scholarly journals On Some Polynomials with Weighted Sums

2017 ◽  
Vol 10 (1) ◽  
pp. 40-42
Author(s):  
Seon-Hong Kim
Keyword(s):  
Weighted Sums

scholarly journals Chaos on the hypercube

2020 ◽  
Vol 2020 (11) ◽  
Author(s):  
Yiyang Jia ◽  
Jacobus J. M. Verbaarschot
Keyword(s):  
Magnetic Flux ◽  
Spectral Density ◽  
Hermite Polynomials ◽  
Weighted Sums ◽  
Majorana Fermions ◽  
Chord Diagrams ◽  
Magnetic Inversion ◽  
Constant Magnitude ◽  
Kitaev Model ◽  
Spectral Statistics

Abstract We analyze the spectral properties of a d-dimensional HyperCubic (HC) lattice model originally introduced by Parisi. The U(1) gauge links of this model give rise to a magnetic flux of constant magnitude ϕ but random orientation through the faces of the hypercube. The HC model, which also can be written as a model of 2d interacting Majorana fermions, has a spectral flow that is reminiscent of Maldacena-Qi (MQ) model, and its spectrum at ϕ = 0, actually coincides with the coupling term of the MQ model. As was already shown by Parisi, at leading order in 1/d, the spectral density of this model is given by the density function of the Q-Hermite polynomials, which is also the spectral density of the double-scaled Sachdev-Ye-Kitaev model. Parisi demonstrated this by mapping the moments of the HC model to Q-weighted sums on chord diagrams. We point out that the subleading moments of the HC model can also be mapped to weighted sums on chord diagrams, in a manner that descends from the leading moments. The HC model has a magnetic inversion symmetry that depends on both the magnitude and the orientation of the magnetic flux through the faces of the hypercube. The spectrum for fixed quantum number of this symmetry exhibits a transition from regular spectra at ϕ = 0 to chaotic spectra with spectral statistics given by the Gaussian Unitary Ensembles (GUE) for larger values of ϕ. For small magnetic flux, the ground state is gapped and is close to a Thermofield Double (TFD) state.

scholarly journals On Some Conditions for Strong Law of Large Numbers for Weighted Sums of END Random Variables under Sublinear Expectations

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Xiaochen Ma ◽  
Qunying Wu
Keyword(s):  
Probability Space ◽  
Law Of Large Numbers ◽  
Random Variables ◽  
Weighted Sums ◽  
Dependent Random Variables ◽  
Strong Law ◽  
Sublinear Expectation ◽  
Negatively Dependent Random Variables ◽  
Large Numbers ◽  
End Random Variables

In this article, we research some conditions for strong law of large numbers (SLLNs) for weighted sums of extended negatively dependent (END) random variables under sublinear expectation space. Our consequences contain the Kolmogorov strong law of large numbers and the Marcinkiewicz strong law of large numbers for weighted sums of extended negatively dependent random variables. Furthermore, our results extend strong law of large numbers for some sequences of random variables from the traditional probability space to the sublinear expectation space context.

scholarly journals Exploration of Free Energy Surface and Thermal Effects on Relative Population and Infrared Spectrum of the Be6B11− Fluxional Cluster

Materials ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 112
Author(s):  
Carlos Emiliano Buelna-Garcia ◽  
José Luis Cabellos ◽  
Jesus Manuel Quiroz-Castillo ◽  
Gerardo Martinez-Guajardo ◽  
Cesar Castillo-Quevedo ◽  
...  
Keyword(s):  
Free Energy ◽  
Infrared Spectrum ◽  
Infrared Spectra ◽  
Thermal Effects ◽  
Global Minimum ◽  
Energy Surface ◽  
Weighted Sums ◽  
Free Energy Surface ◽  
Temperature Dependent ◽  
Relative Population

The starting point to understanding cluster properties is the putative global minimum and all the nearby local energy minima; however, locating them is computationally expensive and difficult. The relative populations and spectroscopic properties that are a function of temperature can be approximately computed by employing statistical thermodynamics. Here, we investigate entropy-driven isomers distribution on Be6B11− clusters and the effect of temperature on their infrared spectroscopy and relative populations. We identify the vibration modes possessed by the cluster that significantly contribute to the zero-point energy. A couple of steps are considered for computing the temperature-dependent relative population: First, using a genetic algorithm coupled to density functional theory, we performed an extensive and systematic exploration of the potential/free energy surface of Be6B11− clusters to locate the putative global minimum and elucidate the low-energy structures. Second, the relative populations’ temperature effects are determined by considering the thermodynamic properties and Boltzmann factors. The temperature-dependent relative populations show that the entropies and temperature are essential for determining the global minimum. We compute the temperature-dependent total infrared spectra employing the Boltzmann factor weighted sums of each isomer’s infrared spectrum and find that at finite temperature, the total infrared spectrum is composed of an admixture of infrared spectra that corresponds to the spectra of the lowest-energy structure and its isomers located at higher energies. The methodology and results describe the thermal effects in the relative population and the infrared spectra.

scholarly journals Quantifying the signals contained in heterogeneous neural responses and determining their relationships with task performance

2014 ◽  
Vol 112 (6) ◽  
pp. 1584-1598 ◽  
Author(s):  
Marino Pagan ◽  
Nicole C. Rust
Keyword(s):  
Task Performance ◽  
Single Neuron ◽  
Weighted Sums ◽  
Neural Responses ◽  
Signal Modulation ◽  
Neural Data ◽  
Match To Sample ◽  
Neural Populations ◽  
Different Types ◽  
High Level

The responses of high-level neurons tend to be mixtures of many different types of signals. While this diversity is thought to allow for flexible neural processing, it presents a challenge for understanding how neural responses relate to task performance and to neural computation. To address these challenges, we have developed a new method to parse the responses of individual neurons into weighted sums of intuitive signal components. Our method computes the weights by projecting a neuron's responses onto a predefined orthonormal basis. Once determined, these weights can be combined into measures of signal modulation; however, in their raw form these signal modulation measures are biased by noise. Here we introduce and evaluate two methods for correcting this bias, and we report that an analytically derived approach produces performance that is robust and superior to a bootstrap procedure. Using neural data recorded from inferotemporal cortex and perirhinal cortex as monkeys performed a delayed-match-to-sample target search task, we demonstrate how the method can be used to quantify the amounts of task-relevant signals in heterogeneous neural populations. We also demonstrate how these intuitive quantifications of signal modulation can be related to single-neuron measures of task performance ( d′).

scholarly journals A Note on the Rate of Strong Convergence for Weighted Sums of Arrays of Rowwise Negatively Orthant Dependent Random Variables

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Qingxia Zhang ◽  
Dingcheng Wang
Keyword(s):  
Strong Convergence ◽  
Open Problem ◽  
Random Variables ◽  
Weighted Sums ◽  
Dependent Random Variables

Let{Xni;i≥1,n≥1}be an array of rowwise negatively orthant dependent (NOD) random variables. The authors discuss the rate of strong convergence for weighted sums of arrays of rowwise NOD random variables and solve an open problem posed by Huang and Wang (2012).

A note on seasonal Markov chains with gamma or gamma-like distributions

1979 ◽  
Vol 16 (1) ◽  
pp. 117-128 ◽  
Author(s):  
E. H. Lloyd ◽  
S. D. Saleem
Keyword(s):  
Markov Chain ◽  
Laplace Transform ◽  
Weighted Sums ◽  
Power Transformation ◽  
Exponential Form ◽  
Continuous State ◽  
Bessel Distribution ◽  
Storage Theory ◽  
Special Case ◽  
Type Of Transition

Weighted sums defined on a Markov chain (MC) are important in applications (e.g. to reservoir storage theory). The rather intractable theory of such sums simplifies to some extent when the transition p.d.f. of the chain {Xt} has a Laplace transform (LT) L(Xt+1; θ |Χ t=x) of the ‘exponential' form H(θ) exp{ – G(θ)x}. An algorithm is derived for the computation of the LT of Σat,Χ t for this class, and for a seasonal generalization of it.A special case of this desirable exponential type of transition LT for a continuous-state discrete-time MC is identified by comparison with the LT of the Bessel distribution. This is made the basis for a new derivation of a gamma-distributed MC proposed by Lampard (1968).A seasonal version of this process is developed, valid for any number of seasons.Reference is made to related chains with three-parameter gamma-like distributions (of the Kritskii–Menkel family) that may be generated from the above by a simple power transformation.

Some mean convergence theorems for weighted sums of Banach space valued random elements

Stochastics ◽  
2021 ◽  
pp. 1-19
Author(s):  
Pingyan Chen ◽  
Manuel Ordóñez Cabrera ◽  
Andrew Rosalsky ◽  
Andrei Volodin
Keyword(s):  
Banach Space ◽  
Weighted Sums ◽  
Convergence Theorems ◽  
Mean Convergence ◽  
Random Elements
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