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The extension of elastic optical networks (EON) to multi-band transmission (MB-EON) shows promise in enhancing spectral efficiency, throughput, and long-term cost-effectiveness for telecom operators. However, designing MB-EON networks introduces complex challenges, notably the optimization of physical parameters like optical power and quality of transmission (QoT). Frequency-dependent characteristics of fiber, such as loss, dispersion, and nonlinear effects, alongside inter-channel stimulated Raman scattering, pose significant hurdles when extending beyond the L+C (LC) band to a continuous spectrum over 100 nm. In this study, we propose a span-by-span methodology for optimal power allocation, introducing two hyper-accelerated power optimization (HPO) strategies: flat launch power (FLP) and flat received power (FRP). These approaches significantly expedite network power optimization while preserving the stability of running services. Our comparative analysis of FLP and FRP models reveals that while FRP has a minimal effect on capacity (increasing less than 10 Tbps for an L+C+S (LCS) system over 100 km), it improves flatness and GSNR/OSNR metrics in the S-band by approximately 2/0 dB and 2.5/6 dB, respectively. A network-wide analysis across various topologies shows that the FRP technique enhances minimum GSNR, contributing to a throughput increase of 12% to 75%, depending on network scale, at a 1% bandwidth blocking rate. Lastly, our application of HPO in MB-EON for both local and global power optimization demonstrates that while both approaches offer comparable performance, global optimization is simpler and more cost-effective for large-scale networks.

Isospin symmetry is a fundamental concept in nuclear physics. Even though isospin symmetry is partially broken, it holds approximately for most nuclear systems, which makes exceptions very interesting from the nuclear structure perspective. In this framework, it is expected that the spins and parities of the ground states of mirror nuclei should be the same, in particular for the simplest systems where a proton is exchanged with a neutron or vice versa. In this work, we present evidence that this assumption is broken in the mirror pair $^{71}$Br and $^{71}$Kr system. Our conclusions are based on a high-statistics $\beta$ decay study of $^{71}$Kr and on state-of-the-art shell model calculations. In our work, we also found evidence of a new state in $^{70}$Se, populated in the $\beta$-delayed proton emission process which can be interpreted as the long sought coexisting 0$^+$ state., Comment: 8 pages with references, 3 figures. Supplemental material 4 pages (1 table, 3 figures)

The accurate modeling of individual movement in cities has significant implications for policy decisions across various sectors. Existing research emphasizes the universality of human mobility, positing that simple models can capture population-level movements. However, population-level accuracy does not guarantee consistent performance across all individuals. By overlooking individual differences, universality laws may accurately describe certain groups while less precisely representing others, resulting in aggregate accuracy from a balance of discrepancies. Using large-scale mobility data, we assess individual-level accuracy of a universal model, the Exploration and Preferential Return (EPR), by examining deviations from expected behavior in two scaling laws - one related to exploration and the other to return patterns. Our findings reveal that, while the model can describe population-wide movement patterns, it displays widespread deviations linked to individuals' behavioral traits, socioeconomic status, and lifestyles, contradicting model assumptions like non-bursty exploration and preferential return. Specifically, individuals poorly represented by the EPR model tend to visit routine locations in sequences, exploring rarely but in a bursty manner when they do. Among socioeconomic factors, income most strongly correlates with significant deviations. Consequently, spatial inhomogeneity emerges in model accuracy, with lower performance concentrated in urbanized, densely populated areas, underscoring policy implications. Our results show that emphasizing population-wide models can propagate socioeconomic inequalities by poorly representing vulnerable population sectors.

Recently, it has been proposed a new method [arXiv:2405.21029] to detect quantum gravity effects, based on generating gravitational entanglement between two nano-diamonds with Nitrogen-Vacancy defects, in a magnetically trapped configuration. Here we analyse in detail the proposed experimental setup, with a particular focus on implementing the detection of the gravitationally-induced entanglement using an optical readout based on measuring the position of the nano-diamonds and its complementary basis. We also summarise some of the key theoretical and experimental ideas on which this proposed scheme is based., Comment: 8 pages, 2 figures

The Zirconium (Z = 40) isotopic chain has attracted interest for more than four decades. The abrupt lowering of the energy of the first $2^+$ state and the increase in the transition strength B(E2; $2_1^\rightarrow 0_1^+$ going from $^{98}$Zr to $^{100}$Zr has been the first example of "quantum phase transition" in nuclear shapes, which has few equivalents in the nuclear chart. Although a multitude of experiments have been performed to measure nuclear properties related to nuclear shapes and collectivity in the region, none of the measured lifetimes were obtained using the Recoil Distance Doppler Shift method in the $\gamma\gamma$-coincidence mode where a gate on the direct feeding transition of the state of interest allows a strict control of systematical errors. This work reports the results of lifetime measurements for the first yrast excited states in $^{98-104}$Zr carried out to extract reduced transition probabilities. The new lifetime values in $\gamma\gamma$-coincidence and $\gamma$-single mode are compared with the results of former experiments. Recent predictions of the Interacting Boson Model with Configuration Mixing, the Symmetry Conserving Configuration Mixing model based on the Hartree-Fock-Bogoliubov approach and the Monte Carlo Shell Model are presented and compared with the experimental data.

Domain shifts are ubiquitous in machine learning, and can substantially degrade a model's performance when deployed to real-world data. To address this, distribution alignment methods aim to learn feature representations which are invariant across domains, by minimising the discrepancy between the distributions. However, the discrepancy estimates can be extremely noisy when training via stochastic gradient descent (SGD), and shifts in the relative proportions of different subgroups can lead to domain misalignments; these can both stifle the benefits of the method. This paper proposes to improve these estimates by inducing diversity in each sampled minibatch. This simultaneously balances the data and reduces the variance of the gradients, thereby enhancing the model's generalisation ability. We describe two options for diversity-based data samplers, based on the k-determinantal point process (k-DPP) and the k-means++ algorithm, which can function as drop-in replacements for a standard random sampler. On a real-world domain shift task of bioacoustic event detection, we show that both options 1) yield minibatches which are more representative of the full dataset; 2) reduce the distance estimation error between distributions, for a given sample size; and 3) improve out-of-distribution accuracy for two distribution alignment algorithms, as well as standard ERM., Comment: DCASE 2024

The removal of carefully-selected examples from training data has recently emerged as an effective way of improving the robustness of machine learning models. However, the best way to select these examples remains an open question. In this paper, we consider the problem from the perspective of unsupervised domain adaptation (UDA). We propose AdaPrune, a method for UDA whereby training examples are removed to attempt to align the training distribution to that of the target data. By adopting the maximum mean discrepancy (MMD) as the criterion for alignment, the problem can be neatly formulated and solved as an integer quadratic program. We evaluate our approach on a real-world domain shift task of bioacoustic event detection. As a method for UDA, we show that AdaPrune outperforms related techniques, and is complementary to other UDA algorithms such as CORAL. Our analysis of the relationship between the MMD and model accuracy, along with t-SNE plots, validate the proposed method as a principled and well-founded way of performing data pruning.

Cavity quantum electrodynamics (QED) studies the interaction between resonator-confined radiation and natural atoms or other formally equivalent quantum excitations, under conditions where the quantum nature of photons is relevant. Phenomena studied in cavity QED can also be explored using superconducting artificial atoms and microwave photons in superconducting resonators. These circuit QED systems offer the possibility to reach the ultrastrong coupling regime with individual artificial atoms, unlike their natural counterparts. In this regime, the light-matter coupling strength reaches a considerable fraction of the bare resonance frequencies in the system. Here, we provide a careful analysis of both incoherent and coherent spectra in circuit QED systems consisting of a flux qubit interacting with an LC resonator. Despite these systems can be effectively described by the quantum Rabi model, as the corresponding cavity QED ones, we find distinctive features, depending on how the system is coupled to the output port, which become evident in the ultrastrong coupling regime., Comment: 14 pages, 12 figures

Low-lying states of $^{94}$Zr were investigated via low-energy multi-step Coulomb excitation. From the measured $\gamma$-ray yields, 13 reduced transition probabilities between low-spin states were determined, together with the spectroscopic quadrupole moments of the $2_{1,2}^+$ states. Based on this information, for the first time in the Zr isotopic chain, the shapes of the $0_{1,2}^+$ states including their deformation softness were inferred in a model-independent way using the quadrupole sum rules approach. The ground state of $^{94}$Zr possesses a rather diffuse shape associated with a spherical configuration, while the $0_2^+$ state is oblate and more strongly deformed. The observed features of shape coexistence in $^{94}$Zr are in agreement with Monte-Carlo shell-model predictions, and the present results are vital to refine the IBM-CM description of the Zr isotopes around $A\approx 100$ in terms of an intertwined quantum phase transition., Comment: 6 pages, 3 figures

This research work is part of a PhD project aiming to design a new helicon plasma thruster for cargo space missions, within a collaboration between the School of Aerospace Engineering of La Sapienza University and the ENEA Frascati research center. A 0-D global design model of the thruster is first established to identify the main operational conditions of the thruster, starting from a targeted performance in terms of specific impulse and thrust. These operational conditions are tested with dedicated simulations on the electromagnetic plasma-wave interaction within the ionization chamber, and on the electrostatic plasma acceleration within the magnetic nozzle. The former are carried out with a finite element electromagnetic code and confirm the technical feasibility of the identified operational RF power with a predefined chamber geometry. The latter are obtained with an electrostatic particle-in-cell code, which allows to estimate more precisely the achieved thruster performance. A sub-optimal thruster with an absorbed plasma power of around 1 kW, a thrust of around 10 mN and a specific impulse higher than 1000 s is successfully simulated. The established simulation framework will serve as the basis for the next optimization of the thruster geometry and operational conditions, with the ultimate goal of building and testing a new helicon thruster prototype.

The application of Riemannian geometry in the decoding of brain-computer interfaces (BCIs) has swiftly garnered attention because of its straightforwardness, precision, and resilience, along with its aptitude for transfer learning, which has been demonstrated through significant achievements in global BCI competitions. This paper presents a comprehensive review of recent advancements in the integration of deep learning with Riemannian geometry to enhance EEG signal decoding in BCIs. Our review updates the findings since the last major review in 2017, comparing modern approaches that utilize deep learning to improve the handling of non-Euclidean data structures inherent in EEG signals. We discuss how these approaches not only tackle the traditional challenges of noise sensitivity, non-stationarity, and lengthy calibration times but also introduce novel classification frameworks and signal processing techniques to reduce these limitations significantly. Furthermore, we identify current shortcomings and propose future research directions in manifold learning and riemannian-based classification, focusing on practical implementations and theoretical expansions, such as feature tracking on manifolds, multitask learning, feature extraction, and transfer learning. This review aims to bridge the gap between theoretical research and practical, real-world applications, making sophisticated mathematical approaches accessible and actionable for BCI enhancements.

We prove the local Lipschitz regularity of the local minimizers of scalar integral functionals of the form \begin{equation*} \mathcal{F}(v;\Omega)= \int_{\Omega} f (x, Dv) dx \end{equation*} under $(p,q)$-growth conditions. The main novelty is that, beside a suitable regularity assumption on the partial map $x\mapsto f(x,\xi)$, we do not assume any special structure for the energy density as a function of the $\xi$-variable.

PLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2 R_(Earth)) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.

Unifying quantum theory and general relativity is the holy grail of contemporary physics. Nonetheless, the lack of experimental evidence driving this process led to a plethora of mathematical models with a substantial impossibility of discriminating among them or even establishing if gravity really needs to be quantized or if, vice versa, quantum mechanics must be "gravitized" at some scale. Recently, it has been proposed that the observation of the generation of entanglement by gravitational interaction, could represent a breakthrough demonstrating the quantum nature of gravity. A few experimental proposals have been advanced in this sense, but the extreme technological requirements (e.g., the need for free-falling gravitationally-interacting masses in a quantum superposition state) make their implementation still far ahead. Here we present a feasibility study for a table-top nanodiamond-based interferometer eventually enabling easier and less resource-demanding quantum gravity tests. With respect to the aforementioned proposals, by relying on quantum superpositions of steady massive (mesoscopic) objects our interferometer may allow exploiting just small-range electromagnetic fields (much easier to implement and control) and, at the same time, the re-utilization of the massive quantum probes exploited, inevitably lost in free-falling interferometric schemes., Comment: 8 pages, 5 figures

The Stimulated Raman Adiabatic Passage (STIRAP) is applied to a system coupled to a bath made of fully-interacting two-level systems, whose dynamics is studied exploiting the generalized Cluster Correlation Expansion (gCCE) theory. We specialize our analysis to a negatively charged silicon vacancy (SiV-1) in non-purified 4H-SiC to assess the possibility of transferring population between two states of the ground manifold, also taking into account the interaction with a spherical nuclear spin bath formed by nuclei of 29Si and 13C. For this system, it is demonstrated that the presence of a small/medium sized bath has no effect on the protocol, finding in particular a set of parameter values for an efficient STIRAP process., Comment: 13 pages, 10 figures

This paper considers the problem of model selection under domain shift. Motivated by principles from distributionally robust optimisation (DRO) and domain adaptation theory, it is proposed that the training-validation split should maximise the distribution mismatch between the two sets. By adopting the maximum mean discrepancy (MMD) as the measure of mismatch, it is shown that the partitioning problem reduces to kernel k-means clustering. A constrained clustering algorithm, which leverages linear programming to control the size, label, and (optionally) group distributions of the splits, is presented. The algorithm does not require additional metadata, and comes with convergence guarantees. In experiments, the technique consistently outperforms alternative splitting strategies across a range of datasets and training algorithms, for both domain generalisation (DG) and unsupervised domain adaptation (UDA) tasks. Analysis also shows the MMD between the training and validation sets to be strongly rank-correlated ($\rho=0.63$) with test domain accuracy, further substantiating the validity of this approach.

The excited states of unstable $^{20}$O were investigated via $\gamma$-ray spectroscopy following the $^{19}$O$(d,p)^{20}$O reaction at 8 $A$MeV. By exploiting the Doppler Shift Attenuation Method, the lifetime of the 2$^+_2$ and 3$^+_1$ states were firmly established. From the $\gamma$-ray branching and E2/M1 mixing ratios for transitions deexciting the 2$^+_2$ and 3$^+_1$ states, the B(E2) and B(M1) were determined. Various chiral effective field theory Hamiltonians, describing the nuclear properties beyond ground states, along with a standard USDB interaction, were compared with the experimentally obtained data. Such a comparison for a large set of $\gamma$-ray transition probabilities with the valence space in medium similarity renormalization group ab-initio calculations was performed for the first time in a nucleus far from stability. It was shown that the ab-initio approaches using chiral EFT forces are challenged by detailed high-precision spectroscopic properties of nuclei. The reduced transition probabilities were found to be a very constraining test of the performance of the ab-initio models., Comment: Supplemental Material available

In this paper we revisit the problem of computing the closure of a set of attributes, given a set of Armstrong dependencies. This problem is of main interest in logics, in the relational database model, in lattice theory and in Formal Concept Analysis as well. We consider here three main closure algorithms, namely Closure, LinClosure and Wild's Closure, which are combined with implication bases which may have different characteristics, among which being "minimal", e.g., the Duquenne-Guigues basis, and being "direct", e.g., the Canonical Basis and the D-basis. The impacts of minimality and directness on the closure algorithms are then deeply studied also experimentally. The results are extensively analyzed and propose a different and fresh look at computing the closure of a set of attributes. This paper has been submitted to the International Journal of Approximate Reasoning.

We present an experimental study of the magnetoelectric coupling (MEC) in the Fe-Ga/PMN-PT thin film multiferroic composite by means of x-ray magnetic circular dichroism (XMCD) and ferromagnetic resonance (FMR). Our measurements show evidence for a charge mediated coupling mechanism, suggested by the asymmetric magnetic remanence (M$_{rem}$) behaviour under opposite electric fields ($\pm$ E) and the asymmetric resonance field (H$_r$) in the FMR measurements. Also, the FMR measurements reveal a perpendicular magnetic anisotropy (PMA), that can be related to an interface charge effect. and it is tunable by E field. Ab initio calculations support the existence of a charge mediated coupling at the Fe-Ga/PMN-PT interface., Comment: 7 pages, 5 figures, Supplemental Material

The Stimulated Raman Adiabatic Passage on a three-state system interacting with a spin bath is considered focusing on the efficiency of the population transfer. Our analysis is based on the perturbation treatment of the interaction term evaluated beyond the Rotating Wave Approximation, thus focusing on the limit of weak system-bath coupling. The analytical expression of the correction to the efficiency and consequent numerical analysis show that in most of the cases the effects of the environment are negligible, confirming the robustness of the population transfer., Comment: 11 pages, 3 figures

We consider local weak solutions of widely degenerate or singular elliptic PDEs of the type \begin{equation*} -\,\mathrm{div}\left((\vert Du\vert-\lambda)_{+}^{p-1}\frac{Du}{\vert Du\vert}\right)=f \,\,\,\,\,\,\, \text{in}\,\,\Omega, \end{equation*} where $\Omega$ is an open subset of $\mathbb{R}^{n}$ for $n\geq2$, $\lambda$ is a positive constant and $(\,\cdot\,)_{+}$ stands for the positive part. We establish some higher differentiability results, under essentially sharp conditions on the datum $f$. For $\lambda=0$, our results give back those contained in [12, 25].

$Ab$ $initio$ calculations show the presence of a strong magnetoelectric interfacial coupling in CaMnO$_3$ ultra-thin film grown on a strained BaTiO$_3$ ferroelectric film. This heterostructure presents a polarization driven magnetic transition from a G-type to an A-type antiferromagnetic structure. Together with this magnetic transition we find a metallic behaviour at the interface between these two insulators, where the charge character of the carriers can be tuned from electrons to holes by switching the electric polarization direction of the FE film. Besides, the electron gas is spin-polarized while the hole-gas is not., Comment: 8 pages, 5 figures, supplementary

Socioeconomic segregation patterns in networks usually evolve gradually, yet they can change abruptly in response to external shocks. The recent COVID-19 pandemic and the subsequent government policies induced several interruptions in societies, potentially disadvantaging the socioeconomically most vulnerable groups. Using large-scale digital behavioral observations as a natural laboratory, here we analyze how lockdown interventions lead to the reorganization of socioeconomic segregation patterns simultaneously in communication and mobility networks in Sierra Leone. We find that while segregation in mobility clearly increased during lockdown, the social communication network reorganized into a less segregated configuration as compared to reference periods. Moreover, due to differences in adaption capacities, the effects of lockdown policies varied across socioeconomic groups, leading to different or even opposite segregation patterns between the lower and higher socioeconomic classes. Such secondary effects of interventions need to be considered for better and more equitable policies.