Miracle-dz/UniFAR-FTUs huggingface dataset:
Core-level x-ray photoemission and Raman spectroscopy studies on electronic structures in Mott-Hubbard type nickelate oxide NdNiO$_2$

We perform core-level X-ray photoemission spectroscopy (XPS) and electronic Raman scattering studies of electronic structures and spin fluctuations in the bulk samples of the nickelate oxide NdNiO$_2$. According to Nd $3d$ and O $1s$ XPS spectra, we conclude that NdNiO$_2$ has a large transfer energy. From the analysis of the main line of the Ni $2p_{3/2}$ XPS, we confirm the NiO$_2$ planes in NdNiO$_2$ are of Mott-Hubbard type in the Zaanen-Sawatzky-Allen scheme. The two-magnon peak in the Raman scattering provides direct evidence for the strong spin-fluctuation in NdNiO$_2$. The peak position determines the antiferromagnetic exchange $J=25$~meV. Our experimental results agree well with our previous theoretical results.
Gravitomagnetic tidal resonance in neutron-star binary inspirals

A compact binary system implicating at least one rotating neutron star undergoes gravitomagnetic tidal resonances as it inspirals toward its final merger. These have a dynamical impact on the phasing of the emitted gravitational waves. The resonances are produced by the inertial modes of vibration of the rotating star. Four distinct modes are involved, and the resonances occur within the frequency band of interferometric gravitational-wave detectors when the star spins at a frequency that lies within this band. The resonances are driven by the gravitomagnetic tidal field created by the companion star; this is described by a post-Newtonian vector potential, which is produced by the mass currents associated with the orbital motion. These resonances were identified previously by Flanagan and Racine [Phys. Rev. D 75, 044001 (2007)], but these authors accounted only for the response of a single mode, the r-mode, a special case of inertial modes. All four relevant modes are included in the analysis presented in this paper. The total accumulated gravitational-wave phase shift is shown to range from approximately $10^{-2}$ radians when the spin and orbital angular momenta are aligned, to approximately $10^{-1}$ radians when they are anti-aligned. Such phase shifts will become measurable in the coming decades with the deployment of the next generation of gravitational-wave detectors (Cosmic Explorer, Einstein Telescope); they might even come to light within this decade, thanks to planned improvements in the current detectors. With good constraints on the binary masses and spins gathered from the inspiral waveform, the phase shifts deliver information regarding the internal structure of the rotating neutron star, and therefore on the equation of state of nuclear matter.
Efficient Behavior-aware Control of Automated Vehicles at Crosswalks using Minimal Information Pedestrian Prediction Model

For automated vehicles (AVs) to reliably navigate through crosswalks, they need to understand pedestrians’ crossing behaviors. Simple and reliable pedestrian behavior models aid in real-time AV control by allowing the AVs to predict future pedestrian behaviors. In this paper, we present a Behavior-aware Model Predictive Controller (B-MPC) for AVs that incorporates long-term predictions of pedestrian crossing behavior using a previously developed pedestrian crossing model. The model incorporates pedestrians’ gap acceptance behavior and utilizes minimal pedestrian information, namely their position and speed, to predict pedestrians’ crossing behaviors. The B-MPC controller is validated through simulations and compared to a rule-based controller. By incorporating predictions of pedestrian behavior, the B-MPC controller is able to efficiently plan for longer horizons and handle a wider range of pedestrian interaction scenarios than the rule-based controller. Results demonstrate the applicability of the controller for safe and efficient navigation at crossing scenarios.
Satellite Alignment. III. Satellite Galaxies’ Spatial Distribution and Their Dependence on Redshift with a Novel Galaxy Finder

After extensively explored, broad agreement between observations and theories has been reached that satellites are preferentially aligned with major axes of their host centrals. There are still some issues unsolved on this topic. In this paper, we present studies on satellite spatial distribution. To fairly compare with observations, we develop a novel galaxy finder and reconstruction algorithm in hydrodynamical simulation, which is based on the projected mock image, taking into account the full consideration of the point spread function, pixel size, surface brightness limit, resolution and redshift dimming effects. With galaxy samples constructed using such an algorithm, the satellite alignment is examined by comparing with observational results. It is found that the observational alignment can be reproduced for red galaxies, which dominate the sample in this study, but not for blue galaxies. Satellites' radial distribution is also investigated. It exhibits that outer satellites within host halos show stronger alignment signal than satellites in the inner regions, especially for red satellites, which is in contrast with previous studies. The disagreement is mainly due to extra galaxies identified by our new galaxy finder, which are mainly located in the inner region of host halos. Our study illustrates that at lower redshift, the alignment strength becomes stronger, while radial distribution curve becomes flatter. This suggests differences in the evolution of the angular distribution between satellites residing in the inner and outer halos, and implies that the post-infall evolution reduces the original alignment signal, that the impact decreases for satellites with later infall times.
Back-reaction in massless de Sitter QFTs: holography, gravitational DBI action and f(R) gravity

We employ gauge-gravity duality to study the backreaction effect of 4-dimensional large-N quantum field theories on constant-curvature backgrounds, and in particular de Sitter space-time. The field theories considered are holographic QFTs, dual to RG flows between UV and IR CFTs. We compute the holographic QFT contribution to the gravitational effective action for 4d Einstein manifold backgrounds. We find that for a given value of the cosmological constant λ, there generically exist two backreacted constant-curvature solutions, as long as λ < λmax ∼ Mp2 / N2, otherwise no such solutions exist. Moreover, the backreaction effect interpolates between that of the UV and IR CFTs. We also find that, at finite cutoff, a holographic theory always reduces the bare cosmological constant, and this is the consequence of thermodynamic properties of the partition function of holographic QFTs on de Sitter.
Self-gravitating barotropic equilibrium configurations of rotating bodies with smoothed particle hydrodynamics

Context. Self-gravitational rotating bodies do not have spherically symmetric geometries. The study of physical events appearing in fast-spinning compact stars and accretion disks, for example those due to localized thermonuclear ignitions in white dwarfs or to the role played by hydrodynamic instabilities in stars and disks, often requires 3D simulations. When the numerical simulations are carried out with the smoothed particle hydrodynamics (SPH) technique a critical point arises as to how to build a stable initial model with rotation because there is no well-established method for that purpose. Aims. We want to provide a portable, easy-to-implement methodology for SPH simulations to procedurally generate physically sound, stable initial conditions for rotating bodies. Methods. We explain and validate an easy and versatile novel relaxation method to obtain 3D equilibrium configurations of rotating bodies with SPH. As detailed below, this method is able to relax barotropic, P(ρ), structures either in rigid or differential rotation. The relaxation procedure strongly relies on the excellent conservation of angular momentum that characterizes the SPH technique. Results. We applied our proposal to obtain stable rotating structures of single white dwarfs, compact binaries harboring two white dwarfs, high-density stars approached as polytropes and accretion disks either in rigid or differential rotation. Conclusions. We present a novel relaxation method to build 3D rotating structures of barotropic bodies using the SPH technique. The method has been successfully applied to a variety of zero-temperature white dwarfs and polytropic self-gravitating structures. Our SPH results have been validated by comparing the main features (energies, central densities, and the polar-to-equatorial radius ratio) to those obtained with independent grid-based methods, for example, the self-consistent field method, showing that both methods agree within a few percent.
SOLOv2: Dynamic, Faster and Stronger

In this work, we aim at building a simple, direct, and fast instance segmentation framework with strong performance. We follow the principle of the SOLO method of Wang et al. "SOLO: segmenting objects by locations". Importantly, we take one step further by dynamically learning the mask head of the object segmenter such that the mask head is conditioned on the location. Specifically, the mask branch is decoupled into a mask kernel branch and mask feature branch, which are responsible for learning the convolution kernel and the convolved features respectively. Moreover, we propose Matrix NMS (non maximum suppression) to significantly reduce the inference time overhead due to NMS of masks. Our Matrix NMS performs NMS with parallel matrix operations in one shot, and yields better results. We demonstrate a simple direct instance segmentation system, outperforming a few state-of-the-art methods in both speed and accuracy. A light-weight version of SOLOv2 executes at 31.3 FPS and yields 37.1% AP. Moreover, our state-of-the-art results in object detection (from our mask byproduct) and panoptic segmentation show the potential to serve as a new strong baseline for many instance-level recognition tasks besides instance segmentation. Code is available at: this https URL
Distributed Optimization with Uncertain Communications

We consider the distributed optimization problem for the sum of convex functions where the underlying communications network connecting agents at each time is drawn at random from a collection of directed graphs. We propose a modified version of the subgradient-push algorithm that is provably almost surely convergent to an optimizer on any such sequence of random directed graphs. We also find an upper bound of the order of $\sim O(\frac{1}{\sqrt{t}})$ on the convergence rate of our proposed algorithm, establishing the first convergence bound in such random settings.
Asymptotics for two-dimensional vectorial Allen-Cahn systems

The formation of codimension-one interfaces for multi-well gradient-driven problems is well-known and established in the scalar case, where the equation is often referred to as the Allen-Cahn equation. The proofs rely for a large on a monotonicity formula for the energy density, which is itself related to the vanishing of the so-called discrepancy function. The vectorial case in contrast is quite open. This lack of results and insight is to a large extend related to the absence of known appropriate monotonicity formula. In this paper, we focus on the \emph{elliptic case in two dimensions}, and introduce methods, relying on the analysis of the partial differential equation, which allow to circumvent the lack of monotonicity formula for the energy density. In the last part of the paper, we recover a \emph{new monotonicity formula} which relies on a \emph{new discrepancy relation}. These tools allow to extend to the vectorial case in two dimensions most of the results obtained for the scalar case. We emphasize also some \emph{specific features} of the vectorial case.
A case study investigation of summer temperature conditions at two coastal sites in the UK, and analysis of future temperatures and heat wave structures in a warming climate scenario

Using observations for two UK coastal sites 25% increase in the number of summer days when the maximum temperature exceeds 25°C, a 60% increase when the temperature exceeds the minimum of 13°C, (Tables 3, 4) and an increase in heat wave events per annum of greater than 10 days, [Gadian et al. 2018]. The increases in summer temperatures are larger than those predicted in the 2013 IPCC assessment [Collins et al 2013], but consistent with the maximum temperatures and increased number of hot days listed in UKCP18 [Met Office 2019(b)]. The higher resolution model results suggest that the IPCC report underestimates the increases in maximum temperatures at these locations.
Exploring the nature and synchronicity of early cluster formation in the Large Magellanic Cloud – V. Multiple populations in ancient globular clusters

We examine four ancient Large Magellanic Cloud (LMC) globular clusters (GCs) for evidence of multiple stellar populations using the Advanced Camera for Surveys and Wide Field Camera 3 on the Hubble Space Telescope Programme GO-14164. NGC 1466, NGC 1841, and NGC 2257 all show evidence for a redder, secondary population along the main-sequence. Reticulum does not show evidence for the presence of a redder population, but this GC has the least number of stars and Monte Carlo simulations indicate that the sample of main sequence stars is too small to robustly infer whether a redder population exists in this cluster. The second, redder, population of the other three clusters constitutes $\sim30-40\%$ of the total population along the main-sequence. This brings the total number of ancient LMC GCs with known split or broadened main-sequences to five. However, unlike for Hodge 11 and NGC 2210 (see arXiv:1904.01434), none of the clusters show evidence for multiple populations in the horizontal branch. We also do not find evidence of a second population along the Red Giant Branch (RGB).
Resilience in Collaborative Optimization: Redundant and Independent Cost Functions

This report considers the problem of Byzantine fault-tolerance in multi-agent collaborative optimization. In this problem, each agent has a local cost function. The goal of a collaborative optimization algorithm is to compute a minimum of the aggregate of the agents' cost functions. We consider the case when a certain number of agents may be Byzantine faulty. Such faulty agents may not follow a prescribed algorithm, and they may send arbitrary or incorrect information regarding their local cost functions. A reasonable goal in presence of such faulty agents is to minimize the aggregate cost of the non-faulty agents. In this report, we show that this goal can be achieved if and only if the cost functions of the non-faulty agents have a minimal redundancy property. We present different algorithms that achieve such tolerance against faulty agents, and demonstrate a trade-off between the complexity of an algorithm and the properties of the agents' cost functions. Further, we also consider the case when the cost functions are independent or do not satisfy the minimal redundancy property. In that case, we quantify the tolerance against faulty agents by introducing a metric called weak resilience. We present an algorithm that attains weak resilience when the faulty agents are in the minority and the cost functions are non-negative.
Centrality Dependence of Chemical Freeze-Out Parameters and Strangeness Equilibration in RHIC and LHC Energies

We have estimated chemical freeze-out parameters from data of rapidity spectra for $\pi^\pm$, $k^\pm$ and $p$, $\bar{p}$ at BES, RHIC and LHC and studied their variation with the centrality. We have considered a simple hadron resonance gas model and employed a formalism involving conserved charges ($B, Q, S$) of QCD for parameterization. Along with temperature and three chemical potentials ($T,\mu_B,\mu_Q,\mu_S$), a strangeness undersaturation factor ($\gamma_S$) has been used to incorporate the partial equilibrium in the strangeness sector. Our obtained freeze-out temperature does not vary much with centrality, whereas chemical potentials and $\gamma_S$ seem to have a significant dependence. For the peripheral collisions, the strange hadrons are found to deviate from a complete chemical equilibrium at freeze-out. This deviation appears to be more prominent as the collision energy decreases at lower BES energies. We have also shown that this departure from equilibrium decreases towards central collisions and strange particle equilibration may happen after a threshold number of participants in $A$-$A$ collision.
WIYN Open Cluster Study. LXXXII. Radial-velocity Measurements and Spectroscopic Binary Orbits in the Open Cluster NGC 7789

We present an extensive time-series radial-velocity (RV) survey of stars in the rich open cluster NGC 7789 (1.6 Gyr, [Fe/H] = +0.02). The stellar sample lies within an 18′ circular radius from the cluster center (10 pc in projection, or about 2 core radii), and includes giants, red clump stars, blue stragglers, red stragglers, sub-subgiants, and main-sequence stars down to 1 mag below the turnoff. Our survey began in 2005 and comprises more than 9000 RV measurements from the Hydra Multi-Object Spectrograph on the WIYN 3.5 m telescope. We identify 624 likely cluster members and present the orbital solutions for 81 cluster binary stars with periods between 1.45 and 4200 days. From the main-sequence binary solutions we fit a circularization period of days. We calculate an incompleteness-corrected main-sequence binary frequency of 31% ± 4% for binaries with periods less than 104 days, similar to other WIYN Open Cluster Survey (WOCS) open clusters of all ages. We detect a blue straggler binary frequency of 33% ± 17%, consistent with the similarly aged open cluster NGC 6819. We also find one secure, rapidly rotating sub-subgiant and one red straggler candidate in our sample.
HDF: Hybrid Deep Features for Scene Image Representation

Nowadays it is prevalent to take features extracted from pre-trained deep learning models as image representations which have achieved promising classification performance. Existing methods usually consider either object-based features or scene-based features only. However, both types of features are important for complex images like scene images, as they can complement each other. In this paper, we propose a novel type of features – hybrid deep features, for scene images. Specifically, we exploit both object-based and scene-based features at two levels: part image level (i.e., parts of an image) and whole image level (i.e., a whole image), which produces a total number of four types of deep features. Regarding the part image level, we also propose two new slicing techniques to extract part based features. Finally, we aggregate these four types of deep features via the concatenation operator. We demonstrate the effectiveness of our hybrid deep features on three commonly used scene datasets (MIT-67, Scene-15, and Event-8), in terms of the scene image classification task. Extensive comparisons show that our introduced features can produce state-of-the-art classification accuracies which are more consistent and stable than the results of existing features across all datasets.
Magnetic Particle Spectroscopy: A Short Review of Applications Using Magnetic Nanoparticles

Magnetic particle spectroscopy (MPS), also called magnetization response spectroscopy, is a novel measurement tool derived from magnetic particle imaging (MPI). It can be interpreted as a zero-dimensional version of MPI scanner. MPS was primarily designed for characterizing superparamagnetic iron oxide nanoparticles (SPIONs) regarding their applicability for MPI. In recent years, it has evolved into an independent, versatile, highly sensitive, inexpensive platform for biological and biomedical assays, cell labeling and tracking, and blood analysis. MPS has also developed into an auxiliary tool for magnetic imaging and hyperthermia by providing high spatial and temporal mappings of temperature and viscosity. Furthermore, other MPS-based applications are being explored such as magnetic fingerprints for product tracking and identification in supply chains. There are a variety of novel MPS-based applications being reported and demonstrated by many groups. In this short review, we highlighted some of the representative applications based on MPS platform, thereby providing a roadmap of this technology and our insights for researchers in this area.
Census of the Young Stellar Population in the Galactic H ii Region Sh2-242

We present here identification and characterization of the young stellar population associated with an active star-forming site Sh2-242. We used our own new optical imaging and spectroscopic observational data, as well as several archival catalogs, e.g., Pan-STARRS 1, Gaia DR2, IPHAS, Wide-field InfraRed Camera, 2MASS, and Spitzer. Slit spectroscopic results confirm the classification of the main ionizing source BD+26 980 as an early-type star of spectral type B0.5 V. The spectrophotometric distance of the star is estimated as 2.08 ± 0.24 kpc, which confirms the source as a member of the cluster. An extinction map covering a large area (diameter ∼50′) is generated with H and K photometry toward the region. From the map, three distinct locations of peak extinction complexes (AV ≃ 7–17 mag) are identified for the very first time. Using the infrared color excess, a total of 33 Class I and 137 Class II young objects are classified within the region. The IPHAS photometry reveals classification of 36 Hα emitting sources, which might be class II objects. Among 36 Hα emitting sources, 5 are already identified using infrared excess emission. In total, 201 young objects are classified toward S242 from this study. The membership status of the young sources is further windowed with the inclusion of parallax from the Gaia DR2 catalog. Using the optical and infrared color–magnitude diagrams, the young stellar objects are characterized with an average age of ∼1 Myr and masses in the range 0.1–3.0 M☉. The census of the stellar content within the region is discussed using combined photometric and spectroscopic data.
A Developmental Neuro-Robotics Approach for Boosting the Recognition of Handwritten Digits

Developmental psychology and neuroimaging research identified a close link between numbers and fingers, which can boost the initial number knowledge in children. Recent evidence shows that a simulation of the children’s embodied strategies can improve the machine intelligence too. This article explores the application of embodied strategies to convolutional neural network models in the context of developmental neurorobotics, where the training information is likely to be gradually acquired while operating rather than being abundant and fully available as the classical machine learning scenarios. The experimental analyses show that the proprioceptive information from the robot fingers can improve network accuracy in the recognition of handwritten Arabic digits when training examples and epochs are few. This result is comparable to brain imaging and longitudinal studies with young children. In conclusion, these findings also support the relevance of the embodiment in the case of artificial agents’ training and show a possible way for the humanization of the learning process, where the robotic body can express the internal processes of artificial intelligence making it more understandable for humans.