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Noise and Fluctuations in Nanowire Biosensors★

2015
*
IFAC-PapersOnLine
*

*The*objective is an

*analysis*

*of*

*the*fluctuations and

*of*

*the*biological noise induced by

*the*inherent

*randomness*

*of*

*the*hybridization process at

*the*surface. ... This work deals with

*the*stochastic simulation

*of*

*a*nanowire biosensor surface and

*the*surrounding liquid domain

*for*DNA detection. ... Signal-to-Noise ratio

*The*signal-to-noise ratio is an important quantity in sensor design, since it is

*a*measure

*for*

*the*quality

*of*

*a*signal and

*determines*

*the*treshold

*for*distinguishing it

*from*noise ...

##
###
Intricacies of quantum computational paths

2012
*
Quantum Information Processing
*

Graph search represents

doi:10.1007/s11128-012-0475-7
fatcat:o6bgjbwsovdytcgagqywvnemk4
*a*cornerstone in computer science and is employed when*the*best*algorithmic*solution to*a*problem consists in performing an*analysis**of**a*search space representing computational ... We discuss*the*different scenarios that are better suited*for*each approach. Keywords quantum computational paths · quantum*random**walks*· quantum search ... Table 1 : 1 Operator sequence*for**the*modified quantum*random**walk*search*algorithm*. ...##
###
Analysis of a Monte Carlo boundary propagation method

1996
*
Computers and Mathematics with Applications
*

*The*new approach reduces

*the*computational complexity

*of*

*the*length

*of*

*a*

*random*

*walk*by one order

*of*magnitude as compared to

*a*standard method described in many text books. ... Also,

*the*number

*of*

*walks*necessary to achieve

*a*desired accuracy is reduced. ... On

*the*other hand,

*the*MCBP method, using

*a*similar

*analysis*, has an average

*random*

*walk*length

*of*WMCBP = 0.37L, (2)

*for*L ranging

*from*4 to 256. ...

##
###
Graph-Based Ascent Algorithms for Function Maximization
[article]

2018
*
arXiv
*
pre-print

We focus on local iterative

arXiv:1802.04475v1
fatcat:lwf2w6dkendnhm5l5ecp7jji44
*algorithms*, which traverse*the*nodes*of**the*graph along*a*path, and*the*next iterate is chosen*from**the*neighbors*of**the*current iterate with probability distribution*determined*... We study two*algorithms*corresponding to*a*Metropolis-Hastings*random**walk*with different transition kernels: (i)*The*first*algorithm*is an exponentially weighted*random**walk*governed by*a*parameter γ. ...*The**algorithms*were run till*the**random**walk*"hit"*the**maximum*, or up to*a**maximum**of*10, 000 steps. ...##
###
A Token-Based Approach for Distributed Computation in Sensor Networks

2011
*
IEEE Journal on Selected Topics in Signal Processing
*

Examples

doi:10.1109/jstsp.2011.2125776
fatcat:hwkdhse5qrcrnb6y6opthkxjl4
*of*such*algorithms*include Simple-*Random**Walk*(SRW), Coalescent-*Random*-*Walk*(CRW), and Controlled Flooding (CFLD) and their hybrid variants. ... We consider distributed*algorithms**for*data aggregation and function computation in sensor networks.*The**algorithms*perform pairwise computations along edges*of*an underlying communication graph. ... Section VI gives*a*novel*analysis**of*coalescing*random**walks*on arbitrary graphs and thereby*determines**the*complexity*of*CRW in*the*general setting. II. ...##
###
An HHL-Based Algorithm for Computing Hitting Probabilities of Quantum Random Walks
[article]

2020
*
arXiv
*
pre-print

We present

arXiv:2009.03618v1
fatcat:y5kk7vxfw5gsjocyrpex222piy
*a*novel application*of**the*HHL (Harrow-Hassidim-Lloyd)*algorithm*--*a*quantum*algorithm*solving systems*of*linear equations -- in solving an open problem about quantum*random**walks*, namely computing ... This is achieved by*a*simple observation that*the*problem*of*computing hitting probabilities*of*quantum*random**walks*can be reduced to inverting*a*matrix. ... ACKNOWLEDGMENTS*The*authors are very grateful to Professor Andris Ambainis*for*helpful discussions. ...##
###
Critical behaviour of the Edwards random walk in two dimensions: a case where the fractal and Hausdorff dimensions are not equal

1988
*
Journal of Physics A: Mathematical and General
*

We establish that

doi:10.1088/0305-4470/21/19/015
fatcat:xotailocs5gcdia5ifrgd5pfri
*the*fractal dimension computed in terms*of*critical exponents is different*from**the*HausdorR dimension computed by measure-theoretic methods. ... We study by Monte Carlo simulations, using two different*algorithms*,*the*Edwards*walk*in two dimensions and extract its critical exponents. ... Acknowledgments Part*of**the*computer time necessary*for**the*simulations was provided through*a*grant*of**the*Minnesota Supercomputer Institute. ...##
###
Bayesian Discovery of Threat Networks

2014
*
IEEE Transactions on Signal Processing
*

*A*novel unified Bayesian framework

*for*network detection is developed, under which

*a*detection

*algorithm*is derived based on

*random*

*walks*on graphs. ...

*A*link to well-known spectral detection methods is provided, and

*the*equivalence

*of*

*the*

*random*

*walk*and harmonic solutions to

*the*Bayesian formulation is proven. ... Fig. 1 . 1 Illustration

*of*

*the*

*random*

*walk*representation

*for*threat propagation

*from*Definition 6 and Eqs. (11) and (33) ,

*for*

*the*case

*of*

*a*single observation. ...

##
###
A Spectrum of Time–Space Trade-offs for Undirecteds-tConnectivity

1997
*
Journal of computer and system sciences (Print)
*

In passing, we also improve previous results regarding

doi:10.1006/jcss.1997.1471
fatcat:uf5k7ro7rzg7lfmuz4qhhushje
*the*rate at which*a**random**walk*discovers new vertices in*a*graph. ] 1997 Academic Press Input to*the**algorithm*. ... Our trade-offs cover*the*whole range between breadth first search and*the**random**walk*procedure*of*Aleliunas et al., and achieve*a*time-space product*of*O (mn) (where n is*the*number*of*vertices in*the*... Their*algorithm*performs*a**random**walk*on*the*vertices*of*G, where at each time step*the**walk*moves to*a*vertex chosen uniformly at*random**from**the*neighbors*of**the*current vertex. Aleliunas et al. ...##
###
Identifying and evaluating community structure in complex networks

2010
*
Pattern Recognition Letters
*

We compare and evaluate different metrics

doi:10.1016/j.patrec.2009.11.001
fatcat:p2wah4cosrcxjgujtuc6tcuyne
*for*community structure in networks. ... In this context we also discuss*a*simple approach to community detection, and show that it performs as well as other methods, but at lower computational complexity. ...*The*authors are also thankful to László Barabási*for*providing*the*cell phone data. This work was supported in part by*the*National Science Foundation under Grant No. 0826958. ...##
###
Local correctability of expander codes

2015
*
Information and Computation
*

This yields

doi:10.1016/j.ic.2014.12.013
fatcat:4kwz46gddra3pgwipxbdh4nr4e
*a*new family*of**constant*-rate codes that can recover*from**a**constant*fraction*of*errors in*the*codeword symbols, and where any symbol*of**the*codeword can be recovered with high probability ... In this work, we present*the*first local-decoding*algorithm**for*expander codes. ... . , v L be*a**random**walk**of*length L on H, starting*from**the*left side at*a*vertex chosen*from**a*distribution ν with ν − 1 n 1 n 2 ≤ 1 √ n . ...##
###
Local Correctability of Expander Codes
[chapter]

2013
*
Lecture Notes in Computer Science
*

This yields

doi:10.1007/978-3-642-39206-1_46
fatcat:t4jsddzw3bggrldnizz3aecxkq
*a*new family*of**constant*-rate codes that can recover*from**a**constant*fraction*of*errors in*the*codeword symbols, and where any symbol*of**the*codeword can be recovered with high probability ... In this work, we present*the*first local-decoding*algorithm**for*expander codes. ... . , v L be*a**random**walk**of*length L on H, starting*from**the*left side at*a*vertex chosen*from**a*distribution ν with ν − 1 n 1 n 2 ≤ 1 √ n . ...##
###
Monte Carlo Algorithms for Finding the Maximum of a Random Walk with Negative Drift

2006
*
Journal of Applied Probability
*

We discuss two Monte Carlo

doi:10.1239/jap/1143936244
fatcat:yg3ufabfavbwjes6ywfdrcjgzq
*algorithms**for*finding*the*global*maximum**of**a*simple*random**walk*with negative drift. ... This problem can be used to connect*the**analysis**of**random*input Monte Carlo*algorithms*with ideas and principles*from*mathematical statistics. ... This implies that P(T N > n) = Finding*the**maximum**of**a**random**walk*83 Because p/q ≤ 2 √ pq, we therefore have P(T N > n) ≤ c 3 (2 √ pq) n*for*all n ∈ N,*for*some positive*constant*c 3 . ...##
###
Monte Carlo Algorithms for Finding the Maximum of a Random Walk with Negative Drift

2006
*
Journal of Applied Probability
*

We discuss two Monte Carlo

doi:10.1017/s0021900200001376
fatcat:dsyacr3xijdbxoxr4yikrvxkli
*algorithms**for*finding*the*global*maximum**of**a*simple*random**walk*with negative drift. ... This problem can be used to connect*the**analysis**of**random*input Monte Carlo*algorithms*with ideas and principles*from*mathematical statistics. ... This implies that P(T N > n) = Finding*the**maximum**of**a**random**walk*83 Because p/q ≤ 2 √ pq, we therefore have P(T N > n) ≤ c 3 (2 √ pq) n*for*all n ∈ N,*for*some positive*constant*c 3 . ...##
###
Monte Carlo Matrix Inversion Policy Evaluation
[article]

2012
*
arXiv
*
pre-print

In 1950, Forsythe and Leibler (1950) introduced

arXiv:1212.2471v1
fatcat:aghqtwdy5ndjlmszz563p73ibq
*a*statistical technique*for*finding*the*inverse*of**a*matrix by characterizing*the*elements*of**the*matrix inverse as expected values*of**a*sequence*of**random*...*walks*. ... derived*from**a*single*random**walk*to equal*the*number*of*steps in that*walk*. ...
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