# Ott-Antonsen ansatz is the only admissible truncation of a circular cumulant series

## TL;DR

This paper proves that the Ott-Antonsen ansatz is the only valid truncation for circular cumulant series in phase oscillator populations, highlighting fundamental limitations and implications for low-dimensional modeling.

## Contribution

It establishes the uniqueness of the Ott-Antonsen ansatz as the only admissible truncation of circular cumulant expansions, extending the understanding of population dynamics models.

## Key findings

- Truncation of circular cumulant series other than Ott-Antonsen is forbidden.
- For linear variables, only the second cumulant is nonzero, unlike circular cumulants.
- Implications for neural population models with diverging firing rates are discussed.

## Abstract

The cumulant representation is common in classical statistical physics for variables on the real line and the issue of closures of cumulant expansions is well elaborated. The case of phase variables significantly differs from the case of linear ones; the relevant order parameters are the Kuramoto-Daido ones but not the conventional moments. One can formally introduce `circular' cumulants for Kuramoto-Daido order parameters, similar to the conventional cumulants for moments. The circular cumulant expansions allow to advance beyond the Ott-Antonsen theory and consider populations of real oscillators. First, we show that truncation of circular cumulant expansions, except for the Ott-Antonsen case, is forbidden. Second, we compare this situation to the case of the Gaussian distribution of a linear variable, where the second cumulant is nonzero and all the higher cumulants are zero, and elucidate why keeping up to the second cumulant is admissible for a linear variable, but forbidden for circular cumulants. Third, we discuss the implication of this truncation issue to populations of quadratic integrate-and-fire neurons [E. Montbri\'o, D. Paz\'o, A. Roxin, Phys. Rev. X, vol. 5, 021028 (2015)], where within the framework of macroscopic description, the firing rate diverges for any finite truncation of the cumulant series, and discuss how one should handle these situations. Fourth, we consider the cumulant-based low-dimensional reductions for macroscopic population dynamics in the context of this truncation issue. These reductions are applicable, where the cumulant series exponentially decay with the cumulant order, i.e., they form a geometric progression hierarchy. Fifth, we demonstrate the formation of this hierarchy for generic distributions on the circle and experimental data for coupled biological and electrochemical oscillators.