Generalized fruit Diophantine equation and super elliptic curves
In this article, we are interested in finding rational points on certain superelliptic curves.
math.NT↗
arXiv subjects
Ankita Das
Publications and source records attributed to Ankita Das.
Frequency-dependent specific heat in quantum supercooled liquids: A mode-coupling study
Frequency-dependence of specific heat in supercooled hard sphere liquid is computed using quantum mode-coupling theory (QMCT). Mode-coupling equations are solved using recently proposed perturbative method that allows to study relaxation in the moderate quantum regime where quantum effects assist liquid to glass transition. Zwanzig's formulation is used to compute the frequency-dependent specific heat in supercooled state using dynamical information from QMCT. Specific heat shows strong variation as the quantumness of the liquid is changed, which becomes more significant as density is increased. It is found that, near the transition point, different dynamical modes contribute to the specific heat in the classical and the quantum liquids.
cond-mat.stat-mech↗
Tagged particle dynamics in supercooled quantum liquid
We analyze dynamics of quantum supercooled liquids in terms of tagged particle dynamics. Unlike the classical case, uncertainty in the position of a particle in quantum liquid leads to qualitative changes. We demonstrate these effects in the dynamics of the first two moments of displacements, namely, the mean-squared displacement, $\langle Δr^2(t)\rangle$, and $\langle Δr^4(t)\rangle$. Results are presented for a hard sphere liquid using mode-coupling theory (MCT) formulation and simulation on a binary Lennard-Jones liquid. As the quantumness (controlled by the de-Broglie thermal wavelength) is increased, a non-zero value of the moments at zero time leads to significant deviations from the classical behavior in the initial dynamics. Initial displacement shows ballistic behavior $\langle Δr^2(t)\rangle\sim t^2$, but, as a result of large uncertainty in the position, the dynamical effects become weaker with increasing quantumness over this time scale.
cond-mat.stat-mech↗
Performance Characterization of Containerized DNN Training and Inference on Edge Accelerators
Edge devices have typically been used for DNN inferencing. The increase in the compute power of accelerated edges is leading to their use in DNN training also. As privacy becomes a concern on multi-tenant edge devices, Docker containers provide a lightweight virtualization mechanism to sandbox models. But their overheads for edge devices are not yet explored. In this work, we study the impact of containerized DNN inference and training workloads on an NVIDIA AGX Orin edge device and contrast it against bare metal execution on running time, CPU, GPU and memory utilization, and energy consumption. Our analysis shows that there are negligible containerization overheads for individually running DNN training and inference workloads.
cs.DC↗
SONIC: Synergizing VisiON Foundation Models for Stress RecogNItion from ECG signals
Stress recognition through physiological signals such as Electrocardiogram (ECG) signals has garnered significant attention. Traditionally, research in this field predominantly focused on utilizing handcrafted features or raw signals as inputs for learning algorithms. However, there is now a burgeoning interest within the community in leveraging large-scale vision foundation models (VFMs) like ResNet50, VGG19, and others. These VFMs are increasingly preferred due to their ability to capture complex features, enhancing the accuracy and effectiveness of stress recognition systems. However, no particular focus has been given on combining these VFMs. The combination of VFMs offers promising benefits by harnessing their collective knowledge to extract richer representations for improved stress recognition. So, to mitigate this research gap, we focus on combining different VFMs for stress recognition from ECG and propose SONIC, a novel framework that combines VFMs through their logits and training a fully connected network on the combined logits. Through extensive experimentation, SONIC showed the top performance against individual VFMs performance on the WESAD benchmark. With SONIC, we report state-of-the-art (SOTA) performance in WESAD with 99.36% and 99.24% (stress vs non-stress) and 97.66% and 97.10% (amusement vs stress vs baseline) in accuracy and F1 respectively.
eess.SP↗
Hesitancy, Awareness and Vaccination: A Computational Analysis on Complex Networks
Considering the global pandemic of coronavirus disease 2019 (COVID-19), around the world several vaccines are being developed. Till now, these vaccines are the most effective way to reduce the high burden on the global health infrastructure. However, the public acceptance towards vaccination is a crucial and pressing problem for health authorities. This study has been designed to determine the parameters affecting the decisions of common individuals towards COVID-19 vaccine. In our study, using the platforms of compartmental model and network simulation, we categorize people and observe their motivation towards vaccination in a mathematical social contagion process. In our model, we consider peer influence as an important factor in this dynamics, and study how individuals are influencing each other for vaccination. The efficiency of the vaccination process is estimated by the period of time required to vaccinate a substantial fraction of total population. We discovered the major barriers and drivers of this dynamics, and concluded that it is required to formulate specific strategies by the healthcare workers which could be more effective for the undecided and vaccine hesitant group of people.
physics.soc-ph↗
Structural relaxation in quantum supercooled liquids: A mode-coupling approach
We study supercooled dynamics in quantum hard-sphere liquid using quantum mode-coupling formulation. In the moderate quantum regime, classical cage effects lead to slower dynamics compared to strongly quantum regime, where tunneling overcomes classical caging, leading to faster relaxation. As a result, the glass transition critical density can become significantly higher than for the classical liquids. Perturbative approach is used to solve time dependent quantum mode-coupling equations to study in detail the dynamics of the supercooled liquid in moderate quantum regime. Similar to the classical case, relaxation time shows power-law increase with increasing density in the supercooled regime. However, the power-law exponent is found to be dependent on the quantumness; it increases linearly as the quantumness is increased in the moderate quantum regime.
cond-mat.stat-mech↗