Chaos and Complex Systems Seminar
Fall 2017 Seminars
All seminars are Tuesday at 12:05 pm in 4274
Hall except as noted. Refreshments will be served.
- Sep 12, 2017 - Aws Albarghouthi, Computer Science
- Sep 19, 2017 - Matt Allen, Engineering Physics
- Sep 26 2017 - Ed Churchwell, Astronomy
- Oct 3, 2017 - Bas Rokers, Psychology
- Oct 10, 2017 - Bernard Z. Friedlander, Psychology
- Oct 17, 2017 - Anda Xiong, Physics
- Oct 24 2017 - Bill Whitford, Law
- Oct 31, 2017 - David Canon, Political Science
- Nov 7, 2017 - Blaise Thompson, Chemistry
- Nov 14, 2017 - Becca Willett, Electrical and Computer
- Nov 21, 2017 - Terry Allard, Office of Naval Research and NASA
- Nov 28, 2017 - Brad Postle, Psychology
- Dec 5, 2017 - Kimberly Palladino, Physics
- Dec 12, 2017 - Tim Allen, Botany
September 12, 2017
The Fairsquare project: Countering programs that discriminate
Aws Albarghouthi, UW Department of Computer Science
Software has become a powerful arbitrator of a range of significant
decisions with far-reaching societal impact---hiring, welfare
allocation, prison sentencing, policing and, among many others. With
the range and sensitivity of algorithmic decisions expanding by the
day, the problem of understanding the nature of program
discrimination and fairness is a pressing one. In this talk, I will
describe our work on the FairSquare project, in which we are
developing program verification and synthesis tools aimed at
rigorously characterizing and reasoning about fairness of
September 19, 2017
Nonlinear normal modes for analysis of geometrically nonlinear
Matthew Allen, UW Department of Engineering Physics
Geometric nonlinearity is an important consideration when designing
many structures, for example the skin panels for future hypersonic
cruise vehicles where intense pressures and aerodynamic heating can
cause the panels to vibrate in and out of buckled states. Highly
flexible joined-wing aircraft, which are being sought for station
keeping at high altitude, can also exhibit nonlinear dynamic
phenomena. It may also be possible to add a nonlinear element
to an otherwise linear structure in order to reduce vibration levels
and increase its life, leading to quieter automobiles or more
durable spacecraft. All of these applications are challenging
because numerical response predictions are expensive and these
nonlinear systems exhibit a large range of phenomena, each of which
may require a specialized analysis technique. This work shows
that tremendous insight can be gained into the dynamics of these
types of nonlinear structures using undamped nonlinear modal
This presentation highlights advances in modeling for geometrically
nonlinear structures and discusses how nonlinear modes can be used
in analysis, design and testing. While academics have used
simplified Galerkin/Ritz models for years to qualitatively study the
geometrically nonlinear response of plates and beams, those methods
often do not scale to industrial practice where the geometry is far
more complicated and many degrees of freedom must be
considered. The work focuses on structures that are modeled in
commercial finite element software and uses a non-intrusive approach
in which a series of static loads are applied to the structure and a
nonlinear Reduced Order Model (ROM) is fit to the load-displacement
behavior. Nonlinear modes prove to be effective in discerning
whether the reduced basis contains the fidelity needed to capture
the dynamics of interest and in assuring that the loads are large
enough to allow the ROM to be accurately computed. Nonlinear
modes are also found to be intimately connected to the response of
the structure to random loading, such as the pressure fields
experienced by many aircraft. These concepts are demonstrated
by applying them to a variety of finite element models, showing that
the nonlinear modes provide tremendous insight into the dynamics of
September 26, 2017
Intelligent extraterrestrial life: Does it exist?
and, if so, what are the prospects for
discovery and communication?
Ed Churchwell, UW Department of Astronomy
I will explain what I mean by intelligent life, review
the high points about what is known about the evolution of
"intelligent" life on Earth and apply some of what are thought to
be global principles that are likely to govern the origin and
evolution of life in the universe. In particular, I will spend
some time on limitations to our prospects for discovery and
communication. This is a very broad subject, and I certainly
will not have time to cover all the issues associated with this
subject, nor am I qualified to speak about many of them.
October 3, 2017
of 3D motion explained by Bayesian inference
Bas Rokers, UW Department of Psychology
Over the years, a number of surprising, but seemingly unrelated errors in 3D motion perception have been reported.
Given the relevance of accurate motion perception to our everyday life,
it is important to understand the cause of these perceptual errors.
We considered that these perceptual
errors might arise as a natural consequence of estimating motion direction
given sensory noise and the geometry of 3D viewing.
characterized the retinal motion signals produced by objects moving
along arbitrary trajectories through three dimensions and developed a
Bayesian model of perceptual
inference. The model predicted a number of known errors, including a
lateral bias in the perception of motion trajectories, and a dependency
of this bias on stimulus contrast and viewing distance. The model also
predicted a number of previously unknown errors,
including a dependency of perceptual bias on eccentricity, and a
surprising tendency to misreport approaching motion as receding and vice
We then used standard 3D displays as well as a virtual reality (VR) headsets to test these predictions in
naturalistic settings, and established
that people make the predicted errors.
a quantitative model of 3D motion perception and provided a
parsimonious account for a range of systematic perceptual errors in
October 10, 2017
Understanding complexities of human development in terms of space,
time, and energy realities
Part 1: Growing up and growing old
Bernard Z. Friedlander, Department of Psychology, University of
These presentations ask three questions:
The two-presentation series touches upon basic concepts in these
four areas of serious study: human development, basic physical
science, industrial manufacturing technology, and the fine arts.
- Are there fundamental principles in physical science that can
be useful in helping us comprehend fundamental concepts in the
organization of human behavior?
- Can these principles help us answer the constant question–How
do people get the way we are?
- Does this approach, in the light of current laboratory
research findings, help us clarify persistent scientific and
philosophical issues in Western thought?
See expanded written pdf version.
Part 2: Individual differences, volition, and "consciousness" will
be given in spring 2018.
October 17, 2017
Chaos theory from a topological perspective
Anda Xiong, UW Department of Physics
I will talk about some phenomena in chaos theory and how can they be
viewed by topology, such as the connection between fractals and
topological subdivision, and calculating the self-linking number of
attractors. Furtherly I will give an example for how persistence
homology can be helpful to research in chaos theory.
October 24, 2017
How an important Supreme Court case was created
Bill Whitford, UW Law School
Whitford is the lead plaintiff in Gill v. Whitford, which will be
heard by the U.S. Supreme Court on Oct. 3, 2017 The case
raises the question whether the federal courts should interpret the
U.S. Constitution to place some limits on the extent of partisan
bias in legislative districting. If Whitford and the
other plaintiffs win, as they did in the trial court, it will be the
first time the federal courts have placed any limits of the extent
of partisan bias, and hence create a new precedent. Whitford
will explain the context in which case arose and how he and others
were able to obtain the services of a team of lawyers and experts
that have gotten the case to its present position.
See a detailed outline of talk.
October 31, 2017
Partisan redistricting in Wisconsin
David Canon, UW Department of Political Science
Professor David Canon will discuss the potential landmark Supreme
Court case, Gill v. Whitford, concerning partisan
redistricting. Canon will provide some background on the law
and the basic principles of redistricting, explore the history of
partisan redistricting and then discuss the Wisconsin case. He will
speculate about the likely outcome, with a focus on the role of
Justice Kennedy and the new measure of partisan bias (the
“efficiency gap”). Canon will conclude by talking about possible
reforms, with a focus on Iowa’s nonpartisan model of redistricting.
November 7, 2017
Multidimensional spectroscopy of complex chemical systems: Using
nonlinearity to isolate signals
Blaise Thompson, UW Department of Chemistry
systems are typically composed of many individual components. Each
component may be unique. Furthermore, each component may experience a
different chemical environment. At room temperature, these environments
evolve on ultrafast time scales. Scientists need specialized techniques
to understand what is happening in these complex, coupled systems.
uses the interaction of light and matter to measure chemical energies.
Multidimensional spectroscopy (MDS) capitalizes on nonlinearities in
this interaction to peer into higher-order properties of the chemical
system. These higher-order signals reveal coupling parameters of the
system. In this way, scientists can use MDS to isolate unique properties
of chemical systems that cannot be measured through other means.
Ultrafast dynamics can also be tracked.
presentation will introduce the basic concepts of MDS. An intuitive
description of the technique will be presented. Practical advantages
will be highlighted.
November 14, 2017
Low algebraic dimension matrix completion
Becca Willett, UW Department of Electrical and Computer Engineering
past decade of research on matrix completion has shown it is possible
to leverage linear dependencies to impute missing values in a low-rank matrix. However, the corresponding assumption that the data lies in or near a low-dimensional linear subspace is not always met in practice. Extending matrix completion theory and algorithms to exploit low-dimensional
nonlinear structure in data will allow missing data imputation in a far
richer class of problems. In this talk, I will describe how models of low-dimensional
nonlinear structure can be used for matrix completion. In particular,
we will explore matrix completion in the context of unions of subspaces,
in which data points lie in or near one of several subspaces, and
nonlinear algebraic varieties, a polynomial generalization of classical linear subspaces. Low Algebraic-Dimension
Matrix Completion (LADMC) is a novel and efficient method for imputing
missing values and admits new bounds on the amount of missing data that
can be accurately imputed. The proposed algorithms are able to recover
synthetically generated data up to predicted sample complexity bounds
and outperform standard low-rank matrix completion in experiments with real recommender system and motion capture data
November 21, 2017
Artificial intelligence: Evolution and agency
Terry Allard, Office of Naval Research and NASA (retired)
One fear often expressed in the mass media and popular culture is
that artificially intelligent machines will become fully autonomous
and self-improving to the point that their capabilities will exceed
that of human beings. As a consequence, intelligent machines could
become a more dominant life form on the planet, superseding human
primacy in culture, science, technology, competitiveness and value.
A key concept underlying this fear is the notion that machines can
have their own agency independent of human control or influence.
Today’s discussion will explore the nature of agency and the future
of artificial intelligence from narrow single-function capability to
super-intelligence exceeding current human potential.
Listen to an audio version of this talk.
See the slides in PDF format for this talk.
November 28, 2017
Activation versus information in visual working memory
Brad Postle, UW Department of Psychology
Working memory refers to the ability to hold a small amount of
information in mind, to manipulate it, and to use it to guide behavior.
Individual differences in working memory capacity predict a wide range
of psychometric and real-world outcomes, from general
fluid intelligence to standardized testing performance to lifetime
earning potential. "Working memory" is also often used, particularly by
cautious psychologists and neuroscientists, as a proxy for the 'contents
of consciousness.' This talk will address recent
work -- using brain imaging (fMRI and EEG), brain stimulation (TMS),
and computational modeling -- that challenges the longstanding
assumption that for information to be held in working memory, it must be
held in an active state.
December 5, 2017
Rewards are worth the risk: Working in direct dark matter detection
Kimberly Palladino, UW Department of Physics
For particle physicists, determining the nature of Dark Matter is one
of the greatest open mysteries. An abundance of astrophysical evidence
indicates that the matter density of the universe is dominated by a new
form of matter, which played a key role in growth of large scale
structure. One candidate for Dark Matter is the Weakly Interacting
Massive Particle (WIMP). We hope to detect WIMPS by seeing them
scattering off of the target materials in our detectors. Liquid xenon
has proved itself an excellent target, and LZ is a dual-phase TPC that
will begin taking science data in 2020. Much of the originally proposed
parameter space for WIMPS has been excluded over the past few decades,
so I will also delve into the sociology of working on direct dark matter
December 12, 2017
Fractal occupancy of human landscapes: The concept of profit in
Tim Allen, UW Department of Botany
Systems are predictable on two criteria: the thermodynamics of
process; rate-independent constraints. The economics of this
distinction is high gain, straight consumption of quality fuel,
versus low gain where low quality material is processed to make
quality fuel. A quality resource might sit on a hot
spot. Evansville, WI, is a low gain system that depended on
rail road (which is planned). Janesville and Madison are
high gain depending or roads and fossil fuel. Roads are not
planned, they simply straighten and widen in response to the flux of
traffic. Railroads and roads end up with roughly the same
fractal dimension, but railroads branch out from the main line,
while roads emerge up scale from small roads to turnpikes.
Evansville depends on a diffuse low quality landscape, while
amassing capital by concentration. Janesville and Madison
depend on high quality, locally focused resources. The argument
turns on my satellite repairman based in Evansville, servicing a
diffuse landscape with information and constraint structure.