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Uniform / Unified Field Theory

Phil Bouchard

Imagine traveling through space at warp speed.
Fiction you say? Think again!


Author Phil Bouchard - Finite Theory of the Universe

Phil Bouchard, a mathematics scholar and computer science professional, has worked in commercial software development for companies in Ottawa and San Diego. As an astrophysics enthusiast, he has always thought this science was stagnant nonetheless.

His book, Finite Theory of the Universe, Dark Matter Disproof, Faster Than Light Speed, comes in a collision course with Albert Einstein’s Theory of relativity. The current mathematical representation of General Relativity uses a four dimensional reference frame to position in space-time an object with time as a linear variable that can have both a negative and positive value. This therefore implies time becomes itself a dimension and causes the theory opening doors to ideas such as: singularity, wormhole, paradoxes and so on!

According to Phil Bouchard’s book, a recent experiment failed to detect dark matter and dark energy and that Einstein's gravitational constant is a fallacy of General Relativity. Also, the "spooky action at a distance" might not be predetermined like Einstein once said. Imagine time travel into the future, faster-than-light speed, leviation and beyond!

You will enjoy how this book shows Albert Einstein to be wrong, and how faster-than-light travel is not science-fiction.

Phil Bouchard was born in 1977 in Ottawa, Canada. A University of Sherbrooke graduate, Phil holds a decade of experience in software development, and likes visual arts & music that seeds imagination. Sportingly speaking, he’s a black belt in taekwon-do and former North-American finalist, practices muay thai, boxing, jiu-jitsu, plays ice hockey, and enjoys skiing, volleyball, surf and golf.

He is also the author of an Open Source project, a shareware and a scientific utility:

  • Deterministic C++ memory manager of constant complexity:
  • Scientific calculator featuring accelerated 3D graphics and nonlinear regressions:
  • Scientific utility for protein sequencing spectrum generation:


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