Abhimanue Udayan

Builder & Teacher at the intersection of computing, physics, and scalable education systems.

ABOUT ME

Abhimanue Udayan

Abhimanue Udayan

Founder of Hexagon Know

I am an avid reader and builder who develops systems at the intersection of computing, animation, and education to drive real-world impact. From an early age, science, nature, and machines became my core interests, while art, gaming, and travel evolved into my most cherished pursuits.

My background spans computational physics, numerical computing, enterprise technical operations, and years of teaching physics and supporting the development of ed-tech solutions for 4 unicorn valued companies over a time of 6 years.

In 2013, I began my corporate career as a technical support agent at AT&T ConnecTech, diagnosing and resolving technical issues across the USA. This experience helped me with my technical problem-solving skills, customer management & effective troubleshooting skills.

Later, I joined VNIT for my Master’s in Applied Physics, where I focused on classical and quantum computational physics, numerical programming, and high-performance computing. During this time, I explored Vedic Mathematics and integrated its principles with modern computational methods, engineering C++-based systems to solve hard equations called Diophantine equations with complete accuracy & remarkable speed. This work culminated in cracking the Archimedes' Cattle Problem, computing solutions exceeding 18 million digits with absolute accuracy.

My passion for teaching physics and mentoring NEET aspirants eventually evolved into building better learning systems and performance-driven education models. After years of training students, mentoring top rankers, and working with leading institutes, I founded Clear Physics Academy — an advanced physics mentorship platform focused on concept mastery, disciplined preparation, and AI-powered learning for serious NEET aspirants.

Work & Education

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Experience

Founder

Hexagon Know Private Limited

Leading the development of HK Skill, an AI-powered workforce development platform, focusing on product development and interactive learning simulations.

Associate - Curriculum Development

Aakash+Byju’s Foundation

Managed curriculum development, content creation, and quality control, enhancing engagement for students across India.

Assistant Professor- Physics

Aakash Institute, Preet Vihar, Delhi

Taught NEET Physics to over 1000+ students and helped many secure amazing results including AIR 1 in AIIMS & AIR 2 in NEET 2019

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Education

M.Sc. Applied Physics

Visvesvaraya National Institute of Technology (VNIT), Nagpur, India

Specialized in computational physics, quantum computing, and solved the Archimedes' Cattle Problem with a 206,545-digit solution.

B.Sc. Physics

Sacred Heart College, Thevara, Cochin, India

Trained in mathematical physics and numerical programming; served as Chief Editor for the college magazine.

Higher Secondary Education - Computer Science

SNDP HSS Udayamperoor, Cochin, India

Completed Higher Secondary Education, specializing in computer science, C++ programming and database management systems.

Archimedes' Cattle Problem

Explored and solved in 2017 during my Master's in Physics at VNIT Nagpur

The Archimedes' Cattle Problem is one of the most notorious puzzles in mathematical history—so complex that its solution spans 206,545 digits and remained unsolved for centuries without computational power. Solving it requires deep mastery of Diophantine equations, particularly large-scale Pell–Fermat systems.

During my master’s in physics, I specialized in Diophantine analysis and developed a high-performance C++ system capable of solving Pell–Fermat equations of arbitrary size. Built on the principles of Bhāskara II’s Chakravala method and extended with my own algorithm for linear congruences, this system was designed for scale and precision.

Using this framework, I solved over one million Pell–Fermat equations, generating insights on the solutions that were formally documented in my master’s thesis at VNIT. An interesting outcome of the project was solving the Archimedes' Cattle Problem on a standard i7 desktop—demonstrating that even historically “intractable” problems can be approached efficiently with the right mathematical and computational design.

This is just the tip of the iceberg—a powerful validation of Indian Vedic mathematics fused with modern computation.

View the complete solution

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My Domains

Startups & Small Teams

I've helped launch and grow ventures since I was a teenager.

Cybersecurity & Support

Over 5,000 support sessions taught me that trust beats hype.

AI & Learning Platforms

Using AI, I design tools that are both secure and user-friendly.

Creative Technology

Transforming ideas through art and tech.

Unity Development

Designs applications for my company Hexagon Know.

Full Stack Development

Worked on a large range of tech including quantum computing.

TECH STACK

React
Django
Postgres
Python
JavaScript
AWS
C++
C#
Unity
Photoshop
After Effects
Character Animator
Premiere Pro

HK Skill : How I Help Enterprises To Systematically Train & Grow

CREATIVE & EDUCATIONAL WORKS

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Contact Info

Open to partnerships, consulting roles, contracts, and growth opportunities.

Address

Ernakulam, Kerala, India
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🐂 What is the Archimedes' Cattle Problem?

Archimedes posed this riddle over 2,000 years ago, asking mathematicians to determine how many white, black, dappled, and brown cattle Zeus owned under a labyrinth of conditions.

The final constraint turns it into a colossal Pell–Fermat equation whose smallest solution contains 206,545 digits—far beyond pencil-and-paper mathematics.

🧠 How I approached it

I built a custom C++ engine inspired by Bhāskara II’s Chakravāla method, optimized for arbitrary-precision arithmetic and modular factorization.

  • Generated continued-fraction expansions to lock onto the minimal Pell solution
  • Vectorized the arithmetic to squeeze maximum performance from a desktop i7
  • Logged intermediate invariants to validate every step against historical references

🚀 Why it matters

This puzzle require solving a 206,545-digit long number with absolutely no room for rounding errors. It’s the kind of calculation that let's you touch the heights of numerical computing and problem solving.

Reaching the correct number meant building fast C++ based systems to computate and study fascinating mathematical problems in human history making me one of the few in the world to tackle this problem with 100% accuracy and the first to solve it with Bhakara II's Chakravala method.

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🧮 What are Diophantine Equations?

Diophantine equations are equations where you're only interested in integer solutions (whole numbers).

Simple example:

x + y = 5

→ many integer solutions like (2,3), (1,4), etc.

Hard example:

x² + y² = z²

→ gives Pythagorean triples like (3,4,5)

The challenge:

👉 No general method works for all Diophantine equations

👉 Some are insanely hard (even unsolvable in general — see Fermat's Last Theorem)

Named after: Diophantus — often called the "father of algebra"

🔥 Pell–Fermat Equation (Core Idea)

The Pell equation looks like:

x² − Dy² = 1

Where: D is a non-square integer (like 2, 3, 5, 7…)

Example:

x² − 2y² = 1

Solutions: (3,2), (17,12), (99,70)… → they grow very fast

Key Insight:

Once you find the smallest solution, you can generate infinite others.

Why it matters:

• Shows deep structure in numbers

• Connected to continued fractions

• Used in cryptography, algebraic number theory

Despite the name: It wasn't really discovered by Pierre de Fermat or Pell — Europeans misunderstood earlier Indian work (important 👇)

🇮🇳 Bhāskara's Chakravāla Method (The Real Power Move)

The Chakravāla method (meaning "cyclic method") was developed by Bhāskara II

This method solves:

x² − Dy² = 1

What makes it insane:

• It's an iterative algorithm

• Works efficiently even for huge numbers

• Way ahead of Europe by ~500 years

Basic idea (simplified):

You start with an approximate solution and repeatedly refine it using a cyclic process until you hit the exact solution.

It's like:

👉 Intelligent trial-and-error with mathematical structure

👉 Not brute force — guided convergence

Example:

For D = 61, the smallest solution is:

x = 1,766,319,049

y = 226,153,980

Bhāskara's method could handle this centuries before computers.