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Noise and Fluctuations in Nanowire Biosensors★

Gerhard Tulzer, Clemens Heitzinger
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  ... 
doi:10.1016/j.ifacol.2015.05.079 fatcat:ef26shnmtvafpe74i5ns2v2x5e

Intricacies of quantum computational paths

Luís Tarrataca, Andreas Wichert
2012 Quantum Information Processing  
Graph search represents 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.  ... 
doi:10.1007/s11128-012-0475-7 fatcat:o6bgjbwsovdytcgagqywvnemk4

Analysis of a Monte Carlo boundary propagation method

M.D. Gunzburger, R.E. Hiromoto, M.O. Mundt
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.  ... 
doi:10.1016/0898-1221(96)00006-5 fatcat:2dwn5gzndfdoridgzk3wev2bwe

Graph-Based Ascent Algorithms for Function Maximization [article]

Muni Sreenivas Pydi, Varun Jog, Po-Ling Loh
2018 arXiv   pre-print
We focus on local iterative 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.  ... 
arXiv:1802.04475v1 fatcat:lwf2w6dkendnhm5l5ecp7jji44

A Token-Based Approach for Distributed Computation in Sensor Networks

Venkatesh Saligrama, Murat Alanyali
2011 IEEE Journal on Selected Topics in Signal Processing  
Examples 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.  ... 
doi:10.1109/jstsp.2011.2125776 fatcat:hwkdhse5qrcrnb6y6opthkxjl4

An HHL-Based Algorithm for Computing Hitting Probabilities of Quantum Random Walks [article]

Ji Guan, Qisheng Wang, Mingsheng Ying
2020 arXiv   pre-print
We present 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.  ... 
arXiv:2009.03618v1 fatcat:y5kk7vxfw5gsjocyrpex222piy

Critical behaviour of the Edwards random walk in two dimensions: a case where the fractal and Hausdorff dimensions are not equal

P de Forcrand, J Pasche, D Petritis
1988 Journal of Physics A: Mathematical and General  
We establish that 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.  ... 
doi:10.1088/0305-4470/21/19/015 fatcat:xotailocs5gcdia5ifrgd5pfri

Bayesian Discovery of Threat Networks

Steven T. Smith, Edward K. Kao, Kenneth D. Senne, Garrett Bernstein, Scott Philips
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.  ... 
doi:10.1109/tsp.2014.2336613 fatcat:j5vivxxm3bgjtfnxgsmbi4euqe

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

Uriel Feige
1997 Journal of computer and system sciences (Print)  
In passing, we also improve previous results regarding 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.  ... 
doi:10.1006/jcss.1997.1471 fatcat:uf5k7ro7rzg7lfmuz4qhhushje

Identifying and evaluating community structure in complex networks

Karsten Steinhaeuser, Nitesh V. Chawla
2010 Pattern Recognition Letters  
We compare and evaluate different metrics 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.  ... 
doi:10.1016/j.patrec.2009.11.001 fatcat:p2wah4cosrcxjgujtuc6tcuyne

Local correctability of expander codes

Brett Hemenway, Rafail Ostrovsky, Mary Wootters
2015 Information and Computation  
This yields 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 .  ... 
doi:10.1016/j.ic.2014.12.013 fatcat:4kwz46gddra3pgwipxbdh4nr4e

Local Correctability of Expander Codes [chapter]

Brett Hemenway, Rafail Ostrovsky, Mary Wootters
2013 Lecture Notes in Computer Science  
This yields 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 .  ... 
doi:10.1007/978-3-642-39206-1_46 fatcat:t4jsddzw3bggrldnizz3aecxkq

Monte Carlo Algorithms for Finding the Maximum of a Random Walk with Negative Drift

Ludwig Baringhaus, Rudolf Grübel
2006 Journal of Applied Probability  
We discuss two Monte Carlo 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 .  ... 
doi:10.1239/jap/1143936244 fatcat:yg3ufabfavbwjes6ywfdrcjgzq

Monte Carlo Algorithms for Finding the Maximum of a Random Walk with Negative Drift

Ludwig Baringhaus, Rudolf Grübel
2006 Journal of Applied Probability  
We discuss two Monte Carlo 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 .  ... 
doi:10.1017/s0021900200001376 fatcat:dsyacr3xijdbxoxr4yikrvxkli

Monte Carlo Matrix Inversion Policy Evaluation [article]

Fletcher Lu, Dale Schuurmans
2012 arXiv   pre-print
In 1950, Forsythe and Leibler (1950) introduced 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.  ... 
arXiv:1212.2471v1 fatcat:aghqtwdy5ndjlmszz563p73ibq
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