cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Managing the Challenges of Modern Research Surveys
Creators: name: Hawthorne, Julie
name: Timms, Kevin
Publisher: name: figshare
Year: 2015
Subjects: subject: Biotechnology
subject: Information Systems
subject: FOS: Computer and information sciences
subject: 60102 Bioinformatics
subject: Computer Software
subject: Data Format

description: Surveys have historically been one of the most important tools available for conducting empirical research. Today, they continue to be prominent within social and behavioral science research, and play growing roles in areas such as clinical outcomes research. However, surveys are taking novel forms that afford new opportunities but face new challenges.
Multiparametric qualimetric microsurgical scanning chip-lancet model: theoretical metrological and biomedical considerations
Creators: name: Jablokov, Arthur
name: Gradov, Oleg
Publisher: name: figshare
Year: 2015
Subjects: subject: Medicine
subject: 60102 Bioinformatics
subject: FOS: Computer and information sciences
subject: Anesthesiology
subject: Biological Engineering
subject: Toxicology
subject: Biological Techniques
subject: Anatomy

description: The construction of a novel surgical instrument is considered, which is also a probing device providing a signal to the measuring equipment, which after its interpretation allows to obtain useful information about the section quality and the biomaterial properties. We propose here some formalized considerations on the possibility of its implementation for different variables registration. The idea is also extrapolated into the field of micrurgy which refers to the microelectrode techniques and the local potential registration in situ.
Rich Nature of Van Hove Singularities in Kagome Superconductor CsV$_3$Sb$_5$
Creators: name: Hu, Yong
name: Wu, Xianxin
name: Ortiz, Brenden R.
name: Ju, Sailong
name: Han, Xinlong
name: Ma, J. Z.
name: Plumb, N. C.
name: Radovic, Milan
name: Thomale, Ronny
name: Wilson, S. D.
name: Schnyder, Andreas P.
name: Shi, M.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Superconductivity (cond-mat.supr-con)
subject: Materials Science (cond-mat.mtrl-sci)
subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: The recently discovered layered kagome metals AV$_3$Sb$_5$ (A=K, Rb, Cs) exhibit diverse correlated phenomena, which are intertwined with a topological electronic structure with multiple van Hove singularities (VHSs) in the vicinity of the Fermi level. As the VHSs with their large density of states enhance correlation effects, it is of crucial importance to determine their nature and properties. Here, we combine polarization-dependent angle-resolved photoemission spectroscopy with density functional theory to directly reveal the sublattice properties of 3d-orbital VHSs in CsV$_3$Sb$_5$. Four VHSs are identified around the M point and three of them are close to the Fermi level, with two having sublattice-pure and one sublattice-mixed nature. Remarkably, the VHS just below the Fermi level displays an extremely flat dispersion along MK, establishing the experimental discovery of higher-order VHS. The characteristic intensity modulation of Dirac cones around K further demonstrates the sublattice interference embedded in the electronic structure. The crucial insights into the electronic structure, revealed by our work, provide a solid starting point for the understanding of the intriguing correlation phenomena in the kagome metals AV$_3$Sb$_5$.
Quantifying the Conceptual Error in Dimensionality Reduction
Creators: name: Hanika, Tom
name: Hirth, Johannes
Publisher: name: arXiv
Year: 2021
Subjects: subject: Machine Learning (cs.LG)
subject: Artificial Intelligence (cs.AI)
subject: Information Theory (cs.IT)
subject: FOS: Computer and information sciences
subject: 03G10, 68T27, 68T30, 06B10, 06A15, 06-08

description: Dimension reduction of data sets is a standard problem in the realm of machine learning and knowledge reasoning. They affect patterns in and dependencies on data dimensions and ultimately influence any decision-making processes. Therefore, a wide variety of reduction procedures are in use, each pursuing different objectives. A so far not considered criterion is the conceptual continuity of the reduction mapping, i.e., the preservation of the conceptual structure with respect to the original data set. Based on the notion scale-measure from formal concept analysis we present in this work a) the theoretical foundations to detect and quantify conceptual errors in data scalings; b) an experimental investigation of our approach on eleven data sets that were respectively treated with a variant of non-negative matrix factorization.
description: 14 pages
Variational quantum algorithm based on the minimum potential energy for solving the Poisson equation
Creators: name: Sato, Yuki
name: Kondo, Ruho
name: Koide, Satoshi
name: Takamatsu, Hideki
name: Imoto, Nobuyuki
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Computer-aided engineering techniques are indispensable in modern engineering developments. In particular, partial differential equations are commonly used to simulate the dynamics of physical phenomena, but very large systems are often intractable within a reasonable computation time, even when using supercomputers. To overcome the inherent limit of classical computing, we present a variational quantum algorithm for solving the Poisson equation that can be implemented in noisy intermediate-scale quantum devices. The proposed method defines the total potential energy of the Poisson equation as a Hamiltonian, which is decomposed into a linear combination of Pauli operators and simple observables. The expectation value of the Hamiltonian is then minimized with respect to a parameterized quantum state. Because the number of decomposed terms is independent of the size of the problem, this method requires relatively few quantum measurements. Numerical experiments demonstrate the faster computing speed of this method compared with classical computing methods and a previous variational quantum approach. We believe that our approach brings quantum computer-aided techniques closer to future applications in engineering developments. Code is available at https://github.com/ToyotaCRDL/VQAPoisson.
description: 17pages, 19 figures
Mean-field description for the architecture of low-energy excitations in glasses
Creators: name: Ji, Wencheng
name: de Geus, Tom W. J.
name: Agoritsas, Elisabeth
name: Wyart, Matthieu
Publisher: name: arXiv
Year: 2021
Subjects: subject: Soft Condensed Matter (cond-mat.soft)
subject: Disordered Systems and Neural Networks (cond-mat.dis-nn)
subject: Statistical Mechanics (cond-mat.stat-mech)
subject: FOS: Physical sciences

description: In amorphous materials, groups of particles can rearrange locally into a new stable configuration. Such elementary excitations are key as they determine the response to external stresses, as well as to thermal and quantum fluctuations. Yet, understanding what controls their geometry remains a challenge. Here we build a scaling description of the geometry and energy of low-energy excitations in terms of the distance to an instability, as predicted for instance at the dynamical transition in mean field approaches of supercooled liquids. We successfully test our predictions in ultrastable computer glasses, with a gapped and ungapped (regular) spectrum. Overall, our approach explains why excitations become less extended, with a higher energy and displacement scale upon cooling.
Entanglement Wedge in Flat Holography and Entanglement Negativity
Creators: name: Basu, Debarshi
name: Chandra, Ashish
name: Raj, Vinayak
name: Sengupta, Gautam
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: We establish a construction for the entanglement wedge in asymptotically flat bulk geometries for subsystems in dual $(1+1)$-dimensional Galilean conformal field theories in the context of flat space holography. In this connection we propose a definition for the bulk entanglement wedge cross section for bipartite states of such dual non relativistic conformal field theories. Utilizing our construction for the entanglement wedge cross section we compute the entanglement negativity for such bipartite states through the generalization of an earlier proposal, in the context of the usual $AdS/CFT$ scenario, to flat space holography. The entanglement negativity obtained from our construction exactly reproduces earlier holographic results and match with the corresponding field theory replica technique results in the large central charge limit.
description: 53 pages, 10 figures and 2 appendices, v2: minor modifications, references added
Time-Aware Language Models as Temporal Knowledge Bases
Creators: name: Dhingra, Bhuwan
name: Cole, Jeremy R.
name: Eisenschlos, Julian Martin
name: Gillick, Daniel
name: Eisenstein, Jacob
name: Cohen, William W.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Computation and Language (cs.CL)
subject: FOS: Computer and information sciences

description: Many facts come with an expiration date, from the name of the President to the basketball team Lebron James plays for. But language models (LMs) are trained on snapshots of data collected at a specific moment in time, and this can limit their utility, especially in the closed-book setting where the pretraining corpus must contain the facts the model should memorize. We introduce a diagnostic dataset aimed at probing LMs for factual knowledge that changes over time and highlight problems with LMs at either end of the spectrum -- those trained on specific slices of temporal data, as well as those trained on a wide range of temporal data. To mitigate these problems, we propose a simple technique for jointly modeling text with its timestamp. This improves memorization of seen facts from the training time period, as well as calibration on predictions about unseen facts from future time periods. We also show that models trained with temporal context can be efficiently "refreshed" as new data arrives, without the need for retraining from scratch.
description: Version accepted to TACL
The rise of populism and the reconfiguration of the German political space
Creators: name: Olbrich, Eckehard
name: Banisch, Sven
Publisher: name: arXiv
Year: 2021
Subjects: subject: Physics and Society (physics.soc-ph)
subject: Social and Information Networks (cs.SI)
subject: FOS: Physical sciences
subject: FOS: Computer and information sciences

description: The paper explores the notion of a reconfiguration of political space in the context of the rise of populism and its effects on the political system. We focus on Germany and the appearance of the new right wing party "Alternative for Germany" (AfD). Many scholars of politics discuss the rise of the new populism in Western Europe and the US with respect to a new political cleavage related to globalization, which is assumed to mainly affect the cultural dimension of the political space. As such, it might replace the older economic cleavage based on class divisions in defining the dominant dimension of political conflict. An explanation along these lines suggests a reconfiguration of the political space in the sense that (1) the main cleavage within the political space changes its direction from the economic axis towards the cultural axis, but (2) also the semantics of the cultural axis itself is changing towards globalization related topics. Using the electoral manifestos from the Manifesto project database, we empirically address this reconfiguration of the political space by comparing political spaces for Germany built using topic modeling with the spaces based on the content analysis of the Manifesto project and the corresponding categories of political goals. We find that both spaces have a similar structure and that the AfD appears on a new dimension. In order to characterize this new dimension we employ a novel technique, inter-issue consistency networks (IICN) that allow to analyze the evolution of the correlations between the political positions on different issues over several elections. We find that the new dimension introduced by the AfD can be related to the split off of a new "cultural right" issue bundle from the previously existing center-right bundle.
description: The version 2 contains the corrected figures from the corrigendum 10.3389/fdata.2021.833037
Combinatorial Optimization with Physics-Inspired Graph Neural Networks
Creators: name: Schuetz, Martin J. A.
name: Brubaker, J. Kyle
name: Katzgraber, Helmut G.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Machine Learning (cs.LG)
subject: Disordered Systems and Neural Networks (cond-mat.dis-nn)
subject: Artificial Intelligence (cs.AI)
subject: Optimization and Control (math.OC)
subject: Quantum Physics (quant-ph)
subject: FOS: Computer and information sciences
subject: FOS: Physical sciences
subject: FOS: Mathematics

description: Combinatorial optimization problems are pervasive across science and industry. Modern deep learning tools are poised to solve these problems at unprecedented scales, but a unifying framework that incorporates insights from statistical physics is still outstanding. Here we demonstrate how graph neural networks can be used to solve combinatorial optimization problems. Our approach is broadly applicable to canonical NP-hard problems in the form of quadratic unconstrained binary optimization problems, such as maximum cut, minimum vertex cover, maximum independent set, as well as Ising spin glasses and higher-order generalizations thereof in the form of polynomial unconstrained binary optimization problems. We apply a relaxation strategy to the problem Hamiltonian to generate a differentiable loss function with which we train the graph neural network and apply a simple projection to integer variables once the unsupervised training process has completed. We showcase our approach with numerical results for the canonical maximum cut and maximum independent set problems. We find that the graph neural network optimizer performs on par or outperforms existing solvers, with the ability to scale beyond the state of the art to problems with millions of variables.
description: Manuscript: 13 pages, 5 figures, 1 table. Supplemental Material: 1 page, 1 table
Higgs portal vector dark matter interpretation: review of Effective Field Theory approach and ultraviolet complete models
Creators: name: Zaazoua, Mohamed
name: Truong, Loan
name: Assamagan, Kétévi A.
name: Fassi, Farida
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: FOS: Physical sciences

description: A review of the Higgs portal-vector dark matter interpretation of the spin-independent dark-matter nucleon elastic scattering cross section is presented, where the invisible Higgs decay width measured at the LHC is used. Effective Field Theory and ultraviolet complete models are discussed. LHC interpretations show only the scalar and Majorana dark-matter scenarios; we propose to include interpretation for vector dark matter in the EFT and UV completions theoretical framework. In addition, our studies suggest an extension of the LHC dark matter interpretations to the sub-GeV regime.
description: contribution to Snowmass 2022
Thermoelectric transport within density functional theory
Creators: name: Sobrino, Nahual
name: Eich, Florian
name: Stefanucci, Gianluca
name: D'Agosta, Roberto
name: Kurth, Stefan
Publisher: name: arXiv
Year: 2021
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: FOS: Physical sciences

description: A new formalism to describe steady-state electronic and thermal transport in the framework of density functional theory is presented. A one-to-one correspondence is proven between the three basic variables of the theory, i.e., the density on as well as the electrical and heat currents through the junction, and the three basic potentials, i.e., the local potential in as well as the DC bias and thermal gradient across the junction. Consequently, the Kohn-Sham system of the theory requires three exchange-correlations potentials. In linear response, the new formalism leads to exact expressions for the many-body transport coefficients (both electrical and thermal conductances and Seebeck coefficient) in terms of both the corresponding Kohn-Sham coefficients and derivatives of the exchange-correlations potentials. The theory is applied to the Single Impurity Anderson Model, and an accurate analytic parametrization for these derivatives in the Coulomb blockade regime is constructed through reverse engineering.
description: 11 pages, 5 figures
The Spum and Sum-diameter of Graphs: Labelings of Sum Graphs
Creators: name: Li, Rupert
Publisher: name: arXiv
Year: 2021
Subjects: subject: Combinatorics (math.CO)
subject: FOS: Mathematics
subject: 05C78

description: A sum graph is a finite simple graph whose vertex set is labeled with distinct positive integers such that two vertices are adjacent if and only if the sum of their labels is itself another label. The spum of a graph $G$ is the minimum difference between the largest and smallest labels in a sum graph consisting of $G$ and the minimum number of additional isolated vertices necessary so that a sum graph labeling exists. We investigate the spum of various families of graphs, namely cycles, paths, and matchings. We introduce the sum-diameter, a modification of the definition of spum that omits the requirement that the number of additional isolated vertices in the sum graph is minimal, which we believe is a more natural quantity to study. We then provide asymptotically tight general bounds on both sides for the sum-diameter, and study its behavior under numerous binary graph operations as well as vertex and edge operations. Finally, we generalize the sum-diameter to hypergraphs.
description: To appear in Discrete Mathematics. 38 pages, 3 figures
Confirmation of the Long-Period Planet Orbiting Gliese 411 and the Detection of a New Planet Candidate
Creators: name: Hurt, Spencer A.
name: Fulton, Benjamin
name: Isaacson, Howard
name: Rosenthal, Lee J.
name: Howard, Andrew W.
name: Weiss, Lauren M.
name: Petigura, Erik A.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Earth and Planetary Astrophysics (astro-ph.EP)
subject: FOS: Physical sciences

description: We perform a detailed characterization of the planetary system orbiting the bright, nearby M dwarf Gliese 411 using radial velocities gathered by APF, HIRES, SOPHIE, and CARMENES. We confirm the presence of a signal with a period near 2900 days that has been disputed as either a planet or a long-period stellar magnetic cycle. An analysis of activity metrics including the $\mathrm{H_α}$ and $\mathrm{log'R_{HK}}$ indices supports the interpretation that the signal corresponds to a Neptune-like planet, GJ 411 c. An additional signal near 215 days was previously dismissed as an instrumental systematic, but we find that a planetary origin cannot be ruled out. With a semi-major axis of $0.5142\pm0.0042$ au, this candidate's orbit falls between those of its companions and is located beyond the outer edge of the system's habitable zone (determined using the moist greenhouse and maximum greenhouse limits in Kopparapu et al., 2013). It has a minimum mass of $4.1\pm0.6$ $M_\oplus$, giving a radial-velocity amplitude of $0.81\pm0.18$ $\mathrm{m\,s^{-1}}$. If confirmed, this would be one of the lowest-amplitude planet detections from any of these four instruments. Our analysis of the joint radial-velocity data set also provides tighter constraints on the orbital parameters for the previously known planets. Photometric data from TESS do not show any signs of a transit event. However, the outermost planet and candidate are prime targets for future direct imaging missions, and GJ 411 c may be detectable via astrometry.
description: 19 pages, 13 figures, 5 tables; accepted to The Astronomical Journal (AJ)
Weakly Supervised Attention Model for RV StrainClassification from volumetric CTPA Scans
Creators: name: Cahan, Noa
name: Marom, Edith M.
name: Soffer, Shelly
name: Barash, Yiftach
name: Konen, Eli
name: Klang, Eyal
name: Greenspan, Hayit
Publisher: name: arXiv
Year: 2021
Subjects: subject: Image and Video Processing (eess.IV)
subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Machine Learning (cs.LG)
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Computer and information sciences
subject: I.4.9; J.6; I.2.1
subject: 92C50, 68T07 (Primary)

description: Pulmonary embolus (PE) refers to obstruction of pulmonary arteries by blood clots. PE accounts for approximately 100,000 deaths per year in the United States alone. The clinical presentation of PE is often nonspecific, making the diagnosis challenging. Thus, rapid and accurate risk stratification is of paramount importance. High-risk PE is caused by right ventricular (RV) dysfunction from acute pressure overload, which in return can help identify which patients require more aggressive therapy. Reconstructed four-chamber views of the heart on chest CT can detect right ventricular enlargement. CT pulmonary angiography (CTPA) is the golden standard in the diagnostic workup of suspected PE. Therefore, it can link between diagnosis and risk stratification strategies. We developed a weakly supervised deep learning algorithm, with an emphasis on a novel attention mechanism, to automatically classify RV strain on CTPA. Our method is a 3D DenseNet model with integrated 3D residual attention blocks. We evaluated our model on a dataset of CTPAs of emergency department (ED) PE patients. This model achieved an area under the receiver operating characteristic curve (AUC) of 0.88 for classifying RV strain. The model showed a sensitivity of 87% and specificity of 83.7%. Our solution outperforms state-of-the-art 3D CNN networks. The proposed design allows for a fully automated network that can be trained easily in an end-to-end manner without requiring computationally intensive and time-consuming preprocessing or strenuous labeling of the data.We infer that unmarked CTPAs can be used for effective RV strain classification. This could be used as a second reader, alerting for high-risk PE patients. To the best of our knowledge, there are no previous deep learning-based studies that attempted to solve this problem.
description: 12 pages, 6 figures, 5 tables
Vincular Pattern Avoidance on Cyclic Permutations
Creators: name: Li, Rupert
Publisher: name: arXiv
Year: 2021
Subjects: subject: Combinatorics (math.CO)
subject: FOS: Mathematics
subject: 05A05

description: Pattern avoidance for permutations has been extensively studied, and has been generalized to vincular patterns, where certain elements can be required to be adjacent. In addition, cyclic permutations, i.e., permutations written in a circle rather than a line, have been frequently studied, including in the context of pattern avoidance. We investigate vincular pattern avoidance on cyclic permutations. In particular, we enumerate many avoidance classes of sets of vincular patterns of length 3, including a complete enumeration for all single patterns of length 3. Further, several of the avoidance classes corresponding to a single vincular pattern of length 4 are enumerated by the Catalan numbers. We then study more generally whether sets of vincular patterns of an arbitrary length $k$ can be avoided for arbitrarily long cyclic permutations, in particular investigating the boundary cases of minimal unavoidable sets and maximal avoidable sets.
description: To appear in Enumerative Combinatorics and Applications. 32 pages, 5 figures
Infinitesimal reference frames suffice to determine the asymmetry properties of a quantum system
Creators: name: Alexander, Rhea
name: Gvirtz-Chen, Si
name: Jennings, David
Publisher: name: arXiv
Year: 2021
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Symmetry principles are fundamental in physics, and while they are well understood within Lagrangian mechanics, their impact on quantum channels has a range of open questions. The theory of asymmetry grew out of information-theoretic work on entanglement and quantum reference frames, and allows us to quantify the degree to which a quantum system encodes coordinates of a symmetry group. Recently, a complete set of entropic conditions was found for asymmetry in terms of correlations relative to infinitely many quantum reference frames. However, these conditions are difficult to use in practice and their physical implications unclear. In the present theoretical work, we show that this set of conditions has extensive redundancy, and one can restrict to reference frames forming any closed surface in the state space that has the maximally mixed state in its interior. This in turn implies that asymmetry can be reduced to just a single entropic condition evaluated at the maximally mixed state. Contrary to intuition, this shows that we do not need macroscopic, classical reference frames to determine the asymmetry properties of a quantum system, but instead infinitesimally small frames suffice. Building on this analysis, we provide simple, closed conditions to estimate the minimal depolarization needed to make a given quantum state accessible under channels covariant with any given symmetry group.
description: 35 pages, 5 figures. Comments welcome! v4 and v3: added corresponding author email address and corrected a few citation errors. v2: Improved proof of lemma 26 (previously lemma 25), minor correction in the generalisation of the $\alpha=2$ Sandwiched R\'{e}yni entropy, slight expansion on conical behaviour of $\Delta H$ at the maximally mixed state, and corrections of minor typos throughout
Microscopic evidence for anisotropic multigap superconductivity in the CsV$_3$Sb$_5$ kagome superconductor
Creators: name: Gupta, Ritu
name: Das, Debarchan
name: Mielke, Charles Hillis
name: Guguchia, Zurab
name: Shiroka, Toni
name: Baines, Christopher
name: Bartkowiak, Marek
name: Luetkens, Hubertus
name: Khasanov, Rustem
name: Yin, Qiangwei
name: Tu, Zhijun
name: Gong, Chunsheng
name: Lei, Hechang
Publisher: name: arXiv
Year: 2021
Subjects: subject: Superconductivity (cond-mat.supr-con)
subject: Materials Science (cond-mat.mtrl-sci)
subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: The recently discovered kagome superconductor CsV$_3$Sb$_5$ ($T_c \simeq 2.5$ K) has been found to host charge order as well as a non-trivial band topology, encompassing multiple Dirac points and probable surface states. Such a complex and phenomenologically rich system is, therefore, an ideal playground for observing unusual electronic phases. Here, we report on microscopic studies of its anisotropic superconducting properties by means of transverse-field muon spin rotation ($μ$SR) experiments. The temperature dependences of the in-plane and out-of-plane components of the magnetic penetration depth $λ_{ab}^{-2}(T)$ and $λ_{c}^{-2}(T)$ indicate that the superconducting order parameter exhibits a two-gap ($s+s$)-wave symmetry, reflecting the multiple Fermi surfaces of CsV3Sb5. The multiband nature of its superconductivity is further validated by the different temperature dependences of the anisotropic magnetic penetration depth $γ_λ(T)$ and upper critical field $γ_{\rm B_{c2}}(T)$, both in close analogy with the well known two-gap superconductor MgB$_2$. Remarkably, the high value of the $T_c/λ^{-2}(0)$ ratio in both field orientations strongly suggests the unconventional nature of superconductivity. The relaxation rates obtained from zero field $μ$SR experiments do not show noticeable change across the superconducting transition, indicating that superconductivity does not break time reversal symmetry.
description: 9 pages, 4 figures
Simple black-box universal adversarial attacks on medical image classification based on deep neural networks
Creators: name: Koga, Kazuki
name: Takemoto, Kazuhiro
Publisher: name: arXiv
Year: 2021
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Cryptography and Security (cs.CR)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: Universal adversarial attacks, which hinder most deep neural network (DNN) tasks using only a small single perturbation called a universal adversarial perturbation (UAP), is a realistic security threat to the practical application of a DNN. In particular, such attacks cause serious problems in medical imaging. Given that computer-based systems are generally operated under a black-box condition in which only queries on inputs are allowed and outputs are accessible, the impact of UAPs seems to be limited because well-used algorithms for generating UAPs are limited to a white-box condition in which adversaries can access the model weights and loss gradients. Nevertheless, we demonstrate that UAPs are easily generatable using a relatively small dataset under black-box conditions. In particular, we propose a method for generating UAPs using a simple hill-climbing search based only on DNN outputs and demonstrate the validity of the proposed method using representative DNN-based medical image classifications. Black-box UAPs can be used to conduct both non-targeted and targeted attacks. Overall, the black-box UAPs showed high attack success rates (40% to 90%), although some of them had relatively low success rates because the method only utilizes limited information to generate UAPs. The vulnerability of black-box UAPs was observed in several model architectures. The results indicate that adversaries can also generate UAPs through a simple procedure under the black-box condition to foil or control DNN-based medical image diagnoses, and that UAPs are a more realistic security threat.
description: 19 pages, 3 figures, 2 tables
Theory of Topological Superconductivity in Doped IV-VI Semiconductors
Creators: name: Li, Zhe
name: Qin, Shengshan
name: Ren, Jie
name: Song, Zhida
name: Shao, Dexi
name: Fang, Chen
Publisher: name: arXiv
Year: 2021
Subjects: subject: Superconductivity (cond-mat.supr-con)
subject: FOS: Physical sciences

description: We theoretically study potential unconventional superconductivity in doped AB-type IV-VI semi-conductors, based on a minimal effective model with interaction up to the next-nearest neighbors. According to the experimental implications, we focus on the spin-triplet channels and obtain the superconducting phase diagram with respect to the anisotropy of the Fermi surfaces and the interaction strength. Abundant nodal and nodeless states with different symmetry breaking appear in the phase diagram, and all the states are time reversal invariant and topologically nontrivial. Specifically, the various nodal superconducting ground states, dubbed as the topological Dirac superconductors, are featured by Dirac nodes in the bulk and Majorana arcs on the surface; among the full-gap states, there exist a mirror-symmetry-protected second-order topological superconductor state favoring helical Majorana hinge cones, and different first-order topological superconductor states supporting 4 surface Majorana cones. The experimental verification of the different kinds of superconducting ground states is also discussed.
description: 31 pages, 7 figures, Accepted version
Detection of nearly periodic spin period reversals in Vela X-1 on long time-scales: inkling of solar-like cycle in the donor star?
Creators: name: Chandra, Amar Deo
name: Roy, Jayashree
name: Agrawal, P. C.
name: Choudhury, Manojendu
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Astrophysical Phenomena (astro-ph.HE)
subject: FOS: Physical sciences

description: We explore the long-term evolution of the spin period of the High Mass X-ray Binary (HMXB) pulsar Vela X-1 over a period of 46 yr. Our analysis indicates nearly periodic variations in the spin period of the pulsar on time-scales of about 5.9 yr. There is suggestion of an overall spin-down behaviour of the pulsar though it is noticed that the source appears to stay near its equilibrium period 283.4 s since MJD 51000, with rather erratic spin-up/spin-down episodes around this value. Our study suggests nearly cyclic turnover in the spin behaviour of the pulsar from spin-up to spin-down regimes on time-scales of about 17-19 yr. To our knowledge this is the first report of periodic variation in the spin behaviour of a wind-fed accreting pulsar. We also observe erratic episodes of spin-up and spin-down behaviour on relatively shorter time-scales which is a well known archetype of this wind-fed X-ray pulsar. We investigate whether nearly periodic long-term spin period changes in the pulsar can be explained by using known mechanisms of torque reversals in the accretion powered neutron stars. It appears that changes in the accretion environment of the pulsar using current ideas can probably lead to long-term spin period changes in this X-ray pulsar.
description: 15 pages, 7 figures, Accepted for publication in MNRAS
Complexity-like properties and parameter asymptotics of $\mathfrak{L}_{q}$-norms of Laguerre and Gegenbauer polynomials
Creators: name: Dehesa, Jesús S.
name: Sobrino, Nahual
Publisher: name: arXiv
Year: 2021
Subjects: subject: Mathematical Physics (math-ph)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: The main monotonic statistical complexity-like measures of the Rakhmanov's probability density associated to the hypergeometric orthogonal polynomials (HOPs) in a real continuous variable, each of them quantifying two configurational facets of spreading, are examined in this work beyond the Cramér-Rao one. The Fisher-Shannon and LMC (López-Ruiz-Mancini-Calvet) complexity measures, which have two entropic components, are analytically expressed in terms of the degree and the orthogonality weight's parameter(s) of the polynomials. The degree and parameter asymptotics of these two-fold spreading measures are shown for the parameter-dependent families of HOPs of Laguerre and Gegenbauer types. This is done by using the asymptotics of the Rényi and Shannon entropies, which are closely connected to the $\mathfrak{L}_{q}$-norms of these polynomials, when the weight's parameter tends towards infinity. The degree and parameter asymptotics of these Laguerre and Gegenbauer algebraic norms control the radial and angular charge and momentum distributions of numerous relevant multidimensional physical systems with a spherically-symmetric quantum-mechanical potential in the high-energy (Rydberg) and high-dimensional (quasi-classical) states, respectively. This is because the corresponding states' wavefunctions are expressed by means of the Laguerre and Gegenbauer polynomials in both position and momentum spaces.
description: 23 pages
Online Range Image-based Pole Extractor for Long-term LiDAR Localization in Urban Environments
Creators: name: Dong, Hao
name: Chen, Xieyuanli
name: Stachniss, Cyrill
Publisher: name: arXiv
Year: 2021
Subjects: subject: Robotics (cs.RO)
subject: FOS: Computer and information sciences

description: Reliable and accurate localization is crucial for mobile autonomous systems. Pole-like objects, such as traffic signs, poles, lamps, etc., are ideal landmarks for localization in urban environments due to their local distinctiveness and long-term stability. In this paper, we present a novel, accurate, and fast pole extraction approach that runs online and has little computational demands such that this information can be used for a localization system. Our method performs all computations directly on range images generated from 3D LiDAR scans, which avoids processing 3D point cloud explicitly and enables fast pole extraction for each scan. We test the proposed pole extraction and localization approach on different datasets with different LiDAR scanners, weather conditions, routes, and seasonal changes. The experimental results show that our approach outperforms other state-of-the-art approaches, while running online without a GPU. Besides, we release our pole dataset to the public for evaluating the performance of pole extractor, as well as the implementation of our approach.
description: Accepted by ECMR 2021
Quantum information approach to high energy interactions
Creators: name: Kharzeev, Dmitri E.
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: High Energy Physics - Theory (hep-th)
subject: Nuclear Theory (nucl-th)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: High energy hadron interactions are commonly described by using a probabilistic parton model that ignores quantum entanglement present in the light-cone wave functions. Here we argue that since a high energy interaction samples an instant snapshot of the hadron wave function, the phases of different Fock state wave functions cannot be measured - therefore the light-cone density matrix has to be traced over these unobservable phases. Performing this trace with the corresponding $U(1)$ Haar integration measure leads to "Haar scrambling" of the density matrix, and to the emergence of entanglement entropy. This entanglement entropy is determined by the Fock state probability distribution, and is thus directly related to the parton structure functions. As proposed earlier, at large rapidity $η$ the hadron state becomes maximally entangled, and the entanglement entropy is $S_E \sim η$ according to QCD evolution equations. When the phases of Fock state components are controlled, for example in spin asymmetry measurements, the Haar average cannot be performed, and the probabilistic parton description breaks down.
description: 9 pages; one typo corrected for archiving purposes, no other changes
Three-dimensional chiral Veselago lensing
Creators: name: Tchoumakov, Serguei
name: Cayssol, Jérôme
name: Grushin, Adolfo G.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: FOS: Physical sciences

description: The effect by which light focuses upon entering a medium with a negative refractive index, known as Veselago lensing, may enable optical imaging below the diffraction limit. Similarly, focusing electrons across a $pn$-junction could realize a technologically promising electronic Veselago lens. However, its scope remains limited by the lack of three-dimensional platforms and its insensitivity to computational degrees of freedom, like spin or chirality. Here we propose a single-material three-dimensional electronic Veselago lens that selectively focuses electrons of a given chirality. Using the chiral anomaly of topological semimetals it is possible to create a sharp $pn$-junction for a single chirality, a chiral Veselago lens, and tune it with a magnetic field to an ideal lensing condition. We estimate that chiral Veselago lensing is observable in non-local transport and spectroscopy experiments. In particular we show that the chiral Veselago lens leads to giant non-local magnetoresistance.
description: 5 pages, 3 figures ; supplementary material included
Understanding Data Storage and Ingestion for Large-Scale Deep Recommendation Model Training
Creators: name: Zhao, Mark
name: Agarwal, Niket
name: Basant, Aarti
name: Gedik, Bugra
name: Pan, Satadru
name: Ozdal, Mustafa
name: Komuravelli, Rakesh
name: Pan, Jerry
name: Bao, Tianshu
name: Lu, Haowei
name: Narayanan, Sundaram
name: Langman, Jack
name: Wilfong, Kevin
name: Rastogi, Harsha
name: Wu, Carole-Jean
name: Kozyrakis, Christos
name: Pol, Parik
Publisher: name: arXiv
Year: 2021
Subjects: subject: Distributed, Parallel, and Cluster Computing (cs.DC)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: Datacenter-scale AI training clusters consisting of thousands of domain-specific accelerators (DSA) are used to train increasingly-complex deep learning models. These clusters rely on a data storage and ingestion (DSI) pipeline, responsible for storing exabytes of training data and serving it at tens of terabytes per second. As DSAs continue to push training efficiency and throughput, the DSI pipeline is becoming the dominating factor that constrains the overall training performance and capacity. Innovations that improve the efficiency and performance of DSI systems and hardware are urgent, demanding a deep understanding of DSI characteristics and infrastructure at scale. This paper presents Meta's end-to-end DSI pipeline, composed of a central data warehouse built on distributed storage and a Data PreProcessing Service that scales to eliminate data stalls. We characterize how hundreds of models are collaboratively trained across geo-distributed datacenters via diverse and continuous training jobs. These training jobs read and heavily filter massive and evolving datasets, resulting in popular features and samples used across training jobs. We measure the intense network, memory, and compute resources required by each training job to preprocess samples during training. Finally, we synthesize key takeaways based on our production infrastructure characterization. These include identifying hardware bottlenecks, discussing opportunities for heterogeneous DSI hardware, motivating research in datacenter scheduling and benchmark datasets, and assimilating lessons learned in optimizing DSI infrastructure.
description: In The 49th Annual International Symposium on Computer Architecture (ISCA 2022)
Implementation of Angularly Ordered Electroweak Parton Shower in Herwig 7
Creators: name: Masouminia, M. R.
name: Richardson, P.
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: FOS: Physical sciences

description: We discuss the necessary steps for implementing an angularly ordered (AO) electroweak (EW) parton shower in Herwig 7 multi-purpose event generator. This includes calculating the helicity-dependent quasi-collinear EW branching functions that correspond to the full range of final-state EW parton shower, in addition to the initial-state EW gauge vector boson radiations. The results are successfully embedded in the AO Herwig 7 shower algorithm and have undergone a set of comprehensive and conclusive performance tests. Furthermore, we have used this EW parton shower algorithm, alongside the existing $QCD+QED$ AO shower, to predict the angular distributions of $W^{\pm}$ bosons in LHC events with high transverse momentum jets. These results are compared against the explicitly generated underlying events as well as the existing ATLAS data to show the effectiveness of the newly implemented $QCD+QED+EW$ AO parton shower scheme.
description: 26 pages, 15 figures and 4 tables
Geometric control of topological dynamics in a singing saw
Creators: name: Shankar, Suraj
name: Bryde, Petur
name: Mahadevan, L.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Soft Condensed Matter (cond-mat.soft)
subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: Materials Science (cond-mat.mtrl-sci)
subject: Applied Physics (physics.app-ph)
subject: FOS: Physical sciences

description: The common handsaw can be converted into a bowed musical instrument capable of producing exquisitely sustained notes when its blade is appropriately bent. Acoustic modes localized at an inflection point are known to underlie the saw's sonorous quality, yet the origin of localization has remained mysterious. Here we uncover a topological basis for the existence of localized modes, that relies on and is protected by spatial curvature. By combining experimental demonstrations, theory and computation, we show how spatial variations in blade curvature control the localization of these trapped states, allowing the saw to function as a geometrically tunable high quality oscillator. Our work establishes an unexpected connection between the dynamics of thin shells and topological insulators, and offers a robust principle to design high quality resonators across scales, from macroscopic instruments to nanoscale devices, simply through geometry.
description: 17 pages, 3 figures, SI available upon request
Supporting information - How does dispersal shape the genetic patterns of animal populations in European cities? A simulation approach
Creators: name: Savary, Paul
name: Tannier, Cécile
name: Foltête, Jean-Christophe
name: Bourgeois, Marc
name: Vuidel, Gilles
name: Khimoun, Aurélie
name: Garnier, Stéphane
Publisher: name: Zenodo
Year: 2024
Subjects: urban ecology
ecological networks
gene flow
biodiversity conservation
green infrastructures

description: Supporting information for "How does dispersal shape the genetic patterns of animal populations in European cities? A simulation approach"
ПРЕПОДАВАНИЕ ФРАЗЕОЛОГИИ РУССКОГО ЯЗЫКА НА УРОКАХ РУССКОГО ЯЗЫКА КАК ИНОСТРАННОГО
Creators: name: Расулова, Шахзода
name: Акрамова, Г.И.
Publisher: name: Zenodo
Year: 2024

description: Статья посвящена методическим аспектам обучения фразеологии учащихся, изучающих русский язык как иностранный. В работе рассматриваются основные подходы и методы, используемые в преподавании фразеологических единиц, а также подчеркивается важность их интеграции в учебный процесс для более глубокого понимания культурных и языковых особенностей русского языка.
Task-Oriented Dialogue System as Natural Language Generation
Creators: name: Wang, Weizhi
name: Zhang, Zhirui
name: Guo, Junliang
name: Dai, Yinpei
name: Chen, Boxing
name: Luo, Weihua
Publisher: name: arXiv
Year: 2021
Subjects: subject: Computation and Language (cs.CL)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: In this paper, we propose to formulate the task-oriented dialogue system as the purely natural language generation task, so as to fully leverage the large-scale pre-trained models like GPT-2 and simplify complicated delexicalization prepossessing. However, directly applying this method heavily suffers from the dialogue entity inconsistency caused by the removal of delexicalized tokens, as well as the catastrophic forgetting problem of the pre-trained model during fine-tuning, leading to unsatisfactory performance. To alleviate these problems, we design a novel GPT-Adapter-CopyNet network, which incorporates the lightweight adapter and CopyNet modules into GPT-2 to achieve better performance on transfer learning and dialogue entity generation. Experimental results conducted on the DSTC8 Track 1 benchmark and MultiWOZ dataset demonstrate that our proposed approach significantly outperforms baseline models with a remarkable performance on automatic and human evaluations.
description: SIGIR 2022
Multi-impurity chiral Kondo model: correlation functions and anyon fusion rules
Creators: name: Gabay, Dor
name: Han, Cheolhee
name: Lopes, Pedro L. S.
name: Affleck, Ian
name: Sela, Eran
Publisher: name: arXiv
Year: 2021
Subjects: subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: The multichannel Kondo model supports effective anyons on the partially screened impurity, as suggested by its fractional impurity entropy. It was recently demonstrated for the multi-impurity chiral Kondo model, that scattering of an electron through the impurities depends on the anyon's total fusion channel. Here we study the correlation between impurity-spins. We argue, based on a combination of conformal field theory, a perturbative limit with a large number of channels $k$, and the exactly solvable two-channel case, that the inter-impurity spin correlation probes the anyon fusion of the pair of correlated impurities. This may allow, using measurement-only topological quantum computing protocols, to braid the multichannel Kondo anyons via consecutive measurements.