Repository to developing quantum software for cracking SHA-256.
Main Problem: How to solve SHA-256 with a quantum computer.
Sub-Problems:
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How is the the cryptographic problem broadcast to the Bitcoin network to validate new blocks?
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How are guesses submitted to the Bitcoin network to validate new blocks?
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How can the quantum computer be used to solve new blocks faster than classical computing systems?
Our goal is to advance the edge in quantum cryptography for the purpose of mining digital assets with a quantum computer.
Quantum computing provides a solution for solving SHA-256 by means other than brute force, which will provide a cost-efficiency improvement in mining.
Quantum mechanics is the scientific discipline concerned with the motion and interaction of subatomic particles. Conceptually, Richard Feynman was the first person to discuss the intuition behind quantum computers, specifically to evolve computers from binary logic to a higher-order logic using quantum mechanical properties. The idea was based on the quantum mechanical principle, superposition. Superposition describes an instance where a subatomic particle occupies two independent spatial positions simultaneously. Feynman’s greatest idea was to exploit this principle to improve computational systems.
A quantum computer is a physical system harnessing quantum effects to perform computation. Quantum computers differ from classical computers because of the way in which they process information. Classical computers process information with bits, a binary representation. However, quantum computers process information with qubits, which represent information in a complex vector space.
The qubit is an innovation advancing the goal to improve the efficiency and power of classical computing methodologies with quantum mechanics. A qubit may represent a zero, one, or zero and one simultaneously in a state of superposition. The qubit allows for faster computing and less electrical power consumption compared to its classical counterpart.
Adiabatic quantum computers (AQCs) are supercomputers harnessing natural quantum state evolution to perform computation. Instead of using Silicon like traditional computer chips, the quantum chip uses a metal called Niobium. The Niobium is looped throughout the chip, connecting the qubits and acting as a superconducting metal where each loop models a quantum spin. The chip is cooled to the near zero Kelvin temperature and becomes a superconductor, a metal with properties including zero electrical resistance and magnetic flux fields. The superconducting properties allow the chip to manipulate quantum mechanical physics and eliminate noise during the computational process.
- Develop a predictive model to cut the search space and predict the next nonce.
- Quantum search algorithm for faster search.
- Boltzmann machine for prediction.
Quantum Machine Learning: A Patent Review
Blockchain Post-Quantum Security and Legal Economics
Proof of the Birch Swinnerton-Dyer Conjecture
Accelerating recurrent Ising machines in photonic integrated circuits
Towards optimal capacity-achieving transceivers with photonic integrated circuits
An Introduction to Quantum Machine Learning
The quest for a Quantum Neural Network
Prediction by Linear Regression on A Quantum Computer
Predictive Quantum Programming
Variational Quantum Boltzmann Machines
Quantum Generative Adversarial Networks for Learning and Loading Random Distributions