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arxiv_dataset-107001901.00453
Spectral asymptotics of radial solutions and nonradial bifurcation for the H\'enon equation math.AP We study the spectral asymptotics of nodal (i.e., sign-changing) solutions of the problem \begin{equation*} (H) \qquad \qquad \left \{ \begin{aligned} -\Delta u &=|x|^\alpha |u|^{p-2}u&&\qquad \text{in ${\bf B}$,} \\ u&=0&&\qquad \text{on $\partial {\bf B}$,} \end{aligned} \right. \end{equation*} in the unit ball ${\bf B} \subset \mathbb{R}^N,N\geq 3$, $p>2$ in the limit $\alpha \to +\infty$. More precisely, for a given positive integer $K$, we derive asymptotic $C^1$-expansions for the negative eigenvalues of the linearization of the unique radial solution $u_\alpha$ of $(H)$ with precisely $K$ nodal domains and $u_\alpha(0)>0$. As an application, we derive the existence of an unbounded sequence of bifurcation points on the radial solution branch $\alpha \mapsto (\alpha,u_\alpha)$ which all give rise to bifurcation of nonradial solutions whose nodal sets remain homeomorphic to a disjoint union of concentric spheres.
arxiv topic:math.AP
arxiv_dataset-107011901.00553
An adaptive stigmergy-based system for evaluating technological indicator dynamics in the context of smart specialization cs.AI cs.CY Regional innovation is more and more considered an important enabler of welfare. It is no coincidence that the European Commission has started looking at regional peculiarities and dynamics, in order to focus Research and Innovation Strategies for Smart Specialization towards effective investment policies. In this context, this work aims to support policy makers in the analysis of innovation-relevant trends. We exploit a European database of the regional patent application to determine the dynamics of a set of technological innovation indicators. For this purpose, we design and develop a software system for assessing unfolding trends in such indicators. In contrast with conventional knowledge-based design, our approach is biologically-inspired and based on self-organization of information. This means that a functional structure, called track, appears and stays spontaneous at runtime when local dynamism in data occurs. A further prototyping of tracks allows a better distinction of the critical phenomena during unfolding events, with a better assessment of the progressing levels. The proposed mechanism works if structural parameters are correctly tuned for the given historical context. Determining such correct parameters is not a simple task since different indicators may have different dynamics. For this purpose, we adopt an adaptation mechanism based on differential evolution. The study includes the problem statement and its characterization in the literature, as well as the proposed solving approach, experimental setting and results.
arxiv topic:cs.AI cs.CY
arxiv_dataset-107021901.00653
A space-consistent version of the minimum-contrast estimator for linear stochastic evolution equations math.PR A new modification of the minimum-contrast estimator (the weighted MCE) of drift parameter in a linear stochastic evolution equation with additive fractional noise is introduced in the setting of the spectral approach (Fourier coordinates of the solution are observed). The reweighing technique, which utilizes the self-similarity property, achieves strong consistency and asymptotic normality of the estimator as number of coordinates increases and time horizon is fixed (the space consistency). In this respect, this modification outperforms the standard (non-weighted) minimum-contrast estimator. Compared to other drift estimators studied within spectral approach (eg. maximum likelihood, trajectory fitting), the weighted MCE is rather universal. It covers discrete time as well as continuous time observations and it is applicable to processes with any value of Hurst index $H \in (0,1)$. To the author's best knowledge, this is so far the first space-consistent estimator studied for $H < 1/2$.
arxiv topic:math.PR
arxiv_dataset-107031901.00753
Experimental demonstration of spectrally-broadband Huygens sources using low-index spheres physics.class-ph physics.optics Manipulating the excitation of resonant electric and magnetic multipole moments in structured dielectric media has unlocked many sophisticated electromagnetic functionalities. This article demonstrates the experimental realization of a broadband Huygens' source. This Huygens' source consists of a spherical particle that exhibits a well-defined forward-scattering pattern across more than an octave-spanning spectral band at GHz frequencies, where the scattering in the entire backward hemisphere is suppressed. Two different low-index nonmagnetic spheres are studied that differ in their permittivity. This causes them to offer a different shape for the forward-scattering pattern. The theoretical understanding of this broadband feature is based on the approximate equality of the resonant electric and magnetic multipole moments in both amplitude and phase in low permittivity spheres. This is a key condition to approximate the electromagnetic duality symmetry which, together with the spherical symmetry, suppresses the backscattering. With such a configuration, broadband Huygens' sources can be designed even if magnetic materials are unavailable. This article provides guidelines for designing broadband Huygens' sources using low-index spheres that could be valuable to a plethora of applications.
arxiv topic:physics.class-ph physics.optics
arxiv_dataset-107041901.00853
Experimental investigation of majorization uncertainty relations in the high-dimensional systems quant-ph Uncertainty relation is not only of fundamental importance to quantum mechanics, but also crucial to the quantum information technology. Recently, majorization formulation of uncertainty relations (MURs) have been widely studied, ranging from two measurements to multiple measurements. Here, for the first time, we experimentally investigate MURs for two measurements and multiple measurements in the high-dimensional systems, and study the intrinsic distinction between direct-product MURs and direct-sum MURs. The experimental results reveal that by taking different nonnegative Schur-concave functions as uncertainty measure, the two types of MURs have their own particular advantages, and also verify that there exists certain case where three-measurement majorization uncertainty relation is much stronger than the one obtained by summing pairwise two-measurement uncertainty relations. Our work not only fills the gap of experimental studies of majorization uncertainty relations, but also represents an advance in quantitatively understanding and experimental verification of majorization uncertainty relations which are universal and capture the essence of uncertainty in quantum theory.
arxiv topic:quant-ph
arxiv_dataset-107051901.00953
Unified view of nonlinear wave structures associated with whistler-mode chorus physics.space-ph astro-ph.SR physics.plasm-ph A range of nonlinear wave structures, including Langmuir waves, unipolar electric fields and bipolar electric fields, are often observed in association with whistler-mode chorus waves in the near-Earth space. We demonstrate that the three seemingly different nonlinear wave structures originate from the same nonlinear electron trapping process by whistler-mode chorus waves. The ratio of the Landau resonant velocity to the electron thermal velocity controls the type of nonlinear wave structures that will be generated.
arxiv topic:physics.space-ph astro-ph.SR physics.plasm-ph
arxiv_dataset-107061901.01053
Cyber Security Challenges and Solutions for V2X Communications: A Survey cs.IT math.IT In recent years, vehicles became able to establish connections with other vehicles and infrastructure units that are located in the roadside. In the near future, the vehicular network will be expanded to include the communication between vehicles and any smart devices in the roadside which is called Vehicle-to-Everything (V2X) communication. The vehicular network causes many challenges due to heterogeneous nodes, various speeds and intermittent connection, where traditional security methods are not always efficacious. As a result, an extensive variety of research works has been done on optimizing security solutions whilst considering network requirements. In this paper, we present a comprehensive survey and taxonomy of the existing security solutions for V2X communication technology. Then, we provide discussions and comparisons with regard to some pertinent criteria. Also, we present a threat analysis for V2X enabling technologies. Finally, we point out the research challenges and some future directions.
arxiv topic:cs.IT math.IT
arxiv_dataset-107071901.01153
Demystifying Multi-Faceted Video Summarization: Tradeoff Between Diversity,Representation, Coverage and Importance cs.CV This paper addresses automatic summarization of videos in a unified manner. In particular, we propose a framework for multi-faceted summarization for extractive, query base and entity summarization (summarization at the level of entities like objects, scenes, humans and faces in the video). We investigate several summarization models which capture notions of diversity, coverage, representation and importance, and argue the utility of these different models depending on the application. While most of the prior work on submodular summarization approaches has focused oncombining several models and learning weighted mixtures, we focus on the explainability of different models and featurizations, and how they apply to different domains. We also provide implementation details on summarization systems and the different modalities involved. We hope that the study from this paper will give insights into practitioners to appropriately choose the right summarization models for the problems at hand.
arxiv topic:cs.CV
arxiv_dataset-107081901.01253
Towards Constraining Parity-Violations in Gravity with Satellite Gradiometry gr-qc Parity violation in gravity, if existed, could have important implications, and it is meaningful to search and test the possible observational effects. Chern-Simons modified gravity serves as a natural model for gravitational parity-violations. Especially, considering extensions to Einstein-Hilbert action up to second order curvature terms, it is known that theories of gravitational parity-violation will reduce to the dynamical Chern-Simons gravity. In this letter, we outline the theoretical principles of testing the dynamical Chern-Simons gravity with orbiting gravity gradiometers, which could be naturally incorporated into future satellite gravity missions. The secular gravity gradient signals, due to the Mashhoon-Theiss (anomaly) effect, in dynamical Chern-Simons gravity are worked out, which can improve the constraint of the corresponding Chern-Simons length scale $\xi^{\frac{1}{4}}_{cs}$ obtained from such measurement scheme. For orbiting superconducting gradiometers or gradiometers with optical readout, a bound $\xi^{\frac{1}{4}}_{cs}\leq 10^6 \ km$ (or even better) could in principle be obtained, which will be at least 2 orders of magnitude stronger than the current one based on the observations from the GP-B mission and the LAGEOS I, II satellites.
arxiv topic:gr-qc
arxiv_dataset-107091901.01353
Observations of A Fast-Expanding and UV-Bright Type Ia Supernova SN 2013gs astro-ph.HE astro-ph.SR In this paper, we present extensive optical and ultraviolet (UV) observations of the type Ia supernova (SN Ia) 2013gs discovered during the Tsinghua-NAOC Transient Survey. The photometric observations in the optical show that the light curves of SN 2013gs is similar to that of normal SNe Ia, with an absolute peak magnitude of $M_{B}$ = $-$19.25 $\pm$ 0.15 mag and a post-maximum decline rate $\Delta$m$_{15}$(B) = 1.00 $ \pm $ 0.05 mag. \emph{Gehrels Swift} UVOT observations indicate that SN 2013gs shows unusually strong UV emission (especially in the $uvw1$ band) at around the maximum light (M$_{uvw1}$ $\sim$ $-$18.9 mag). The SN is characterized by relatively weak Fe~{\sc ii} {\sc iii} absorptions at $\sim$ 5000{\AA} in the early spectra and a larger expansion velocity ($v_{Si}$ $\sim$ 13,000 km s$^{-1}$ around the maximum light) than the normal-velocity SNe Ia. We discuss the relation between the $uvw1-v$ color and some observables, including Si~{\sc ii} velocity, line strength of Si~{\sc ii} $\lambda$6355, Fe~{\sc ii}/{\sc iii} lines and $\Delta m_{15}$(B). Compared to other fast-expanding SNe Ia, SN 2013gs exhibits Si and Fe absorption lines with similar strength and bluer $uvw1-v$ color. We briefly discussed the origin of the observed UV dispersion of SNe Ia.
arxiv topic:astro-ph.HE astro-ph.SR
arxiv_dataset-107101901.01453
Metrics on triangulated categories math.CT math.AG math.AT math.RT In this survey we explain the results of the recent article arXiv:1806.06471. Following a 1973 article by Lawvere one can define metrics on categories, and following Kelly's 1982 book one can complete a category with respect to its metric. We specialize these general constructions to triangulated categories, and restrict our attention to "good metrics". And the remarkable new theorem is that, when we start with a triangulated category $\mathcal S$ with a good metric, its completion $\mathfrak{L}(\mathcal{S})$ contains an interesting subcategory $\mathfrak{S}(\mathcal{S})$ which is always triangulated. As special cases we obtain $\mathcal{H}^0(\mathrm{Perf}(X))$ and $D^b_{\mathrm{coh}}(X)$ from each other. We also give a couple of other examples.
arxiv topic:math.CT math.AG math.AT math.RT
arxiv_dataset-107111901.01553
Search for dark matter produced in association with a single top quark or a top quark pair in proton-proton collisions at $\sqrt{s} =$ 13 TeV hep-ex A search for dark matter produced in association with top quarks in proton-proton collisions at a center-of-mass energy of 13 TeV is presented. The data set used corresponds to an integrated luminosity of 35.9 fb$^{-1}$ recorded with the CMS detector at the LHC. Whereas previous searches for neutral scalar or pseudoscalar mediators considered dark matter production in association with a top quark pair only, this analysis also includes production modes with a single top quark. The results are derived from the combination of multiple selection categories that are defined to target either the single top quark or the top quark pair signature. No significant deviations with respect to the standard model predictions are observed. The results are interpreted in the context of a simplified model in which a scalar or pseudoscalar mediator particle couples to a top quark and subsequently decays into dark matter particles. Scalar and pseudoscalar mediator particles with masses below 290 and 300 GeV, respectively, are excluded at 95% confidence level, assuming a dark matter particle mass of 1 GeV and mediator couplings to fermions and dark matter particles equal to unity.
arxiv topic:hep-ex
arxiv_dataset-107121901.01653
Learning Nonlinear Input-Output Maps with Dissipative Quantum Systems quant-ph cs.LG cs.SY eess.SY In this paper, we develop a theory of learning nonlinear input-output maps with fading memory by dissipative quantum systems, as a quantum counterpart of the theory of approximating such maps using classical dynamical systems. The theory identifies the properties required for a class of dissipative quantum systems to be {\em universal}, in that any input-output map with fading memory can be approximated arbitrarily closely by an element of this class. We then introduce an example class of dissipative quantum systems that is provably universal. Numerical experiments illustrate that with a small number of qubits, this class can achieve comparable performance to classical learning schemes with a large number of tunable parameters. Further numerical analysis suggests that the exponentially increasing Hilbert space presents a potential resource for dissipative quantum systems to surpass classical learning schemes for input-output maps.
arxiv topic:quant-ph cs.LG cs.SY eess.SY
arxiv_dataset-107131901.01753
Paired Open-Ended Trailblazer (POET): Endlessly Generating Increasingly Complex and Diverse Learning Environments and Their Solutions cs.NE While the history of machine learning so far largely encompasses a series of problems posed by researchers and algorithms that learn their solutions, an important question is whether the problems themselves can be generated by the algorithm at the same time as they are being solved. Such a process would in effect build its own diverse and expanding curricula, and the solutions to problems at various stages would become stepping stones towards solving even more challenging problems later in the process. The Paired Open-Ended Trailblazer (POET) algorithm introduced in this paper does just that: it pairs the generation of environmental challenges and the optimization of agents to solve those challenges. It simultaneously explores many different paths through the space of possible problems and solutions and, critically, allows these stepping-stone solutions to transfer between problems if better, catalyzing innovation. The term open-ended signifies the intriguing potential for algorithms like POET to continue to create novel and increasingly complex capabilities without bound. Our results show that POET produces a diverse range of sophisticated behaviors that solve a wide range of environmental challenges, many of which cannot be solved by direct optimization alone, or even through a direct-path curriculum-building control algorithm introduced to highlight the critical role of open-endedness in solving ambitious challenges. The ability to transfer solutions from one environment to another proves essential to unlocking the full potential of the system as a whole, demonstrating the unpredictable nature of fortuitous stepping stones. We hope that POET will inspire a new push towards open-ended discovery across many domains, where algorithms like POET can blaze a trail through their interesting possible manifestations and solutions.
arxiv topic:cs.NE
arxiv_dataset-107141901.01853
Primes in Beatty sequence math.NT For a polynomial $g(x)$ of deg $k \geq 2$ with integer coefficients and positive integer leading coefficient, we prove an upper bound for the least prime $p$ such that $g(p)$ is in non-homogeneous Beatty sequence $\lbrace \lfloor \alpha n+\beta\rfloor : n=1,2,3, \dots \rbrace$, where $\alpha, \beta \in \mathbb{R}$ with $\alpha >1$ is irrational and we prove an asymptotic formula for the number of primes $p$ such that $g(p)=\lfloor \alpha n+\beta \rfloor.$ Next we obtain an asymptotic formula for number of primes $p$ of the form $p=\lfloor \alpha n+\beta \rfloor$ which also satisfies $p \equiv f \pmod d$ where $f, d$ are integers with $1\leq f < d$ and $(f,d)=1$.
arxiv topic:math.NT
arxiv_dataset-107151901.01953
Modified Reynolds equation for steady flow through a curved pipe math-ph math.AP math.MP A modified Reynolds equation governing the steady flow of a fluid with low Reynolds number through a curvilinear, narrow tube, with its derivation from Stokes equations through asymptotic methods is presented. The channel considered may have large curvature and torsion. Approximations of the velocity and the pressure of the fluid inside the channel are constructed by artificially imposing appropriate boundary conditions at the inlet and the outlet. A justification for the approximations is provided along with a comparison with a simpler case.
arxiv topic:math-ph math.AP math.MP
arxiv_dataset-107161901.02053
Detecting the Trend in Musical Taste over the Decade -- A Novel Feature Extraction Algorithm to Classify Musical Content with Simple Features cs.IR cs.LG cs.SD eess.AS This work proposes a novel feature selection algorithm to classify Songs into different groups. Classification of musical content is often a non-trivial job and still relatively less explored area. The main idea conveyed in this article is to come up with a new feature selection scheme that does the classification job elegantly and with high accuracy but with simpler but wisely chosen small number of features thus being less prone to over-fitting. This uses a very basic general idea about the structure of the audio signal which is generally in the shape of a trapezium. So, using this general idea of the Musical Community we propose three frames to be considered and analyzed for feature extraction for each of the audio signal -- opening, stanzas and closing -- and it has been established with the help of a lot of experiments that this scheme leads to much efficient classification with less complex features in a low dimensional feature space thus is also a computationally less expensive method. Step by step analysis of feature extraction, feature ranking, dimensionality reduction using PCA has been carried in this article. Sequential Forward selection (SFS) algorithm is used to explore the most significant features both with the raw Fisher Discriminant Ratio (FDR) and also with the significant eigen-values after PCA. Also during classification extensive validation and cross validation has been done in a monte-carlo manner to ensure validity of the claims.
arxiv topic:cs.IR cs.LG cs.SD eess.AS
arxiv_dataset-107171901.02153
Audio Captcha Recognition Using RastaPLP Features by SVM cs.LG cs.SD eess.AS stat.ML Nowadays, CAPTCHAs are computer generated tests that human can pass but current computer systems can not. They have common usage in various web services in order to be able to detect a human from computer programs autonomously. In this way, owners can protect their web services from bots. In addition to visual CAPTCHAs which consist of distorted images, mostly test images, that a user must write some description about that image, there are a significant amount of audio CAPTCHAs as well. Briefly, audio CAPTCHAs are sound files which consist of human sound under heavy noise where the speaker pronounces a bunch of digits consecutively. Generally, in those sound files, there are some periodic and non-periodic noises to get difficult to recognize them with a program but not for a human listener. We gathered numerous randomly collected audio file to train and then test them using our SVM algorithm to be able to extract digits out of each conversation.
arxiv topic:cs.LG cs.SD eess.AS stat.ML
arxiv_dataset-107181901.02253
Thrust distribution in Higgs decays at the next-to-leading order and beyond hep-ph We present predictions for the thrust distribution in hadronic decays of the Higgs boson at the next-to-leading order and the approximate next-to-next-to-leading order. The approximate NNLO corrections are derived from a factorization formula in the soft/collinear phase-space regions. We find large corrections, especially for the gluon channel. The scale variations at the lowest orders tend to underestimate the genuine higher order contributions. The results of this paper is therefore necessary to control the perturbative uncertainties of the theoretical predictions. We also discuss on possible improvements to our results, such as a soft-gluon resummation for the 2-jets limit, and an exact next-to-next-to-leading order calculation for the multi-jets region.
arxiv topic:hep-ph
arxiv_dataset-107191901.02353
On neighbourhood degree sequences of complex networks cs.SI physics.soc-ph Network topology is a fundamental aspect of network science that allows us to gather insights into the complicated relational architectures of the world we inhabit. We provide a first specific study of neighbourhood degree sequences in complex networks. We consider how to explicitly characterise important physical concepts such as similarity, heterogeneity and organisation in these sequences, as well as updating the notion of hierarchical complexity to reflect previously unnoticed organisational principles. We also point out that neighbourhood degree sequences are related to a powerful subtree kernel for unlabelled graph classification. We study these newly defined sequence properties in a comprehensive array of graph models and over 200 real-world networks. We find that these indices are neither highly correlated with each other nor with classical network indices. Importantly, the sequences of a wide variety of real world networks are found to have greater similarity and organisation than is expected for networks of their given degree distributions. Notably, while biological, social and technological networks all showed consistently large neighbourhood similarity and organisation, hierarchical complexity was not a consistent feature of real world networks. Neighbourhood degree sequences are an interesting tool for describing unique and important characteristics of complex networks.
arxiv topic:cs.SI physics.soc-ph
arxiv_dataset-107201901.02453
Neural Inverse Rendering of an Indoor Scene from a Single Image cs.CV Inverse rendering aims to estimate physical attributes of a scene, e.g., reflectance, geometry, and lighting, from image(s). Inverse rendering has been studied primarily for single objects or with methods that solve for only one of the scene attributes. We propose the first learning-based approach that jointly estimates albedo, normals, and lighting of an indoor scene from a single image. Our key contribution is the Residual Appearance Renderer (RAR), which can be trained to synthesize complex appearance effects (e.g., inter-reflection, cast shadows, near-field illumination, and realistic shading), which would be neglected otherwise. This enables us to perform self-supervised learning on real data using a reconstruction loss, based on re-synthesizing the input image from the estimated components. We finetune with real data after pretraining with synthetic data. To this end, we use physically-based rendering to create a large-scale synthetic dataset, which is a significant improvement over prior datasets. Experimental results show that our approach outperforms state-of-the-art methods that estimate one or more scene attributes.
arxiv topic:cs.CV
arxiv_dataset-107211901.02553
The second RIT binary black hole simulations catalog and its application to gravitational waves parameter estimation gr-qc astro-ph.HE The RIT numerical relativity group is releasing the second public catalog of black-hole-binary waveforms \url{http://ccrg.rit.edu/~RITCatalog}. This release consists of 320 accurate simulations that include 46 precessing and 274 nonprecessing binary systems with mass ratios $q=m_1/m_2$ in the range $1/6\leq q\leq1$ and individual spins up to $s/m^2=0.95$. The new catalog contains search and ordering tools for the waveforms based on initial parameters of the binary, trajectory information, peak radiation, and final remnant black hole properties. The final black hole remnant properties provided here can be used to model the merger of black-hole binaries from its initial configurations. The waveforms are extrapolated to infinite observer location and can be used to independently interpret gravitational wave signals from laser interferometric detectors. As an application of this waveform catalog we reanalyze the signal of GW150914 implementing parameter estimation techniques that make use of only numerical waveforms without any reference to information from phenomenological models.
arxiv topic:gr-qc astro-ph.HE
arxiv_dataset-107221901.02653
A new proof of Jacquet-Rallis's fundamental lemma math.NT math.RT We give a new proof of the so-called Lie algebra version of Jacquet-Rallis's fundamental lemma for local non-Archimedean fields of characteristic zero. This proof is local and based on a previous result of W. Zhang on the compatibility of smooth transfer with a (partial) Fourier transform.
arxiv topic:math.NT math.RT
arxiv_dataset-107231901.02753
Diagrammatic Coupled Cluster Monte Carlo physics.chem-ph physics.comp-ph We propose a modified coupled cluster Monte Carlo algorithm that stochastically samples connected terms within the truncated Baker--Campbell--Hausdorff expansion of the similarity transformed Hamiltonian by construction of coupled cluster diagrams on the fly. Our new approach -- diagCCMC -- allows propagation to be performed using only the connected components of the similarity-transformed Hamiltonian, greatly reducing the memory cost associated with the stochastic solution of the coupled cluster equations. We show that for perfectly local, noninteracting systems, diagCCMC is able to represent the coupled cluster wavefunction with a memory cost that scales linearly with system size. The favorable memory cost is observed with the only assumption of fixed stochastic granularity and is valid for arbitrary levels of coupled cluster theory. Significant reduction in memory cost is also shown to smoothly appear with dissociation of a finite chain of helium atoms. This approach is also shown not to break down in the presence of strong correlation through the example of a stretched nitrogen molecule. Our novel methodology moves the theoretical basis of coupled cluster Monte Carlo closer to deterministic approaches.
arxiv topic:physics.chem-ph physics.comp-ph
arxiv_dataset-107241901.02853
Lambda Calculus and Probabilistic Computation cs.LO We introduce two extensions of the $\lambda$-calculus with a probabilistic choice operator, $\Lambda_\oplus^{cbv}$ and $\Lambda_\oplus^{cbn}$, modeling respectively call-by-value and call-by-name probabilistic computation. We prove that both enjoys confluence and standardization, in an extended way: we revisit these two fundamental notions to take into account the asymptotic behaviour of terms. The common root of the two calculi is a further calculus based on Linear Logic, $\Lambda_\oplus^!$, which allows for a fine control of the interaction between choice and copying, and which allows us to develop a unified, modular approach.
arxiv topic:cs.LO
arxiv_dataset-107251901.02953
Black hole scalarisation from the breakdown of scale-invariance gr-qc hep-th Electro-vacuum black holes are scale-invariant; their energy-momentum tensor is traceless. Quantum corrections of various sorts, however, can often produce a trace anomaly and a breakdown of scale-invariance. The (quantum-corrected) black hole solutions of the corresponding gravitational effective field theory (EFT) have a non-vanishing Ricci scalar. Then, the presence of a scalar field with the standard non-minimal coupling $\xi \phi^2 R$ naturally triggers a spontaneous scalarisation of the corresponding black holes. This scalarisation phenomenon occurs for an (infinite) discrete set of $\xi$. We illustrate the occurrence of this phenomenon for two examples of static, spherically symmetric, asymptotically flat black hole solution of EFTs. In one example the trace anomaly comes from the matter sector -- a novel, closed form, generalisation of the Reissner-Nordstr\"om solution with an $F^4$ correction -- whereas in the other example it comes from the geometry sector -- a noncommutative geometry generalization of the Schwarzschild black hole. For comparison, we also consider the scalarisation of a black hole surrounded by (non-conformally invariant) classical matter (Einstein-Maxwell-dilaton black holes). We find that the scalarised solutions are, generically, entropically favoured.
arxiv topic:gr-qc hep-th
arxiv_dataset-107261901.03053
Vibration isolation system with a compact damping system for power recycling mirrors of KAGRA physics.ins-det gr-qc A vibration isolation system called Type-Bp system used for power recycling mirrors has been developed for KAGRA, the interferometric gravitational-wave observatory in Japan. A suspension of the Type-Bp system passively isolates an optic from seismic vibration using three main pendulum stages equipped with two vertical vibration isolation systems. A compact reaction mass around each of the main stages allows for achieving sufficient damping performance with a simple feedback as well as vibration isolation ratio. Three Type-Bp systems were installed in KAGRA, and were proved to satisfy the requirements on the damping performance, and also on estimated residual displacement of the optics.
arxiv topic:physics.ins-det gr-qc
arxiv_dataset-107271901.03153
Optimal mean value estimates beyond Vinogradov's mean value theorem math.NT We establish improved mean value estimates associated with the number of integer solutions of certain systems of diagonal equations, in some instances attaining the sharpest conjectured conclusions. This is the first occasion on which bounds of this quality have been attained for Diophantine systems not of Vinogradov type. As a consequence of this progress, whenever $u \ge 3v$ we obtain the Hasse principle for systems consisting of $v$ cubic and $u$ quadratic diagonal equations in $6v+4u+1$ variables, thus attaining the convexity barrier for this problem.
arxiv topic:math.NT
arxiv_dataset-107281901.03253
Reverse-Engineering Satire, or "Paper on Computational Humor Accepted Despite Making Serious Advances" cs.AI cs.CL Humor is an essential human trait. Efforts to understand humor have called out links between humor and the foundations of cognition, as well as the importance of humor in social engagement. As such, it is a promising and important subject of study, with relevance for artificial intelligence and human-computer interaction. Previous computational work on humor has mostly operated at a coarse level of granularity, e.g., predicting whether an entire sentence, paragraph, document, etc., is humorous. As a step toward deep understanding of humor, we seek fine-grained models of attributes that make a given text humorous. Starting from the observation that satirical news headlines tend to resemble serious news headlines, we build and analyze a corpus of satirical headlines paired with nearly identical but serious headlines. The corpus is constructed via Unfun.me, an online game that incentivizes players to make minimal edits to satirical headlines with the goal of making other players believe the results are serious headlines. The edit operations used to successfully remove humor pinpoint the words and concepts that play a key role in making the original, satirical headline funny. Our analysis reveals that the humor tends to reside toward the end of headlines, and primarily in noun phrases, and that most satirical headlines follow a certain logical pattern, which we term false analogy. Overall, this paper deepens our understanding of the syntactic and semantic structure of satirical news headlines and provides insights for building humor-producing systems.
arxiv topic:cs.AI cs.CL
arxiv_dataset-107291901.03353
RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free cs.CV Recently two-stage detectors have surged ahead of single-shot detectors in the accuracy-vs-speed trade-off. Nevertheless single-shot detectors are immensely popular in embedded vision applications. This paper brings single-shot detectors up to the same level as current two-stage techniques. We do this by improving training for the state-of-the-art single-shot detector, RetinaNet, in three ways: integrating instance mask prediction for the first time, making the loss function adaptive and more stable, and including additional hard examples in training. We call the resulting augmented network RetinaMask. The detection component of RetinaMask has the same computational cost as the original RetinaNet, but is more accurate. COCO test-dev results are up to 41.4 mAP for RetinaMask-101 vs 39.1mAP for RetinaNet-101, while the runtime is the same during evaluation. Adding Group Normalization increases the performance of RetinaMask-101 to 41.7 mAP. Code is at:https://github.com/chengyangfu/retinamask
arxiv topic:cs.CV
arxiv_dataset-107301901.03453
The Fourier extension method and discrete orthogonal polynomials on an arc of the circle math.NA cs.NA The Fourier extension method, also known as the Fourier continuation method, is a method for approximating non-periodic functions on an interval using truncated Fourier series with period larger than the interval on which the function is defined. When the function being approximated is known at only finitely many points, the approximation is constructed as a projection based on this discrete set of points. In this paper we address the issue of estimating the absolute error in the approximation. The error can be expressed in terms of a system of discrete orthogonal polynomials on an arc of the unit circle, and these polynomials are then evaluated asymptotically using Riemann--Hilbert methods.
arxiv topic:math.NA cs.NA
arxiv_dataset-107311901.03553
DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders cs.CV cs.LG q-bio.NC q-bio.QM stat.ML Here we present DIVE: Data-driven Inference of Vertexwise Evolution. DIVE is an image-based disease progression model with single-vertex resolution, designed to reconstruct long-term patterns of brain pathology from short-term longitudinal data sets. DIVE clusters vertex-wise biomarker measurements on the cortical surface that have similar temporal dynamics across a patient population, and concurrently estimates an average trajectory of vertex measurements in each cluster. DIVE uniquely outputs a parcellation of the cortex into areas with common progression patterns, leading to a new signature for individual diseases. DIVE further estimates the disease stage and progression speed for every visit of every subject, potentially enhancing stratification for clinical trials or management. On simulated data, DIVE can recover ground truth clusters and their underlying trajectory, provided the average trajectories are sufficiently different between clusters. We demonstrate DIVE on data from two cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Dementia Research Centre (DRC), UK, containing patients with Posterior Cortical Atrophy (PCA) as well as typical Alzheimer's disease (tAD). DIVE finds similar spatial patterns of atrophy for tAD subjects in the two independent datasets (ADNI and DRC), and further reveals distinct patterns of pathology in different diseases (tAD vs PCA) and for distinct types of biomarker data: cortical thickness from Magnetic Resonance Imaging (MRI) vs amyloid load from Positron Emission Tomography (PET). Finally, DIVE can be used to estimate a fine-grained spatial distribution of pathology in the brain using any kind of voxelwise or vertexwise measures including Jacobian compression maps, fractional anisotropy (FA) maps from diffusion imaging or other PET measures. DIVE source code is available online: https://github.com/mrazvan22/dive
arxiv topic:cs.CV cs.LG q-bio.NC q-bio.QM stat.ML
arxiv_dataset-107321901.03653
Cubefree Trinomial Discriminants math.NT The discriminant of a polynomial of the form $\pm x^n \pm x^m \pm 1$ has the form $n^n \pm m^m(n-m)^{n-m}$ when $n,m$ are relatively prime. We investigate when these discriminants have prime power divisors. We explain several symmetries that appear in the classification of these values of $n,m$. We prove that there are infinitely many pairs of integers $n,m$ for which this discriminant has no prime cube divisors. This result is extended to show that for infinitely many fixed $m$, there are infinitely many $n$ for which the discriminant has no prime cube divisor.
arxiv topic:math.NT
arxiv_dataset-107331901.03753
Analysis of the Frequency and Detectability of Objects Resembling Nuclear/Radiological Threats in Commercial Cargo physics.soc-ph physics.ins-det The threat of smuggled nuclear/radiological weapons and material in commercial containerized cargo remains a significant threat to global security more than a decade after the enactment of laws in the United States and elsewhere mandating interdiction efforts. While significant progress has been made towards deploying passive radiation detection systems in maritime ports, such systems are incapable of detecting shielded threats or even certain scenarios in which material is unshielded. Research efforts towards developing systems for detecting such threats have typically focused on the development of systems that are highly-specific to nuclear/radiological threats and no such systems have been widely deployed. While most existing commercially-available cargo radiography systems are not specifically designed for this interdiction task, if items resembling nuclear/radiological threats are sufficiently rare in cargo radiographs to limit false alarms to an acceptably low frequency, then a smuggling interdiction scheme based on existing technology may be feasible. This analysis characterizes the relevant nuclear and radiological threats that may evade detection by passive monitors, and utilizes a dataset of 122,500 stream-of-commerce cargo container images from a 6 MeV endpoint gamma radiography system to determine the frequency at which objects of similar size and density to such threats occur in containers. It is found that for a broad class of threats, including assembled fission devices, gamma radiography is sufficient to flag threats in this cargo stream at false positive rates of $\lesssim$2%.
arxiv topic:physics.soc-ph physics.ins-det
arxiv_dataset-107341901.03853
Caristi-Kirk and Oettli-Th\'era Ball Spaces and applications math.FA Based on the theory of ball spaces introduced by Kuhlmann and Kuhlmann we introduce and study Caristi-Kirk and Oettli-Th\'era ball spaces. We show that if the underlying metric space is complete, then these have a very strong property: every ball contains a singleton ball. This fact provides quick proofs for several results which are equivalent to the Caristi-Kirk Fixed Point Theorem, namely Ekeland's Variational Principles, the Oettli-Th\'era Theorem, Takahashi's Theorem and the Flower Petal Theorem.
arxiv topic:math.FA
arxiv_dataset-107351901.03953
Light-Field for RF eess.IV cs.CV Most computer vision systems and computational photography systems are visible light based which is a small fraction of the electromagnetic (EM) spectrum. In recent years radio frequency (RF) hardware has become more widely available, for example, many cars are equipped with a RADAR, and almost every home has a WiFi device. In the context of imaging, RF spectrum holds many advantages compared to visible light systems. In particular, in this regime, EM energy effectively interacts in different ways with matter. This property allows for many novel applications such as privacy preserving computer vision and imaging through absorbing and scattering materials in visible light such as walls. Here, we expand many of the concepts in computational photography in visible light to RF cameras. The main limitation of imaging with RF is the large wavelength that limits the imaging resolution when compared to visible light. However, the output of RF cameras is usually processed by computer vision and perception algorithms which would benefit from multi-modal sensing of the environment, and from sensing in situations in which visible light systems fail. To bridge the gap between computational photography and RF imaging, we expand the concept of light-field to RF. This work paves the way to novel computational sensing systems with RF.
arxiv topic:eess.IV cs.CV
arxiv_dataset-107361901.04053
Moonshots for aging q-bio.OT As the global population ages, there is increased interest in living longer and improving one's quality of life in later years. However, studying aging - the decline in body function - is expensive and time-consuming. And despite research success to make model organisms live longer, there still aren't really any feasible solutions for delaying aging in humans. With space travel, scientists couldn't know what it would take to get to the moon. They had to extrapolate from theory and shorter-range tests. Perhaps with aging, we need a similar moonshot philosophy. And though "shot" might imply medicine, perhaps we need to think beyond biological interventions. Like the moon, we seem a long way away from provable therapies to increase human healthspan (the healthy period of one's life) or lifespan (how long one lives). This review therefore focuses on radical proposals. We hope it might stimulate discussion on what we might consider doing significantly differently than ongoing aging research.
arxiv topic:q-bio.OT
arxiv_dataset-107371901.04153
Optimal Strategies of Blotto Games: Beyond Convexity cs.GT The Colonel Blotto game, first introduced by Borel in 1921, is a well-studied game theory classic. Two colonels each have a pool of troops that they divide simultaneously among a set of battlefields. The winner of each battlefield is the colonel who puts more troops in it and the overall utility of each colonel is the sum of weights of the battlefields that s/he wins. Over the past century, the Colonel Blotto game has found applications in many different forms of competition from advertisements to politics to sports. Two main objectives have been proposed for this game in the literature: (i) maximizing the guaranteed expected payoff, and (ii) maximizing the probability of obtaining a minimum payoff $u$. The former corresponds to the conventional utility maximization and the latter concerns scenarios such as elections where the candidates' goal is to maximize the probability of getting at least half of the votes (rather than the expected number of votes). In this paper, we consider both of these objectives and show how it is possible to obtain (almost) optimal solutions that have few strategies in their support. One of the main technical challenges in obtaining bounded support strategies for the Colonel Blotto game is that the solution space becomes non-convex. This prevents us from using convex programming techniques in finding optimal strategies which are essentially the main tools that are used in the literature. However, we show through a set of structural results that the solution space can, interestingly, be partitioned into polynomially many disjoint convex polytopes that can be considered independently. Coupled with a number of other combinatorial observations, this leads to polynomial time approximation schemes for both of the aforementioned objectives.
arxiv topic:cs.GT
arxiv_dataset-107381901.04253
Ruprecht 147: a paradigm of dissolving star cluster astro-ph.GA We employed recent Gaia/DR2 data to investigate the dynamical status of the nearby (300 pc), old (2.5 Gyr) open cluster Ruprecht~147. We found prominent leading and trailing tails of stars along the cluster orbit, which demonstrates that Ruprecht~147 is losing stars at fast pace. Star counts indicate the cluster has a core radius of 33.3 arcmin, and a tidal radius of 137.5 arcmin. The cluster also possesses an extended corona, which cannot be reproduced by a simple King model. We computed the present-day cluster mass using its luminosity and mass function, and derived an estimate of 234$\pm$52 $M_{\odot}$. We also estimated the cluster original mass using available recipes extracted from N-body simulations obtaining a mass at birth of 50000$\pm$6500 $M_{\odot}$. Therefore dynamical mass loss, mostly caused by tidal interaction with the Milky Way, reduced the cluster mass by about 99\%. We then conclude that Ruprecht~147 is rapidly dissolving into the general Galactic disc.
arxiv topic:astro-ph.GA
arxiv_dataset-107391901.04353
Distribution of solutions of the fastest apparent convergence condition in optimized perturbation theory and its relation to anti-Stokes lines hep-th hep-ph math-ph math.MP We discuss fundamental properties of the fastest apparent convergence (FAC) condition which is used as a variational criterion in optimized perturbation theory (OPT). We examine an integral representation of the FAC condition and a distribution of the zeros of the integral in a complex artificial parameter space on the basis of theory of Lefschetz thimbles. We find that the zeros accumulate on a certain line segment so-called anti-Stokes line in the limit $K \to \infty$, where $K$ is a truncation order of a perturbation series. This phenomenon gives an underlying mechanism that physical quantities calculated by OPT can be insensitive to the choice of the artificial parameter.
arxiv topic:hep-th hep-ph math-ph math.MP
arxiv_dataset-107401901.04453
The geometry of involutions in ranked groups with a TI-subgroup math.LO math.GR We revisit the geometry of involutions in groups of finite Morley rank. Our approach unifies and generalises numerous results, both old and recent, that have exploited this geometry; though in fact, we prove much more. We also conjecture that this path leads to a new identification theorem for $\operatorname{PGL}_2(\mathbb{K})$.
arxiv topic:math.LO math.GR
arxiv_dataset-107411901.04553
Reactor neutrino oscillations as constraints on Effective Field Theory hep-ph hep-ex We study constraints on the Standard Model Effective Field Theory (SMEFT) from neutrino oscillations in short-baseline reactor experiments. We calculate the survival probability of reactors antineutrinos at the leading order in the SMEFT expansion, that is including linear effects of dimension-6 operators. It is shown that, at this order, reactor experiments alone cannot probe charged-current contact interactions between leptons and quarks that are of the (pseudo)vector (V$\pm$A) or pseudo-scalar type. We also note that flavor-diagonal (pseudo)vector coefficients do not have observable effects in oscillation experiments. In this we reach novel or different conclusions than prior analyses of non-standard neutrino interactions. On the other hand, reactor experiments offer a unique opportunity to probe tensor and scalar SMEFT operators that are off-diagonal in the lepton-flavor space. We derive constraints on the corresponding SMEFT parameters using the most recent data from the Daya Bay and RENO experiments.
arxiv topic:hep-ph hep-ex
arxiv_dataset-107421901.04653
Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks using PAC-Bayesian Analysis stat.ML cs.LG The notion of flat minima has played a key role in the generalization studies of deep learning models. However, existing definitions of the flatness are known to be sensitive to the rescaling of parameters. The issue suggests that the previous definitions of the flatness might not be a good measure of generalization, because generalization is invariant to such rescalings. In this paper, from the PAC-Bayesian perspective, we scrutinize the discussion concerning the flat minima and introduce the notion of normalized flat minima, which is free from the known scale dependence issues. Additionally, we highlight the scale dependence of existing matrix-norm based generalization error bounds similar to the existing flat minima definitions. Our modified notion of the flatness does not suffer from the insufficiency, either, suggesting it might provide better hierarchy in the hypothesis class.
arxiv topic:stat.ML cs.LG
arxiv_dataset-107431901.04753
The generality of transient compartmentalization and its associated error thresholds q-bio.PE cond-mat.soft physics.bio-ph Can prelife proceed without cell division? A recently proposed mechanism suggests that transient compartmentalization could have preceded cell division in prebiotic scenarios. Here, we study transient compartmentalization dynamics in the presence of mutations and noise in replication, as both can be detrimental the survival of compartments. Our study comprises situations where compartments contain uncoupled autocatalytic reactions feeding on a common resource, and systems based on RNA molecules copied by replicases, following a recent experimental study. Using the theory of branching processes, we show analytically that two regimes are possible. In the diffusion-limited regime, replication is asynchronous which leads to a large variability in the composition of compartments. In contrast, in a replication-limited regime, the growth is synchronous and thus the compositional variability is low. Typically, simple autocatalysts are in the former regime, while polymeric replicators can access the latter. For deterministic growth dynamics, we introduce mutations that turn functional replicators into parasites. We derive the phase boundary separating coexistence or parasite dominance as a function of relative growth, inoculation size and mutation rate. We show that transient compartmentalization allows coexistence beyond the classical error threshold, above which the parasite dominates. Our findings invite to revisit major prebiotic transitions, notably the transitions towards cooperation, complex polymers and cell division.
arxiv topic:q-bio.PE cond-mat.soft physics.bio-ph
arxiv_dataset-107441901.04853
Search for Anderson localization of light by cold atoms in a static electric field cond-mat.dis-nn physics.atom-ph We explore the potential of a static electric field to induce Anderson localization of light in a large three-dimensional (3D) cloud of randomly distributed, immobile atoms with a degenerate ground state (total angular momentum $J_g = 0$) and a three-fold degenerate excited state ($J_e = 1$). We study both the spatial structure of quasimodes of the atomic cloud and the scaling of the Thouless number with the size of the cloud. Our results indicate that unlike the static magnetic field, the electric field does not induce Anderson localization of light by atoms. We explain this conclusion by the incomplete removal of degeneracy of the excited atomic state by the field and the relatively strong residual dipole-dipole coupling between atoms which is weaker than in the absence of external fields but stronger than in the presence of a static magnetic field. A joint analysis of these results together with our previous results concerning Anderson localization of scalar waves and light suggests the existence of a critical strength of dipole-dipole interactions that should not be surpassed for Anderson localization to be possible in 3D.
arxiv topic:cond-mat.dis-nn physics.atom-ph
arxiv_dataset-107451901.04953
A forgotten Theorem of Schoenberg on one-sided integral averages math.CA math.ST stat.TH Let $f:\mathbb{R} \rightarrow \mathbb{R}$ be a function for which we want to take local averages. Assuming we cannot look into the future, the 'average' at time $t$ can only use $f(s)$ for $s \leq t$. A natural way to do so is via a weight $\phi$ and $$ g(t) = \int_{0}^{\infty}{f(t-s) \phi(s) ds}.$$ We would like that (1) constant functions, $f(t) \equiv \mbox{const}$, are mapped to themselves and (2) $\phi$ to be monotonically decreasing (the more recent past should weigh more heavily than the distant past). Moreover, we want that (3) if $f(t)$ crosses a certain threshold $n$ times, then $g(t)$ should not cross the same threshold more than $n$ times (if $f(t)$ is the outside wind speed and crosses the Tornado threshold at two points in time, we would like the averaged wind speed to cross the Tornado threshold at most twice). A Theorem implicit in the work of Schonberg is that these three conditions characterize a unique weight that is given by the exponential distribution $$ \phi(s) = \lambda^{} e^{-\lambda s} \qquad \mbox{for some} \quad \lambda > 0.$$
arxiv topic:math.CA math.ST stat.TH
arxiv_dataset-107461901.05053
An Agent-Based Model to Explain the Emergence of Stylised Facts in Log Returns q-fin.TR This paper outlines an agent-based model of a simple financial market in which a single asset is available for trade by three different types of traders. The model was first introduced in the PhD thesis of one of the authors, see reference [1]. The simulated log returns are examined for the presence of the stylised facts of financial data. The features of leptokurtosis, volatility clustering and aggregational Gaussianity are especially highlighted and studied in detail. The following ingredients are found to be essential for the production of these stylised facts: the memory of noise traders who make random trade decisions; the inclusion of technical traders that trade in line with trends in the price and the inclusion of fundamental traders who know the "fundamental value" of the stock and trade accordingly. When these three basic types of traders are included log returns are produced with a leptokurtic distribution and volatility clustering as well as some further statistical features of empirical data. This enhances and broadens our understanding of the fundamental processes involved in the production of empirical data by the market.
arxiv topic:q-fin.TR
arxiv_dataset-107471901.05153
Channel Conditions for the Optimality of Interference Decoding Schemes for K-user Gaussian Interference Channels cs.IT math.IT The Han-Kobayashi (HK) scheme achieves the best known achievable rate region for the K user interference channel (IC). Simple HK schemes are HK schemes with Gaussian signaling, no time sharing, and no private-common power splitting. The class of simple HK schemes includes the treating interference as noise (TIN) scheme and schemes that involve various levels of interference decoding and cancellation at each receiver. We derive conditions under which simple HK schemes achieve sum capacity for general K user Gaussian ICs. These results generalize existing sum capacity results for the TIN scheme to the class of simple HK schemes.
arxiv topic:cs.IT math.IT
arxiv_dataset-107481901.05253
OxH2x+1+ Clusters: A New Series of Non-Metallic Superalkali Cations by Trapping H3O+ into Water physics.chem-ph The term superalkali refers to the clusters with lower ionization energy than alkali atoms. Typical superalkali cations include a central electronegative core with excess metal ligands, OLi3+, for instance, which mimic the properties of alkali metal ions. We report a new series of non-metallic superalkali cations, OxH2x+1+ (x = 1-5) using ab initio MP2/6-311++G(d,p) level. These cations are designed by successive replacement of H-ligands of hydronium cation (OH3+) by ammonium (OH3) moieties followed by their geometry optimization. The resulting OxH2x+1 + clusters, which can be expressed in the form of OH3 + (x-1)H2O complexes, possess a number of electrostatic as well as partially covalent H-bonds, with the interacting energy in the range 5.2-29.3 kcal/mol as revealed by quantum theory of atoms in molecules analyses. These cations are found to be stable against deprotonation as well as dehydration pathways, and their stability increases with the increase in x. Interestingly, the vertical electron affinities (EAv) of OxH2x+1 + clusters decreases rapidly from 5.16 eV for x = 1 to 2.67 eV for x = 5, which suggest their superalkali nature. It is also possible to continue this series of non-metallic superalkali cations for x > 5 with even lower EAv, down to an approximated limit of 1.85 eV, which is obtained for OH3 + trapped into water cavity implicitly using polarizable continuum model. The findings of this study will not only provide new insights into structure and interactions of OxH2x+1 + clusters but also reveal their novel properties, which can be exploited their interesting applications.
arxiv topic:physics.chem-ph
arxiv_dataset-107491901.05353
A Primer on PAC-Bayesian Learning stat.ML cs.LG Generalised Bayesian learning algorithms are increasingly popular in machine learning, due to their PAC generalisation properties and flexibility. The present paper aims at providing a self-contained survey on the resulting PAC-Bayes framework and some of its main theoretical and algorithmic developments.
arxiv topic:stat.ML cs.LG
arxiv_dataset-107501901.05453
A Study of Charge Radii and Neutron Skin Thickness near Nuclear Drip Lines nucl-th We studied the charge radius, rms radius and neutron skin thickness $\Delta r_{np}$ in even-even isotopes of Si, S, Ar and Ca and isotones of N =20, 28, 50 and 82. The $\Delta r_{np}$ in doubly-magic $^{48}$Ca, $^{68}$Ni, $^{120,132}$Sn and $^{208}$Pb nuclei has also been calculated. Theoretical calculations are done with the Hartree-Fock-Bogoliubov theory with the effective Skyrme interactions. Calculated theoretical estimates are in good agreement with the recently available experimental data. The charge radii for Si, S, Ar and Ca isotopes is observed to be minimum at neutron number N =14. The theoretically computed results with UNEDF0 model parameterization of functional are reasonably reproducing the experimental data for $\Delta r_{np}$ in $^{48}$Ca, $^{68}$Ni and $^{120,132}$Sn. The energy density functional of UNEDF1 model provides much improved result of $\Delta r_{np}$ for $^{208}$Pb.
arxiv topic:nucl-th
arxiv_dataset-107511901.05553
Truly Generalizable Radiograph Segmentation with Conditional Domain Adaptation cs.CV Digitization techniques for biomedical images yield different visual patterns in radiological exams. These differences may hamper the use of data-driven approaches for inference over these images, such as Deep Neural Networks. Another noticeable difficulty in this field is the lack of labeled data, even though in many cases there is an abundance of unlabeled data available. Therefore an important step in improving the generalization capabilities of these methods is to perform Unsupervised and Semi-Supervised Domain Adaptation between different datasets of biomedical images. In order to tackle this problem, in this work we propose an Unsupervised and Semi-Supervised Domain Adaptation method for segmentation of biomedical images using Generative Adversarial Networks for Unsupervised Image Translation. We merge these unsupervised networks with supervised deep semantic segmentation architectures in order to create a semi-supervised method capable of learning from both unlabeled and labeled data, whenever labeling is available. We compare our method using several domains, datasets, segmentation tasks and traditional baselines, such as unsupervised distance-based methods and reusing pretrained models both with and without Fine-tuning. We perform both quantitative and qualitative analysis of the proposed method and baselines in the distinct scenarios considered in our experimental evaluation. The proposed method shows consistently better results than the baselines in scarce labeled data scenarios, achieving Jaccard values greater than 0.9 and good segmentation quality in most tasks. Unsupervised Domain Adaptation results were observed to be close to the Fully Supervised Domain Adaptation used in the traditional procedure of Fine-tuning pretrained networks.
arxiv topic:cs.CV
arxiv_dataset-107521901.05653
Protoperads i: Combinatorics and definitions math.AT This paper is the first of two articles which develop the notion of protoperads. In this one, we construct a new monoidal product on the category of reduced S-modules. We study the associated monoids, called protoperads, which are a generalization of operads. As operads encode algebraic operations with several inputs and one outputs, protoperads encode algebraic operations with the same number of inputs and outputs. We describe the underlying combinatorics of protoperads, and show that there exists a notion of free protoperad. We also show that the monoidal product introduced here is related to Vallette's one on the category of S-bimodules, via the induction functor.
arxiv topic:math.AT
arxiv_dataset-107531901.05753
Spin transport parameters of NbN thin films characterised by spin pumping experiments cond-mat.mtrl-sci cond-mat.mes-hall We present measurements of ferromagnetic-resonance - driven spin pumping and inverse spin-Hall effect in NbN/Y3Fe5O12 (YIG) bilayers. A clear enhancement of the (effective) Gilbert damping constant of the thin-film YIG was observed due to the presence of the NbN spin sink. By varying the NbN thickness and employing spin-diffusion theory, we have estimated the room temperature values of the spin diffusion length and the spin Hall angle in NbN to be 14 nm and -1.1 10-2, respectively. Furthermore, we have determined the spin-mixing conductance of the NbN/YIG interface to be 10 nm-2. The experimental quantification of these spin transport parameters is an important step towards the development of superconducting spintronic devices involving NbN thin films.
arxiv topic:cond-mat.mtrl-sci cond-mat.mes-hall
arxiv_dataset-107541901.05853
Nuclear dimension of simple C*-algebras math.OA We compute the nuclear dimension of separable, simple, unital, nuclear, Z-stable C*-algebras. This makes classification accessible from Z-stability and in particular brings large classes of C*-algebras associated to free and minimal actions of amenable groups on finite dimensional spaces within the scope of the Elliott classification programme.
arxiv topic:math.OA
arxiv_dataset-107551901.05953
Outline for a quantum theory of gravity gr-qc hep-th quant-ph By invoking an asymmetric metric tensor, and borrowing ideas from non-commutative geometry, string theory, and trace dynamics, we propose an action function for quantum gravity. The action is proportional to the four dimensional non-commutative curvature scalar (which is torsion dependent) that is sourced by the Nambu-Goto world-sheet action for a string, plus the Kalb-Ramond string action. This `quantum gravity' is actually a non-commutative {\it classical} matrix dynamics, and the only two fundamental constants in the theory are the square of Planck length and the speed of light. By treating the entity described by this action as a microstate, one constructs the statistical thermodynamics of a large number of such microstates, in the spirit of trace dynamics. Quantum field theory (and $\hbar$) and quantum general relativity (and $G$) emerge from the underlying matrix dynamics in the thermodynamic limit. The statistical fluctuations that are inevitably present about equilibrium, are the source for spontaneous localisation, which drives macroscopic quantum gravitational systems to the classical general relativistic limit. While the mathematical formalism governing these ideas remains to be developed, we hope here to highlight the deep connection between quantum foundations, and the sought for quantum theory of gravity. In the sense described in this article, ongoing experimental tests of spontaneous collapse theories are in fact also tests of string theory!
arxiv topic:gr-qc hep-th quant-ph
arxiv_dataset-107561901.06053
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks cs.LG stat.ML The gradient noise (GN) in the stochastic gradient descent (SGD) algorithm is often considered to be Gaussian in the large data regime by assuming that the classical central limit theorem (CLT) kicks in. This assumption is often made for mathematical convenience, since it enables SGD to be analyzed as a stochastic differential equation (SDE) driven by a Brownian motion. We argue that the Gaussianity assumption might fail to hold in deep learning settings and hence render the Brownian motion-based analyses inappropriate. Inspired by non-Gaussian natural phenomena, we consider the GN in a more general context and invoke the generalized CLT (GCLT), which suggests that the GN converges to a heavy-tailed $\alpha$-stable random variable. Accordingly, we propose to analyze SGD as an SDE driven by a L\'{e}vy motion. Such SDEs can incur `jumps', which force the SDE transition from narrow minima to wider minima, as proven by existing metastability theory. To validate the $\alpha$-stable assumption, we conduct extensive experiments on common deep learning architectures and show that in all settings, the GN is highly non-Gaussian and admits heavy-tails. We further investigate the tail behavior in varying network architectures and sizes, loss functions, and datasets. Our results open up a different perspective and shed more light on the belief that SGD prefers wide minima.
arxiv topic:cs.LG stat.ML
arxiv_dataset-107571901.06153
Infeasibility and structural bias in Differential Evolution cs.NE This paper thoroughly investigates a range of popular DE configurations to identify components responsible for the emergence of structural bias - recently identified tendency of the algorithm to prefer some regions of the search space for reasons directly unrelated to the objective function values. Such tendency was already studied in GA and PSO where a connection was established between the strength of structural bias and population sizes and potential weaknesses of these algorithms was highlighted. For DE, this study goes further and extends the range of aspects that can contribute to presence of structural bias by including algorithmic component which is usually overlooked - constraint handling technique. A wide range of DE configurations were subjected to the protocol for testing for bias. Results suggest that triggering mechanism for the bias in DE differs to the one previously found for GA and PSO - no clear dependency on population size exists. Setting of DE parameters is based on a separate study which on its own leads to interesting directions of new research. Overall, DE turned out to be robust against structural bias - only DE/current-to-best/1/bin is clearly biased but this effect is mitigated by the use of penalty constraint handling technique.
arxiv topic:cs.NE
arxiv_dataset-107581901.06253
CONet: A Cognitive Ocean Network cs.CY cs.AI The scientific and technological revolution of the Internet of Things has begun in the area of oceanography. Historically, humans have observed the ocean from an external viewpoint in order to study it. In recent years, however, changes have occurred in the ocean, and laboratories have been built on the seafloor. Approximately 70.8% of the Earth's surface is covered by oceans and rivers. The Ocean of Things is expected to be important for disaster prevention, ocean-resource exploration, and underwater environmental monitoring. Unlike traditional wireless sensor networks, the Ocean Network has its own unique features, such as low reliability and narrow bandwidth. These features will be great challenges for the Ocean Network. Furthermore, the integration of the Ocean Network with artificial intelligence has become a topic of increasing interest for oceanology researchers. The Cognitive Ocean Network (CONet) will become the mainstream of future ocean science and engineering developments. In this article, we define the CONet. The contributions of the paper are as follows: (1) a CONet architecture is proposed and described in detail; (2) important and useful demonstration applications of the CONet are proposed; and (3) future trends in CONet research are presented.
arxiv topic:cs.CY cs.AI
arxiv_dataset-107591901.06353
Spectra of biperiodic planar networks math.CO math.AG A biperiodic planar network is a pair $(G,c)$ where $G$ is a graph embedded on the torus and $c$ is a function from the edges of $G$ to non-zero complex numbers. Associated to the discrete Laplacian on a biperiodic planar network is its spectrum: a triple $(C,S,\nu)$, where $C$ is a curve and $S$ is a divisor on it. We give a complete classification of networks (modulo a natural equivalence) in terms of their spectral data. The space of networks has a large group of cluster automorphisms arising from the $Y-\Delta$ transformations. We show that the spectrum provides action-angle coordinates for the discrete cluster integrable systems defined by these automorphisms.
arxiv topic:math.CO math.AG
arxiv_dataset-107601901.06453
Holographic Phase Retrieval and Reference Design cs.IT cs.NA eess.SP math.IT math.NA math.OC A general mathematical framework and recovery algorithm is presented for the holographic phase retrieval problem. In this problem, which arises in holographic coherent diffraction imaging, a "reference" portion of the signal to be recovered via phase retrieval is a priori known from experimental design. A generic formula is also derived for the expected recovery error when the measurement data is corrupted by Poisson shot noise. This facilitates an optimization perspective towards reference design and analysis. We employ this optimization perspective towards quantifying the performance of various reference choices.
arxiv topic:cs.IT cs.NA eess.SP math.IT math.NA math.OC
arxiv_dataset-107611901.06553
Neuroflight: Next Generation Flight Control Firmware cs.RO Little innovation has been made to low-level attitude flight control used by uncrewed aerial vehicles (UAVs), which still predominantly uses the classical PID controller. In this work we introduce Neuroflight, the first open source neuro-flight controller firmware. We present our toolchain for training a neural network in simulation and compiling it to run on embedded hardware. Challenges faced jumping from simulation to reality are discussed along with our solutions. Our evaluation shows the neural network can execute at over 2.67kHz on an Arm Cortex-M7 processor and flight tests demonstrate a quadcopter running Neuroflight can achieve stable flight and execute aerobatic maneuvers.
arxiv topic:cs.RO
arxiv_dataset-107621901.06653
Fast algorithms at low temperatures via Markov chains cs.DS math.CO math.PR We define a discrete-time Markov chain for abstract polymer models and show that under sufficient decay of the polymer weights, this chain mixes rapidly. We apply this Markov chain to polymer models derived from the hard-core and ferromagnetic Potts models on bounded-degree (bipartite) expander graphs. In this setting, Jenssen, Keevash and Perkins (2019) recently gave an FPTAS and an efficient sampling algorithm at sufficiently high fugacity and low temperature respectively. Their method is based on using the cluster expansion to obtain a complex zero-free region for the partition function of a polymer model, and then approximating this partition function using the polynomial interpolation method of Barvinok. Our approach via the polymer model Markov chain circumvents the zero-free analysis and the generalization to complex parameters, and leads to a sampling algorithm with a fast running time of $O(n \log n)$ for the Potts model and $O(n^2 \log n)$ for the hard-core model, in contrast to typical running times of $n^{O(\log \Delta)}$ for algorithms based on Barvinok's polynomial interpolation method on graphs of maximum degree $\Delta$. We finally combine our results for the hard-core and ferromagnetic Potts models with standard Markov chain comparison tools to obtain polynomial mixing time for the usual spin Glauber dynamics restricted to even and odd or `red' dominant portions of the respective state spaces.
arxiv topic:cs.DS math.CO math.PR
arxiv_dataset-107631901.06753
Thermofield Theory for Finite-Temperature Quantum Chemistry physics.chem-ph cond-mat.str-el Thermofield dynamics has proven to be a very useful theory in high-energy physics, particularly since it permits the treatment of both time- and temperature-dependence on an equal footing. We here show that it also has an excellent potential for studying thermal properties of electronic systems in physics and chemistry. We describe a general framework for constructing finite temperature correlated wave function methods typical of ground state methods. We then introduce two distinct approaches to the resulting imaginary time Schrodinger equation, which we refer to as fixed-reference and covariant methods. As an example, we derive the two corresponding versions of thermal configuration interaction theory, and apply them to the Hubbard model, while comparing with exact benchmark results.
arxiv topic:physics.chem-ph cond-mat.str-el
arxiv_dataset-107641901.06853
Schubert Derivations on the Infinite Wedge Power math.AG math-ph math.CO math.MP math.RT The {\em Schubert derivation} is a distinguished Hasse-Schmidt derivation on the exterior algebra of a free abelian group, encoding the formalism of Schubert calculus for all Grassmannians at once. The purpose of this paper is to extend the Schubert derivation to the infinite exterior power of a free ${\mathbb Z}$-module of infinite rank (fermionic Fock space). Classical vertex operators naturally arise from the {\em integration by parts formula}, that also recovers the generating function occurring in the {\em bosonic vertex representation} of the Lie algebra $gl_\infty({\mathbb Z})$, due to Date, Jimbo, Kashiwara and Miwa (DJKM). In the present framework, the DJKM result will be interpreted as a limit case of the following general observation: the singular cohomology of the complex Grassmannian $G(r,n)$ is an irreducible representation of the Lie algebra of $n\times n$ square matrices.}
arxiv topic:math.AG math-ph math.CO math.MP math.RT
arxiv_dataset-107651901.06953
Edelstein effects, spin-transfer torque, and spin pumping caused by pristine surface states of topological insulators cond-mat.mes-hall The Edelstein effect caused by the pristine surface states of three-dimensional topological insulators is investigated by means of a semiclassical approach. The combined effect of random impurity scattering and the spin-momentum locking of the gapless Dirac cone yields a current-induced surface spin accumulation independent from chemical potential and temperature. In a nearby ferromagnet that does not make direct contact with the topological insulator, the bound state nature of the pristine surface state causes a spin-transfer torque that is entirely field-like, whose magnitude is highly influenced by the interface cleanliness and the quantum well state of the ferromagnet. Through incorporating quantum tunneling into Bloch equation, the spin pumping mediated by the pristine surface state is shown to be described by the same spin mixing conductance as the spin-transfer torque, and a semiclassical approach is proposed to explain the inverse Edelstein effect that converts the spin pumping spin current into a charge current. Consistency of these results with various experiments will be elaborated in detail.
arxiv topic:cond-mat.mes-hall
arxiv_dataset-107661901.07053
Concave power solutions of the Dominative $p$-Laplace equation math.AP In this paper, we study properties of solutions of the Dominative $p$-Laplace equation with homogeneous Dirichlet boundary conditions in a bounded convex domain $\Omega$. For the equation $-\mathcal{D}_p u= 1$, we show that $\sqrt{u}$ is concave, and for the eigenvalue problem $\mathcal{D}_p u + \lambda u=0$, we show that $\log {u}$ is concave.
arxiv topic:math.AP
arxiv_dataset-107671901.07153
Convergence of $p$-Stable Random Fractional Wavelet Series and Some of its Properties math.FA For appropriate orthonormal wavelet basis $\{\psi_{j\,k}^e \}_{j\in\mathbb{Z}\,k\in\mathbb{Z}^d\,e\in\{0,1\}^d}$, constants $p$ and $\gamma$, if $\mathcal{I}_{\gamma}$ denotes the Riesz fractional integral operator of order $\gamma$ and $(\eta_{j\,k\,e})_{j\in\mathbb{Z} k\in\mathbb{Z}^d \,e\in\{0,1\}^d}$ a sequence of independent identically distributed symmetric $p$-stable random variables, we investigate the convergence of the series $\sum\limits_{j\,k\,e} \eta_{j\,k\,e} \mathcal{I}_{\gamma} \psi_{j\,k\,}^e$. Similar results are also studied for modified fractional integral operators. Finally, some geometric properties related to self similarity are studied.
arxiv topic:math.FA
arxiv_dataset-107681901.07253
Direct and inverse approximation theorems of functions in the Orlicz type spaces S_M math.CA In the Orlicz type spaces ${\mathcal S}_{M}$, we prove direct and inverse approximation theorems in terms of the best approximations of functions and moduli of smoothness of fractional order. We also show the equivalence between moduli of smoothness and Peetre $K$-functionals in the spaces ${\mathcal S}_{M}$.
arxiv topic:math.CA
arxiv_dataset-107691901.07353
Small-Angle Scattering physics.ins-det Small-Angle Scattering (SAS) investigates structures in samples that generally range from approximately 0.5 nm to a few 100 nm. This can both be done for isotropic samples such as blends and liquids, as well as anisotropic samples such as quasi-crystals. In order to obtain data about that size regime scattered intensity, mostly of x-rays or neutrons, is investigated at angles from close to zero, still in the region of the primary beam up to 10\deg , depending on the wavelength of the incoming radiation. The two primary sources for SAS experiments are x-ray (small-angle x-ray scattering, SAXS) sources and neutron (small-angle neutron scattering, SANS) sources, which shall be the two cases discussed here. Also scattering with electrons or other particle waves is possible, but not the main use case for the purpose of this manuscript. For most small-angle scattering instruments, both SAXS and SANS, the science case covers the investigation of self-assembled polymeric and biological systems, multi-scale systems with large size distribution of the contained particles, solutions of (nano-)particles and soft-matter systems, protein solutions, and material science investigations. In the case of SANS this is augmented by the possibility to also investigate the spin state of the sample and hence perform investigations of the magnetic structure of the sample. In the following sections the general setup of both SAXS and SANS instruments shall be discussed, as well as data acquisition and evaluation and preparation of the sample and the experiment in general. The information contained herein should provide sufficient information for planning and performing a SAS experiment and evaluate the gathered data.
arxiv topic:physics.ins-det
arxiv_dataset-107701901.07453
Orbital Angular Momentum at Small $x$ hep-ph nucl-ex nucl-th We determine the small Bjorken $x$ asymptotics of the quark and gluon orbital angular momentum (OAM) distributions in the proton in the double-logarithmic approximation (DLA), which resums powers of $\alpha_s \ln^2 (1/x)$ with $\alpha_s$ the strong coupling constant. Starting with the operator definitions for the quark and gluon OAM, we simplify them at small $x$, relating them, respectively, to the polarized dipole amplitudes for the quark and gluon helicities defined in our earlier works. Using the small-$x$ evolution equations derived for these polarized dipole amplitudes earlier we arrive at the following small-$x$ asymptotics of the quark and gluon OAM distributions in the large-$N_c$ limit: \begin{align} L_{q + \bar{q}} (x, Q^2) = - \Delta \Sigma (x, Q^2) \sim \left(\frac{1}{x}\right)^{\frac{4}{\sqrt{3}} \, \sqrt{\frac{\alpha_s \, N_c}{2 \pi}} }, \ \ \ \ \ L_G (x, Q^2) \sim \Delta G (x, Q^2) \sim \left(\frac{1}{x}\right)^{\frac{13}{4 \sqrt{3}} \, \sqrt{\frac{\alpha_s \, N_c}{2 \pi}}} . \end{align}
arxiv topic:hep-ph nucl-ex nucl-th
arxiv_dataset-107711901.07553
Specification of additional information for solving stochastic inverse problems math.NA cs.NA math.PR Methods have been developed to identify the probability distribution of a random vector $Z$ from information consisting of its bounded range and the probability density function or moments of a quantity of interest, $Q(Z)$. The mapping from $Z$ to $Q(Z)$ may arise from a stochastic differential equation whose coefficients depend on $Z$. This problem differs from Bayesian inverse problems as the latter is primarily driven by observation noise. We motivate this work by demonstrating that additional information on $Z$ is required to recover its true law. Our objective is to identify what additional information on $Z$ is needed and propose methods to recover the law of $Z$ under such information. These methods employ tools such as Bayes' theorem, principle of maximum entropy, and forward uncertainty quantification to obtain solutions to the inverse problem that are consistent with information on $Z$ and $Q(Z)$. The additional information on $Z$ may include its moments or its family of distributions. We justify our objective by considering the capabilities of solutions to this inverse problem to predict the probability law of unobserved quantities of interest.
arxiv topic:math.NA cs.NA math.PR
arxiv_dataset-107721901.07653
Determining eigenstates and thermal states on a quantum computer using quantum imaginary time evolution quant-ph The accurate computation of Hamiltonian ground, excited, and thermal states on quantum computers stands to impact many problems in the physical and computer sciences, from quantum simulation to machine learning. Given the challenges posed in constructing large-scale quantum computers, these tasks should be carried out in a resource-efficient way. In this regard, existing techniques based on phase estimation or variational algorithms display potential disadvantages; phase estimation requires deep circuits with ancillae, that are hard to execute reliably without error correction, while variational algorithms, while flexible with respect to circuit depth, entail additional high-dimensional classical optimization. Here, we introduce the quantum imaginary time evolution and quantum Lanczos algorithms, which are analogues of classical algorithms for finding ground and excited states. Compared to their classical counterparts, they require exponentially less space and time per iteration, and can be implemented without deep circuits and ancillae, or high-dimensional optimization. We furthermore discuss quantum imaginary time evolution as a subroutine to generate Gibbs averages through an analog of minimally entangled typical thermal states. Finally, we demonstrate the potential of these algorithms via an implementation using exact classical emulation as well as through prototype circuits on the Rigetti quantum virtual machine and Aspen-1 quantum processing unit.
arxiv topic:quant-ph
arxiv_dataset-107731901.07753
Construction of Liouville Brownian motion via Dirichlet form theory math.PR The Liouville Brownian motion which was introduced in \cite{GRV} is a natural diffusion process associated with a random metric in two dimensional Liouville quantum gravity. In this paper we construct the Liouville Brownian motion via Dirichlet form theory. By showing that the Liouville measure is smooth in the strict sense, the positive continuous additive functional $(F_t)_{t \ge 0}$ of the Liouville measure in the strict sense w.r.t. the planar Brownian motion $(B_t)_{t \ge 0}$ is obtained. Then the Liouville Brownian motion can be defined as a time changed process of the planar Brownian motion $B_{F_t^{-1}}$.
arxiv topic:math.PR
arxiv_dataset-107741901.07853
Synthesis and investigation of the properties of organic-inorganic perovskite films with non-contact optical methods physics.app-ph cond-mat.mtrl-sci Presented in this work are the results of our study of the photoelectric properties of perovskite $CH_3NH_3PbI_{2.98}Cl_{0.02}$ films deposited on a glass substrate using the spin-coating method. The unit cell parameters of the perovskite are determined using x-ray diffractometry. It is shown that the film morphology represents a net of non-oriented needle-like structures with significant roughness and porosity. In order to investigate the properties of the films obtained, non-contact methods were used, such as transmission and reflection measurements and the measurements of the spectral characteristics of the small-signal surface photovoltage. The method of spectral characteristics of the low-signal surface photovoltage and the transmission method reveal information about the external quantum yield in the films studied and about the diffusion length of minority carriers in the perovskite films. As a result of this analysis, it has been established that the films obtained are naturally textured, and their bandgap is 1.59 eV. It is shown that in order to correctly determine absorption coefficient and the bandgap values, Urbach effect should be accounted for. Minority carriers' diffusion length is longer than the film thickness, which is equal to 400 nm. The films obtained are promising materials for solar cells.
arxiv topic:physics.app-ph cond-mat.mtrl-sci
arxiv_dataset-107751901.07953
Direct Reconstruction of Distorted Signals and Images Using Shifts Methods eess.SP Mathematical methods of step-by-step and combined shifts are proposed for experimental data processing to reconstruct the measuring system impulse response distorted by shift-invariant blur. Proposed methods base on direct non-blind deconvolution without using approximations and integral transforms. Methods are fast and effective for accurate data reconstruction, which gives a possibility of increasing the effective resolution of measuring systems by mathematical methods up to physical limits without solving the expensive and quite difficult scientific and technical problems. Step-by-step and combined shifts methods supplement each other in data reconstruction at different distortions of signals, noise levels and data volumes. Methods may be adapted for reconstruction of multi-dimensional data. There are considered the restorations of 2D images blurred by uniform motion and distorted by functions, which may be factored, such as Gaussian-like functions. The comparative analysis of step-by-step and combined shifts methods is presented. Reconstruction inaccuracies are estimated. Examples of signal reconstructions and image restorations at different distortions are considered.
arxiv topic:eess.SP
arxiv_dataset-107761901.08053
Quantum States of a Time-Asymmetric Universe: Wave Function, Density Matrix, and Empirical Equivalence quant-ph hep-th physics.hist-ph What is the quantum state of the universe? Although there have been several interesting suggestions, the question remains open. In this paper, I consider a natural choice for the universal quantum state arising from the Past Hypothesis, a boundary condition that accounts for the time-asymmetry of the universe. The natural choice is given not by a wave function (representing a pure state) but by a density matrix (representing a mixed state). I begin by classifying quantum theories into two types: theories with a fundamental wave function and theories with a fundamental density matrix. The Past Hypothesis is compatible with infinitely many initial wave functions, none of which seems to be particularly natural. However, once we turn to density matrices, the Past Hypothesis provides a natural choice---the normalized projection onto the Past Hypothesis subspace in the Hilbert space. Nevertheless, the two types of theories can be empirically equivalent. To provide a concrete understanding of the empirical equivalence, I provide a novel subsystem analysis in the context of Bohmian theories. Given the empirical equivalence, it seems empirically underdetermined whether the universe is in a pure state or a mixed state. Finally, I discuss some theoretical payoffs of the density-matrix theories and present some open problems for future research.
arxiv topic:quant-ph hep-th physics.hist-ph
arxiv_dataset-107771901.08153
Robust 3D Surface Recovery by Applying a Focus Criterion in White Light Scanning Interference Microscopy physics.optics White light scanning interference (WLSI) microscopes provide an accurate surface topography of engineered surfaces. However, the measurement accuracy is substantially reduced in surfaces with low-reflectivity regions or high roughness, like a surface affected by corrosion. An alternative technique called shape from focus (SFF) takes advantage of the surface texture to recover the 3D surface by using a focus metric through a vertical scan. In this work, we propose a technique called SFF-WLSI, which consists of recovering the 3D surface of an object by applying the Tenegrad Variance (TENV) focus metric to WLSI images. Extensive simulation results show that the proposed technique yields accurate measurements under different surface roughness and surface reflectivity, outperforming the conventional WLSI and the SFF techniques. We validated the simulation results on two real objects with a Mirau-type microscope. The first was a flat lapping specimen with Ra = 0.05 {\mu}m for which we measured an average value of Ra = 0.055 {\mu}m and standard deviation {\sigma} = 0.008 {\mu}m. The second was a metallic sphere with corrosion, which we reconstructed with WLSI versus the proposed SFF-WLSI technique, producing a better 3D reconstruction with less undefined depth values.
arxiv topic:physics.optics
arxiv_dataset-107781901.08253
Gas flow around a planet embedded in a protoplanetary disc: the dependence on the planetary mass astro-ph.EP The three-dimensional structure of the gas flow around a planet is thought to influence the accretion of both gas and solid materials. In particular, the outflow in the mid-plane region may prevent the accretion of the solid materials and delay the formation of super-Earths' cores. However, it is not yet understood how the nature of the flow field and outflow speed change as a function of the planetary mass. In this study, we investigate the dependence of gas flow around a planet embedded in a protoplanetary disc on the planetary mass. Assuming an isothermal, inviscid gas disc, we perform three-dimensional hydrodynamical simulations on the spherical polar grid, which has a planet located at its centre. We find that gas enters the Bondi or Hill sphere at high latitudes and exits through the mid-plane region of the disc regardless of the assumed dimensionless planetary mass $m=R_{\rm Bondi}/H$, where $R_{\rm Bondi}$ and $H$ are the Bondi radius of the planet and disc scale height, respectively. The altitude from where gas predominantly enters the envelope varies with the planetary mass. The outflow speed can be expressed as $|u_{\rm out}|=\sqrt{3/2}mc_{\rm s}$ $(R_{\rm Bondi}\leq R_{\rm Hill})$ or $|u_{\rm out}|=\sqrt{3/2}(m/3)^{1/3} c_{\rm s}$ ($R_{\rm Bondi}\geq R_{\rm Hill}$), where $c_{\rm s}$ is the isothermal sound speed and $R_{\rm Hill}$ is the Hill radius. The outflow around a planet may reduce the accretion of dust and pebbles onto the planet when $m\gtrsim\sqrt{\rm St}$, where St is the Stokes number. Our results suggest that the flow around proto-cores of super-Earths may delay their growth and, consequently, help them to avoid runaway gas accretion within the lifetime of the gas disc.
arxiv topic:astro-ph.EP
arxiv_dataset-107791901.08353
Stabilizing Scheduling Policies for Networked Control Systems eess.SY cs.SY This paper deals with the problem of allocating communication resources for Networked Control Systems (NCSs). We consider an NCS consisting of a set of discrete-time LTI plants whose stabilizing feedback loops are closed through a shared communication channel. Due to a limited communication capacity of the channel, not all plants can exchange information with their controllers at any instant of time. We propose a method to find periodic scheduling policies under which global asymptotic stability of each plant in the NCS is preserved. The individual plants are represented as switched systems, and the NCS is expressed as a weighted directed graph. We construct stabilizing scheduling policies by employing cycles on the underlying weighted directed graph of the NCS that satisfy appropriate contractivity conditions. We also discuss algorithmic design of these cycles.
arxiv topic:eess.SY cs.SY
arxiv_dataset-107801901.08453
Computational Modular Character Theory math.RT This book describes some computational methods to deal with modular characters of finite groups. It is the theoretical background of the MOC system of the same authors. This system was, and is still used, to compute the modular character tables of sporadic simple groups.
arxiv topic:math.RT
arxiv_dataset-107811901.08553
Data Interpolations in Deep Generative Models under Non-Simply-Connected Manifold Topology cs.LG stat.ML Exploiting the deep generative model's remarkable ability of learning the data-manifold structure, some recent researches proposed a geometric data interpolation method based on the geodesic curves on the learned data-manifold. However, this interpolation method often gives poor results due to a topological difference between the model and the dataset. The model defines a family of simply-connected manifolds, whereas the dataset generally contains disconnected regions or holes that make them non-simply-connected. To compensate this difference, we propose a novel density regularizer that make the interpolation path circumvent the holes denoted by low probability density. We confirm that our method gives consistently better interpolation results from the experiments with real-world image datasets.
arxiv topic:cs.LG stat.ML
arxiv_dataset-107821901.08653
An Identity for Vertically Aligned Entries in Pascal's Triangle math.CO math.NT The classic way to write down Pascal's triangle leads to entries in alternating rows being vertically aligned. In this paper, we prove a linear dependence on vertically aligned entries in Pascal's triangle. Furthermore, we give an application of this dependence to morphisms between hyperelliptic curves.
arxiv topic:math.CO math.NT
arxiv_dataset-107831901.08753
On Output Activation Functions for Adversarial Losses: A Theoretical Analysis via Variational Divergence Minimization and An Empirical Study on MNIST Classification cs.LG stat.ML Recent years have seen adversarial losses been applied to many fields. Their applications extend beyond the originally proposed generative modeling to conditional generative and discriminative settings. While prior work has proposed various output activation functions and regularization approaches, some open questions still remain unanswered. In this paper, we aim to study the following two research questions: 1) What types of output activation functions form a well-behaved adversarial loss? 2) How different combinations of output activation functions and regularization approaches perform empirically against one another? To answer the first question, we adopt the perspective of variational divergence minimization and consider an adversarial loss well-behaved if it behaves as a divergence-like measure between the data and model distributions. Using a generalized formulation for adversarial losses, we derive the necessary and sufficient conditions of a well-behaved adversarial loss. Our analysis reveals a large class of theoretically valid adversarial losses. For the second question, we propose a simple comparative framework for adversarial losses using discriminative adversarial networks. The proposed framework allows us to efficiently evaluate adversarial losses using a standard evaluation metric such as the classification accuracy. With the proposed framework, we evaluate a comprehensive set of 168 combinations of twelve output activation functions and fourteen regularization approaches on the handwritten digit classification problem to decouple their effects. Our empirical findings suggest that there is no single winning combination of output activation functions and regularization approaches across all settings. Our theoretical and empirical results may together serve as a reference for choosing or designing adversarial losses in future research.
arxiv topic:cs.LG stat.ML
arxiv_dataset-107841901.08853
Spin-phonon coupling in hole-doped pyrochlore iridates Y$_2$(Ir$_{1-x}$Ru$_x$)$_2$O$_7$: A Raman scattering study cond-mat.str-el Temperature dependent Raman scattering measurements have been performed to explore unusual coupling between magnetism and crystal structure in doped pyrochlore iridate Y$_2$(Ir$_{1-x}$Ru$_x$)$_2$O$_7$ with $x$ = 0.0, 0.05 and 0.2. The parent Y$_2$Ir$_2$O$_7$ shows an onset of magnetic ordering around $\sim$ 160 K ($T_{N}$) which monotonically decreases with Ru doping. Further, magnetic moment also decreases with progressive substitution of Ru. Substitution of Ru$^{4+}$ (4$d^4$) for Ir$^{4+}$ (5$d^5$) does not introduce significant modification in structural parameters, however, the magnetic transition temperature decreases systematically with doping. Raman scattering data show an anomalous change in $A_{1g}$ and $P_3$ Raman mode frequency and line-width across $T_{N}$ of individual samples. We further show that the shifting of Raman mode frequency with temperature exhibits a strong deviation from anharmonic decay around and below the $T_{N}$ of respective samples which underlines a spin-phonon coupling in these materials.
arxiv topic:cond-mat.str-el
arxiv_dataset-107851901.08953
Indecomposable objects determined by their index in Higher Homological Algebra math.RT Let $\mathscr{C}$ be a 2-Calabi-Yau triangulated category, and let $\mathscr{T}$ be a cluster tilting subcategory of $\mathscr{C}$. An important result from Dehy and Keller tells us that a rigid object $c \in \mathscr{C}$ is uniquely defined by its index with respect to $\mathscr{T}$. The notion of triangulated categories extends to the notion of $(d+2)$-angulated categories. Thanks to a paper by Oppermann and Thomas, we now have a definition for cluster tilting subcategories in higher dimensions. This paper proves that under a technical assumption, an indecomposable object in a $(d+2)$-angulated category is uniquely defined by its index with respect to a higher dimensional cluster tilting subcategory. We also demonstrate an application of this result in higher dimensional cluster categories.
arxiv topic:math.RT
arxiv_dataset-107861901.09053
Seeds for Generalized Taxicab Numbers math.NT The generalized taxicab number $T(n,m,t)$ is equal to the smallest number that is the sum of $n$ positive $m$th powers in $t$ ways. This definition is inspired by Ramanujan's observation that $1729 = 1^3+ 12^3 =9^3 + 10^3 $ is the smallest number that is the sum of two cubes in two ways and thus $1729= T(2,3,2)$. In this paper we prove that for any given positive integers $m$ and $t$, there exists a number $s$ such $T(s+k,m,t) =T(s,m,t) +k$ for every $k \geq 0$. The smallest such $s$ is termed the seed for the generalized taxicab number. Furthermore, we find explicit expressions for this seed number when the number of ways $t$ is 2 or 3 and present a conjecture for $t \geq 4$ ways.
arxiv topic:math.NT
arxiv_dataset-107871901.09153
Transverse bifurcation of viscous slow MHD shocks math.AP We study by a combination of analytical and numerical Evans function techniques multi-D viscous and inviscid stability and associated transverse bifurcation of planar slow Lax MHD shocks in a channel with periodic boundary conditions. Notably, this includes the first multi-D numerical Evans function study for viscous MHD. Our results suggest that, rather than a planar shock, a nonplanar traveling wave with the same normal velocity is the typical mode of propagation in the slow Lax mode. Moreover, viscous and inviscid stability transitions appear to agree, answering (for this particular model and setting) an open question of Zumbrun and Serre.
arxiv topic:math.AP
arxiv_dataset-107881901.09253
On Deriving Probabilistic Models for Adsorption Energy on Transition Metals using Multi-level Ab initio and Experimental Data physics.data-an physics.comp-ph In this paper, we apply multi-task Gaussian Process (MT-GP) to show that the adsorption energy of small adsorbates on transition metal surfaces can be modeled to a high level of fidelity using data from multiple sources, taking advantage of the relatively abundant ''low fidelity" data (such as from density functional theory computations) and small amounts of ''high fidelity" computational (e.g. using the random phase approximation) or experimental data. To fully explore the performance of MT-GP, we perform two case studies - one using purely computational datasets and the other using a combination of experimental and computational datasets. In both cases, the performance of MT-GPs is significantly better than single-task models built on a single data source. This method can be used to learn improved models from fused datasets, and thereby build accurate models under tight computational and experimental budget.
arxiv topic:physics.data-an physics.comp-ph
arxiv_dataset-107891901.09353
Subsumption of Weakly Well-Designed SPARQL Patterns is Undecidable cs.DB Weakly well-designed SPARQL patterns is a recent generalisation of well-designed patterns, which preserve good computational properties but also capture almost all patterns that appear in practice. Subsumption is one of static analysis problems for SPARQL, along with equivalence and containment. In this paper we show that subsumption is undecidable for weakly well-designed patterns, which is in stark contrast to well-designed patterns, and to equivalence and containment.
arxiv topic:cs.DB
arxiv_dataset-107901901.09453
On Learning Invariant Representation for Domain Adaptation cs.LG cs.AI stat.ML Due to the ability of deep neural nets to learn rich representations, recent advances in unsupervised domain adaptation have focused on learning domain-invariant features that achieve a small error on the source domain. The hope is that the learnt representation, together with the hypothesis learnt from the source domain, can generalize to the target domain. In this paper, we first construct a simple counterexample showing that, contrary to common belief, the above conditions are not sufficient to guarantee successful domain adaptation. In particular, the counterexample exhibits \emph{conditional shift}: the class-conditional distributions of input features change between source and target domains. To give a sufficient condition for domain adaptation, we propose a natural and interpretable generalization upper bound that explicitly takes into account the aforementioned shift. Moreover, we shed new light on the problem by proving an information-theoretic lower bound on the joint error of \emph{any} domain adaptation method that attempts to learn invariant representations. Our result characterizes a fundamental tradeoff between learning invariant representations and achieving small joint error on both domains when the marginal label distributions differ from source to target. Finally, we conduct experiments on real-world datasets that corroborate our theoretical findings. We believe these insights are helpful in guiding the future design of domain adaptation and representation learning algorithms.
arxiv topic:cs.LG cs.AI stat.ML
arxiv_dataset-107911901.09553
On the dynamics of reaction coordinates in classical, time-dependent, many-body processes cond-mat.stat-mech Complex microscopic many-body processes are often interpreted in terms of so-called `reaction coordinates', i.e. in terms of the evolution of a small set of coarse-grained observables. A rigorous method to produce the equation of motion of such observables is to use projection operator techniques, which split the dynamics of the observables into a main contribution and a marginal one. The basis of any derivation in this framework is the classical (or quantum) Heisenberg equation for an observable. If the Hamiltonian of the underlying microscopic dynamics and the observable under study do not explicitly depend on time, this equation is obtained by a straight-forward derivation. However, the problem is more complicated if one considers Hamiltonians which depend on time explicitly as e.g. in systems under external driving, or if the observable of interest has an explicit dependence on time. We use an analogy to fluid dynamics to derive the classical Heisenberg picture and then apply a projection operator formalism to derive the non-stationary generalized Langevin equation for a coarse-grained variable. We show, in particular, that the results presented for time-independent Hamiltonians and observables in J. Chem. Phys. 147, 214110 (2017) can be generalized to the time-dependent case.
arxiv topic:cond-mat.stat-mech
arxiv_dataset-107921901.09653
Optimal inflow control penalizing undersupply in transport systems with uncertain demands math.OC We are concerned with optimal control strategies subject to uncertain demands. An Ornstein-Uhlenbeck process describes the uncertain demand. The transport within the supply system is modeled by the linear advection equation. We consider different approaches to control the produced amount at a given time to meet the stochastic demand in an optimal way. In particular, we introduce an undersupply penalty and analyze its effect on the optimal output in a numerical simulation study.
arxiv topic:math.OC
arxiv_dataset-107931901.09753
On maximum of Gaussian process with unique maximum point of its variance math.PR Gaussian random processes which variances reach theirs maximum values at unique points are considered. Exact asymptotic behaviors of probabilities of large absolute maximums of theirs trajectories have been evaluated using Double Sum Method under the widest possible conditions.
arxiv topic:math.PR
arxiv_dataset-107941901.09853
Universal four-dimensional representation of $H \to \gamma \gamma$ at two loops through the Loop-Tree Duality hep-ph hep-th We extend useful properties of the $H\to\gamma\gamma$ unintegrated dual amplitudes from one- to two-loop level, using the Loop-Tree Duality formalism. In particular, we show that the universality of the functional form -- regardless of the nature of the internal particle -- still holds at this order. We also present an algorithmic way to renormalise two-loop amplitudes, by locally cancelling the ultraviolet singularities at integrand level, thus allowing a full four-dimensional numerical implementation of the method. Our results are compared with analytic expressions already available in the literature, finding a perfect numerical agreement. The success of this computation plays a crucial role for the development of a fully local four-dimensional framework to compute physical observables at Next-to-Next-to Leading order and beyond.
arxiv topic:hep-ph hep-th
arxiv_dataset-107951901.09953
TGAN: Deep Tensor Generative Adversarial Nets for Large Image Generation cs.CV cs.LG Deep generative models have been successfully applied to many applications. However, existing works experience limitations when generating large images (the literature usually generates small images, e.g. 32 * 32 or 128 * 128). In this paper, we propose a novel scheme, called deep tensor adversarial generative nets (TGAN), that generates large high-quality images by exploring tensor structures. Essentially, the adversarial process of TGAN takes place in a tensor space. First, we impose tensor structures for concise image representation, which is superior in capturing the pixel proximity information and the spatial patterns of elementary objects in images, over the vectorization preprocess in existing works. Secondly, we propose TGAN that integrates deep convolutional generative adversarial networks and tensor super-resolution in a cascading manner, to generate high-quality images from random distributions. More specifically, we design a tensor super-resolution process that consists of tensor dictionary learning and tensor coefficients learning. Finally, on three datasets, the proposed TGAN generates images with more realistic textures, compared with state-of-the-art adversarial autoencoders. The size of the generated images is increased by over 8.5 times, namely 374 * 374 in PASCAL2.
arxiv topic:cs.CV cs.LG
arxiv_dataset-107961901.10053
Towards Fair Deep Clustering With Multi-State Protected Variables cs.LG stat.ML Fair clustering under the disparate impact doctrine requires that population of each protected group should be approximately equal in every cluster. Previous work investigated a difficult-to-scale pre-processing step for $k$-center and $k$-median style algorithms for the special case of this problem when the number of protected groups is two. In this work, we consider a more general and practical setting where there can be many protected groups. To this end, we propose Deep Fair Clustering, which learns a discriminative but fair cluster assignment function. The experimental results on three public datasets with different types of protected attribute show that our approach can steadily improve the degree of fairness while only having minor loss in terms of clustering quality.
arxiv topic:cs.LG stat.ML
arxiv_dataset-107971901.10153
Simultaneous prediction of multiple outcomes using revised stacking algorithms q-bio.QM cs.LG stat.ML Motivation: HIV is difficult to treat because its virus mutates at a high rate and mutated viruses easily develop resistance to existing drugs. If the relationships between mutations and drug resistances can be determined from historical data, patients can be provided personalized treatment according to their own mutation information. The HIV Drug Resistance Database was built to investigate the relationships. Our goal is to build a model using data in this database, which simultaneously predicts the resistance of multiple drugs using mutation information from sequences of viruses for any new patient. Results: We propose two variations of a stacking algorithm which borrow information among multiple prediction tasks to improve multivariate prediction performance. The most attractive feature of our proposed methods is the flexibility with which complex multivariate prediction models can be constructed using any univariate prediction models. Using cross-validation studies, we show that our proposed methods outperform other popular multivariate prediction methods. Availability: An R package will be made available.
arxiv topic:q-bio.QM cs.LG stat.ML
arxiv_dataset-107981901.10253
Dynamic Inverse Wave Problems - Part II: Operator Identification and Applications math.AP We present a framework which enables the analysis of dynamic inverse problems for wave phenomena that are modeled through second-order hyperbolic PDEs. This includes well-posedness and regularity results for the forward operator in an abstract setting, where the operators in an evolution equation represent the unknowns. We also prove Fr\'echet-differentiability and local ill-posedness for this problem. We then demonstrate how to apply this theory to actual problems by two example equations motivated by linear elasticity and electrodynamics. For these problems it is even possible to obtain a simple characterization of the adjoint of the Fr\'echet-derivative of the forward operator, which is of particular interest for the application of regularization schemes.
arxiv topic:math.AP
arxiv_dataset-107991901.10353
Discovery of kilogauss magnetic fields on the nearby white dwarfs WD1105-340 and WD2150+591 astro-ph.SR Magnetic fields are present in roughly 10% of white dwarfs. These fields affect the structure and evolution of such stars, and may provide clues about their earlier evolution history. Particularly important for statistical studies is the collection of high-precision spectropolarimetric observations of (1) complete magnitude-limited samples and (2) complete volume-limited samples of white dwarfs. In the course of one of our surveys we have discovered previously unknown kG-level magnetic fields on two nearby white dwarfs, WD1105-340 and WD2150+591. Both stars are brighter than m_V = 15. WD2150+591 is within the 20-pc volume around the Sun, while WD1105-340 is just beyond 25 pc in distance. These discoveries increase the small sample of such weak-field white dwarfs from 21 to 23 stars. Our data appear consistent with roughly dipolar field topology, but it also appears that the surface field structure may be more complex on the older star than on the younger one, a result similar to one found earlier in our study of the weak-field stars WD2034+372 and WD2359-434. This encourages further efforts to uncover a clear link between magnetic morphology and stellar evolution.
arxiv topic:astro-ph.SR