A. Moraes

96.0k citations
13 papers · 47 indexed · h-index 5

Impact in

Papers in

A. Moraes

9 papers receiving 44 citations

Peers

A. Moraes
Comparison fields: 5 of 9
  • Nuclear and High Energy Physics 29
  • Atomic and Molecular Physics, and Optics 16
  • Artificial Intelligence 16
  • Radiation 2
  • Astronomy and Astrophysics 3
Replace K. Toms with:
K. Toms Russia
F. Fabbri Italy
P. Kurashvili Poland
Chen Qian China
Ydalia Delgado Austria
K. Ehatäht Estonia
E. Kajomovitz Israel
J. Martens Netherlands
E. Cattaruzza Italy
S. Ganguly Japan
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Citations per field
00.5×
K. Toms · 1×
Citations per year

Countries citing papers authored by A. Moraes

Since Specialization
Citations

This map shows the geographic impact of A. Moraes's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by A. Moraes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. Moraes more than expected).

Fields of papers citing papers by A. Moraes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. Moraes. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by A. Moraes. The network helps show where A. Moraes may publish in the future.

Co-authors

The 25 scholars most cited alongside A. Moraes, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with A. Moraes Line = papers co-authored together A. Moraes links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 200716
2 200511
3
Simulations of Minimum Bias Events and the Underlying Event, MC Tuning and Predictions for the LHC
20045
4 20054
5 20054
6 20032
7 20212
8 20012
9 20211
10
Minimum bias and the underlying event: towards the LHC
20040
11 20030
12
Measuring the underlying event at ATLAS
20050
13
Preparing for measurements of dijet azimuthal decorrelations at ATLAS
20050

About A. Moraes

A. Moraes is a scholar working on Nuclear and High Energy Physics, Atomic and Molecular Physics, and Optics, Artificial Intelligence, Radiation and Computer Networks and Communications, having authored 13 papers that have together received 47 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (7 papers), High-Energy Particle Collisions Research (4 papers), Particle Detector Development and Performance (3 papers), Quantum Mechanics and Applications (3 papers), Quantum Information and Cryptography (3 papers), Quantum Chromodynamics and Particle Interactions (2 papers), Radiation Detection and Scintillator Technologies (2 papers) and Astrophysics and Cosmic Phenomena (2 papers). The work is most often cited by research in Nuclear and High Energy Physics (29 citations), Atomic and Molecular Physics, and Optics (16 citations), Artificial Intelligence (16 citations), Radiation (2 citations) and Astronomy and Astrophysics (3 citations). A. Moraes has collaborated with scholars based in United Kingdom, Brazil and United States. Frequent co-authors include C. M. Buttar, I. Dawson, Guilherme Colherinhas, I. Dawson, D. Clements, M. Santander, Stefan Hoeche, Luis Miguel Domingues Mendes, I. O. Skillicorn and J. Vícha. Their work appears in journals such as Physica A Statistical Mechanics and its Applications, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, Physics Letters A, The European Physical Journal C and Acta Physica Polonica B.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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