Research
Protection of Quantum Computers from Cosmic Ray Error Bursts
Independent Research • Ongoing
This description will be left intentionally vague for the purposes of potential future commercialization. Broadly speaking, it is concerned with the protection of quantum computers from cosmic rays, which generate correlated errors harder for classical quantum error correction to solve.
Empirical Tests for a Hedging Framework for the Quantum Binomial Options Pricing Model
Independent Research • 2025
The Quantum Binomial Options Pricing Model is a novel approach to pricing derivatives. It serves as a quantum analogue to the classical binomial options pricing model, using concepts from quantum mechanics like the Pauli matrices and Bloch sphere to represent the derivatives market. Through usage of a density matrix and mixed states, the model can potentially price derivatives more accurately. However, at this time there exist no clear formulae and methods for hedging derivatives through this model. This paper numerically tests the performance of the hedging framework corresponding to the model as compared to the classical model using a year of historical S\&P 500 data. The simulation reveals that the Quantum Binomial Options Pricing model is, at least in its current state, not viable for usage in actually hedging derivatives. This is due to numerical instabilities, particularly in the Quantum Theta and Quantum Vega, the former of which ends up negative, betraying fundamental financial postulates, and the latter of which is blown out of scale. We hypothesize that these nonsensical values for Quantum Theta and Quantum Vega stem from the single period nature of the model we tested, as well as the isotropic assumption of the operator A. We conclude that the single period Quantum Binomial Options Pricing Model is currently unsuitable for practical applications of hedging and that our findings reveal the necessity of rigorously testing new financial models against benchmark models like the Classical Binomial Options Pricing Model.
