Monte Carlo - Science topic

For the different branches of science, we need to know accurately all possible reactions and collisional cross sections. Although the last decades, were a trial of a large-scale study to provide this data, still many basic atomic and molecular cross section data are missing and the accuracy of the available cross sections needs to be checked. In th...

Design waves have been used in the past for the probabilistic assessment of wave-induced loads and responses of offshore structures. Various response-conditioning techniques have been employed to determine suitable wave episodes, typically based on linear response transfer functions. Nevertheless, extreme events are not always driven by linear phen...

Monte Carlo radiation transport simulation codes are widely used for dose evaluation in various radiation therapies owing to their high precision. Several tools have been developed for automatically converting SPECT/CT and PET/CT images into input files for these Monte Carlo codes. These tools can be used for dose evaluation in nuclear medicine. In...

The performance of sequential Monte Carlo (SMC) samplers heavily depends on the tuning of the Markov kernels used in the path proposal. For SMC samplers with unadjusted Markov kernels, standard tuning objectives, such as the Metropolis-Hastings acceptance rate or the expected-squared jump distance, are no longer applicable. While stochastic gradien...

Volume rendering techniques for scientific visualization have increasingly transitioned toward Monte Carlo (MC) methods in recent years due to their flexibility and robustness. However, their application in multi-channel visualization remains underexplored. Traditional compositing-based approaches often employ arbitrary color blending functions, wh...

This study investigated the shielding properties of five glass samples (same molecular composition, varying component percentages) against nuclear radiation using Geant4 Monte Carlo. Calculations determined the linear attenuation coefficient, MFP, TVL, and HVL for the samples against \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wa...

This study employs the Blume–Emery–Griffiths model and applies Monte Carlo simulations to investigate the dielectric properties of fullerene C60, drawing an analogy between magnetic properties by applying an external magnetic field and dielectric properties by applying an external electric field. The analysis examines thermal behavior and electric...

Background Alzheimer's disease (AD) is a severe neurodegenerative disorder, yet its molecular mechanisms remain incompletely understood. It is known that the joint action of a number of genetic and other factors is involved in the pathogenesis of this disorder. Objective In the past years, extensive research has focused on identifying novel AD pre...

Tanah lunak yang memiliki daya dukung rendah menjadi tantangan dalam konstruksi infrastruktur seperti Jalan Tol Kayu Agung–Palembang–Betung. Penelitian ini bertujuan untuk menganalisis metode perbaikan tanah yang paling efisien berbasis pendekatan Value engineering (VE), mengevaluasi risiko yang mungkin terjadi dari tiap metode, serta mensimulasika...

In this paper, we thoroughly examined the Berezinskii-Kosterlitz-Thouless (BKT) phase transition in the two-dimensional XY model on the honeycomb lattice. To address its thermodynamical behavior, we combined standard numerical Monte Carlo simulations with the simulated annealing (SA) protocol and entropic simulations based on the Wang-Landau (WL) a...

While LLMs excel at open-ended reasoning, they often struggle with cost-sensitive planning, either treating all actions as having equal cost or failing to stay within strict budgets. In this paper, we introduce Cost-Augmented Monte Carlo Tree Search (CATS), a novel approach that brings explicit cost-awareness into LLM-guided planning. Tight cost co...

Parton showers lie at the core of Shower Monte Carlo event generators, the default theoretical tools used to interpret collider data. In these proceedings, we summarise the strategy of the PanScales collaboration that led to the attainment of the first demonstrably next-to-next-to-leading-logarithmic accurate parton showers.

Operator learning is a rapidly growing field that aims to approximate nonlinear operators related to partial differential equations (PDEs) using neural operators. These rely on discretization of input and output functions and are, usually, expensive to train for large-scale problems at high-resolution. Motivated by this, we present a Multi-Level Mo...

During Gallium ⁶⁸ Ga-PSMA PET prostate imaging, the kidneys and liver tissue is the uptake amount of radioactive. The doses in the critical organs should be well determined due to the toxic effects of radiation exposure on the human body. The absorbed dose distribution in the liver and kidneys for ⁶⁸ Ga activity data and absorbed dose values were c...

A successful detection of the cosmological 21 cm signal from intensity mapping experiments (e.g., during the Epoch of Reionization or Cosmic Dawn) is contingent on the suppression of subtle systematic effects in the data. Some of these systematic effects, with mutual coupling a major concern in interferometric data, manifest with temporal variabili...

While Multimodal Large Language Models (MLLMs) have achieved impressive progress in vision-language understanding, they still struggle with complex multi-step reasoning, often producing logically inconsistent or partially correct solutions. A key limitation lies in the lack of fine-grained supervision over intermediate reasoning steps. To address t...

Entangled matter provides intriguing perspectives in terms of deformation mechanisms, mechanical properties, assembly and disassembly. However, collective entanglement mechanisms are complex, occur over multiple length scales, and they are not fully understood to this day. In this report, we propose a simple pick-up test to measure entanglement in...

We present a novel Monte Carlo implementation of the EKRT model, MC-EKRT, for computing partonic initial states in high-energy nuclear collisions. Our new MC-EKRT event generator is based on collinearly factorized, dynamically fluctuating perturbative QCD (pQCD) minijet production, supplemented with a saturation conjecture that controls the low- p...

In this paper, we fit the \(B\rightarrow D\) vector transition form factor (TFF) by using the data measured by BABAR and Belle Collaborations within Monte Carlo (MC) method. Meanwhile, the \(B\rightarrow D\) TFF is also calculated by using the QCD light-cone sum rules approach (LCSRs) within right-handed chiral current correlation function. In the...

This work introduces a new method called scalable Bayesian Monte Carlo (SBMC). The model interpolates between a point estimator and the posterior, and the algorithm is a parallel implementation of a consistent (asymptotically unbiased) Bayesian deep learning algorithm: sequential Monte Carlo (SMC) or Markov chain Monte Carlo (MCMC). The method is m...

Graphdiyne-like nanoribbons are promising for information retrieval, storage, and magnetic refrigeration due to their excellent magnetic and thermodynamic properties. In this paper, we build a ferrimagnetic mixed-spin (2, 5/2) Ising model for the bilayer graphdiyne-like nanoribbon. The instantaneous magnetization, dynamic order parameter, magnetic...

Importance sampling is a Monte Carlo technique for efficiently estimating the likelihood of rare events by biasing the sampling distribution towards the rare event of interest. By drawing weighted samples from a learned proposal distribution, importance sampling allows for more sample-efficient estimation of rare events or tails of distributions. A...

The Kohn-Sham density functional method for the fractional quantum Hall (FQH) effect has recently been developed by mapping the strongly interacting electrons into an auxiliary system of weakly interacting composite fermions (CFs) that experience a density-dependent effective magnetic field. This approach has been successfully applied to explore th...

The proximity effect induced by electron scattering is one of the main factors limiting the development of high-resolution electron beam lithography (EBL) technology. Existing proximity effect correction (PEC) methods often face challenges related to either high computational demands or insufficient accuracy when calculating the point spread functi...

We study the Hamiltonian flow for optimization (HF-opt), which simulates the Hamiltonian dynamics for some integration time and resets the velocity to $0$ to decrease the objective function; this is the optimization analogue of the Hamiltonian Monte Carlo algorithm for sampling. For short integration time, HF-opt has the same convergence rates as g...

We establish epigraphical and uniform laws of large numbers for sample-based approximations of law invariant composite risk functionals. These sample-based approximation schemes include Monte Carlo and certain randomized quasi-Monte Carlo integration methods, such as scrambled net integration. Our results can be applied to the approximation of risk...

Bearing fault diagnosis and prognosis are crucial for the effective management of industrial equipment. Due to the automatic feature extraction of Deep Learning (DL) models, many recent studies have focused on using DL for these tasks. However, most studies address only one of these tasks. This study aims to present DL models and their powerful ML...

The article sets out to clarify a number of confusions that exist in connection with the Born–Oppenheimer approximation (BOA) (Born-Oppenheimer, 1927). It is generally claimed that chemistry cannot be reduced to quantum mechanics because of the nature of this commonly used approximation in quantum chemistry, that is popularly believed to require a...

The He I line at 1.08 $\mu$m is a valuable tracer of atmospheric escape in exoplanet atmospheres. We expand past networks used to predict the absorbing He(2$^3S$) by including, firstly, processes that involve H$_2$ and some molecular ions and, secondly, the interaction of photoelectrons with the atmosphere. We survey the literature on the chemical-...

Accurate segmentation of skin lesions is a critical step in automated skin cancer diagnosis, enabling precise localization and characterization of suspicious regions. Traditional deterministic deep learning methods provide point estimates that may lack confidence measures, limiting clinical trust and robustness. Probabilistic deep learning models,...

We use Langevin dynamics (LD) simulations to investigate single-file diffusion (SFD) in a dilute solution of flexible linear polymers inside a narrow tube with periodic boundary conditions (a torus). The transition from SFD, where the time (t) dependence of the mean-square displacement scales like $\langle x^2\rangle \sim t^{1/2}$, to normal diffus...

Compressing long chain-of-thought (CoT) from large language models (LLMs) is an emerging strategy to improve the reasoning efficiency of LLMs. Despite its promising benefits, existing studies equally compress all thoughts within a long CoT, hindering more concise and effective reasoning. To this end, we first investigate the importance of different...

Objective. Uncertainty assessment of deep learning autosegmentation (DLAS) models can support contour corrections in adaptive radiotherapy (ART), e.g. by utilizing Monte Carlo Dropout (MCD) uncertainty maps. However, poorly calibrated uncertainties at the patient level often render these clinically nonviable. We evaluated population-based and patie...

A bstract We present NNLOCAL, a proof-of-concept parton-level Monte Carlo program implementing the extension of the completely local subtraction scheme CoLoRFulNNLO to the case of color-singlet production in hadron collisions. We have built general local subtraction terms that regularize all single and double unresolved infrared singularities in re...

A bstract We introduce multi-jet merging for deep inelastic scattering in the V incia parton shower in the Monte Carlo event generator P ythia 8. Merging combines event samples of different parton multiplicities with logarithmically enhanced parton-shower radiation. We consider up to five outgoing partons using two different merging algorithms. We...

One of the primary limitations of the recommendations of the American Association of Physicists in Medicine (AAPM) Task Group is that it does not consider attenuation effects from individual sources in multi-source brachytherapy implants. To address this issue, the inter-source effect (ISE) parameter has been introduced. In the present study the IS...

Network reliability computation is an NP-hard problem which has attracted much attention in literature. This problem consists in, given a network where the links may fail or operate with known probabilities, to compute the probability that a given subset of nodes (known as terminals) are connected by the operational links. Given the difficulty to c...

Finding high-quality trial wave functions for quantum Monte Carlo calculations of light nuclei requires a strong intuition for modeling the interparticle correlations as well as large computational resources for exploring the space of variational parameters. Moreover, for systems with three-body interactions, the wave function should account for ma...

Photoplethysmography (PPG) signals encode information about relative changes in blood volume that can be used to assess various aspects of cardiac health non-invasively, e.g.\ to detect atrial fibrillation (AF) or predict blood pressure (BP). Deep networks are well-equipped to handle the large quantities of data acquired from wearable measurement d...

p>Radionuclides decaying by electron capture or internal transition produce a large number of Auger electrons in a cascade that follows their radioactive decay. A shortlist of the most potent Auger electron-emitters has appeared in the literature including ^103mRh, ¹⁰³Pd, ¹¹¹In, ¹¹⁹Sb, ¹²³I, <su...

Objective. To develop a regression testing system for TOPAS-nBio: a wrapper of Geant4-DNA, and the radiobiological extension of TOPAS—a Monte Carlo code for the simulation of radiation transport. This regression testing system will be made publicly available on the TOPAS-nBio GitHub page. Approach. A set of seven regression tests were chosen to eva...

Diffusion models have recently gained prominence in offline reinforcement learning due to their ability to effectively learn high-performing, generalizable policies from static datasets. Diffusion-based planners facilitate long-horizon decision-making by generating high-quality trajectories through iterative denoising, guided by return-maximizing o...

DC-SRF-II gun, a high-brightness continuous-wave photocathode gun, has greater potential in electron beam irradiation applications. This paper presents the in-vacuum and in-air irradiation dosimetry study of the high repetition rate electron beam from the DC-SRF-II gun with both Monte Carlo simulations and experiments. Especially, high-dose uniform...

A bstract Quantum cosmology aims at elucidating the beginning of our Universe. Back in early 80’s, Vilenkin and Hartle-Hawking put forward the “tunneling from nothing” and “no boundary” proposals. Recently there has been renewed interest in this subject from the viewpoint of defining the oscillating path integral for Lorentzian quantum gravity usin...

We propose a neural approach for estimating spatially varying light selection distributions to improve importance sampling in Monte Carlo rendering, particularly for complex scenes with many light sources. Our method uses a neural network to predict the light selection distribution at each shading point based on local information, trained by minimi...

The increasing focus on rare-earth-based intermetallic materials has intensified the search for compounds capable of delivering superior performance in low-temperature magnetic refrigeration systems. In the present work, we theoretically examine the electronic, magnetic, and magnetocaloric characteristics of the NdSi intermetallic compound by emplo...

Modern tooling is demanded for predicting the transport and reaction characteristics of atoms and molecules, especially in the context of magnetic confinement fusion. DEGAS2, among the most common and capable tools currently in use, shares many fundamental similarities with the OpenMC framework, which was primarily developed for neutron and photon...

Path integral Monte Carlo (PIMC) simulations are a cornerstone for studying quantum many-body systems. The analytic continuation (AC) needed to estimate dynamic quantities from these simulations is an inverse Laplace transform, which is ill-conditioned. If this inversion were surmounted, then dynamical observables (e.g. dynamic structure factor (DS...

Quantile regression, a robust method for estimating conditional quantiles, has advanced significantly in fields such as econometrics, statistics and machine learning. In high-dimensional settings, where the number of covariates exceeds sample size, penalized methods like lasso have been developed to address sparsity challenges. Bayesian methods, in...

Autonomous vehicles require intelligent computer vision (CV) to perform critical navigational perception tasks. To achieve this, sensors such as camera, LiDAR and radar are utilized to provide data to artificial intelligence (AI) systems. Continuous monitoring of these intelligent CV systems is required to achieve a trustworthy AI system in a zero-...

The remnant black hole–accretion disk system resulting from binary neutron star mergers has proven to be a promising site for synthesizing the heaviest elements via rapid neutron capture ( r -process). A critical factor in determining the full r -process pattern in these environments is the neutron richness of the ejecta, which is strongly influenc...

Introduction: Neutrons are produced when photons interact with parts of the accelerator, materials in the treatment room, or the patient's body. These neutrons have significant biological effects due to their high quality factor, potentially leading to secondary cancers. Material and method: A Monte Carlo simulation was conducted using the MCNPX co...

Effective epidemic modeling and surveillance require computationally efficient methods that can continuously update estimates as new data becomes available. This paper explores the application of an online variant of Sequential Monte Carlo Squared (O-SMC$^2$) to the stochastic Susceptible-Exposed-Infectious-Removed (SEIR) model for real-time epidem...

The assessment of imaging biomarkers is critical for advancing precision medicine and improving disease characterization. Despite the availability of methods to derive disease heterogeneity metrics in imaging studies, a robust framework for evaluating measurement uncertainty remains underdeveloped. To address this gap, we propose a novel Bayesian f...

A hybrid Monte-Carlo molecular-dynamics method for determining solidus and liquidus compositions in multicomponent systems is presented that overcomes both the time limitations in conventional molecular dynamics that prevent the evolution of distinct solid and liquid compositions via diffusion and the complexity challenge that prevents use of therm...

We describe our approach to solve the problem of ensuring the solenoidality of the magnetic field vector in three-dimensional (3D) inversions, as well as the estimation of the uncertainty in the inferred magnetic field. The solenoidality of the magnetic field vector is often disregarded in the inversion of spectropolarimetric data due to limitation...

Colloids are particle suspensions in a continuous medium. The particle interactions promote the assembly of structures under the influence of a magnetic field, known as directed-assembly. The magnetic properties and shape anisotropy are relevant features of the particle building blocks to the assembled structures. The dipolar interaction between co...

Quantum correlations in the degree of polarization of freedom of the two-photon system have been extensively studied and form our current understanding of the quantum nature of our world. Most of the studies are concentrated on the low-energy (optical) photon pairs, for which efficient polarization measurement devices exist. However, for high-energ...

We aimed to design small fields collimators made of lead blocks, with diameters of 40 mm, 30 mm, 20 mm, and 10 mm, for the calibration of small volume radiotherapy ionization chambers using the Algerian Secondary Standard Dosimetry Laboratory (SSDL) ELDORADO 78 ⁶⁰Co calibration unit. The radiation properties of the designed collimators were assesse...

In the framework of the TOP-IMPLART project, a beam delivery line has been designed and is under commissioning for the TOP-IMPLART proton linear accelerator to enable irradiation scans of extended targets at energies of 63 and 71 MeV. To suitably plan these irradiations, it is necessary to know the lateral size and angular spread of the beam arrivi...

We extend the rejection-free event-chain Monte Carlo approach to a liquid-crystal system consisting of infinitely thin hard triangles. This triangle liquid crystal behaves very similar to hard circular platelets, which are an important model system for discotic liquid crystals. We investigate the isotropic-nematic phase transition of the triangle l...

Recent disagreement between state-of-the-art quantum chemical methods, coupled cluster with single, double and perturbative triples excitations and fixed-node diffusion Monte Carlo, calls for systematic examination of possible sources of error within both methodological approaches. Coupled cluster theory is systematically improvable toward the exac...

Model uncertainty—often termed epistemic uncertainty—is a critical factor in the reliability of AI systems, especially in safety-critical domains such as healthcare, autonomous vehicles, and legal decision-making. This study examines methods to identify and quantify model uncertainty by combining a systematic literature survey with empirical modeli...

Seminario tenuto al Primo anno della Laurea Magistrale in Ingegneria Gestionale inerente il problema del calcolo della "Nearest Correlation Matrix"

Abstract: Background: Preclinical investigations studies have shown that FLASH radiotherapy (FLASH-RT), delivering radiation in ultra-high dose rates (UHDR), preserves healthy tissue and reduces toxicity, all while maintaining an effective tumor response compared to conventional radiotherapy (CONV-RT), the combined biological benefit was termed as...

The Flexible Job-Shop Scheduling Problem (FJSSP) is an NP-hard combinatorial optimization problem, with several application domains, especially for manufacturing purposes. The objective is to efficiently schedule multiple operations on dissimilar machines. These operations are gathered into jobs, and operations pertaining to the same job need to be...

Assessing blood metal levels in older adults is crucial for monitoring nutritional, occupational, and environmental exposures, as environmental metals may potentially affect the health of older people through dietary intake. In this study, we collected blood samples from 2493 older participants in Yiwu, China. 11 metal elements in whole blood were...

The erosion of tungsten plasma-facing components due to charge-exchange atoms, predicted to be the dominant cause of the observed W radiation in most JET plasmas with a Be/W wall (formerly ITER-like wall), is quantified by the first EIRENE simulations of the bivariate energy-angular impact spectrum and the incident flux of deuterium and tritium ato...

In factory environments, stable and high-precision localization capabilities are crucial for the automated guided vehicles. Adaptive Monte Carlo localization (AMCL) is widely used in 2D laser navigation due to its excellent performance in addressing global localization and position tracking issues in localization. However, AMCL faces challenges in...

In this paper, we propose an analytical method to compute the collateral liquidation probability in decentralized finance (DeFi) stablecoin single-collateral lending. Our approach models the collateral exchange rate as a zero-drift geometric Brownian motion, converts it into a regular zero-drift Brownian motion, and employs the reflection principle...

The determination of the intrinsic transverse momentum distribution of partons is central both for applications of parton shower Monte Carlo generators and for QCD studies of transverse momentum dependent (TMD) parton densities. Valuable information on this distribution is provided by experimental measurements of Drell-Yan transverse momentum $p_T$...

An assumed density approximate likelihood is derived for a class of partially observed stochastic compartmental models which permit observational over-dispersion. This is achieved by treating time-varying reporting probabilities as latent variables and integrating them out using Laplace approximations within Poisson Approximate Likelihoods (LawPAL)...

Based on crop statistics, this paper uses Monte Carlo intelligent algorithms to optimize crop cultivation between 2024 and 2030, aiming to develop a cultivation strategy that maximizes returns. First, this paper checked the completeness and accuracy of the data through data preprocessing, dealt with the stagnant sales situation in which the total c...

The earliest form of continental crust was produced by tonalite‐trondhjemite‐granodiorite (TTG) magmas. Molten albite (NaAlSi3O8) is representative of TTGs and also a major component of modern crust‐forming magma. The viscosity of the melt controls the magma ascent rate and hence influences the production of new continental crust. It is well known...

Recently, there has been a growing interest in generative models based on diffusions driven by the empirical robustness of these methods in generating high-dimensional photorealistic images and the possibility of using the vast existing toolbox of stochastic differential equations. %This remarkable ability may stem from their capacity to model and...

Organic optoelectronic materials are a promising avenue for next-generation electronic devices due to their solution processability, mechanical flexibility, and tunable electronic properties. In particular, near-infrared (NIR) sensitive molecules have unique applications in night-vision equipment and biomedical imaging. Molecular engineering has pl...

Blockchain dan cryptocurrency merupakan teknologi yang merevolusi sistem fi-nansial dan data global. Blockchain sebagai rantai blok terdesentralisasi menyedi-akan mekanisme pencatatan transaksi yang imutabel dan aman 1. Cryptocurrency, seperti Bitcoin dan Ethereum, adalah aset digital yang dihasilkan dan diatur melalui sistem blockchain. Paper ini...

Este estudio examina la gestión de riesgos financieros en empresas multinacionales, con un enfoque particular en la metodología y sus etapas clave: identificación, evaluación, priorización y monitoreo de riesgos. A partir del caso de General Electric (GE), se ilustran las consecuencias de una gestión de riesgos inadecuada y la importancia de aplica...

Simulating water droplets made up of millions of molecules and on timescales as needed in biological and technological applications is challenging due to the difficulty of balancing accuracy with computational capabilities. Most detailed descriptions, such as ab initio, polarizable, or rigid models, are typically constrained to a few hundred (for a...

He 4 nanodroplets doped with an alkali ion feature a snowball of crystallized layers surrounded by superfluid helium. For large droplets, we predict that a transitional supersolid layer can form, bridging between the solid core and the liquid bulk, where the He 4 density displays modulations of icosahedral group symmetry. To identify the different...

Various studies show that the gravitational collapse of inhomogeneous matter clouds leads to naked singularity formation. We investigate here the spin precession frequency of a test gyroscope attached to a stationary observer in a rotating naked singularity spacetime. In the weak field limit, Lense-Thirring precession for rotating naked singularity...

The deposition processes of geotechnical materials are inherently complex, resulting in significant spatial variability in soil and rock properties. This study proposes a probabilistic framework applicable to braced excavations in composite soil-rock layers, designed to quantitatively evaluate the impact of variability on these excavations and to e...

The piecewise exponential model is a flexible non-parametric approach for time-to-event data, but extrapolation beyond final observation times typically relies on random walk priors and deterministic knot locations, resulting in unrealistic long-term hazards. We introduce the diffusion piecewise exponential model, a prior framework consisting of a...

Silica is a suitable material to encapsulate proteins at room temperature, enabling their analysis at the atomic level using laser-assisted atom probe tomography (La- APT). In this study, we show that UV and deep-UV lasers can achieve a high success rate in La-APT of silica in terms of chemical resolution and three-dimensional image volume, with bo...

This report presents a comprehensive evaluation of three Value-at-Risk (VaR) modeling approaches: Historical Simulation (HS), GARCH with Normal approximation (GARCH-N), and GARCH with Filtered Historical Simulation (FHS), using both in-sample and multi-day forecasting frameworks. We compute daily 5 percent VaR estimates using each method and assess...