Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Intermolecular Zero-Quantum Coherence imaging in structured samples

Bernard M. Siow, Sun, L, Andrew Matthew Blamire

Published Jan 1, 2008• 0 citations
OpenAlex

Related papers

Understanding Intermolecular Multiple-Quantum Coherences and Their Applications.

W. S. Warren

Non-Monotonic Reasoning•Jan 1, 2001•0 citations

Observation of intermolecular double-quantum coherence signal dips in nuclear magnetic resonance

Shen Shen, Guiping, Cai +4 more

Chinese Physics B•Jan 1, 2011•0 citations

THE VALIDITY OF HIGH TEMPERATURE APPROXIMATION IN NMR SPECTROSCOPY AND ITS RELATED PROBLEMS

Ding Shang

A large body of conspicuous publications in recent years asserts that the high temperature approximation (HTA), a mostly tested and most widely used assumption in NMR spectroscopy and MRI technology, is invalid for concentrated samples in high magnetic fields such as for a proton COSY spectrum of water. A by product of the alleged collapse of HTA, which is equally surprising, is the existence of intermolecular multi quantum coherences (MQC) in low viscosity liquids such as water. In this work, both HTA and intermolecular MQCs in liquids will be critically examined in light of our theoretical analysis and experimental results. Our conclusions are: (1) There are no macroscopic quantum systems in conventional NMR samples such as water at room temperature. (2) At room temperature, high temperature approximation is still one of the most trustworthy approximations applicable to NMR and (3) The MQCs observed in proton COSY spectrum in, e.g., water, have nothing to do with quantum mechanical intermolecular spin interactions.

Bopuxue zazhi•Jan 1, 2002•0 citations

Mechanism of intermolecular dephasings on time-resolved anti-Stokes Raman scattering from a molecular ensemble

Michitoshi Hayashi, Michihiko Sugawara, Yuichi Fujimura

Mechanisms of intermolecular dephasings revealed in the time-resolved coherent anti-Stokes Raman scattering (CARS) spectra of a molecular ensemble are theoretically studied by deriving the microscopical expression for the scattered photon intensity averaged over the heat-bath variables. The intermolecular dephasing means the decay of the intermolecular coherence created by the pumping process, i.e., a linear combination of the vibrational Raman transitions of the molecules at different sites. The intensity of the time-resolved CARS is expressed in terms of time-development matrix elements of the intermolecular coherence. An equation of motion for the intermolecular coherence is derived by using the projection operator method. The structure of the intermolecular-dephasing constant is clarified. The intermolecular-dephasing constant consists of the sum of population decay constants and the intermolecular pure dephasing constant that originates from an elastic interaction between the relevant molecules and a common heat-bath mode. The intermolecular pure dephasing constant is expressed in terms of the intramolecular pure dephasing constants and destructive interference of the intramolecular pure dephasings between the relevant two molecules. The intermolecular-dephasing constant is expressed as the sum of the intramolecular-dephasing constants of the relevant molecules when there is no common heat-bath mode. Inhomogeneous effects on the time-resolved CARS spectra are also investigated. A degree of the structural order is introduced to qualitatively express the inhomogeneity of local structures in the molecular ensemble. The microscopic expression derived in this paper has taken into account both incoherent and coherent optical processes in the thermally distributed molecular ensemble.

Physical Review A•Mar 1, 1991•15 citations

Quantum imaging in biological samples

Christian Schnell

Nature Methods•Feb 27, 2019•10 citations

Quantum-Inspired Trainable and Parameter-Efficient Tensor Networks for Image Inpainting

Shiwen An, Konstantinos Slavakis

This work introduces quantum-inspired tensor-network circuits as trainable transforms for image inpainting. Among the proposed architectures, the diagonal quantum Fourier transform (QFT) relaxation is invertible with $O(N^2 \log N)$ computational cost for $N\times N$ images, inherently preserving minimum coherence throughout training via its circuit structure and eliminating the need for explicit coherence penalties. Unconstrained gradient-based phase optimization (Riemannian-optimization free) enables efficient learning from randomly sampled training data, allowing the learned transform to generalize to test images observed through fixed sampling masks. Numerical tests show that the learned models outperform fixed transforms and per-image optimization while matching the performance of much larger unitary architectures, yet with far fewer parameters.

arXiv:2609.17298•Sep 15, 2026•0 citations
A large body of conspicuous publications in recent years asserts that the high temperature approximation (HTA), a mostly tested and most widely used assumption in NMR spectroscopy and MRI technology, is invalid for concentrated samples in high magnetic fields such as for a proton COSY spectrum of water. A by product of the alleged collapse of HTA, which is equally surprising, is the existence of intermolecular multi quantum coherences (MQC) in low viscosity liquids such as water. In this work, both HTA and intermolecular MQCs in liquids will be critically examined in light of our theoretical analysis and experimental results. Our conclusions are: (1) There are no macroscopic quantum systems in conventional NMR samples such as water at room temperature. (2) At room temperature, high temperature approximation is still one of the most trustworthy approximations applicable to NMR and (3) The MQCs observed in proton COSY spectrum in, e.g., water, have nothing to do with quantum mechanical intermolecular spin interactions.
Mechanisms of intermolecular dephasings revealed in the time-resolved coherent anti-Stokes Raman scattering (CARS) spectra of a molecular ensemble are theoretically studied by deriving the microscopical expression for the scattered photon intensity averaged over the heat-bath variables. The intermolecular dephasing means the decay of the intermolecular coherence created by the pumping process, i.e., a linear combination of the vibrational Raman transitions of the molecules at different sites. The intensity of the time-resolved CARS is expressed in terms of time-development matrix elements of the intermolecular coherence. An equation of motion for the intermolecular coherence is derived by using the projection operator method. The structure of the intermolecular-dephasing constant is clarified. The intermolecular-dephasing constant consists of the sum of population decay constants and the intermolecular pure dephasing constant that originates from an elastic interaction between the relevant molecules and a common heat-bath mode. The intermolecular pure dephasing constant is expressed in terms of the intramolecular pure dephasing constants and destructive interference of the intramolecular pure dephasings between the relevant two molecules. The intermolecular-dephasing constant is expressed as the sum of the intramolecular-dephasing constants of the relevant molecules when there is no common heat-bath mode. Inhomogeneous effects on the time-resolved CARS spectra are also investigated. A degree of the structural order is introduced to qualitatively express the inhomogeneity of local structures in the molecular ensemble. The microscopic expression derived in this paper has taken into account both incoherent and coherent optical processes in the thermally distributed molecular ensemble.
This work introduces quantum-inspired tensor-network circuits as trainable transforms for image inpainting. Among the proposed architectures, the diagonal quantum Fourier transform (QFT) relaxation is invertible with O(N2log⁡N)O(N^2 \log N)O(N2logN) computational cost for N×NN\times NN×N images, inherently preserving minimum coherence throughout training via its circuit structure and eliminating the need for explicit coherence penalties. Unconstrained gradient-based phase optimization (Riemannian-optimization free) enables efficient learning from randomly sampled training data, allowing the learned transform to generalize to test images observed through fixed sampling masks. Numerical tests show that the learned models outperform fixed transforms and per-image optimization while matching the performance of much larger unitary architectures, yet with far fewer parameters.