Divide-and-conquer dividing by a half recurrences, of the form xn = a • x ⌈n/2⌉ + a • x ⌊n/2⌋ + p(n), n 2, appear in many areas of applied mathematics, from the analysis of algorithms to the optimization of phylogenetic balance indices. The Master Theorems that solve these equations do not provide the solution's explicit expression, only its big-Θ order of growth. In this paper we give an explicit expression -in terms of the binary decomposition of n-for the solution xn of a recurrence of this form, with given initial condition x1, when the independent term p(n) is a polynomial in ⌈n/2⌉ and ⌊n/2⌋.for the Total Cophenetic index, p Φ (n) = n 2 = ⌈n/2⌉+⌊n/2⌋
2; and for the rooted Quartet index, p rQI (n) = ⌈n/2⌉ 2 ⌊n/2⌋ 2[15]. At the moment of writing this paper, the values of S(B n ) and C(B n ) were known (see Examples 2 and 3 in Section 3), but not those of Φ(B n ) or rQI(B n ).In the context of the analysis of algorithms, divide-and-conquer recurrences like (1) and more general ones are "solved" by finding the big-Θ order of growth of x n using some Master Theorem. The original Master Theorem was obtained by Bentley, Haken, and Saxe [4] and extended in [7, §4.5-6], and since then several improved versions have been obtained by other researchers: see, for instance, [3,11,20,23,30,37,38,39]. Tipically, a Master Theorem deduces the asymptotic behaviour of a solution x n of (1) from that of the independent term of the recurrence (and, in more general recurrences, from the number of parts into which the input is divided, which we fix here to 2, and the contribution of each subproblem to the general problem, which we assume here to be equal and represented by the coefficient a). Thus, Master Theorems do not provide explicit solutions of recurrences, only their asymptotic behaviour.In the analysis of algorithms, knowing the growing order of the computational cost of an algorithm on an instance of size n is usually enough. But in other applications, like for instance in order to normalize balance indices as we explained above, an explicit expression for the solution is needed. Many specific divide-and-conquer recurrences are explicitly solved when needed, like for instance the cost of the mergesort algorithm in the worst case, solved as Ex. 34 in [19, Ch. 3], but no general solution is known. To our knowledge, the only attempt to find an explicit solution of Eqn. ( 1) is made by Hwang, Janson and Tsai [22] by proving that, when a = 1 and under very general conditions on the independent term p(n), the solution x n has the formwith P continuous and 1-periodic and F, Q of precise growing orders, and giving explicit expressions for P, F, Q in terms of series expansions.In this paper we consider the more restrictive case when p(n) is a polynomial in ⌈n/2⌉ and ⌊n/2⌋. In this case, we are able to give an explicit finite formula for x n in terms of the binary decomposition of n. Although for our applications the case when a = 1 was enough, our formula works for the arbitrary a case.