitiveness in the future, part-time family farmers (PFF) were not interested in pig welfare because they did not want to increase productivity and feared for their existence. Communication between institutional stakeholders and FFF with more than ten sows is best stablished, whereas communication with EFE is more via private consultants and communication with PFF is lacking. As Croatia is today counting over 85% farms as production units with up to 10 sows covering 75% of whole pig production, these results represent considerably important indicators of necessity to approach this population of farmers

The Phase Diagram and Spectrum of Gauge-Fixed Abelian Lattice Gauge Theory

We consider a lattice discretization of a covariantly gauge-fixed abelian gauge theory. The gauge fixing is part of the action defining the theory, and we study the phase diagram in detail. As there is no BRST symmetry on the lattice, counterterms are needed, and we construct those explicitly. We show that the proper adjustment of these counterterms drives the theory to a new type of phase transition, at which we recover a continuum theory of (free) photons. We present both numerical and (one-loop) perturbative results, and show that they are in good agreement near this phase transition. Since perturbation theory plays an important role, it is important to choose a discretization of the gauge-fixing action such that lattice perturbation theory is valid. Indeed, we find numerical evidence that lattice actions not satisfying this requirement do not lead to the desired continuum limit. While we do not consider fermions here, we argue that our results, in combination with previous work, provide very strong evidence that this new phase transition can be used to define abelian lattice chiral gauge theories.Comment: 42 pages, 30 figure

Degree Landscapes in Scale-Free Networks

We generalize the degree-organizational view of real-world networks with broad degree-distributions in a landscape analogue with mountains (high-degree nodes) and valleys (low-degree nodes). For example, correlated degrees between adjacent nodes corresponds to smooth landscapes (social networks), hierarchical networks to one-mountain landscapes (the Internet), and degree-disassortative networks without hierarchical features to rough landscapes with several mountains. We also generate ridge landscapes to model networks organized under constraints imposed by the space the networks are embedded in, associated to spatial or, in molecular networks, to functional localization. To quantify the topology, we here measure the widths of the mountains and the separation between different mountains.Comment: 4 pages, 5 figure

Faster k-Medoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms

Clustering non-Euclidean data is difficult, and one of the most used algorithms besides hierarchical clustering is the popular algorithm Partitioning Around Medoids (PAM), also simply referred to as k-medoids. In Euclidean geometry the mean-as used in k-means-is a good estimator for the cluster center, but this does not hold for arbitrary dissimilarities. PAM uses the medoid instead, the object with the smallest dissimilarity to all others in the cluster. This notion of centrality can be used with any (dis-)similarity, and thus is of high relevance to many domains such as biology that require the use of Jaccard, Gower, or more complex distances. A key issue with PAM is its high run time cost. We propose modifications to the PAM algorithm to achieve an O(k)-fold speedup in the second SWAP phase of the algorithm, but will still find the same results as the original PAM algorithm. If we slightly relax the choice of swaps performed (at comparable quality), we can further accelerate the algorithm by performing up to k swaps in each iteration. With the substantially faster SWAP, we can now also explore alternative strategies for choosing the initial medoids. We also show how the CLARA and CLARANS algorithms benefit from these modifications. It can easily be combined with earlier approaches to use PAM and CLARA on big data (some of which use PAM as a subroutine, hence can immediately benefit from these improvements), where the performance with high k becomes increasingly important. In experiments on real data with k=100, we observed a 200-fold speedup compared to the original PAM SWAP algorithm, making PAM applicable to larger data sets as long as we can afford to compute a distance matrix, and in particular to higher k (at k=2, the new SWAP was only 1.5 times faster, as the speedup is expected to increase with k)