Domain decomposition and multilevel integration for fermions

The numerical computation of many hadronic correlation functions is exceedingly difficult due to the exponentially decreasing signal-to-noise ratio with the distance between source and sink. Multilevel integration methods, using independent updates of separate regions in space-time, are known to be able to solve such problems but have so far been available only for pure gauge theory. We present first steps into the direction of making such integration schemes amenable to theories with fermions, by factorizing a given observable via an approximated domain decomposition of the quark propagator. This allows for multilevel integration of the (large) factorized contribution to the observable, while its (small) correction can be computed in the standard way.Comment: 14 pages, 6 figures, v2: published version, talk presented at the 34th annual International Symposium on Lattice Field Theory, 24-30 July 2016, University of Southampton, U

Local multiboson factorization of the quark determinant

We discuss the recently proposed multiboson domain-decomposed factorization of the gauge-field dependence of the fermion determinant in lattice QCD. In particular, we focus on the case of a lattice divided in an arbitrary number of thick time slices. As a consequence, multiple space-time regions can be updated independently. This allows to address the exponential degradation of the signal-to-noise ration of correlation functions with multilevel Monte Carlo sampling. We show numerical evidence of the effectiveness of a two-level integration for pseudoscalar propagators with momentum and for vector propagators, in a two active regions setup. These results are relevant to lattice computation of the hadronic contributions to the anomalous magnetic moment of the muon and to heavy meson decay form factors.Comment: 8 pages, 4 figures, talk presented at the 35th International Symposium on Lattice Field Theory, 18-24 June 2017, Granada, Spai

Optimal encoding of interval timing in expert percussionists

We measured temporal reproduction in expert drummers, string-musicians and non-musical subjects. While duration reproduction of the controls showed a characteristic regression to the mean, drummers responded veridically. This behavior is well explained by a model that combines optimally the sensory estimate for duration (more precise in drummers) with a prior, given by the average of the past few trials. These results highlight the efficiency and adaptability of sensori-motor mechanisms estimating temporal duration

Three-dimensional ISAR imaging: a review

Three-dimensional (3D) inverse synthetic aperture radar (ISAR) imaging has been proven feasible by combining traditional ISAR imaging and interferometry. Such technique, namely inteferometric ISAR (In-ISAR), allows for the main target scattering centres to be mapped into a 3D spatial domain as point clouds. Specifically, the use of an In-ISAR system can overcome the main geometrical interpretation issues imposed by the monostatic acquisition geometry as the problem of cross-range scaling and unknown image projection plane (IPP). However, some issues remain such as scatterer scintillation, shadowing effects, poor SNR etc., which limit the effectiveness of 3D imaging. A solution to such unsolved issues can be found in the use of multiple 3D views, which can be obtained exploiting either multi-temporal or multi-perspective configurations or a combination of both. This study aims to review the main concepts to produce multi-view 3D ISAR images by using In-ISAR systems also presenting real data collected with a multi-static In-ISAR system

Collisions of self-bound quantum droplets

We report on the study of binary collisions between quantum droplets formed by an attractive mixture of ultracold atoms. We distinguish two main outcomes of the collision, i.e. merging and separation, depending on the velocity of the colliding pair. The critical velocity $v_c$ that discriminates between the two cases displays a different dependence on the atom number $N$ for small and large droplets. By comparing our experimental results with numerical simulations, we show that the non-monotonic behavior of $v_c(N)$ is due to the crossover from a compressible to an incompressible regime, where the collisional dynamics is governed by different energy scales, i.e. the droplet binding energy and the surface tension. These results also provide the first evidence of the liquid-like nature of quantum droplets in the large $N$ limit, where their behavior closely resembles that of classical liquid droplets

Proportional similarity-based Openmax classifier for open set recognition in SAR images

Most of the existing Non-Cooperative Target Recognition (NCTR) systems follow the “closed world” assumption, i.e., they only work with what was previously observed. Nevertheless, the real world is relatively “open” in the sense that the knowledge of the environment is incomplete. Therefore, unknown targets can feed the recognition system at any time while it is operational. Addressing this issue, the Openmax classifier has been recently proposed in the optical domain to make convolutional neural networks (CNN) able to reject unknown targets. There are some fundamental limitations in the Openmax classifier that can end up with two potential errors: (1) rejecting a known target and (2) classifying an unknown target. In this paper, we propose a new classifier to increase the robustness and accuracy. The proposed classifier, which is inspired by the limitations of the Openmax classifier, is based on proportional similarity between the test image and different training classes. We evaluate our method by radar images of man-made targets from the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset. Moreover, a more in-depth discussion on the Openmax hyper-parameters and a detailed description of the Openmax functioning are given

Optimized Nonlinear PRI Variation Strategy Using Knowledge-Guided Genetic Algorithm for Staggered SAR Imaging

Staggered synthetic aperture radar (SAR), which operates with variable pulse repetition interval (PRI), staggers blind areas to solve the blind range problem caused by constant PRI in conventional high-resolution wide-swath SAR imaging. The PRI variation strategy determines the blind area distribution, and thus has a significant influence on the imaging performance in staggered mode. Generally, the existing strategies based on linear PRI variation can control the blind areas in a straightforward way, which has achieved impressive results. However, the linearity of the PRI variation imposes regularity or even periodicity on the locations of the blind areas, which limits the distribution of the blind areas. The imaging performance has the potential to be further improved by introducing much more irregularity into the PRI sequences. To this end, this article proposes an optimized nonlinear PRI variation strategy for staggered SAR mode. First, a novel objective function is defined that quantitatively measures the uniformity of the blind area distribution along the slant range and the discontinuity of the blind area distribution along the azimuth. Subsequently, the optimum nonlinear PRI variation strategy is found using an optimization problem and the proposed objective function. A knowledge-guided genetic algorithm is proposed to solve the optimization problem. Comparisons with the existing linear variation strategies show that the proposed strategy can provide a superior imaging performance after reconstruction with a lower objective function value. Simulations and experiments on raw data generated in staggered SAR mode are performed to verify the effectiveness of the optimized nonlinear PRI variation strategy

Occurrence of microplastics in bivalves: can a systematic literature review support the risk assessment?

Microplastics (MPs) are a global environmental issue, particularly affecting the aquatic ecosystem. Due to their small size (<5 mm), MPs can be absorbed or ingested by aquatic organisms, and transferred through food webs. Toxic effects due to the ingestion of MPs, alone or contaminated with additives or pollutants, have been hypothesized. Human exposure is inevitable, also following accumulation in the food chain. Seafood, especially bivalves, being filter feeders and consumed as whole, are an important potential pathway. The scientific interest in the topic is rising, and several narrative reviews on MPs in food, including seafood, have been published since the publication of a statement on the presence of MPs and nanoplastics in food by EFSA in 2016 (1), highlighting a scarcity of data on MPs occurrence. The aim of this review was to systematically revise scientific papers (SPs) to assess the occurrence of MPs in different categories of bivalves (mussels, clams, oysters and scallop) worldwide. A double-step filtration was used, applying increasingly stricter quality criteria. Data on MPs abundance were first discussed focusing on all the investigated species and geographical areas. Then, a subset of SPs selected in the second filtering step was used to calculate the weighted MPs mean abundance and the human exposure per serving size. In the first filtering process 87 SPs, published between 2014 and 2020 in 30 different scientific journals, were retained. Overall, 67 species, 6 genera and 1 family of bivalves were analysed. Mussels were the most analysed (61 SPs), followed by clams (55 SPs), oysters (31 SPs), and scallops (7 SPs). Mytilus edulis and M. galloprovincialis were the most investigated species, followed by P. viridis, Mytilus sp., R. philippinarum and C. gigas. All these are commercial species, globally farmed and distributed. Marine FAO areas 61 and 27 were most investigated. Overall, MPs mean abundance was variably reported, as well as the use of different methods and procedural controls. Therefore, in this study, the weighted MPs mean abundance was calculated only including data from a subset of SPs (n=32; 37%). The overall weighted MPs mean abundance including data from all FAO areas was 1.19 MPs/g ww. The highest value was observed in FAO area 61 (2.33 MPs/g ww), while values <1 MPs/g ww were observed in FAO areas 27 and 57. Among bivalve categories, the highest weighted MPs mean abundance (overall FAO areas) was observed for scallops (1.99 MPs/g ww), followed by mussels (1.71 MPs/g ww), clams (0.84 MPs/g ww) and oysters (0.65 MPs/g ww). Thus, the consumption of standard portions of each bivalve category determines the ingestion of a different number of MPs depending on the FAO area; the highest value (⁓645 MPs) would be ingested with a portion of mussels from FAO area 61. Our findings confirmed the existence of quality issues and the lack of analytical standardization. A disparity among investigated species and geographical areas was observed, and only three studies addressed processed products. These aspects affect the outcome of systematic reviews to support risk assessment; future studies should explore the issue of MPs adopting an interdisciplinary perspective, integrating different technical and scientific competences to collect evidences for risk assessment and management