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We consider the problem of forecasting the aggregate demand of a pool of price-responsive consumers of electricity. The price-response of the aggregation is modeled by an optimization problem that is characterized by a set of marginal…

Optimization and Control · Mathematics 2016-07-26 Javier Saez-Gallego , Juan M. Morales

We study adaptive approximation algorithms for general multivariate linear problems where the sets of input functions are non-convex cones. While it is known that adaptive algorithms perform essentially no better than non-adaptive…

Numerical Analysis · Mathematics 2019-03-27 Yuhan Ding , Fred J. Hickernell , Peter Kritzer , Simon Mak

Adaptive optimization algorithms such as Adam are widely used in deep learning. The stability of such algorithms is often improved with a warmup schedule for the learning rate. Motivated by the difficulty of choosing and tuning warmup…

Machine Learning · Computer Science 2021-03-23 Jerry Ma , Denis Yarats

An intense beam of muons is needed to provide a luminosity on the order of 10$^{34}$ cm$^{-2}$s$^{-1}$ for a multi-TeV collider. Because muons produced by colliding a multi-MW proton beam with a target made of carbon or mercury have a large…

We introduce a new numerical method based on machine learning to approximate the solution of elliptic partial differential equations with collocation using a set of sigmoidal functions. We show that a feedforward neural network with a…

Numerical Analysis · Mathematics 2023-03-24 Francesco Calabrò , Gianluca Fabiani , Constantinos Siettos

Achieving ultimate bounds in estimation processes is the main objective of quantum metrology. In this context, several problems require measurement of multiple parameters by employing only a limited amount of resources. To this end,…

Combined-resolution simulations are an effective way to study molecular properties across a range of length- and time-scales. These simulations can benefit from adaptive boundaries that allow the high-resolution region to adapt (change size…

Computational Physics · Physics 2018-05-09 Jason A. Wagoner , Vijay S. Pande

A new family of penalty functions, adaptive to likelihood, is introduced for model selection in general regression models. It arises naturally through assuming certain types of prior distribution on the regression parameters. To study…

Methodology · Statistics 2013-08-26 Yang Feng , Tengfei Li , Zhiliang Ying

An active-sensing-based learning algorithm is proposed to solve the near-field beam alignment problem with the aid of wavenumber-domain transform matrices (WTMs). Specifically, WTMs can transform the antenna-domain channel into a sparse…

Information Theory · Computer Science 2023-11-28 Hao Jiang , Zhaolin Wang , Yuanwei Liu

Valve-point loading affects the input-output characteristics of generating units, bringing the fuel costs nonlinear and nonsmooth. This has been considered in the solution of load dispatch problems, but not in the planning phase of unit…

Optimization and Control · Mathematics 2014-04-22 João Pedro Pedroso , Mikio Kubo , Ana Viana

Complex soft matter systems can be efficiently studied with the help of adaptive resolution simulation methods, concurrently employing two levels of resolution in different regions of the simulation domain. The non-matching properties of…

We propose and analyze several schemes for cooling bosonic and fermionic atoms in an optical lattice potential close to the ground state of the no-tunnelling regime. Some of the protocols rely on the concept of algorithmic cooling, which…

Other Condensed Matter · Physics 2007-05-23 M. Popp , J. -J. Garcia-Ripoll , K. G. H. Vollbrecht , J. I. Cirac

A high-precision intra-bunch-train beam orbit feedback correction system has been developed and tested in the ATF2 beamline of the Accelerator Test Facility at the High Energy Accelerator Research Organization in Japan. The system uses the…

Accelerator Physics · Physics 2021-02-03 D. R. Bett , P. N. Burrows , C. Perry , R. Ramjiawan , N. Terunuma , K. Kubo , T. Okugi

We propose a novel adaptive approximation approach for test-time resource-constrained prediction. Given an input instance at test-time, a gating function identifies a prediction model for the input among a collection of models. Our…

Machine Learning · Statistics 2017-05-30 Feng Nan , Venkatesh Saligrama

For simulation studies of (macro) molecular liquids it would be of significant interest to be able to adjust or increase the level of resolution within one region of space, while allowing for the free exchange of molecules between open…

We analyze the performance of optomechanical cooling of a mechanical resonator in the presence of a degenerate optical parametric amplifier within the optomechanical cavity, which squeezes the cavity light. We demonstrate that this allows…

Quantum Physics · Physics 2019-12-18 Muhammad Asjad , Najmeh Etehadi Abari , Stefano Zippilli , David Vitali

We propose two variants of Newton method for solving unconstrained minimization problem. Our method leverages optimization techniques such as penalty and augmented Lagrangian method to generate novel variants of the Newton method namely the…

Optimization and Control · Mathematics 2022-05-24 Md Sarowar Morshed

It has recently been shown [Rossi et al., Phys. Rev. Lett. 119, 123603 (2017); ibid. 120, 073601 (2018)] that feedback--controlled in--loop light can be used to enhance the efficiency of optomechanical systems. We analyse the theoretical…

Quantum Physics · Physics 2018-08-14 Stefano Zippilli , Nenad Kralj , Massimiliano Rossi , Giovanni Di Giuseppe , David Vitali

In the last decade, increasing attention has been drawn to high precision optical experiments, which push resolution and accuracy of the measured quantities beyond their current limits. This challenge requires to place optical elements…

The challenging propagation environment, combined with the hardware limitations of mmWave systems, gives rise to the need for accurate initial access beam alignment strategies with low latency and high achievable beamforming gain. Much of…

Information Theory · Computer Science 2024-01-25 Daniel Tandler , Marc Gauger , Ahmet Serdar Tan , Sebastian Dörner , Stephan ten Brink