Miracle-dz/UniFAR-FTUs huggingface dataset:
The continuum limit of interacting dislocations on multiple slip systems

In this paper we derive the continuum limit of a multiple-species, interacting particle system by proving a Γ-convergence result on the interaction energy as the number of particles tends to infinity. As the leading application, we consider n edge dislocations in multiple slip systems. Since the interaction potential of dislocations has a logarithmic singularity at zero with a sign that depends on the orientation of the slip systems, the interaction energy is unbounded from below. To make the minimization problem of this energy meaningful, we follow the common approach to regularise the interaction potential over a length-scale δ > 0. The novelty of our result is that we leave the type of regularisation general, and that we consider the joint limit n →∞ and δ → 0. Our result shows that the limit behaviour of the interaction energy is not affected by the type of the regularisation used, but that it may depend on how fast the size (i.e., δ) decays as n →∞.
The deep learning and statistical physics applications to the problems of combinatorial optimization

We present herein a new approach based on the simultaneous application of the deep learning and statistical physics methods to solve the combinatorial optimization problems. The recent modern advanced techniques, such as an artificial neural network, demonstrate their efficiency for solving various physical tasks for the quantum many-body systems, which may be related directly to the problems of combinatorial optimization. One of them is a classical Maximum Cut (MaxCut) problem, which we ascribe here to the search of the ground state of a quantum many-body system using an artificial neural network and deep learning. We found that the exact solution received for a quantum system corresponds to its counterpart in a classical MaxCut problem. As a proof, we have realized our approach for two random graphs of different size, containing 60 vertices (885 edges) and 100 vertices (2475 edges), and achieved for them the total performances p60~0.99 and $p100~0.97 of known maximal cuts, respectively.
Effects of Adopting Ultra-Fast Charging Stations in the San Francisco Bay Area

Ultra-Fast Charging (UFC) is a rising technology that can shorten the time of charging an Electric Vehicle (EV) from hours to minutes. However, the power consumption characteristics of UFC bring new challenges to the existing power system, and its pros and cons are yet to be studied. This project aims to set up a framework for studying the different aspects of substituting the normal non-residential EV chargers within the San Francisco Bay Area with Ultra-Fast Charging (UFC) stations. Three objectives were defined for three stakeholders involved in this simulation, namely: the EV user, the station owner, and the grid operator. The results show that, UFCs will significantly contribute to increase of peak load and power consumption during the peak demand period, which is an undesirable outcome from grid operation perspective. Total electricity and operations and maintenance costs for station owner would increase subsequently, while this can be justified by analyzing the value of time (VOT) from an EV-user perspective. Additionally, peak-shaving using battery storage facilities is studied for complementing the applied technology change and mitigating the impacts of higher power consumption on the grid.
The generalised buoyancy/inertial forces and available energy of axisymmetric compressible stratified vortex motions

Adiabatic and inviscid axisymmetric perturbations to a stable reference vortex in gradient wind balance are known to experience two kinds of restoring forces: one that is proportional to both the perturbation density and the reference pressure gradient, and one that is purely radial and proportional to the squared angular momentum perturbation. We show that the work required to move a fluid parcel against such forces from its equilibrium to actual position is path-independent and formally equivalent to the available energy accounting for momentum constraints previously constructed by Andrews (2006) and Codoban and Shepherd (2006). Physically, this work represents the energy of the unbalanced part of the vortex and hence a form of eddy energy. It can be partitioned into available acoustic energy, slantwise available potential energy and centrifugal potential energy. We show that the conditions required for these energies to be positive definite correspond to the classical conditions for symmetric stability, valid for both small and finite-amplitude perturbations. The new available energy framework possesses various advantageous features over previous approaches that shed new light on how the thermodynamic and mechanical sinks/sources of energy control the intensification of the balanced and unbalanced parts of a warm core cyclonic vortex. These features should prove useful in the future to re-examine and clarify the links between the different existing paradigms of tropical cyclone (TC) intensification within a single unifying theoretical framework.
Echoing the recent Google success: Foundational Roots of Quantum Supremacy

The recent Google's claim on breakthrough in quantum computing is a gong signal for further analysis of foundational roots of (possible) superiority of some quantum algorithms over the corresponding classical algorithms. This note is a step in this direction. We start with critical analysis of rather common reference to entanglement and quantum nonlocality as the basic sources of quantum superiority. We elevate the role of the Bohr's {\it principle of complementarity}\footnote{} (PCOM) by interpreting the Bell-experiments as statistical tests of this principle. (Our analysis also includes comparison of classical vs genuine quantum entanglements.) After a brief presentation of PCOM and endowing it with the information interpretation, we analyze its computational counterpart. The main implication of PCOM is that by using the quantum representation of probability, one need not compute the joint probability distribution (jpd) for observables involved in the process of computation. Jpd's calculation is exponentially time consuming. Consequently, classical probabilistic algorithms involving calculation of jpd for $n$ random variables can be over-performed by quantum algorithms (for big values of $n). $ Quantum algorithms are based on quantum probability calculus. It is crucial that the latter modifies the classical formula of total probability (FTP). Probability inference based on the quantum version of FTP leads to constructive interference of probabilities increasing probabilities of some events. We also stress the role the basic feature of the genuine quantum superposition comparing with the classical wave superposition: generation of discrete events in measurements on superposition states. Finally, the problem of superiority of quantum computations is coupled with the quantum measurement problem and linearity of dynamics of the quantum state update.
DeepSmartFuzzer: Reward Guided Test Generation For Deep Learning

Testing Deep Neural Network (DNN) models has become more important than ever with the increasing usage of DNN models in safety-critical domains such as autonomous cars. The traditional approach of testing DNNs is to create a test set, which is a random subset of the dataset about the problem of interest. This kind of approach is not enough for testing most of the real-world scenarios since these traditional test sets do not include corner cases, while a corner case input is generally considered to introduce erroneous behaviors. Recent works on adversarial input generation, data augmentation, and coverage-guided fuzzing (CGF) have provided new ways to extend traditional test sets. Among those, CGF aims to produce new test inputs by fuzzing existing ones to achieve high coverage on a test adequacy criterion (i.e. coverage criterion). Given that the subject test adequacy criterion is a well-established one, CGF can potentially find error inducing inputs for different underlying reasons. In this paper, we propose a novel CGF solution for structural testing of DNNs. The proposed fuzzer employs Monte Carlo Tree Search to drive the coverage-guided search in the pursuit of achieving high coverage. Our evaluation shows that the inputs generated by our method result in higher coverage than the inputs produced by the previously introduced coverage-guided fuzzing techniques.
ViewSynth: Learning Local Features from Depth using View Synthesis

The rapid development of inexpensive commodity depth sensors has made keypoint detection and matching in the depth image modality an important problem in computer vision. Despite great improvements in recent RGB local feature learning methods, adapting them directly in the depth modality leads to unsatisfactory performance. Most of these methods do not explicitly reason beyond the visible pixels in the images. To address the limitations of these methods, we propose a framework ViewSynth, to jointly learn: (1) viewpoint invariant keypoint-descriptor from depth images using a proposed Contrastive Matching Loss, and (2) view synthesis of depth images from different viewpoints using the proposed View Synthesis Module and View Synthesis Loss. By learning view synthesis, we explicitly encourage the feature extractor to encode information about not only the visible, but also the occluded parts of the scene. We demonstrate that in the depth modality, ViewSynth outperforms the state-of-the-art depth and RGB local feature extraction techniques in the 3D keypoint matching and camera localization tasks on the RGB-D datasets 7-Scenes, TUM RGBD and CoRBS in most scenarios. We also show the generalizability of ViewSynth in 3D keypoint matching across different datasets.
Accurate Computations of Euler Products over Primes in Arithmetic Progressions

This note provides truncated formulae with explicit error terms to compute Euler products over primes in arithmetic progressions of rational fractions. It further provides such a formula for the product of terms of the shape $F(1/p, 1/p^s)$ when $F$ is a two-variable polynomial with coefficients in $\mathbb{C}$ and satisfying some restrictive conditions.
No Need for Recovery: A Simple Two-Step Byzantine Consensus

In this paper, we give a deterministic two-step Byzantine consensus protocol that achieves safety and liveness. A two-step Byzantine consensus protocol only needs two communication steps to commit in the absence of faults. Most two-step Byzantine consensus protocols exploit optimism and require a recovery protocol in the presence of faults. In this paper, we give a simple two-step Byzantine consensus protocol that does not need a recovery protocol.
Exploring the “L–σ” Relation of H ii Galaxies and Giant Extragalactic H ii Regions Acting as Standard Candles

Cosmological applications of H ii galaxies and giant extragalactic H ii regions (GEHRs) to construct the Hubble diagram at high redshifts require knowledge of the “L–σ” relation of the standard candles used. In this paper, we study the properties of a large sample of 156 sources (25 high-z H ii galaxies, 107 local H ii galaxies, and 24 GEHRs) compiled by Terlevich et al. Using the cosmological distances reconstructed through two new cosmology-independent methods, we investigate the correlation between the Hβ emission-line luminosity L and the ionized gas velocity dispersion σ. The method is based on non-parametric reconstruction using the measurements of Hubble parameters from cosmic clocks, as well as the simulated data of gravitational waves from the third-generation gravitational wave detector (the Einstein Telescope, ET), which can be considered as standard sirens. Assuming the relation between emission-line luminosity and ionized gas velocity dispersion, , we find that the full sample provides a tight constraint on the correlation parameters. However, similar analysis done on three different subsamples seems to support the scheme of treating H ii galaxies and GEHRs with distinct strategies. Using the corrected “L–σ” relation for the H ii observational sample beyond the current reach of Type Ia supernovae, we obtain values of the matter density parameter, Ωm = 0.314 ± 0.054 (calibrated with standard clocks) and Ωm = 0.311 ± 0.049 (calibrated with standard sirens), in the spatially flat ΛCDM cosmology.
On computing non-equilibrium dynamics following a quench

Computing the non-equilibrium dynamics that follows a quantum quench is difficult, even in exactly solvable models. Results are often predicated on the ability to compute overlaps between the initial state and eigenstates of the Hamiltonian that governs time evolution. Except for a handful of known cases, it is generically not possible to find these overlaps analytically. Here we develop a numerical approach to preferentially generate the states with high overlaps for a quantum quench starting from the ground state or an excited state of an initial Hamiltonian. We use these preferentially generated states, in combination with a "high overlap states truncation scheme" and a modification of the numerical renormalization group, to compute non-equilibrium dynamics following a quench in the Lieb-Liniger model. The method is non-perturbative, works for reasonable numbers of particles, and applies to both continuum and lattice systems. It can also be easily extended to more complicated scenarios, including those with integrability breaking.
What goes into a word: generating image descriptions with top-down spatial knowledge

Generating grounded image descriptions requires associating linguistic units with their corresponding visual clues. A common method is to train a decoder language model with attention mechanism over convolutional visual features. Attention weights align the stratified visual features arranged by their location with tokens, most commonly words, in the target description. However, words such as spatial relations (e.g. next to and under) are not directly referring to geometric arrangements of pixels but to complex geometric and conceptual representations. The aim of this paper is to evaluate what representations facilitate generating image descriptions with spatial relations and lead to better grounded language generation. In particular, we investigate the contribution of three different representational modalities in generating relational referring expressions: (i) pre-trained convolutional visual features, (ii) different top-down geometric relational knowledge between objects, and (iii) world knowledge captured by contextual embeddings in language models.
Random projections: Data perturbation for classification problems

Random projections offer an appealing and flexible approach to a wide range of large‐scale statistical problems. They are particularly useful in high‐dimensional settings, where we have many covariates recorded for each observation. In classification problems, there are two general techniques using random projections. The first involves many projections in an ensemble—the idea here is to aggregate the results after applying different random projections, with the aim of achieving superior statistical accuracy. The second class of methods include hashing and sketching techniques, which are straightforward ways to reduce the complexity of a problem, perhaps therefore with a huge computational saving, while approximately preserving the statistical efficiency.
A proof of the Conjecture of Lehmer

The Conjecture of Lehmer is proved to be true. The proof mainly relies upon: (i) the properties of the Parry Upper functions $f_{\house{\alpha}}(z)$ associated with the dynamical zeta functions $\zeta_{\house{\alpha}}(z)$ of the R\'enyi--Parry arithmetical dynamical systems ($\beta$-shift), for $\alpha$ a reciprocal algebraic integer $\alpha$ of house $\house{\alpha}$ greater than 1, (ii) the discovery of lenticuli of poles of $\zeta_{\house{\alpha}}(z)$ which uniformly equidistribute at the limit on a limit ``lenticular" arc of the unit circle, when $\house{\alpha}$ tends to $1^+$, giving rise to a continuous lenticular minorant ${\rm M}_{r}(\house{\alpha})$ of the Mahler measure ${\rm M}(\alpha)$, (iii) the Poincar\'e asymptotic expansions of these poles and of this minorant ${\rm M}_{r}(\house{\alpha})$ as a function of the dynamical degree. The Conjecture of Schinzel-Zassenhaus is proved to be true. A Dobrowolski type minoration of the Mahler measure M$(\alpha)$ is obtained. The universal minorant of M$(\alpha)$ obtained is $\theta_{\eta}^{-1} > 1$, for some integer $\eta \geq 259$, where $\theta_{\eta}$ is the positive real root of $-1+x+x^{\eta}$. The set of Salem numbers is shown to be bounded from below by the Perron number $\theta_{31}^{-1} = 1.08545\ldots$, dominant root of the trinomial $-1 - z^{30} + z^{31}$. Whether Lehmer's number is the smallest Salem number remains open. For sequences of algebraic integers of Mahler measure smaller than the smallest Pisot number $\Theta = 1.3247\ldots$, whose houses have a dynamical degree tending to infinity, the Galois orbit measures of conjugates are proved to converge towards the Haar measure on $|z|=1$ (limit equidistribution).
Adaptive Nearest Neighbor: A General Framework for Distance Metric Learning

$K$-NN classifier is one of the most famous classification algorithms, whose performance is crucially dependent on the distance metric. When we consider the distance metric as a parameter of $K$-NN, learning an appropriate distance metric for $K$-NN can be seen as minimizing the empirical risk of $K$-NN. In this paper, we design a new type of continuous decision function of the $K$-NN classification rule which can be used to construct the continuous empirical risk function of $K$-NN. By minimizing this continuous empirical risk function, we obtain a novel distance metric learning algorithm named as adaptive nearest neighbor (ANN). We have proved that the current algorithms such as the large margin nearest neighbor (LMNN), neighbourhood components analysis (NCA) and the pairwise constraint methods are special cases of the proposed ANN by setting the parameter different values. Compared with the LMNN, NCA, and pairwise constraint methods, our method has a broader searching space which may contain better solutions. At last, extensive experiments on various data sets are conducted to demonstrate the effectiveness and efficiency of the proposed method.
Minimum-cost integer circulations in given homology classes

Let $ D $ be a directed graph cellularly embedded on a surface together with costs and capacities on its arcs. Given any integer circulation in $ D $, we study the problem of finding a minimum-cost integer circulation in $ D $ that is homologous (over the integers) to the given circulation and respects the capacities. It has been recently shown that the stable set problem for graphs with bounded genus and bounded odd cycle packing number can be efficiently reduced to this problem, in which the surface is non-orientable. For orientable surfaces, polynomial-time algorithms have been obtained for different variants of this problem. We complement these findings by showing that the convex hull of feasible solutions has a very simple polyhedral description. In contrast, only little seems to be known about the case of non-orientable surfaces. We show that the problem is strongly NP-hard in this case. For surfaces of fixed genus, we obtain that the problem can be recast as an integer linear program with a coefficient matrix of bounded sub-determinants, which yields a polynomial-time algorithm for the projective plane. Moreover, we describe a pseudo-polynomial time algorithm for the case in which the surface has fixed genus and the circulation is only restricted to be non-negative.
The Bouquet Algorithm for Model Checking Unbounded Until Properties

The problem of verifying the “Unbounded Until” fragment in temporal logic formulas has been studied extensively in the past, especially in the context of statistical model checking. Statistical model checking, a computationally inexpensive sampling based alternative to the more expensive numerical model checking technique, presents the following decision dilemma-what length of the sample is enough in general? In this paper, we discuss an algorithm for this problem that combines ideas from graph theory, statistical model checking and numerical model checking. We analyze the algorithm, and show through experiments that this approach outperforms the standard statistical model checking algorithm for verifying unbounded until for low density Discrete Time Markov Chains.
Editing Fusarium graminearum genome with CRISPR/Cas9

CRISPR/Cas9 technology can be used to mutate genomes and make a pathogenic organism less infectious. We used CRISPR/Cas9 plasmids constructed by a former undergraduate student to mutate three genes in the cereal fungal pathogen Fusarium graminearum. One of the genes (AUR1) is a visual marker and the other two genes (MGV1 and Tri5) are essential for infection. The CRISPR/Cas9 plasmids also contain a hygromycin B resistance gene for selection. We transformed F. graminearum protoplasts and selected colonies on media containing hygromycin B. We then screened the target genes for mutations by PCR and gel electrophoresis. Unfortunately, we were unable to confirm mutations in the transformants. However, many fungi, including F. graminearum, are multinucleated and this made it difficult to isolate colonies with genetically identical nuclei (homokaryotes). Further work is needed to isolate homokaryotic cells.
TESTING THE DAPTOCEPHALUS AND LYSTROSAURUS ASSEMBLAGE ZONES IN A LITHOSTRATOGRAPHIC, MAGNETOSTRATIGRAPHIC, AND PALYNOLOGICAL FRAMEWORK IN THE FREE STATE, SOUTH AFRICA

Abstract: The vertebrate-fossil record in the Karoo Basin has served as the accepted model for how terrestrial ecosystems responded to the end-Permian extinction event. A database of several hundred specimens, placed into generalized stratigraphies, has formed the basis of a step-wise extinction scenario interpreted by other workers as spanning the upper Daptocephalus (=Dicynodon) to Lystrosaurus Assemblage Zones (AZ). Seventy-three percent of specimens used to construct the published model originate from three farms in the Free State: Bethel, Heldenmoed, and Donald 207 (Fairydale). The current contribution empirically tests: (1) the stratigraphic resolution of the vertebrate record on these farms; (2) whether a sharp boundary exists that delimits the vertebrate assemblage zones in these classic localities; and (3) if the Lystrosaurus AZ is of early Triassic age. We have used a multi-disciplinary approach, combining lithostratigraphy, magnetostratigraphy, vertebrate biostratigraphy, and palynology, to test these long-held assumptions. Previously reported vertebrate-collection sites have been physically placed into a litho- and magnetostratigraphic framework on the Bethel and Heldenmoed farms. The reported assemblage-zone boundary is used as the datum against which the stratigraphic position of vertebrates is compared and a preliminary magnetostratigraphy constructed. We find specimens of the Daptocephalus AZ originate in the Lystrosaurus AZ (as currently defined) and vice versa, and discrepancies between reported and field-checked stratigraphic positions below or above the assemblage-zone boundary often exceed 30 m. Hence, the utility of the data set in defining a sharp or abrupt biozone boundary is questionable. We further demonstrate the presence of a stratigraphically thick reverse polarity magnetozone that encompasses the reported assemblage-zone boundary, implying that these rocks are not correlative with the end-Permian event, which is reported to lie in a normal polarity chron. A latest Permian age is supported by palynological data from the Lystrosaurus AZ on the Donald 207 (Fairydale) farm, with equivalence to Australian (APP602) and Eastern Cape Province assemblages. We conclude that the turnover from the Daptocephalus to Lystrosaurus Assemblage Zones is more protracted than envisioned, it is not coincident with the end-Permian event as recognized in the marine realm, and little evidence exists in support of a three-phased extinction model based on vertebrate assemblages in the Karoo Basin.