Danilo Lewański

Hi! I'm Danilo, and in 2022 I joined the Geometry group at the University of Trieste.

I have been PI of the SNF Ambizione project EnTIRe (2021 - 2025, 1M Eur funding) hosted at the University of Geneva. I'm part of the SwissMap network and of INdAM in the GNSAGA group.

From 2019 to 2021 I have been a postdoctoral researcher at IHES and IPhT in Paris (FR) as part of the ERC Synergy Grant ReNewQuantum (Recursive and Exact New Quantum Theory) with PIs Jørgen Ellegaard AndersenBertrand Eynard, Maxim Kontsevich, and Marcos Mariño.

From 2017 to 2019 I worked as postdoctoral researcher in Bonn (DE) at the MPIM, under the mentorship of Gaëtan Borot and Don Zagier

From 2013 to 2017 I pursued my PhD in Mathematics under the supervision of Sergey Shadrin

Research interests:

I am interested in the interaction between Algebraic Geometry, Mathematical Physics and Theoretical Physics. In particular, I study the connections between the cohomology of moduli spaces of curves in Algebraic Geometry, integrable systems and integrable hierarchies in Mathematical Physics,  Physics models arising from (topological) string theory and Statistical Physics models arising from random matrix integrals. My research employs the innovative methods of Topological Recursion (TR) theory. 

Promoted to a mathematical theory in 2007 by Eynard and Orantin, Topological Recursion has proved to be a universal and unifying tool across different fields, leading to significant progress in enumerative algebraic geometry, integrable systems and hierarchies, random matrix models, Gromov-Witten theory, Hurwitz theory, enumeration of maps on surfaces, topological string theory, moduli spaces of curves, Hitchin systems, knot theory theory, resurgence, and more. 

Here you can find the video of two of my recent talks at the Topological Recursion seminar.

FIGURE 1: A schematic drawing on the interaction between Theoretical Physics, Mathematical Physics, and Algebraic Geometry; the hidden underlying instanton corrections from Resurgence; Topological Recursion as a tool to build a solid understanding of the theory.

A little bit about topological recursion:

Random matrix models carry a fundamental object called spectral curve, and TR generates the asymptotic expansion of the correlation functions of the model from this spectral curve. In different words, TR can be thought as an algorithm, concretely  implementable, which takes as input a spectral curve and produces as output the infinite list of numbers. These numbers are solutions of some enumerative problem --- matching enumerative problems  and their corresponding spectral curves is one direction of research for TR. TR has three very valuable features:

In a simplified setting, a spectral curve can be thought of the tuple  (C, x(z), y(z), B(z_1, z_2)), where:

The initial data of the recursion is given by ω_{0,1}(z) = y(z)dx(z) and ω_{0,2}(z_1, z_2) = B(z_1, z_2).

FIGURE 2. A schematic representation of Topological Recursion (TR). It can be thought as an implementable algorithm which takes a spectral curve as input and spits as output an infinite set of numbers {N_{g,μ}} indexed by a natural number g and a partition μ of positive length n. These numbers arise from the series expansion of meromorphic n-multidifferentials ω_{g,n}(z_1, . . . , z_n) defined on the topological product of n copies of the curve. Each ω_{g,n} is computed recursively in terms of all other ω_{g ′ ,n ′} with 2g′ −2+n′ < 2g−2+n, and this is why it is called a recursion. The recursion is performed layer by layer, each layer corresponding to a fixed Euler characteristic 2g - 2 + n, and that motivates the adjective topological. Let us make a few examples. The input spectral curve already produces ω_{0,1} and ω_{0,2}.  So the first layers read:

Layer 2g - 2 + n = 1: computation of ω_{1,1}, ω_{0,3}

Layer 2g - 2 + n = 2: computation of ω_{1,2}, ω_{0,4}

Layer 2g - 2 + n = 3: computation of ω_{2,1}, ω_{1,3}, ω_{0,5}

Layer 2g - 2 + n = 4: computation of ω_{2,2}, ω_{1,4}, ω_{0,6}

Layer 2g - 2 + n = 5: computation of ω_{3,1}, ω_{2,3}, ω_{1,5}, ω_{0,7}

Layer 2g - 2 + n = 6: computation of ω_{3,2}, ω_{2,4}, ω_{1,6}, ω_{0,8}

Layer 2g - 2 + n = 7: computation of ω_{4,1}, ω_{3,3}, ω_{2,5}, ω_{1,7}, ω_{0,9}

Layer 2g - 2 + n = 8: computation of ω_{4,2}, ω_{3,4}, ω_{2,6}, ω_{1,8}, ω_{0,10}

.......

and so on. Each layer uses all preceding layers in combination with ω_{0,1} and ω_{0,2} and a certain recursion kernel.

The cover of my PhD thesis in 2017 at the University of Amsterdam with Prof. Shadrin.

 Let us mention a few examples of enumerative geometric problems computed by TR (we are omitting important details, normalisations, and citations, to keep the reading light. For more details we refer to Eynard's beautiful book "Counting Surfaces") : 

All examples above are computed using the same unifying universal formula. Many more examples have already been found and worked out, despite the methods being so recent. Several important restatements and generalisations of TR have been developed.

More to be written (and much more to be discovered) ....