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Mirror descent (MD) is a powerful first-order optimization technique that subsumes several optimization algorithms including gradient descent (GD). In this work, we develop a semi-definite programming (SDP) framework to analyze the…

Optimization and Control · Mathematics 2022-01-19 Youbang Sun , Mahyar Fazlyab , Shahin Shahrampour

Harnessing dipolar spin environments as controllable quantum resources is a central challenge in solid-state quantum technologies. Here, we report the observation of a coherent mesoscopic spin state in a disordered ensemble of…

Quantum Physics · Physics 2026-02-20 Taewoong Yoon , Sangwon Oh , Junghyun Lee , Hyunyong Choi

Decentralized optimization is typically studied under the assumption of noise-free transmission. However, real-world scenarios often involve the presence of noise due to factors such as additive white Gaussian noise channels or…

Optimization and Control · Mathematics 2023-07-28 Suhail M. Shah , Raghu Bollapragada

We analyze the noise in macro-particle methods used in plasma physics and fluid dynamics, leading to approaches for minimizing the total error, focusing on electrostatic models in one dimension. We describe kernel density estimation for…

Plasma Physics · Physics 2021-06-30 E. G. Evstatiev , J. M. Finn , B. A. Shadwick , N. Hengartner

Localized spins in the solid state are attracting widespread attention as highly sensitive quantum sensors with nanoscale spatial resolution and fascinating applications. Recently, adaptive measurements were used to improve the dynamic…

Quantum Physics · Physics 2018-09-26 Yi-Hao Zhang , Wen Yang

The single sideband (SSB) framework of analytical electron ptychography can account for the presence of residual geometrical aberrations induced by the probe-forming lens. However, the accuracy of this aberration correction method is highly…

Effective spin mixing conductance (ESMC) across the nonmagnetic metal (NM)/ferromagnet interface, spin Hall conductivity (SHC) and spin diffusion length (SDL) in the NM layer govern the functionality and performance of pure spin current…

Materials Science · Physics 2016-09-02 L. Ma , H. A. Zhou , L. Wang , X. L. Fan , W. J. Fan , D. S. Xue , K. Xia , G. Y. Guo , S. M. Zhou

This work considers finding optimal positions for the electrodes within the Bayesian paradigm based on available prior information on the conductivity; the aim is to place the electrodes so that the posterior density of the (discretized)…

Optimization and Control · Mathematics 2014-09-11 Nuutti Hyvönen , Aku Seppänen , Stratos Staboulis

In this paper, optimal control problems governed by diffusion equations with Dirichlet and Neumann boundary conditions are investigated in the framework of the gradient discretisation method. Gradient schemes are defined for the optimality…

Numerical Analysis · Mathematics 2018-10-09 Jerome Droniou , Neela Nataraj , Devika Shylaja

Defects in silicon carbide are of intense and increasing interest for quantum-based applications due to this material's properties and technological maturity. We calculate the multi-particle symmetry adapted wave functions of the negatively…

Mesoscale and Nanoscale Physics · Physics 2016-03-23 Ö. O. Soykal , Pratibha Dev , Sophia E. Economou

Qubits require a compromise between operation speed and coherence. Here, we demonstrate a compromise-free singlet-triplet (ST) qubit, where the qubit couples maximally to the driving field while simultaneously coupling minimally to the…

We consider an optimal control problem subject to the thin-film equation which is deduced from the Navier--Stokes equation. The PDE constraint lacks well-posedness for general right-hand sides due to possible degeneracies; state constraints…

Optimization and Control · Mathematics 2015-08-11 Markus Klein , Andreas Prohl

Atom interferometers are reaching sensitivities fundamentally constrained by quantum fluctuations. A main challenge is to integrate entanglement into quantum sensing protocols to enhance precision while ensuring robustness against noise and…

Coordinate descent algorithms are widely used in machine learning and large-scale data analysis due to their strong optimality guarantees and impressive empirical performance in solving non-convex problems. In this work, we introduce Block…

Optimization and Control · Mathematics 2024-12-17 Zhijie Yuan , Ganzhao Yuan , Lei Sun

We study an optimization problem that aims to determine the shape of an obstacle that is submerged in a fluid governed by the Stokes equations. The mentioned flow takes place in a channel, which motivated the imposition of a Poiseuille-like…

Numerical Analysis · Mathematics 2021-08-13 John Sebastian H. Simon , Hirofumi Notsu

Noise-induced control imperfection is an important problem in applications of diamond-based nano-scale sensing, where measurement-based strategies are generally utilized to correct low-frequency noises in realtime. However, the spin-state…

Quantum Physics · Physics 2023-03-31 Nanyang Xu , Feifei Zhou , Xiangyu Ye , Xue Lin , Bao Chen , Ting Zhang , Feng Yue , Bing Chen , Ya Wang , Jiangfeng Du

We use all-electrical methods to inject, transport, and detect spin-polarized electrons vertically through a 350-micron-thick undoped single-crystal silicon wafer. Spin precession measurements in a perpendicular magnetic field at different…

Materials Science · Physics 2009-11-13 Biqin Huang , Douwe J. Monsma , Ian Appelbaum

We consider a mechanism of spin decay for an electron spin in a quantum dot due to coupling to a nearby quantum point contact (QPC) with and without an applied bias voltage. The coupling of spin to charge is induced by the spin-orbit…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 Massoud Borhani , Vitaly N. Golovach , Daniel Loss

In this paper, we design a controller for an interconnected system composed of a linear Stochastic Differential Equation (SDE) controlled through a linear hetero-directional hyperbolic Partial Differential Equation (PDE). Our objective is…

Optimization and Control · Mathematics 2025-02-19 Gabriel Velho , Jean Auriol , Islam Boussaada , Riccardo Bonalli

We consider the problem of finding optimal piecewise constant approximations of one-dimensional signals. These approximations should consist of a specified number of segments (samples) and minimise the mean squared error to the original…

Signal Processing · Electrical Eng. & Systems 2019-06-12 Leif Bergerhoff , Joachim Weickert , Yehuda Dar
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