Our papers are the official record of our discoveries. They allow others to build on and apply our work. Each one is the result of many months of research, so we make a special effort to make our papers clear, inspiring and beautiful, and publish them in leading journals.

- Date
- Subject
- Theme
- Journal
- Citations
- Altmetric
- SNIP
- Author

*x*26

- O. Gamayun
- A. Esterov
- Y. He
- A. V. Kosyak
- A. Ochirov
- E. Sobko
- M. Burtsev
- M. Reeves
- I. Shkredov
- T. Fink
- F. Sheldon
- G. Caldarelli
- R. Hannam
- F. Caravelli
- A. Coolen
- O. Dahlsten
- A. Mozeika
- M. Bardoscia
- P. Barucca
- M. Rowley
- I. Teimouri
- F. Antenucci
- A. Scala
- R. Farr
- A. Zegarac
- S. Sebastio
- B. Bollobás
- F. Lafond
- D. Farmer
- C. Pickard
- T. Reeves
- J. Blundell
- A. Gallagher
- M. Przykucki
- P. Smith
- L. Pietronero

AI-assisted maths

### On AI-driven discovery

Reviewing progress in the field of AI-assisted discovery for maths and theoretical physics reveals a triumvirate of different approaches.

AI-assisted maths

### Triangulating polytopes

Machine learning generates desirable triangulations of geometric objects that are required for Calabi-Yau compactification in string theory.

AI-assisted maths

### Clifford invariants by ML

Coxeter transformations for root diagrams of simply-laced Lie groups are exhaustively computed then machine learned to very high accuracy.

AI-assisted maths

### AI for cluster algebras

Investigating cluster algebras through the lens of modern data science reveals an elegant symmetry in the quiver exchange graph embedding.

Algebraic geometry

### Bundled Laplacians

By approximating the basis of eigenfunctions, we computationally determine the harmonic modes of bundle-valued Laplacians on Calabi-Yau manifolds.

AI-assisted maths

### Computing Sasakians

Topological quantities for the Calabi-Yau link construction of G2 manifolds are computed and machine learnt with high performance scores.

Algebraic geometry

### Genetic polytopes

Genetic algorithms, which solve optimisation problems in a natural selection-inspired way, reveal previously unconstructed Calabi-Yau manifolds.

Algebraic geometry

### Analysing amoebae

Genetic symbolic regression methods reveal the relationship between amoebae from tropical geometry and the Mahler measure from number theory.

Group theory

### On John McKay

This obituary celebrates the life and work of John Keith Stuart McKay, highlighting the mathematical miracles for which he will be remembered.

AI-assisted maths

### AI for arithmetic curves

AI can predict invariants of low genus arithmetic curves, including those key to the Birch-Swinnerton-Dyer conjecture—a millennium prize problem.

AI-assisted maths

### Clustered cluster algebras

Cluster variables in Grassmannian cluster algebras can be classified with HPC by applying the tableaux method up to a fixed number of columns.

Number theory

### Elliptical murmurations

Certain properties of the bivariate cubic equations used to prove Fermat’s last theorem exhibit flocking patterns, machine learning reveals.

String theory

### World in a grain of sand

An AI algorithm of few-shot learning finds that the vast string landscape could be reduced by only seeing a tiny fraction to predict the rest.

Evolvability

### Flowers of immortality

The eigenvalues of the mortality equation fall into two classes—the flower and the stem—but only the stem eigenvalues control the dynamics.

Gravity

### AI classifies space-time

A neural network learns to classify different types of spacetime in general relativity according to their algebraic Petrov classification.

String theory

### Algebra of melting crystals

Certain states in quantum field theories are described by the geometry and algebra of melting crystals via properties of partition functions.

AI-assisted maths

### Machine learning Hilbert series

Neural networks find efficient ways to compute the Hilbert series, an important counting function in algebraic geometry and gauge theory.

AI-assisted maths

### Line bundle connections

Neural networks find numerical solutions to Hermitian Yang-Mills equations, a difficult system of PDEs crucial to mathematics and physics.

AI-assisted maths

### Calabi-Yau anomalies

Unsupervised machine-learning of the Hodge numbers of Calabi-Yau hypersurfaces detects new patterns with an unexpected linear dependence.

String theory

### Mahler measure for quivers

Mahler measure from number theory is used for the first time in physics, yielding “Mahler flow” which extrapolates different phases in QFT.

AI-assisted maths

### Learning the Sato–Tate conjecture

Machine-learning methods can distinguish between Sato-Tate groups, promoting a data-driven approach for problems involving Euler factors.

Machine learning

### Universes as big data

Machine-learning is a powerful tool for sifting through the landscape of possible Universes that could derive from Calabi-Yau manifolds.

Number theory

### Reflexions on Mahler

With physically-motivated Newton polynomials from reflexive polygons, we find the Mahler measure and dessin d’enfants are in 1-to-1 correspondence.

String theory

### QFT and kids’ drawings

Groethendieck's “children’s drawings”, a type of bipartite graph, link number theory, geometry, and the physics of conformal field theory.

Machine learning

### Neurons on amoebae

Machine-learning 2-dimensional amoeba in algebraic geometry and string theory is able to recover the complicated conditions from so-called lopsidedness.

Group theory

### New approaches to the Monster

Editorial of the last set of lectures given by the founder, McKay, of Moonshine Conjectures, the proof of which got Borcherds the Fields Medal.