Vasilis Niarchos

University of Crete · Crete Center for Theoretical Physics

I am a theoretical physicist working in the field of elementary particle physics. My main research interests revolve around (super)string theory, gravity and quantum field theory. I am especially interested in the non-perturbative structure of quantum field theory and a variety of bootstrap ideas that can bring together tools from very different directions (analytic and numeric, perturbative and non-perturbative). More recently, in this context, I have been thinking about Artificial Intelligence and how Machine Learning algorithms can be employed to address fundamental questions in formal quantum field theory.

Research topics

  • Non-perturbative dynamics and duality in Quantum Field Theory
  • Conformal bootstrap
  • Supersymmetry and supersymmetry breaking
  • Machine learning applications to Quantum Field Theory
  • Holographic dualities
  • String theory
  • Black Holes

Published software packages

BootSTOP

A STochastic OPtimizer for Conformal Bootstrap studies. Release 2 includes the modifications of the improved truncation methods with tail approximation, more pre-generated conformal blocks, and access to all the PyGMO algorithms.

GitHub Project site
GoBlocks

A fast, flexible Go implementation of a recursive algorithm for computing conformal blocks supporting both CLI and library modes, with choice between efficient binary or CSV outputs.

GitHub
FeynTune

Large Language Models for High Energy Theory. The code used to curate the datasets, fine-tune and evaluate the models can be found at the GitHub link. The fine-tuned models are available as LoRA adapters at the Hugging Face link.

GitHub Hugging Face

Publications

For an updated full list of publications with citation statistics, see INSPIRE-HEP.

Selected Physics publications

  1. Thermal double-twist data in holography
    V. Niarchos, C. Papageorgakis, A. Stratoudakis
    arXiv:2606.30806
  2. Scattering, absorption and emission of highly excited strings
    M. Firrotta, E. Kiritsis, V. Niarchos · JHEP 01 (2025) 051
    arXiv:2407.16476
  3. Covariantly constant anomalies on conformal manifolds
    E. Andriolo, V. Niarchos, C. Papageorgakis, E. Pomoni · Phys.Rev.D 107 (2023) 2, 025006
    arXiv:2210.10891
  4. On the Kaehler-Hodge structure of superconformal manifolds
    V. Niarchos, K. Papadodimas · JHEP 09 (2022) 104
    arXiv:2112.11425
  5. Type-B Anomaly Matching and the 6D (2,0) Theory
    V. Niarchos, C. Papageorgakis, E. Pomoni · JHEP 04 (2020) 048
    arXiv:1911.05827
  6. Metastable nonextremal antibranes
    J. Armas, N. Nguyen, V. Niarchos, N.A. Obers, T. Van Riet · Phys.Rev.Lett. 122 (2019) 18, 181601
    arXiv:1812.01067
  7. Geometry of Higgs-branch superconformal primary bundles
    V. Niarchos · Phys.Rev.D 98 (2018) 6, 065012
    arXiv:1807.04296
  8. Aspects of Berry phase in QFT
    M. Baggio, V. Niarchos, K. Papadodimas · JHEP 1704 (2017) 062
    arXiv:1701.05587
  9. Large-N correlation functions in N=2 superconformal QCD
    M. Baggio, V. Niarchos, K. Papadodimas · JHEP 01 (2017) 101
    arXiv:1610.07612
  10. N=2 supersymmetric field theories on 3-manifolds with A-type boundaries
    F. Aprile, V. Niarchos · JHEP 07 (2016) 126
    arXiv:1604.01561
  11. tt* equations, localization and exact chiral rings in 4d N=2 SCFTs
    M. Baggio, V. Niarchos, K. Papadodimas · JHEP 1502 (2015) 122
    arXiv:1409.4212

Physics and AI

  1. When does critique improve AI-assisted theoretical physics? SCALAR: structured critic–actor loop for agentic reasoning
    V. Niarchos, C. Papageorgakis, A.G. Stapleton, S. Trifinopoulos
    arXiv:2605.06772
  2. Neural networks reveal a universal bias in conformal correlators
    K. Ghosh, S. Kumar, V. Niarchos, A. Stergiou
    arXiv:2604.18673
  3. Deep finite temperature bootstrap
    V. Niarchos, C. Papageorgakis, A. Stratoudakis, M. Woolley · Phys.Rev.D 112 (2025) 12, 126012
    arXiv:2508.08560
  4. FeynTune: large language models for high-energy theory
    P. Richmond, P. Agarwal, B. Chowdhury, V. Niarchos, C. Papageorgakis · Mach.Learn.Sci.Tech. 7 (2026) 2, 025012
    arXiv:2508.03716
  5. Learning S-matrix phases with neural operators
    V. Niarchos, C. Papageorgakis · Phys.Rev.D 110 (2024) 4, 045020
    arXiv:2404.14551
  6. Bootstrability in line-defect CFT with improved truncation methods
    V. Niarchos, C. Papageorgakis, P. Richmond, A.G. Stapleton, M. Woolley · Phys.Rev.D 108 (2023) 10, 105027
    arXiv:2306.15730
  7. 6D (2,0) bootstrap with soft-actor-critic
    G. Kantor, V. Niarchos, C. Papageorgakis, P. Richmond · Phys.Rev.D 107 (2023) 2, 025005
    arXiv:2209.02801
  8. Conformal bootstrap with reinforcement learning
    G. Kantor, V. Niarchos, C. Papageorgakis · Phys.Rev.D 105 (2022) 2, 025018
    arXiv:2108.09330
  9. Solving conformal field theories with artificial intelligence
    G. Kantor, V. Niarchos, C. Papageorgakis · Phys.Rev.Lett. 128 (2022) 4, 041601
    arXiv:2108.08859

Preprint servers and article databases