On the ultimate complexity of factorials

AbstractIt has long been observed that certain factorization algorithms provide a way to write the product of many different integers succinctly. In this paper, we study the problem of representing the product of all integers from 1 to n (i.e. n!) by straight-line programs. Formally, we say that a sequence of integers an is ultimately f(n)-computable, if there exists a nonzero integer sequence mn such that for any n, anmn can be computed by a straight-line program (using only additions, subtractions and multiplications) of length at most f(n). Shub and Smale [12] showed that if n! is ultimately hard to compute, then the algebraic version of NP≠P is true. Assuming a widely believed number theory conjecture concerning smooth numbers in a short interval, a subexponential upper bound (exp(clognloglogn)) for the ultimate complexity of n! is proved in this paper, and a randomized subexponential algorithm constructing such a short straight-line program is presented as well

Exponential Sums and Congruences with Factorials

We estimate the number of solutions of certain diagonal congruences involving factorials. We use these results to bound exponential sums with products of two factorials $n!m!$ and also derive asymptotic formulas for the number of solutions of various congruences with factorials. For example, we prove that the products of two factorials $n!m!$ with $\max\{n,m\}<p^{1/2+\epsilon}$ are uniformly distributed modulo $p$, and that any residue class modulo $p$ is representable in the form $m!n!+n_1! + ... +n_{49}!$ with $\max \{m,n, n_1, >..., n_{49}\} < p^{8775/8794+ \epsilon}$.Comment: 21 page

Counting arithmetic formulas

An arithmetic formula is an expression involving only the constant 1, and the binary operations of addition and multiplication, with multiplication by 1 not allowed. We obtain an asymptotic formula for the number of arithmetic formulas evaluating to as goes to infinity, solving a conjecture of E.K. Gnang and D. Zeilberger. We give also an asymptotic formula for the number of arithmetic formulas evaluating to and using exactly multiplications. Finally we analyze three specific encodings for producing arithmetic formulas. For almost all integers , we compare the lengths of the arithmetic formulas for that each encoding produces with the length of the shortest formula for (which we estimate from below). We briefly discuss the time-space tradeoff offered by each

Counting arithmetic formulas

Anarithmeticformulaisanexpressioninvolvingonlytheconstant1, and the binary operations of addition and multiplication, withmultiplicationby1notallowed.Weobtainanasymptoticformulaforthenumberofarithmeticformulasevaluatingtonasngoestoinfinity, solving a conjecture of E.K. Gnang and D. Zeilberger. Wegivealsoanasymptoticformulaforthenumberofarithmeticfor-mulas evaluating tonand using exactlykmultiplications. Finallyweanalyzethreespecificencodingsforproducingarithmeticfor-mulas. For almost all integersn, we compare the lengths of thearithmetic formulas fornthat each encoding produces with thelength of the shortest formula forn(which we estimate from be-low).Webrieflydiscussthetime-spacetradeoffofferedbyeac

Lower Bounds for Straight Line Factoring

Straight line factoring algorithms include a variant Lenstra\u27s elliptic curve method. This note proves lower bounds on the length of straight line factoring algorithms

Counting arithmetic formulas

An arithmetic formula is an expression involving only the constant 1, and the binary operations of addition and multiplication, with multiplication by 1 not allowed. We obtain an asymptotic formula for the number of arithmetic formulas evaluating to as goes to infinity, solving a conjecture of E.K. Gnang and D. Zeilberger. We give also an asymptotic formula for the number of arithmetic formulas evaluating to and using exactly multiplications. Finally we analyze three specific encodings for producing arithmetic formulas. For almost all integers , we compare the lengths of the arithmetic formulas for that each encoding produces with the length of the shortest formula for (which we estimate from below). We briefly discuss the time-space tradeoff offered by each