arXiv subjects

Ting Gong

Publications and source records attributed to Ting Gong.

29 records · Page 2Linked to original sources

arXiv2023

Machine-learning-informed parameter estimation improves the reliability of spinal cord diffusion MRI

Purpose: We address the challenge of inaccurate parameter estimation in diffusion MRI when the signal-to-noise ratio (SNR) is very low, as in the spinal cord. The accuracy of conventional maximum-likelihood estimation (MLE) depends highly on initialisation. Unfavourable choices could result in suboptimal parameter estimates. Current methods to address this issue, such as grid search (GS) can increase computation time substantially. Methods: We propose a machine learning (ML) informed MLE approach that combines conventional MLE with ML approaches synergistically. ML-based methods have been developed recently to improve the speed and precision of parameter estimation. However, they can generate high systematic bias in estimated parameters when SNR is low. In the proposed ML-MLE approach, an artificial neural network model is trained to provide sensible initialisation for MLE efficiently, with the final solution determined by MLE, avoiding biases typically affecting pure ML estimations. Results: Using parameter estimation of neurite orientation dispersion and density imaging as an example, simulation and in vivo experiments suggest that the ML-MLE method can reduce outlier estimates from conventional MLE in white matter voxels affected by CSF contamination. It also accelerates computation compared to GS-MLE. Conclusion: The ML-MLE method can improve the reliability of parameter estimation with reduced computation time compared to GS-MLE, making it a practical tool for diffusion dataset with low SNR.

physics.med-ph↗

arXiv2022

Analyzing the photoassociation spectra of ultracold $^{85}$Rb$^{133}$Cs molecule in $(3)^3Σ^+$ state

We establish a theoretical model to analyze the photoassociative (PA) spectroscopy of $(3)^3Σ^+$ state of $^{85}$Rb$^{133}$Cs molecule. The term energy, spin-spin coupling constants and hyperfine interaction constant of nine vibrational levels in the $(3)^3Σ^+$ state are determined. Based on the fitted term energy and rotation constant, the potential energy curve of $(3)^3Σ^+$ state is obtained by using the RKR method which is compared with the ab initial potential curve.

physics.atom-ph↗

arXiv2021

Optimized multi-axis spiral projection MR fingerprinting with subspace reconstruction for rapid whole-brain high-isotropic-resolution quantitative imaging

Purpose: To improve image quality and accelerate the acquisition of 3D MRF. Methods: Building on the multi-axis spiral-projection MRF technique, a subspace reconstruction with locally low rank (LLR) constraint and a modified spiral-projection spatiotemporal encoding scheme termed tiny-golden-angle-shuffling (TGAS) were implemented for rapid whole-brain high-resolution quantitative mapping. The LLR regularization parameter and the number of subspace bases were tuned using retrospective in-vivo data and simulated examinations, respectively. B0 inhomogeneity correction using multi-frequency interpolation was incorporated into the subspace reconstruction to further improve the image quality by mitigating blurring caused by off-resonance effect. Results: The proposed MRF acquisition and reconstruction framework can produce provide high quality 1-mm isotropic whole-brain quantitative maps in a total acquisition time of 1 minute 55 seconds, with higher-quality results than ones obtained from the previous approach in 6 minutes. The comparison of quantitative results indicates that neither the subspace reconstruction nor the TGAS trajectory induce bias for T1 and T2 mapping. High quality whole-brain MRF data were also obtained at 0.66-mm isotropic resolution in 4 minutes using the proposed technique, where the increased resolution was shown to improve visualization of subtle brain structures. Conclusion: The proposed TGAS-SPI-MRF with optimized spiral-projection trajectory and subspace reconstruction can enable high-resolution quantitative mapping with faster acquisition speed.

physics.med-ph↗

arXiv2021

Finite Permutation Groups with Few Orbits Under the Action on the Power Set

We study the orbits under the natural action of a permutation group $G \subseteq S_n$ on the powerset $\mathscr{P}(\{1, \dots , n\})$. The permutation groups having exactly $n+1$ orbits on the powerset can be characterized as set-transitive groups and were fully classified in \cite{BP55}. In this paper, we establish a general method that allows one to classify the permutation groups with $n+r$ set-orbits for a given $r$, and apply it to integers $2 \leq r \leq 15$ using the computer algebra system GAP.

math.GR↗

arXiv2020

Microwave-assisted coherent control of ultracold polar molecules with a ladder-type rotational states

We have demonstrated microwave-assisted coherent control of ultracold $^{85}$Rb$^{133}$Cs molecules with a ladder-type configuration of rotational states. A probe microwave (MW) field is used to couple a lower state $X^1Σ^+(v=0, J=1)$ and a middle state $X^1Σ^+(v=0, J=2)$, while a control MW field couples the middle state and a upper state $X^1Σ^+(v=0, J=3)$. In the presence of the control field, the population of middle rotational states, $X^1Σ^+(v=0, J=2)$, can be reduced by a control MW field. Broadening of spectral splitting and shift of central frequency in this coherent spectrum are observed to be dependent on Rabi frequency of the control MW field. Applying Akaike's information criterion, we conclude that our observed coherent spectra happen through the crossover range of electromagnetically induced transparency and Aulter-Townes splitting as Rabi frequency of control field increases. Our work is a significant development in microwave-assisted quantum control of ultracold polar molecules with multilevel configuration, and also offers a great potential in quantum information based on ultracold molecules.

physics.atom-ph↗

arXiv2020

Microwave coherent control of ultracold ground-state molecules formed by short-range photoassociation

We report the observation of microwave coherent control of rotational states of ultracold $^{85}$Rb$^{133}$Cs molecules formed in their vibronic ground state by short-range photoassociation. Molecules are formed in the single rotational state $X(v=0,J=1)$ by exciting pairs of atoms to the short-range state $(2)^{3}Π_{0^{-}} (v=11, J=0)$, followed by spontaneous decay. We use depletion spectroscopy to record the dynamic evolution of the population distribution and observe clear Rabi oscillations while irradiating on a microwave transition between coupled neighbouring rotational levels. A density-matrix formalism that accounts for longitudinal and transverse decay times reproduces both the dynamic evolution during the coherent process and the equilibrium population. The coherent control reported here is valuable both for investigating coherent quantum effects and for applications of cold polar molecules produced by continuous short-range photoassociation.

physics.atom-ph↗

arXiv2020

On the odd order composition factors of finite linear groups

In this paper, we study the product of orders of composition factors of odd order in a composition series of a finite linear group. First we generalize a result by Manz and Wolf about the order of solvable linear groups of odd order. Then we use this result to find bounds for the product of orders of composition factors of odd order in a composition series of a finite linear group.

math.GR↗

arXiv2020

Shifted and Squeezed 8-bit Floating Point format for Low-Precision Training of Deep Neural Networks

Training with larger number of parameters while keeping fast iterations is an increasingly adopted strategy and trend for developing better performing Deep Neural Network (DNN) models. This necessitates increased memory footprint and computational requirements for training. Here we introduce a novel methodology for training deep neural networks using 8-bit floating point (FP8) numbers. Reduced bit precision allows for a larger effective memory and increased computational speed. We name this method Shifted and Squeezed FP8 (S2FP8). We show that, unlike previous 8-bit precision training methods, the proposed method works out-of-the-box for representative models: ResNet-50, Transformer and NCF. The method can maintain model accuracy without requiring fine-tuning loss scaling parameters or keeping certain layers in single precision. We introduce two learnable statistics of the DNN tensors - shifted and squeezed factors that are used to optimally adjust the range of the tensors in 8-bits, thus minimizing the loss in information due to quantization.

cs.LG↗

arXiv2019

Label-efficient audio classification through multitask learning and self-supervision

While deep learning has been incredibly successful in modeling tasks with large, carefully curated labeled datasets, its application to problems with limited labeled data remains a challenge. The aim of the present work is to improve the label efficiency of large neural networks operating on audio data through a combination of multitask learning and self-supervised learning on unlabeled data. We trained an end-to-end audio feature extractor based on WaveNet that feeds into simple, yet versatile task-specific neural networks. We describe several easily implemented self-supervised learning tasks that can operate on any large, unlabeled audio corpus. We demonstrate that, in scenarios with limited labeled training data, one can significantly improve the performance of three different supervised classification tasks individually by up to 6% through simultaneous training with these additional self-supervised tasks. We also show that incorporating data augmentation into our multitask setting leads to even further gains in performance.

eess.AS↗

arXiv2019

Robust diffusion parametric mapping of motion-corrupted data with a three-dimensional convolutional neural network

Head motion is inevitable in the acquisition of diffusion-weighted images, especially for certain motion-prone subjects and for data gathering of advanced diffusion models with prolonged scan times. Deficient accuracy of motion correction cause deterioration in the quality of diffusion model reconstruction, thus affecting the derived measures. This results in either loss of data, or introducing bias in outcomes from data of different motion levels, or both. Hence minimizing motion effects and reutilizing motion-contaminated data becomes vital to quantitative studies. We have previously developed a 3-dimensional hierarchical convolution neural network (3D H-CNN) for robust diffusion kurtosis mapping from under-sampled data. In this study, we propose to extend this method to motion-contaminated data for robust recovery of diffusion model-derived measures with a process of motion assessment and corrupted volume rejection. We validate the proposed pipeline in two in-vivo datasets. Results from the first dataset of individual subjects show that all the diffusion tensor and kurtosis tensor-derived measures from the new pipeline are minimally sensitive to motion effects, and are comparable to the motion-free reference with as few as eight volumes retained from the motion-contaminated data. Results from the second dataset of a group of children with attention deficit hyperactivity disorder demonstrate the ability of our approach in ameliorating spurious group differences due to head motion. This method shows great potential for exploiting some valuable but motion-corrupted DWI data which are likely to be discarded otherwise, and applying to data with different motion level thus improving their utilization and statistic power.

physics.med-ph↗

arXiv2018

Dynamical process of optically trapped singlet ground state $^{85}$Rb$^{133}$Cs molecules produced via short-range photoassociation

We investigate the dynamical process of optically trapped X$^{1}$$Σ$$^{+}$ (v" = 0) state $^{85}$Rb$^{133}$Cs molecules distributing in J" = 1 and J" = 3 rotational states. The considered molecules, formed from short-range photoassociation of mixed cold atoms, are subsequently confined in a crossed optical dipole trap. Based on a phenomenological rate equation, we provide a detailed study of the dynamics of $^{85}$Rb$^{133}$Cs molecules during the loading and holding processes. The inelastic collisions of $^{85}$Rb$^{133}$Cs molecules in the X$^{1}$$Σ$$^{+}$ (v" = 0, J" = 1 and J" = 3) states with ultracold $^{85}$Rb (or $^{133}$Cs) atoms are measured to be 1.0 (2)$\times$10$^{-10}$ cm$^{3}$s$^{-1}$ (1.2 (3)$ \times$ 10$^{-10}$ cm$^{3}$s$^{-1}$). Our work provides a simple and generic procedure for studying the dynamical process of trapped cold molecules in the singlet ground states.

physics.atom-ph↗