Characterisation of cyclic variability in an optically accessible IC Engine by means of phase-independent POD

Investigation of cyclic variability in engine operation has recently received new impulse with the widespread application of advanced numerical and experimental techniques. The present work attempts to shed some light on the existence and nature of correlations between coherent structures dynamics and cyclic variability in IC engines by means of phase-independent Proper Orthogonal Decomposition applied to highly-resolved PIV measurements obtained in an optically accessible, motored engine. Analysis of the conditional means and variances of the reconstruction coefficients reveal interesting patterns in the break-up of coherent structures which are also confirmed by experimental observation and leave room for speculation on the true nature of the flow field at different crank angles. A first attempt has also been carried out to reconstruct missing information from available measurements, with encouraging results: the development of such interpolation/reconstruction technique could obviously have a great impact on the reduction of the cost normally involved in experimental and computational campaigns

Laser induced modulation of the Landau level structure in single-layer graphene

We present perturbative analytical results of the Landau level quasienergy spectrum, autocorrelation function and out of plane pseudospin polarization for a single graphene sheet subject to intense circularly polarized terahertz radiation. For the quasienergy spectrum, we find a striking non trivial level-dependent dynamically induced gap structure. This photoinduced modulation of the energy band structure gives rise to shifts of the revival times in the autocorrelation function and it also leads to modulation of the oscillations in the dynamical evolution of the out of plane pseudospin polarization, which measures the angular momentum transfer between light and graphene electrons. For a coherent state, chosen as an initial pseudospin configuration, the dynamics induces additional quantum revivals of the wave function that manifest as shifts of the maxima and minima of the autocorrelation function, with additional partial revivals and beating patterns. These additional maxima and beating patterns stem from the effective dynamical coupling of the static eigenstates. We discuss the possible experimental detection schemes of our theoretical results and their relevance in new practical implementation of radiation fields in graphene physics.Comment: 12 pages, 5 figures. Accepted version for publication in Physical Review

The Casimir Energy in Curved Space and its Supersymmetric Counterpart

We study $d$-dimensional Conformal Field Theories (CFTs) on the cylinder, $S^{d-1}\times \mathbb{R}$, and its deformations. In $d=2$ the Casimir energy (i.e. the vacuum energy) is universal and is related to the central charge $c$. In $d=4$ the vacuum energy depends on the regularization scheme and has no intrinsic value. We show that this property extends to infinitesimally deformed cylinders and support this conclusion with a holographic check. However, for $\mathcal{N}=1$ supersymmetric CFTs, a natural analog of the Casimir energy turns out to be scheme independent and thus intrinsic. We give two proofs of this result. We compute the Casimir energy for such theories by reducing to a problem in supersymmetric quantum mechanics. For the round cylinder the vacuum energy is proportional to $a+3c$. We also compute the dependence of the Casimir energy on the squashing parameter of the cylinder. Finally, we revisit the problem of supersymmetric regularization of the path integral on Hopf surfaces.Comment: 53 pages; v2: minor changes, references added, version published in JHE

Polarimetric Thermal to Visible Face Verification via Self-Attention Guided Synthesis

Polarimetric thermal to visible face verification entails matching two images that contain significant domain differences. Several recent approaches have attempted to synthesize visible faces from thermal images for cross-modal matching. In this paper, we take a different approach in which rather than focusing only on synthesizing visible faces from thermal faces, we also propose to synthesize thermal faces from visible faces. Our intuition is based on the fact that thermal images also contain some discriminative information about the person for verification. Deep features from a pre-trained Convolutional Neural Network (CNN) are extracted from the original as well as the synthesized images. These features are then fused to generate a template which is then used for verification. The proposed synthesis network is based on the self-attention generative adversarial network (SAGAN) which essentially allows efficient attention-guided image synthesis. Extensive experiments on the ARL polarimetric thermal face dataset demonstrate that the proposed method achieves state-of-the-art performance.Comment: This work is accepted at the 12th IAPR International Conference On Biometrics (ICB 2019

NonClassicality Criteria in Multiport Interferometry

Interference lies at the heart of the behavior of classical and quantum light. It is thus crucial to understand the boundaries between which interference patterns can be explained by a classical electromagnetic description of light and which, on the other hand, can only be understood with a proper quantum mechanical approach. While the case of two-mode interference has received a lot of attention, the multimode case has not yet been fully explored. Here we study a general scenario of intensity interferometry: we derive a bound on the average correlations between pairs of output intensities for the classical wavelike model of light, and we show how it can be violated in a quantum framework. As a consequence, this violation acts as a nonclassicality witness, able to detect the presence of sources with sub-Poissonian photon-number statistics. We also develop a criterion that can certify the impossibility of dividing a given interferometer into two independent subblocks.Comment: 5 + 3 pages, published versio

The importance of human capital in the era of automation

As new technologies continue to displace workers, technological progress also creates new occupations depending on the interplay between humans with machines, causing a skill mismatch. Giuseppe Di Giacomo and Benjamin Lerch discuss how workers are responding to the growing automation of production processes, and why human capital adjustments are crucial for future labour market competition

Off-line vs. On-line Evaluation of Recommender Systems in Small E-commerce

In this paper, we present our work towards comparing on-line and off-line evaluation metrics in the context of small e-commerce recommender systems. Recommending on small e-commerce enterprises is rather challenging due to the lower volume of interactions and low user loyalty, rarely extending beyond a single session. On the other hand, we usually have to deal with lower volumes of objects, which are easier to discover by users through various browsing/searching GUIs. The main goal of this paper is to determine applicability of off-line evaluation metrics in learning true usability of recommender systems (evaluated on-line in A/B testing). In total 800 variants of recommending algorithms were evaluated off-line w.r.t. 18 metrics covering rating-based, ranking-based, novelty and diversity evaluation. The off-line results were afterwards compared with on-line evaluation of 12 selected recommender variants and based on the results, we tried to learn and utilize an off-line to on-line results prediction model. Off-line results shown a great variance in performance w.r.t. different metrics with the Pareto front covering 68\% of the approaches. Furthermore, we observed that on-line results are considerably affected by the novelty of users. On-line metrics correlates positively with ranking-based metrics (AUC, MRR, nDCG) for novice users, while too high values of diversity and novelty had a negative impact on the on-line results for them. For users with more visited items, however, the diversity became more important, while ranking-based metrics relevance gradually decrease.Comment: Submitted to ACM Hypertext 2020 Conferenc