The presence of an epsilon (ε) in complexity notation like O(n^{2+ε}) indicates that the algorithm's complexity is strictly greater than O(n²) for any ε > 0, but still less than O(n^{2.1}) for small values of ε. This notation suggests that while the complexity grows faster than quadratic time, it does not reach cubic time complexity. Additionally, complexities such as O(n³) or O(n⁴) would still fall under the broader classification of O(n³), highlighting the hierarchical nature of big O notation in describing algorithm efficiency.
