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We present a scheme for achieving macroscopic quantum superpositions in optomechanical systems by using single photon postselection and detecting them with nested interferometers. This method relieves many of the challenges associated with…

Quantum Physics · Physics 2012-10-08 Brian Pepper , Roohollah Ghobadi , Evan Jeffrey , Christoph Simon , Dirk Bouwmeester

The design of an interferometric array should allow optimal instrumental response regarding all possible source positions, times of integration and scientific goals. It should also take into account constraints such as forbidden regions on…

Astrophysics · Physics 2009-11-07 F. Boone

Optimal designs are usually model-dependent and likely to be sub-optimal if the postulated model is not correctly specified. In practice, it is common that a researcher has a list of candidate models at hand and a design has to be found…

Statistics Theory · Mathematics 2023-03-29 Mingyao Ai , Holger Dette , Zhengfu Liu , Jun Yu

Machine unlearning algorithms aim to remove the influence of specific training samples, ideally recovering the model that would have resulted from training on the remaining data alone. We study unlearning in the overparameterized setting,…

Machine Learning · Computer Science 2025-10-24 Jacob L. Block , Aryan Mokhtari , Sanjay Shakkottai

Optical interferometry has made tremendous development in fundamentals and applications of light. Traditional optical interferometry using simplex plane phase light just allows one dimensional measurement, but incapable of retrieving…

Optics · Physics 2019-12-10 Liang Fang , Zhenyu Wan , Jian Wang

We conducted an extensive computational experiment, lasting multiple CPU-years, to optimally select parameters for two important classes of algorithms for finding sparse solutions of underdetermined systems of linear equations. We make the…

Numerical Analysis · Computer Science 2015-05-14 Arian Maleki , David L. Donoho

The high-precision interferometric measurement of an unknown phase is the basis for metrology in many areas of science and technology. Quantum entanglement provides an increase in sensitivity, but present techniques have only surpassed the…

Quantum Physics · Physics 2011-01-25 G. Y. Xiang , B. L. Higgins , D. W. Berry , H. M. Wiseman , G. J. Pryde

On the one hand, artificial neural networks have many successful applications in the field of machine learning and optimization. On the other hand, interferometers are integral parts of any field that deals with waves such as optics,…

Quantum Physics · Physics 2023-10-26 Arun Sehrawat

Shearing interferometry is a common-path quantitative phase imaging technique in which an object beam interferes with a laterally shifted replica of itself, providing high temporal stability, reduced sensitivity to environmental noise,…

Current optical interferometers are affected by unknown turbulent phases on each telescope. In the field of radio-interferometry, the self-calibration technique is a powerful tool to process interferometric data with missing phase…

Optics · Physics 2009-11-13 Serge Meimon , Laurent M. Mugnier , Guy Le Besnerais

Detection of phase transitions is a critical task in statistical physics, traditionally pursued through analytic methods and direct numerical simulations. Recently, machine-learning techniques have emerged as promising tools in this…

Statistical Mechanics · Physics 2025-02-19 Burak Çivitcioğlu , Rudolf A. Römer , Andreas Honecker

Machine learning, especially deep learning, is dramatically changing the methods associated with optical thin-film inverse design. The vast majority of this research has focused on the parameter optimization (layer thickness, and structure…

Machine Learning · Computer Science 2021-02-19 Anqing Jiang , Liangyao Chen , Osamu Yoshie

The optical elements comprised of sub-diffractive light scatterers, or metasurfaces, hold a promise to reduce the footprint and unfold new functionalities of optical devices. A particular interest is focused on metasurfaces for manipulation…

We propose a systematic methodology to identify the topological phase transition through a self-supervised machine learning model, which is trained to correlate system parameters to the non-local observables in time-of-flight experiments of…

Quantum Gases · Physics 2021-09-01 Chi-Ting Ho , Daw-Wei Wang

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

Supervised operator learning centers on the use of training data, in the form of input-output pairs, to estimate maps between infinite-dimensional spaces. It is emerging as a powerful tool to complement traditional scientific computing,…

Machine Learning · Computer Science 2024-08-14 Nicholas H. Nelsen , Andrew M. Stuart

The problem of unambiguously distinguishing among nonorthogonal but linearly independent quantum states can be solved by mapping the set of nonorthogonal quantum states onto a set of orthogonal ones, which can then be distinguished without…

Quantum Physics · Physics 2009-11-06 Yuqing Sun , Mark Hillery , Janos Bergou

This paper reported a general noninterferometric high-accuracy quantitative phase imaging (QPI) method for arbitrary complex valued objects. Given by a typical 4f optical configuration as the imaging system, three frames of small-window…

Image and Video Processing · Electrical Eng. & Systems 2021-05-05 Jianhui Huang , An Pan , Huiliang Jin , Guoxiang Meng , Qian Ye

Programmable photonic circuits of reconfigurable interferometers can be used to implement arbitrary operations on optical modes, facilitating a flexible platform for accelerating tasks in quantum simulation, signal processing, and…

Emerging Technologies · Computer Science 2021-09-28 Saumil Bandyopadhyay , Ryan Hamerly , Dirk Englund

The autonomous operation of flexible-wing aircraft is technically challenging and has never been presented within literature. The lack of an exact modeling framework is due to the complex nonlinear aerodynamic relationships governed by the…

Systems and Control · Electrical Eng. & Systems 2021-03-31 Mohammed Abouheaf , Nathaniel Mailhot , Wail Gueaieb , Davide Spinello
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