Related papers: A network of parametrically driven silicon nitride…

The use of a complex ferromagnetic system to manipulate GHz surface acoustic waves is a rich current topic under investigation, but the high-power nonlinear regime is under-explored. We introduce focused surface acoustic waves, which…

We report on the optical and mechanical characterization of arrays of parallel micromechanical membranes. Pairs of high-tensile stress, 100 nm-thick silicon nitride membranes are assembled parallel with each other with separations ranging…

Nowadays, Information Photonics is extensively studied and sees applications in many fields. The interest in this breakthrough technology is mainly stimulated by the possibility of achieving real-time data processing for high-bandwidth…

We demonstrate a method to optically map multiple modes of mechanical structures simultaneously. The fast and robust method, based on a modified phase-lock-loop, is demonstrated on a silicon nitride membrane and compared with three…

Advancing large-scale quantum computing requires superconducting circuits that combine long coherence times with compatibility with semiconductor technology. We investigate niobium nitride (NbN) coplanar waveguide resonators integrated with…

Silicon is a nonlinear material and optics based on silicon makes use of these nonlinearities to realize various functionalities required for on-chip communications. This article describes foundations of these nonlinearities in silicon at…

In this work, we investigate a tool for hybrid quantum systems that implements a transducer to map small position changes of a micro-mechanical membrane onto the polarization of a laser beam. This is achieved with an interferometric setup…

The hallmark feature of topological insulators renders edge transport virtually impervious to scattering at defects and lattice disorder. In our work, we experimentally demonstrate a topological system, using a photonic platform, in which…

The paper investigates nonlinear system identification using system output data at various linearized operating points. A feed-forward multi-layer Artificial Neural Network (ANN) based approach is used for this purpose and tested for two…

Silicon nitride (SiN) mechanical resonators with high quality mechanical properties are attractive for fundamental research and applications. However, it is challenging to maintain these mechanical properties while achieving strong coupling…

Accurate models are essential for design, performance prediction, control, and diagnostics in complex engineering systems. Physics-based models excel during the design phase but often become outdated during system deployment due to changing…

As a model of coupled nano-electromechanical resonantors we study two nonlinear driven oscillators with an arbitrary coupling strength between them. Analytical expressions are derived for the oscillation amplitudes as a function of the…

Nonreciprocal devices, such as isolator or circulator, are crucial for information routing and processing in quantum networks. Traditional nonreciprocal devices, which rely on the application of bias magnetic fields to break time-reversal…

Stress-optic modulators are emerging as a necessary building block of photonic integrated circuits tasked with controlling and manipulating classical and quantum optical systems. While photonic platforms such as lithium niobate and silicon…

Topological Insulator-based devices can transport electrons/photons at the surfaces of materials without any back reflections, even in the presence of obstacles. Topological properties have recently been studied using non-reciprocal…

Magnonics and magnon spintronics aim at the utilization of spin waves and magnons, their quanta, for the construction of wave-based logic networks via the generation of pure all-magnon spin currents and their interfacing with electrical…

This paper addresses the problem of optimally controlling nonlinear systems with norm-bounded disturbances and parametric uncertainties while robustly satisfying constraints. The proposed approach jointly optimizes a nominal nonlinear…

The increasing resource demands of artificial neural networks have prompted the exploration of novel platforms better suited for machine learning. In this context, phase oscillators represent a promising candidate due to their intrinsic…

Maximally synchronizable networks (MSNs) are acyclic directed networks that maximize synchronizability. In this paper, we investigate the feasibility of transforming networks of coupled oscillators into their corresponding MSNs. By tuning…

Guided phonons have become an increasingly important platform for classical and quantum information processing. While conventional surface acoustic wave systems are typically only guided in the vertical direction, two-dimensionally confined…