NP-complete problems and tautologies

Many NP complete problems can be encoded in system of polynomial equations. For example, in partition problem one is asking whether it is possible to divide a list of integers into two lists that the sum of element of each least are equal. Given the list of elements a \in \mathbb{Z}^n one is looking for the element x \in \{ \pm 1 \}^n, such that \sum \limits_{k=1}^n x_k a_k =0 .

To encode the problem into the system of polynomial equations over \mathbb{C} one need n equations of the form x_k^2-1=0 – that will ensure variables x_k=\pm 1, and the above mentioned equation \sum \limits_{k=1}^n x_k a_k =0 . In total n+1 nonlinear equations. We can also change the variables that x'_k= \frac{x_k+1}{2} \in \{0,1\} . In some sense this variables may be easier for the analyses later.

One way to solve this equation is to linearise it, e.g. we define a new set of variables y_{(k,m)}= x'_k x'_m,\ k,m=0..n , and we set x'_0=1. Now in terms of y_{(k,m)} we have system of linear equations. Unfortunately, we have lost relationship between terms. Linear system does not “know” that y_{(2,3)}= y_2 y_3, etc. On the other hand, if solution of the original system exists it should lay in the null space of the coefficient matrix. We will try use it. Suppose, we have null space U=[u_1,..., u_K] \in \mathbb{C}^{ \frac{(n+1)(n+2)}{2} \times K }, than if system of equations has the solution all monomials will be simultaneously expressed as a linear combination of null space vectors y_{(k,m)}(c)= \sum \limits_{i=1}^K c_i u_{i,(k,m)}. The dimensionality of null space K is exactly the number of quadratic monomials minus number of equations.

So far, we were looking only at second order monomials. If we go to higher order monomials we can see that x_{k_1} x_{k_2} x_{k_3} x_{k_4}= (x_{k_1} x_{k_2}) (x_{k_3} x_{k_4})=(x_{k_1} x_{k_3}) (x_{k_2} x_{k_4})=(x_{k_1} x_{k_4})( x_{k_2} x_{k_3}). What we wrote is tautology – this is true independent of the values of x_k. This is also true for any k_1,...,k_4. So this tautologies can be written in terms of our new variables y_{(k_1,k_2)}y_{(k_3,k_4)}-y_{(k_1,k_3)}y_{(k_2,k_4)}=0, y_{(k_1,k_2)}y_{(k_3,k_4)}-y_{(k_1,k_4)}y_{(k_2,k_3)}=0. On the other hand, if we have k_m = k_n \forall m \neq n, than we does not have tautology. In any case, we can write down all tautologies for up to order 4, and their expression in terms of new variables y. Moreover, for each y_{k,m} we have its linear expression in terms of unknowns c_i. So if we expand tautologies in terms of c_i we will get a new set of quadratic equations, that must be satisfied, if original system has a solution.

Now we already know what to do. We need to linearise the system of quadratic equations, for which we need to introduce new variables b_{k,m}= c_k c_m, write down the system of linear equations, find the null space of coefficient matrix, encode b_{m,k} as a linear combination of the null space basis, and finally encode forth-order monomials in terms of new coefficient of new null space basis. Ok, we can repeat this forever, just remember to write down all quadratic tautologies in terms of known monomials (e.g. (x_1x_2x_3x_4)(x_5x_6x_7x_8)= (x_1x_2x_3x_5)(x_4x_6x_7x_8)=... many more tautologies). What is interesting here is how K changes with iterations.

Ok, I will come back here later, when I cool down and wil have more time. Note that the number of tautologies are much more (seems to be exponentially more) than the number of monomials.

Each iteration we are squaring the number of variables which encode monomials in terms of null space. Now consider only monomials with k_m \neq k_n, \forall m \neq n. If we have monomial of degree 2k than only for that monomial we have \frac{1}{2}\binom{2k}{k}, since we want to choose half variables, and one half comes from the fact that multiplication is commutative. The number of monomials is \binom{n}{2k}. So, assuming tautologies are linearly independent, we have K_0=n^2, K_{m+1}=K_m^2-\frac{1}{2}\binom{2m}{m}\binom{n}{2m} = K_m^2-\frac{1}{2}\binom{n-m}{m}\binom{n}{m} \approx K_m^2-\frac{1}{2} n^{2m}/m!. So the lower bound is asymptotically …

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2 Responses to NP-complete problems and tautologies

  1. mkatkov says:

    Many NP-complete problems can be encoded in the system of polynomial equations. Some examples are in the introduction here. Basically the idea is to encode binary variables in the equations f_k= x_k^2-1= 0, or f_k = x_k^2-x_k=0, and add one or more quadratic equations (g_k=0 ) encoding decision problem. Since the system can have exponentially many solutions finding them is hard. On the other hand, we can try to figure out if the system has solutions at all. One of the approaches is to use Nulstellensatz certificate, e.g. find the set of polynomials P_k, P'_k  \in \mathbb{K}[x_1,...x_n], where \mathbb{K} is an algebraically closed field, for example \mathbb{C} such that the following equation is satisfied 1= \sum_k P_k f_k +\sum_m P'_m g_m. The problem with this approach is that one need very high degree polynomials P_k, P'_k and the certificate has exponentially many monomials. The intuition here is following. The problem is hard since all variables are influencing other variables, otherwise the problem can be split into independent subproblems. Since all of them are important the term with monomial x_1 ... x_n has to appear in the certificate. That lead to the certificate of degree n, which has too many monomials. There is no clear way of selecting right monomials, and we need to use all of them. So the problem is that by increasing the degree of certificate the “mixing” of variables is too slow!!! And we need a way to speed-up mixing of the variables.

    Here it is. We do usual trick of linearizing quadratic equations in terms of quadratic monomials (for 3-SAT we need cubic monomials), e.g. y_{x_k,x_m}= x_k x_m,\ k, m = 0..n,\ x_0=1 . This linear system has \approx n^2 linear variables (monomials), and \approx n equations, e.g. highly under-complete. The solution of this (homogenised) linear system is \approx n^2 dimensional projective space. The original system has a solution iff there is a point c \in \mathbb{C}^{\approx n^2} in this projective space such that all corresponding equations on y_{x_k,x_m} = y_{x_0,x_k} y_{x_0, x_m}, y_{0,0}=1 are satisfied. These are quadratic equations on c, so we can write all the quadratic in c constraints. For example, y_{x_k,x_m} y_{x_p,x_q}= y_{x_k,x_p} y_{x_m,x_q}= y_{x_k,x_q} y_{x_p,x_m} (So we are using tautologies, instead of deriving them as done in propositional proof systems). Therefore, we have \approx \frac{2}{3} n^4 quadratic equations with \approx n^2 indeterminates c_k. Now we have equivalent, in terms of satisfiability, system of quadratic equations with O(n^4) equations and O(n^2) variables, and before we had O(n) quadratic equations with O(n) variables. In other words, now we have O(1) > C equations in terms of the number of monomials, and before we had o(1) equations in terms of monomials.

    Now we can write Nulstellensatz certificate for the new system. The number of independent coefficients grow faster then the number of monomials with increasing the certificate degree. Therefore, there is a fixed (independent of n) degree of certificate that depend on C. If the above arguments are correct, it would be possible to check whether NP-complete problem has a solution in polynomial time, with all consequencies.

  2. Pingback: Monomial problems | Birthofgaming

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