Related papers: Automated event generation for loop-induced proces…
Concolic testing is a scalable solution for automated generation of directed tests for validation of hardware designs. Unfortunately, concolic testing also fails to cover complex corner cases such as hard-to-activate branches. In this…
The FLAME methodology makes it possible to derive provably correct algorithms from a formal description of a linear algebra problem. So far, the methodology has been successfully used to automate the derivation of direct algorithms such as…
Event scenarios are often complex and involve multiple event sequences connected through different entity participants. Exploring such complex scenarios requires an ability to branch through different sequences, something that is difficult…
Hard scattering events in high-energy collisions produce highly virtual partons that subsequently fragment into collimated hadronic cascades. When such partonic showers evolve in a QCD medium, as in deep-inelastic scattering or heavy-ion…
New machine learning based algorithms have been developed and tested for Monte Carlo integration based on generative Boosted Decision Trees and Deep Neural Networks. Both of these algorithms exhibit substantial improvements compared to…
In the era of graph-based retrieval-augmented generation (RAG), link prediction is a significant preprocessing step for improving the quality of fragmented or incomplete domain-specific data for the graph retrieval. Knowledge management in…
Modern large-scale scientific applications consist of thousands to millions of individual tasks. These tasks involve not only computation but also communication with one another. Typically, the communication pattern between tasks is sparse…
We consider the problem of optimally designing a system for repeated use under uncertainty. We develop a modeling framework that integrates design and operational phases, which are represented by a mixed-integer program and discounted-cost…
Distribution-level phasor measurement units, a.k.a, micro-PMUs, report a large volume of high resolution phasor measurements which constitute a variety of event signatures of different phenomena that occur all across power distribution…
A new Monte Carlo program for photohadronic interactions of relativistic nucleons with an ambient photon radiation field is presented. The event generator is designed to fulfil typical astrophysical requirements, but can also be used for…
We propose a general approach for the description of multijet events in the framework of QCD event generators. We introduce a new algorithm to match parton showers and arbitrary matrix elements for the production of any number of jets via…
This paper presents a novel approach for directly generating full events at detector-level from parton-level information, leveraging cutting-edge machine learning techniques. To address the challenge of multiplicity variations between…
We uncover an effective and communicative set of agents working with MadGraph. Agentic installation, learning-by-doing training, and user support provide easy access to state-of-the-art simulations and accelerate LHC research. We show in…
Whilst most engineered systems use signals that are continuous in time, there is a domain of systems in which signals consist of events. Events, like Dirac delta functions, have no meaningful time duration. Many important real-world systems…
Generating inferential texts about an event in different perspectives requires reasoning over different contexts that the event occurs. Existing works usually ignore the context that is not explicitly provided, resulting in a…
Event-driven multi-threaded programming is an important idiom for structuring concurrent computations. Stateless Model Checking (SMC) is an effective verification technique for multi-threaded programs, especially when coupled with Dynamic…
This is the user's manual of MC@NLO 3.2. This package is a practical implementation, based upon the HERWIG event generator, of the MC@NLO formalism, which allows one to incorporate NLO QCD matrix elements consistently into a parton shower…
Structured point process data harvested from various platforms poses new challenges to the machine learning community. By imposing a matrix structure to repeatedly observed marked point processes, we propose a novel mixture model of…
Hadronization is a non-perturbative process, which theoretical description can not be deduced from first principles. Modeling hadron formation requires several assumptions and various phenomenological approaches. Utilizing state-of-the-art…
Branching processes are a class of continuous-time Markov chains (CTMCs) with ubiquitous applications. A general difficulty in statistical inference under partially observed CTMC models arises in computing transition probabilities when the…