193 citations · 759 across the 35 of their papers we have counts for
36 papers
Experimental differentiation and extremization with analog quantum circuits
Evan Philip, Julius de Hond, Vytautas Abramavicius +8
Solving and optimizing differential equations (DEs) is ubiquitous in both engineering and fundamental science. The promise of quantum architectures to accelerate scientific computi…
Evaluation of derivatives using approximate generalized parameter shift rule
Vytautas Abramavicius, Evan Philip, Kaonan Micadei +5
Parameter shift rules are instrumental for derivatives estimation in a wide range of quantum algorithms, especially in the context of Quantum Machine Learning. Application of singl…
PulserDiff: a pulse differentiable extension for Pulser
Vytautas Abramavicius, Melvin Mathé, Gergana V. Velikova +6
Programming analog quantum processing units (QPUs), such as those produced by Pasqal, can be achieved using specialized low-level pulse libraries like Pulser. However, few currentl…
Multidimensional Quantum Generative Modeling by Quantum Hartley Transform
Hsin-Yu Wu, Vincent E. Elfving, Oleksandr Kyriienko
We develop an approach for building quantum models based on the exponentially growing orthonormal basis of Hartley kernel functions. First, we design a differentiable Hartley featu…
Potential of quantum scientific machine learning applied to weather modelling
Ben Jaderberg, Antonio A. Gentile, Atiyo Ghosh +5
In this work we explore how quantum scientific machine learning can be used to tackle the challenge of weather modelling. Using parameterised quantum circuits as machine learning m…
Quantum Iterative Methods for Solving Differential Equations with Application to Computational Fluid Dynamics
Chelsea A. Williams, Antonio A. Gentile, Vincent E. Elfving +2
We propose quantum methods for solving differential equations that are based on a gradual improvement of the solution via an iterative process, and are targeted at applications in…