Search

We propose an imaging method to enhance and reveal structures within samples by using a polarization-based filter. This filter removes the isotropic content while amplifying the anisotropic component of depolarization. Whereas isotropic depolarization leads to a complete loss of polarimetric information, the anisotropic one is connected with intrinsic characteristics of samples. The filter has the capability to diminish the isotropic depolarization of samples, revealing their inherent information. As representative cases, we analyze the effect of the filter in heart and brain sections of animal origin. Results highlight the outstanding performance of the filter. In heart, myocardial and subendocardial structures are better visualized, whereas in the brain, fiber tracts are identified. These proves the significance of this filter in the medical field, paving the way to the early detection of pathologies. The methodologies here presented could be applied in a wide range of applications, providing a significant advance in polarization imaging where high isotropic depolarization response is present, this being a common scenario in nature.

We establish general conditions for stochastic evolution equations with locally monotone drift and degenerate additive L\'evy noise in variational formulation resulting in the existence of a unique invariant measure for the associated weakly ergodic Markovian Feller semigroup. We prove improved moment estimates for the solutions and the so-called $e$-property of the semigroup. Examples include the stochastic incompressible 2D Navier-Stokes equations, shear thickening stochastic power-law fluid equations, the stochastic heat equation, as well as, stochastic semilinear equations such as the 1D stochastic Burgers equation., Comment: 43 pages, 80 references

We introduce the Data Analysis Pipeline (DAP) for the Sloan Digital Sky Survey V (SDSS-V) Local Volume Mapper (LVM) project, referred to as the LVM-DAP. We outline our methods for recovering both stellar and emission line components from the optical integral field spectroscopy, highlighting the developments and changes implemented to address specific challenges of the data set. The observations from the LVM project are unique because they cover a wide range of physical resolutions, from approximately 0.05 pc to 100 pc, depending on the distance to the targets. This, along with the varying number of stars sampled in each aperture (ranging from zero, just one of a few, to thousands), presents challenges in using previous spectral synthesis methods and interpreting the spectral fits. We provide a detailed explanation of how we model the stellar content and separate it from the ionized gas emission lines. To assess the accuracy of our results, we compare them with both idealized and more realistic simulations, highlighting the limitations of our methods. We find that the DAP robustly correct for stellar continuum features and recover emission line parameters (e.g. flux, equivalent width, systemtic velocity and velocity dispersion) with a precision and accuracy that fulfill the requirements of the primary goal of the analysis. In addition, the recovered stellar parameters are reliable for single stars, the recovery of integrated populations is less precise. We conclude with a description of the data products we provide, instructions for downloading and using our software, and a showcase illustrating the quality of the data and the analysis on a deep exposure taken on the Huygens region at the center of the Orion Nebula., Comment: 35 pages, 17 figures, 8 tables, accepted for publication in AJ

Given two real numbers $q_0,q_1$ with $q_0, q_1 > 1$ satisfying $q_0+q_1 \ge q_0q_1$, we call a sequence $(d_i)$ with $d_i\in \{0,1\}$ a $(q_0,q_1)$-expansion or a double-base expansion of a real number $x$ if \[ x=\mathop{\sum}\limits_{i=1}^{\infty} \frac{d_{i}}{q_{d_1}q_{d_2}\cdots q_{d_i}}. \] When $q_0=q_1=q$, the set of univoque bases is given by the set of $q$'s such that $x = 1$ has exactly one $(q, q)$-expansion. The topological, dimensional and symbolic properties of such sets and their corresponding sequences have been intensively investigated. In our research, we study the topological and dimensional properties of the set of univoque bases for double-base expansions. This problem is more complicated, requiring new research strategies. Several new properties are uncovered. In particular, we show that the set of univoque bases in the double base setting is a meagre set with full Hausdorff dimension.

Centraliser algebras of monomial representations of finite groups may be constructed and studied using methods similar to those employed in the study of permutation groups. Guided by results of D. G. Higman and others, we give an explicit construction for a basis of the centraliser algebra of a monomial representation. The character table of this algebra is then constructed via character sums over double cosets. We locate the theory of group-developed and cocyclic-developed Hadamard matrices within this framework. We apply Gr\"obner bases to produce a new classification of highly symmetric complex Hadamard matrices., Comment: 20 pages

This paper presents surface acoustic wave (SAW) acoustic delay lines (ADL) for studying propagation loss mechanisms in Lithium Niobate (LN). Devices were fabricated by depositing 50 nm aluminum patterns on 600 nm X-Cut LN on amorphous silicon on silicon carbide, where longitudinally dominant SAW was targeted. Upon fabrication, higher-order thickness-based cross-sectional Lam\'e modes and Rayleigh modes were studied for their Q factors using acoustic delay lines. Utilizing bi-directional electrodes, ADL with lateral lambda values ranging from 0.4 um to 0.6 um were measured. Higher order Lame modes were found to have consistently higher Q factors than their Rayleigh mode counterpart, on the order of 1000-3000, showing high-frequency SAW devices as still viable candidates for frequency scaling without a substantial increase in loss., Comment: 4 pages, 7 figures, accepted by IEEE UFFC-JS

Resilience refers to the ability of systems to withstand, adapt to, and recover from disruptive events. While studies on resilience have attracted significant attention across various research domains, the precise definition of this concept within the field of cooperative artificial intelligence remains unclear. This paper addresses this gap by proposing a clear definition of `cooperative resilience' and outlining a methodology for its quantitative measurement. The methodology is validated in an environment with RL-based and LLM-augmented autonomous agents, subjected to environmental changes and the introduction of agents with unsustainable behaviors. These events are parameterized to create various scenarios for measuring cooperative resilience. The results highlight the crucial role of resilience metrics in analyzing how the collective system prepares for, resists, recovers from, sustains well-being, and transforms in the face of disruptions. These findings provide foundational insights into the definition, measurement, and preliminary analysis of cooperative resilience, offering significant implications for the broader field of AI. Moreover, the methodology and metrics developed here can be adapted to a wide range of AI applications, enhancing the reliability and effectiveness of AI in dynamic and unpredictable environments., Comment: Supplementary material in https://github.com/mavivi95/resilience/blob/main/Supplementary_File.pdf

The paper investigates a generalization of the classical Sitnikov problem, concentrating on the movement of a satellite along the Z-axis as it interacts with $n$ primary bodies in periodic motion. It establishes the existence of an infinite number of even and anti-periodic solutions with increasing periods. The proof employs the Leray-Schauder degree theory to trace the critical points of action functionals, using a homotopy from solutions when the primary bodies are transformed into circular orbits., Comment: 21 pages, 2 figures

Classical shadow (CS) has opened the door to predicting the characteristics of quantum systems using very few measurements. As quantum systems grow in size, new ways to characterize them are needed to show the quality of their qubits, gates, and how noise affects them. In this work, we explore the capabilities of CS for reconstructing density state operators of sections of quantum devices to make a diagnostic of their qubits quality. We introduce zero-entropy classical shadow (ZECS), a methodology that focuses on reconstructing a positive semidefinite and unit trace density state operator using the CS information. This procedure makes a reliable reconstruction of the density state operator removing partially the errors associated with a limited sampling and quantum device noise. It gives a threshold of the maximum coherent information that qubits on a quantum device have. We test ZECS on ibm_lagos and ibm_brisbane using up to 10,000 shots. We show that with only 6,000 shots, we can make a diagnostic of the properties of groups of 2, 3, and 4 qubits on the 127-qubits ibm_brisbane device. We show two applications of ZECS: as a routing technique and as a detector for non-local noisy correlations. In the routing technique, an optimal set of 20 ibm_brisbane qubits is selected based on the ZECS procedure and used for a quantum optimization application. This method improves the solution quality by 10% and extends the quantum algorithm's lifetime by 33% when compared to the qubits chosen by the best transpilation procedure in Qiskit. Additionally, with the detector of non-local correlations, we identify regions of ibm\_brisbane that are not directly connected but have a strong correlation that maintains in time, suggesting some non-local crosstalk that can come, for example, at the multiplexing readout stage., Comment: 13 pages, 10 figures

We present a method to convert weather data into probabilistic forecasts of Aedes aegypti abundance. The approach, which relies on the Aedes-AI suite of neural networks, produces weekly point predictions with corresponding uncertainty estimates. Once calibrated on past trap and weather data, the model is designed to use weather forecasts to estimate future trap catches. We demonstrate that when reliable input data are used, the resulting predictions have high skill. This technique may therefore be used to supplement vector surveillance efforts or identify periods of elevated risk for vector-borne disease outbreaks.

We discuss the cold dark matter plus massive neutrinos simulations of the MillenniumTNG (MTNG) project, which aim to improve understanding of how well ongoing and future large-scale galaxy surveys will measure neutrino masses. Our largest simulations, $3000\,{\rm Mpc}$ on a side, use $10240^3$ particles of mass $m_{p} = 6.66\times 10^{8}\,h^{-1}{\rm M}_\odot$ to represent cold dark matter, and $2560^3$ to represent a population of neutrinos with summed mass $M_\nu = 100\,{\rm meV}$. Smaller volume runs with $\sim 630\,{\rm Mpc}$ also include cases with $M_\nu = 0\,\textrm{and}\, 300\,{\rm meV}$. All simulations are carried out twice using the paired-and-fixed technique for cosmic variance reduction. We evolve the neutrino component using the particle-based $\delta f$ importance sampling method, which greatly reduces shot noise in the neutrino density field. In addition, we modify the GADGET-4 code to account both for the influence of relativistic and mildly relativistic components on the expansion rate and for non-Newtonian effects on the largest represented simulation scales. This allows us to quantify accurately the impact of neutrinos on basic statistical measures of nonlinear structure formation, such as the matter power spectrum and the halo mass function. We use semi-analytic models of galaxy formation to predict the galaxy population and its clustering properties as a function of summed neutrino mass, finding significant ($\sim 10\%$) impacts on the cosmic star formation rate history, the galaxy mass function, and the clustering strength. This offers the prospect of identifying combinations of summary statistics that are optimally sensitive to the neutrino mass., Comment: 19 pages, 15 figures

This work reports an acoustic solidly mounted resonator (SMR) at 18.64 GHz, among the highest operating frequencies reported. The device is built in scandium aluminum nitride (ScAlN) on top of silicon dioxide (SiO2) and tantalum pentoxide (Ta2O5) Bragg reflectors on silicon (Si) wafer. The stack is analyzed with X-ray reflectivity (XRR) and high-resolution X-ray diffraction (HRXRD). The resonator shows a coupling coefficient (k2) of 2.0%, high series quality factor (Qs) of 156, shunt quality factor (Qp) of 142, and maximum Bode quality factor (Qmax) of 210. The third-order harmonics at 59.64 GHz is also observed with k2 around 0.6% and Q around 40. Upon further development, the reported acoustic resonator platform can enable various front-end signal-processing functions, e.g., filters and oscillators, at future frequency range 3 (FR3) bands., Comment: 5 pages, 9 figures, 5 tables

The advent of Large Language Models (LLMs) and Generative AI has revolutionized natural language applications across various domains. However, high-stakes decision-making tasks in fields such as medical, legal and finance require a level of precision, comprehensiveness, and logical consistency that pure LLM or Retrieval-Augmented-Generation (RAG) approaches often fail to deliver. At Elemental Cognition (EC), we have developed a neuro-symbolic AI platform to tackle these problems. The platform integrates fine-tuned LLMs for knowledge extraction and alignment with a robust symbolic reasoning engine for logical inference, planning and interactive constraint solving. We describe Cora, a Collaborative Research Assistant built on this platform, that is designed to perform complex research and discovery tasks in high-stakes domains. This paper discusses the multi-step inference challenges inherent in such domains, critiques the limitations of existing LLM-based methods, and demonstrates how Cora's neuro-symbolic approach effectively addresses these issues. We provide an overview of the system architecture, key algorithms for knowledge extraction and formal reasoning, and present preliminary evaluation results that highlight Cora's superior performance compared to well-known LLM and RAG baselines.

ExaGRyPE describes a suite of solvers for numerical relativity, based upon ExaHyPE 2, the second generation of our Exascale Hyperbolic PDE Engine. The presented generation of ExaGRyPE solves the Einstein equations in the CCZ4 formulation under a 3+1 foliation and focuses on black hole spacetimes. It employs a block-structured Cartesian grid carrying a higher-order order Finite Difference scheme with adaptive mesh refinement, it facilitates massive parallelism combining message passing, domain decomposition and task parallelism, and it supports the injection of particles into the grid as data probes or tracers. We introduce the ExaGRyPE-specific building blocks within ExaHyPE 2, and discuss its software architecture and compute-n-feel: For this, we formalize the creation of any specific simulation with ExaGRyPE as a sequence of lowering operations, where abstract logical tasks are successively broken into finer tasks until we obtain an abstraction level that can be mapped onto a C++ executable. The overall program logic is fully specified via a domain-specific Python interface, we map this logic onto a more detailed set of numerical tasks, subsequently lower this representation onto technical tasks that the underlying ExaHyPE engine uses to parallelize the application, before eventually the technical tasks are mapped onto task graphs including the actual PDE term evaluations, initial conditions, boundary conditions, and so forth. We end up with a rigorous separation of concerns which shields ExaGRyPE users from technical details and hence simplifies the development of novel physical models. We present the simulations and data for the gauge wave, static single black holes and rotating binary black hole systems, demonstrating that the code base is mature and usable. However, we also uncover domain-specific numerical challenges that need further study by the community in future work.

The C++ programming language and its cousins lean towards a memory-inefficient storage of structs: The compiler inserts helper bits into the struct such that individual attributes align with bytes, and it adds additional bytes aligning attributes with cache lines, while it is not able to exploit knowledge about the range of integers, enums or bitsets to bring the memory footprint down. Furthermore, the language provides neither support for data exchange via MPI nor for arbitrary floating-point precision formats. If developers need to have a low memory footprint and MPI datatypes over structs which exchange only minimal data, they have to manipulate the data and to write MPI datatypes manually. We propose a C++ language extension based upon C++ attributes through which developers can guide the compiler what memory arrangements would be beneficial: Can multiple booleans be squeezed into one bit field, do floats hold fewer significant bits than in the IEEE standard, or does the code require a user-defined MPI datatype for certain subsets of attributes? The extension offers the opportunity to fall back to normal alignment and padding rules via plain C++ assignments, no dependencies upon external libraries are introduced, and the resulting code remains standard C++. Our work implements the language annotations within LLVM and demonstrates their potential impact, both upon the runtime and the memory footprint, through smoothed particle hydrodynamics (SPH) benchmarks. They uncover the potential gains in terms of performance and development productivity.

This work reports the procedure for modeling piezoelectric acoustic resonators and filters at millimeter wave (mmWave). Different from conventional methods for lower frequency piezoelectric devices, we include both acoustic and electromagnetic (EM) effects, e.g., self-inductance, in both the circuit-level fitting and finite element analysis, toward higher accuracy at higher frequencies. To validate the method, thin-film lithium niobate (LiNbO3) first-order antisymmetric (A1) mode devices are used as the testbed, achieving great agreement for both the standalone resonators and a fifth-order ladder filter. Upon further development, the reported acoustic and EM co-modeling could guide the future design of compact piezoelectric devices at mmWave and beyond., Comment: 6 pages, 11 figures, submitted to IEEE JMEMS

The Orion Molecular Cloud complex, one of the nearest (D = 406 pc) and most extensively studied massive star-forming regions, is ideal for constraining the physics of stellar feedback, but its ~12 deg diameter on the sky requires a dedicated approach to mapping ionized gas structures within and around the nebula. The Sloan Digital Sky Survey (SDSS-V) Local Volume Mapper (LVM) is a new optical integral field unit (IFU) that will map the ionized gas within the Milky Way and Local Group galaxies, covering 4300 deg^2 of the sky with the new LVM Instrument. We showcase optical emission line maps from LVM covering 12 deg^2 inside of the Orion belt region, with 195,000 individual spectra combined to produce images at 0.07 pc (35.3") resolution. This is the largest IFU map made (to date) of the Milky Way, and contains well-known nebulae (the Horsehead Nebula, Flame Nebula, IC 434, and IC 432), as well as ionized interfaces with the neighboring dense Orion B molecular cloud. We resolve the ionization structure of each nebula, and map the increase in both the [SII]/Ha and [NII]/Ha line ratios at the outskirts of nebulae and along the ionization front with Orion B. [OIII] line emission is only spatially resolved within the center of the Flame Nebula and IC 434, and our ~0.1 pc scale line ratio diagrams show how variations in these diagnostics are lost as we move from the resolved to the integrated view of each nebula. We detect ionized gas emission associated with the dusty bow wave driven ahead of the star sigma Orionis, where the stellar wind interacts with the ambient interstellar medium. The Horsehead Nebula is seen as a dark occlusion of the bright surrounding photo-disassociation region. This small glimpse into Orion only hints at the rich science that will be enabled by the LVM., Comment: 13 pages, 10 figures, accepted for publication in A&A

The quantum approximate optimization algorithm (QAOA) is a promising algorithm for solving combinatorial optimization problems (COPs). In this algorithm, there are alternating layers consisting of a mixer and a problem Hamiltonian. Each layer $i=0,\ldots,p-1$ is parameterized by $\beta_i$ and $\gamma_i$. How to find these parameters has been an open question with the majority of the research focused on finding them using classical algorithms. In this work, we present evidence that fixed linear ramp schedules constitute a universal set of QAOA parameters, i.e., a set of $\gamma$ and $\beta$ parameters that rapidly approximate the optimal solution, $x^*$, independently of the COP selected, and that the success probability of finding it, $probability(x^*)$, increases with the number of QAOA layers $p$. We simulate linear ramp QAOA protocols (LR-QAOA) involving up to $N_q=42$ qubits and $p = 400$ layers on random instances of 9 different COPs. The results suggest that $probability(x^*) \approx 1/2^{(\eta N_q / p)}$ for a constant $\eta$. For example, when implementing LR-QAOA with $p=42$, the $probability(x^*)$ for 42-qubit Weighted MaxCut problems (W-MaxCut) increases from $2/2^{42}\approx 10^{-13}$ to an average of 0.13. We compare LR-QAOA, simulated annealing (SA), and branch-and-bound (B\&B) finding a scaling improvement in LR-QAOA. We test LR-QAOA on real hardware using IonQ Aria, Quantinuum H2-1, IBM Brisbane, IBM Kyoto, and IBM Osaka, encoding random weighted MaxCut (W-MaxCut) problems from 5 to 109 qubits and $p=3$ to $100$. Even for the largest case, $N_q=109$ qubits and $p=100$, information about the LR-QAOA optimization protocol is present. The circuit involved requires 21200 CNOT gates. These results show that LR-QAOA effectively finds high-quality solutions for a large variety of COPs and suggest a scaling advantage of quantum computation for combinatorial optimization.

As 5G connectivity proliferates, signal processing applications at 6G centimeter bands have gained attention for urban wireless capacity expansion. At sub-5 GHz, acoustic resonators operating in the fundamental symmetric (S0) Lamb mode hold significant promise if frequency scaled to the 6G centimeter bands. Concurrently, the lateral wavelength dependency and the traveling wave nature of S0 mode enable monolithic multi-frequency fabrication, transversal filters, correlators, and other compact signal processing components. In this work, we present thin-film lithium niobate (LN) S0 resonators scaled up to 16 GHz. Specifically, we study the characteristics of the S0 mode as the wavelength is minimized and showcase a device at 14.9 GHz with a Bode Q maximum of 391, a k2 of 6%, and a figure of merit (FoM) of 23.33, surpassing the state-of-the-art (SoA) in its frequency range., Comment: 4 pages, 8 figures, to be presetned in Hilton Head 2024,the 19th in the series of Hilton Head Workshops on the science and technology of solid-state sensors, actuators, and microsystems

Binary Neural Networks emerged as a cost-effective and energy-efficient solution for computer vision tasks by binarizing either network weights or activations. However, common binary activations, such as the Sign activation function, abruptly binarize the values with a single threshold, losing fine-grained details in the feature outputs. This work proposes an activation that applies multiple thresholds following dithering principles, shifting the Sign activation function for each pixel according to a spatially periodic threshold kernel. Unlike literature methods, the shifting is defined jointly for a set of adjacent pixels, taking advantage of spatial correlations. Experiments over the classification task demonstrate the effectiveness of the designed dithering Sign activation function as an alternative activation for binary neural networks, without increasing the computational cost. Further, DeSign balances the preservation of details with the efficiency of binary operations., Comment: 7 pages

We present the Sloan Digital Sky Survey V (SDSS-V) Local Volume Mapper (LVM). The LVM is an integral-field spectroscopic survey of the Milky Way, Magellanic Clouds, and of a sample of local volume galaxies, connecting resolved pc-scale individual sources of feedback to kpc-scale ionized interstellar medium (ISM) properties. The 4-year survey covers the southern Milky Way disk at spatial resolutions of 0.05 to 1 pc, the Magellanic Clouds at 10 pc resolution, and nearby large galaxies at larger scales totaling $>4300$ square degrees of sky, and more than 55M spectra. It utilizes a new facility of alt-alt mounted siderostats feeding 16 cm refractive telescopes, lenslet-coupled fiber-optics, and spectrographs covering 3600-9800A at R ~ 4000. The ultra-wide field IFU has a diameter of 0.5 degrees with 1801 hexagonally packed fibers of 35.3 arcsec apertures. The siderostats allow for a completely stationary fiber system, avoiding instability of the line spread function seen in traditional fiber feeds. Scientifically, LVM resolves the regions where energy, momentum, and chemical elements are injected into the ISM at the scale of gas clouds, while simultaneously charting where energy is being dissipated (via cooling, shocks, turbulence, bulk flows, etc.) to global scales. This combined local and global view enables us to constrain physical processes regulating how stellar feedback operates and couples to galactic kinematics and disk-scale structures, such as the bar and spiral arms, as well as gas in- and out-flows., Comment: 29 pages, 12 figures, accepted for publication in The Astronomical Journal

In this paper, the construction of $C^{1}$ cubic quasi-interpolants on a three-direction mesh of $\RR^{2}$ is addressed. The quasi-interpolating splines are defined by directly setting their Bernstein-B\'{e}zier coefficients relative to each triangle from point and gradient values in order to reproduce the polynomials of the highest possible degree. Moreover, additional global properties are required. Finally, we provide some numerical tests confirming the approximation properties.

We prove a version of the Thom Isotopy Theorem for nonproper semialgebraic maps $f\colon X\rightarrow \mathbb{R}^m$, where $X \subset\mathbb{R}^n$ is a semialgebraic set and $f$ is the restriction to $X$ of a smooth semialgebraic map $F:\mathbb{R}^n\to \mathbb{R}^m$.

Transformation optics applied to low frequency magnetic systems has been recently implemented to design magnetic field concentrators and cloaks with superior performance. Although this achievement has been amply demonstrated theoretically and experimentally in bulk 3D macrostructures, the performance of these devices at low dimensions remains an open question. In this work, we numerically investigate the non-monotonic evolution of the gain of a magnetic metamaterial field concentrator as the axial dimension is progressively shrunk. In particular, we show that in planar structures the role played by the diamagnetic components becomes negligible, whereas the paramagnetic elements increase their magnetic field channeling efficiency. This is further demonstrated experimentally by tracking the gain of superconductor-ferromagnet concentrators through the superconducting transition. Interestingly, for thicknesses where the diamagnetic petals play an important role for the concentration gain, they also help to reduce the stray field of the concentrator, thus limiting the perturbation of the external field (invisibility). Our findings establish a roadmap and set clear geometrical limits for designing low dimensional magnetic field concentrators.

Gravitational waves from black-hole merging events have revealed a population of extra-galactic BHs residing in short-period binaries with masses that are higher than expected based on most stellar evolution models - and also higher than known stellar-origin black holes in our Galaxy. It has been proposed that those high-mass BHs are the remnants of massive metal-poor stars. Gaia astrometry is expected to uncover many Galactic wide-binary systems containing dormant BHs, which may not have been detected before. The study of this population will provide new information on the BH-mass distribution in binaries and shed light on their formation mechanisms and progenitors. As part of the validation efforts in preparation for the fourth Gaia data release (DR4), we analysed the preliminary astrometric binary solutions, obtained by the Gaia Non-Single Star pipeline, to verify their significance and to minimise false-detection rates in high-mass-function orbital solutions. The astrometric binary solution of one source, Gaia BH3, implies the presence of a 32.70 \pm 0.82 M\odot BH in a binary system with a period of 11.6 yr. Gaia radial velocities independently validate the astrometric orbit. Broad-band photometric and spectroscopic data show that the visible component is an old, very metal-poor giant of the Galactic halo, at a distance of 590 pc. The BH in the Gaia BH3 system is more massive than any other Galactic stellar-origin BH known thus far. The low metallicity of the star companion supports the scenario that metal-poor massive stars are progenitors of the high-mass BHs detected by gravitational-wave telescopes. The Galactic orbit of the system and its metallicity indicate that it might belong to the Sequoia halo substructure. Alternatively, and more plausibly, it could belong to the ED-2 stream, which likely originated from a globular cluster that had been disrupted by the Milky Way., Comment: 23 pages, accepted fro publication in A&A Letters. New version with small fixes