What is he best known for?
The fields of study he is best known for:
- Quantum mechanics
- Particle physics
- Astronomy
Lian-Tao Wang mostly deals with Astrophysics, Astronomy, Particle physics, Galaxy and Dark matter.
His study in the field of Redshift, Spire and Sky also crosses realms of Confusion.
His work in Particle physics addresses subjects such as Nuclear physics, which are connected to disciplines such as Gauge boson.
His Galaxy course of study focuses on Flux and Stellar mass and Space observatory.
His studies in Dark matter integrate themes in fields like Effective field theory, Weakly interacting massive particles, Supersymmetry, Light dark matter and Collider.
The Higgs boson study combines topics in areas such as Electroweak interaction and Technicolor.
His most cited work include:
- The Herschel Multi-tiered Extragalactic Survey: HerMES (659 citations)
- The Herschel Multi-tiered Extragalactic Survey: HerMES (657 citations)
- Jet Trimming (413 citations)
What are the main themes of his work throughout his whole career to date?
Lian-Tao Wang mainly investigates Particle physics, Astrophysics, Large Hadron Collider, Galaxy and Higgs boson.
His studies examine the connections between Particle physics and genetics, as well as such issues in Nuclear physics, with regards to Photon.
Astrophysics and Astronomy are commonly linked in his work.
As a part of the same scientific study, Lian-Tao Wang usually deals with the Large Hadron Collider, concentrating on Lepton and frequently concerns with Invariant mass.
His Galaxy research includes themes of Infrared and Photometry.
His Higgs boson research incorporates themes from Boson, Elementary particle and Effective field theory.
He most often published in these fields:
- Particle physics (61.00%)
- Astrophysics (37.45%)
- Large Hadron Collider (31.66%)
What were the highlights of his more recent work (between 2017-2021)?
- Particle physics (61.00%)
- Large Hadron Collider (31.66%)
- Higgs boson (24.71%)
In recent papers he was focusing on the following fields of study:
His main research concerns Particle physics, Large Hadron Collider, Higgs boson, Physics beyond the Standard Model and Collider.
All of his Particle physics and Effective field theory, Electroweak interaction, Standard Model, Dark matter and Quark investigations are sub-components of the entire Particle physics study.
His research investigates the connection between Large Hadron Collider and topics such as Lepton that intersect with issues in Invariant mass and Muon.
His Physics beyond the Standard Model study integrates concerns from other disciplines, such as Boson and Tera-.
The concepts of his Collider study are interwoven with issues in Inflation, Inflaton and Electron–positron annihilation.
Lian-Tao Wang combines topics linked to Astrophysics with his work on Wavenumber.
Between 2017 and 2021, his most popular works were:
- Dark Matter Benchmark Models for Early LHC Run-2 Searches. Report of the ATLAS/CMS Dark Matter Forum (88 citations)
- Experimental targets for photon couplings of the QCD axion (65 citations)
- Enhancing Long-Lived Particles Searches at the LHC with Precision Timing Information (60 citations)
In his most recent research, the most cited papers focused on:
- Quantum mechanics
- Particle physics
- Astronomy
Lian-Tao Wang focuses on Particle physics, Large Hadron Collider, Physics beyond the Standard Model, Dark matter and Photon.
Lian-Tao Wang combines subjects such as Effective field theory, Higgs boson and Lepton with his study of Large Hadron Collider.
Lian-Tao Wang has included themes like Supersymmetry breaking and Standard Model in his Higgs boson study.
Within one scientific family, Lian-Tao Wang focuses on topics pertaining to Collider under Physics beyond the Standard Model, and may sometimes address concerns connected to Inflaton, Symmetry, Inflation and Scale invariance.
His study on Dark photon is often connected to Channel models as part of broader study in Dark matter.
The various areas that Lian-Tao Wang examines in his Photon study include Astrophysics and Axion.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
