With P = NP, the factorization of large primes is trivial, an example for large RSA numbers.

http://pic.twitter.com/cCCbW2Icrm

http://independent.academia.edu/oarr

For factorizing a number any of these 'bases' (exclusive of each
number) is an Universal factor and can be traduces to decimal factors
i.e p*q (with p, q prime numbers) have many factors than only p*q in my
Universal Number Theory - Copyrightc (c) 2013 -2014 Oscar Riveros, All
right reserved.
The factorization of large primes are trivial, P = NP

# Mx

Oscar Riveros @maxtuno Research, Music Composition, CS, Mathematics, Physics, Philosophy, Multi-Paradigm Programming, Quantum Algorithms, H+ (I'm not an artist, I'm a scientist)

## Monday, August 18, 2014

## Monday, July 14, 2014

### NumPy O(n^2) vs P=NP O(log n)

Matrix addition 1024x1024,

NumPy O(n^2) vs P=NP O(log n)

almost 10 times faster, Pure Python.

https://dl.dropboxusercontent.com/u/25911035/peqnp.py

NumPy O(n^2) vs P=NP O(log n)

almost 10 times faster, Pure Python.

https://dl.dropboxusercontent.com/u/25911035/peqnp.py

### P = NP, A Case Study: The Sum Subset Problem

P = NP
A Case Study: The Sum Subset Problem

(techniques, algorithms, new theories and implications)

Test Suit From:

## Monday, July 7, 2014

### P = NP EXPLAINED FOR DUMMIES WITH EXAMPLES

Abstract. The purpose of this tutorial is to clarify the common questions
on my demonstration that P = NP, and their practical applications, in simple
language, and minimally technician.

UPDATE: Add O(3n+(n+1)log(n) - 2) algorithm for NP-Complete Set Cover problem P = NP Explained for Dummies with Examples

http://en.wikipedia.org/wiki/Set_cover_problem

http://www.academia.edu/7583610/P_NP_Explained_for_Dummies_with_Examples

## Sunday, July 6, 2014

### P=NP Ω(log n) Matrix Addition (with code)

The source code of video: (use with sage math)

https://dl.dropboxusercontent.com/u/25911035/%CE%A9%28log%20n%29%20Matrix%20addition%20youtube%20video.sws

"There is a big difference to write from 1 to 2^googolplex not even "god"! would know, but H(googolplex) you know it in nanoseconds. (and is exactly the same)"

"Imagine the process of information more massively and parallel, you can conceive, and limited only by the speed of light? that is P=NP & H-Family functions."

Massive and Parallel Arithmetic, P = NP Explained!!! for Dummies!!!

https://twitter.com/maxtuno/status/485652072894050304"

The Theorical Proof

https://www.academia.edu/7518078/P_NP_The_Collapse_of_Hierarchies

## Saturday, July 5, 2014

### 100x100 Matrix Addition. NumPy vs P = NP (technique) 0.003502 (ms) vs 5.99999999906e-05 (ms)

"There is a big difference to write from 1 to 2^googolplex not even
"god"! would know, but H(googolplex) you know it in nanoseconds. (and is
exactly the same)"

"Imagine the process of information more massively and parallel, you can conceive, and limited only by the speed of light? that is P=NP & H-Family functions."

100x100 Matrix Addition. NumPy vs P = NP (technique) 0.003502 (ms) vs 5.99999999906e-05 (ms)

https://twitter.com/maxtuno/status/485642472325140480

Massive and Parallel Arithmetic, P = NP Explained!!! for Dummies!!!

https://twitter.com/maxtuno/status/485652072894050304

P = NP, The Collapse of Hierarchies

https://www.academia.edu/7518078/P_NP_The_Collapse_of_Hierarchies

"Imagine the process of information more massively and parallel, you can conceive, and limited only by the speed of light? that is P=NP & H-Family functions."

100x100 Matrix Addition. NumPy vs P = NP (technique) 0.003502 (ms) vs 5.99999999906e-05 (ms)

https://twitter.com/maxtuno/status/485642472325140480

Massive and Parallel Arithmetic, P = NP Explained!!! for Dummies!!!

https://twitter.com/maxtuno/status/485652072894050304

P = NP, The Collapse of Hierarchies

https://www.academia.edu/7518078/P_NP_The_Collapse_of_Hierarchies

## Tuesday, July 1, 2014

### P = NP, The Collapse of Hierarchies

P = NP

The Collapse of Hierarchies

The Collapse of Hierarchies

The P versus NP problem is a major unsolved problem in computer science. Informally, it asks whether every problem whose solution can be quickly verified by a computer can also be quickly solved by a computer. It was introduced in 1971 by Stephen Cook in his seminal paper "The complexity of theorem proving procedures" and is considered by many to be the most important open problem in the field. And this is my modest attempt to resolve this question. I dedicate all this work to my wife Natalia Jaimes, for their infinite patience and inexhaustible love.

O. A. Riveros

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