activity
20202025
most citedOptimizing optical potentials with physics-inspired learning algorithms

8 citations · 11 across the 5 of their papers we have counts for

collaborators

5 papers

quant-ph2025

Classical feature map surrogates and metrics for quantum control landscapes

Martino Calzavara, Tommaso Calarco, Felix Motzoi

We derive and analyze three feature map representations of parametrized quantum dynamics, which generalize variational quantum circuits. These are (i) a Lie-Fourier partial sum, (i…

quant-ph2024

Neutral atom transport and transfer between optical tweezers

Cristina Cicali, Martino Calzavara, Eloisa Cuestas +2

We focus on the optimization of neutral atom transport and transfer between optical tweezers, both critical steps towards the implementation of quantum processors and simulators. W…

cond-mat.quant-gas2022★ 8 cited

Optimizing optical potentials with physics-inspired learning algorithms

Martino Calzavara, Yevhenii Kuriatnikov, Andreas Deutschmann-Olek +6

We present our new experimental and theoretical framework which combines a broadband superluminescent diode (SLED/SLD) with fast learning algorithms to provide speed and accuracy i…

eess.SY2022

Iterative shaping of optical potentials for one-dimensional Bose-Einstein condensates

Andreas Deutschmann-Olek, Mohammadamin Tajik, Martino Calzavara +3

The ability to manipulate clouds of ultra-cold atoms is crucial for modern experiments on quantum manybody systems and quantum thermodynamics as well as future metrological applica…

cond-mat.quant-gas2020★ 3 cited

Dark solitons in the unitary Bose gas

M. Calzavara, L. Salasnich

We study the dilute and ultracold unitary Bose gas, which is characterized by a universal equation of state due to the diverging s-wave scattering length, under a transverse harmon…