Quantum computing is coming, and it will change everything. Quantum computers are a threat to bitcoin, as they would be able to crack the private/public keypairs that secure the blockchain.
QRL offers the first cryptographically secure blockchain solution that can resist the effects of quantum computing technology in the near future. In stealth since 2014, QRL was developed by academic team-leading experts in the field of cryptography and computer science. As quantum computing progresses faster than anticipated, QRL is positioned to become the first industry-grade blockchain platform to utilize it.
The QRL platform is built on an enterprise-grade consensus algorithm. This has allowed QRL to be ready for the quantum threat. The platform incorporates many of the latest academic developments in quantum-resistant cryptography, such as XMSS, allowing it to survive future advances in technology.
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To summarize, prediction of financial instability is hard, and quantum computers could be tapped to use a quantum algorithm to make this easier. Banks and other financial institutions could use information from quantum computers to provide accurate crash predictions, even before they ever had to fail. Imagine a day when a financial institution could use a quantum computer to forewarn it of impending malfeasance. Or better yet, they could use quantum computation to reconstruct the financial network and run an alarm on a hypothetical future network state.
Forecasting financial crashes with quantum computing
A key problem in financial mathematics is the forecasting of financial crashes: If we perturb asset prices, will financial institutions fail on a massive scale? This was recently shown to be a computationally intractable (NP-hard) problem. Financial crashes are inherently difficult to predict, even for a regulator which has complete information about the financial system. In this Rapid Communication, we show how this problem can be handled by quantum annealers. More specifically, we map the equilibrium condition of a toy-model financial network to the ground-state problem of a spin-1/2 quantum Hamiltonian with two-body interactions, i.e., a quadratic unconstrained binary optimization problem. The equilibrium market values of institutions after a sudden shock to the network can then be calculated via adiabatic quantum computation and, more generically, by quantum annealers. Our procedure could be implemented on near-term quantum processors, thus providing a potentially more efficient way to assess financial equilibrium and predict financial crashes.