Computations in Science Seminars
Apr
1
Wed 12:15
Andrea Bertozzi, UCLA
e-mail:
Host: Leo Kadanoff ()
Organizer: Sayantan Majumdar ()
Particle laden thin films: theory and experiment

Modeling of particle laden flow, especially in the case of higher particle concentrations, does not readily allow for first principles models. Rather, semi-empirical models of the bulk dynamics require careful comparision with experiments. At UCLA we have developed this theory for the geometry of viscous thin film flow with non-neutrally buoyant particles. We have found that for these slower flows, that diffusive flux models, involving a balance between shear-induced migration and hindered settling, can provide reasonably accurate predictive models. I will discuss the current state of this work including recent extensions to bidensity slurries and the relevant mathematics needed to understand the dynamics. Lubrication theory can be derived for this problem and results in a coupled system of conservation laws including regular shock dynamics and singular shocks. I will also briefly discuss relevant applications such as spiral separators.

Apr
8
Wed 12:15
Emmanuel Villermaux, Institut Universitaire de France
e-mail:
Host: William Irvine ()
Organizer: Ivo Peters ()
Explosive Fragmentation

The forced radial expansion of a spherical liquid shell by an exothermic chemical reaction is a prototypical configuration for the explosion of cohesive materials in three dimensions. The shell is formed by the capillary pinch off of a thin liquid annular jet surrounding a jet of reactive gaseous mixture at ambient pressure. The encapsulated gas in the resulting liquid bubble is a mixture of hydrogen and oxygen in controlled relative proportions, which is ignited by a laser plasma aimed at the center of the bubble. The strongly exothermic combustion of the mixture induces the expansion of the hot burnt gas, pushing the shell radially outwards in a violently accelerated motion. That motion triggers the instability of the shell, developing thickness modulations ultimately piercing it in a number of holes. The capillary retraction of the holes concentrates the liquid constitutive of the shell into a web of ligaments, whose breakup leads to stable drops. We offer a comprehensive description of the overall process, from the kinematics of the shell initial expansion, to the final drops size distribution as a function of the composition of the gas mixture, and the initial shell radius and thickness of the bubble. This problem, in which the fragments distribution is the result of a competition between deformation, breakup and cohesion, is relevant to a collection of phenomena spanning over a broad range of length scales, among which are: Exploding blood cells in the human body, spore dispersal from plants, boiling droplets, underwater explosions, magma eruption in volcanoes, up to the torn patterns of supernovae in the Universe.

Apr
15
Wed 12:15
Michael Brenner, Harvard
e-mail:
Host: Leo Kadanoff ()
Organizer: Kim Weirich ()
A potential mechanism for a singular solution of the Euler Equation

I will describe a potential mechanism for a singular solution of the Euler equation. The mechanism involves the interaction of vortex filaments, but occurs sufficiently quickly and at a small enough scales that could have plausibly evaded experimental and computational detection. Joint work with Sahand Hormoz and Alain Pumir.

Apr
22
Wed 12:15
Joseph Vallino, Marine Biological Labortory
e-mail:
Host: Leo Kadanoff ()
Organizer: Kim Weirich ()
Living systems defined in the context of maximum entropy production and information: A computational approach

The maximum entropy production (MEP) principle holds that non equilibrium systems with sufficient degrees of freedom will likely be found in a dynamic state that maximizes entropy production or, analogously, maximizes potential energy destruction rate. The theory does not distinguish between abiotic or biotic systems; however, I will show that systems that can coordinate function over time and/or space can potentially dissipate more free energy than purely Markovian processes (such as fire or a rock rolling down a hill) that only maximize instantaneous entropy production. Biological systems have the ability to store useful information acquired via evolution and culled by natural selection in genomic sequences that allow them to execute temporal strategies and coordinate function over space. For example, circadian rhythms allow phototrophs to “predict” that sun light will return and can orchestrate metabolic machinery appropriately before sunrise, which not only gives them a competitive advantage, but also increases the total entropy production rate compared to systems that lack such anticipatory control. Similarly, coordination over space, such a quorum sensing in microbial biofilms, can increase acquisition of spatially distributed resources and free energy and thereby enhance entropy production. In this talk a computational modeling framework will be presented to describe microbial biogeochemistry based on the MEP conjecture constrained by information and resource availability. Results from model simulations will be compared to laboratory experiments to demonstrate the approach.

Apr
29
Wed 12:15
Michael Rubenstein, Harvard
e-mail:
Host: Leo Kadanoff ()
Organizer: Sayantan Majumdar ()
Taming the Swarm: Control and Design of Multi-Robot Systems.

Advances in technology have begun to allow for the production of large groups, or swarms, of robots; however, there exists a large gap between their current capabilities and those of swarms found in nature or envisioned for future robot swarms. These deficiencies are the result of two factors, difficulties in algorithmic control of these swarms, and limitations in hardware capabilities of the individuals. Creating a hardware system for large robotic swarms is an open challenge; cost and manufacturability pressure hardware designs to be simple with minimal capabilities, while algorithm design favors more capable hardware. The robot design must balance these factors to create a simple robot that is, at the same time, capable of performing the desired behaviors. To investigate these challenges, I created the Kilobot robot swarm, a swarm of 1024 (“kilo”) robots. In this talk, I will discuss the many challenges associated with creating a robot swarm at this scale and the implications this has for creating even larger, more capable swarms in the future.

Controlling these swarms is also a challenge, as the properties desired from these systems, e.g. shape, locomotion, are generally a global property; however, we can only control local interactions between individuals. Furthermore, the mapping between controllable local behaviors and desired global results is not well understood. Their control is further complicated by the very nature of these systems which are composed of decentralized, distributed, asynchronous, error-prone individuals with often limited capabilities. I will discuss two examples of algorithms recently implemented on the Kilobot swarm, self-assembly of user-defined 2D shapes, and the collective transport of objects. Both of these examples provide guarantees of correctness and performance bounds of the swarm, and provide examples of reliable global-to-local control over a robot swarm. I will describe unexpected challenges faced while trying to control the Kilobot swarm, and how these challenges will influence the design of future swarm algorithms.

May
6
Wed 12:15
Tim Sanchez, Harvard
e-mail:
Host: Leo Kadanoff ()
Organizer: Shiladitya Banerjee ()
May
13
Wed 12:15
Luis Bettencourt, Santa Fe Institute
e-mail:
Host: Daniel Holz ()
Organizer: Ivo Peters ()
May
20
Wed 12:15
Andrew Ferguson, University of Illinois at Urbana-Champaign
e-mail:
Host: Leo Kadanoff ()
Machine learning of viral fitness landscapes and protein folding funnels

“Big computing” – petascale systems and the multicore paradigm – has enabled rapid, large-scale biomolecular simulation and property prediction. Similarly, “big biology” – high-throughput sequencing and the “-omics” revolution – has heralded voluminous bioinformatics databases. These large data sets present exciting opportunities to advance scientific understanding, but their size presents new challenges, and demands new paradigms, for their analysis. In the first part of this talk, I will discuss the translation of clinical sequence databases into viral fitness landscapes based on spin glass models from statistical physics. In an application to hepatitis C virus, we identified particular viral vulnerabilities and rationally designed T-cell vaccines to hit the virus where is hurts. In the second part of this talk, I will describe an approach integrating ideas from dynamical systems theory and nonlinear machine learning to infer multidimensional biomolecular folding funnels from univariate experimental measurements.

May
27
Wed 12:15
Matthew Pinson, University of Chicago
e-mail:
Host: Leo Kadanoff ()
Jun
3
Wed 12:15
Alisa Bokulich, Boston University
e-mail:
Host: Leo Kadanoff ()
Jun
8
Mon 12:15
Stephan Herminghaus, Max Planck Institute
e-mail:
Host: Tom Witten
Jun
17
Wed 12:15
OPEN
Jun
24
Wed 12:15
OPEN
Jul
1
Wed 12:15
OPEN
Jul
8
Wed 12:15
OPEN
Jul
15
Wed 12:15
OPEN
Jul
22
Wed 12:15
OPEN
Jul
29
Wed 12:15
Shiladitya Banerjee, University of Chicago
e-mail:
Host: Leo Kadanoff ()
Aug
5
Wed 12:15
OPEN
Aug
12
Wed 12:15
OPEN
Aug
19
Wed 12:15
OPEN
Aug
26
Wed 12:15
OPEN
Oct
7
Wed 12:15
OPEN
Oct
14
Wed 12:15
OPEN
Oct
21
Wed 12:15
Kathleen Stebe, University of Pennsylvania
e-mail:
Host: Leo Kadanoff ()
Oct
28
Wed 12:15
Tom Lubensky, University of Pennsylvania
e-mail:
Host: Leo Kadanoff ()
Nov
4
Wed 12:15
OPEN
Nov
11
Wed 12:15
David Schuster, University of Chicago
e-mail:
Host: Leo Kadanoff ()
Nov
18
Wed 12:15
OPEN
Dec
2
Wed 12:15
OPEN
Dec
9
Wed 12:15
OPEN
Dec
16
Wed 12:15
OPEN