NP As Minimization of Degree 4 Polynomial, Integration Or Grassmann Number Problem, and New Graph Isomorphism Problem Approac
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1 P?=NP as minimization of degree 4 polynomial, integration or Grassmann number problem, and new graph isomorphism problem approaches Jarek Duda Jagiellonian University, Golebia 24, 31-007 Krakow, Poland, Email: [email protected] Abstract—While the P vs NP problem is mainly approached problem, vertex cover problem, independent set problem, form the point of view of discrete mathematics, this paper subset sum problem, dominating set problem and graph proposes reformulations into the field of abstract algebra, ge- coloring problem. All of them stay in widely understood ometry, fourier analysis and of continuous global optimization - which advanced tools might bring new perspectives and field of discrete mathematics, like combinatorics, graph approaches for this question. The first one is equivalence of theory, logic. satisfaction of 3-SAT problem with the question of reaching The unsuccessfulness of a half century search for zero of a nonnegative degree 4 multivariate polynomial (sum the answer might suggest to try to look out of this of squares), what could be tested from the perspective of relatively homogeneous field - try to apply advances algebra by using discriminant. It could be also approached as a continuous global optimization problem inside [0; 1]n, of more distant fields of mathematics, like abstract for example in physical realizations like adiabatic quantum algebra fluent in working with the ring of polynomials, computers. However, the number of local minima usually use properties of multidimensional geometry, or other grows exponentially. Reducing to degree 2 polynomial plus continuous mathematics including numerical methods n constraints of being in f0; 1g , we get geometric formulations perfecting approaches for common problem of continuous as the question if plane or sphere intersects with f0; 1gn. There will be also presented some non-standard perspectives for the global optimization. Subset-Sum, like through convergence of a series, or zeroing R 2π Q of 0 i cos('ki)d' fourier-type integral for some natural While there are approaches for reformulation of 3-SAT ki. The last discussed approach is using anti-commuting into continuous constrained optimization [1] of a complex n Grassmann numbers θi, making (A·diag(θi)) nonzero only if formula which has to additionally fulfill some constraints, A has a Hamilton cycle. Hence, the P6=NP assumption implies exponential growth of matrix representation of Grassmann this article shows that 3-SAT can be reformulated as the numbers. There will be also discussed a looking promising question of just reaching zero of a multivariate real nonneg- algebraic/geometric approach to the graph isomorphism prob- ative degree 4 polynomial, and this degree cannot be further lem - tested to successfully distinguish strongly regular graphs reduced. with up to 29 vertices. This reformulation (reduction) allows to place this prob- Keywords: 3-SAT, Hamilton cycle, discriminant, fourier lem in both global continuous optimization (unconstrained) analysis, Grassmann numbers, adiabatic quantum comput- and abstract algebra. Hence, it allows to translate the com- ers, cryptography, graph isomorphism problem plexity of NP-complete problems to possibly exponential growth of the number of local minima of such multivariate polynomial, what suggests similar issue for recently popular I. INTRODUCTION arXiv:1703.04456v13 [cs.CC] 5 Nov 2020 adiabatic quantum computers also representing combinato- The P versus NP question is a major unsolved problem of rial tasks as (energy) optimization problems - might require computer science. It asks about existence of a polynomial exponential reduction of temperature to even distinguish time algorithm for so called NP-complete problems, for between exponentially growing number of local minima. which being a solution can be tested in a polynomial time, This degree of polynomial can be reduced further to 2 if however, there is not known efficient way to locate the we additionally enforce variables to obtain boolean values solution in exponentially large set of possibilities. This f0; 1gN . Zero of degree 2 polynomial is simple linear plane, class contains many problems which can be reformulated allowing to polynomially reduce 3-SAT to a geometric (reduced) one into another through a polynomial transfor- problem of plane or sphere intersecting with f0; 1gN . mation. Hence, existence of a polynomial time algorithm Alternatively, from the abstract algebra point of view, for one of them would imply polynomial time algorithm for polynomial formulation allows to shift the difficulty for ex- all of them. Additionally, such hypothetical efficient method ample into the problem of calculating multivariate analogue would endanger most of currently used cryptography. of discriminant of polynomial. Some well known representants of this family are: 3- There will be also presented solution of Hamilton cycle SAT, Hamilton cycle problem, knapsack problem, travelling problem using anti-commuting Grassmann numbers, sug- salesman problem, subgraph isomorphism problem, clique gesting requirement of exponential growth of representation 2 for this algebra. Alternatively, derivatives can be also used The first one looks at four possibilities for x and y variables, for a related approach. enforcing the use of v = x _ y. Thanks of it, the second alternative becomes equivalent to x _ y _ z. II. 3-SAT AS GLOBAL MINIMIZATION OF POLYNOMIAL The left hand side alternative has 4 possibilities for being 3-SAT is the problem of determining if we can assign 0/1 satisfied, hence can be transformed into minimization of values to boolean variables, such that all alternatives from degree 8 nonnegative polynomial. Summing such 2m polynomials for all m c, we get n+m a chosen set of clauses (triples) are satisfied: 8i=1;:::;m Ci variable nonnegative polynomial of degree 8, which reaches . The alternatives may contain negation, for example C1 ^ zero if and only if the 3-SAT can be satisfied. C2 = (x _:y _ z) ^ (:x _ y _ u). Denote n as the number of variables, m as the number of clauses. We will now translate this conjugation of alternatives C. Approach for degree 6 into a nonnegative polynomial which zeros correspond to The main contribution of this paper is alternative approach satisfying variable assignments. The boolean variables will which directly obtains degree 6 polynomial and can be be transformed into real continuous variables, which are further reduced to degree 4 by adding m variables. enforced to finally choose 0 or 1 by the condition of zeroing Specifically, observe that C = x _ y _ z is satisfied when the polynomial. While the final values have to be discrete, the sum of representing 0/1 numbers is in f1; 2; 3g, leading their search might involve intermediately using real values to degree 6 polynomial: - especially from the [0; 1]n hypercube. _ 2 2 2 A. Degree 14 polynomial P3 (C) := (x+y+z−1) (x+y+z−2) (x+y+z−3) (3) The original author’s approach [2] from 2010 has used Reaching zero of this polynomial does not enforce vari- degree 14 polynomial, reduced to 8 by introducing one ables being in f0; 1g yet, but it can be done by additional additional variable per clause (triple). degree 4 polynomials: Specifically, the C = x _ y alternative is satisfied in 3 cases: 01, 10 and 11. It is equivalent to zeroing of degree 6 X _ X 2 2 nonnegative polynomial: p(x1; : : : ; xn) = P3 (Ci)+ xj (1−xj) (4) i=1;:::;m j=1;:::;n _ 2 2 p2 (C) := (x − 1) + y · This final polynomial of n variables is nonnegative, · (x − 1)2 + (y − 1)2 · x2 + (y − 1)2 (1) degree 6, and reaches zero if and only if the 3-SAT is satisfied. Alternative of three variables is satisfied in 7 cases: 001, 010, 100, 011, 101, 110, 111. Analogously we get degree _ D. The final reduction: degree 4 7 · 2 = 14 nonnegative polynomial p3 (C), which zeroes if and only if the alternative C is satisfied. To reduce to degree 4 polynomial, observe that the x+y+ _ We can now construct the final polynomial as sum of p3 z = 3 possibility can be avoided by adding a new variable _ for all m clauses: v - instead of P3 using polynomial: X _ p(x1; : : : ; xn) = p3 (Ci) (2) i=1;:::;m (x + y + v − 1)2(x + y + v − 2)2 + (z − v)2(z − v − 1)2 where for the negated variables we use 1 − x instead of x. For x = y = 0, the zeroing of the left hand side part This nonnegative polynomial is zero if and only if all p_ are 3 enforces v = 1, for which the right hand side part enforces zero, what is equivalent with all alternatives being satisfied. z = 1. In the remaining cases, the right hand side part allows We got degree 14 polynomial of n variables - there is a for z equal 0 or 1. natural question if this degree can be reduced at cost of at Summing the corresponding polynomials for all m most polynomial growth of the number of variables. 2 2 clauses with polynomials xi (1 − xi) for all original n variables and m additional ones, we get a nonnegative B. Reduction to degree 8 degree 4 polynomial of n+m variables, which reaches zero The original reduction has used additional variables (one if and only if the 3-SAT is satisfied. per clause) to reduce the number of possibilities satisfying Observe that if P6=NP, this degree 4 generally cannot alternative from 7 to 4, hence reducing the degree of be further reduced. Nonnegativity requires the degree to polynomial from 14 to 8. be even, so such hypothetical reduction would need to For this purpose, for each C = x _ y _ z clause introduce be to degree 2, which can be minimized in polynomial variable v and replace C with conjunction of the following time.