Programmable Bell state generation in an integrated thin film lithium niobate circuit [PDF]
Light: Science & ApplicationsEntanglement is central to quantum technologies such as cryptography, sensing, and computing. Photon pairs generated via nonlinear optical processes are excellent for preparing entangled states due to their long coherence times and compatibility with ...
Andreas Maeder +5 more
doaj +2 more sources
Broadband THz quantum cascade laser frequency combs with surface emission and inverse-designed facet reflectors [PDF]
EPJ Web of Conferences, 2023 We present a planarized waveguide cavity with an integrated broadband output coupler that improves both the output power and far-field properties of THz quantum cascade laser frequency combs. The laser mirror reflectivity can be tuned by the shape of the
Senica Urban +5 more
doaj +1 more source
Surface-emitting THz quantum cascade laser frequency comb with tunable external mirror dispersion compensation [PDF]
EPJ Web of Conferences, 2023 We present a surface emitting THz quantum cascade laser frequency comb with an adjustable chromatic dispersion compensation via a mechanically tunable GTI cavity.
Digiorgio Valerio +5 more
doaj +1 more source
Field-enhancing tapered planarized waveguides for THz quantum cascade laser frequency combs [PDF]
EPJ Web of Conferences, 2022 We present a new planarized waveguide geometry for THz quantum cascade laser frequency combs with improved waveguide losses, RF and thermal dissipation properties.
Senica Urban +8 more
doaj +1 more source
Coherent walk and lock in driven fast-gain frequency-combs [PDF]
EPJ Web of Conferences, 2023 Locking multiple modes into a frequency comb is key for multiple metrological applications, and a great effort has been therefore invested in this challenge over the last decade. The most common techniques are based on either nonlinearities or modulation
Heckelmann Ina +5 more
doaj +1 more source
Group-Invariant Quantum Machine Learning [PDF]
PRX Quantum, 2022 Quantum Machine Learning (QML) models are aimed at learning from data encoded in quantum states. Recently, it has been shown that models with little to no inductive biases (i.e., with no assumptions about the problem embedded in the model) are likely to ...
Martín Larocca +5 more
semanticscholar +1 more source
Covariant quantum kernels for data with group structure [PDF]
Nature Physics, 2021 The use of kernel functions is a common technique to extract important features from datasets. A quantum computer can be used to estimate kernel entries as transition amplitudes of unitary circuits.
Jennifer R. Glick +6 more
semanticscholar +1 more source
Speeding up Learning Quantum States through Group Equivariant Convolutional Quantum Ans{ä}tze [PDF]
PRX Quantum, 2021 We develop a theoretical framework for $S_n$-equivariant convolutional quantum circuits with SU$(d)$-symmetry, building on and significantly generalizing Jordan's Permutational Quantum Computing (PQC) formalism based on Schur-Weyl duality connecting both
Han Zheng +4 more
semanticscholar +1 more source
Nanoimprinting for all-polymer electro-optic waveguide devices [PDF]
EPJ Web of Conferences, 2023 We performed the design and fabrication of polymer waveguide circuits, aiming for applications as electro-optic devices. Uniform waveguides with over one centimeter of length were fabricated by soft nanoimprint lithography.
Henrique Franciele +9 more
doaj +1 more source
PRX Quantum, 2023 We develop a density-matrix renormalization group (DMRG) algorithm for the simulation of quantum circuits. This algorithm can be seen as the extension of the time-dependent DMRG from the usual situation of Hermitian Hamiltonian matrices to quantum ...
T. Ayral +5 more
semanticscholar +1 more source