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quant-ph2026★ 1 cited

A simple understanding of quantum electrodynamics using Bohmian trajectories: detecting non-ontic photons

Juan José Seoane, Abdelilah Benali, Xavier Oriols

The use of Bohmian mechanics as a practical tool for modeling non-relativistic quantum phenomena of matter provides clear evidence of its success, not only as a way to interpret th…

quant-ph2026★ 3 cited

Comment on "Association between quantum paradoxes based on weak values and a realistic interpretation of quantum measurements"

Juan José Seoane, Xabier Oianguren-Asua, Albert Solé +1

In their paper (arXiv:2402.09879), Aredes and Saldanha analyze several paradoxes related to weak values and present a "general argument" that aims to show that "realistic interpret…

quant-ph2026★ 1 cited

Entanglement percolation in random quantum networks

Alessandro Romancino, Jordi Romero-Pallejà, G. Massimo Palma +1

Entanglement percolation aims at generating maximal entanglement between any two nodes of a quantum network by utilizing strategies based solely on local operations and classical c…

quant-ph2025

The Lattice Schwinger Model and Its Quantum Simulation

Joao C. Pinto Barros, Pierpaolo Fontana, Pasquale Sodano +1

In this chapter we review results on the lattice Schwinger model. In par-ticular, we show how the effect of the anomaly is reproduced on the lattice. We connect these results to re…

quant-ph2025★ 1 cited

Relativistic Quantum-Speed Limit for Gaussian Systems and Prospective Experimental Verification

Salman Sajad Wani, Aatif Kaisar Khan, Saif Al-Kuwari +1

Timing and phase resolution in satellite QKD, kilometre-scale gravitational-wave detectors, and space-borne clock networks hinge on quantum-speed limits (QSLs), yet benchmarks omit…

quant-ph2025

Shallow instantaneous quantum polynomial-time circuits for generative modeling on noisy intermediate-scale quantum hardware

Oriol Balló-Gimbernat, Marcos Arroyo-Sánchez, Paula García-Molina +2

Generative modeling is one of the most promising applications of quantum machine learning, yet training and deploying Quantum Generative Models (QGMs) on near-term hardware remains…