#MMA Contest 015 - K Make a Sequence
#リジャッジでTLEになっていたので(は？) リベンジ

#static Li Chao Tree
class Li_Chao_Tree:
    def __init__(self, X_list):
        #X_list: 線分追加・最小値計算で使用する、すべてのx座標
        #_X[i] = x, _D[x] = i  x座標とLi Chao Tree上のノードを対応
        #_L[i] = (a, b): 区間の最大値候補たり得る線分 y = ax + b
        #_S[i] = (Lt, mid, Rt): ノードの区間(index表記)  [X[Lt], X[Rt]]の閉区間が対象
        self._inf = inf = 4 * 10 ** 18
        X_list = sorted(set(X_list + [inf]))
        self._N = N = len(X_list)
        self._logN = logN = (N - 1).bit_length()
        self._size = size = 1 << logN
        self._X = X = X_list + [inf] * (size - N)
        self._D = D = {x: i for i, x in enumerate(X_list)}
        self._L = L = [None] * 2 * size
        self._S = S = [None] * size + [(i, i, i) for i in range(size)]
        for i in range(size - 1, 0, -1):
            S[i] = (S[i << 1][0], S[i << 1 | 1][0], S[i << 1 | 1][2])

    def _f(self, line, x):
        return line[0] * x + line[1]

    def _add_line(self, line, i):  #ノードi(と、その子)に線分を追加
        Q = [(i, line)]
        while Q:
            i, line = Q.pop()
            if self._L[i] == None:
                self._L[i] = line
                continue
            Lt, mid, Rt = self._S[i]
            xL, xM, xR = self._X[Lt], self._X[mid], self._X[Rt]
            hL = self._f(line, xL) < self._f(self._L[i], xL)
            hM = self._f(line, xM) < self._f(self._L[i], xM)     
            hR = self._f(line, xR) < self._f(self._L[i], xR)
            if hL == hR == True:
                self._L[i] = line
                continue
            if hL == hR == False:
                continue
            if hM == True:
                self._L[i], line = line, self._L[i]
            if hL != hM:
                Q.append((i << 1, line))
            else:
                Q.append((i << 1 | 1, line))

    def add_line(self, line, x_Lt = None, x_Rt = None):  #半開区間[x_Lt, x_Rt)に線分追加
        if x_Lt == x_Rt == None:
            self._add_line(line, 1)
            return
        Lt = self._D[x_Lt] if x_Lt != None else 0
        Rt = self._D[x_Rt] if x_Rt != None else self._D[self._inf]
        Lt, Rt = Lt + self._size, Rt + self._size
        while Lt < Rt:
            if Lt & 1:
                self._add_line(line, Lt)
                Lt += 1
            if Rt & 1:
                Rt -= 1
                self._add_line(line, Rt)
            Lt >>= 1
            Rt >>= 1

    def fold(self, x):  #座標xの最小値を計算
        i = self._D[x] + self._size
        ans = self._inf
        while i > 0:
            if self._L[i]:
                ans = min(ans, self._f(self._L[i], x))
            i >>= 1
        return ans

#Z-algorithm  TとS[i:]のLCP判定は、T+'$'+S のようにSに出ない文字を挟んで実行するとよい
#Reference: https://tjkendev.github.io/procon-library/python/string/z-algorithm.html
def Z_algorithm(S):  #SとS[i:]の最長共通接頭辞を求める
    N=len(S); A=[0]*N; i,j=1,0; A[0]=L=N
    while i<L:
        while i+j<L and S[j]==S[i+j]: j+=1
        if not j: i+=1; continue
        A[i]=j; k=1
        while L-i>k<j-A[k]: A[i+k]=A[k]; k+=1
        i+=k; j-=k
    return A


#入力受取
N, M = map(int, input().split())
A = list(map(int, input().split()))
B = list(map(int, input().split()))
C = list(map(int, input().split()))

#Bの(Aとの)最長共通接頭辞を計算
same = Z_algorithm(A + [0] + B)[N + 1:]

#DP[i]: 列Sを[0: i)まで(つまり、i文字目の直前まで)一致させるための最小コスト とする
#これはLi Chao Treeの線分追加で計算が可能
#k = same[i]として、[i: i + k)に y = C[i] * x + (DP[i] - C[i] * i) の線分を追加する
LCT = Li_Chao_Tree([i for i in range(M + 2)])
LCT.add_line((0, 0), 0, 1)  #初期化
for i in range(M):
    b = LCT.fold(i)
    k = same[i]
    if b > 10 ** 18 or k == 0:
        continue
    LCT.add_line((C[i], b - C[i] * i), i + 1, min(M, i + k) + 1)
    
#答えを出力
ans = LCT.fold(M)
print(ans if ans < 10 ** 18 else -1)