Self-Annealing Dynamics in a Multistable System

A new type of dynamical behavior of a multistable system is reported. We found that a simple non-equilibrium system can reduce its effective temperature autonomously at a global minimum if the residual frustration at a global minimum is small enough, which highlights an unexpected feature of non-equilibrium multistable systems.Comment: 6 pages, Figures available upon reques

Differences Between Ultrasound and Electrical Stimulation in Wound Healing

When a patient enters a physical therapy clinic for wound therapy, a physical therapist must decide the best way to provide care. The therapy that is decided upon depends on the client, the therapist, and the goals that are trying to be achieved. Through a literature review, I will compare two methods of wound care treatment: therapeutic ultrasound and electrical stimulation. This paper will look at the way these two treatments work and how these treatments are beneficial in wound healing. The benefit of this literature review will be to provide a source of information in choosing an effective or optimal treatment regime for the patient with delayed wound healing. This literature review has found that ultrasound works by stimulating the release of mediators and attracting monocytes to the area, stimulating fibroblasts, epithelial cells, and indirectly, monocytes in accelerating the growth of new tissue. Electrical stimulation is used to accelerate and enhance healing by retarding bacterial growth, increasing local circulation, and enhancing the natural process of tissue repair. Finally, electrical stimulation increases the number of leukocytes, increases collagen synthesis, and accelerates wound epithelializaton

Physics of Type Ia Supernovae

Type Ia supernovae (SNe Ia), the thermonuclear explosion of a white dwarf, were once considered standard candles. However, increased observations reveal inhomogeneities in chemical composition and luminosity behavior, roughly dividing SNe Ia into three luminosity classes; super-luminous, sub-luminous, and normally-luminous. After introducing the problem in the context of previous observations and modeling, this thesis explores the physical processes occurring in a SN Ia after explosion, and discusses observations of SN light curves. A simple model of the expanding ejecta calculates the energy deposition from the decay of radioactive Ni56 as well as photon diffusion. It produces light curves that match early bolometric observations of normal SNe Ia. Variable chemical composition of the ejecta allows for testing a number of explosion scenarios. It becomes apparent that the shape of the light curve is sensitive to the amount and location of synthesized Ni56. Monitoring gamma ray transport through Compton scattering indicates that gamma rays escape at late times. At this epoch an assumption of instantaneous deposition of energy is inaccurate. It is unclear whether positrons escape the ejecta or are trapped at even later times. The photometry of SN2007ax proved it to be the dimmest and reddest SN Ia observed. SN2008D was serendipitously observed in X-rays before it was even visible in optical light, revealing that an early x-ray outburst may accompany every core collapse SN. Subsequent observations resulted in a well-sampled, multi-band early light curve. Observations of SN2006D, another SN Ia, in B,V,R,I up to about 500 days after maximum light are also presented. The light curve may answer questions about the physics of SNe at late times, if more observations can be included. Future modifications of the simple model and strategies for useful observations are discussed

THE POWER OF THERMONUCLEAR SUPERNOVAE AFTER ONE YEAR

Type Ia supernovae (SNe Ia), the thermonuclear explosion of a white dwarf, shape our understanding of the expansion of the universe with the use of their uniformity in distance determinations. Powered by radioactivity synthesized in the explosion, they fade slowly over hundreds of days. Sometime after 200 days, the continually expanding ejecta allows γ-rays from 56 Ni and 56 Co decays to escape, and soon any radioactive power contributing to lighting up the SN comes from positrons formed in 19% of 56 Co decays. While at first it seemed that positrons escaped through the thinning ejecta, it has become apparent that conclusions can only be drawn from accounting for all the power from the near-infrared (NIR) as well as the optical. Only a handfull of SNe have been observed during epochs at a year after explosion in both the optical and NIR. These seem to make an argument for the complete trapping of positrons while also suggesting there is more power unobserved in other bands. This dissertation discusses observations of three nearby SNe; 2006E, 2006ce, and 2006mq, which were all discovered after maximum light, but bright enough to be observed to late times (the latest at ∼525 days after peak). The late multi-wavelength observations are converted to fluxes and luminosity and we assess the behvaior of different wavelength regimes. A simple positron deposition model is employed to estimate the feasibility of positron escape. We find that we cannot rule out positron escape, but that it seems likely that there is a color evolution that shifts power away from observed bands. This shifting of power seems to vary from SN to SN and is not uniform across all normal SNe Ia

Protein Folding and Spin Glass

We explicitly show the connection between the protein folding problem and spin glass transition. This is then used to identify appropriate quantities that are required to describe the transition. A possible way of observing the spin glass transition is proposed.Comment: Revtex3+epsf, 8 pages and one postscript figure tarred, compressed and uuencoded--appended at the end of the file. Minor TeX change

RoseNNa: A performant, portable library for neural network inference with application to computational fluid dynamics

The rise of neural network-based machine learning ushered in high-level libraries, including TensorFlow and PyTorch, to support their functionality. Computational fluid dynamics (CFD) researchers have benefited from this trend and produced powerful neural networks that promise shorter simulation times. For example, multilayer perceptrons (MLPs) and Long Short Term Memory (LSTM) recurrent-based (RNN) architectures can represent sub-grid physical effects, like turbulence. Implementing neural networks in CFD solvers is challenging because the programming languages used for machine learning and CFD are mostly non-overlapping, We present the roseNNa library, which bridges the gap between neural network inference and CFD. RoseNNa is a non-invasive, lightweight (1000 lines), and performant tool for neural network inference, with focus on the smaller networks used to augment PDE solvers, like those of CFD, which are typically written in C/C++ or Fortran. RoseNNa accomplishes this by automatically converting trained models from typical neural network training packages into a high-performance Fortran library with C and Fortran APIs. This reduces the effort needed to access trained neural networks and maintains performance in the PDE solvers that CFD researchers build and rely upon. Results show that RoseNNa reliably outperforms PyTorch (Python) and libtorch (C++) on MLPs and LSTM RNNs with less than 100 hidden layers and 100 neurons per layer, even after removing the overhead cost of API calls. Speedups range from a factor of about 10 and 2 faster than these established libraries for the smaller and larger ends of the neural network size ranges tested.Comment: 10 pages, 4 figure