Exact and Scaling Form of the Bipartite Fidelity of the Infinite XXZ Chain

We find an exact expression for the bipartite fidelity f=|'|^2, where |vac> is the vacuum eigenstate of an infinite-size antiferromagnetic XXZ chain and |vac>' is the vacuum eigenstate of an infinite-size XXZ chain which is split in two. We consider the quantity -ln(f) which has been put forward as a measure of quantum entanglement, and show that the large correlation length xi behaviour is consistent with a general conjecture -ln(f) ~ c/8 ln(xi), where c is the central charge of the UV conformal field theory (with c=1 for the XXZ chain). This behaviour is a natural extension of the existing conformal field theory prediction of -ln(f) ~ c/8 ln(L) for a length L bipartite system with 0<< L <<xi.Comment: 6 page

FreezeOut: Accelerate Training by Progressively Freezing Layers

The early layers of a deep neural net have the fewest parameters, but take up the most computation. In this extended abstract, we propose to only train the hidden layers for a set portion of the training run, freezing them out one-by-one and excluding them from the backward pass. Through experiments on CIFAR, we empirically demonstrate that FreezeOut yields savings of up to 20% wall-clock time during training with 3% loss in accuracy for DenseNets, a 20% speedup without loss of accuracy for ResNets, and no improvement for VGG networks. Our code is publicly available at https://github.com/ajbrock/FreezeOutComment: Extended Abstrac

Generative and Discriminative Voxel Modeling with Convolutional Neural Networks

When working with three-dimensional data, choice of representation is key. We explore voxel-based models, and present evidence for the viability of voxellated representations in applications including shape modeling and object classification. Our key contributions are methods for training voxel-based variational autoencoders, a user interface for exploring the latent space learned by the autoencoder, and a deep convolutional neural network architecture for object classification. We address challenges unique to voxel-based representations, and empirically evaluate our models on the ModelNet benchmark, where we demonstrate a 51.5% relative improvement in the state of the art for object classification.Comment: 9 pages, 5 figures, 2 table

SMASH: One-Shot Model Architecture Search through HyperNetworks

Designing architectures for deep neural networks requires expert knowledge and substantial computation time. We propose a technique to accelerate architecture selection by learning an auxiliary HyperNet that generates the weights of a main model conditioned on that model's architecture. By comparing the relative validation performance of networks with HyperNet-generated weights, we can effectively search over a wide range of architectures at the cost of a single training run. To facilitate this search, we develop a flexible mechanism based on memory read-writes that allows us to define a wide range of network connectivity patterns, with ResNet, DenseNet, and FractalNet blocks as special cases. We validate our method (SMASH) on CIFAR-10 and CIFAR-100, STL-10, ModelNet10, and Imagenet32x32, achieving competitive performance with similarly-sized hand-designed networks. Our code is available at https://github.com/ajbrock/SMAS

An on-board near-optimal climb-dash energy management

On-board real time flight control is studied in order to develop algorithms which are simple enough to be used in practice, for a variety of missions involving three dimensional flight. The intercept mission in symmetric flight is emphasized. Extensive computation is required on the ground prior to the mission but the ensuing on-board exploitation is extremely simple. The scheme takes advantage of the boundary layer structure common in singular perturbations, arising with the multiple time scales appropriate to aircraft dynamics. Energy modelling of aircraft is used as the starting point for the analysis. In the symmetric case, a nominal path is generated which fairs into the dash or cruise state. Feedback coefficients are found as functions of the remaining energy to go (dash energy less current energy) along the nominal path

When do young birds disperse? : Tests from studies of golden eagles in Scotland

Peer reviewedPublisher PD

Impurity Operators in RSOS Models

We give a construction of impurity operators in the `algebraic analysis' picture of RSOS models. Physically, these operators are half-infinite insertions of certain fusion-RSOS Boltzmann weights. They are the face analogue of insertions of higher spin lines in vertex models. Mathematically, they are given in terms of intertwiners of $U(\hat{sl}_2)_q$ modules. We present a detailed perturbation theory check of the conjectural correspondence between the physical and mathematical constructions in a particular simple example.Comment: Latex, 24 pages, uses amsmath, amsthm, amssymb, epic, eepic and texdraw style files (Minor typos corrected) (minor changes

Innovative Approaches to Emergency Medical Services Fellowship Challenges

Introduction: Since the development of an Accreditation Council of Graduate Medical Education (ACGME)-accredited emergency medical services (EMS) fellowship, there has been little published literature on effective methods of content delivery or training modalities. Here we explore a variety of innovative approaches to the development and revision of the EMS fellowship curriculum.Methods: Three academic, university-based ACGME-accredited EMS fellowship programs each implemented an innovative change to their existing training curricula. These changes included the following: a novel didactic curriculum delivery modality and evaluation; implementation of a distance education program to improve EMS fellows’ rural EMS experiences; and modification of an existing EMS fellowship curriculum to train a non-emergency medicine physician.Results: Changes made to each of the above EMS fellowship programs addressed unique challenges, demonstrating areas of success and promise for more generalized implementation of these curricula. Obstacles remain in tailoring the described curricula to the needs of each unique institution and system.Conclusion: Three separate curricula and program changes were implemented to overcome specific challenges and achieve educational goals. It is our hope that our shared experiences will enable others in addressing common barriers to teaching the EMS fellowship core content and share similar innovative approaches to educational challenges

Climb-dash real-time calculations

On-board rear-optimal climb-dash energy management, optimal symmetric flight with an intermediate vehicle model, and energy states are presented