5 papers
Gradient Scalability and Taylor Surrogation of Quantum Cost Landscapes
Sabri Meyer, Francesco Scala, Francesco Tacchino +1
Variational Quantum Algorithms are promising candidates for near-term quantum computing, yet they face scalability challenges due to barren plateaus, where gradients vanish exponen…
Resource-efficient quantum algorithm for linear systems of equations
Francesco Ghisoni, Francesco Scala, Daniele Bajoni +1
Finding the solution to linear systems is at the heart of many applications in science and technology. Over the years a number of algorithms have been proposed to solve this proble…
Noise-Induced Equalization in quantum learning models
Francesco Scala, Giacomo Guarnieri, Aurelien Lucchi
Quantum noise is known to strongly affect quantum computation, thus potentially limiting the performance of currently available quantum processing units. Even learning models based…
Spectral Gap Estimation via Adiabatic Preparation
Davide Cugini, Francesco Ghisoni, Angela Rosy Morgillo +1
Estimating energy gaps, i.e. the energy difference between two different states, in quantum systems is crucial for understanding their properties. Conventionally, spectral gap esti…
Towards Practical Quantum Neural Network Diagnostics with Neural Tangent Kernels
Francesco Scala, Christa Zoufal, Dario Gerace +1
Knowing whether a Quantum Machine Learning model would perform well on a given dataset before training it can help to save critical resources. However, gathering a priori informati…