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1,802.0716
Performance analysis of a novel hybrid FSO / RF communication system
In this paper, a novel dual-hop relay-assisted hybrid Free Space Optical / Radio Frequency (FSO / RF) communication system is presented. In this structure an access point connects users within the building to the Base Station via a hybrid parallel FSO / RF link, this link is proposed firstly. Parallel combination of FSO and RF links and use of an access point, will increase capacity, reliability and data rate of the system. It is the first time that the effect of number of users on the performance of a dual-hop relay-assisted hybrid parallel FSO / RF system is investigated. FSO link is considered in Gamma-Gamma atmospheric turbulence with the effect of pointing error and RF link is considered in Rayleigh fading. For the first time, closed-form expressions are derived for Bit Error Rate (BER) and Outage Probability (P_out) of the proposed system. Derived expressions are verified through MATLAB simulations. It is shown that the performance of the proposed system is almost independent of atmospheric turbulence intensity, thereby when atmospheric turbulence strengthens, low power consumption is required for maintenance of the system performance. Hence the proposed structure is particularly suitable for mobile communication systems in which a small mobile battery supplies transmitter power. Also the proposed system performance of the system is preferable even at low signal to noise ratio (SNR). Therefore, proposed structure significantly reduces power consumption while maintaining performance of the system.
eess.SP
in this paper a novel dualhop relayassisted hybrid free space optical radio frequency fso rf communication system is presented in this structure an access point connects users within the building to the base station via a hybrid parallel fso rf link this link is proposed firstly parallel combination of fso and rf links and use of an access point will increase capacity reliability and data rate of the system it is the first time that the effect of number of users on the performance of a dualhop relayassisted hybrid parallel fso rf system is investigated fso link is considered in gammagamma atmospheric turbulence with the effect of pointing error and rf link is considered in rayleigh fading for the first time closedform expressions are derived for bit error rate ber and outage probability p_out of the proposed system derived expressions are verified through matlab simulations it is shown that the performance of the proposed system is almost independent of atmospheric turbulence intensity thereby when atmospheric turbulence strengthens low power consumption is required for maintenance of the system performance hence the proposed structure is particularly suitable for mobile communication systems in which a small mobile battery supplies transmitter power also the proposed system performance of the system is preferable even at low signal to noise ratio snr therefore proposed structure significantly reduces power consumption while maintaining performance of the system
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1,802.07161
Fourier optics: basic concepts
Based on diffraction theory and the propagation of the light, Fourier optics is a powerful tool allowing the estimation of a visible-range imaging system to transfer the spatial frequency components of an object. The analyses of the imaging systems can thus be performed and the the performance retrieved. For a better understanding of the optical study, we present a short introduction of the Fourier optics and we review the mathematical treatment depending on the illumination conditions of the imaging system. Furthermore, resolution criteria based on Fourier optics are detailed. Also, the impact of aberrations on the imaging quality are discussed.
physics.gen-ph physics.optics
based on diffraction theory and the propagation of the light fourier optics is a powerful tool allowing the estimation of a visiblerange imaging system to transfer the spatial frequency components of an object the analyses of the imaging systems can thus be performed and the the performance retrieved for a better understanding of the optical study we present a short introduction of the fourier optics and we review the mathematical treatment depending on the illumination conditions of the imaging system furthermore resolution criteria based on fourier optics are detailed also the impact of aberrations on the imaging quality are discussed
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1,802.07162
Marginal Stability of Sweet-Parker Type Current Sheets at Low Lundquist Numbers
Magnetohydrodynamic simulations have shown that a non-unique critical Lundquist number $S_c$ exists, hovering around $S_c \sim 10^4$, above which threshold Sweet-Parker type stationary reconnecting configurations become unstable to a fast tearing mode dominated by plasmoid generation. It is known that the flow along the sheet plays a stabilizing role, though a satisfactory explanation of the non-universality and variable critical Lundquist numbers observed is still lacking. Here we discuss this question using 2D linear MHD simulations and linear stability analyses of Sweet-Parker type current sheets in the presence of background stationary inflows and outflows at low Lundquist numbers ($S\le 10^4$). Simulations show that the inhomogeneous outflow stabilizes the current sheet by stretching the growing magnetic islands and at the same time evacuating the magnetic islands out of the current sheet. This limits the time during which fluctuations which begin at any given wave-length can remain unstable, rendering the instability non-exponential. We find that the linear theory based on the expanding-wavelength assumption works well for $S$ larger than $\sim 1000$. However we also find that the inflow and location of the initial perturbation also affect the stability threshold.
physics.plasm-ph astro-ph.SR physics.space-ph
magnetohydrodynamic simulations have shown that a nonunique critical lundquist number s_c exists hovering around s_c sim 104 above which threshold sweetparker type stationary reconnecting configurations become unstable to a fast tearing mode dominated by plasmoid generation it is known that the flow along the sheet plays a stabilizing role though a satisfactory explanation of the nonuniversality and variable critical lundquist numbers observed is still lacking here we discuss this question using 2d linear mhd simulations and linear stability analyses of sweetparker type current sheets in the presence of background stationary inflows and outflows at low lundquist numbers sle 104 simulations show that the inhomogeneous outflow stabilizes the current sheet by stretching the growing magnetic islands and at the same time evacuating the magnetic islands out of the current sheet this limits the time during which fluctuations which begin at any given wavelength can remain unstable rendering the instability nonexponential we find that the linear theory based on the expandingwavelength assumption works well for s larger than sim 1000 however we also find that the inflow and location of the initial perturbation also affect the stability threshold
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1,802.07163
Transport-Based Pattern Theory: A Signal Transformation Approach
In many scientific fields imaging is used to relate a certain physical quantity to other dependent variables. Therefore, images can be considered as a map from a real-world coordinate system to the non-negative measurements being acquired. In this work we describe an approach for simultaneous modeling and inference of such data, using the mathematics of optimal transport. To achieve this, we describe a numerical implementation of the linear optimal transport transform, based on the solution of the Monge-Ampere equation, which uses Brenier's theorem to characterize the solution of the Monge functional as the derivative of a convex potential function. We use our implementation of the transform to compute a curl-free mapping between two images, and show that it is able to match images with lower error that existing methods. Moreover, we provide theoretical justification for properties of the linear optimal transport framework observed in the literature, including a theorem for the linear separation of data classes. Finally, we use our optimal transport method to empirically demonstrate that the linear separability theorem holds, by rendering non-linearly separable data as linearly separable following transform to transport space.
cs.CV
in many scientific fields imaging is used to relate a certain physical quantity to other dependent variables therefore images can be considered as a map from a realworld coordinate system to the nonnegative measurements being acquired in this work we describe an approach for simultaneous modeling and inference of such data using the mathematics of optimal transport to achieve this we describe a numerical implementation of the linear optimal transport transform based on the solution of the mongeampere equation which uses breniers theorem to characterize the solution of the monge functional as the derivative of a convex potential function we use our implementation of the transform to compute a curlfree mapping between two images and show that it is able to match images with lower error that existing methods moreover we provide theoretical justification for properties of the linear optimal transport framework observed in the literature including a theorem for the linear separation of data classes finally we use our optimal transport method to empirically demonstrate that the linear separability theorem holds by rendering nonlinearly separable data as linearly separable following transform to transport space
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1,802.07164
Cubic graphs, their Ehrhart quasi-polynomials, and a scissors congruence phenomenon
The scissors congruence conjecture for the unimodular group is an analogue of Hilbert's third problem, for the equidecomposability of polytopes. Liu and Osserman studied the Ehrhart quasi-polynomials of polytopes naturally associated to graphs whose vertices have degree one or three. In this paper, we prove the scissors congruence conjecture, posed by Haase and McAllister, for this class of polytopes. The key ingredient in the proofs is the nearest neighbor interchange on graphs and a naturally arising piecewise unimodular transformation.
math.CO cs.DM
the scissors congruence conjecture for the unimodular group is an analogue of hilberts third problem for the equidecomposability of polytopes liu and osserman studied the ehrhart quasipolynomials of polytopes naturally associated to graphs whose vertices have degree one or three in this paper we prove the scissors congruence conjecture posed by haase and mcallister for this class of polytopes the key ingredient in the proofs is the nearest neighbor interchange on graphs and a naturally arising piecewise unimodular transformation
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1,802.07165
On a certain identity involving the Gamma function
The goal of this paper is to prove the identity \begin{align}\sum \limits_{j=0}^{\lfloor s\rfloor}\frac{(-1)^j}{s^j}\eta_s(j)+\frac{1}{e^{s-1}s^s}\sum \limits_{j=0}^{\lfloor s\rfloor}(-1)^{j+1}\alpha_s(j)+\bigg(\frac{1-((-1)^{s-\lfloor s\rfloor +2})^{1/(s-\lfloor s\rfloor +2)}}{2}\bigg)\nonumber \\ \bigg(\sum \limits_{j=\lfloor s\rfloor +1}^{\infty}\frac{(-1)^j}{s^j}\eta_s(j)+\frac{1}{e^{s-1}s^s}\sum \limits_{j=\lfloor s\rfloor +1}^{\infty}(-1)^{j+1}\alpha_s(j)\bigg)=\frac{1}{\Gamma(s+1)},\nonumber \end{align}where \begin{align}\eta_s(j):=\bigg(e^{\gamma (s-j)}\prod \limits_{m=1}^{\infty}\bigg(1+\frac{s-j}{m}\bigg)\nonumber \\e^{-(s-j)/m}\bigg)\bigg(2+\log s-\frac{j}{s}+\sum \limits_{m=1}^{\infty}\frac{s}{m(s+m)}-\sum \limits_{m=1}^{\infty}\frac{s-j}{m(s-j+m)}\bigg), \nonumber \end{align}and \begin{align}\alpha_s(j):=\bigg(e^{\gamma (s-j)}\prod \limits_{m=1}^{\infty}\bigg(1+\frac{s-j}{m}\bigg)e^{-(s-j)/m}\bigg)\bigg(\sum \limits_{m=1}^{\infty}\frac{s}{m(s+m)}-\sum \limits_{m=1}^{\infty}\frac{s-j}{m(s-j+m)}\bigg),\nonumber \end{align}where $\Gamma(s+1)$ is the Gamma function defined by $\Gamma(s):=\int \limits_{0}^{\infty}e^{-t}t^{s-1}dt$ and $\gamma =\lim \limits_{n\longrightarrow \infty}\bigg(\sum \limits_{k=1}^{n}\frac{1}{k}-\log n\bigg)=0.577215664\cdots $ is the Euler-Mascheroni constant.
math.GM
the goal of this paper is to prove the identity beginalignsum limits_j0lfloor srfloorfrac1jsjeta_sjfrac1es1sssum limits_j0lfloor srfloor1j1alpha_sjbiggfrac11slfloor srfloor 21slfloor srfloor 22biggnonumber biggsum limits_jlfloor srfloor 1inftyfrac1jsjeta_sjfrac1es1sssum limits_jlfloor srfloor 1infty1j1alpha_sjbiggfrac1gammas1nonumber endalignwhere beginaligneta_sjbiggegamma sjprod limits_m1inftybigg1fracsjmbiggnonumber esjmbiggbigg2log sfracjssum limits_m1inftyfracsmsmsum limits_m1inftyfracsjmsjmbigg nonumber endalignand beginalignalpha_sjbiggegamma sjprod limits_m1inftybigg1fracsjmbiggesjmbiggbiggsum limits_m1inftyfracsmsmsum limits_m1inftyfracsjmsjmbiggnonumber endalignwhere gammas1 is the gamma function defined by gammasint limits_0inftyetts1dt and gamma lim limits_nlongrightarrow inftybiggsum limits_k1nfrac1klog nbigg0577215664cdots is the eulermascheroni constant
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1,802.07166
Closed, Two Dimensional Surface Dynamics
We present dynamic equations for two dimensional closed surfaces and analytically solve it for some simplified cases. We derive final equations for surface normal motions by two different ways. The solution of the equations of motions in normal direction indicates that any closed, two dimensional, homogeneous surface with time invariable surface energy density adopts constant mean curvature shape when it comes in equilibrium with environment. As an example, we apply the formalism to analyze equilibrium shapes of micelles and explain why they adopt spherical, lamellar and cylindrical shapes. We show that theoretical calculation for micellar optimal radius is in good agreement with all atom simulations and experiments.
physics.bio-ph cond-mat.soft
we present dynamic equations for two dimensional closed surfaces and analytically solve it for some simplified cases we derive final equations for surface normal motions by two different ways the solution of the equations of motions in normal direction indicates that any closed two dimensional homogeneous surface with time invariable surface energy density adopts constant mean curvature shape when it comes in equilibrium with environment as an example we apply the formalism to analyze equilibrium shapes of micelles and explain why they adopt spherical lamellar and cylindrical shapes we show that theoretical calculation for micellar optimal radius is in good agreement with all atom simulations and experiments
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1,802.07167
High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach
This paper considers the generation of prediction intervals (PIs) by neural networks for quantifying uncertainty in regression tasks. It is axiomatic that high-quality PIs should be as narrow as possible, whilst capturing a specified portion of data. We derive a loss function directly from this axiom that requires no distributional assumption. We show how its form derives from a likelihood principle, that it can be used with gradient descent, and that model uncertainty is accounted for in ensembled form. Benchmark experiments show the method outperforms current state-of-the-art uncertainty quantification methods, reducing average PI width by over 10%.
stat.ML
this paper considers the generation of prediction intervals pis by neural networks for quantifying uncertainty in regression tasks it is axiomatic that highquality pis should be as narrow as possible whilst capturing a specified portion of data we derive a loss function directly from this axiom that requires no distributional assumption we show how its form derives from a likelihood principle that it can be used with gradient descent and that model uncertainty is accounted for in ensembled form benchmark experiments show the method outperforms current stateoftheart uncertainty quantification methods reducing average pi width by over 10
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1,802.07168
Some results relating to (p,q)-th relative Gol'dberg order and (p,q)-relative Gol'dberg type of entire functions of several variables
In this paper we introduce the notions of (p,q)-th relative Gol'dberg order and (p,q)-th relative Gol'dberg type of entire functions of several complex variables where p,q are any positive integers. Then we study some growth properties of entire functions of several complex variables on the basis of their (p,q)-th relative Gol'dberg order and (p,q)-th relative Gol'dberg type.
math.CV
in this paper we introduce the notions of pqth relative goldberg order and pqth relative goldberg type of entire functions of several complex variables where pq are any positive integers then we study some growth properties of entire functions of several complex variables on the basis of their pqth relative goldberg order and pqth relative goldberg type
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1,802.07169
Self-organization principles of intracellular pattern formation
Dynamic patterning of specific proteins is essential for the spatiotemporal regulation of many important intracellular processes in procaryotes, eucaryotes, and multicellular organisms. The emergence of patterns generated by interactions of diffusing proteins is a paradigmatic example for self-organization. In this article we review quantitative models for intracellular Min protein patterns in E. coli, Cdc42 polarization in S. cerevisiae, and the bipolar PAR protein patterns found in C. elegans. By analyzing the molecular processes driving these systems we derive a theoretical perspective on general principles underlying self-organized pattern formation. We argue that intracellular pattern formation is not captured by concepts such as "activators"', "inhibitors", or "substrate-depletion". Instead, intracellular pattern formation is based on the redistribution of proteins by cytosolic diffusion, and the cycling of proteins between distinct conformational states. Therefore, mass-conserving reaction-diffusion equations provide the most appropriate framework to study intracellular pattern formation. We conclude that directed transport, e.g. cytosolic diffusion along an actively maintained cytosolic gradient, is the key process underlying pattern formation. Thus the basic principle of self-organization is the establishment and maintenance of directed transport by intracellular protein dynamics.
physics.bio-ph q-bio.SC
dynamic patterning of specific proteins is essential for the spatiotemporal regulation of many important intracellular processes in procaryotes eucaryotes and multicellular organisms the emergence of patterns generated by interactions of diffusing proteins is a paradigmatic example for selforganization in this article we review quantitative models for intracellular min protein patterns in e coli cdc42 polarization in s cerevisiae and the bipolar par protein patterns found in c elegans by analyzing the molecular processes driving these systems we derive a theoretical perspective on general principles underlying selforganized pattern formation we argue that intracellular pattern formation is not captured by concepts such as activators inhibitors or substratedepletion instead intracellular pattern formation is based on the redistribution of proteins by cytosolic diffusion and the cycling of proteins between distinct conformational states therefore massconserving reactiondiffusion equations provide the most appropriate framework to study intracellular pattern formation we conclude that directed transport eg cytosolic diffusion along an actively maintained cytosolic gradient is the key process underlying pattern formation thus the basic principle of selforganization is the establishment and maintenance of directed transport by intracellular protein dynamics
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1,802.0717
CytonMT: an Efficient Neural Machine Translation Open-source Toolkit Implemented in C++
This paper presents an open-source neural machine translation toolkit named CytonMT (https://github.com/arthurxlw/cytonMt). The toolkit is built from scratch only using C++ and NVIDIA's GPU-accelerated libraries. The toolkit features training efficiency, code simplicity and translation quality. Benchmarks show that CytonMT accelerates the training speed by 64.5% to 110.8% on neural networks of various sizes, and achieves competitive translation quality.
cs.CL
this paper presents an opensource neural machine translation toolkit named cytonmt httpsgithubcomarthurxlwcytonmt the toolkit is built from scratch only using c and nvidias gpuaccelerated libraries the toolkit features training efficiency code simplicity and translation quality benchmarks show that cytonmt accelerates the training speed by 645 to 1108 on neural networks of various sizes and achieves competitive translation quality
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1,802.07171
Constrained minimum Riesz and Green energy problems for vector measures associated with a generalized condenser
For a finite collection $\mathbf A=(A_i)_{i\in I}$ of locally closed sets in $\mathbb R^n$, $n\geqslant3$, with the sign $\pm1$ prescribed such that the oppositely charged plates are mutually disjoint, we consider the minimum energy problem relative to the $\alpha$-Riesz kernel $|x-y|^{\alpha-n}$, $\alpha\in(0,2]$, over positive vector Radon measures $\boldsymbol\mu=(\mu^i)_{i\in I}$ such that each $\mu^i$, $i\in I$, is carried by $A_i$ and normalized by $\mu^i(A_i)=a_i\in(0,\infty)$. We show that, though the closures of oppositely charged plates may intersect each other even in a set of nonzero capacity, this problem has a solution $\boldsymbol\lambda^{\boldsymbol\xi}_{\mathbf A}=(\lambda^i_{\mathbf A})_{i\in I}$ (also in the presence of an external field) if we restrict ourselves to $\boldsymbol\mu$ with $\mu^i\leqslant\xi^i$, $i\in I$, where the constraint $\boldsymbol\xi=(\xi^i)_{i\in I}$ is properly chosen. We establish the sharpness of the sufficient conditions on the solvability thus obtained, provide descriptions of the weighted vector $\alpha$-Riesz potentials of the solutions, single out their characteristic properties, and analyze the supports of the $\lambda^i_{\mathbf A}$, $i\in I$. Our approach is based on the simultaneous use of the vague topology and an appropriate semimetric structure defined in terms of the $\alpha$-Riesz energy on a set of vector measures associated with $\mathbf A$, as well as on the establishment of an intimate relationship between the constrained minimum $\alpha$-Riesz energy problem and a constrained minimum $\alpha$-Green energy problem, suitably formulated. The results are illustrated by examples.
math.CA
for a finite collection mathbf aa_i_iin i of locally closed sets in mathbb rn ngeqslant3 with the sign pm1 prescribed such that the oppositely charged plates are mutually disjoint we consider the minimum energy problem relative to the alphariesz kernel xyalphan alphain02 over positive vector radon measures boldsymbolmumui_iin i such that each mui iin i is carried by a_i and normalized by muia_ia_iin0infty we show that though the closures of oppositely charged plates may intersect each other even in a set of nonzero capacity this problem has a solution boldsymbollambdaboldsymbolxi_mathbf alambdai_mathbf a_iin i also in the presence of an external field if we restrict ourselves to boldsymbolmu with muileqslantxii iin i where the constraint boldsymbolxixii_iin i is properly chosen we establish the sharpness of the sufficient conditions on the solvability thus obtained provide descriptions of the weighted vector alphariesz potentials of the solutions single out their characteristic properties and analyze the supports of the lambdai_mathbf a iin i our approach is based on the simultaneous use of the vague topology and an appropriate semimetric structure defined in terms of the alphariesz energy on a set of vector measures associated with mathbf a as well as on the establishment of an intimate relationship between the constrained minimum alphariesz energy problem and a constrained minimum alphagreen energy problem suitably formulated the results are illustrated by examples
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1,802.07172
Spin-1/2 anisotropic Heisenberg antiferromagnet with Dzyaloshinskii-Moriya interaction via mean-field approximation
The spin-1/2 anisotropic Heisenberg model with antiferromagnetic exchange interactions in the presence of a external magnetic field and a Dzyaloshinskii-Moriya interaction is studied by employing the usual mean-field approximation. The magnetic properties are obtained and it is shown that only second-order phase transitions take place for any values of the theoretical Hamiltonian parameters. Contrary to previous results from effective field theory, no anomalies have been observed at low temperatures. However, some re-entrancies still persist in some region of the phase diagram.
cond-mat.stat-mech
the spin12 anisotropic heisenberg model with antiferromagnetic exchange interactions in the presence of a external magnetic field and a dzyaloshinskiimoriya interaction is studied by employing the usual meanfield approximation the magnetic properties are obtained and it is shown that only secondorder phase transitions take place for any values of the theoretical hamiltonian parameters contrary to previous results from effective field theory no anomalies have been observed at low temperatures however some reentrancies still persist in some region of the phase diagram
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1,802.07173
Existence of the gauge for fractional Laplacian Schr\"{o}dinger operators
Let $\Omega \subseteq \mathbb{R}^n$ be an open set, where $n \geq 2$. Suppose $\omega $ is a locally finite Borel measure on $\Omega$. For $\alpha \in (0,2)$, define the fractional Laplacian $(-\triangle )^{\alpha/2}$ via the Fourier transform on $\mathbb{R}^n$, and let $G $ be the corresponding Green's operator of order $\alpha$ on $\Omega$. Define $T(u) = G(u \omega).$ If $\Vert T \Vert_{L^2(\omega) \rightarrow L^2 (\omega)} <1$, we obtain a representation for the unique weak solution $u$ in the homogeneous Sobolev space $L^{\alpha/2, 2}_0 (\Omega)$ of \[ (-\triangle)^{\alpha/2} u = u \omega + \nu \,\,\, \mbox{on} \,\,\, \Omega, \,\,\, u=0 \,\,\, \mbox{on} \,\,\, \Omega^c, \] for $\nu$ in the dual Sobolev space $L^{-\alpha/2, 2} (\Omega)$. If $\Omega$ is a bounded $C^{1,1}$ domain, this representation yields matching exponential upper and lower pointwise estimates for the solution when $\nu = \chi_{\Omega}$. These estimates are used to study the existence of a solution $u_1$ (called the "gauge") of the integral equation $u_1=1+G(u_1 \omega)$ corresponding to the problem \[ (-\triangle)^{\alpha/2} u = u \omega \,\,\, \mbox{on} \,\,\, \Omega, \,\,\, u \geq 0 \,\,\, \mbox{on} \,\,\, \Omega, \,\,\, u=1 \,\,\, \mbox{on} \,\,\, \Omega^c . \] We show that if $\Vert T \Vert <1$, then $u_1$ always exists if $0<\alpha <1$. For $1 \leq \alpha <2$, a solution exists if the norm of $T$ is sufficiently small. We also show that the condition $\Vert T \Vert <1$ does not imply the existence of a solution if $1 < \alpha <2$.
math.AP math.CA
let omega subseteq mathbbrn be an open set where n geq 2 suppose omega is a locally finite borel measure on omega for alpha in 02 define the fractional laplacian triangle alpha2 via the fourier transform on mathbbrn and let g be the corresponding greens operator of order alpha on omega define tu gu omega if vert t vert_l2omega rightarrow l2 omega 1 we obtain a representation for the unique weak solution u in the homogeneous sobolev space lalpha2 2_0 omega of trianglealpha2 u u omega nu mboxon omega u0 mboxon omegac for nu in the dual sobolev space lalpha2 2 omega if omega is a bounded c11 domain this representation yields matching exponential upper and lower pointwise estimates for the solution when nu chi_omega these estimates are used to study the existence of a solution u_1 called the gauge of the integral equation u_11gu_1 omega corresponding to the problem trianglealpha2 u u omega mboxon omega u geq 0 mboxon omega u1 mboxon omegac we show that if vert t vert 1 then u_1 always exists if 0alpha 1 for 1 leq alpha 2 a solution exists if the norm of t is sufficiently small we also show that the condition vert t vert 1 does not imply the existence of a solution if 1 alpha 2
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1,802.07174
Soft-photon corrections to the Bethe-Heitler process in the $\gamma p\rightarrow l^+l^-p$ reaction
We report on the calculation of first-order QED corrections for the $\gamma p\rightarrow l^+l^-p^{\prime}$ process. An upcoming experiment at MAMI (Mainz) aims to compare the cross sections of muon- and electron-pair production in this reaction to test lepton universality. Precise knowledge of the electromagnetic radiative corrections is needed for these measurements. As a first step, we present the leading QED radiative corrections in the soft-photon approximation when accounting for the finite lepton mass. For the kinematics at MAMI, we find corrections of the percent level for muons, and of order $10\%$ for electrons.
hep-ph nucl-ex nucl-th
we report on the calculation of firstorder qed corrections for the gamma prightarrow llpprime process an upcoming experiment at mami mainz aims to compare the cross sections of muon and electronpair production in this reaction to test lepton universality precise knowledge of the electromagnetic radiative corrections is needed for these measurements as a first step we present the leading qed radiative corrections in the softphoton approximation when accounting for the finite lepton mass for the kinematics at mami we find corrections of the percent level for muons and of order 10 for electrons
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1,802.07175
The parameterized complexity of finding a 2-sphere in a simplicial complex
We consider the problem of finding a subcomplex K' of a simplicial complex K such that K' is homeomorphic to the 2-dimensional sphere, S^2. We study two variants of this problem. The first asks if there exists such a K' with at most k triangles, and we show that this variant is W[1]-hard and, assuming ETH, admits no O(n^{o(sqrt(k))}) time algorithm. We also give an algorithm that is tight with regards to this lower bound. The second problem is the dual of the first, and asks if K' can be found by removing at most k triangles from K. This variant has an immediate O(3^k poly(|K|)) time algorithm, and we show that it admits a polynomial kernelization to O(k^2) triangles, as well as a polynomial compression to a weighted version with bit-size O(k log k).
cs.DS math.CO
we consider the problem of finding a subcomplex k of a simplicial complex k such that k is homeomorphic to the 2dimensional sphere s2 we study two variants of this problem the first asks if there exists such a k with at most k triangles and we show that this variant is w1hard and assuming eth admits no onosqrtk time algorithm we also give an algorithm that is tight with regards to this lower bound the second problem is the dual of the first and asks if k can be found by removing at most k triangles from k this variant has an immediate o3k polyk time algorithm and we show that it admits a polynomial kernelization to ok2 triangles as well as a polynomial compression to a weighted version with bitsize ok log k
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1,802.07176
Adaptive Sampling for Coarse Ranking
We consider the problem of active coarse ranking, where the goal is to sort items according to their means into clusters of pre-specified sizes, by adaptively sampling from their reward distributions. This setting is useful in many social science applications involving human raters and the approximate rank of every item is desired. Approximate or coarse ranking can significantly reduce the number of ratings required in comparison to the number needed to find an exact ranking. We propose a computationally efficient PAC algorithm LUCBRank for coarse ranking, and derive an upper bound on its sample complexity. We also derive a nearly matching distribution-dependent lower bound. Experiments on synthetic as well as real-world data show that LUCBRank performs better than state-of-the-art baseline methods, even when these methods have the advantage of knowing the underlying parametric model.
cs.LG stat.ML
we consider the problem of active coarse ranking where the goal is to sort items according to their means into clusters of prespecified sizes by adaptively sampling from their reward distributions this setting is useful in many social science applications involving human raters and the approximate rank of every item is desired approximate or coarse ranking can significantly reduce the number of ratings required in comparison to the number needed to find an exact ranking we propose a computationally efficient pac algorithm lucbrank for coarse ranking and derive an upper bound on its sample complexity we also derive a nearly matching distributiondependent lower bound experiments on synthetic as well as realworld data show that lucbrank performs better than stateoftheart baseline methods even when these methods have the advantage of knowing the underlying parametric model
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1,802.07177
Wireless Expanders
This paper introduces an extended notion of expansion suitable for radio networks. A graph $G=(V,E)$ is called an $(\alpha_w, \beta_w)$-{wireless expander} if for every subset $S \subseteq V$ s.t. $|S|\leq \alpha_w \cdot |V|$, there exists a subset $S'\subseteq S$ s.t. there are at least $\beta_w \cdot |S|$ vertices in $V\backslash S$ adjacent in $G$ to exactly one vertex in $S'$. The main question we ask is the following: to what extent are ordinary expanders also good {wireless} expanders? We answer this question in a nearly tight manner. On the positive side, we show that any $(\alpha, \beta)$-expander with maximum degree $\Delta$ and $\beta\geq 1/\Delta$ is also a $(\alpha_w, \beta_w)$ wireless expander for $\beta_w = \Omega(\beta / \log (2 \cdot \min\{\Delta / \beta, \Delta \cdot \beta\}))$. Thus the wireless expansion is smaller than the ordinary expansion by at most a factor logarithmic in $\min\{\Delta / \beta, \Delta \cdot \beta\}$, which depends on the graph \emph{average degree} rather than maximum degree; e.g., for low arboricity graphs, the wireless expansion matches the ordinary expansion up to a constant. We complement this positive result by presenting an explicit construction of a "bad" $(\alpha, \beta)$-expander for which the wireless expansion is $\beta_w = O(\beta / \log (2 \cdot \min\{\Delta / \beta, \Delta \cdot \beta\})$. We also analyze the theoretical properties of wireless expanders and their connection to unique neighbor expanders, and demonstrate their applicability: Our results yield improved bounds for the {spokesmen election problem} that was introduced in the seminal paper of Chlamtac and Weinstein (1991) to devise efficient broadcasting for multihop radio networks. Our negative result yields a significantly simpler proof than that from the seminal paper of Kushilevitz and Mansour (1998) for a lower bound on the broadcast time in radio networks.
cs.DS
this paper introduces an extended notion of expansion suitable for radio networks a graph gve is called an alpha_w beta_wwireless expander if for every subset s subseteq v st sleq alpha_w cdot v there exists a subset ssubseteq s st there are at least beta_w cdot s vertices in vbackslash s adjacent in g to exactly one vertex in s the main question we ask is the following to what extent are ordinary expanders also good wireless expanders we answer this question in a nearly tight manner on the positive side we show that any alpha betaexpander with maximum degree delta and betageq 1delta is also a alpha_w beta_w wireless expander for beta_w omegabeta log 2 cdot mindelta beta delta cdot beta thus the wireless expansion is smaller than the ordinary expansion by at most a factor logarithmic in mindelta beta delta cdot beta which depends on the graph emphaverage degree rather than maximum degree eg for low arboricity graphs the wireless expansion matches the ordinary expansion up to a constant we complement this positive result by presenting an explicit construction of a bad alpha betaexpander for which the wireless expansion is beta_w obeta log 2 cdot mindelta beta delta cdot beta we also analyze the theoretical properties of wireless expanders and their connection to unique neighbor expanders and demonstrate their applicability our results yield improved bounds for the spokesmen election problem that was introduced in the seminal paper of chlamtac and weinstein 1991 to devise efficient broadcasting for multihop radio networks our negative result yields a significantly simpler proof than that from the seminal paper of kushilevitz and mansour 1998 for a lower bound on the broadcast time in radio networks
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1,802.07178
Primitive abundant and weird numbers with many prime factors
We give an algorithm to enumerate all primitive abundant numbers (briefly, PANs) with a fixed $\Omega$ (the number of prime factors counted with their multiplicity), and explicitly find all PANs up to $\Omega=6$, count all PANs and square-free PANs up to $\Omega=7$ and count all odd PANs and odd square-free PANs up to $\Omega=8$. We find primitive weird numbers (briefly, PWNs) with up to 16 prime factors, improving the previous results of [Amato-Hasler-Melfi-Parton] where PWNs with up to 6 prime factors have been given. The largest PWN we find has 14712 digits: as far as we know, this is the largest example existing, the previous one being 5328 digits long [Melfi]. We find hundreds of PWNs with exactly one square odd prime factor: as far as we know, only five were known before. We find all PWNs with at least one odd prime factor with multiplicity greater than one and $\Omega = 7$ and prove that there are none with $\Omega < 7$. Regarding PWNs with a cubic (or higher) odd prime factor, we prove that there are none with $\Omega\le 7$, and we did not find any with larger $\Omega$. Finally, we find several PWNs with 2 square odd prime factors, and one with 3 square odd prime factors. These are the first such examples.
math.NT
we give an algorithm to enumerate all primitive abundant numbers briefly pans with a fixed omega the number of prime factors counted with their multiplicity and explicitly find all pans up to omega6 count all pans and squarefree pans up to omega7 and count all odd pans and odd squarefree pans up to omega8 we find primitive weird numbers briefly pwns with up to 16 prime factors improving the previous results of amatohaslermelfiparton where pwns with up to 6 prime factors have been given the largest pwn we find has 14712 digits as far as we know this is the largest example existing the previous one being 5328 digits long melfi we find hundreds of pwns with exactly one square odd prime factor as far as we know only five were known before we find all pwns with at least one odd prime factor with multiplicity greater than one and omega 7 and prove that there are none with omega 7 regarding pwns with a cubic or higher odd prime factor we prove that there are none with omegale 7 and we did not find any with larger omega finally we find several pwns with 2 square odd prime factors and one with 3 square odd prime factors these are the first such examples
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1,802.07179
Finite temperature electronic structure of Diamond and Silicon
The electron-phonon interaction contribution to the electronic energies is included in density functional total energy calculations with ab initio pseudopotentials via the Allen formalism [Phys. Rev. B 18, 5217 (1978)] to obtain temperature dependent electronic structure of diamond and silicon. This method allows us to obtain the thermally-averaged ab initio electronic structure in a straightforward and computationally inexpensive way. Our investigations on the finite temperature electronic structure of diamond and silicon lead to a new criterion, temperature transferability, which is required in the ab initio pseudopotentials for temperature dependent studies. The temperature transferability of the Troullier-Martins pseudopotentials used in this work is strongly dependent on the cut-off radius and the inclusion of the unbound 3d$^0$ state. The finite temperature indirect band gaps are highly sensitive to the choice of cut-off radius used in the pseudopotentials. The finite temperature band structures and density of states show that thermal vibrations affect the electron energies throughout the valence and conduction band. We compare our results on the band gap shifts with that due to the Debye-Waller term in the Allen-Heine theory and discuss the observed differences in the zero point and high temperature band gap shifts. Although, the electron energy shifts in the highest occupied valence band and lowest unoccupied conduction band enable to obtain the changes in the indirect and direct band gaps at finite temperatures, the shifts in other electronic levels with temperature enable investigations into the finite temperature valence charge distribution in the bonding region. Thus, we demonstrate that the Allen theory provides a simple and theoretically justified formalism to obtain finite temperature valence electron charge densities that go beyond the rigid pseudo-atom approximation.
cond-mat.mtrl-sci
the electronphonon interaction contribution to the electronic energies is included in density functional total energy calculations with ab initio pseudopotentials via the allen formalism phys rev b 18 5217 1978 to obtain temperature dependent electronic structure of diamond and silicon this method allows us to obtain the thermallyaveraged ab initio electronic structure in a straightforward and computationally inexpensive way our investigations on the finite temperature electronic structure of diamond and silicon lead to a new criterion temperature transferability which is required in the ab initio pseudopotentials for temperature dependent studies the temperature transferability of the troulliermartins pseudopotentials used in this work is strongly dependent on the cutoff radius and the inclusion of the unbound 3d0 state the finite temperature indirect band gaps are highly sensitive to the choice of cutoff radius used in the pseudopotentials the finite temperature band structures and density of states show that thermal vibrations affect the electron energies throughout the valence and conduction band we compare our results on the band gap shifts with that due to the debyewaller term in the allenheine theory and discuss the observed differences in the zero point and high temperature band gap shifts although the electron energy shifts in the highest occupied valence band and lowest unoccupied conduction band enable to obtain the changes in the indirect and direct band gaps at finite temperatures the shifts in other electronic levels with temperature enable investigations into the finite temperature valence charge distribution in the bonding region thus we demonstrate that the allen theory provides a simple and theoretically justified formalism to obtain finite temperature valence electron charge densities that go beyond the rigid pseudoatom approximation
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1,802.0718
Comparison of threshold-based algorithms for sparse signal recovery
Intensively growing approach in signal processing and acquisition, the Compressive Sensing approach, allows sparse signals to be recovered from small number of randomly acquired signal coefficients. This paper analyses some of the commonly used threshold-based algorithms for sparse signal reconstruction. Signals satisfy the conditions required by the Compressive Sensing theory. The Orthogonal Matching Pursuit, Iterative Hard Thresholding and Single Iteration Reconstruction algorithms are observed. Comparison in terms of reconstruction error and execution time is performed within the experimental part of the paper.
eess.SP cs.MM
intensively growing approach in signal processing and acquisition the compressive sensing approach allows sparse signals to be recovered from small number of randomly acquired signal coefficients this paper analyses some of the commonly used thresholdbased algorithms for sparse signal reconstruction signals satisfy the conditions required by the compressive sensing theory the orthogonal matching pursuit iterative hard thresholding and single iteration reconstruction algorithms are observed comparison in terms of reconstruction error and execution time is performed within the experimental part of the paper
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1,802.07181
Algorithmic Information Dynamics of Persistent Patterns and Colliding Particles in the Game of Life
Without loss of generalisation to other systems, including possibly non-deterministic ones, we demonstrate the application of methods drawn from algorithmic information dynamics to the characterisation and classification of emergent and persistent patterns, motifs and colliding particles in Conway's Game of Life (GoL), a cellular automaton serving as a case study illustrating the way in which such ideas can be applied to a typical discrete dynamical system. We explore the issue of local observations of closed systems whose orbits may appear open because of inaccessibility to the global rules governing the overall system. We also investigate aspects of symmetry related to complexity in the distribution of patterns that occur with high frequency in GoL (which we thus call motifs) and analyse the distribution of these motifs with a view to tracking the changes in their algorithmic probability over time. We demonstrate how the tools introduced are an alternative to other computable measures that are unable to capture changes in emergent structures in evolving complex systems that are often too small or too subtle to be properly characterised by methods such as lossless compression and Shannon entropy.
nlin.CG cs.IT math.DS math.IT
without loss of generalisation to other systems including possibly nondeterministic ones we demonstrate the application of methods drawn from algorithmic information dynamics to the characterisation and classification of emergent and persistent patterns motifs and colliding particles in conways game of life gol a cellular automaton serving as a case study illustrating the way in which such ideas can be applied to a typical discrete dynamical system we explore the issue of local observations of closed systems whose orbits may appear open because of inaccessibility to the global rules governing the overall system we also investigate aspects of symmetry related to complexity in the distribution of patterns that occur with high frequency in gol which we thus call motifs and analyse the distribution of these motifs with a view to tracking the changes in their algorithmic probability over time we demonstrate how the tools introduced are an alternative to other computable measures that are unable to capture changes in emergent structures in evolving complex systems that are often too small or too subtle to be properly characterised by methods such as lossless compression and shannon entropy
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1,802.07182
The Gaussian Process Autoregressive Regression Model (GPAR)
Multi-output regression models must exploit dependencies between outputs to maximise predictive performance. The application of Gaussian processes (GPs) to this setting typically yields models that are computationally demanding and have limited representational power. We present the Gaussian Process Autoregressive Regression (GPAR) model, a scalable multi-output GP model that is able to capture nonlinear, possibly input-varying, dependencies between outputs in a simple and tractable way: the product rule is used to decompose the joint distribution over the outputs into a set of conditionals, each of which is modelled by a standard GP. GPAR's efficacy is demonstrated on a variety of synthetic and real-world problems, outperforming existing GP models and achieving state-of-the-art performance on established benchmarks.
stat.ML
multioutput regression models must exploit dependencies between outputs to maximise predictive performance the application of gaussian processes gps to this setting typically yields models that are computationally demanding and have limited representational power we present the gaussian process autoregressive regression gpar model a scalable multioutput gp model that is able to capture nonlinear possibly inputvarying dependencies between outputs in a simple and tractable way the product rule is used to decompose the joint distribution over the outputs into a set of conditionals each of which is modelled by a standard gp gpars efficacy is demonstrated on a variety of synthetic and realworld problems outperforming existing gp models and achieving stateoftheart performance on established benchmarks
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1,802.07183
Unitary Scheme Model Calculations of the Ground- and Excited-State Characteristics of 3H and 4He
The ground and excited states of the 3H and 4He nuclei are studied in the framework of group-theoretical methods. Basis functions of the unitary scheme model corresponding to even numbers of quanta of excitation in the range from zero to twenty are constructed for the even-parity states of these two nuclei, and bases from one to nineteen are constructed for the odd-parity states of the 4He nucleus. The ground-state and first-excited-state energies and wave functions, the ground S-, P- and D-state probabilities, the root-mean-square radius and the magnetic dipole moment of Triton are calculated. Furthermore, for the 4He nucleus, the spectrum and the wave functions, the ground S-, P- and D-state probabilities, the root-mean-square radius and the total integral cross section of the dipole electric transition accompanying the photoabsorption of gamma quanta by this nucleus are calculated. The GPT and AV8' two-body interactions and the Urbana nine three-nucleon interaction are used in these investigations. Moreover, the convergence of the calculations is examined by incrementally extrapolating the nuclear characteristics calculated for N less than or equal to twenty to N equals thirty.
nucl-th
the ground and excited states of the 3h and 4he nuclei are studied in the framework of grouptheoretical methods basis functions of the unitary scheme model corresponding to even numbers of quanta of excitation in the range from zero to twenty are constructed for the evenparity states of these two nuclei and bases from one to nineteen are constructed for the oddparity states of the 4he nucleus the groundstate and firstexcitedstate energies and wave functions the ground s p and dstate probabilities the rootmeansquare radius and the magnetic dipole moment of triton are calculated furthermore for the 4he nucleus the spectrum and the wave functions the ground s p and dstate probabilities the rootmeansquare radius and the total integral cross section of the dipole electric transition accompanying the photoabsorption of gamma quanta by this nucleus are calculated the gpt and av8 twobody interactions and the urbana nine threenucleon interaction are used in these investigations moreover the convergence of the calculations is examined by incrementally extrapolating the nuclear characteristics calculated for n less than or equal to twenty to n equals thirty
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1,802.07184
Comment on the Bekenstein bound
We propose a rigorous derivation of the Bekenstein upper limit for the entropy/information that can be contained by a physical system in a given finite region of space with given finite energy. The starting point is the observation that the derivation of such a bound provided by Casini [6] is similar to the description of the black hole incremental free energy that had been given by the first named author [23]. The approach here is different but close in the spirit to [6]. Our bound is obtained by operator algebraic methods, in particular Connes' bimodules, Tomita-Takesaki modular theory and Jones' index are essential ingredients inasmuch as the von Neumann algebras in question are typically of type III. We rely on the general mathematical framework, recently set up in [26], concerning quantum information of infinite systems.
math-ph gr-qc hep-th math.MP math.OA
we propose a rigorous derivation of the bekenstein upper limit for the entropyinformation that can be contained by a physical system in a given finite region of space with given finite energy the starting point is the observation that the derivation of such a bound provided by casini 6 is similar to the description of the black hole incremental free energy that had been given by the first named author 23 the approach here is different but close in the spirit to 6 our bound is obtained by operator algebraic methods in particular connes bimodules tomitatakesaki modular theory and jones index are essential ingredients inasmuch as the von neumann algebras in question are typically of type iii we rely on the general mathematical framework recently set up in 26 concerning quantum information of infinite systems
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1,802.07185
The Planetary Nebula Luminosity Function (PNLF): Contamination from Supernova Remnants
The planetary nebula luminosity function (PNLF) has been used as an extragalactic distance indicator since the 1980's, but there are still unsolved problems associated with its use. One of the most serious involves PNLF distances beyond ~ 10 Mpc, which tend to be slightly smaller than those of other methods. We consider the implications of previous spectroscopic investigations that found that several of the brightest planetary nebula (PN) candidates in M74 are actually compact supernova remnants (SNRs). Using narrow-band imaging data from the KPNO 4-m telescope, we measure the [O III] $\lambda$5007 and H$\alpha$ fluxes of all the known SNRs in M31 and M33, and test whether those objects could be misidentified as bright PNe at distances beyond ~ 10 Mpc. Our results suggest that compact SNRs are not an important source of contamination in photometric surveys for extragalactic PNe.
astro-ph.GA astro-ph.SR
the planetary nebula luminosity function pnlf has been used as an extragalactic distance indicator since the 1980s but there are still unsolved problems associated with its use one of the most serious involves pnlf distances beyond 10 mpc which tend to be slightly smaller than those of other methods we consider the implications of previous spectroscopic investigations that found that several of the brightest planetary nebula pn candidates in m74 are actually compact supernova remnants snrs using narrowband imaging data from the kpno 4m telescope we measure the o iii lambda5007 and halpha fluxes of all the known snrs in m31 and m33 and test whether those objects could be misidentified as bright pne at distances beyond 10 mpc our results suggest that compact snrs are not an important source of contamination in photometric surveys for extragalactic pne
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1,802.07186
Stochastic compressible Euler equations and inviscid limits
We prove the existence of a unique local strong solution to the stochastic compressible Euler system with nonlinear multiplicative noise. This solution exists up to a positive stopping time and is strong in both the PDE and probabilistic sense. Based on this existence result, we study the inviscid limit of the stochastic compressible Navier--Stokes system. As the viscosity tends to zero, any sequence of finite energy weak martingale solutions converges to the compressible Euler system.
math.AP math.PR physics.flu-dyn
we prove the existence of a unique local strong solution to the stochastic compressible euler system with nonlinear multiplicative noise this solution exists up to a positive stopping time and is strong in both the pde and probabilistic sense based on this existence result we study the inviscid limit of the stochastic compressible navierstokes system as the viscosity tends to zero any sequence of finite energy weak martingale solutions converges to the compressible euler system
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1,802.07187
Leader-follower based Coalition Formation in Large-scale UAV Networks, A Quantum Evolutionary Approach
The problem of decentralized multiple Point of Interests (PoIs) detection and associated task completion in an unknown environment with multiple resource-constrained and self-interested Unmanned Aerial Vehicles (UAVs) is studied. The UAVs form several coalitions to efficiently complete the compound tasks which are impossible to be performed individually. The objectives of such coalition formation are to firstly minimize resource consumption in completing the encountered tasks on time, secondly to enhance the reliability of the coalitions, and lastly in segregating the most trusted UAVs amid the self interested of them. As many previous publications have merely focused on minimizing costs, this study considers a multi-objective optimization coalition formation problem that considers the three aforementioned objectives. In doing so, a leader-follower- inspired coalition formation algorithm amalgamating the three objectives to address the problem of the computational complexity of coalition formation in large-scale UAV networks is proposed. This algorithm attempts to form the coalitions with minimally exceeding the required resources for the encountered tasks while maximizing the number of completed tasks. The proposed algorithm is based on Quantum Evolutionary Algorithms(QEA) which are a combination of quantum computing and evolutionary algorithms. Results from simulations show that the proposed algorithm significantly outperforms the existing coalition formation algorithms such as merge-and-split and a famous multi-objective genetic algorithm called NSGA-II.
cs.MA cs.GT
the problem of decentralized multiple point of interests pois detection and associated task completion in an unknown environment with multiple resourceconstrained and selfinterested unmanned aerial vehicles uavs is studied the uavs form several coalitions to efficiently complete the compound tasks which are impossible to be performed individually the objectives of such coalition formation are to firstly minimize resource consumption in completing the encountered tasks on time secondly to enhance the reliability of the coalitions and lastly in segregating the most trusted uavs amid the self interested of them as many previous publications have merely focused on minimizing costs this study considers a multiobjective optimization coalition formation problem that considers the three aforementioned objectives in doing so a leaderfollower inspired coalition formation algorithm amalgamating the three objectives to address the problem of the computational complexity of coalition formation in largescale uav networks is proposed this algorithm attempts to form the coalitions with minimally exceeding the required resources for the encountered tasks while maximizing the number of completed tasks the proposed algorithm is based on quantum evolutionary algorithmsqea which are a combination of quantum computing and evolutionary algorithms results from simulations show that the proposed algorithm significantly outperforms the existing coalition formation algorithms such as mergeandsplit and a famous multiobjective genetic algorithm called nsgaii
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1,802.07188
Adjoint Sensitivity Analysis of Hybrid Multibody Dynamical Systems
Sensitivity analysis of multibody systems computes the derivatives of general cost functions that depend on the system solution with respect to parameters or initial conditions. This work develops adjoint sensitivity analysis for hybrid multibody dynamic systems. Hybrid systems are characterized by trajectories that are piecewise continuous in time, with finitely-many discontinuities being caused by events such as elastic/inelastic impacts or sudden changes in constraints. The corresponding direct and adjoint sensitivity variables are also discontinuous at the time of events. The framework discussed herein uses a jump sensitivity matrix to relate the jump conditions for the direct and adjoint sensitivities before and after the time event, and provides analytical jump equations for the adjoint variables. The theoretical framework for sensitivities for hybrid systems is validated on a five-bar mechanism with non-smooth contacts.
math.OC
sensitivity analysis of multibody systems computes the derivatives of general cost functions that depend on the system solution with respect to parameters or initial conditions this work develops adjoint sensitivity analysis for hybrid multibody dynamic systems hybrid systems are characterized by trajectories that are piecewise continuous in time with finitelymany discontinuities being caused by events such as elasticinelastic impacts or sudden changes in constraints the corresponding direct and adjoint sensitivity variables are also discontinuous at the time of events the framework discussed herein uses a jump sensitivity matrix to relate the jump conditions for the direct and adjoint sensitivities before and after the time event and provides analytical jump equations for the adjoint variables the theoretical framework for sensitivities for hybrid systems is validated on a fivebar mechanism with nonsmooth contacts
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1,802.07189
On configuration space, Born's rule and ontological states
It is shown how configuration space, possibly encompassing ordinary spatial structures, Born's rule, and ontological states aiming to address an underlying reality beyond Quantum Mechanics relate to each other in models of Hamiltonian cellular automata.
quant-ph physics.hist-ph
it is shown how configuration space possibly encompassing ordinary spatial structures borns rule and ontological states aiming to address an underlying reality beyond quantum mechanics relate to each other in models of hamiltonian cellular automata
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1,802.0719
Evolutionary games: natural selection of strategies
In this paper, I model and study the process of natural selection between all possible mixed strategies in classical two-player two-strategy games. I derive and solve an equation that is a natural generalization of the Taylor-Jonker replicator equation that describes dynamics of pure strategy frequencies. I then investigate the evolution of not only frequencies of pure strategies but also of total distribution of mixed strategies. I show that the process of natural selection of strategies for all games obeys the dynamical Principle of minimum of information gain.
q-bio.PE q-bio.QM
in this paper i model and study the process of natural selection between all possible mixed strategies in classical twoplayer twostrategy games i derive and solve an equation that is a natural generalization of the taylorjonker replicator equation that describes dynamics of pure strategy frequencies i then investigate the evolution of not only frequencies of pure strategies but also of total distribution of mixed strategies i show that the process of natural selection of strategies for all games obeys the dynamical principle of minimum of information gain
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1,802.07191
Neural Architecture Search with Bayesian Optimisation and Optimal Transport
Bayesian Optimisation (BO) refers to a class of methods for global optimisation of a function $f$ which is only accessible via point evaluations. It is typically used in settings where $f$ is expensive to evaluate. A common use case for BO in machine learning is model selection, where it is not possible to analytically model the generalisation performance of a statistical model, and we resort to noisy and expensive training and validation procedures to choose the best model. Conventional BO methods have focused on Euclidean and categorical domains, which, in the context of model selection, only permits tuning scalar hyper-parameters of machine learning algorithms. However, with the surge of interest in deep learning, there is an increasing demand to tune neural network \emph{architectures}. In this work, we develop NASBOT, a Gaussian process based BO framework for neural architecture search. To accomplish this, we develop a distance metric in the space of neural network architectures which can be computed efficiently via an optimal transport program. This distance might be of independent interest to the deep learning community as it may find applications outside of BO. We demonstrate that NASBOT outperforms other alternatives for architecture search in several cross validation based model selection tasks on multi-layer perceptrons and convolutional neural networks.
cs.LG stat.ML
bayesian optimisation bo refers to a class of methods for global optimisation of a function f which is only accessible via point evaluations it is typically used in settings where f is expensive to evaluate a common use case for bo in machine learning is model selection where it is not possible to analytically model the generalisation performance of a statistical model and we resort to noisy and expensive training and validation procedures to choose the best model conventional bo methods have focused on euclidean and categorical domains which in the context of model selection only permits tuning scalar hyperparameters of machine learning algorithms however with the surge of interest in deep learning there is an increasing demand to tune neural network empharchitectures in this work we develop nasbot a gaussian process based bo framework for neural architecture search to accomplish this we develop a distance metric in the space of neural network architectures which can be computed efficiently via an optimal transport program this distance might be of independent interest to the deep learning community as it may find applications outside of bo we demonstrate that nasbot outperforms other alternatives for architecture search in several cross validation based model selection tasks on multilayer perceptrons and convolutional neural networks
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1,802.07192
Robust Optimal Eco-driving Control with Uncertain Traffic Signal Timing
This paper proposes a robust optimal eco-driving control strategy considering multiple signalized intersections with uncertain traffic signal timing. A spatial vehicle velocity profile optimization formulation is developed to minimize the global fuel consumption, with driving time as one state variable. We introduce the concept of effective red-light duration (ERD), formulated as a random variable, to describe the feasible passing time through signalized intersections. A chance constraint is appended to the optimal control problem to incorporate robustness with respect to uncertain signal timing. The optimal eco-driving control problem is solved via dynamic programming (DP). Simulation results demonstrate that the optimal eco-driving can save fuel consumption by 50-57% while maintaining arrival time at the same level, compared with a modified intelligent driver model as the benchmark. The robust formulation significantly reduces traffic intersection violations, in the face of uncertain signal timing, with small sacrifice on fuel economy compared to a non-robust approach.
math.OC cs.SY
this paper proposes a robust optimal ecodriving control strategy considering multiple signalized intersections with uncertain traffic signal timing a spatial vehicle velocity profile optimization formulation is developed to minimize the global fuel consumption with driving time as one state variable we introduce the concept of effective redlight duration erd formulated as a random variable to describe the feasible passing time through signalized intersections a chance constraint is appended to the optimal control problem to incorporate robustness with respect to uncertain signal timing the optimal ecodriving control problem is solved via dynamic programming dp simulation results demonstrate that the optimal ecodriving can save fuel consumption by 5057 while maintaining arrival time at the same level compared with a modified intelligent driver model as the benchmark the robust formulation significantly reduces traffic intersection violations in the face of uncertain signal timing with small sacrifice on fuel economy compared to a nonrobust approach
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1,802.07193
Construction of Milnorian representations
We prove a partial converse to the main theorem of the author's previous paper "Proper affine actions: a sufficient criterion" (submitted; available at arXiv:1612.08942). More precisely, let $G$ be a semisimple real Lie group with a representation $\rho$ on a finite-dimensional real vector space $V$, that does not satisfy the criterion from the previous paper. Assuming that $\rho$ is irreducible and under some additional assumptions on $G$ and $\rho$, we then prove that there does not exist a group of affine transformations acting properly discontinuously on $V$ whose linear part is Zariski-dense in $\rho(G)$.
math.GR math.RT
we prove a partial converse to the main theorem of the authors previous paper proper affine actions a sufficient criterion submitted available at arxiv161208942 more precisely let g be a semisimple real lie group with a representation rho on a finitedimensional real vector space v that does not satisfy the criterion from the previous paper assuming that rho is irreducible and under some additional assumptions on g and rho we then prove that there does not exist a group of affine transformations acting properly discontinuously on v whose linear part is zariskidense in rhog
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1,802.07194
A Note on "Quantum Algorithm for Linear Systems of Equations"
Recently, an efficient quantum algorithm for linear systems of equations introduced by Harrow, Hassidim, and Lloyd, has received great concern from the academic community. However, the error and complexity analysis for this algorithm seems so complicated that it may not be applicable to other filter functions for other tasks. In this note, a concise proof is proposed. We hope that it may inspire some novel HHL-based algorithms that can compute $F(A)|b\rangle$ for any computable $F$.
quant-ph
recently an efficient quantum algorithm for linear systems of equations introduced by harrow hassidim and lloyd has received great concern from the academic community however the error and complexity analysis for this algorithm seems so complicated that it may not be applicable to other filter functions for other tasks in this note a concise proof is proposed we hope that it may inspire some novel hhlbased algorithms that can compute fabrangle for any computable f
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1,802.07195
Ultrafast magnetization dynamics in pure and doped Heusler and inverse Heusler alloys
By using a multiscale approach based on first-principles density functional theory combined with atomistic spin dynamics, we investigate the electronic structure and magnetization dynamics of an inverse Heusler and a Heusler compound and their alloys, i. e. Mn$_{2-x}Z_x$CoAl and Mn$_{2-x}Z_x$VAl, where $Z$ = Mo, W, Os and Ru, respectively. A signature of the ferrimagnetic ordering of Mn$_{2}$CoAl and Mn$_{2}$VAl Heusler alloys is reflected in the calculated Heisenberg exchange constants. They decay very rapidly with the interatomic distance and have short range, which is a consequence of the existence of the finite gap in the minority spin band. The calculated Gilbert damping parameter of both Mn$_2$CoAl and Mn$_2$VAl is high compared to other half-metals, but interestingly in the particular case of the inverse Mn$_{2}$CoAl alloys and due to the spin-gapless semiconducting property, the damping parameters decrease with the doping concentration in clear contradiction to the general trend. Atomistic spin dynamics simulations predict ultrafast magnetisation switching in Mn$_{2}$CoAl and Mn$_{2}$VAl under the influence of an external magnetic field, starting from a threshold field of $2\text{T}$. Our overall finding extends with Heusler and inverse Heusler alloys, the class of materials that exhibits laser induced magnetic switching.
cond-mat.mtrl-sci
by using a multiscale approach based on firstprinciples density functional theory combined with atomistic spin dynamics we investigate the electronic structure and magnetization dynamics of an inverse heusler and a heusler compound and their alloys i e mn_2xz_xcoal and mn_2xz_xval where z mo w os and ru respectively a signature of the ferrimagnetic ordering of mn_2coal and mn_2val heusler alloys is reflected in the calculated heisenberg exchange constants they decay very rapidly with the interatomic distance and have short range which is a consequence of the existence of the finite gap in the minority spin band the calculated gilbert damping parameter of both mn_2coal and mn_2val is high compared to other halfmetals but interestingly in the particular case of the inverse mn_2coal alloys and due to the spingapless semiconducting property the damping parameters decrease with the doping concentration in clear contradiction to the general trend atomistic spin dynamics simulations predict ultrafast magnetisation switching in mn_2coal and mn_2val under the influence of an external magnetic field starting from a threshold field of 2textt our overall finding extends with heusler and inverse heusler alloys the class of materials that exhibits laser induced magnetic switching
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1,802.07196
On Davenport constant of finite abelian groups
$G$ be an additive finite abelian group. The Davenport constant $\mathsf D(G)$ is the smallest integer $t$ such that every sequence (multiset) $S$ over $G$ of length $|S|\ge t$ has a non-empty zero-sum subsequence. Recently, B. Girard proved that for every fixed integer $r > 1$ the Davenport constant $\mathsf D(C_n^r)$ is asymptotic to $rn$ when $n$ tends to infinity. In this paper, for every fixed positive integer $r$, we prove that $$\mathsf D(C_n^r)=rn+O(\frac{n}{\ln n}).$$ This is an explicit version of the above result of B. Girard. Furthermore, we can get better estimates of the error term for some $n$ of special types. Finally, we get an asymptotic result for some finite abelian groups of special types. Our proof combines a classical argument in the zero-sum theory together with some basic tools and results from analytic number theory.
math.CO
g be an additive finite abelian group the davenport constant mathsf dg is the smallest integer t such that every sequence multiset s over g of length sge t has a nonempty zerosum subsequence recently b girard proved that for every fixed integer r 1 the davenport constant mathsf dc_nr is asymptotic to rn when n tends to infinity in this paper for every fixed positive integer r we prove that mathsf dc_nrrnofracnln n this is an explicit version of the above result of b girard furthermore we can get better estimates of the error term for some n of special types finally we get an asymptotic result for some finite abelian groups of special types our proof combines a classical argument in the zerosum theory together with some basic tools and results from analytic number theory
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1,802.07197
Topological nature of spinons and holons: Elementary excitations from matrix product states with conserved symmetries
We develop variational matrix product state (MPS) methods with symmetries to determine dispersion relations of one dimensional quantum lattices as a function of momentum and preset quantum number. We test our methods on the XXZ spin chain, the Hubbard model and a non-integrable extended Hubbard model, and determine the excitation spectra with a precision similar to the one of the ground state. The formulation in terms of quantum numbers makes the topological nature of spinons and holons very explicit. In addition, the method also enables an easy and efficient direct calculation of the necessary magnetic field or chemical potential required for a certain ground state magnetization or particle density.
cond-mat.str-el quant-ph
we develop variational matrix product state mps methods with symmetries to determine dispersion relations of one dimensional quantum lattices as a function of momentum and preset quantum number we test our methods on the xxz spin chain the hubbard model and a nonintegrable extended hubbard model and determine the excitation spectra with a precision similar to the one of the ground state the formulation in terms of quantum numbers makes the topological nature of spinons and holons very explicit in addition the method also enables an easy and efficient direct calculation of the necessary magnetic field or chemical potential required for a certain ground state magnetization or particle density
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1,802.07198
DarkSide-50 532-day Dark Matter Search with Low-Radioactivity Argon
The DarkSide-50 direct-detection dark matter experiment is a dual-phase argon time projection chamber operating at Laboratori Nazionali del Gran Sasso. This paper reports on the blind analysis of a (16,660+-270) kg d exposure using a target of low-radioactivity argon extracted from underground sources. We find no events in the dark matter selection box and set a 90% C.L. upper limit on the dark matter-nucleon spin-independent cross section of 1.14E-44 cm^2 (3.78E-44 cm^2, 3.43E-43 cm^2) for a WIMP mass of 100 GeV/c^2 (1 TeV/c^2, 10 TeV/c^2).
astro-ph.CO astro-ph.IM
the darkside50 directdetection dark matter experiment is a dualphase argon time projection chamber operating at laboratori nazionali del gran sasso this paper reports on the blind analysis of a 16660270 kg d exposure using a target of lowradioactivity argon extracted from underground sources we find no events in the dark matter selection box and set a 90 cl upper limit on the dark matternucleon spinindependent cross section of 114e44 cm2 378e44 cm2 343e43 cm2 for a wimp mass of 100 gevc2 1 tevc2 10 tevc2
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1,802.07199
A Parametric MPC Approach to Balancing the Cost of Abstraction for Differential-Drive Mobile Robots
When designing control strategies for differential-drive mobile robots, one standard tool is the consideration of a point at a fixed distance along a line orthogonal to the wheel axis instead of the full pose of the vehicle. This abstraction supports replacing the non-holonomic, three-state unicycle model with a much simpler two-state single-integrator model (i.e., a velocity-controlled point). Yet this transformation comes at a performance cost, through the robot's precision and maneuverability. This work contains derivations for expressions of these precision and maneuverability costs in terms of the transformation's parameters. Furthermore, these costs show that only selecting the parameter once over the course of an application may cause an undue loss of precision. Model Predictive Control (MPC) represents one such method to ameliorate this condition. However, MPC typically realizes a control signal, rather than a parameter, so this work also proposes a Parametric Model Predictive Control (PMPC) method for parameter and sampling horizon optimization. Experimental results are presented that demonstrate the effects of the parameterization on the deployment of algorithms developed for the single-integrator model on actual differential-drive mobile robots.
cs.RO cs.SY
when designing control strategies for differentialdrive mobile robots one standard tool is the consideration of a point at a fixed distance along a line orthogonal to the wheel axis instead of the full pose of the vehicle this abstraction supports replacing the nonholonomic threestate unicycle model with a much simpler twostate singleintegrator model ie a velocitycontrolled point yet this transformation comes at a performance cost through the robots precision and maneuverability this work contains derivations for expressions of these precision and maneuverability costs in terms of the transformations parameters furthermore these costs show that only selecting the parameter once over the course of an application may cause an undue loss of precision model predictive control mpc represents one such method to ameliorate this condition however mpc typically realizes a control signal rather than a parameter so this work also proposes a parametric model predictive control pmpc method for parameter and sampling horizon optimization experimental results are presented that demonstrate the effects of the parameterization on the deployment of algorithms developed for the singleintegrator model on actual differentialdrive mobile robots
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1,802.072
Asymptotics of Hitchin's metric on the Hitchin section
We consider Hitchin's hyperk\"ahler metric $g$ on the moduli space $\mathcal{M}$ of degree zero $\mathrm{SL}(2)$-Higgs bundles over a compact Riemann surface. It has been conjectured that, when one goes to infinity along a generic ray in $\mathcal{M}$, $g$ converges to an explicit "semiflat" metric $g^{\mathrm{sf}}$, with an exponential rate of convergence. We show that this is indeed the case for the restriction of $g$ to the tangent bundle of the Hitchin section $\mathcal{B} \subset \mathcal{M}$.
math.DG
we consider hitchins hyperkahler metric g on the moduli space mathcalm of degree zero mathrmsl2higgs bundles over a compact riemann surface it has been conjectured that when one goes to infinity along a generic ray in mathcalm g converges to an explicit semiflat metric gmathrmsf with an exponential rate of convergence we show that this is indeed the case for the restriction of g to the tangent bundle of the hitchin section mathcalb subset mathcalm
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1,802.07201
Inference of gene loss rates after whole genome duplications at early vertebrates through ancient genome reconstructions
The famous 2R hypothesis was first proposed by Susumu Ohno in 1970. It states that the two whole genome duplications had shaped the genome of early vertebrates. The most convincing evidence for 2R hypothesis comes from the 4:1 ratio chromosomal regions that have preserved both gene content and order in vertebrates compared with closely related. However, due to the shortage of such strict evidence, the 2R hypothesis is still under debates. Here, we present a combined perspective of phylogenetic and genomic homology to revisit the hypothesis of 2R whole genome duplications. Ancestral vertebrate genomes as well as ancient duplication events were created from 17 extant vertebrate species. Extant descendants from the duplication events at early vertebrates were extracted and reorganized to partial genomes. We then examined the gene order based synteny, and projected back to phylogenetic gene trees for examination of synteny evidence of the reconstructed early vertebrate genes. We identified 7877 ancestral genes that were created from 3026 duplication events at early vertebrates, and more than 50% of the duplication events show synteny evidence. Thus, our reconstructions provide very strong evidence for the 2R hypothesis. We also reconstructed the genome of early vertebrates, and built a model of the gene gains and losses in early vertebrates. We estimated that there were about 12,000 genes in early vertebrates before 2R, and the probability of a random gene get lost after the first round of whole genome duplication is around 0.45, and the probability of a random gene get lost after the second round of whole genome duplication is around 0.55. This research provides convincing evidence for the 2R hypothesis, and may provide further insights in vertebral evolution. Data availability: https://github.com/haimingt/Ohnologs-and-2R-WGD
q-bio.PE q-bio.GN
the famous 2r hypothesis was first proposed by susumu ohno in 1970 it states that the two whole genome duplications had shaped the genome of early vertebrates the most convincing evidence for 2r hypothesis comes from the 41 ratio chromosomal regions that have preserved both gene content and order in vertebrates compared with closely related however due to the shortage of such strict evidence the 2r hypothesis is still under debates here we present a combined perspective of phylogenetic and genomic homology to revisit the hypothesis of 2r whole genome duplications ancestral vertebrate genomes as well as ancient duplication events were created from 17 extant vertebrate species extant descendants from the duplication events at early vertebrates were extracted and reorganized to partial genomes we then examined the gene order based synteny and projected back to phylogenetic gene trees for examination of synteny evidence of the reconstructed early vertebrate genes we identified 7877 ancestral genes that were created from 3026 duplication events at early vertebrates and more than 50 of the duplication events show synteny evidence thus our reconstructions provide very strong evidence for the 2r hypothesis we also reconstructed the genome of early vertebrates and built a model of the gene gains and losses in early vertebrates we estimated that there were about 12000 genes in early vertebrates before 2r and the probability of a random gene get lost after the first round of whole genome duplication is around 045 and the probability of a random gene get lost after the second round of whole genome duplication is around 055 this research provides convincing evidence for the 2r hypothesis and may provide further insights in vertebral evolution data availability httpsgithubcomhaimingtohnologsand2rwgd
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1,802.07202
Regularity of bicyclic Graphs and their powers
Let $I(G)$ be the edge ideal of a bicyclic graph. In this paper, we characterize the Castelnuovo-Mumford regularity of $I(G)$ in terms of the induced matching number of $G$. For the base case of this family of graphs, i.e. dumbbell graph, we explicitly compute the induced matching number. Moreover, we prove that $ \operatorname{reg}(I(G)^q)=2q+\operatorname{reg}(I(G))-2$, for all $ q\geq 1 $, when $ G $ is a dumbbell graph with a connecting path having no more than two vertices.
math.AC
let ig be the edge ideal of a bicyclic graph in this paper we characterize the castelnuovomumford regularity of ig in terms of the induced matching number of g for the base case of this family of graphs ie dumbbell graph we explicitly compute the induced matching number moreover we prove that operatornameregigq2qoperatornameregig2 for all qgeq 1 when g is a dumbbell graph with a connecting path having no more than two vertices
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1,802.07203
Endomorphisms of Koszul complexes: formality and application to deformation theory
We study the differential graded Lie algebra of endomorphisms of the Koszul resolution of a regular sequence on a unitary commutative $K$-algebra $R$ and we prove that it is homotopy abelian over $K$, while it is generally not formal over $R$. We apply this result to prove an annihilation theorem for obstructions of (derived) deformations of locally complete intersection ideal sheaves on projective schemes.
math.AG math.QA
we study the differential graded lie algebra of endomorphisms of the koszul resolution of a regular sequence on a unitary commutative kalgebra r and we prove that it is homotopy abelian over k while it is generally not formal over r we apply this result to prove an annihilation theorem for obstructions of derived deformations of locally complete intersection ideal sheaves on projective schemes
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1,802.07204
Automation of gene function prediction through modeling human curators' decisions in GO phylogenetic annotation project
The Gene Ontology Consortium launched the GO-PAINT project (Phylogenetic Annotation and INference Tool) 9 years ago and is currently being used in the GO Reference Genome Annotation Project to support inference of GO function terms (molecular function, cellular component and biological process) by homology. PAINT uses a phylogenetic model to infer gene function by homology, a process that requires manual curation of experienced biocurators. Tremendous amount of time and efforts have been spent on the GO-PAINT project yielding more than 4000 fully annotated phylogenetic families with more than 170,000 annotations. These preliminary data have thus enabled potential algorithmic representation and automatic solvation of the additional 9000 unannoated phylogenetic families. Here we present an automated pipeline for phylogenetic annotation and inference, which simulates the standard annotation procedures of curators and models the curators' decisions during the manual curation process. The pipeline has been built into the newest version of PAINT software available at http://www.pantherdb.org/downloads/index.jsp. The standalone automation pipeline and datasets are available at https://github.com/haimingt/GO-PAINT-automation
q-bio.QM q-bio.GN
the gene ontology consortium launched the gopaint project phylogenetic annotation and inference tool 9 years ago and is currently being used in the go reference genome annotation project to support inference of go function terms molecular function cellular component and biological process by homology paint uses a phylogenetic model to infer gene function by homology a process that requires manual curation of experienced biocurators tremendous amount of time and efforts have been spent on the gopaint project yielding more than 4000 fully annotated phylogenetic families with more than 170000 annotations these preliminary data have thus enabled potential algorithmic representation and automatic solvation of the additional 9000 unannoated phylogenetic families here we present an automated pipeline for phylogenetic annotation and inference which simulates the standard annotation procedures of curators and models the curators decisions during the manual curation process the pipeline has been built into the newest version of paint software available at httpwwwpantherdborgdownloadsindexjsp the standalone automation pipeline and datasets are available at httpsgithubcomhaimingtgopaintautomation
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1,802.07205
Information gain and loss for a quantum Maxwell's demon
We use continuous weak measurements of a driven superconducting qubit to experimentally study the information dynamics of a quantum Maxwell's demon. We show how information gained by a demon who can track single quantum trajectories of the qubit can be converted into work using quantum coherent feedback. We verify the validity of a quantum fluctuation theorem with feedback by utilizing information obtained along single trajectories. We demonstrate, in particular, that quantum backaction can lead to a loss of information in imperfect measurements. We furthermore probe the transition between information gain and loss by varying the initial purity of the qubit.
quant-ph cond-mat.mes-hall cond-mat.stat-mech
we use continuous weak measurements of a driven superconducting qubit to experimentally study the information dynamics of a quantum maxwells demon we show how information gained by a demon who can track single quantum trajectories of the qubit can be converted into work using quantum coherent feedback we verify the validity of a quantum fluctuation theorem with feedback by utilizing information obtained along single trajectories we demonstrate in particular that quantum backaction can lead to a loss of information in imperfect measurements we furthermore probe the transition between information gain and loss by varying the initial purity of the qubit
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1,802.07206
The Fifth Force in the Local Cosmic Web
Extensions of the standard models of particle physics and cosmology often lead to long-range fifth forces with properties dependent on gravitational environment. Fifth forces on astrophysical scales are best studied in the cosmic web where perturbation theory breaks down. We present constraints on chameleon- and symmetron-screened fifth forces with Yukawa coupling and megaparsec range -- as well as unscreened fifth forces with differential coupling to galactic mass components -- by searching for the displacements they predict between galaxies' stars and gas. Taking data from the Alfalfa HI survey, identifying galaxies' gravitational environments with the maps of Desmond et al. (2018a) and forward-modelling with a Bayesian likelihood framework, we set upper bounds on fifth-force strength relative to Newtonian gravity from $\Delta G/G_N < \text{few} \: \times 10^{-4}$ for range $\lambda_C = 50$ Mpc, to $\Delta G/G_N \lesssim 0.1$ for $\lambda_C = 500$ kpc. In $f(R)$ gravity this requires $f_{R0} < \text{few} \: \times \: 10^{-8}$. The analogous bounds without screening are $\Delta G/G_N < \text{few} \: \times 10^{-4}$ and $\Delta G/G_N < \text{few} \times 10^{-3}$. These are the tightest and among the only fifth-force constraints on galaxy scales. We show how our results may be strengthened with future survey data and identify the key features of an observational programme for furthering fifth-force tests beyond the Solar System.
astro-ph.CO astro-ph.GA gr-qc
extensions of the standard models of particle physics and cosmology often lead to longrange fifth forces with properties dependent on gravitational environment fifth forces on astrophysical scales are best studied in the cosmic web where perturbation theory breaks down we present constraints on chameleon and symmetronscreened fifth forces with yukawa coupling and megaparsec range as well as unscreened fifth forces with differential coupling to galactic mass components by searching for the displacements they predict between galaxies stars and gas taking data from the alfalfa hi survey identifying galaxies gravitational environments with the maps of desmond et al 2018a and forwardmodelling with a bayesian likelihood framework we set upper bounds on fifthforce strength relative to newtonian gravity from delta gg_n textfew times 104 for range lambda_c 50 mpc to delta gg_n lesssim 01 for lambda_c 500 kpc in fr gravity this requires f_r0 textfew times 108 the analogous bounds without screening are delta gg_n textfew times 104 and delta gg_n textfew times 103 these are the tightest and among the only fifthforce constraints on galaxy scales we show how our results may be strengthened with future survey data and identify the key features of an observational programme for furthering fifthforce tests beyond the solar system
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1,802.07207
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning
Clinical prognostic models derived from largescale healthcare data can inform critical diagnostic and therapeutic decisions. To enable off-theshelf usage of machine learning (ML) in prognostic research, we developed AUTOPROGNOSIS: a system for automating the design of predictive modeling pipelines tailored for clinical prognosis. AUTOPROGNOSIS optimizes ensembles of pipeline configurations efficiently using a novel batched Bayesian optimization (BO) algorithm that learns a low-dimensional decomposition of the pipelines high-dimensional hyperparameter space in concurrence with the BO procedure. This is achieved by modeling the pipelines performances as a black-box function with a Gaussian process prior, and modeling the similarities between the pipelines baseline algorithms via a sparse additive kernel with a Dirichlet prior. Meta-learning is used to warmstart BO with external data from similar patient cohorts by calibrating the priors using an algorithm that mimics the empirical Bayes method. The system automatically explains its predictions by presenting the clinicians with logical association rules that link patients features to predicted risk strata. We demonstrate the utility of AUTOPROGNOSIS using 10 major patient cohorts representing various aspects of cardiovascular patient care.
cs.LG stat.ML
clinical prognostic models derived from largescale healthcare data can inform critical diagnostic and therapeutic decisions to enable offtheshelf usage of machine learning ml in prognostic research we developed autoprognosis a system for automating the design of predictive modeling pipelines tailored for clinical prognosis autoprognosis optimizes ensembles of pipeline configurations efficiently using a novel batched bayesian optimization bo algorithm that learns a lowdimensional decomposition of the pipelines highdimensional hyperparameter space in concurrence with the bo procedure this is achieved by modeling the pipelines performances as a blackbox function with a gaussian process prior and modeling the similarities between the pipelines baseline algorithms via a sparse additive kernel with a dirichlet prior metalearning is used to warmstart bo with external data from similar patient cohorts by calibrating the priors using an algorithm that mimics the empirical bayes method the system automatically explains its predictions by presenting the clinicians with logical association rules that link patients features to predicted risk strata we demonstrate the utility of autoprognosis using 10 major patient cohorts representing various aspects of cardiovascular patient care
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1,802.07208
Experimental single-photon pulse characterization by electro-optic shearing interferometry
The ability to characterize the complete quantum state of light is essential for both fundamental and applied science. For single photons the quantum state is provided by the mode that it occupies. The spectral temporal mode structure of light has recently emerged as an essential means for quantum information science. Here we experimentally demonstrate a self-referencing technique to completely determine the pulse-mode structure of single photons by means of spectral shearing interferometry. We detail the calibration and resolution of the measurement and discuss challenges and critical requirements for future advances of this method.
physics.optics quant-ph
the ability to characterize the complete quantum state of light is essential for both fundamental and applied science for single photons the quantum state is provided by the mode that it occupies the spectral temporal mode structure of light has recently emerged as an essential means for quantum information science here we experimentally demonstrate a selfreferencing technique to completely determine the pulsemode structure of single photons by means of spectral shearing interferometry we detail the calibration and resolution of the measurement and discuss challenges and critical requirements for future advances of this method
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1,802.07209
Distributed Symmetry-Breaking Algorithms for Congested Cliques
The {Congested Clique} is a distributed-computing model for single-hop networks with restricted bandwidth that has been very intensively studied recently. It models a network by an $n$-vertex graph in which any pair of vertices can communicate one with another by transmitting $O(\log n )$ bits in each round. Various problems have been studied in this setting, but for some of them the best-known results are those for general networks. In this paper we devise significantly improved algorithms for various symmetry-breaking problems, such as forests-decompositions, vertex-colorings, and maximal independent set. We analyze the running time of our algorithms as a function of the arboricity $a$ of a clique subgraph that is given as input. Our algorithms are especially efficient in Trees, planar graphs, graphs with constant genus, and many other graphs that have bounded arboricity, but unbounded size. We obtain $O(a)$-forest-decomposition algorithm with $O(\log a)$ time that improves the previously-known $O(\log n)$ time, $O(a^{2 + \epsilon})$-coloring in $O(\log^* n)$ time that improves upon an $O(\log n)$-time algorithm, $O(a)$-coloring in $O(a^{\epsilon})$-time that improves upon several previous algorithms, and a maximal independent set algorithm with $O(\sqrt a)$ time that improves at least quadratically upon the state-of-the-art for small and moderate values of $a$. Those results are achieved using several techniques. First, we produce a forest decomposition with a helpful structure called {$H$-partition} within $O(\log a)$ rounds. In general graphs this structure requires $\Theta(\log n)$ time, but in Congested Cliques we are able to compute it faster. We employ this structure in conjunction with partitioning techniques that allow us to solve various symmetry-breaking problems efficiently.
cs.DC cs.DS
the congested clique is a distributedcomputing model for singlehop networks with restricted bandwidth that has been very intensively studied recently it models a network by an nvertex graph in which any pair of vertices can communicate one with another by transmitting olog n bits in each round various problems have been studied in this setting but for some of them the bestknown results are those for general networks in this paper we devise significantly improved algorithms for various symmetrybreaking problems such as forestsdecompositions vertexcolorings and maximal independent set we analyze the running time of our algorithms as a function of the arboricity a of a clique subgraph that is given as input our algorithms are especially efficient in trees planar graphs graphs with constant genus and many other graphs that have bounded arboricity but unbounded size we obtain oaforestdecomposition algorithm with olog a time that improves the previouslyknown olog n time oa2 epsiloncoloring in olog n time that improves upon an olog ntime algorithm oacoloring in oaepsilontime that improves upon several previous algorithms and a maximal independent set algorithm with osqrt a time that improves at least quadratically upon the stateoftheart for small and moderate values of a those results are achieved using several techniques first we produce a forest decomposition with a helpful structure called hpartition within olog a rounds in general graphs this structure requires thetalog n time but in congested cliques we are able to compute it faster we employ this structure in conjunction with partitioning techniques that allow us to solve various symmetrybreaking problems efficiently
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1,802.0721
Real-Time Dense Stereo Matching With ELAS on FPGA Accelerated Embedded Devices
For many applications in low-power real-time robotics, stereo cameras are the sensors of choice for depth perception as they are typically cheaper and more versatile than their active counterparts. Their biggest drawback, however, is that they do not directly sense depth maps; instead, these must be estimated through data-intensive processes. Therefore, appropriate algorithm selection plays an important role in achieving the desired performance characteristics. Motivated by applications in space and mobile robotics, we implement and evaluate a FPGA-accelerated adaptation of the ELAS algorithm. Despite offering one of the best trade-offs between efficiency and accuracy, ELAS has only been shown to run at 1.5-3 fps on a high-end CPU. Our system preserves all intriguing properties of the original algorithm, such as the slanted plane priors, but can achieve a frame rate of 47fps whilst consuming under 4W of power. Unlike previous FPGA based designs, we take advantage of both components on the CPU/FPGA System-on-Chip to showcase the strategy necessary to accelerate more complex and computationally diverse algorithms for such low power, real-time systems.
cs.CV cs.RO
for many applications in lowpower realtime robotics stereo cameras are the sensors of choice for depth perception as they are typically cheaper and more versatile than their active counterparts their biggest drawback however is that they do not directly sense depth maps instead these must be estimated through dataintensive processes therefore appropriate algorithm selection plays an important role in achieving the desired performance characteristics motivated by applications in space and mobile robotics we implement and evaluate a fpgaaccelerated adaptation of the elas algorithm despite offering one of the best tradeoffs between efficiency and accuracy elas has only been shown to run at 153 fps on a highend cpu our system preserves all intriguing properties of the original algorithm such as the slanted plane priors but can achieve a frame rate of 47fps whilst consuming under 4w of power unlike previous fpga based designs we take advantage of both components on the cpufpga systemonchip to showcase the strategy necessary to accelerate more complex and computationally diverse algorithms for such low power realtime systems
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1,802.07211
An algorithm for determining the rotation count of pulsars
We present here a simple, systematic method for determining the correct global rotation count of a radio pulsar; an essential step for the derivation of an accurate phase-coherent ephemeris. We then build on this method by developing a new algorithm for determining the global rotational count for pulsars with sparse timing data sets. This makes it possible to obtain phase-coherent ephemerides for pulsars for which this has been impossible until now. As an example, we do this for PSR J0024-7205aa, an extremely faint MSP recently discovered in the globular cluster 47 Tucanae. This algorithm has the potential to significantly reduce the number of observations and the amount of telescope time needed to follow up on new pulsar discoveries.
astro-ph.IM astro-ph.HE
we present here a simple systematic method for determining the correct global rotation count of a radio pulsar an essential step for the derivation of an accurate phasecoherent ephemeris we then build on this method by developing a new algorithm for determining the global rotational count for pulsars with sparse timing data sets this makes it possible to obtain phasecoherent ephemerides for pulsars for which this has been impossible until now as an example we do this for psr j00247205aa an extremely faint msp recently discovered in the globular cluster 47 tucanae this algorithm has the potential to significantly reduce the number of observations and the amount of telescope time needed to follow up on new pulsar discoveries
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1,802.07212
Acoustic microstreaming near a plane wall due to a pulsating free/coated bubble: Nyborg result revisited and vortices
Acoustic microstreaming due to an oscillating microbubble is analytically investigated to obtain the circular streaming motion adjacent to a nearby wall. Classical theory due to Nyborg is carefully derived in the radial coordinates. The theory is used to obtain the flow field and the vortical motion caused by the microbubble motion. The length of the vertices are decreasing when the microbubble is excited at distances close to the rigid wall, while the maximum shear stress is increasing.
physics.flu-dyn
acoustic microstreaming due to an oscillating microbubble is analytically investigated to obtain the circular streaming motion adjacent to a nearby wall classical theory due to nyborg is carefully derived in the radial coordinates the theory is used to obtain the flow field and the vortical motion caused by the microbubble motion the length of the vertices are decreasing when the microbubble is excited at distances close to the rigid wall while the maximum shear stress is increasing
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1,802.07213
Heegaard splittings of graph manifolds
In this paper we give a method to construct Heegaard splittings of oriented graph manifolds with orientable bases. A graph manifold is a closed $3$-manifold admitting only Seifert-fibered pieces in its Jaco-Shalen decomposition; for technical reasons, we restrict our attention to the fully oriented case, i.e. both the pieces and the bases are oriented.
math.GT
in this paper we give a method to construct heegaard splittings of oriented graph manifolds with orientable bases a graph manifold is a closed 3manifold admitting only seifertfibered pieces in its jacoshalen decomposition for technical reasons we restrict our attention to the fully oriented case ie both the pieces and the bases are oriented
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1,802.07214
Inverse Design of Discrete Mechanical Metamaterials
Mechanical and phononic metamaterials exhibiting negative elastic moduli, gapped vibrational spectra, or topologically protected modes enable precise control of structural and acoustic functionalities. While much progress has been made in their experimental and theoretical characterization, the inverse design of mechanical metamaterials with arbitrarily programmable spectral properties and mode localization remains an unsolved problem. Here, we present a flexible computational inverse-design framework that allows the efficient tuning of one or more gaps at nearly arbitrary positions in the spectrum of discrete phononic metamaterial structures. The underlying algorithm optimizes the linear response of elastic networks directly, is applicable to ordered and disordered structures, scales efficiently in 2D and 3D, and can be combined with a wide range of numerical optimization schemes. We illustrate the broad practical potential of this approach by designing mechanical bandgap switches that open and close pre-programmed spectral gaps in response to an externally applied stimulus such as shear or compression. We further show that the designed structures can host topologically protected edge modes, and validate the numerical predictions through explicit 3D finite element simulations of continuum elastica with experimentally relevant material parameters. Generally, this network-based inverse design paradigm offers a direct pathway towards manufacturing phononic metamaterials, DNA origami structures and topolectric circuits that can realize a wide range of static and dynamic target functionalities.
cond-mat.mtrl-sci cond-mat.soft
mechanical and phononic metamaterials exhibiting negative elastic moduli gapped vibrational spectra or topologically protected modes enable precise control of structural and acoustic functionalities while much progress has been made in their experimental and theoretical characterization the inverse design of mechanical metamaterials with arbitrarily programmable spectral properties and mode localization remains an unsolved problem here we present a flexible computational inversedesign framework that allows the efficient tuning of one or more gaps at nearly arbitrary positions in the spectrum of discrete phononic metamaterial structures the underlying algorithm optimizes the linear response of elastic networks directly is applicable to ordered and disordered structures scales efficiently in 2d and 3d and can be combined with a wide range of numerical optimization schemes we illustrate the broad practical potential of this approach by designing mechanical bandgap switches that open and close preprogrammed spectral gaps in response to an externally applied stimulus such as shear or compression we further show that the designed structures can host topologically protected edge modes and validate the numerical predictions through explicit 3d finite element simulations of continuum elastica with experimentally relevant material parameters generally this networkbased inverse design paradigm offers a direct pathway towards manufacturing phononic metamaterials dna origami structures and topolectric circuits that can realize a wide range of static and dynamic target functionalities
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1,802.07215
Preparation contextuality as an essential feature underlying quantum communication advantage
The study of ontology (hidden variables) provides for a vital ground on which significant non-classical features of quantum theory are revealed. One such non-classical ontic-feature is preparation contextuality (PC) and advantage in oblivious communication tasks is one of its operational signatures. This article primarily pursues the ontic-feature underlying quantum advantage in communication complexity (CC). We construct oblivious communication tasks tailored to given CC problems. We upper-bound the classical success probability of these oblivious communication tasks, obtaining preparation non-contextual inequalities. We use the very states and measurements responsible for advantage in CC problems along with the orthogonal mixtures of these states to orchestrate an advantageous protocol for the associated oblivious communication tasks and the violation of the associated inequalities, thereby unveiling PC. To showcase the vitality of our results, we find a criterion for unbounded violation of these inequalities and demonstrate the same for two widely studied CC problems.
quant-ph
the study of ontology hidden variables provides for a vital ground on which significant nonclassical features of quantum theory are revealed one such nonclassical onticfeature is preparation contextuality pc and advantage in oblivious communication tasks is one of its operational signatures this article primarily pursues the onticfeature underlying quantum advantage in communication complexity cc we construct oblivious communication tasks tailored to given cc problems we upperbound the classical success probability of these oblivious communication tasks obtaining preparation noncontextual inequalities we use the very states and measurements responsible for advantage in cc problems along with the orthogonal mixtures of these states to orchestrate an advantageous protocol for the associated oblivious communication tasks and the violation of the associated inequalities thereby unveiling pc to showcase the vitality of our results we find a criterion for unbounded violation of these inequalities and demonstrate the same for two widely studied cc problems
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1,802.07216
Cosmic Visions Dark Energy: Small Projects Portfolio
Understanding cosmic acceleration is one of the key science drivers for astrophysics and high-energy physics in the coming decade (2014 P5 Report). With the Large Synoptic Survey Telescope (LSST) and the Dark Energy Spectroscopic Instrument (DESI) and other new facilities beginning operations soon, we are entering an exciting phase during which we expect an order of magnitude improvement in constraints on dark energy and the physics of the accelerating Universe. This is a key moment for a matching Small Projects portfolio that can (1) greatly enhance the science reach of these flagship projects, (2) have immediate scientific impact, and (3) lay the groundwork for the next stages of the Cosmic Frontier Dark Energy program. In this White Paper, we outline a balanced portfolio that can accomplish these goals through a combination of observational, experimental, and theory and simulation efforts.
astro-ph.CO
understanding cosmic acceleration is one of the key science drivers for astrophysics and highenergy physics in the coming decade 2014 p5 report with the large synoptic survey telescope lsst and the dark energy spectroscopic instrument desi and other new facilities beginning operations soon we are entering an exciting phase during which we expect an order of magnitude improvement in constraints on dark energy and the physics of the accelerating universe this is a key moment for a matching small projects portfolio that can 1 greatly enhance the science reach of these flagship projects 2 have immediate scientific impact and 3 lay the groundwork for the next stages of the cosmic frontier dark energy program in this white paper we outline a balanced portfolio that can accomplish these goals through a combination of observational experimental and theory and simulation efforts
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1,802.07217
Measuring frequency fluctuations in nonlinear nanomechanical resonators
Advances in nanomechanics within recent years have demonstrated an always expanding range of devices, from top-down structures to appealing bottom-up MoS$_2$ and graphene membranes, used for both sensing and component-oriented applications. One of the main concerns in all of these devices is frequency noise, which ultimately limits their applicability. This issue has attracted a lot of attention recently, and the origin of this noise remains elusive up to date. In this Letter we present a very simple technique to measure frequency noise in nonlinear mechanical devices, based on the presence of bistability. It is illustrated on silicon-nitride high-stress doubly-clamped beams, in a cryogenic environment. We report on the same $T/f$ dependence of the frequency noise power spectra as reported in the literature. But we also find unexpected {\it damping fluctuations}, amplified in the vicinity of the bifurcation points; this effect is clearly distinct from already reported nonlinear dephasing, and poses a fundamental limit on the measurement of bifurcation frequencies. The technique is further applied to the measurement of frequency noise as a function of mode number, within the same device. The relative frequency noise for the fundamental flexure $\delta f/f_0$ lies in the range $0.5 - 0.01~$ppm (consistent with literature for cryogenic MHz devices), and decreases with mode number in the range studied. The technique can be applied to {\it any types} of nano-mechanical structures, enabling progresses towards the understanding of intrinsic sources of noise in these devices.
cond-mat.mes-hall
advances in nanomechanics within recent years have demonstrated an always expanding range of devices from topdown structures to appealing bottomup mos_2 and graphene membranes used for both sensing and componentoriented applications one of the main concerns in all of these devices is frequency noise which ultimately limits their applicability this issue has attracted a lot of attention recently and the origin of this noise remains elusive up to date in this letter we present a very simple technique to measure frequency noise in nonlinear mechanical devices based on the presence of bistability it is illustrated on siliconnitride highstress doublyclamped beams in a cryogenic environment we report on the same tf dependence of the frequency noise power spectra as reported in the literature but we also find unexpected it damping fluctuations amplified in the vicinity of the bifurcation points this effect is clearly distinct from already reported nonlinear dephasing and poses a fundamental limit on the measurement of bifurcation frequencies the technique is further applied to the measurement of frequency noise as a function of mode number within the same device the relative frequency noise for the fundamental flexure delta ff_0 lies in the range 05 001ppm consistent with literature for cryogenic mhz devices and decreases with mode number in the range studied the technique can be applied to it any types of nanomechanical structures enabling progresses towards the understanding of intrinsic sources of noise in these devices
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1,802.07218
A 3D Game Theoretical Framework for the Evaluation of Unmanned Aircraft Systems Airspace Integration Concepts
Predicting the outcomes of integrating Unmanned Aerial Systems (UAS) into the National Airspace System (NAS) is a complex problem which is required to be addressed by simulation studies before allowing the routine access of UAS into the NAS. This paper focuses on providing a 3-dimensional (3D) simulation framework using a game theoretical methodology to evaluate integration concepts using scenarios where manned and unmanned air vehicles co-exist. In the proposed method, human pilot interactive decision making process is incorporated into airspace models which can fill the gap in the literature where the pilot behavior is generally assumed to be known a priori. The proposed human pilot behavior is modeled using dynamic level-k reasoning concept and approximate reinforcement learning. The level-k reasoning concept is a notion in game theory and is based on the assumption that humans have various levels of decision making. In the conventional "static" approach, each agent makes assumptions about his or her opponents and chooses his or her actions accordingly. On the other hand, in the dynamic level-k reasoning, agents can update their beliefs about their opponents and revise their level-k rule. In this study, Neural Fitted Q Iteration, which is an approximate reinforcement learning method, is used to model time-extended decisions of pilots with 3D maneuvers. An analysis of UAS integration is conducted using an example 3D scenario in the presence of manned aircraft and fully autonomous UAS equipped with sense and avoid algorithms.
cs.GT cs.RO
predicting the outcomes of integrating unmanned aerial systems uas into the national airspace system nas is a complex problem which is required to be addressed by simulation studies before allowing the routine access of uas into the nas this paper focuses on providing a 3dimensional 3d simulation framework using a game theoretical methodology to evaluate integration concepts using scenarios where manned and unmanned air vehicles coexist in the proposed method human pilot interactive decision making process is incorporated into airspace models which can fill the gap in the literature where the pilot behavior is generally assumed to be known a priori the proposed human pilot behavior is modeled using dynamic levelk reasoning concept and approximate reinforcement learning the levelk reasoning concept is a notion in game theory and is based on the assumption that humans have various levels of decision making in the conventional static approach each agent makes assumptions about his or her opponents and chooses his or her actions accordingly on the other hand in the dynamic levelk reasoning agents can update their beliefs about their opponents and revise their levelk rule in this study neural fitted q iteration which is an approximate reinforcement learning method is used to model timeextended decisions of pilots with 3d maneuvers an analysis of uas integration is conducted using an example 3d scenario in the presence of manned aircraft and fully autonomous uas equipped with sense and avoid algorithms
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1,802.07219
Leibniz algebras as non-associative algebras
In this paper we define the basic concepts for left or right Leibniz algebras and prove some of the main results. Our proofs are often variations of the known proofs and several results seem to be new.
math.RA
in this paper we define the basic concepts for left or right leibniz algebras and prove some of the main results our proofs are often variations of the known proofs and several results seem to be new
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1,802.0722
Thermoelectricity in correlated narrow-gap semiconductors
We review many-body effects, their microscopic origin, as well as their impact onto thermoelectricity in correlated narrow-gap semiconductors. Members of this class---such as FeSi and FeSb$_2$---display an unusual temperature dependence in various observables: insulating with large thermopowers at low temperatures, they turn bad metals at temperatures much smaller than the size of their gaps. This insulator-to-metal crossover is accompanied by spectral weight-transfers over large energies in the optical conductivity and by a gradual transition from activated to Curie-Weiss-like behaviour in the magnetic susceptibility. We show a retrospective of the understanding of these phenomena, discuss the relation to heavy-fermion Kondo insulators---such as Ce$_3$Bi$_4$Pt$_3$ for which we present new results---and propose a general classification of paramagnetic insulators. From the latter FeSi emerges as an orbital-selective Kondo insulator. Focussing on intermetallics such as silicides, antimonides, skutterudites, and Heusler compounds we showcase successes and challenges for the realistic simulation of transport properties in the presence of electronic correlations. Further, we advert to new avenues in which electronic correlations may contribute to the improvement of thermoelectric performance.
cond-mat.str-el cond-mat.mtrl-sci
we review manybody effects their microscopic origin as well as their impact onto thermoelectricity in correlated narrowgap semiconductors members of this classsuch as fesi and fesb_2display an unusual temperature dependence in various observables insulating with large thermopowers at low temperatures they turn bad metals at temperatures much smaller than the size of their gaps this insulatortometal crossover is accompanied by spectral weighttransfers over large energies in the optical conductivity and by a gradual transition from activated to curieweisslike behaviour in the magnetic susceptibility we show a retrospective of the understanding of these phenomena discuss the relation to heavyfermion kondo insulatorssuch as ce_3bi_4pt_3 for which we present new resultsand propose a general classification of paramagnetic insulators from the latter fesi emerges as an orbitalselective kondo insulator focussing on intermetallics such as silicides antimonides skutterudites and heusler compounds we showcase successes and challenges for the realistic simulation of transport properties in the presence of electronic correlations further we advert to new avenues in which electronic correlations may contribute to the improvement of thermoelectric performance
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1,802.07221
Geometric structures and representations of discrete groups
We describe recent links between two topics: geometric structures on manifolds in the sense of Ehresmann and Thurston, and dynamics "at infinity" for representations of discrete groups into Lie groups.
math.GT
we describe recent links between two topics geometric structures on manifolds in the sense of ehresmann and thurston and dynamics at infinity for representations of discrete groups into lie groups
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1,802.07222
007: Democratically Finding The Cause of Packet Drops
Network failures continue to plague datacenter operators as their symptoms may not have direct correlation with where or why they occur. We introduce 007, a lightweight, always-on diagnosis application that can find problematic links and also pinpoint problems for each TCP connection. 007 is completely contained within the end host. During its two month deployment in a tier-1 datacenter, it detected every problem found by previously deployed monitoring tools while also finding the sources of other problems previously undetected.
cs.NI
network failures continue to plague datacenter operators as their symptoms may not have direct correlation with where or why they occur we introduce 007 a lightweight alwayson diagnosis application that can find problematic links and also pinpoint problems for each tcp connection 007 is completely contained within the end host during its two month deployment in a tier1 datacenter it detected every problem found by previously deployed monitoring tools while also finding the sources of other problems previously undetected
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1,802.07223
Stable processes conditioned to avoid an interval
Conditioning Markov processes to avoid a domain is a classical problem that has been studied in many settings. Ingredients for standard arguments involve the leading order tail asymptotics of the distribution of the first hitting time of the domain of interest and its relation to an underlying harmonic function. In the present article we condition stable processes to avoid intervals. The required tail asymptotics in the stable setting for $\alpha\geq 1$ go back to classical work of Blumenthal et al. and Port from the 1960s. For $\alpha<1$, we appeal to recent results centred around the so-called deep factorisation of the stable process to compute hitting probabilities and, moreover, to identify the associated harmonic functions for all $\alpha\in (0,2)$. With these in hand, we thus prove that conditioning to avoid an interval is possible in the classical sense and that the resulting process is a Doob $h$-transform of the stable process killed on entering the aforesaid interval. Appealing to the representation of the conditioned process as a Doob $h$-transform, we verify that the conditioned process is transient.
math.PR
conditioning markov processes to avoid a domain is a classical problem that has been studied in many settings ingredients for standard arguments involve the leading order tail asymptotics of the distribution of the first hitting time of the domain of interest and its relation to an underlying harmonic function in the present article we condition stable processes to avoid intervals the required tail asymptotics in the stable setting for alphageq 1 go back to classical work of blumenthal et al and port from the 1960s for alpha1 we appeal to recent results centred around the socalled deep factorisation of the stable process to compute hitting probabilities and moreover to identify the associated harmonic functions for all alphain 02 with these in hand we thus prove that conditioning to avoid an interval is possible in the classical sense and that the resulting process is a doob htransform of the stable process killed on entering the aforesaid interval appealing to the representation of the conditioned process as a doob htransform we verify that the conditioned process is transient
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1,802.07224
Precision temperature sensing in the presence of magnetic field noise and vice-versa using nitrogen-vacancy centers in diamond
We demonstrate a technique for precision sensing of temperature or the magnetic field by simultaneously driving two hyperfine transitions involving distinct electronic states of the nitrogen-vacancy center in diamond. Frequency modulation of both driving fields is used with either the same or opposite phase, resulting in the immunity to fluctuations in either the magnetic field or the temperature, respectively. In this way, a sensitivity of 1.4 nT Hz$^{-1/2}$ or 430 $\mu$K Hz$^{-1/2}$ is demonstrated. The presented technique only requires a single frequency demodulator and enables the use of phase-sensitive camera imaging sensors. A simple extension of the method utilizing two demodulators allows for simultaneous, independent, and high-bandwidth monitoring of both the magnetic field and temperature.
cond-mat.mes-hall physics.ins-det quant-ph
we demonstrate a technique for precision sensing of temperature or the magnetic field by simultaneously driving two hyperfine transitions involving distinct electronic states of the nitrogenvacancy center in diamond frequency modulation of both driving fields is used with either the same or opposite phase resulting in the immunity to fluctuations in either the magnetic field or the temperature respectively in this way a sensitivity of 14 nt hz12 or 430 muk hz12 is demonstrated the presented technique only requires a single frequency demodulator and enables the use of phasesensitive camera imaging sensors a simple extension of the method utilizing two demodulators allows for simultaneous independent and highbandwidth monitoring of both the magnetic field and temperature
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1,802.07225
The logic of behavior of atoms
Understanding of the atomic structures and ways in which the atoms interacting is critical to the understanding of chemistry. In this paper applied the concepts of game theory in explaining reactions between elements of the periodic table. The findings in this study suggest that the coordination and anti coordination, also cooperation and non-cooperation between atoms and molecules lead to bonding formation according to the game theory. Therefore, the chemical behavior and physical treats of any chemical reaction can be predicted. Multiple examples of each batch of the chemical reactions is expressed to support the useability of our claims.
physics.atm-clus physics.chem-ph
understanding of the atomic structures and ways in which the atoms interacting is critical to the understanding of chemistry in this paper applied the concepts of game theory in explaining reactions between elements of the periodic table the findings in this study suggest that the coordination and anti coordination also cooperation and noncooperation between atoms and molecules lead to bonding formation according to the game theory therefore the chemical behavior and physical treats of any chemical reaction can be predicted multiple examples of each batch of the chemical reactions is expressed to support the useability of our claims
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1,802.07226
Implicit Argument Prediction with Event Knowledge
Implicit arguments are not syntactically connected to their predicates, and are therefore hard to extract. Previous work has used models with large numbers of features, evaluated on very small datasets. We propose to train models for implicit argument prediction on a simple cloze task, for which data can be generated automatically at scale. This allows us to use a neural model, which draws on narrative coherence and entity salience for predictions. We show that our model has superior performance on both synthetic and natural data.
cs.CL
implicit arguments are not syntactically connected to their predicates and are therefore hard to extract previous work has used models with large numbers of features evaluated on very small datasets we propose to train models for implicit argument prediction on a simple cloze task for which data can be generated automatically at scale this allows us to use a neural model which draws on narrative coherence and entity salience for predictions we show that our model has superior performance on both synthetic and natural data
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1,802.07227
The reduced ring order and lower semi-lattices
Every reduced ring $R$ has a natural partial order defined by $a\le b$ if $a^2=ab$; it generalizes the natural order on a boolean ring. The article examines when $R$ is a lower semi-lattice in this order with examples drawn from weakly Baer rings (pp-rings) and rings of continuous functions. Locally connected spaces and basically disconnected spaces give rings $C(X)$ which are such lower semi-lattices. Liftings of countable orthogonal (in this order) sets over surjective ring homomorphisms are studied.
math.RA
every reduced ring r has a natural partial order defined by ale b if a2ab it generalizes the natural order on a boolean ring the article examines when r is a lower semilattice in this order with examples drawn from weakly baer rings pprings and rings of continuous functions locally connected spaces and basically disconnected spaces give rings cx which are such lower semilattices liftings of countable orthogonal in this order sets over surjective ring homomorphisms are studied
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1,802.07228
The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation
This report surveys the landscape of potential security threats from malicious uses of AI, and proposes ways to better forecast, prevent, and mitigate these threats. After analyzing the ways in which AI may influence the threat landscape in the digital, physical, and political domains, we make four high-level recommendations for AI researchers and other stakeholders. We also suggest several promising areas for further research that could expand the portfolio of defenses, or make attacks less effective or harder to execute. Finally, we discuss, but do not conclusively resolve, the long-term equilibrium of attackers and defenders.
cs.AI cs.CR cs.CY
this report surveys the landscape of potential security threats from malicious uses of ai and proposes ways to better forecast prevent and mitigate these threats after analyzing the ways in which ai may influence the threat landscape in the digital physical and political domains we make four highlevel recommendations for ai researchers and other stakeholders we also suggest several promising areas for further research that could expand the portfolio of defenses or make attacks less effective or harder to execute finally we discuss but do not conclusively resolve the longterm equilibrium of attackers and defenders
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1,802.07229
Actively Avoiding Nonsense in Generative Models
A generative model may generate utter nonsense when it is fit to maximize the likelihood of observed data. This happens due to "model error," i.e., when the true data generating distribution does not fit within the class of generative models being learned. To address this, we propose a model of active distribution learning using a binary invalidity oracle that identifies some examples as clearly invalid, together with random positive examples sampled from the true distribution. The goal is to maximize the likelihood of the positive examples subject to the constraint of (almost) never generating examples labeled invalid by the oracle. Guarantees are agnostic compared to a class of probability distributions. We show that, while proper learning often requires exponentially many queries to the invalidity oracle, improper distribution learning can be done using polynomially many queries.
cs.LG cs.DS stat.ML
a generative model may generate utter nonsense when it is fit to maximize the likelihood of observed data this happens due to model error ie when the true data generating distribution does not fit within the class of generative models being learned to address this we propose a model of active distribution learning using a binary invalidity oracle that identifies some examples as clearly invalid together with random positive examples sampled from the true distribution the goal is to maximize the likelihood of the positive examples subject to the constraint of almost never generating examples labeled invalid by the oracle guarantees are agnostic compared to a class of probability distributions we show that while proper learning often requires exponentially many queries to the invalidity oracle improper distribution learning can be done using polynomially many queries
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1,802.0723
A Minimaxmax Problem for Improving the Torsional Stability of Rectangular Plates
We use a gap function in order to compare the torsional performances of different reinforced plates under the action of external forces. Then, we address a shape optimization problem, whose target is to minimize the torsional displacements of the plate: this leads us to set up a minimaxmax problem, which includes a new kind of worst-case optimization. Two kinds of reinforcements are considered: one aims at strengthening the plate, the other aims at weakening the action of the external forces. For both of them, we study the existence of optima within suitable classes of external forces and reinforcements. Our results are complemented with numerical experiments and with a number of open problems and conjectures.
math.AP math.CA math.OC
we use a gap function in order to compare the torsional performances of different reinforced plates under the action of external forces then we address a shape optimization problem whose target is to minimize the torsional displacements of the plate this leads us to set up a minimaxmax problem which includes a new kind of worstcase optimization two kinds of reinforcements are considered one aims at strengthening the plate the other aims at weakening the action of the external forces for both of them we study the existence of optima within suitable classes of external forces and reinforcements our results are complemented with numerical experiments and with a number of open problems and conjectures
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1,802.07231
Frictionless Authentication System: Security & Privacy Analysis and Potential Solutions
This paper proposes a frictionless authentication system, provides a comprehensive security analysis of and proposes potential solutions for this system. It first presents a system that allows users to authenticate to services in a frictionless manner, i.e., without the need to perform any particular authentication-related actions. Based on this system model, the paper analyses security problems and potential privacy threats imposed on users, leading to the specification of a set of security and privacy requirements. These requirements can be used as a guidance on designing secure and privacy-friendly frictionless authentication systems. The paper also sketches three potential solutions for such systems and highlights their advantages and disadvantages.
cs.CR
this paper proposes a frictionless authentication system provides a comprehensive security analysis of and proposes potential solutions for this system it first presents a system that allows users to authenticate to services in a frictionless manner ie without the need to perform any particular authenticationrelated actions based on this system model the paper analyses security problems and potential privacy threats imposed on users leading to the specification of a set of security and privacy requirements these requirements can be used as a guidance on designing secure and privacyfriendly frictionless authentication systems the paper also sketches three potential solutions for such systems and highlights their advantages and disadvantages
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1,802.07232
Observational constraints on the free parameters of an interacting Bose-Einstein gas as a dark-energy model
Dark energy is modelled by a Bose-Einstein gas of particles with an attractive interaction. It is coupled to cold dark matter, within a flat universe, for the late-expansion description, producing variations in particle-number densities. The model's parameters, and physical association, are: $\Omega_{G0}$, $\Omega_{m0}$, the dark-energy rest-mass energy density and the dark-matter term scaling as a mass term, respectively; $\Omega_{i0}$, the self-interaction intensity; $x$, the energy exchange rate. Energy conservation relates such parameters. The Hubble equation omits $\Omega_{G0}$, but also contains $h$, the present-day expansion rate of the flat Friedman--Lem\^aitre--Robertson--Walker metric, and $\Omega_{b0}$, the baryon energy density, used as a prior. This results in the four effective chosen parameters $\Omega_{b0}$, $h$, $\Omega_{m0}$, $\Omega_{i0}$, fit with the Hubble expansion rate $H(z)$, and data from its value today, near distance, and supernovas. We derive wide $1\sigma$ and $2\sigma$ likelihood regions compatible with definite positive total CDM and IBEG mass terms. Additionally, the best-fit value of parameter $x$ relieves the coincidence problem, and a second potential coincidence problem related to the choice of $\Omega_{G0}$.
astro-ph.CO
dark energy is modelled by a boseeinstein gas of particles with an attractive interaction it is coupled to cold dark matter within a flat universe for the lateexpansion description producing variations in particlenumber densities the models parameters and physical association are omega_g0 omega_m0 the darkenergy restmass energy density and the darkmatter term scaling as a mass term respectively omega_i0 the selfinteraction intensity x the energy exchange rate energy conservation relates such parameters the hubble equation omits omega_g0 but also contains h the presentday expansion rate of the flat friedmanlemaitrerobertsonwalker metric and omega_b0 the baryon energy density used as a prior this results in the four effective chosen parameters omega_b0 h omega_m0 omega_i0 fit with the hubble expansion rate hz and data from its value today near distance and supernovas we derive wide 1sigma and 2sigma likelihood regions compatible with definite positive total cdm and ibeg mass terms additionally the bestfit value of parameter x relieves the coincidence problem and a second potential coincidence problem related to the choice of omega_g0
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1,802.07233
Frictionless Authentication Systems: Emerging Trends, Research Challenges and Opportunities
Authentication and authorization are critical security layers to protect a wide range of online systems, services and content. However, the increased prevalence of wearable and mobile devices, the expectations of a frictionless experience and the diverse user environments will challenge the way users are authenticated. Consumers demand secure and privacy-aware access from any device, whenever and wherever they are, without any obstacles. This paper reviews emerging trends and challenges with frictionless authentication systems and identifies opportunities for further research related to the enrollment of users, the usability of authentication schemes, as well as security and privacy trade-offs of mobile and wearable continuous authentication systems.
cs.CR
authentication and authorization are critical security layers to protect a wide range of online systems services and content however the increased prevalence of wearable and mobile devices the expectations of a frictionless experience and the diverse user environments will challenge the way users are authenticated consumers demand secure and privacyaware access from any device whenever and wherever they are without any obstacles this paper reviews emerging trends and challenges with frictionless authentication systems and identifies opportunities for further research related to the enrollment of users the usability of authentication schemes as well as security and privacy tradeoffs of mobile and wearable continuous authentication systems
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1,802.07234
A support theorem for nested Hilbert schemes of planar curves
Consider a family of integral complex locally planar curves. We show that under some assumptions on the basis, the relative nested Hilbert scheme is smooth. In this case, the decomposition theorem of Beilinson, Bernstein and Deligne asserts that the pushforward of the constant sheaf on the relative nested Hilbert scheme splits as a direct sum of shifted semisimple perverse sheaves. We will show that no summand is supported in positive codimension.
math.AG
consider a family of integral complex locally planar curves we show that under some assumptions on the basis the relative nested hilbert scheme is smooth in this case the decomposition theorem of beilinson bernstein and deligne asserts that the pushforward of the constant sheaf on the relative nested hilbert scheme splits as a direct sum of shifted semisimple perverse sheaves we will show that no summand is supported in positive codimension
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1,802.07235
A note on a weakly singular elliptic equation from theory of elasticity
Qualitative properties of a second order elliptic equation from the anisotropic elasticity are investigated. Some explicit solutions for a disk are presented. Behaviour of these solutions in dependence of coefficients is investigated. The problem of presence of singularities of solutions at the origin of coordinates is discussed.
cond-mat.soft
qualitative properties of a second order elliptic equation from the anisotropic elasticity are investigated some explicit solutions for a disk are presented behaviour of these solutions in dependence of coefficients is investigated the problem of presence of singularities of solutions at the origin of coordinates is discussed
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1,802.07236
The Fourier transform on negatively curved harmonic manifolds
Let $X$ be a complete, simply connected harmonic manifold with sectional curvatures $K$ satisfying $K \leq -1$, and let $\partial X$ denote the boundary at infinity of $X$. Let $h > 0$ denote the mean curvature of horospheres in $X$, and let $\rho = h/2$. Fixing a basepoint $o \in X$, for $\xi \in \partial X$, let $B_{\xi}$ denote the Busemann function at $\xi$ such that $B_{\xi}(o) = 0$, then for $\lambda \in \mathbb{C}$ the function $e^{(i\lambda - \rho)B_{\xi}}$ is an eigenfunction of the Laplace-Beltrami operator with eigenvalue $-(\lambda^2 + \rho^2)$. For a function $f$ on $X$, we define the Fourier transform of $f$ by $$\tilde{f}(\lambda, \xi) := \int_X f(x) e^{(-i\lambda - \rho)B_{\xi}(x)} dvol(x)$$ for all $\lambda \in \mathbb{C}, \xi \in \partial X$ for which the integral converges. We prove a Fourier inversion formula $$f(x) = C_0 \int_{0}^{\infty} \int_{\partial X} \tilde{f}(\lambda, \xi) e^{(i\lambda - \rho)B_{\xi}(x)} d\lambda_o(\xi) |c(\lambda)|^{-2} d\lambda$$ for $f \in C^{\infty}_c(X)$, where $c$ is a certain function on $\mathbb{R} - \{0\}$, $\lambda_o$ is the visibility measure on $\partial X$ with respect to the basepoint $o \in X$ and $C_0 > 0$ is a constant. We also prove a Plancherel theorem. This generalizes the corresponding results for rank one symmetric spaces of noncompact type and negatively curved harmonic $NA$ groups (or Damek-Ricci spaces).
math.DG
let x be a complete simply connected harmonic manifold with sectional curvatures k satisfying k leq 1 and let partial x denote the boundary at infinity of x let h 0 denote the mean curvature of horospheres in x and let rho h2 fixing a basepoint o in x for xi in partial x let b_xi denote the busemann function at xi such that b_xio 0 then for lambda in mathbbc the function eilambda rhob_xi is an eigenfunction of the laplacebeltrami operator with eigenvalue lambda2 rho2 for a function f on x we define the fourier transform of f by tildeflambda xi int_x fx eilambda rhob_xix dvolx for all lambda in mathbbc xi in partial x for which the integral converges we prove a fourier inversion formula fx c_0 int_0infty int_partial x tildeflambda xi eilambda rhob_xix dlambda_oxi clambda2 dlambda for f in cinfty_cx where c is a certain function on mathbbr 0 lambda_o is the visibility measure on partial x with respect to the basepoint o in x and c_0 0 is a constant we also prove a plancherel theorem this generalizes the corresponding results for rank one symmetric spaces of noncompact type and negatively curved harmonic na groups or damekricci spaces
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1,802.07237
Interpreting top-quark LHC measurements in the standard-model effective field theory
This note proposes common standards and prescriptions for the effective-field-theory interpretation of top-quark measurements at the LHC.
hep-ph hep-ex
this note proposes common standards and prescriptions for the effectivefieldtheory interpretation of topquark measurements at the lhc
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1,802.07238
Quadratic conservative scheme for relativistic Vlasov--Maxwell system
For more than half a century, most of the plasma scientists have encountered a violation of the conservation laws of charge, momentum, and energy whenever they have numerically solve the first-principle equations of kinetic plasmas, such as the relativistic Vlasov--Maxwell system. This fatal problem is brought by the fact that both the Vlasov and Maxwell equations are indirectly associated with the conservation laws by means of some mathematical manipulations. Here we propose a quadratic conservative scheme, which can strictly maintain the conservation laws by discretizing the relativistic Vlasov--Maxwell system. A discrete product rule and summation-by-parts are the key players in the construction of the quadratic conservative scheme. Numerical experiments of the relativistic two-stream instability and relativistic Weibel instability prove the validity of our computational theory, and the proposed strategy will open the doors to the first-principle studies of mesoscopic and macroscopic plasma physics.
physics.plasm-ph physics.comp-ph
for more than half a century most of the plasma scientists have encountered a violation of the conservation laws of charge momentum and energy whenever they have numerically solve the firstprinciple equations of kinetic plasmas such as the relativistic vlasovmaxwell system this fatal problem is brought by the fact that both the vlasov and maxwell equations are indirectly associated with the conservation laws by means of some mathematical manipulations here we propose a quadratic conservative scheme which can strictly maintain the conservation laws by discretizing the relativistic vlasovmaxwell system a discrete product rule and summationbyparts are the key players in the construction of the quadratic conservative scheme numerical experiments of the relativistic twostream instability and relativistic weibel instability prove the validity of our computational theory and the proposed strategy will open the doors to the firstprinciple studies of mesoscopic and macroscopic plasma physics
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1,802.07239
Continual Reinforcement Learning with Complex Synapses
Unlike humans, who are capable of continual learning over their lifetimes, artificial neural networks have long been known to suffer from a phenomenon known as catastrophic forgetting, whereby new learning can lead to abrupt erasure of previously acquired knowledge. Whereas in a neural network the parameters are typically modelled as scalar values, an individual synapse in the brain comprises a complex network of interacting biochemical components that evolve at different timescales. In this paper, we show that by equipping tabular and deep reinforcement learning agents with a synaptic model that incorporates this biological complexity (Benna & Fusi, 2016), catastrophic forgetting can be mitigated at multiple timescales. In particular, we find that as well as enabling continual learning across sequential training of two simple tasks, it can also be used to overcome within-task forgetting by reducing the need for an experience replay database.
cs.AI cs.LG cs.NE
unlike humans who are capable of continual learning over their lifetimes artificial neural networks have long been known to suffer from a phenomenon known as catastrophic forgetting whereby new learning can lead to abrupt erasure of previously acquired knowledge whereas in a neural network the parameters are typically modelled as scalar values an individual synapse in the brain comprises a complex network of interacting biochemical components that evolve at different timescales in this paper we show that by equipping tabular and deep reinforcement learning agents with a synaptic model that incorporates this biological complexity benna fusi 2016 catastrophic forgetting can be mitigated at multiple timescales in particular we find that as well as enabling continual learning across sequential training of two simple tasks it can also be used to overcome withintask forgetting by reducing the need for an experience replay database
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1,802.0724
Cobalt: BFT Governance in Open Networks
We present Cobalt, a novel atomic broadcast algorithm that works in networks with non-uniform trust and no global agreement on participants, and is probabilistically guaranteed to make forward progress even in the presence of maximal faults and arbitrary asynchrony. The exact properties that Cobalt satisfies makes it particularly applicable to designing an efficient decentralized "voting network" that allows a public, open-entry group of nodes to agree on changes to some shared set of rules in a fair and consistent manner while tolerating some trusted nodes and arbitrarily many untrusted nodes behaving maliciously. We also define a new set of properties which must be satisfied by any safe decentralized governance algorithm, and all of which Cobalt satisfies.
cs.DC
we present cobalt a novel atomic broadcast algorithm that works in networks with nonuniform trust and no global agreement on participants and is probabilistically guaranteed to make forward progress even in the presence of maximal faults and arbitrary asynchrony the exact properties that cobalt satisfies makes it particularly applicable to designing an efficient decentralized voting network that allows a public openentry group of nodes to agree on changes to some shared set of rules in a fair and consistent manner while tolerating some trusted nodes and arbitrarily many untrusted nodes behaving maliciously we also define a new set of properties which must be satisfied by any safe decentralized governance algorithm and all of which cobalt satisfies
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1,802.07241
Influence of crystalline structure on RF dissipation in Niobium: flux trapping, hydride precipitate, doping behavior...
Bulk niobium is the material mostly used in RF superconducting cavities for accelerator. Predicting and reducing the surface dissipation in RF is mandatory, since it has a tremendous cost impact on most of the large accelerator projects. The theoretical approach of superconducting radiofrequency (SRF) behavior has been far less explored than DC behavior and is still based on the description of relatively simple systems, quite remote from the realistic material in use. Nevertheless, because the actual crystalline substructure is not taken into account, it is still difficult to predict surface dissipation accurately. Moreover, Niobium with its large lambda (~40 nm), exhibit an original behavior compared to the usual superconductors used in applied superconductivity, and generalities (e.g. pinning at grain boundaries) needs to be reconsidered. In this paper we hope to demonstrate that sources of dissipation usually attributed to external causes (mainly flux trapping during cooldown and hydrides precipitates) are related to the same type of crystalline defects which are not grain boundaries; that they affect the local superconducting properties and can also be at the source of early vortex penetration at the surface. We want also to stretch out how those defects can explain some of the discrepancies observed from lab to lab on recent results obtained i.e. in doping experiments. Understanding the origin and the role of these defects could provide indications for updating specification as well as fabrication follow up. Rather than new results the author wishes to present to the superconducting accelerators community the synthesis of multiple experimental results scattered in the literature that provide a new lighting on recently published work, in particular in the domain of SRF cavity doping as well as issues such as sensitivity to trapped flux during cooldown.
physics.acc-ph
bulk niobium is the material mostly used in rf superconducting cavities for accelerator predicting and reducing the surface dissipation in rf is mandatory since it has a tremendous cost impact on most of the large accelerator projects the theoretical approach of superconducting radiofrequency srf behavior has been far less explored than dc behavior and is still based on the description of relatively simple systems quite remote from the realistic material in use nevertheless because the actual crystalline substructure is not taken into account it is still difficult to predict surface dissipation accurately moreover niobium with its large lambda 40 nm exhibit an original behavior compared to the usual superconductors used in applied superconductivity and generalities eg pinning at grain boundaries needs to be reconsidered in this paper we hope to demonstrate that sources of dissipation usually attributed to external causes mainly flux trapping during cooldown and hydrides precipitates are related to the same type of crystalline defects which are not grain boundaries that they affect the local superconducting properties and can also be at the source of early vortex penetration at the surface we want also to stretch out how those defects can explain some of the discrepancies observed from lab to lab on recent results obtained ie in doping experiments understanding the origin and the role of these defects could provide indications for updating specification as well as fabrication follow up rather than new results the author wishes to present to the superconducting accelerators community the synthesis of multiple experimental results scattered in the literature that provide a new lighting on recently published work in particular in the domain of srf cavity doping as well as issues such as sensitivity to trapped flux during cooldown
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1,802.07242
Analysis of the XRP Ledger Consensus Protocol
The XRP Ledger Consensus Protocol is a previously developed consensus protocol powering the XRP Ledger. It is a low-latency Byzantine agreement protocol, capable of reaching consensus without full agreement on which nodes are members of the network. We present a detailed explanation of the algorithm and derive conditions for its safety and liveness.
cs.DC
the xrp ledger consensus protocol is a previously developed consensus protocol powering the xrp ledger it is a lowlatency byzantine agreement protocol capable of reaching consensus without full agreement on which nodes are members of the network we present a detailed explanation of the algorithm and derive conditions for its safety and liveness
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1,802.07243
Value iteration for approximate dynamic programming under convexity
This paper studies value iteration for infinite horizon contracting Markov decision processes under convexity assumptions and when the state space is uncountable. The original value iteration is replaced with a more tractable form and the fixed points from the modified Bellman operators will be shown to converge uniformly on compacts sets to their original counterparts. This holds under various sampling approaches for the random disturbances. Moreover, this paper will present conditions in which these fixed points form monotone sequences of lower bounding or upper bounding functions for the original fixed point. This approach is then demonstrated numerically on a perpetual Bermudan put option.
math.OC
this paper studies value iteration for infinite horizon contracting markov decision processes under convexity assumptions and when the state space is uncountable the original value iteration is replaced with a more tractable form and the fixed points from the modified bellman operators will be shown to converge uniformly on compacts sets to their original counterparts this holds under various sampling approaches for the random disturbances moreover this paper will present conditions in which these fixed points form monotone sequences of lower bounding or upper bounding functions for the original fixed point this approach is then demonstrated numerically on a perpetual bermudan put option
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1,802.07244
Steering Social Activity: A Stochastic Optimal Control Point Of View
User engagement in online social networking depends critically on the level of social activity in the corresponding platform--the number of online actions, such as posts, shares or replies, taken by their users. Can we design data-driven algorithms to increase social activity? At a user level, such algorithms may increase activity by helping users decide when to take an action to be more likely to be noticed by their peers. At a network level, they may increase activity by incentivizing a few influential users to take more actions, which in turn will trigger additional actions by other users. In this paper, we model social activity using the framework of marked temporal point processes, derive an alternate representation of these processes using stochastic differential equations (SDEs) with jumps and, exploiting this alternate representation, develop two efficient online algorithms with provable guarantees to steer social activity both at a user and at a network level. In doing so, we establish a previously unexplored connection between optimal control of jump SDEs and doubly stochastic marked temporal point processes, which is of independent interest. Finally, we experiment both with synthetic and real data gathered from Twitter and show that our algorithms consistently steer social activity more effectively than the state of the art.
cs.SI cs.LG stat.ML
user engagement in online social networking depends critically on the level of social activity in the corresponding platformthe number of online actions such as posts shares or replies taken by their users can we design datadriven algorithms to increase social activity at a user level such algorithms may increase activity by helping users decide when to take an action to be more likely to be noticed by their peers at a network level they may increase activity by incentivizing a few influential users to take more actions which in turn will trigger additional actions by other users in this paper we model social activity using the framework of marked temporal point processes derive an alternate representation of these processes using stochastic differential equations sdes with jumps and exploiting this alternate representation develop two efficient online algorithms with provable guarantees to steer social activity both at a user and at a network level in doing so we establish a previously unexplored connection between optimal control of jump sdes and doubly stochastic marked temporal point processes which is of independent interest finally we experiment both with synthetic and real data gathered from twitter and show that our algorithms consistently steer social activity more effectively than the state of the art
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1,802.07245
Meta-Reinforcement Learning of Structured Exploration Strategies
Exploration is a fundamental challenge in reinforcement learning (RL). Many of the current exploration methods for deep RL use task-agnostic objectives, such as information gain or bonuses based on state visitation. However, many practical applications of RL involve learning more than a single task, and prior tasks can be used to inform how exploration should be performed in new tasks. In this work, we explore how prior tasks can inform an agent about how to explore effectively in new situations. We introduce a novel gradient-based fast adaptation algorithm -- model agnostic exploration with structured noise (MAESN) -- to learn exploration strategies from prior experience. The prior experience is used both to initialize a policy and to acquire a latent exploration space that can inject structured stochasticity into a policy, producing exploration strategies that are informed by prior knowledge and are more effective than random action-space noise. We show that MAESN is more effective at learning exploration strategies when compared to prior meta-RL methods, RL without learned exploration strategies, and task-agnostic exploration methods. We evaluate our method on a variety of simulated tasks: locomotion with a wheeled robot, locomotion with a quadrupedal walker, and object manipulation.
cs.LG cs.AI cs.NE
exploration is a fundamental challenge in reinforcement learning rl many of the current exploration methods for deep rl use taskagnostic objectives such as information gain or bonuses based on state visitation however many practical applications of rl involve learning more than a single task and prior tasks can be used to inform how exploration should be performed in new tasks in this work we explore how prior tasks can inform an agent about how to explore effectively in new situations we introduce a novel gradientbased fast adaptation algorithm model agnostic exploration with structured noise maesn to learn exploration strategies from prior experience the prior experience is used both to initialize a policy and to acquire a latent exploration space that can inject structured stochasticity into a policy producing exploration strategies that are informed by prior knowledge and are more effective than random actionspace noise we show that maesn is more effective at learning exploration strategies when compared to prior metarl methods rl without learned exploration strategies and taskagnostic exploration methods we evaluate our method on a variety of simulated tasks locomotion with a wheeled robot locomotion with a quadrupedal walker and object manipulation
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1,802.07246
Exact equations of state for nematics
We propose a novel approach to the solution of nematic Liquid Crystal models based on the derivation of a system of nonlinear wave equations for order parameters such that the occurrence of uniaxial and biaxial phase transitions can be interpreted as the propagation of a two-dimensional shock wave in the space of thermodynamic parameters. We obtain the exact equations of state for an integrable model of biaxial nematic liquid crystals and show that the classical transition from isotropic to uniaxial phase in absence of external fields is the result of a van der Waals type phase transition, where the jump in the order parameters is a classical shock generated from a gradient catastrophe at a non-zero isotropic field. The study of the equations of state provides the first analytical description of the rich structure of nematics phase diagrams in presence of external fields.
cond-mat.soft nlin.SI physics.class-ph
we propose a novel approach to the solution of nematic liquid crystal models based on the derivation of a system of nonlinear wave equations for order parameters such that the occurrence of uniaxial and biaxial phase transitions can be interpreted as the propagation of a twodimensional shock wave in the space of thermodynamic parameters we obtain the exact equations of state for an integrable model of biaxial nematic liquid crystals and show that the classical transition from isotropic to uniaxial phase in absence of external fields is the result of a van der waals type phase transition where the jump in the order parameters is a classical shock generated from a gradient catastrophe at a nonzero isotropic field the study of the equations of state provides the first analytical description of the rich structure of nematics phase diagrams in presence of external fields
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1,802.07247
Reverse Monte Carlo reconstruction of electron spin-label coordinates from scanned-probe magnetic resonance microscope signals
Individual electron spins have been observed using magnetic resonance in combination with a number of distinct detection approaches. The coordinates of an individual electron spin can then in principle be determined by introducing a 10 to 100 nm diameter magnetic needle, scanning the needle, and collecting signal as a function of the needle's position. Although individual electrons have recently been localized with nanometer precision in this way using a nitrogen-vacancy center in diamond as the spin detector, the experiment's low signal-to-noise ratio limited acquisition to two-dimensional scanning of just a few dozen data points and was incompatible with nitroxide spin labels widely used to label proteins and nucleic acids. We introduce and numerically simulate a protocol for detecting and imaging individual nitroxide electron spins mechanically with high spatial resolution. In our protocol a scanned magnet-tipped cantilever is brought near the sample, modulated microwaves are applied to resonantly excite electron spins, and changes in spin magnetization are detected as a shift in the mechanical frequency of the cantilever. By carefully applying resonant microwaves in short bursts in synchrony with the cantilever's oscillation, we propose to retain high spatial resolution even at large cantilever amplitude where sensitivity is highest. Numerical simulations reveal nanometer-diameter rings of frequency-shift signal as the tip is scanned. Our primary finding is that it is possible --- using a Bayesian, reverse Monte Carlo algorithm introduced here --- to obtain the full three-dimensional distribution of electron coordinates from the signal rings revealed in a two-dimensional frequency-shift map. This reduction in dimensionality brings within reach, on a practical timescale, the angstrom-resolution three-dimensional imaging of spin-labeled macromolecules.
cond-mat.mes-hall
individual electron spins have been observed using magnetic resonance in combination with a number of distinct detection approaches the coordinates of an individual electron spin can then in principle be determined by introducing a 10 to 100 nm diameter magnetic needle scanning the needle and collecting signal as a function of the needles position although individual electrons have recently been localized with nanometer precision in this way using a nitrogenvacancy center in diamond as the spin detector the experiments low signaltonoise ratio limited acquisition to twodimensional scanning of just a few dozen data points and was incompatible with nitroxide spin labels widely used to label proteins and nucleic acids we introduce and numerically simulate a protocol for detecting and imaging individual nitroxide electron spins mechanically with high spatial resolution in our protocol a scanned magnettipped cantilever is brought near the sample modulated microwaves are applied to resonantly excite electron spins and changes in spin magnetization are detected as a shift in the mechanical frequency of the cantilever by carefully applying resonant microwaves in short bursts in synchrony with the cantilevers oscillation we propose to retain high spatial resolution even at large cantilever amplitude where sensitivity is highest numerical simulations reveal nanometerdiameter rings of frequencyshift signal as the tip is scanned our primary finding is that it is possible using a bayesian reverse monte carlo algorithm introduced here to obtain the full threedimensional distribution of electron coordinates from the signal rings revealed in a twodimensional frequencyshift map this reduction in dimensionality brings within reach on a practical timescale the angstromresolution threedimensional imaging of spinlabeled macromolecules
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1,802.07248
Gelfand-Tsetlin variety for $\mathfrak{gl}_n$
S. Ovsienko proved that the Gelfand-Tsetlin variety for $\mathfrak{gl}_n$ is equidimensional (i.e. all its irreducible components have the same dimension) with dimension equals $\frac{n(n-1)}{2}$. This result has important consequences in Representation Theory of Algebras, implying, in particular, the equidimensionality of the nilfiber of the Kostant-Wallach map. In this paper we will present the generalization of this result and will address a weak version of Ovsienko's Theorem which includes the regular case.
math.RT math.AG
s ovsienko proved that the gelfandtsetlin variety for mathfrakgl_n is equidimensional ie all its irreducible components have the same dimension with dimension equals fracnn12 this result has important consequences in representation theory of algebras implying in particular the equidimensionality of the nilfiber of the kostantwallach map in this paper we will present the generalization of this result and will address a weak version of ovsienkos theorem which includes the regular case
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1,802.07249
Three Dimensional Imaging of the Nucleon
We study the Wigner distributions of quarks and gluons in light-front dressed quark model using the overlap of light front wave functions (LFWFs). We take the target to be a dressed quark, this is a composite spin $-1/2$ state of quark dressed with a gluon. This state allows us to calculate the quark and gluon Wigner distributions analytically in terms of LFWFs using Hamiltonian perturbation theory. We analyze numerically the Wigner distributions of quark and gluon and report their nature in the contour plots. We use an improved numerical technique to remove the cutoff dependence of the Fourier transformed integral over ${\bf \Delta}_\perp$.
hep-ph
we study the wigner distributions of quarks and gluons in lightfront dressed quark model using the overlap of light front wave functions lfwfs we take the target to be a dressed quark this is a composite spin 12 state of quark dressed with a gluon this state allows us to calculate the quark and gluon wigner distributions analytically in terms of lfwfs using hamiltonian perturbation theory we analyze numerically the wigner distributions of quark and gluon and report their nature in the contour plots we use an improved numerical technique to remove the cutoff dependence of the fourier transformed integral over bf delta_perp
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1,802.0725
Bifurcations in the theory of current transfer to cathodes of dc discharges and observations of transitions between different modes
General scenarios of transitions between different spot patterns on electrodes of dc gas discharges and their relation to bifurcations of steady-state solutions are analyzed. In the case of cathodes of arc discharges, it is shown that any transition between different modes of current transfer is related to a bifurcation of steady-state solutions. In particular, transitions between diffuse and spot modes on axially symmetric cathodes, frequently observed in the experiment, represent an indication of the presence of pitchfork or fold bifurcations of steady-state solutions. Experimental observations of transitions on cathodes of dc glow microdischarges are analyzed and those potentially related to bifurcations of steady-state solutions are identified. The relevant bifurcations are investigated numerically and the computed patterns are found to conform to those observed in the course of the corresponding transitions in the experiment.
physics.plasm-ph
general scenarios of transitions between different spot patterns on electrodes of dc gas discharges and their relation to bifurcations of steadystate solutions are analyzed in the case of cathodes of arc discharges it is shown that any transition between different modes of current transfer is related to a bifurcation of steadystate solutions in particular transitions between diffuse and spot modes on axially symmetric cathodes frequently observed in the experiment represent an indication of the presence of pitchfork or fold bifurcations of steadystate solutions experimental observations of transitions on cathodes of dc glow microdischarges are analyzed and those potentially related to bifurcations of steadystate solutions are identified the relevant bifurcations are investigated numerically and the computed patterns are found to conform to those observed in the course of the corresponding transitions in the experiment
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1,802.07251
A fuzzy logic feedback filter design tuned with PSO for L1 adaptive controller
L1 adaptive controller has been recognized for having a structure that allows decoupling between robustness and adaption owing to the introduction of a low pass filter with adjustable gain in the feedback loop. The trade-off between performance, fast adaptation and robustness, is the main criteria when selecting the structure or the coefficients of the filter. Several off-line methods with varying levels of complexity exist to help finding bounds or initial values for these coefficients. Such values may require further refinement using trial-and-error procedures upon implementation. Subsequently, these approaches suggest that once implemented these values are kept fixed leading to sub-optimal performance in both speed of adaptation and robustness. In this paper, a new practical approach based on fuzzy rules for online continuous tuning of these coefficients is proposed. The fuzzy controller is optimally tuned using Particle Swarm Optimization (PSO) taking into accounts both the tracking error and the controller output signal range. The simulation of several examples of systems with moderate to severe nonlinearities demonstrate that the proposed approach offers improved control performance. Keywords: Fuzzy logic control, single-objective, multi-objective particle swarm optimization, L1 Adaptive control, fuzzy L1 adaptive controller, L1 fuzzy adaptive control, L1 fuzzy adaptive controller, fuzzy L1 adaptive control, Filter tuning, Fuzzy membership function tuning, optimal, optimal tuning, Fuzzy membership function optimization, Robustness, Adaptation, multi-input multi-output, single-input single-output, estimate, PSO, FLC, nonlinear, adaptive, online, off-line, Fuzzy adaptive controller, Fuzzy adaptive control, single input single output, multi input multi output, SISO, MIMO, robust, uncertain, uncertain nonlinear system, disturbance, unknown, Adaptive Fuzzy Control Design, stable.
cs.SY
l1 adaptive controller has been recognized for having a structure that allows decoupling between robustness and adaption owing to the introduction of a low pass filter with adjustable gain in the feedback loop the tradeoff between performance fast adaptation and robustness is the main criteria when selecting the structure or the coefficients of the filter several offline methods with varying levels of complexity exist to help finding bounds or initial values for these coefficients such values may require further refinement using trialanderror procedures upon implementation subsequently these approaches suggest that once implemented these values are kept fixed leading to suboptimal performance in both speed of adaptation and robustness in this paper a new practical approach based on fuzzy rules for online continuous tuning of these coefficients is proposed the fuzzy controller is optimally tuned using particle swarm optimization pso taking into accounts both the tracking error and the controller output signal range the simulation of several examples of systems with moderate to severe nonlinearities demonstrate that the proposed approach offers improved control performance keywords fuzzy logic control singleobjective multiobjective particle swarm optimization l1 adaptive control fuzzy l1 adaptive controller l1 fuzzy adaptive control l1 fuzzy adaptive controller fuzzy l1 adaptive control filter tuning fuzzy membership function tuning optimal optimal tuning fuzzy membership function optimization robustness adaptation multiinput multioutput singleinput singleoutput estimate pso flc nonlinear adaptive online offline fuzzy adaptive controller fuzzy adaptive control single input single output multi input multi output siso mimo robust uncertain uncertain nonlinear system disturbance unknown adaptive fuzzy control design stable
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1,802.07252
Properties of dirty two-bands superconductors with repulsive interband interaction: normal modes, length scales, vortices and magnetic response
Disorder in two-band superconductors with repulsive interband interaction induces a frustrated competition between the phase-locking preferences of the various potential and kinetic terms. This frustrated interaction can result in the formation of an $s+is$ superconducting state, that breaks the time-reversal symmetry. In this paper we study the normal modes and their associated coherence lengths in such materials. We especially focus on the consequences of the soft modes stemming from the frustration and time-reversal-symmetry breakdown. We find that two-bands superconductors with such impurity-induced frustrated interactions display a rich spectrum of physical properties that are absent in their clean counterparts. It features a mixing of Leggett's and Anderson-Higgs modes, and a soft mode with diverging coherence length at the impurity-induced second order phase transition from $s_{\pm}/s_{++}$ states to the $s+is$ state. Such a soft mode generically results in long-range attractive intervortex forces that can trigger the formation of vortex clusters. We find that, if such clusters are formed, their size and internal flux density have a characteristic temperature dependence that could be probed in muon-spin-rotation experiments. We also comment on the appearance of spontaneous magnetic fields due to spatially varying impurities.
cond-mat.supr-con
disorder in twoband superconductors with repulsive interband interaction induces a frustrated competition between the phaselocking preferences of the various potential and kinetic terms this frustrated interaction can result in the formation of an sis superconducting state that breaks the timereversal symmetry in this paper we study the normal modes and their associated coherence lengths in such materials we especially focus on the consequences of the soft modes stemming from the frustration and timereversalsymmetry breakdown we find that twobands superconductors with such impurityinduced frustrated interactions display a rich spectrum of physical properties that are absent in their clean counterparts it features a mixing of leggetts and andersonhiggs modes and a soft mode with diverging coherence length at the impurityinduced second order phase transition from s_pms_ states to the sis state such a soft mode generically results in longrange attractive intervortex forces that can trigger the formation of vortex clusters we find that if such clusters are formed their size and internal flux density have a characteristic temperature dependence that could be probed in muonspinrotation experiments we also comment on the appearance of spontaneous magnetic fields due to spatially varying impurities
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1,802.07253
Neuro-adaptive distributed control with prescribed performance for the synchronization of unknown nonlinear networked systems
This paper proposes a neuro-adaptive distributive cooperative tracking control with prescribed performance function (PPF) for highly nonlinear multi-agent systems. PPF allows error tracking from a predefined large set to be trapped into a predefined small set. The key idea is to transform the constrained system into unconstrained one through transformation of the output error. Agents' dynamics are assumed to be completely unknown, and the controller is developed for strongly connected structured network. The proposed controller allows all agents to follow the trajectory of the leader node, while satisfying necessary dynamic requirements. The proposed approach guarantees uniform ultimate boundedness of the transformed error and the adaptive neural network weights. Simulations include two examples to validate the robustness and smoothness of the proposed controller against highly nonlinear heterogeneous networked system with time varying uncertain parameters and external disturbances.
math.OC cs.SY
this paper proposes a neuroadaptive distributive cooperative tracking control with prescribed performance function ppf for highly nonlinear multiagent systems ppf allows error tracking from a predefined large set to be trapped into a predefined small set the key idea is to transform the constrained system into unconstrained one through transformation of the output error agents dynamics are assumed to be completely unknown and the controller is developed for strongly connected structured network the proposed controller allows all agents to follow the trajectory of the leader node while satisfying necessary dynamic requirements the proposed approach guarantees uniform ultimate boundedness of the transformed error and the adaptive neural network weights simulations include two examples to validate the robustness and smoothness of the proposed controller against highly nonlinear heterogeneous networked system with time varying uncertain parameters and external disturbances
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1,802.07254
Observed Type II supernova colours from the Carnegie Supernova Project-I
We present a study of observed Type II supernova (SN~II) colours using optical/near-infrared photometric data from the \textit{Carnegie Supernovae Project-I}. We analyse four colours ($B-V$, $u-g$, $g-r$, and $g-Y$) and find that SN~II colour curves can be described by two linear regimes during the photospheric phase. The first ($s_{\rm 1,colour}$) is steeper and has a median duration of $\sim 40$ days. The second, shallower slope ($s_{\rm 2,colour}$) lasts until the end of the "plateau" ($\sim 80$ days). The two slopes correlate in the sense that steeper initial colour curves also imply steeper colour curves at later phases. As suggested by recent studies, SNe~II form a continuous population of objects from the colour point of view as well. We investigate correlations between the observed colours and a range of photometric and spectroscopic parameters including the absolute magnitude, the $V$-band light-curve slopes, and metal-line strengths. We find that less luminous SNe~II appear redder, a trend that we argue is not driven by uncorrected host-galaxy reddening. While there is significant dispersion, we find evidence that redder SNe~II (mainly at early epochs) display stronger metal-line equivalent widths. Host-galaxy reddening does not appear to be a dominant parameter, neither driving observed trends nor dominating the dispersion in observed colours. Intrinsic SN~II colours are most probably dominated by photospheric temperature differences, with progenitor metallicity possibly playing a minor role. Such temperature differences could be related to differences in progenitor radius, together with the presence or absence of circumstellar material close to the progenitor stars.
astro-ph.HE
we present a study of observed type ii supernova snii colours using opticalnearinfrared photometric data from the textitcarnegie supernovae projecti we analyse four colours bv ug gr and gy and find that snii colour curves can be described by two linear regimes during the photospheric phase the first s_rm 1colour is steeper and has a median duration of sim 40 days the second shallower slope s_rm 2colour lasts until the end of the plateau sim 80 days the two slopes correlate in the sense that steeper initial colour curves also imply steeper colour curves at later phases as suggested by recent studies sneii form a continuous population of objects from the colour point of view as well we investigate correlations between the observed colours and a range of photometric and spectroscopic parameters including the absolute magnitude the vband lightcurve slopes and metalline strengths we find that less luminous sneii appear redder a trend that we argue is not driven by uncorrected hostgalaxy reddening while there is significant dispersion we find evidence that redder sneii mainly at early epochs display stronger metalline equivalent widths hostgalaxy reddening does not appear to be a dominant parameter neither driving observed trends nor dominating the dispersion in observed colours intrinsic snii colours are most probably dominated by photospheric temperature differences with progenitor metallicity possibly playing a minor role such temperature differences could be related to differences in progenitor radius together with the presence or absence of circumstellar material close to the progenitor stars
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1,802.07255
Enhancing the Sensitivity of Searches for Gravitational Waves from Core-Collapse Supernovae with a Bayesian classification of candidate events
We demonstrate how a morphological veto involving Bayesian statistics can improve the receiver-operating characteristic (ROC) curves of the current search for core-collapse supernovae (CCSNe) as implemented by the coherent Waveburst (cWB) algorithm. Examples involving two implementations of BayesWave (BW), one that makes no assumption of the polarization state of the gravitational wave (GW) and one that uses the same elliptical polarization settings adopted in previous usages for Binary systems are provided on the set of waveforms currently adopted for the first and second Advanced LIGO (aLIGO) science runs for the targeted CCSNe search. A comparison of the performance for all-sky searches versus the targeted searches with optical triggers is provided. The average cWB+BW ROC range improvements with respect to a fixed false-alarm rate (FAR) for slowly-rotating waveforms ranged from [+1.30%, +15.76%] while the improvement for rapidly-rotating waveforms were on the order of [+1.19%, +22.05%]. The application of BW to CCSN GW triggers also shows a significant reduction of the FAR while maintaining detection efficiency and remaining sensitive to a wide range of morphological CCSNe signals. It appears that the code developed for arbitrarily polarized signals outperforms the previous code for the GW morphologies tested.
astro-ph.HE
we demonstrate how a morphological veto involving bayesian statistics can improve the receiveroperating characteristic roc curves of the current search for corecollapse supernovae ccsne as implemented by the coherent waveburst cwb algorithm examples involving two implementations of bayeswave bw one that makes no assumption of the polarization state of the gravitational wave gw and one that uses the same elliptical polarization settings adopted in previous usages for binary systems are provided on the set of waveforms currently adopted for the first and second advanced ligo aligo science runs for the targeted ccsne search a comparison of the performance for allsky searches versus the targeted searches with optical triggers is provided the average cwbbw roc range improvements with respect to a fixed falsealarm rate far for slowlyrotating waveforms ranged from 130 1576 while the improvement for rapidlyrotating waveforms were on the order of 119 2205 the application of bw to ccsn gw triggers also shows a significant reduction of the far while maintaining detection efficiency and remaining sensitive to a wide range of morphological ccsne signals it appears that the code developed for arbitrarily polarized signals outperforms the previous code for the gw morphologies tested
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1,802.07256
Hampering G\"{o}rtler vortices via optimal control in the framework of nonlinear boundary region equations
The control of stream-wise vortices in high Reynolds number boundary layer flows often aims at reducing the vortex energy as a means of mitigating the growth of secondary instabilities, which eventually delay the transition from laminar to turbulent flow. In this paper, we aim at utilizing such an energy reduction strategy using optimal control theory to limit the growth of G\"{o}rtler vortices developing in an incompressible laminar boundary layer flow over a concave wall, and excited by a row of roughness elements with span-wise separation in the same order of magnitude as the boundary layer thickness. Commensurate with control theory formalism, we transform a constrained optimization problem into an unconstrained one by applying the method of Lagrange multipliers. A high Reynolds number asymptotic framework is utilized, wherein the Navier-Stokes equations are reduced to the boundary region equations (BRE), in which wall deformations enter the problem through an appropriate Prandtl transformation. In the optimal control strategy, the wall displacement or the wall transpiration velocity serve as control variables, while the cost functional is defined in terms of the wall shear stress. Our numerical results indicate, among other things, that the optimal control algorithm is very effective in reducing the amplitude of the G\"{o}rtler vortices, especially for the control based on wall displacement.
physics.flu-dyn
the control of streamwise vortices in high reynolds number boundary layer flows often aims at reducing the vortex energy as a means of mitigating the growth of secondary instabilities which eventually delay the transition from laminar to turbulent flow in this paper we aim at utilizing such an energy reduction strategy using optimal control theory to limit the growth of gortler vortices developing in an incompressible laminar boundary layer flow over a concave wall and excited by a row of roughness elements with spanwise separation in the same order of magnitude as the boundary layer thickness commensurate with control theory formalism we transform a constrained optimization problem into an unconstrained one by applying the method of lagrange multipliers a high reynolds number asymptotic framework is utilized wherein the navierstokes equations are reduced to the boundary region equations bre in which wall deformations enter the problem through an appropriate prandtl transformation in the optimal control strategy the wall displacement or the wall transpiration velocity serve as control variables while the cost functional is defined in terms of the wall shear stress our numerical results indicate among other things that the optimal control algorithm is very effective in reducing the amplitude of the gortler vortices especially for the control based on wall displacement
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1,802.07257
Predicting Natural Hazards with Neuronal Networks
Gravitational mass flows, such as avalanches, debris flows and rockfalls are common events in alpine regions with high impact on transport routes. Within the last few decades, hazard zone maps have been developed to systematically approach this threat. These maps mark vulnerable zones in habitable areas to allow effective planning of hazard mitigation measures and development of settlements. Hazard zone maps have shown to be an effective tool to reduce fatalities during extreme events. They are created in a complex process, based on experience, empirical models, physical simulations and historical data. The generation of such maps is therefore expensive and limited to crucially important regions, e.g. permanently inhabited areas. In this work we interpret the task of hazard zone mapping as a classification problem. Every point in a specific area has to be classified according to its vulnerability. On a regional scale this leads to a segmentation problem, where the total area has to be divided in the respective hazard zones. The recent developments in artificial intelligence, namely convolutional neuronal networks, have led to major improvement in a very similar task, image classification and semantic segmentation, i.e. computer vision. We use a convolutional neuronal network to identify terrain formations with the potential for catastrophic snow avalanches and label points in their reach as vulnerable. Repeating this procedure for all points allows us to generate an artificial hazard zone map. We demonstrate that the approach is feasible and promising based on the hazard zone map of the Tirolean Oberland. However, more training data and further improvement of the method is required before such techniques can be applied reliably.
eess.IV cs.AI
gravitational mass flows such as avalanches debris flows and rockfalls are common events in alpine regions with high impact on transport routes within the last few decades hazard zone maps have been developed to systematically approach this threat these maps mark vulnerable zones in habitable areas to allow effective planning of hazard mitigation measures and development of settlements hazard zone maps have shown to be an effective tool to reduce fatalities during extreme events they are created in a complex process based on experience empirical models physical simulations and historical data the generation of such maps is therefore expensive and limited to crucially important regions eg permanently inhabited areas in this work we interpret the task of hazard zone mapping as a classification problem every point in a specific area has to be classified according to its vulnerability on a regional scale this leads to a segmentation problem where the total area has to be divided in the respective hazard zones the recent developments in artificial intelligence namely convolutional neuronal networks have led to major improvement in a very similar task image classification and semantic segmentation ie computer vision we use a convolutional neuronal network to identify terrain formations with the potential for catastrophic snow avalanches and label points in their reach as vulnerable repeating this procedure for all points allows us to generate an artificial hazard zone map we demonstrate that the approach is feasible and promising based on the hazard zone map of the tirolean oberland however more training data and further improvement of the method is required before such techniques can be applied reliably
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1,802.07258
Rank dynamics of word usage at multiple scales
The recent dramatic increase in online data availability has allowed researchers to explore human culture with unprecedented detail, such as the growth and diversification of language. In particular, it provides statistical tools to explore whether word use is similar across languages, and if so, whether these generic features appear at different scales of language structure. Here we use the Google Books $N$-grams dataset to analyze the temporal evolution of word usage in several languages. We apply measures proposed recently to study rank dynamics, such as the diversity of $N$-grams in a given rank, the probability that an $N$-gram changes rank between successive time intervals, the rank entropy, and the rank complexity. Using different methods, results show that there are generic properties for different languages at different scales, such as a core of words necessary to minimally understand a language. We also propose a null model to explore the relevance of linguistic structure across multiple scales, concluding that $N$-gram statistics cannot be reduced to word statistics. We expect our results to be useful in improving text prediction algorithms, as well as in shedding light on the large-scale features of language use, beyond linguistic and cultural differences across human populations.
physics.soc-ph
the recent dramatic increase in online data availability has allowed researchers to explore human culture with unprecedented detail such as the growth and diversification of language in particular it provides statistical tools to explore whether word use is similar across languages and if so whether these generic features appear at different scales of language structure here we use the google books ngrams dataset to analyze the temporal evolution of word usage in several languages we apply measures proposed recently to study rank dynamics such as the diversity of ngrams in a given rank the probability that an ngram changes rank between successive time intervals the rank entropy and the rank complexity using different methods results show that there are generic properties for different languages at different scales such as a core of words necessary to minimally understand a language we also propose a null model to explore the relevance of linguistic structure across multiple scales concluding that ngram statistics cannot be reduced to word statistics we expect our results to be useful in improving text prediction algorithms as well as in shedding light on the largescale features of language use beyond linguistic and cultural differences across human populations
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1,802.07259
Multigrid Renormalization
We combine the multigrid (MG) method with state-of-the-art concepts from the variational formulation of the numerical renormalization group. The resulting MG renormalization (MGR) method is a natural generalization of the MG method for solving partial differential equations. When the solution on a grid of $N$ points is sought, our MGR method has a computational cost scaling as $\mathcal{O}(\log(N))$, as opposed to $\mathcal{O}(N)$ for the best standard MG method. Therefore MGR can exponentially speed up standard MG computations. To illustrate our method, we develop a novel algorithm for the ground state computation of the nonlinear Schr\"{o}dinger equation. Our algorithm acts variationally on tensor products and updates the tensors one after another by solving a local nonlinear optimization problem. We compare several different methods for the nonlinear tensor update and find that the Newton method is the most efficient as well as precise. The combination of MGR with our nonlinear ground state algorithm produces accurate results for the nonlinear Schr\"{o}dinger equation on $N = 10^{18}$ grid points in three spatial dimensions.
physics.comp-ph quant-ph
we combine the multigrid mg method with stateoftheart concepts from the variational formulation of the numerical renormalization group the resulting mg renormalization mgr method is a natural generalization of the mg method for solving partial differential equations when the solution on a grid of n points is sought our mgr method has a computational cost scaling as mathcalologn as opposed to mathcalon for the best standard mg method therefore mgr can exponentially speed up standard mg computations to illustrate our method we develop a novel algorithm for the ground state computation of the nonlinear schrodinger equation our algorithm acts variationally on tensor products and updates the tensors one after another by solving a local nonlinear optimization problem we compare several different methods for the nonlinear tensor update and find that the newton method is the most efficient as well as precise the combination of mgr with our nonlinear ground state algorithm produces accurate results for the nonlinear schrodinger equation on n 1018 grid points in three spatial dimensions
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