def monotone_minima(N,cost,cnt=0,inf=1<<60):
    dp=[inf]*(N+1)
    dp[0]=0
    if cnt:
        for _ in range(cnt):
            prev=dp
            dp=[inf]*(N+1)
            idx=[None]*(N+1)
            dp[0]=0
            idx[0]=0
            for n in range(N+1):
                if prev[n]+cost(n,N)<dp[N]:
                    dp[N]=prev[n]+cost(n,N)
                    idx[N]=n
            while inf in dp:
                lst=[i for i in range(N+1) if dp[i]!=inf]
                for l,r in zip(lst,lst[1:]):
                    mid=(l+r)//2
                    for n in range(idx[l],min(idx[r],mid)+1):
                        if prev[n]+cost(n,mid)<dp[mid]:
                            dp[mid]=prev[n]+cost(n,mid)
                            idx[mid]=n
    else:
        def transition(L,R):
            if R-L<=1:
                return
            mid=(L+R)//2
            transition(L,mid)
            update=[inf]*(R-mid)
            idx=[inf]*(R-mid)
            for n in range(L,mid):
                if dp[n]+cost(n,mid)<update[0]:
                    update[0]=dp[n]+cost(n,mid)
                    idx[0]=n
                if dp[n]+cost(n,R-1)<update[R-mid-1]:
                    update[R-mid-1]=dp[n]+cost(n,R-1)
                    idx[R-mid-1]=n
            while inf in update:
                lst=[i+mid for i in range(R-mid) if update[i]!=inf]
                for l,r in zip(lst,lst[1:]):
                    m=(l+r)//2
                    for n in range(idx[l-mid],min(idx[r-mid],m)+1):
                        if dp[n]+cost(n,m)<update[m-mid]:
                            update[m-mid]=dp[n]+cost(n,m)
                            idx[m-mid]=n
            for n in range(mid,R):
                dp[n]=min(dp[n],update[n-mid])
            transition(mid,R)
        transition(0,N+1)
    return dp[N]

N=int(input())
A=list(map(int,input().split()))
X=list(map(int,input().split()))
Y=list(map(int,input().split()))
inf=1<<60
def cost(l,r):
    return abs(X[l]-A[r-1])**3+abs(Y[l])**3
ans=monotone_minima(N,cost,inf=inf)
print(ans)