Distributing entanglement over long distances remains a challenge due to its fragility when exposed to environmental effects. In this work, we compare various entanglement distribution protocols in a realistic noisy fiber network. We focus specifically on two schemes that only require the sending of a non-entangled carrier photon to remote nodes of the network. These protocols rely on optical CNOT gates and we vary the probability with which they can be successfully performed. Encoding our entangled states in photon polarization, we analyse the effect of depolarizing noise on the photonic states as the carrier passes through the fibers. Building a robust model of photon loss and calculating the distillable entanglement of the noisy states, we find the entanglement distribution rate. We discover that methods involving a separable carrier can reach a higher rate than the standard entanglement distribution protocol, provided that the success probability of the optical CNOT gates is sufficiently high.

A main challenge in quantum technology development is mitigating or, conversely, exploting the interaction with the environment. THENCE tackles this by devising effective TDDFT methods, exploring measurement-induced phase transitions and designing spin Hamiltonians in engineered photonic lattices.

Quantum extreme learning machines (QELMs) leverage untrained quantum dynamics to efficiently process information encoded in input quantum states, avoiding the high computational cost of training more complicated nonlinear models. On the other hand, quantum information scrambling (QIS) quantifies how the spread of quantum information into correlations makes it irretrievable from local measurements. Here, we explore the tight relation between QIS and the predictive power of QELMs. In particular, we show efficient state estimation is possible even beyond the scrambling time, for many different types of dynamics – in fact, we show that in all the cases we studied, the reconstruction efficiency at long interaction times matches the optimal one offered by random global unitary dynamics. These results offer promising venues for robust experimental QELM-based state estimation protocols, as well as providing novel insights into the nature of QIS from a state estimation perspective.

Quantum mechanics predicts that massive particles exhibit wave-like behavior. Matterwave interferometry has been able to validate such predictions through ground-breaking experiments involving microscopic systems like atoms and molecules. The wavefunction of such systems coherently extends over a distance much larger than their size, an achievement that is incredibly challenging for massive and more complex objects. Yet, reaching similar level of coherent diffusion will enable tests of fundamental physics at the genuinely macroscopic scale, as well as the development of quantum sensing apparata of great sensitivity. We report on experimentally achieving an unprecedented degree of position diffusion in a massive levitated optomechanical system through frequency modulation of the trapping potential. By starting with a pre-cooled state of motion and employing a train of sudden pulses yet of mild modulation depth, we surpass previously attained values of position diffusion in this class of systems to reach diffusion lengths that exceed the physical dimensions of the trapped nanoparticle.