Dr Costis Papageorgakis

Profile

I am a Reader in Theoretical Physics at the Centre for Theoretical Physics, Department of Physics and Astronomy. My work has focussed on various aspects of supersymmetric/superconformal field theories and their relation to String/M-theory.

I hold an undergraduate diploma from the University of Patras (Greece), an MSc from Durham University and a PhD from Queen Mary University of London. I have previously held postdoctoral positions at the Tata Institute of Fundamental Research (India), King's College London and Rutgers University (USA). 

Teaching

I currently teach the undergraduate course "Quantum Mechanics and Symmetry" over the second semester of the 2024-2025 academic year.

I am a Fellow of Advance HE.

Research

Research Interests:

See Costis Papageorgakis’ research profile pages including details of research interests, publications, and live grants.

Publications

(A complete and up to date list of publications with an accurate citation count can also be found at this link)

• Papageorgakis C, Niarchos V (2024). Learning S-matrix phases with neural operators. nameOfConference

  
  

  DOI: 10.1103/PhysRevD.110.045020

  
  

  QMRO: https://qmro.qmul.ac.uk/xmlui/handle/123456789/98713
• Niarchos V, Papageorgakis C, Richmond P et al. (2023). Bootstrability in line-defect CFTs with improved truncation methods. nameOfConference

  
  

  DOI: 10.1103/physrevd.108.105027

  
  

  QMRO: https://qmro.qmul.ac.uk/xmlui/handle/123456789/92671
• Kántor G, Niarchos V, Papageorgakis C et al. (2023). 6D (2,0) bootstrap with the soft-actor-critic algorithm. nameOfConference

  
  

  DOI: 10.1103/PhysRevD.107.025005

  
  

  QMRO: https://qmro.qmul.ac.uk/xmlui/handle/123456789/84509
• Andriolo E, Niarchos V, Papageorgakis C et al. (2023). Covariantly Constant Anomalies on Conformal Manifolds. nameOfConference

  
  

  DOI: 10.1103/PhysRevD.107.025006

  
  

  QMRO: https://uat2-qmro.qmul.ac.uk/xmlui/handle/123456789/83843
• Andriolo E, Lambert N, Orchard T et al. (publicationYear). A path integral for the chiral-form partition function. nameOfConference

  
  

  DOI: 10.1007/jhep04(2022)115

  
  

  QMRO: https://uat2-qmro.qmul.ac.uk/xmlui/handle/123456789/78093
• Kántor G, Niarchos V, Papageorgakis C (2022). Conformal bootstrap with reinforcement learning. nameOfConference

  
  

  DOI: 10.1103/physrevd.105.025018

  
  

  QMRO: https://uat2-qmro.qmul.ac.uk/xmlui/handle/123456789/75663
• Kántor G, Niarchos V, Papageorgakis C (2022). Solving Conformal Field Theories with Artificial Intelligence. nameOfConference

  
  

  DOI: 10.1103/PhysRevLett.128.041601

  
  

  QMRO: https://uat2-qmro.qmul.ac.uk/xmlui/handle/123456789/75343
• Agarwal P, Andriolo E, Kántor G et al. (2021). Macdonald indices for four-dimensional N=3 theories. nameOfConference

  
  

  DOI: 10.1103/PhysRevD.103.L121701

  
  

  QMRO: https://uat2-qmro.qmul.ac.uk/xmlui/handle/123456789/71898
• Niarchos V, Papageorgakis C, Pini A et al. (2021). (Mis-)matching type-B anomalies on the Higgs branch. nameOfConference

  
  

  DOI: 10.1007/JHEP01(2021)106

  
  

  QMRO: https://uat2-qmro.qmul.ac.uk/xmlui/handle/123456789/69236
• Melnikov IV, Papageorgakis C, Royston AB (2020). Accelerating solitons. nameOfConference

  
  

  DOI: 10.1103/PhysRevD.102.125002

  
  

  QMRO: https://uat2-qmro.qmul.ac.uk/xmlui/handle/123456789/67302

Supervision

PhD students:

• James Chryssanthacopoulos (jointly with Dr David Vegh-PhD expected 2028)
• Alexander Stapleton (jointly with Prof. David Berman-PhD expected 2026)
• Mitchell Woolley (PhD expected 2026)
• L. Sidney Baines (jointly with Dr Ulla Blumenschein-PhD expected 2025)
• Enrico Andriolo (PhD 2023)
• Gergely Kántor (PhD 2022)
• Joseph Hayling (PhD 2019)

I am also interested in taking on new students for the following project:

Conformal Field Theories are mathematical descriptions of natural phenomena that look the same at all length scales. They find fundamental applications over a large spectrum of topics ranging from condensed-matter physics, particle physics, string theory and quantum gravity. They are, however, incredibly hard to solve with the exception of a handful of examples.

This project aims to exploit the tremendous recent progress in Artificial Intelligence to solve arbitrary conformal field theories. This will be achieved by utilising machine-learning techniques similar to those used by Google’s DeepMind Technologies when building the AlphaGo programme, which spectacularly beat professional Go champions.

Requirements:

A very good grasp of graduate Quantum Field Theory and supersymmetry, as well as some basic conformal field theory and string theory. Coding experience is desirable.