This award under the Information Technology Research initiative explores and strengthens connections between computer science and the physics of complex systems, addressing the important examples of membranes and disordered materials from condensed matter physics. The proposed research brings these disciplines closer together by recognizing that not only are novel algorithmic tools crucial for modeling complex physical systems, but that there are fundamental links between the physical properties of the system and the computational complexity of the simulation. This project will also train students and researchers in this area at the interface between condensed matter theory and information technology and provide simulation software components for the research community.
Many of the challenges in sciences such as physics and biology are problems in understanding the behavior of a very large number of strongly interacting degrees of freedom, where the macroscopic behavior is determined by the competition between local ordering and disordering effects, including temperature, heterogeneities, and geometry. Examples abound in the both the classical and quantum world, including vortex lines in superconductors, strongly correlated electrons in disordered solids, and fluctuating membranes, as seen in cells and artificial colloidal structures. Describing the phases and transitions in these systems relies upon being able to build up the large-scale behavior from microscopic models. This is quite challenging for conventional simulations. The intent here is to draw on ideas from computer science to develop new algorithms and to identify universal features using extensive simulations. In turn these features will be used to develop new simulation methods and analytical understanding. This project will focus on specific areas in condensed matter physics that are of direct experimental relevance and raise general algorithmic questions:
The PIs will study the phase diagram of realistic models of physical membranes, with important applications to biological membranes. The PIs will explore the defect structure of crystals on topographies of fixed curvature, such as a crystal on the surface of a sphere, and more complex geometries. This work has direct relevance to the rich physics of colloidosomes, spherical viruses and other systems currently studied in many laboratories. This work will rely on combining knowledge about small-scale defects and long wavelength elasticity and exploring optimization algorithms. The PIs will investigate the phases of a class of disordered classical (e.g., vortex lines in superconductors) and quantum (interacting electrons in disordered solids) disordered systems that can be studied simultaneously by the same numerical algorithm. The PIs will explore the connection between polynomial time optimization algorithm and physical theories of disordered materials. This includes the development of new approaches to explain the timing of algorithms by adapting physical concepts of phases and correlation lengths to their nonphysical dynamics.
The achievement of the scientific goals for specific physical systems and algorithmic studies will be closely linked with more general benefits: The training of undergraduate and graduate students and postdoctoral researchers who will have the expertise and inclination to work at the bridge between statistical physics and computer science. Building a common expertise and suggesting potential collaborations in the computer science and physics communities. Software development, in three parts (problem generators, solvers, and data analyzers), that can be adopted by researchers to solve related problems and for testing alternate computational approaches. %%% This award under the Information Technology Research initiative explores and strengthens connections between computer science and the physics of complex systems. The research enhances and builds connections between these disciplines by recognizing that not only are novel algorithmic tools crucial for modeling complex physical systems, but that there are fundamental links between the physical properties of the system and the computational complexity of the simulation. This project will also train students and researchers in this area at the interface between condensed matter theory and information technology and provide simulation software components for the research community.
Many of the challenges in sciences such as physics and biology are problems in understanding the behavior of a very large number of strongly interacting degrees of freedom, where the macroscopic behavior is determined by the competition between local ordering and disordering effects, including temperature, heterogeneities, and geometry. Examples abound in the both the classical and quantum world, including vortex lines in superconductors, strongly correlated electrons in disordered solids, and fluctuating membranes, as seen in cells and artificial colloidal structures. Describing the phases and transitions in these systems relies upon being able to build up the large-scale behavior from microscopic models. This is quite challenging for conventional simulations. The intent here is to draw on ideas from computer science to develop new algorithms and to identify universal features using extensive simulations. In turn these features will be used to develop new simulation methods and analytical understanding. This project will focus on specific areas in condensed matter physics that are of direct experimental relevance and raise general algorithmic questions:
The PIs will study the phase diagram of realistic models of physical membranes, with important applications to biological membranes. The PIs will explore the defect structure of crystals on topographies of fixed curvature, such as a crystal on the surface of a sphere, and more complex geometries. This work has direct relevance to the rich physics of colloidosomes, spherical viruses and other systems currently studied in many laboratories. This work will rely on combining knowledge about small-scale defects and long wavelength elasticity and exploring optimization algorithms. The PIs will investigate the phases of a class of disordered classical (e.g., vortex lines in superconductors) and quantum (interacting electrons in disordered solids) disordered systems that can be studied simultaneously by the same numerical algorithm. The PIs will explore the connection between polynomial time optimization algorithm and physical theories of disordered materials. This includes the development of new approaches to explain the timing of algorithms by adapting physical concepts of phases and correlation lengths to their nonphysical dynamics.
The achievement of the scientific goals for specific physical systems and algorithmic studies will be closely linked with more general benefits: The training of undergraduate and graduate students and postdoctoral researchers who will have the expertise and inclination to work at the bridge between statistical physics and computer science. Building a common expertise and suggesting potential collaborations in the computer science and physics communities. Software development, in three parts (problem generators, solvers, and data analyzers), that can be adopted by researchers to solve related problems and for testing alternate computational approaches. ***
