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D. Schwarz

188 papers hereh-index 294.3k citations433 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author4
  • last author3

Across the 7 of 188 papers where every author was matched, so the position is known.

fields
  • hep-ex160
  • nucl-ex17
  • physics.ins-det6
  • hep-ph4
  • physics.data-an1
same name
  • D. Schwarz — 156 papers, h 53
  • D. Schwarz — 142 papers
  • D. Schwarz — 22 papers, h 4
  • D. Schwarz — 12 papers, h 3
  • D. Schwarz — 10 papers, h 4
  • D. Schwarz — 9 papers, h 8

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192026
most citedThe CMS statistical analysis and combination tool: COMBINE

108 citations · 1.2k across the 186 of their papers we have counts for

collaborators
Showing hep-phShow all

4 papers · 1 filter

hep-ph2025★ 1 cited

How to Unfold Top Decays

Luigi Favaro, Roman Kogler, Alexander Paasch +3

Using unfolded top-quark decay data we can measure the top quark mass, as well as search for unexpected kinematic effects. We present a new generative unfolding method for the two…

hep-ph2024★ 3 cited

Energy-scaling behavior of intrinsic transverse momentum parameters in Drell-Yan simulation

CMS Collaboration

An analysis is presented based on models of the intrinsic transverse momentum (intrinsic kT​) of partons in nucleons by studying the dilepton transverse momentum in Drel…

hep-ph2022★ 5 cited

Learning the EFT likelihood with tree boosting

Suman Chatterjee, Stefan Rohshap, Robert Schöfbeck +1

We develop a tree boosting algorithm for collider measurements of multiple Wilson coefficients in effective field theories describing phenomena beyond the standard model of particl…

hep-ph2021★ 20 cited

Tree boosting for learning EFT parameters

Suman Chatterjee, Nikolaus Frohner, Lukas Lechner +2

We present a new tree boosting algorithm designed for the measurement of parameters in the context of effective field theory (EFT). To construct the algorithm, we interpret the opt…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.