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Nuclear magnetic resonance spectroscopy is one of the few remaining areas of physical chemistry for which polynomially scaling simulation methods have not so far been available. Here, we report such a method and illustrate its performance…

Chemical Physics · Physics 2014-07-16 Luke J. Edwards , D. V. Savostyanov , Z. T. Welderufael , Donghan Lee , Ilya Kuprov

Nematic liquid crystal (LC) molecules adsorbed on two dimensional materials are aligned along the crystal directions of the hexagonal lattice. It was demonstrated that short electric pulses can reorient the aligned LC molecules in the…

Two-dimensional (2D) photonic crystals offer strong control over the propagation of light through their bands. Theoretical methods for computing the band structure in 2D are well-established and fast because 2D photonic crystals are…

Optics · Physics 2026-03-10 Timon J. Vreman , Melissa J. Goodwin , Ad Lagendijk , Willem L. Vos

We present a new method for high-resolution nanoscale magnetic resonance imaging (nano-MRI) that combines the high spin sensitivity of nanowire-based magnetic resonance detection with high spectral resolution nuclear magnetic resonance…

Mesoscale and Nanoscale Physics · Physics 2018-03-07 William Rose , Holger Haas , Angela Q. Chen , Nari Jeon , Lincoln J. Lauhon , David G. Cory , Raffi Budakian

Much new solid state technology for single-photon sources, detectors, photovoltaics and quantum computation relies on the fabrication of strained semiconductor nanostructures. Successful development of these devices depends strongly on…

We propose and experimentally demonstrate a nonlinear-optics approach to pattern recognition with single-pixel imaging and deep neural network. It employs mode selective image up-conversion to project a raw image onto a set of coherent…

Optics · Physics 2021-02-03 Ting Bu , Santosh Kumar , He Zhang , Irwin Huang , Yuping Huang

Nuclear Magnetic Resonance (NMR) spectroscopy has served as a powerful analytical tool for studying molecular structure and dynamics in chemistry and biology. However, the processing of raw data acquired from NMR spectrometers and…

Quantitative Methods · Quantitative Biology 2023-09-15 Di Guo , Sijin Li , Jun Liu , Zhangren Tu , Tianyu Qiu , Jingjing Xu , Liubin Feng , Donghai Lin , Qing Hong , Meijin Lin , Yanqin Lin , Xiaobo Qu

Nuclear magnetic resonance (NMR) spectroscopy serves as an indispensable tool in chemistry and biology but often suffers from long experimental time. We present a proof-of-concept of application of deep learning and neural network for…

Medical Physics · Physics 2019-05-15 Xiaobo Qu , Yihui Huang , Hengfa Lu , Tianyu Qiu , Di Guo , Tatiana Agback , Vladislav Orekhov , Zhong Chen

A three-qubit 13C solid-state nuclear magnetic resonance (NMR) system for quantum information processing, based on the malonic acid molecule, is used to demonstrate high-fidelity universal quantum control via strongly-modulating…

Nitrogen vacancy (NV) centers in diamond have been used as ultrasensitive magnetometers to perform nuclear magnetic resonance (NMR) spectroscopy of statistically polarized samples at 1 - 100 nm length scales. However, the spectral linewidth…

Diamond-based quantum sensors have enabled high-resolution NMR spectroscopy at the microscale in scenarios where fast molecular motion averages out dipolar interactions among target nuclei. However, in samples with low-diffusion, ubiquitous…

Quantum Physics · Physics 2025-08-26 Carlos Munuera-Javaloy , Ander Tobalina , Jorge Casanova

The metabolism of an organism is regulated at the cellular level, yet is strongly influenced by its environment. The precise metabolomic study of living organisms is currently hampered by measurement sensitivity: most metabolomic…

Quantitative Methods · Quantitative Biology 2017-07-28 Jan G. Korvink , Vlad Badilita , Lorenzo Bordonali , Mazin Jouda , Dario Mager , Neil MacKinnon

We propose a new simple approach for image compression: instead of storing the RGB values for each pixel of an image, we store the weights of a neural network overfitted to the image. Specifically, to encode an image, we fit it with an MLP…

Image and Video Processing · Electrical Eng. & Systems 2021-04-13 Emilien Dupont , Adam Goliński , Milad Alizadeh , Yee Whye Teh , Arnaud Doucet

Nuclear magnetic resonance (NMR) has enormous applications. Two-dimensional NMR is an essential technique to characterize correlations between nuclei and, hence, molecule structures. Towards the ultimate goal of single-molecule NMR,…

Quantum Physics · Physics 2016-11-30 Wen-Long Ma , Ren-Bao Liu

In relation to recent experimental data [1], we develop a theory framework for demonstrating the feasibility of detecting sharp Nuclear Magnetic Resonance (NMR) oscillations in a real time ESR data. The procedure is to follow real time…

Mesoscale and Nanoscale Physics · Physics 2025-09-04 Baruch Horovitz , Alexander Shnirman

Despite being the main tool to visualize molecules at the atomic scale, AFM with CO-functionalized metal tips is unable to chemically identify the observed molecules. Here we present a strategy to address this challenging task using deep…

Materials Science · Physics 2025-09-03 Jaime Carracedo-Cosme , Carlos Romero-Muñiz , Pablo Pou , Rubén Pérez

Combining multiple fast image acquisitions to mitigate scan noise and drift artifacts has proven essential for picometer precision, quantitative analysis of atomic resolution scanning transmission electron microscopy (STEM) data. For very…

Nuclear magnetic resonance (NMR) spectroscopy is a powerful technique to study local magnetism in a variety of materials. However, the inherently low sensitivity of conventional inductively detected solid state NMR typically requires a…

Mesoscale and Nanoscale Physics · Physics 2025-12-16 Louis Beaudoin , Aimé Verrier , Youcef A. Bioud , Mathieu Massicotte , Bertrand Reulet , Jeffrey A. Quilliam

We report on Fourier spectroscopy experiments performed with near-surface nitrogen-vacancy centers in a diamond chip. By detecting the free precession of nuclear spins rather than applying a multipulse quantum sensing protocol, we are able…

Quantum Physics · Physics 2016-05-18 J. M. Boss , K. Chang , J. Armijo , K. Cujia , T. Rosskopf , J. R. Maze , C. L. Degen

Machine learning methods are becoming increasingly important for the development of materials science. In spite of this, the use of image analysis in the development of these systems is still recent and underexplored, especially in…

Data Analysis, Statistics and Probability · Physics 2022-01-17 Arthur A. B. Pessa , Rafael S. Zola , Matjaz Perc , Haroldo V. Ribeiro
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