Related papers: On the nonlinearity of a tuning fork

This paper introduces a machine learning approach to take a nonlinear differential-equation model that exhibits qualitative agreement with a physical experiment over a range of parameter values and produce a hybrid model that also exhibits…

Instrumental variables are commonly used to estimate effects of a treatment afflicted by unmeasured confounding, and in practice instruments are often continuous (e.g., measures of distance, or treatment preference). However, available…

The objective of this paper is to understand the critical parameters that need to be addressed while designing a guitar tuner. The focus of the design lies in developing a suitable algorithm to accurately detect the fundamental frequency of…

Using the integral equations of the Noncrossing Approximation, the differential conductance is computed as a function of voltage for scattering from a two channel Kondo impurity in a point contact. The results compare well to experimental…

This paper investigates the learnability of the nonlinearity property of Boolean functions using neural networks. We train encoder style deep neural networks to learn to predict the nonlinearity of Boolean functions from examples of…

In this extended abstract, we propose a tuning approach for nonlinear mechanical systems to modify the behavior of the closed-loop system, where we are particularly interested in attenuating oscillations from the transient response. Towards…

With the advantages of high modeling accuracy and large bandwidth, recurrent neural network (RNN) based inversion model control has been proposed for output tracking. However, some issues still need to be addressed when using the RNN-based…

A low cost scheme to determine the frequency sweep nonlinearity using atomic saturated absorption spectroscopy is demonstrated. The frequency modulation rate is determined by directly measuring the interference fringe number and frequency…

The task of estimating the gradient of a function in the presence of noise is central to several forms of reinforcement learning, including policy search methods. We present two techniques for reducing gradient estimation errors in the…

We demonstrate the use of an optimized 5 core photonic lantern (PL) to simultaneously measure tip/tilt errors at the telescope focal plane, while also providing the input to an instrument. By replacing a single mode (SM) fiber with the PL…

We report the first measurement of the transverse momentum dependence of double spin asymmetries in semi-inclusive production of pions in deep inelastic scattering off the longitudinally polarized proton. Data have been obtained using a…

A recent line of research has highlighted the existence of a "double descent" phenomenon in deep learning, whereby increasing the number of training examples $N$ causes the generalization error of neural networks to peak when $N$ is of the…

Mechanical sources of nonlinear damping play a central role in modern physics, from solid-state physics to thermodynamics. The microscopic theory of mechanical dissipation [M. I . Dykman, M. A. Krivoglaz, Physica Status Solidi (b) 68, 111…

Measurement-induced nonclassical effects in a two-mode interferometer are investigated theoretically using numerical simulations and analytical results. We demonstrate that for certain parameters measurements within the interferometer lead…

Diverse applications in photonics and microwave engineering require a means of measurement of the instantaneous frequency of a signal. A photonic implementation typically applies an interferometer equipped with three or more output ports to…

We propose structured prompt tuning, a simple and effective method to improve prompt tuning. Instead of prepending a sequence of tunable embeddings to the input, we generate the soft prompt embeddings through a hypernetwork. Our approach…

A stripline-type near-field microwave probe is microfabricated for microwave impedance microscopy. Unlike the poorly shielded coplanar probe that senses the sample tens of microns away, the stripline structure removes the stray fields from…

Fine-tuning is a common practice in deep learning, achieving excellent generalization results on downstream tasks using relatively little training data. Although widely used in practice, it is lacking strong theoretical understanding. We…

Context. The QUBIC collaboration is building a bolometric interferometer dedicated to the detection of B-mode polarization fluctuations in the Cosmic Microwave Background. Aims. We introduce a self-calibration procedure related to those…

A major limitation of laser interferometers using continuous wave lasers are parasitic light fields, such as ghost beams, scattered or stray light, which can cause non-linear noise. This is especially relevant for laser interferometric…