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A monte-carlo algorithm FOR ESTIMATING THE PERMANENT

SIAM JOURNAL ON COMPUTING 1993年第2期22卷 284-293页

作者： KARMARKAR, N KARP, R LIPTON, R LOVASZ, L LUBY, M UNIV CALIF BERKELEY DIV COMP SCIBERKELEYCA 94720 PRINCETON UNIV DEPT COMP SCIPRINCETONNJ 08544 HUNGARIAN ACAD SCI H-1051 BUDAPESTHUNGARY INT COMP SCI INST BERKELEYCA 94720

Let A be an n x n matrix with 0-1 valued entries, and let per(A) be the permanent of A. This paper describes a monte-carlo algorithm that produces a ''good in the relative sense'' estimate of per(A) an... 详细信息

关键词： PERMANENT MATCHING monte-carlo algorithm algorithm BIPARTITE GRAPH DETERMINANT

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monte-carlo algorithm for line-by-line calculations of thermal radiation in multiple scattering layered atmospheres

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JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER 2006年第1期98卷 107-115页

作者： Fomin, BA CPTEC INPE BR-12630000 Sao Paulo Brazil

An algorithm for calculations of the longwave radiation in cloudy and aerosol slab atmospheres is described. It is based on the line-by-line and monte-carlo methods and is suitable for accurate treatment of both the gaseous absorption and the particulate multiple scattering in any spectral regions;other published algorithms as accurate as this can only make calculations in narrow spectral regions. It is recommended that this algorithm is well suited for radiation code validations as well as for theoretical investigations of radiative transfer in clouds and aerosols and satellite signal simulations. (c) 2005 Elsevier Ltd. All rights reserved.

关键词： atmospheric radiation longwave scattering and absorption line-by-line calculations monte-carlo algorithm

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An algebraic monte-carlo algorithm for the partition adjacency matrix realization problem

Algebraic Statistics

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Algebraic Statistics 2021年第2期12卷 115-124页

作者： Éva Czabarka László Székely Zoltán Toroczkai Shanise Walker Department of Mathematics University of South Carolina Columbia SC United States Visiting Professor Department of Pure and Applied Mathematics University of Johannesburg South Africa Department of Physics Department of Computer Science and Engineering University of Notre Dame IN United States Department of Mathematics University of Wisconsin-Eau Claire WI United States

The graphical realization of a given degree sequence and given partition adjacency matrix simultaneously, is a relevant problem in data driven modeling of networks. Here we formulate common generalizations of this problem and the exact matching problem, and solve them with an algebraic monte-carlo algorithm that runs in polynomial time if the number of partition classes is bounded by a constant. We note, that no deterministic polynomial time algorithm is known for any of these problems.

关键词： perfect matching exact matching degree sequence bipartite graph Hall's theorem joint degree matrix partition adjacency matrix monte-carlo algorithm computational complexity

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Coordination of repeaters based on Simulated Annealing algorithm and monte-carlo algorithm

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Neurocomputing 2012年 97卷 9-15页

作者： Ya Cai Yuanqing Xia Li Dai Chi Xiao Jiaxiang Wu School of Automation Beijing Institute of Technology Beijing 100081 PR China

This paper considers the design of repeaters network in both flat and mountainous area. The main purpose is to design a network that is not only able to accommodate the communication need of all users in a certain area, but also with lower cost than previous design methods of the network. Considering the propagation and attenuation of radio signals, the problem can be transformed to search for best locations of centers of circles in order to reach maximum coverage percent in the whole area. Applying the Simulated Annealing algorithm and monte-carlo algorithm, numerical examples are given to show the potential of the proposed techniques. Compared with previous method, our proposed method shows its effectiveness.

关键词： Repeaters network Wireless communication Simulated Annealing algorithm monte-carlo algorithm

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Feasibility of monte-carlo algorithm in comparison with collapse-cone dose calculation algorithm of a commercial treatment planning system in the presence of high-density metallic implant: a dosimetric study

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JOURNAL OF THE EGYPTIAN NATIONAL CANCER INSTITUTE 2021年第1期33卷 2-2页

作者： Bhushan, Manindra Tripathi, Deepak Yadav, Girigesh Kumar, Lalit Chowdhary, Rahul Lal Pahuja, Anjali K. Suresh, Tamilarasu Shukla, Sushil Kumar Mitra, Swarupa Rajiv Gandhi Canc Inst & Res Ctr Div Med Phys Sect 5 New Delhi 110085 India Rajiv Gandhi Canc Inst & Res Ctr Dept Radiat Oncol Sect 5 New Delhi 110085 India Amity Univ AUUP Amity Sch Appl Sci Noida India Dr APJ Abdul Kalam Tech Univ Lucknow Uttar Pradesh India

Background The number of people with implanted hip prosthesis has grown worldwide. For radiotherapy planning of patients with hip implants, few main challenges are encountered. The aim of the present study was to evaluate the feasibility of different planning algorithms in the presence of high-density metallic implant in the treatment of patients with carcinoma cervix. Results It was found that D-98% were 44.49 +/- 0.11, 44.51 +/- 0.13, 44.39 +/- 0.22, and 44.45 +/- 0.16 Gy for 4FMC6MV (4-field technique calculated with monte-carlo algorithm and 6 MV photon energy), 4FMC6MV_WP (4-field technique calculated with monte-carlo algorithm and 6 MV photon energy without prosthesis), 4FCC6MV (4-field technique calculated with collapse-cone-convolution algorithm and 6 MV photon energy), and 4FCC6MV_WP (4-field technique calculated with collapse-cone-convolution algorithm and 6 MV photon energy without prosthesis) respectively. Similarly, D-2% were 49.40 +/- 0.84, 49.05 +/- 0.76, 48.97 +/- 0.91, and 48.57 +/- 0.85 Gray (Gy) for 4FMC6MV, 4FMC6MV_WP, 4FCC6MV, and 4FCC6MV_WP respectively. The present study has not suggested any major difference between the monte-carlo (MC) and collapse-cone-convolution (CCC) calculation algorithm in the presence of high-Z metallic implants. Volume of bowel receiving 15 Gy dose has shown a significant difference with prosthesis cases. This study investigates that hip prosthesis creates considerable changes in the treatment planning of cervical malignancies. Conclusion CCC algorithm is in good agreement with MC calculation algorithm in the presence of high-density metallic implants in terms of target coverage and avoidance organ sparing except few parameters.

关键词： Implant Collapse-cone-convolution Box technique monte-carlo algorithm Carcinoma cervix

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Parameter optimization of thermal network model for aerial cameras utilizing monte-carlo and genetic algorithm

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SCIENTIFIC REPORTS 2024年第1期14卷 1-18页

作者： Fan, Yue Feng, Wei Ren, Zhenxing Liu, Bingqi Huang, Long Wang, Dazhi Chengdu Univ Coll Mech Engn Chengdu 610106 Sichuan Peoples R China Chinese Acad Sci Inst Opt & Elect Chengdu 610209 Sichuan Peoples R China

It is crucial to precisely calculate temperature utilizing thermal models, which require the determination of thermal parameters that optimally align model outcomes with experimental data. In many instances, the refinement of these models is undertaken within space instruments. This paper introduces an optimization methodology for thermal network models, with the objective of enhancing the accuracy of temperature predictions for aerial cameras. The investigation of internal convective heat transfer coefficients for both cylindrical and planar structures provides an estimation of convective thermal parameters. Based on the identification of thermally sensitive parameters and the reliability evaluation of transient temperature data through the monte-carlo simulation, the genetic algorithm is employed to search for global optimal parameter values that minimize the root mean square error (RMSE) between calculated and measured node temperatures. As a result, the optimized model shows significantly improved accuracy in temperature prediction, attaining an RMSE of 1.07 degrees C and reducing the maximum relative error between predicted and experimental results from 33.8 to 3.1%. Furthermore, the flight simulation and thermal control experiments validate the robustness of the optimized model, demonstrating that discrepancies between the observed and predicted temperatures are within 2 degrees C after re-correcting the external convection heat transfer coefficient value.

关键词： Aerial camera Thermal network model Parameter optimization monte-carlo algorithm Genetic algorithm

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Exploiting the polyhedral geometry of stochastic linear bilevel programming

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MATHEMATICAL PROGRAMMING 2025年第1-2期210卷 695-730页

作者： Munoz, Gonzalo Salas, David Svensson, Anton Univ O Higgins Engn Sci Inst Rancagua Chile

We study linear bilevel programming problems whose lower-level objective is given by a random cost vector with known distribution. We consider the case where this distribution is nonatomic, allowing to reformulate the problem of the leader using the Bayesian approach in the sense of Salas and Svensson (SIAM J Optim 33(3):2311-2340, 2023), with a decision-dependent distribution that concentrates on the vertices of the feasible set of the follower's problem. We call this a vertex-supported belief. We prove that this formulation is piecewise affine over the so-called chamber complex of the feasible set of the high-point relaxation. We propose two algorithmic approaches to solve general problems enjoying this last property. The first one is based on enumerating the vertices of the chamber complex. This approach is not scalable, but we present it as a computational baseline and for its theoretical interest. The second one is a monte-carlo approximation scheme based on the fact that randomly drawn points of the domain lie, with probability 1, in the interior of full-dimensional chambers, where the problem (restricted to this chamber) can be reduced to a linear program. Finally, we evaluate these methods through computational experiments showing both approaches' advantages and challenges.

关键词： Bilevel programming Bayesian approach Chamber complex Enumeration algorithm monte-carlo algorithm

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Optimization using pathwise algorithmic derivatives of electromagnetic shower simulations

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COMPUTER PHYSICS COMMUNICATIONS 2025年 309卷

作者： Aehle, Max Novak, Mihaly Vassilev, Vassil Gauger, Nicolas R. Heinrich, Lukas Kagan, Michael Lange, David Univ Kaiserslautern Landau RPTU Gottlieb Daimler Str 42 D-67663 Kaiserslautern Germany European Org Nucl Res CERN Esplanade Particules 1 CH-1217 Geneva Switzerland Princeton Univ Dept Phys Jadwin HallWashington Rd Princeton NJ 08544 USA Tech Univ Munich Arcisstr 21 D-80333 Munich Germany SLAC Natl Accelerator Lab 2575 Sand Hill Rd Menlo Pk CA 94025 USA

Among the well-known methods to approximate derivatives of expectancies computed by monte-carlo simulations, averages of pathwise derivatives are often the easiest one to apply. Computing them via algorithmic differentiation typically does not require major manual analysis and rewriting of the code, even for very complex programs like simulations of particle-detector interactions in high-energy physics. However, the pathwise derivative estimator can be biased if there are discontinuities in the program, which may diminish its value for applications. This work integrates algorithmic differentiation into the electromagnetic shower simulation code HepEmShow based on G4HepEm, allowing us to study how well pathwise derivatives approximate derivatives of energy depositions in a sampling calorimeter with respect to parameters of the beam and geometry. We found that when multiple scattering is disabled in the simulation, means of pathwise derivatives converge quickly to their expected values, and these are close to the actual derivatives of the energy deposition. Additionally, we demonstrate the applicability of this novel gradient estimator for stochastic gradient-based optimization in a model example.

关键词： Automatic differentiation Differentiable programming Gradient estimation monte-carlo algorithm High-energy physics Sampling calorimeter

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Comparison of Pencil-beam, Collapsed-cone and monte-carlo algorithms in Radiotherapy Treatment Planning for 6-MV photons

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JOURNAL OF THE KOREAN PHYSICAL SOCIETY 2015年第1期67卷 153-158页

作者： Kim, Sung Jin Kim, Sung Kyu Kim, Dong Ho Yeungnam Univ Dept Phys Gyongsan 712749 South Korea Eulji Univ Hosp Dept Radiat Oncol Daejeon 302799 South Korea Yeungnam Univ Dept Radiat Oncol Coll Med Taegu 705717 South Korea

Treatment planning system calculations in inhomogeneous regions may present significant inaccuracies due to loss of electronic equilibrium. In this study, three different dose calculation algorithms, pencil beam (PB), collapsed cone (CC), and monte-carlo (MC), provided by our planning system were compared to assess their impact on the three-dimensional planning of lung and breast cases. A total of five breast and five lung cases were calculated by using the PB, CC, and MC algorithms. Planning treatment volume (PTV) and organs at risk (OARs) delineations were performed according to our institution's protocols on the Oncentra MasterPlan image registration module, on 0.3 - 0.5 cm computed tomography (CT) slices taken under normal respiration conditions. Intensity-modulated radiation therapy (IMRT) plans were calculated for the three algorithm for each patient. The plans were conducted on the Oncentra MasterPlan (PB and CC) and CMS Monaco (MC) treatment planning systems for 6 MV. The plans were compared in terms of the dose distribution in target, the OAR volumes, and the monitor units (MUs). Furthermore, absolute dosimetry was measured using a three-dimensional diode array detector (ArcCHECK) to evaluate the dose differences in a homogeneous phantom. Comparing the dose distributions planned by using the PB, CC, and MC algorithms, the PB algorithm provided adequate coverage of the PTV. The MUs calculated using the PB algorithm were less than those calculated by using. The MC algorithm showed the highest accuracy in terms of the absolute dosimetry. Differences were found when comparing the calculation algorithms. The PB algorithm estimated higher doses for the target than the CC and the MC algorithms. The PB algorithm actually overestimated the dose compared with those calculated by using the CC and the MC algorithms. The MC algorithm showed better accuracy than the other algorithms.

关键词： Dose calculation algorithm Collapsed cone algorithm monte-carlo algorithm

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monte-carlo based random passive energy beamforming for reconfigurable intelligent surface assisted wireless power transfer

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Digital Communications and Networks 2023年第3期9卷 667-676页

作者： Ziyang Lu Yubin Zhao Xiaofan Li School of Microelectronics Science and Technology Sun Yat-Sen UniversityZhuhai519082China School of Intelligent System Science and Engineering Jinan UniversityZhuhai519070China

Reconfigurable intelligent surface(RIS)employs passive beamforming to control the wireless propagation channel,which benefits the wireless communication capacity and the received energy efficiency of wireless power transfer(WPT)*** beamforming schemes are classified as discrete and non-convex integer program-ming *** this paper,we propose a monte-carlo(MC)based random energy passive beamforming of RIS to achieve the maximum received power of electromagnetic(EM)WPT ***,the Gibbs sampling and re-sampling methods are employed to generate phase shift vector *** the sample with the maximum received power is considered the optimal *** order to adapt to the application scenarios,we develop two types of passive beamforming algorithms based on such MC sampling *** first passive beamforming uses an approximation of the integer programming as the initial sample,which is calculated based on the channel *** the second one is a purely randomized algorithm with the only total received power *** proposed methods present several advantages for RIS control,e.g.,fast convergence,easy implementation,robustness to the channel noise,and limited feedback requirement,and they are applicable even if the channel information is *** to the simulation results,our proposed methods outperform other approxi-mation and genetic *** our methods,the WPT system even significantly improves the power effi-ciency in the nonline-of-sight(NLOS)environment.

关键词： Reconfigurable intelligence surface Wireless power transfer monte-carlo algorithm Passive beamforming Gibbs sampling

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