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Single-ion mass identification is important for atomic and nuclear physics experiments on ions produced with low yields. Cooling the ion to ultra-low temperatures by interacting with a laser-cooled ion will enhance the precision of the measurements. In this paper we present axial-common-mode frequency measurements of balanced and unbalanced Coulomb crystals from the Fourier transform of the fluorescence photons from a Doppler-cooling transition in calcium ions, after probing the ion/crystal with a 5-radiofrequency comb. A single ion non-destructively detected can be used for identification yielding a mass resolving power $m/\Delta m_\mathrm{FWHM}\approx 310$ from the axial common mode. This identification can be performed from a single measurement within times below one second., Comment: 6 pages, 4 figures

A strong increase of the reflection loss (from 25 up to 35 dBs) and an extension of the absorption bandwidth up to 20% under far-field real radar conditions are experimentally reported in this work by creating a functional bilayer system. Each layer consists of a composite material, typically a dielectric matrix filled with magnetic entities (powder or wires). Combining the two types of materials into a bilayer structure has shown unprecedented improvements in microwave absorption capacities compared to the former absorption of each layer. The potential of random magnets to create thin broadband absorbers is also demonstrated. The capacity to improve the shielding behavior is strongly related to each layer's permittivity, permeability, and thickness. This provides strong control over the design of novel materials for stealth applications.

We investigate the electronic structure and transport properties of twisted bilayer graphene (TBLG) at a twist angle of $\theta\approx 1.696\text{{\deg}}$. Using a combination of molecular dynamics and tight-binding calculations, we find two superlattice gaps in the energy spectrum of the bulk, which emerge close to the Fermi level from the atomic rearrangement of the carbon atoms leading to a corrugation of the graphene sheets. Nanoribbons made from 1.696{\deg}-TBLG show edge-localized states inside the superlattice gaps. Applying the Green's function method, we demonstrate that the edge states carry electronic current with conductance values close to the conductance quantum. The edge states can generate a non-local resistance, which is not due to one-way transport at the edges but due to the fact that these states are localized only at certain edges of the system, depending on how the nanoribbon has been cut from the bulk., Comment: 9 pages, 6 figures

The power grid is a critical infrastructure that allows for the efficient and robust generation, transmission, delivery and consumption of electricity. In the recent years, the physical components have been equipped with computing and network devices, which optimizes the operation and maintenance of the grid. The cyber domain of this smart power grid opens a new plethora of threats, which adds to classical threats on the physical domain. Accordingly, different stakeholders including regulation bodies, industry and academy, are making increasing efforts to provide security mechanisms to mitigate and reduce cyber-risks. Despite these efforts, there have been various cyberattacks that have affected the smart grid, leading in some cases to catastrophic consequences, showcasing that the industry might not be prepared for attacks from high profile adversaries. At the same time, recent work shows a lack of agreement among grid practitioners and academic experts on the feasibility and consequences of academic-proposed threats. This is in part due to inadequate simulation models which do not evaluate threats based on attackers full capabilities and goals. To address this gap, in this work we first analyze the main attack surfaces of the smart grid, and then conduct a threat analysis from the adversarial model perspective, including different levels of knowledge, goals, motivations and capabilities. To validate the model, we provide real-world examples of the potential capabilities by studying known vulnerabilities in critical components, and then analyzing existing cyber-attacks that have affected the smart grid, either directly or indirectly., Comment: Presented at the Workshop on Attackers and Cyber-Crime Operations (WACCO). More details available at https://wacco-workshop.org

Dimensional confinement has shown to be an effective strategy to tune competing degrees of freedom in complex oxides. Here, we achieved atomic layered growth of trigonal vanadium sesquioxide (V2O3) by means of oxygen-assisted molecular beam epitaxy. This led to a series of high-quality epitaxial ultrathin V2O3 films down to unit cell thickness, enabling the study of the intrinsic electron correlations upon confinement. By electrical and optical measurements, we demonstrate a dimensional confinement-induced metal-insulator transition in these ultrathin films. We shed light on the Mott-Hubbard nature of this transition, revealing an abrupt vanishing of the quasiparticle weight as demonstrated by photoemission spectroscopy. Furthermore, we prove that dimensional confinement acts as an effective out-of-plane stress. This highlights the structural component of correlated oxides in a confined architecture, while opening an avenue to control both in-plane and out-of-plane lattice components by epitaxial strain and confinement, respectively.

In the last decade, some algebraic tools have been successfully applied to phylogenetic reconstruction. These tools are mainly based on the knowledge of equations describing algebraic varieties associated to phylogenetic trees evolving under Markov processes of molecular substitution, the so called phylogenetic invariants. Although the theory involved allows to explicitly obtain these equations for all equivariant models (which include some of the most popular nucleotide substitution models), practical uses of these algebraic tools have been restricted to the case of the general Markov model. Arguably, one of the reasons for this restriction is that knowledge of linear representation theory is required before making these equations explicit. With the aim of enlarging the practical uses of algebraic phylogenetics, in this paper we prove that phylogenetic invariants for trees evolving under equivariant models can be derived from phylogenetic invariants for the general Markov model, without the need of representation theory. Our main result states that the algebraic variety corresponding to a phylogenetic tree evolving under an equivariant model is an irreducible component of the variety corresponding to the same tree under the general Markov model cut with the linear space defined by the model. We also prove that, for any equivariant model, those phylogenetic invariants that are relevant for practical uses (e.g. tree reconstruction) can be simply deduced from a single rank constraint on the matrices obtained by flattening the joint distribution at the leaves of the tree. This condition can be easily tested from singular values of the matrices and extends our results from trees to phylogenetic networks., Comment: 30 pages, 4 figures

Fe3C/few-layered graphene core/shell nanoparticles embedded in a carbon matrix are synthesized by a novel two-step surfactant sol-gel strategy, where the processes of hydrolysis, polycondensation and drying take place in a one-pot. The present approach is based on the combined action of oleic acid and oleylamine, which act sterically on the precursor micelles when a densification temperature is performed in a reducing atmosphere. The structural and magnetic evolution of the formed compounds is investigated, ranging from iron oxides such as Fe3O4 and FeO, to the formation of pure Fe3C/C samples from 700 {\deg}C onwards. Interestingly, Fe3C nanoparticles with a size of ~20 nm crystallize immersed in the carbon matrix and the surrounding environment forms an oriented encapsulation built by few-layered graphene. The nanostructures show a saturation magnetization of ~43 emu/g and a moderate coercivity of ~500 Oe. Thereby, an innovative chemical route to produce single phase Fe3C nanoparticles is described, and an effective method of few-layered graphene passivation is proposed, yielding a product with a high magnetic response and high chemical stability against environmental corrosion.

In this work we have investigated the effect of the solvent during the processing of SrFe12O19 platelet-based permanent magnets by cold sintering process (CSP) plus a post-thermal treatment. Several organic solvents: glacial acetic acid, oleic acid and oleylamine have been analyzed, optimizing the CSP temperatures at 190-270 {\deg}C, under pressures of 375-670 MPa and 6-50 wt% of solvent. Modifications in the morphological and structural properties are identified depending on the solvent, which impacts on the magnetic response. Independently of the solvent, the mechanical integrity of ferrite magnets obtained by CSP is improved by a post-annealing at 1100 {\deg}C for 2 h, resulting in relative densities around 92 % with an average grain size of 1 {\mu}m and a fraction of SrFe12O19 phase > 91 %. Hc > 2.1 kOe and MS of 73 emu/g are obtained in the final sintered ceramic magnets, exhibiting the highest HC value of 2.8 kOe for the magnet sintered using glacial acetic acid.

The incessant technological pursuit towards a more sustainable and green future depends strongly on permanent magnets. At present, their use is widespread, making it imperative to develop new processing methods that generate highly competitive magnetic properties reducing the fabrication temperatures and costs. Herein, a novel strategy for developing dense sintered magnets based on Sr-hexaferrites with upper functional characteristics is presented. An innovative cold sintering approach using glacial acetic acid as novelty, followed by a post-annealing at 1100 {\deg}C, achieves a densification of the ceramic magnets of 92% with respect to the theoretical density and allows controlling the particle growth. After the cold sintering process, a fraction of amorphous SrO is identified, in addition to a partial transformation to {\alpha}-Fe2O3 as secondary crystalline phase. 46 wt% of SrFe12O19 remains, which is mostly recuperated after the post-thermal treatment. These findings do not significantly modify the final structure of ferrite magnets, neither at short- nor long-range order. The innovative process has a positive impact on the magnetic properties, yielding competitive ferrite magnets at lower sintering temperatures with an energy efficiency of at least 25%, which opens up a new horizon in the field of rare-earth free permanent magnets and new possibilities in other applications.

The joint effects of Kekul\'e lattice distortions and Rashba-type spin-orbit coupling on the electronic properties of graphene are explored. We modeled the position dependence of the Rashba energy term in a manner that allows its seamless integration into the scheme introduced by Gamayun et al.[New J. Phys. 20, 023016 (2018)] to describe graphene with Kekul\'e lattice distortion. Particularly for the Kekul\'e-Y texture, the effective low energy Dirac Hamiltonian contains a new spin-valley locking term, in addition to the well-known Rashba-induced momentum-pseudospin and spin-pseudospin couplings, and the Kekul\'e-induced momentum-valley coupling term. We report on the low-energy band structure and Landau level spectra of Rashba-spin-orbit-coupled Kek-Y graphene, and propose an experimental scheme to discern between the presence of Rashba spin-orbit coupling, Kek-Y lattice distortion, and both, based on doping-dependent magnetotransport measurements., Comment: 14 pages, including 8 figures and 4 appendices

We study equivariant families of Dirac operators on the source fibers of a Lie groupoid with a closed space of units and equipped with an action of an auxiliary compact Lie group. We use the Getzler rescaling method to derive a fixed-point formula for the pairing of a trace with the K-theory class of such a family. For the pair groupoid of a closed manifold, our formula reduces to the standard fixed-point formula for the equivariant index of a Dirac operator. Further examples involve foliations and manifolds equipped with a normal crossing divisor., Comment: 51 pages. Brief section on proper actions of non-compact groups added. Simplification of the fixed-point calculation. Further explanation added to sections on group actions and vanishing theorem. Author information updated

Function-as-a-Service (FaaS) is a type of serverless computing that allows developers to write and deploy code as individual functions, which can be triggered by specific events or requests. FaaS platforms automatically manage the underlying infrastructure, scaling it up or down as needed, being highly scalable, cost-effective and offering a high level of abstraction. Prototypes being developed within the SKA Regional Center Network (SRCNet) are exploring models for data distribution, software delivery and distributed computing with the goal of moving and executing computation to where the data is. Since SKA will be the largest data producer on the planet, it will be necessary to distribute this massive volume of data to the SRCNet nodes that will serve as a hub for computing and analysis operations on the closest data. Within this context, in this work we want to validate the feasibility of designing and deploying functions and applications commonly used in radio interferometry workflows within a FaaS platform to demonstrate the value of this computing model as an alternative to explore for data processing in the distributed nodes of the SRCNet. We have analyzed several FaaS platforms and successfully deployed one of them, where we have imported several functions using two different methods: microfunctions from the CASA framework, which are written in Python code, and highly specific native applications like wsclean. Therefore, we have designed a simple catalogue that can be easily scaled to provide all the key features of FaaS in highly distributed environments using orchestrators, as well as having the ability to integrate them with workflows or APIs. This paper contributes to the ongoing discussion of the potential of FaaS models for scientific data processing, particularly in the context of large-scale, distributed projects such as SKA., Comment: 6

Homogeneity across lineages is a common assumption in phylogenetics according to which nucleotide substitution rates remain constant in time and do not depend on lineages. This is a simplifying hypothesis which is often adopted to make the process of sequence evolution more tractable. However, its validity has been explored and put into question in several papers. On the other hand, dealing successfully with the general case (heterogeneity across lineages) is one of the key features of phylogenetic reconstruction methods based on algebraic tools. The goal of this paper is twofold. First, we present a new weighting system for quartets (ASAQ) based on algebraic and semi-algebraic tools, thus specially indicated to deal with data evolving under heterogeneus rates. This method combines the weights two previous methods by means of a test based on the positivity of the branch length estimated with the paralinear distance. ASAQ is statistically consistent when applied to GM data, considers rate and base composition heterogeneity among lineages and does not assume stationarity nor time-reversibility. Second, we test and compare the performance of several quartet-based methods for phylogenetic tree reconstruction (namely, Quartet Puzzling, Weight Optimization and Wilson's method) in combination with ASAQ weights and other weights based on algebraic and semi-algebraic methods or on the paralinear distance. These tests are applied to both simulated and real data and support Weight Optimization with ASAQ weights as a reliable and successful reconstruction method., Comment: Main article: 25 pages, 6 figures, 4 tables; 1 appendix: 22 pages, 11 figures, 7 yables

A nanoelectronic device made of twisted bilayer graphene (TBLG) is proposed to steer the direction of the current flow. The ballistic electron current, injected at one edge of the bottom layer, can be guided predominantly to one of the lateral edges of the top layer. The current is steered to the opposite lateral edge, if either the twist angle is reversed or the electrons are injected in the valence band instead of the conduction band, making it possible to control the current flow by electric gates. When both graphene layers are aligned, the current passes straight through the system without changing its initial direction. The observed steering angle exceeds well the twist angle and emerges for a broad range of experimentally accessible parameters. It is explained by the trigonal shape of the energy bands beyond the van Hove singularity due to the Moir\'e interference pattern. As the shape of the energy bands depends on the valley degree of freedom, the steered current is partially valley polarized. Our findings show how to control and manipulate the current flow in TBLG. Technologically, they are of relevance for applications in twistronics and valleytronics., Comment: 10 pages, 10 figures

Scalable fabrication of magnetic 2D materials and heterostructures constitutes a crucial step for scaling down current spintronic devices and the development of novel spintronic applications. Here, we report on van der Waals (vdW) epitaxy of the layered magnetic metal Fe$_3$GeTe$_2$ - a 2D crystal with highly tunable properties and a high prospect for room temperature ferromagnetism - directly on graphene by employing molecular beam epitaxy. Morphological and structural characterization confirmed the realization of large-area, continuous Fe$_3$GeTe$_2$/graphene heterostructure films with stable interfaces and good crystalline quality. Furthermore, magneto-transport and X-ray magnetic circular dichroism investigations confirmed a robust out-of-plane ferromagnetism in the layers, comparable to state-of-the-art exfoliated flakes from bulk crystals. These results are highly relevant for further research on wafer-scale growth of vdW heterostructures combining Fe$_3$GeTe$_2$ with other layered crystals such as transition metal dichalcogenides for the realization of multifunctional, atomically thin devices.

The Large Intelligent Surface (LIS) is a promising technology in the areas of wireless communication, remote sensing and positioning. It consists of a continuous radiating surface located in the proximity of the users, with the capability to communicate by transmission and reception (replacing base stations). Despite of its potential, there are numerous challenges from implementation point of view, being the interconnection data-rate, computational complexity, and storage the most relevant ones. In order to address those challenges, hierarchical architectures with distributed processing techniques are envisioned to to be relevant for this task, while ensuring scalability. In this work we perform algorithm-architecture codesign to propose two distributed interference cancellation algorithms, and a tree-based interconnection topology for uplink processing. We also analyze the performance, hardware requirements, and architecture tradeoffs for a discrete LIS, in order to provide concrete case studies and guidelines for efficient implementation of LIS systems., Comment: Manuscript submitted for journal publication

We present the phylogenetic quartet reconstruction method SAQ (Semi-algebraic quartet reconstruction). SAQ is consistent with the most general Markov model of nucleotide substitution and, in particular, it allows for rate heterogeneity across lineages. Based on the algebraic and semi-algebraic description of distributions that arise from the general Markov model on a quartet, the method outputs normalized weights for the three trivalent quartets (which can be used as input of quartet-base methods). We show that SAQ is a highly competitive method that outperforms most of the well known reconstruction methods on data simulated under the general Markov model on 4-taxon trees. Moreover, it also achieves a high performance on data that violates the underlying assumptions.

Characterizing whether a Markov process of discrete random variables has an homogeneous continuous-time realization is a hard problem. In practice, this problem reduces to deciding when a given Markov matrix can be written as the exponential of some rate matrix (a Markov generator). This is an old question known in the literature as the embedding problem (Elfving37), which has been only solved for matrices of size $2\times 2$ or $3\times 3$. In this paper, we address this problem and related questions and obtain results in two different lines. First, for matrices of any size, we give a bound on the number of Markov generators in terms of the spectrum of the Markov matrix. Based on this, we establish a criterion for deciding whether a generic Markov matrix (different eigenvalues) is embeddable and propose an algorithm that lists all its Markov generators. Then, motivated and inspired by recent results on substitution models of DNA, we focus in the $4\times 4$ case and completely solve the embedding problem for any Markov matrix. The solution in this case is more concise as the embeddability is given in terms of a single condition.

A Markov matrix is embeddable if it can represent a homogeneous continuous-time Markov process. It is well known that if a Markov matrix has real and pairwise-different eigenvalues, then the embeddability can be determined by checking whether its principal logarithm is a rate matrix or not. The same holds for Markov matrices close enough to the identity matrix or that rule a Markov process subjected to certain restrictions. In this paper we prove that this criterion cannot be generalized and we provide open sets of Markov matrices that are embeddable and whose principal logarithm is a not a rate matrix.

Less rigid than phylogenetic trees, phylogenetic networks allow the description of a wider range of evolutionary events. In this note, we explain how to extend the rank invariants from phylogenetic trees to phylogenetic networks evolving under the general Markov model and the equivariant models., Comment: 5 pages, 1 figure. This paper will appear in Research Perspectives CRM Barcelona, Spring 2019, vol. 10, in Trends in Mathematics Springer-Birkhauser

Typical massive multiple-input multiple-output (MIMO) architectures consider a centralized approach, in which all baseband data received by each antenna has to be sent to a central processing unit (CPU) to be processed. Due to the enormous amount of antennas expected in massive MIMO base stations (BSs), the number of connections to the CPU required in centralized massive MIMO is not scalable. In recent literature decentralized approaches have been proposed to reduce the number of connections between the antennas and the CPU. However, the reduction in the connections to the CPU requires more outputs per antenna to be generated. We study the trade-off between number of connections to the CPU and number of outputs per antenna. We propose a generalized architecture that allows exploitation of this trade-off, and we define a novel matrix decomposition that allows lossless linear equalization within our proposed architecture., Comment: 6 pages, 4 figures, accepted at IEEE ICC 2020 workshop on scalable massive MIMO technologies for beyond 5G

The Large Intelligent Surface (LIS) concept has emerged recently as a new paradigm for wireless communication, remote sensing and positioning. It consists of a continuous radiating surface placed relatively close to the users, which is able to communicate with users by independent transmission and reception (replacing base stations). Despite of its potential, there are a lot of challenges from an implementation point of view, with the interconnection data-rate and computational complexity being the most relevant. Distributed processing techniques and hierarchical architectures are expected to play a vital role addressing this while ensuring scalability. In this paper we perform algorithm-architecture codesign and analyze the hardware requirements and architecture trade-offs for a discrete LIS to perform uplink detection. By doing this, we expect to give concrete case studies and guidelines for efficient implementation of LIS systems., Comment: Presented at IEEE ICC 2020

Modelling the substitution of nucleotides along a phylogenetic tree is usually done by a hidden Markov process. This allows to define a distribution of characters at the leaves of the trees and one might be able to obtain polynomial relationships among the probabilities of different characters. The study of these polynomials and the geometry of the algebraic varieties defined by them can be used to reconstruct phylogenetic trees. However, not all points in these algebraic varieties have biological sense. In this paper, we explore the extent to which adding semi-algebraic conditions arising from the restriction to parameters with statistical meaning can improve existing methods of phylogenetic reconstruction. To this end, our aim is to compute the distance of data points to algebraic varieties and to the stochastic part of these varieties. Computing these distances involves optimization by nonlinear programming algorithms. We use analytical methods to find some of these distances for quartet trees evolving under the Kimura 3-parameter or the Jukes-Cantor models. Numerical algebraic geometry and computational algebra play also a fundamental role in this paper., Comment: 33 pages; 11 figures; to appear in Journal of Symbolic Computation

The Large Intelligent Surface (LIS) concept is a promising technology aiming to revolutionize wireless communication by exploiting spatial multiplexing at its fullest. Despite of its potential, due to the size of the LIS and the large number of antenna elements involved there is a need of decentralized architectures together with distributed algorithms which can reduce the inter-connection data-rate and computational requirement in the Central Processing Unit (CPU). In this article we address the uplink detection problem in the LIS system and propose a decentralize architecture based on panels, which perform local linear processing. We also provide the sum-rate capacity for such architecture and derive an algorithm to obtain the equalizer, which aims to maximize the sum-rate capacity. A performance analysis is also presented, including a comparison to a naive approach based on a reduced form of the matched filter (MF) method. The results shows the superiority of the proposed algorithm.