ENABLING TECHNIQUES FOR EXPRESSIVE FLOW FIELD VISUALIZATION AND EXPLORATION

Flow visualization plays an important role in many scientific and engineering disciplines such as climate modeling, turbulent combustion, and automobile design. The most common method for flow visualization is to display integral flow lines such as streamlines computed from particle tracing. Effective streamline visualization should capture flow patterns and display them with appropriate density, so that critical flow information can be visually acquired. In this dissertation, we present several approaches that facilitate expressive flow field visualization and exploration. First, we design a unified information-theoretic framework to model streamline selection and viewpoint selection as symmetric problems. Two interrelated information channels are constructed between a pool of candidate streamlines and a set of sample viewpoints. Based on these information channels, we define streamline information and viewpoint information to select best streamlines and viewpoints, respectively. Second, we present a focus+context framework to magnify small features and reduce occlusion around them while compacting the context region in a full view. This framework parititions the volume into blocks and deforms them to guide streamline repositioning. The desired deformation is formulated into energy terms and achieved by minimizing the energy function. Third, measuring the similarity of integral curves is fundamental to many tasks such as feature detection, pattern querying, streamline clustering and hierarchical exploration. We introduce FlowString that extracts shape invariant features from streamlines to form an alphabet of characters, and encodes each streamline into a string. The similarity of two streamline segments then becomes a specially designed edit distance between two strings. Leveraging the suffix tree, FlowString provides a string-based method for exploratory streamline analysis and visualization. A universal alphabet is learned from multiple data sets to capture basic flow patterns that exist in a variety of flow fields. This allows easy comparison and efficient query across data sets. Fourth, for exploration of vascular data sets, which contain a series of vector fields together with multiple scalar fields, we design a web-based approach for users to investigate the relationship among different properties guided by histograms. The vessel structure is mapped from the 3D volume space to a 2D graph, which allow more efficient interaction and effective visualization on websites. A segmentation scheme is proposed to divide the vessel structure based on a user specified property to further explore the distribution of that property over space

Computational Light Transport for Forward and Inverse Problems.

El transporte de luz computacional comprende todas las técnicas usadas para calcular el flujo de luz en una escena virtual. Su uso es ubicuo en distintas aplicaciones, desde entretenimiento y publicidad, hasta diseño de producto, ingeniería y arquitectura, incluyendo el generar datos validados para técnicas basadas en imagen por ordenador. Sin embargo, simular el transporte de luz de manera precisa es un proceso costoso. Como consecuencia, hay que establecer un balance entre la fidelidad de la simulación física y su coste computacional. Por ejemplo, es común asumir óptica geométrica o una velocidad de propagación de la luz infinita, o simplificar los modelos de reflectancia ignorando ciertos fenómenos. En esta tesis introducimos varias contribuciones a la simulación del transporte de luz, dirigidas tanto a mejorar la eficiencia del cálculo de la misma, como a expandir el rango de sus aplicaciones prácticas. Prestamos especial atención a remover la asunción de una velocidad de propagación infinita, generalizando el transporte de luz a su estado transitorio. Respecto a la mejora de eficiencia, presentamos un método para calcular el flujo de luz que incide directamente desde luminarias en un sistema de generación de imágenes por Monte Carlo, reduciendo significativamente la variancia de las imágenes resultantes usando el mismo tiempo de ejecución. Asimismo, introducimos una técnica basada en estimación de densidad en el estado transitorio, que permite reusar mejor las muestras temporales en un medio parcipativo. En el dominio de las aplicaciones, también introducimos dos nuevos usos del transporte de luz: Un modelo para simular un tipo especial de pigmentos gonicromáticos que exhiben apariencia perlescente, con el objetivo de proveer una forma de edición intuitiva para manufactura, y una técnica de imagen sin línea de visión directa usando información del tiempo de vuelo de la luz, construida sobre un modelo de propagación de la luz basado en ondas.<br /

ANALYSIS AND VISUALIZATION OF FLOW FIELDS USING INFORMATION-THEORETIC TECHNIQUES AND GRAPH-BASED REPRESENTATIONS

Three-dimensional flow visualization plays an essential role in many areas of science and engineering, such as aero- and hydro-dynamical systems which dominate various physical and natural phenomena. For popular methods such as the streamline visualization to be effective, they should capture the underlying flow features while facilitating user observation and understanding of the flow field in a clear manner. My research mainly focuses on the analysis and visualization of flow fields using various techniques, e.g. information-theoretic techniques and graph-based representations. Since the streamline visualization is a popular technique in flow field visualization, how to select good streamlines to capture flow patterns and how to pick good viewpoints to observe flow fields become critical. We treat streamline selection and viewpoint selection as symmetric problems and solve them simultaneously using the dual information channel [81]. To the best of my knowledge, this is the first attempt in flow visualization to combine these two selection problems in a unified approach. This work selects streamline in a view-independent manner and the selected streamlines will not change for all viewpoints. My another work [56] uses an information-theoretic approach to evaluate the importance of each streamline under various sample viewpoints and presents a solution for view-dependent streamline selection that guarantees coherent streamline update when the view changes gradually. When projecting 3D streamlines to 2D images for viewing, occlusion and clutter become inevitable. To address this challenge, we design FlowGraph [57, 58], a novel compound graph representation that organizes field line clusters and spatiotemporal regions hierarchically for occlusion-free and controllable visual exploration. We enable observation and exploration of the relationships among field line clusters, spatiotemporal regions and their interconnection in the transformed space. Most viewpoint selection methods only consider the external viewpoints outside of the flow field. This will not convey a clear observation when the flow field is clutter on the boundary side. Therefore, we propose a new way to explore flow fields by selecting several internal viewpoints around the flow features inside of the flow field and then generating a B-Spline curve path traversing these viewpoints to provide users with closeup views of the flow field for detailed observation of hidden or occluded internal flow features [54]. This work is also extended to deal with unsteady flow fields. Besides flow field visualization, some other topics relevant to visualization also attract my attention. In iGraph [31], we leverage a distributed system along with a tiled display wall to provide users with high-resolution visual analytics of big image and text collections in real time. Developing pedagogical visualization tools forms my other research focus. Since most cryptography algorithms use sophisticated mathematics, it is difficult for beginners to understand both what the algorithm does and how the algorithm does that. Therefore, we develop a set of visualization tools to provide users with an intuitive way to learn and understand these algorithms

Deep Learning Gauss–Manin Connections

The Gauss–Manin connection of a family of hypersurfaces governs the change of the period matrix along the family. This connection can be complicated even when the equations defining the family look simple. When this is the case, it is expensive to compute the period matrices of varieties in the family via homotopy continuation. We train neural networks that can quickly and reliably guess the complexity of the Gauss–Manin connection of pencils of hypersurfaces. As an application, we compute the periods of 96 % of smooth quartic surfaces in projective 3-space whose defining equation is a sum of five monomials; from the periods of these quartic surfaces, we extract their Picard lattices and the endomorphism fields of their transcendental lattices. © 2022, The Author(s)

2016 GREAT Day Program

SUNY Geneseo’s Tenth Annual GREAT Day.https://knightscholar.geneseo.edu/program-2007/1010/thumbnail.jp

Perspectives On String Phenomenology

The remarkable recent discovery of the Higgs boson at the CERN Large Hadron Collider completed the Standard Model of particle physics and has paved the way for understanding the physics which may lie beyond it. String/M theory has emerged as a broad framework for describing a plethora of diverse physical systems, which includes condensed matter systems, gravitational systems as well as elementary particle physics interactions. If string/M theory is to be considered as a candidate theory of Nature, it must contain an effectively four-dimensional universe among its solutions that is indistinguishable from our own. In these solutions, the extra dimensions of string/M theory are “compactified” on tiny scales which are often comparable to the Planck length. String phenomenology is the branch of string/M theory that studies such solutions, relates their properties to data, and aims to answer many of the outstanding questions of particle physics beyond the Standard Model.This book contains perspectives on string phenomenology from some of the leading experts in the field. Contributions will range from pedagogical general overviews and perspectives to more technical reviews. We hope that the reader will get a sense of the significant progress that has been made in the field in recent years (e.g. in the topic of moduli stabilization) as well as the topics currently being researched, outstanding problems and some perspectives for the future

Perspectives On String Phenomenology

The remarkable recent discovery of the Higgs boson at the CERN Large Hadron Collider completed the Standard Model of particle physics and has paved the way for understanding the physics which may lie beyond it. String/M theory has emerged as a broad framework for describing a plethora of diverse physical systems, which includes condensed matter systems, gravitational systems as well as elementary particle physics interactions. If string/M theory is to be considered as a candidate theory of Nature, it must contain an effectively four-dimensional universe among its solutions that is indistinguishable from our own. In these solutions, the extra dimensions of string/M theory are “compactified” on tiny scales which are often comparable to the Planck length. String phenomenology is the branch of string/M theory that studies such solutions, relates their properties to data, and aims to answer many of the outstanding questions of particle physics beyond the Standard Model.This book contains perspectives on string phenomenology from some of the leading experts in the field. Contributions will range from pedagogical general overviews and perspectives to more technical reviews. We hope that the reader will get a sense of the significant progress that has been made in the field in recent years (e.g. in the topic of moduli stabilization) as well as the topics currently being researched, outstanding problems and some perspectives for the future