387 citations · 413 across the 5 of their papers we have counts for
9 papers
A highly efficient tensor network algorithm for multi-asset Fourier options pricing
Michael Kastoryano, Nicola Pancotti
Risk assessment and in particular derivatives pricing is one of the core areas in computational finance and accounts for a sizeable fraction of the global computing resources of th…
Learning Neural Network Quantum States with the Linear Method
J. Thorben Frank, Michael J. Kastoryano
Due to the strong correlations present in quantum systems, classical machine learning algorithms like stochastic gradient descent are often insufficient for the training of neural…
Classical restrictions of generic matrix product states are quasi-locally Gibbsian
Yaiza Aragonés-Soria, Johan Åberg, Chae-Yeun Park +1
We show that the norm squared amplitudes with respect to a local orthonormal basis (the classical restriction) of finite quantum systems on one-dimensional lattices can be exponent…
Avoiding local minima in variational quantum eigensolvers with the natural gradient optimizer
David Wierichs, Christian Gogolin, Michael Kastoryano
We compare the BFGS optimizer, ADAM and Natural Gradient Descent (NatGrad) in the context of Variational Quantum Eigensolvers (VQEs). We systematically analyze their performance on…
Geometry of learning neural quantum states
Chae-Yeun Park, Michael J. Kastoryano
Combining insights from machine learning and quantum Monte Carlo, the stochastic reconfiguration method with neural network Ansatz states is a promising new direction for high-prec…
The role of entropy in topological quantum error correction
Michael E. Beverland, Benjamin J. Brown, Michael J. Kastoryano +1
The performance of a quantum error-correction process is determined by the likelihood that a random configuration of errors introduced to the system will lead to the corruption of…