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Phase estimation in quantum interferometry is a major scenario where the quantum advantage is significantly revealed. Recently, the optimal finite-dimensional probe states (OFPSs) for phase estimation in two-mode quantum interferometry have…

Quantum Physics · Physics 2026-05-07 Jin-Feng Qin , Jing Liu

Inter satellite laser interferometry is a central component of future space-borne gravity instruments like LISA, eLISA, NGO and future geodesy missions. The inherently small laser wavelength allows to measure distance variations with…

We present a rapid-scanning approach to fluorescence-detected two-dimensional electronic spectroscopy that combines acousto-optic phase-modulation with digital lock-in detection. The approach shifts the signal detection window to suppress…

Contemporary field-programmable gate arrays (FPGAs) are predestined for the application of finite impulse response (FIR) filters. Their embedded digital signal processing (DSP) blocks for multiply-accumulate operations enable efficient…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-10-13 Philipp Födisch , Artsiom Bryksa , Bert Lange , Wolfgang Enghardt , Peter Kaever

Compensating for nonlinear effects using digital signal processing (DSP) is complex and computationally expensive in long-haul optical communication systems due to intractable interactions between Kerr nonlinearity, chromatic dispersion…

Signal Processing · Electrical Eng. & Systems 2023-08-24 Naveenta Gautam , Sai Vikranth Pendem , Brejesh Lall , Amol Choudhary

Differential wavefront sensing is an essential technique for optimising the performance of many precision interferometric experiments. Perhaps the most extensive application of this is for alignment sensing using radio-frequency beats…

Instrumentation and Detectors · Physics 2021-05-26 Daniel D. Brown , Huy Tuong Cao , Alexei Ciobanu , Peter Veitch , David Ottaway

A Dual Digital Signal Processing VME Board was developed for the Continuous Electron Beam Accelerator Facility (CEBAF) Beam Current Monitor (BCM) system at Jefferson Lab. It is a versatile general-purpose digital signal processing board…

Hardware Architecture · Computer Science 2014-11-17 H. Dong , R. Flood , C. Hovater , J. Musson

Digital Signal Processing (DSP) and Digital Image Processing (DIP) with Machine Learning (ML) and Deep Learning (DL) are popular research areas in Computer Vision and related fields. We highlight transformative applications in image…

Two steps phase shifting interferometry has been a hot topic in the recent years. We present a comparison study of 12 representative self--tunning algorithms based on two-steps phase shifting interferometry. We evaluate the performance of…

Image and Video Processing · Electrical Eng. & Systems 2020-02-28 Víctor H. Flores , Alan Reyes-Figueroa , César Carrillo-Delgado , Mariano Rivera

All-optical image processing provides a fast and energy-efficient alternative to conventional electronic systems by directly manipulating optical wavefronts. However, metasurface-based optical processors reported to date are often limited…

Emerging analog computing substrates, such as oscillator-based Ising machines, offer rapid convergence times for combinatorial optimization but often suffer from limited scalability due to physical implementation constraints. To tackle…

Emerging Technologies · Computer Science 2026-02-19 Ruihong Yin , Yue Zheng , Chaohui Li , Ahmet Efe , Abhimanyu Kumar , Ziqing Zeng , Ulya R. Karpuzcu , Sachin S. Sapatnekar , Chris H. Kim

High-throughput imaging workflows, such as Parallel Rapid Imaging with Spectroscopic Mapping (PRISM), generate data at rates that exceed conventional real-time processing capabilities. We present a scalable FPGA-based preprocessing pipeline…

Hardware Architecture · Computer Science 2025-11-26 Weichien Liao

Low-latency, energy-efficient deep neural networks (DNNs) inference are critical for edge applications, where traditional cloud-based deployment suffers from high latency and security risks. Field-Programmable Gate Arrays (FPGAs) offer a…

Hardware Architecture · Computer Science 2025-06-10 Zeyu Guo

This paper proposes a deep sound-field denoiser, a deep neural network (DNN) based denoising of optically measured sound-field images. Sound-field imaging using optical methods has gained considerable attention due to its ability to achieve…

Signal Processing · Electrical Eng. & Systems 2023-09-22 Kenji Ishikawa , Daiki Takeuchi , Noboru Harada , Takehiro Moriya

Distributed quantum computing (DQC) is crucial for high-volume quantum processing in the NISQ era. Many different technologies are utilized to implement a quantum computer, each with a different advantages and disadvantages. Various…

Quantum Physics · Physics 2025-05-26 Juan C. Boschero , Niels M. P. Neumann , Ward van der Schoot , Frank Phillipson

We address the exploitation of an optical parametric oscillator (OPO) in the task of mitigating, at least partially, phase noise produced by phase diffusion. In particular, we analyze two scenarios where phase diffusion is typically…

We propose a method to track signals from quadrant photodiodes (QPD) in heterodyne laser interferometers that employ digital phase-locked loops for phase readout. Instead of separately tracking the four segments from the QPD and then…

Instrumentation and Detectors · Physics 2020-11-17 Gerhard Heinzel , Miguel Dovale Álvarez , Alvise Pizzella , Nils Brause , Juan José Esteban Delgado

A novel concept of self-phasematched optical frequency conversion in dispersive dielectric microcavities is studied theoretically and experimentally. We develop a time-dependent model, incorporating the dispersion into the structure of the…

Optics · Physics 2009-11-13 Alex Hayat , Meir Orenstein

Self-mixing interferometry is a measurement approach in which a laser beam is re-injected into the emitting laser itself after reflection on a target. Information about the position of the target can be obtained from monitoring the voltage…

Instrumentation and Detectors · Physics 2024-05-07 Pierre-Emmanuel Novac , Laurent Rodriguez , Stéphane Barland

We investigate methods for experimental performance enhancement of auto-encoders based on a recurrent neural network (RNN) for communication over dispersive nonlinear channels. In particular, our focus is on the recently proposed sliding…

Signal Processing · Electrical Eng. & Systems 2020-05-19 Boris Karanov , Mathieu Chagnon , Vahid Aref , Filipe Ferreira , Domanic Lavery , Polina Bayvel , Laurent Schmalen
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