output
19952026
most citedElectromagnetic Angular Momentum

1.4k citations

Showing 2023 · quant-phShow all

27 papers · 2 filters

quant-ph2023★ 6 cited

Fourier Quantum Process Tomography

Francesco Di Colandrea, Nazanin Dehghan, Alessio D'Errico +1

The characterization of a quantum device is a crucial step in the development of quantum experiments. This is accomplished via Quantum Process Tomography, which combines the outcom…

quant-ph2023★ 2 cited

Algebra of Nonlocal Boxes and the Collapse of Communication Complexity

Pierre Botteron, Anne Broadbent, Reda Chhaibi +2

Communication complexity quantifies how difficult it is for two distant computers to evaluate a function f(X,Y), where the strings X and Y are distributed to the first and second c…

quant-ph2023★ 6 cited

Dynamic Control of Spontaneous Emission Using Magnetized InSb Higher-Order-Mode Antennas

Sina Aghili, Rasoul Alaee, Amirreza Ahmadnejad +5

We exploit InSb's magnetic-induced optical properties to propose THz sub-wavelength antenna designs that actively tune the radiative decay rates of dipole emitters at their proximi…

quant-ph2023★ 9 cited

Seeding Gaussian boson samplers with single photons for enhanced state generation

Valerio Crescimanna, Aaron Z. Goldberg, Khabat Heshami

Non-Gaussian quantum states are crucial to fault-tolerant quantum computation with continuous-variable systems. Usually, generation of such states involves trade-offs between succe…

quant-ph2023★ 12 cited

Generating a 4-photon Tetrahedron State: Towards Simultaneous Super-sensitivity to Non-commuting Rotations

Hugo Ferretti, Y. Batuhan Yilmaz, Kent Bonsma-Fisher +5

It is often thought that the super-sensitivity of a quantum state to an observable comes at the cost of a decreased sensitivity to other non-commuting observables. For example, a s…

quant-ph2023★ 2 cited

Deep Quantum Graph Dreaming: Deciphering Neural Network Insights into Quantum Experiments

Tareq Jaouni, Sören Arlt, Carlos Ruiz-Gonzalez +3

Despite their promise to facilitate new scientific discoveries, the opaqueness of neural networks presents a challenge in interpreting the logic behind their findings. Here, we use…