# Riemannian Trust Region Method for Haplotype Assembly

## TL;DR

This paper introduces a Riemannian trust region optimization method to accurately solve the haplotype assembly problem by modeling it as a sphere-constrained maximization, effectively escaping local maxima and saddle points.

## Contribution

It presents a novel manifold optimization approach using trust region methods for haplotype assembly, addressing nonconvexity challenges.

## Key findings

- High accuracy in haplotype estimation demonstrated
- Effective escape from local maxima and saddle points
- Outperforms existing methods in simulation results

## Abstract

In this letter we model the Haplotype assembly problem (HAP) as a maximization problem over an $(n-1)$-dimensional sphere. Due to nonconvexity of the feasible set, we propose a manifold optimization approach to solve the mentioned maximization problem. To escape local maxima as well as saddle points we utilize trust region method. Simulation results show that our proposed method is with high accuracy in estimation of Haplotype.