Miracle-dz/UniFAR-FTUs huggingface dataset:
Impurity potential renormalization by strong electron correlation

Renormalization of non-magnetic impurity potential by strong electron correlation is investigated in detail. We adopt the t-t'-t"-J model and consider mainly a delta-function impurity potential. The variational Monte Carlo method shows that impurity potential scattering matrix elements between Gutzwiller-projected quasi-particle excited states are as strongly renormalized as the hopping terms. Such renormalization is also seen by the Bogoliubov-de Gennes equation with an impurity, where the strong correlation is treated by a Gutzwiller mean-field theory with local Gutzwiller factors and local chemical potentials. Namely, the delta-function potential is effectively weakened and broadened. We emphasize the importance of including the local chemical potential, which is paid little attention to in the literature, by physical consideration of the doping dependence of a local hole density. We also investigate effect of smooth impurity potential variation; the strong correlation yields anticorrelation between the gap energy and the coherence peak height simultaneously with large gap distribution, which is consistent with the experiments.
QUANTIFYING AND PREDICTING THE PRESENCE OF CLOUDS IN EXOPLANET ATMOSPHERES

One of the most outstanding issues in exoplanet characterization is understanding the prevalence of obscuring clouds and hazes in their atmospheres. The ability to predict the presence of clouds/hazes a priori is an important goal when faced with limited telescope resources and advancements in atmospheric characterization that rely on the detection of spectroscopic features. As a means to identify favorable targets for future studies with Hubble Space Telescope (HST) and James Webb Space Telescope, we use published HST/WFC3 transmission spectra to determine the strength of each planet's water feature, as defined by the H2O – J index. By expressing this parameter in units of atmospheric scale height, we provide a means to efficiently compare the size of spectral features over a physically diverse sample of exoplanets. We find the H2O – J index to be strongly correlated with planet temperature when Teq < 750 − 60 + 90 ? > K and weakly correlated with surface gravity for planets with log g < 3.2 − 0.2 + 0.3 ? > dex. Otherwise, the median value of the H2O – J index is 1.8 ± 0.3 H. Using these two physical parameters, we identify a division between “classes” of exoplanets, such that objects above Teq = 700 K and log g = 2.8 ? > dex are more likely to have clearer atmospheres with stronger spectral features (H2O – J > 1) and those below at least one of these thresholds are increasingly likely to have predominantly cloudy atmospheres with muted spectral features (H2O – J < 1). Additional high-precision measurements are needed to corroborate the reported trends.
No firewalls in quantum gravity: the role of discreteness of quantum geometry in resolving the information loss paradox

In an approach to quantum gravity where space-time arises from coarse graining of fundamentally discrete structures, black hole formation and subsequent evaporation can be described by a unitary evolution without the problems encountered by the standard remnant scenario or the schemes where information is assumed to come out with the radiation during evaporation (firewalls and complementarity). The final state is purified by correlations with the fundamental pre-geometric structures (in the sense of Wheeler), which are available in such approaches, and, like defects in the underlying space-time weave, can carry zero energy.
Towards a Low-Cost Object Collecting and Organizing Household Robot using Deep Learning

Recent advances in deep learning algorithms, and the availability of low-cost sensors, processors, and actuators are opening up a new opportunity for making household robots with a limited budget. Household robots can help automate the monotonous tasks of daily life such as putting dishes in the dishwasher, folding the laundry after washing, cleaning the floor, and organizing kids’ toys on the shelf at the end of the day. In this paper, a robot has been developed that can detect and recognize an object using deep learning from images, move toward the object scoops and lifts the object, and then puts the object to its assigned level on a shelf. This robot can be used to collect and organize objects such as toys, in the kid’s room. A deep learning model is trained with a custom dataset and the mean average precision (mAP) of the object detector is 79.1%. A prototype of the robot - with mechanical structure, camera, motors, controller, and image processing algorithms - is developed and tested successfully.
Young stellar structures in four nearby galaxies

A cluster finding method was developed and applied in four Local Group Galaxies (SMC, M31, M33 and NGC 6822). The aim is to study the young stellar population of these galaxies by identifying stellar structures in small and large scales. Also our aim is to assess the potential of using the observations of ESA's space mission Gaia for the study of nearby galaxies resolved in stars. The detection method used is a Hierarchical technique based on a modified friends of friends algorithm. The identified clusters are classified in five distinct categories according to their size. The data for our study were used from two ground based surveys, the Local Group Galaxy Survey and the Maggelanic Clouds Spectroscopic Survey. Relatively young main sequence stars were selected from the stellar catalogs and were used by the detection algorithm. Multiple young stellar structures were identified in all galaxies with size varying from very small scales of a few pc up to scales larger than 1 kpc. The same cluster finding method was used in six spiral galaxies observed with the Hubble Space Telescope in a previous study. The average size in each category of the identified structures in the Local Group galaxies presents values consistent with the identified structures in the relatively distant spiral galaxies. Most of the structures consist of stars within the observational limits of Gaia's instruments. It is expected that Gaia's observations will contribute significantly on the study of the young stellar population of nearby galaxies.
Notes on spreads of degrees in graphs

Perhaps the very first elementary exercise one encounters in graph theory is the result that any graph on at least two vertices must have at least two vertices with the same degree. There are various ways in which this result can be non-trivially generalised. For example, one can interpret this result as saying that in any graph $G$ on at least two vertices there is a set $B$ of at least two vertices such that the difference between the largest and the smallest degrees (in $G$) of the vertices of $B$ is zero. In this vein we make the following definition. For any $B\subset V(G)$, let the spread $sp(B)$ of $B$ be defined to be the difference between the largest and the smallest of the degrees of the vertices in $B$. For any $k\geq 0$, let $sp(G,k)$ be the largest cardinality of a set of vertices $B$ such that $sp(B)\leq k$. Therefore the first elementary result in graph theory says that, for any graph $G$ on at least two vertices, $sp(G,0)\geq 2$. In this paper we first give a proof of a result of Erd\" os, Chen, Rousseau and Schelp which generalises the above to $sp(G,k)\geq k+2$ for any graph on at least $k+2$ vertices. Our proof is short and elementary and does not use the famous Erd\" os-Gallai Theorem on vertex degrees. We then develop lower bounds for $sp(G,k)$ in terms of the order of $G$ and its minimum, maximum and average degree. We then use these results to give lower bounds on $sp(G,k)$ for trees and maximal outerplanar graphs, most of which we show to be sharp.
An initial assessment of plankton tow detection probabilities for dreissenid mussels in the western United States

Early detection of dreissenid mussels ( Dreissena polymorpha and D. rostriformis bugensis ) is crucial to mitigating the economic and environmental impacts of an infestation. Plankton tow sampling is a common method used for early detection of dreissenid mussels, but little is known about the sampling intensity required for a high probability of early detection using the method. We used implicit dynamic occupancy models to estimate plankton tow detection probabilities of dreissenid mussels from a long-term data set containing plankton tow samples collected across central and western United States. We fit models using a) the entire data set, including water bodies with unknown occupancy status in addition to heavily infested water bodies, b) a data subset that included water bodies with paired water temperature data, and c) a data subset that included water bodies with lower dreissenid densities. For the entire data set, we found that estimated detection probabilities varied by water body size and ranged from approximately 0.10 to 0.86. For the water temperature subset, we observed the same pattern between detection probability and water body size as we did for the full data but additionally found that the estimated detection probabilities were much higher when water temperatures were above 12 °C. For the lower dreissenid density subset, we found that the estimated probability of detecting dreissenid mussels with a single aggregated plankton tow sample was near zero. Given these estimates, we conclude that the number of aggregated plankton tow samples taken per water body in the data is far fewer than the number needed to ensure a high probability of detecting dreissenid mussels, especially if they are at low densities. We summarize the analyses with a discussion of plankton tow sampling protocol changes needed to improve estimates of dreissenid detection probabilities.
Three-dimensional Keplerian orbit-superposition models of the nucleus of M31

We present three-dimensional eccentric disc models of the nucleus of M31, modelling the disc as a linear combination of thick rings of massless stars orbiting in the potential of a central black hole. Our models are non-parametric generalizations of the parametric models of Peiris and Tremaine. The models reproduce well the observed Wide Field Planetary Camera 2 photometry, the detailed line-of-sight velocity distributions from Space Telescope Spectroscopy Imaging Spectrograph observations along P1 and P2, together with the qualitative features of the OASIS kinematic maps. We confirm Peiris and Tremaine’s finding that nuclear discs aligned with the larger disc of M31 are strongly ruled out. Our optimal model is inclined at 57 ◦ with respect to the line of sight of M31 and has position angle PA = θl + 90 ◦ = 55 ◦ . It has a central black hole of mass M• � 1.0 × 10 8 M� , and, when viewed in three dimensions, shows a clear enhancement in the density of stars around the black hole. The distribution of orbit eccentricities in our models is similar to Peiris and Tremaine’s model, but we find significantly different inclination distributions, which might provide valuable clues to the origin of the disc.
Statistical fluctuations of correlators in the Color Glass Condensate

In the McLerran-Venugopalan model, correlators of Wilson lines are given by an average over a Gaussian ensemble of random color sources. In numerical implementations, these averages are approximated by a Monte-Carlo sampling. In this paper, we study the statistical error made with such a sampling, with emphasis on the momentum dependence of this error. Using the example of the dipole amplitude, we consider various approximants that are all equivalent in the limit of infinite statistics but differ with finite statistics and compare their statistical errors. For correlation functions that are translation invariant, we show that averaging over the barycenter coordinate drastically reduces the statistical error and more importantly modifies its momentum dependence.
Random Group Problem-Based Learning in Engineering Dynamics

Dynamics problem-solving is highly specific to the problem at hand and to develop the general mind framework to become an effective problem-solver requires ingenuity and creativity on top of a solid grounding on theoretical and conceptual knowledge. A blended approach with prototype demo, problem-based learning, and an opinion questionnaire was used during 1 st semester of 2013. Students working in randomly selected teams had to interact with classmates while solving a randomly selected Dynamics problem. The approach helps improve students’ awareness of what is important to learn in this class while reducing grading load on the instructor. It also provides a more rewarding contact time for both pupils and instructor.
Theory of graphene saturable absorption

Saturable absorption is a non-perturbative nonlinear optical phenomenon that plays a pivotal role in the generation of ultrafast light pulses. Here we show that this effect emerges in graphene at unprecedentedly low light intensities, thus opening avenues to new nonlinear physics and applications in optical technology. Specifically, we theoretically investigate saturable absorption in extended graphene by developing a non-perturbative single-particle approach, describing conduction-electron dynamics in the atomically-thin material using the two-dimensional Dirac equation for massless Dirac fermions, which is recast in the form of generalized Bloch equations. By solving the electron dynamics non-perturbatively, we account for both interband and intraband contributions to the intensity-dependent saturated conductivity and conclude that the former dominates regardless of the intrinsic doping state of the material. The results are in excellent agreement with atomistic quantum-mechanical simulations including higher-band effects. Additionally, we find that the modulation depth of saturable absorption in graphene can be electrically manipulated through an externally applied gate voltage. Our results are relevant for the development of graphene-based optoelectronic devices, as well as for applications in mode-locking and random lasers.
The Origin of the EUV Late Phase: A Case Study of the C8.8 Flare on 2010 May 5

Since the launch of NASA's Solar Dynamics Observatory on 2010 February 11, the Extreme ultraviolet Variability Experiment (EVE) has observed numerous flares. One interesting feature observed by EVE is that a subset of flares exhibit an additional enhancement of the 2-3 million K emission several hours after the flares soft X-ray emission. From the Atmospheric Imaging Assembly (AIA) images, we observe that this secondary emission, dubbed the EUV late phase, occurs in the same active region as the flare but not in the same coronal loops. Here, we examine the C8.8 flare that occurred on 2010 May 5 as a case study of EUV late phase flares. In addition to presenting detailed observations from both AIA and EVE, we develop a physical model of this flare and test it using the Enthalpy Based Thermal Evolution of Loops (EBTEL) model.
Lighting a Path for Autonomous Vehicle Communication: The Effect of Light Projection on the Detection of Reversing Vehicles by Older Adult Pedestrians

Pedestrian understanding of driver intent is key to pedestrian safety on the road and in parking lots. With the development of autonomous vehicles (AVs), the human driver will be removed, and with it, the exchange that occurs between drivers and pedestrians (e.g., head nods, hand gestures). One possible solution for augmenting that communication is an array of high-intensity light-emitting diodes (LEDs) to project vehicle-to-pedestrian (V2P) messages on the ground plane behind a reversing vehicle. This would be particularly beneficial to elderly pedestrians, who are at particular risk of being struck by reversing cars in parking lots. Their downward gaze and slower reaction time make them particularly vulnerable. A survey was conducted to generate designs, and a simulator experiment was conducted to measure detection and reaction times. The study found that elderly pedestrians are significantly more likely to detect an additional projected message on the ground than detect the existing brake light alone when walking in a parking lot.
Kaluza-Klein models: Can we construct a viable example?

In Kaluza-Klein models with toroidal compactification of the extra dimensions, we investigate soliton solutions of Einstein equation. The nonrelativistic gravitational potential of these solitons exactly coincides with the Newtonian one. We obtain the formulas for perihelion shift, deflection of light, time delay of radar echoes and post-Newtonian (PPN) parameters. Using the constraint on PPN parameter $\ensuremath{\gamma}$, we find that the solitonic parameter $k$ should be very big: $|k|\ensuremath{\ge}2.3\ifmmode\times\else\texttimes\fi{}{10}^{4}$. We define a soliton solution which corresponds to a pointlike mass source. In this case the soliton parameter $k=2$, which is clearly contrary to this restriction. A similar problem with the observations takes place for static spherically symmetric perfect fluid with the dustlike equation of state in all dimensions. The common for both of these models is the same (dustlike) equations of state in our three dimensions and in the extra dimensions. All dimensions are treated at equal footing. This is the crucial point. To be in agreement with observations, it is necessary to break the symmetry (in terms of equations of state) between the external/our and internal spaces. It takes place for black strings which are particular examples of solitons with $k\ensuremath{\rightarrow}\ensuremath{\infty}$. For such $k$, black strings are in concordance with the observations. Moreover, we show that they are the only solitons which are at the same level of agreement with the observations as in general relativity. Black strings can be treated as perfect fluid with dustlike equation of state ${p}_{0}=0$ in the external/our space and very specific equation of state ${p}_{1}=\ensuremath{-}(1/2)\ensuremath{\epsilon}$ in the internal space. The latter equation is due to negative tension in the extra dimension. We also demonstrate that dimension 3 for the external space is a special one. Only in this case we get the latter equation of state. We show that the black string equations of state satisfy the necessary condition of the internal space stabilization. Therefore, black strings are good candidates for a viable model of astrophysical objects (e.g., Sun) if we can provide a satisfactory explanation of negative tension for particles constituting these objects.
MAMBO image of the debris disk around epsilon Eridani : robustness of the azimuthal structure

The debris disk closest to Earth is the one around the star epsilon Eridani at a distance of 3.2 pc. It is the prime target for detailed studies of a belt of planetesimals left from the early phase of planet formation other than the Kuiper Belt. The non-uniform ring-like structure around epsilon Eridani, originally discovered at lambda=850 microns with the bolometer camera SCUBA, could be the signpost of unseen long-period planets interior to the disk that gravitationally interact with it through mean-motion resonances. However, the reliability of the structure at 850 microns, which has been debated, has not been verified with independent observations until now. We present a high signal-to-noise ratio image of this structure at lambda=1.2 mm made with the bolometer camera MAMBO and compare this with the SCUBA image. We have found that three of the four emission clumps (NE, NW, SW) and the two deep hollows to the east and west are at the same positions in the MAMBO and SCUBA images within astrometric uncertainty. The SE clump is at odds, significantly brighter and more extended in the SCUBA than in the MAMBO images, but it is possible that this mismatch is an artifact. We conclude that this degree of positional coincidence provides tentative evidence that the observed structure is robust. In addition, we present the radial brightness profile of our MAMBO image and show that the width of the planetesimal belt around epsilon Eridani is narrower than 22 AU, a more stringent upper limit than determined from previous observations. The corresponding relative width is $0.1 < \Delta R / R < 0.4$, which is lower than for the Kuiper Belt.
Computational studies of x-ray scattering from three-dimensionally-aligned asymmetric-top molecules

We theoretically and numerically analyze x-ray scattering from asymmetric-top molecules three-dimensionally aligned using elliptically polarized laser light. A rigid-rotor model is assumed. The principal axes of the polarizability tensor are assumed to coincide with the principal axes of the moment of inertia tensor. Several symmetries in the Hamiltonian are identified and exploited to enhance the efficiency of solving the time-dependent Schroedinger equation for each rotational state initially populated in a thermal ensemble. Using a phase-retrieval algorithm, the feasibility of structure reconstruction from a quasiadiabatically aligned sample is illustrated for the organic molecule naphthalene. The spatial resolution achievable strongly depends on the laser parameters, the initial rotational temperature, and the x-ray pulse duration. We demonstrate that for a laser peak intensity of 5 TW/cm{sup 2}, a laser pulse duration of 100 ps, a rotational temperature of 10 mK, and an x-ray pulse duration of 1 ps, the molecular structure may be probed at a resolution of 1 A ring .
Infrastructure Condition Assessment and Prediction under Variable Traffic Demand and Management Scenarios

1 The Virginia Department of Transportation (VDOT) is responsible for keeping its road network in a state of good repair while also aiming to reduce congestion through the implementation of different traffic control and demand management strategies. These strategies can result in changes in traffic volume distributions, which in turn affect the level of pavement deterioration due to traffic loading. To address this issue, this paper introduces an integrated simulation-optimization framework that accounts for the combined effects of pavement condition and traffic management decision-making strategies. The research focuses on exploring the range of possible performance outcomes resulting from this integrated modeling approach. The authors illustrate the proposed framework and provide a case study analysis in Virginia, USA. The results showed that the optimized model could achieve a maximum Critical Condition Index (CCI) increase from an average of 65 to 100, causing about 80% of travel time increase. On the other hand, a do-nothing approach preserves travel time but decreases the CCI by seven points on average during one fiscal year. The use of the proposed framework is therefore crucial for decision-making purposes and can help DOTs understand the trade-off involved when considering traffic management and pavement performance. 1 Abi Aad, M. , M. Abbas, and L. Wang. A Simulation-Optimization Framework for Integrated Infrastructure Condition and Traffic Management Strategies. In IEEE 2022 – 2022 IEEE International Intelligent Transportation. (Accepted for Publication)