arXiv subjects

Damien Leflot

Publications and source records attributed to Damien Leflot.

3 recordsLinked to original sources

arXiv2026

Neural S-matrix bootstrap II: solvable 4d amplitudes with particle production

We study a model for nonperturbative unitarization of the four-point contact scalar amplitude in four dimensions. It is defined through an infinite sum of planar diagrams, constructed using two-particle unitarity and crossing symmetry. We reformulate the problem in terms of a set of nonlinear integral equations obeyed by the single and double discontinuities of the amplitude. We then solve them using a neural-network ansatz trained by minimizing a physics-informed loss functional. We obtain a one-parameter family of amplitudes, which exhibit rich structure: sizeable particle production, nontrivial emergent Regge behavior, Landau curves, a logarithmic decay at high energy and fixed angle. Finally, we go beyond the two-particle-reducible setup by treating the multi-particle data -- supported above the multi-particle Landau curves due to multi-particle unitarity -- as a dynamical variable. We demonstrate that it can be tuned to suppress low-spin particle production -- a phenomenon we call Aks screening -- at the cost of generating larger and oscillatory double spectral density in the multi-particle region.

hep-th↗

arXiv2024

The S-matrix bootstrap with neural optimizers I: zero double discontinuity

In this work, we develop machine learning techniques to study nonperturbative scattering amplitudes. We focus on the two-to-two scattering amplitude of identical scalar particles, setting the double discontinuity to zero as a simplifying assumption. Neural networks provide an efficient parameterization for scattering amplitudes, offering a flexible toolkit to describe their fine nonperturbative structure. Combined with the bootstrap approach based on the dispersive representation of the amplitude and machine learning's gradient descent algorithms, they offer a new method to explore the space of consistent S-matrices. We derive bounds on the values of the first two low-energy Taylor coefficients of the amplitude and characterize the resulting amplitudes that populate the allowed region. Crucially, we parallel our neural network analysis with the standard S-matrix bootstrap, both primal and dual, and observe perfect agreement across all approaches.

hep-th↗

arXiv2024

The flavor invariants of the $ν$SM

Sixty years after the experimental discovery of CP violation in the quark sector, the existence of a similar CP violation in the lepton sector is still to be established. Actually, the structure of such a violation depends crucially on the origin of the neutrino masses. In an attempt at categorizing the leptonic sources of CP violation, we studied the $ν$SM, the Standard Model extended with three generations of sterile neutrinos, that can interpolate continuously between the Dirac and Majorana scenarios of neutrino masses. In particular, we perform a classification of the Jarlskog-like flavor invariants entering CP-violating observables and we study their suppression with the heavy Majorana mass in the seesaw limit of the model. To simplify the construction of the invariants, we introduce a graph-based method. With the guidance of the Hilbert series and plethystic logarithm of the theory, we construct the \emph{generating} and \emph{primary} sets of invariants for the $ν$SM for the first time. Unlike in the Standard Model and some other theories, we find that the numbers of generating invariants and the syzygies among them cannot immediately be read off from the plethystic logarithm, but require a more careful examination. Our analysis reveals that the \emph{generating} set contains 459 invariants, out of which 208 are CP-even and 251 are CP-odd. In the seesaw limit of the $ν$SM, we show that all parameters of the UV theory can be captured in the effective theory with a certain suppression with the heavy Majorana mass, while these parameters can only appear in a \emph{flavor-invariant} way with a \emph{higher} mass suppression. Furthermore, we discuss how the necessary and sufficient conditions for CP violation can be captured by utilizing these invariants. Along the way, we present useful algorithms to enumerate and build the flavor invariants.

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