Summary
- Postquant Labs has launched the Quip Network, a blockchain testnet enabling mining via quantum as well as traditional hardware.
- This system utilizes optimization problems based on the Ising model instead of Bitcoin-style hashing.
- Postquant claims the network could also monitor developments in quantum computing that might threaten Bitcoin’s cryptographic security.
A startup collaborating with D-Wave, a quantum computing firm, has developed a novel crypto mining testnet that substitutes traditional Bitcoin-style hashing with optimization challenges that quantum systems may resolve more effectively.
Postquant Labs introduced the Quip Network, described as the first publicly accessible quantum-classical blockchain testnet. It allows users to mine cryptocurrency using both quantum computers and conventional CPUs and GPUs, focusing on solving optimization problems rather than hash-based calculations.
According to Richard Carback, CTO and co-founder of Postquant Labs, “With Bitcoin, you solve the hashcash problem, while we search for an Ising model that meets a certain energy target, a challenge classical computers struggle with but quantum computers can address much faster.”
In addition to mining, the Quip Network focuses on solving Ising model optimization issues, which use an energy function related to interacting binary variables. Successful miners earn QUIP tokens, designed to facilitate access to network-connected quantum computing resources.
Postquant also highlights potential energy efficiency improvements; while Bitcoin mining is often criticized for its high energy usage, Quip Network anticipates needing only about 13 watts to mine a block on a quantum computer, comparable to the consumption of a single lightbulb over an hour.
However, the accessibility of quantum hardware remains limited compared to traditional mining setups. While GPUs are commonly available, quantum systems are often found only in corporate labs and universities. Postquant aims to assess progress in breaking elliptic curve cryptography through future iterations of the network.
