2019
DOI: 10.1007/s41781-018-0018-8
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Abstract: Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware, either to build new facilities and experiments, or to upgrade existing ones. Similarly, it requires commensurate investment in the R&D of software to acquire, manage, process, and analyse the shear amounts of data to be recorded. In planning for the HL-LHC in particular, it is critical that all of the collaborating stakeholders agree on the software goals an… Show more

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Cited by 119 publications
(94 citation statements)
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“…As with any Monte Carlo method, the accept-reject procedure in step 4 can only preserve Eqs. (8) and (9) in expectation value. As long as a given phase space point has a nontrivial spectrum of weights, the above reduction will decrease the computational cost of subsequent detector simulation with the same asymptotic statistical properties as captured by the first and second moments.…”
Section: Preserving Uncertaintiesmentioning
confidence: 99%
See 1 more Smart Citation
“…As with any Monte Carlo method, the accept-reject procedure in step 4 can only preserve Eqs. (8) and (9) in expectation value. As long as a given phase space point has a nontrivial spectrum of weights, the above reduction will decrease the computational cost of subsequent detector simulation with the same asymptotic statistical properties as captured by the first and second moments.…”
Section: Preserving Uncertaintiesmentioning
confidence: 99%
“…Outputs from these Monte Carlo generators are then fed into sophisticated detector simulation frameworks, such as those based on GEANT4 [8]. Event generation and simulation is becoming an increasing relevant computational bottleneck for collider data analysis [9,10], particularly for the upcoming High Luminosity Large Hadron Collider (HL-LHC).…”
Section: Introductionmentioning
confidence: 99%
“…Other data-intensive scientific domains, such as high-energy physics (HEP), share similar challenges in building and sustaining a cohesive community, workforce training, development and advancement, access and delivery of large amounts 6/13 of data, low-latency data analysis, and using machine learning techniques. In HEP, 18 workshops in two years engaged key national and international partners from HEP, computer science, industry, and data science to generate over eight community position papers, including a software institute Strategic Plan 105 and a Community White paper 106 as a roadmap for HEP software and computing research and development over the next decade. The MMA community should consider what can be learned from this intensive community effort, and use the transferable solutions.…”
Section: Community Buildingmentioning
confidence: 99%
“…The roadmap [1] represents a bottom-up discussion in the particle physics community, which ultimately produced a Community White Paper, the basis of this report. The community took stock of current needs and attempted to identify target areas for increasing efficiency, e.g.…”
mentioning
confidence: 99%