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We show experimentally that the fundamental ingredient of wave-based signal differentiation, namely zeros of the scattering matrix that lie exactly on the real axis, can be imposed at will and in situ by purposefully perturbing an overmoded…

Applied Physics · Physics 2022-04-01 Jérôme Sol , David R. Smith , Philipp del Hougne

Aberrations limit optical systems in many situations, for example when imaging in biological tissue. Machine learning offers novel ways to improve imaging under such conditions by learning inverse models of aberrations. Learning requires…

Optics · Physics 2021-04-30 Ivan Vishniakou , Johannes D. Seelig

In this paper, we consider the problem of information-theoretic waveform design for active sensing systems such as radar for extended targets. Contrary to the popular formulation of the problem in the estimation-theoretic context, we are…

Information Theory · Computer Science 2014-02-24 Mir H. Mahmood , Mark R. Bell

The problem of suboptimality under bounded disturbances for the adaptive systems based on speed-graadient approach is discussed. A formulation of the estimated optimality of nonlinear nonlinearly parametrized adaptive control systems is…

Optimization and Control · Mathematics 2025-03-27 Alexander Fradkov

This letter investigates dynamical optimal transport of underactuated linear systems over an infinite time horizon. In our previous work, we proposed to integrate model predictive control and the celebrated Sinkhorn algorithm to perform…

Optimization and Control · Mathematics 2023-08-16 Kaito Ito , Kenji Kashima

This paper addresses Online Convex Optimization (OCO) problems where the constraints have additive perturbations that (i) vary over time and (ii) are not known at the time to make a decision. Perturbations may not be i.i.d. generated and…

Optimization and Control · Mathematics 2019-06-04 Víctor Valls , George Iosifidis , Douglas J. Leith , Leandros Tassiulas

As a consequence of the wave nature of light, invisibility devices based on isotropic media cannot be perfect. The principal distortions of invisibility are due to reflections and time delays. Reflections can be made exponentially small for…

Optics · Physics 2009-11-11 Ulf Leonhardt

We consider stochastic optimization with delayed gradients where, at each time step $t$, the algorithm makes an update using a stale stochastic gradient from step $t - d_t$ for some arbitrary delay $d_t$. This setting abstracts asynchronous…

Optimization and Control · Mathematics 2021-11-16 Alon Cohen , Amit Daniely , Yoel Drori , Tomer Koren , Mariano Schain

Undesired wave reflections, which occur at domain boundaries in flow simulations with free-surface waves, can be minimized by applying source terms in the vicinity of the boundary to damp the waves. Examples of such approaches are absorbing…

Fluid Dynamics · Physics 2017-11-13 Robinson Perić , Moustafa Abdel-Maksoud

We present a new measurement principle to determine the absolute time delay of a waveform from an optical reference plane to an electrical reference plane and vice versa. We demonstrate a method based on this principle with 2 ps…

Optics · Physics 2018-05-28 H. Z. Peek , T. J. Pinkert , P. P. M. Jansweijer , J. C. J. Koelemeij

We propose an adaptive method for online time-varying (TV) convex optimization, termed $\mathcal{L}_{1}$ adaptive optimization ($\mathcal{L}_{1}$-AO). TV optimizers utilize a prediction model to exploit the temporal structure of TV…

Optimization and Control · Mathematics 2025-03-04 Jinrae Kim , Naira Hovakimyan

The response of the Advanced LIGO interferometers is known to vary with time [arXiv:1608.05134]. Accurate calibration of the interferometers must therefore track and compensate for temporal variations in calibration model parameters. These…

Instrumentation and Methods for Astrophysics · Physics 2023-01-11 Madeline Wade , Aaron D. Viets , Theresa Chmiel , Madeline Stover , Leslie Wade

We consider the setting of online convex optimization with adversarial time-varying constraints in which actions must be feasible w.r.t. a fixed constraint set, and are also required on average to approximately satisfy additional…

Machine Learning · Computer Science 2024-02-15 Dan Garber , Ben Kretzu

Optical aberrations prevent telescopes from reaching their theoretical diffraction limit. Once estimated, these aberrations can be compensated for using deformable mirrors in a closed loop. Focal plane wavefront sensing enables the…

Forecasting the evolution of complex systems is one of the grand challenges of modern data science. The fundamental difficulty lies in understanding the structure of the observed stochastic process. In this paper, we show that every…

Statistics Theory · Mathematics 2020-01-01 Xiucai Ding , Zhou Zhou

In this report, we propose a new adaptive time filter algorithm for the unsteady Stokes/Darcy model. First we present a first order ${\theta}$-scheme with the variable time step which is one parameter family of Linear Multi-step methods and…

Numerical Analysis · Mathematics 2022-08-29 Yi Qin , Yang Wang , Yi Li , Jian Li

In this paper we characterize sharp time-data tradeoffs for optimization problems used for solving linear inverse problems. We focus on the minimization of a least-squares objective subject to a constraint defined as the sub-level set of a…

Information Theory · Computer Science 2016-01-06 Samet Oymak , Benjamin Recht , Mahdi Soltanolkotabi

Some optical measurements require relative timing of intensity variations with accuracy much finer than the camera frame period. One motivating example is dynamic aurora, where different prompt emissions are expected to originate from…

Space Physics · Physics 2026-05-29 Juha Vierinen , Pavithiran Sivasothy , Björn Gustavsson

The least squares linear filter, also called the Wiener filter, is a popular tool to predict the next element(s) of time series by linear combination of time-delayed observations. We consider observation sequences of deterministic dynamics,…

Dynamical Systems · Mathematics 2024-04-02 Péter Koltai , Philipp Kunde

Diffractive optical information processors have demonstrated significant promise in delivering high-speed, parallel, and energy efficient inference for scaling machine learning tasks. Training, however, remains a major computational…

Optics · Physics 2025-06-27 Manon P. Bart , Nick Sparks , Ryan T. Glasser