A command line tool for computational hard problems and their reductions
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Updated
May 25, 2026 - Rust
A command line tool for computational hard problems and their reductions
Lectures for the "Problem Solving" Class at Nanjing University.
Efficient zero-knowledge arguments in the discrete log setting, revisited
Experimental Subset Sum solver for large integers using SQLite as an out-of-core storage engine.
This repository was setup to help people who believe that they solved the P vs NP problem and to help the people who review proposed solutions.
A C++ program that efficiently calculates the average values of nodes at each level in a binary tree, employing a level-order traversal approach for accurate and fast computation.
P ≠ NP via Ising Energy Landscape Fragmentation — OGP 0.00%, 35/35 checks, n = 50,000, SOS conjecture ⟹ P ≠ NP
CA and Problem Sheets assigned to expedite the learning of the Theory of Computation, formally named the Theory of Algorithms. Fourth Year, Theory of Algorithms, Software Development.
Push_swap is a project about sorting data on a stack, with a limited set of instructions, using the lowest possible number of actions. Its goal is reaching an optimized data sorting solution.
A public copy of the trend-prof empirical computational complexity measurement tool
A program that sorts a stack of numbers using a minimal set of operations
This library is developed to perform efficient and exact computation of Dempster's and Fagin-Halpern conditionals (DS-Conditional-One and DS-Conditional-All in C++)
Trackability regimes for single-cell perturbation prediction: LAOT, synthetic phase transitions, and biological benchmarks.
Python and LaTeX source code of my MSc thesis
Code written for lectures and homework in USC CSCI570-Analysis-of-Algorithms Course 🚀🚀🚀
Mathematics-Backed Peer to Peer Network — Rust node, marketplace, Lean 4 verified math
Trusted base of definitions, schemas, and verification artifacts for the Unified Rigidity Framework
Flagship executable URF/Chronos implementation with verified build and test surface
Pattern-Aware Complexity Framework (PACF) - A Python implementation for analyzing and exploiting structural patterns in NP-hard optimization problems, with a focus on the Traveling Salesman Problem (TSP). Supports extensible domains like genetic sequences and weather forecasting. Licensed under MIT
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