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Solving complex optimization problems using optics

A new mathematical approach using optics helps computers solve larger, more complex optimization problems by reducing computational demands. The framework can be applied to various real-world challenges, including facility placement and data clustering, with potential benefits for a carbon-neutral future.

SourceThe University of Osaka·JournalCommunications Physics·TypeComputational simulation/modeling·DateJul 29, 2026

Researchers shed light on skin tone bias in breast cancer imaging

Researchers developed a new photoacoustic imaging technique that addresses skin tone bias in breast cancer detection. The technique, combined with specific wavelengths and beamforming methods, enhances target visibility across all skin tones, providing clearer images with improved signal-to-noise ratios.

SourceSPIE--International Society for Optics and Photonics·JournalBiophotonics Discovery·DateNov 14, 2024
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UW students have turned Schrödinger's cat on its head

The UW students' achievement enables the implementation of a fractional Fourier Transform in optical pulses, allowing for more precise pulse identification and filtering. This innovation has significant implications for spectroscopy and telecommunications, where precise signal processing is crucial.

SourceUniversity of Warsaw, Faculty of Physics·JournalPhysical Review Letters·DateJun 29, 2023

Accelerating aerial image simulations for optimal lithography

A research team from Taiwan has found a way to massively speed up aerial image simulations using wavelength scaling and fast Fourier transformation. The new algorithm improves computation speed by 4000-5000 times while maintaining only a slight intensity deviation.

SourceSPIE--International Society for Optics and Photonics·JournalJournal of Micro/Nanopatterning Materials and Metrology·DateJun 21, 2023

Scientific AI’s ‘black box’ is no match for 200-year-old method

A new study uses Fourier analysis to understand how deep neural networks learn complex physics. By analyzing the equation of a fully trained model, researchers were able to identify crucial information about how the network learns and generalizes. This breakthrough could accelerate the use of scientific deep learning in climate science.

SourceRice University·JournalPNAS Nexus·TypeComputational simulation/modeling·DateFeb 13, 2023

Light can compute any desired linear transform without a digital processor

Researchers have developed an all-optical processor that uses spatially-engineered diffractive surfaces to compute arbitrary linear transforms, eliminating the need for digital processors. The processing speed is comparable to light propagation, and the system consumes no power except for illumination.

SourceLight Publishing Center, Changchun Institute of Optics, Fine Mechanics And Physics, CAS·JournalLight Science & Applications·DateSep 28, 2021
SAMSUNG T9 Portable SSD 2TB

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Bringing a power tool from math into quantum computing

Researchers from Tokyo University of Science design a new quantum circuit that calculates the fast Fourier transform, a key algorithm in engineering. The QFFT circuit exploits superposition of states to greatly increase computational speed and is more versatile than traditional QFT.

SourceTokyo University of Science·JournalQuantum Information Processing·DateOct 14, 2020

Fast and flexible computation of optical diffraction

A team of scientists has proposed an efficient full-path calculation method for optical diffraction, leveraging the mathematical similarities between scalar and vector diffraction. The method uses the Bluestein approach to reduce computation time to sub-second levels, with superior flexibility in choosing ROIs and sampling numbers.

SourceLight Publishing Center, Changchun Institute of Optics, Fine Mechanics And Physics, CAS·DateJul 17, 2020

A new dimension in chemical nanoimaging

Researchers developed hyperspectral infrared nanoimaging, enabling recording of two-dimensional arrays of nano-FTIR spectra in a few hours. This technique allows for nanoscale-resolved chemical and structural information extraction, revealing spatial distribution and spectral anomalies of individual components.

SourceElhuyar Fundazioa·JournalNature Communications·DateFeb 23, 2017

Leaner Fourier transforms

MIT researchers have developed an algorithm that can perform Fourier transforms using close to the theoretical minimum number of samples. This could significantly reduce the time it takes for medical devices like MRI machines to scan patients, or allow astronomers to take more detailed images of the universe.

SourceMassachusetts Institute of Technology·DateDec 11, 2013
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MIT: The faster-than-fast Fourier transform

MIT researchers have found a way to increase the speed of the Fourier transform, a fundamental concept in information sciences. The new algorithm improves on the fast Fourier transform by dividing signals into narrower slices of bandwidth, allowing for dramatic tenfold increases in speed in certain cases.

SourceMassachusetts Institute of Technology·DateJan 18, 2012