## Previous COMPUTE seminars

#### Detecting solar system objects with convolutional neural networks

Maggie Lieu (European Space Agency)

Monday May 6th, 14.00

Lundmarksalen, astronomihuset

Joint COMPUTE/AIML seminar

With upcoming big astronomical surveys such as LSST and Euclid imaging enormous
volumes of the sky at high speeds, the detection of asteroids, comets and
other moving bodies with traditional methods will not be feasible. Machine
learning methods such as convolutional neural networks can help us to sift
through the large amounts of data and quickly identify objects of interest
for follow up observation and tracking. In this talk I will show how CNNs can
be trained to effectively identify asteroids and other astronomical
objects in an unbiased manner even when the training data sample is small.

#### Cognitive Discovery: How AI is Changing Technical R&D

Costas Bekas (IBM Research, Zurich)

Tuesday March 26, 14.00

Lundmarksalen, astronomihuset

Joint COMPUTE/AIML event

**Abstract:** Cognitive Discovery (CD) is an AI-based holistic framework
designed to massively accelerate technical R&D. It introduces novel AI
technologies to ingest and represent complicated technical knowledge and
know-how, sift through oceans of data and drive technical hypothesis
discovery and verification by clever design of simulations. Real market
deployments of CD have demonstrated at least an order of magnitude
improvement in discovery rates of new technologies such as chemicals and
materials, while in addition driving the creation and curation of corporate
deep technical memory.

*Speaker biography* Dr. Costas Bekas is managing the Foundations of
Cognitive Solutions group at IBM Research-Zurich. He received B. Eng., Msc
and PhD diplomas, all from the Computer Engineering & Informatics
Department, University of Patras, Greece, in 1998, 2001 and 2003
respectively. Between 2003-2005, he worked as a postdoctoral associate with
prof. Yousef Saad at the Computer Science & Engineering Department,
University of Minnesota, USA. He has been with IBM since September 2005.
Costas's main research interests span AI, massive scale analytics and energy
aware algorithms and architectures. Costas is a recipient of the PRACE 2012
award and the ACM Gordon Bell 2013 and 2015 prizes.

__Monday March 18, 15.15__

**Andrew Winters** (Mathematical Institute, University of Cologne): Stability in High-Order Numerics

**Abstract:** Nature is non-linear. Many fundamental physical principles
such as conservation of mass, momentum, and energy are mathematically
modeled by non-linear time dependent partial differential equations (PDEs).
Such non-linear conservation laws describe a broad range of applications in
science and engineering, e.g., the prediction of noise and drag from
aircraft, the build up and propagation of tsunamis in oceans, the
behavior of gas clouds, and propagation of non-linear acoustic waves in
different materials.

In practice, marginally resolved simulations of non-linear conservation
laws, such as the compressible Navier-Stokes equations or the ideal
magnetohydrodynamics (MHD) equations, reveal that high-order methods are
prone to aliasing instabilities. This can lead to total failure and
breakdown of the algorithms. Aliasing issues are introduced and intensified
by a combination of insufficient discrete integration precision, collocation
of non-linear terms, polynomial approximations applied to rational
functions, and, again, by insufficient grid resolution. The aim of this
talk is to discuss a remedy for such aliasing issues and present its
connection to discrete variants of the product and chain rules. As such, we
construct nodal high-order numerical methods for non-linear conservation
laws that are entropy stable. To do so, we focus on particular approximate
derivative operators used to mimic steps from the continuous well-posedness
PDE analysis on the discrete level and enhance the robustness of the
high-order numerics.

__6 December 2018__

**Benjamin Ragan-Kelley** (Simula Research Laboratory):

Jupyter: facilitating interactive, open, and reproducible
science

__Friday 16 November 2018__

**Björn Nystedt** (NBIS):

Presentation of NBIS — National Bioinformatics Infrastructure Sweden

__21 September 2018__

**Steven Longmore** (Liverpool John Moores University):

Using machine learning to identify animals from drones

Video can be found
__
here__.

Abstract:

The World Wildlife Fund for Nature (WWF) estimates that up to five species of life on our planet become extinct every day. This astonishing rate of decline has potentially catastrophic consequences, not just for the ecosystems where the species are lost, but also for the world economy and planet as a whole. Indeed, biodiversity loss and consequent ecosystem collapse is commonly listed as one of the 10 foremost dangers facing humanity, and most pressingly in the developing world. There is a fundamental need to routinely monitor animal populations over much of the globe so that conservation strategies can be optimized with such information. The challenge faced to meet this need is considerable. To date most monitoring of animal populations is conducted manually, which is extremely labour-intensive, inherently slow and costly. Building on technological and software innovations in astronomy and machine learning, we have developed a drone plus thermal infrared imaging system and an associated automated detection/identification pipeline that has the potential to provide a cost-effective and efficient way to overcome this challenge. I will describe the current status of the system and our efforts to enable local communities in developing countries with little/no technical background to run routine monitoring and management of animal populations over large and inhospitable areas and thereby tackle global biodiversity loss.

__8 May 2018__

**Alice Quillen** (University of Rochester):

Astro-viscoelastodynamics or Soft Astronomy: Tidal encounters,
tidal evolution and spin dynamics

Abstract:

Mass spring models, originally developed for graphics and
gaming applications, can measure remarkably small deformations while
conserving angular momentum. By combining a mass spring model with an
N-body simulation, we simulate tidal spin down of a viscoelastic moon,
directly tying simulated rheology to orbital drift and internal heat
generation. I describe a series of applications of mass spring models
in planetary science. Close tidal encounters among large
planetesimals and moons were more common than impacts. Tidal
encounters can induce sufficient stress on the surface to cause large
scale brittle failure of an icy crust. Strong tidal encounters may be
responsible for the formation of long chasmata in ancient terrain of
icy moons such as Dione and Charon. The new Horizons mission
discovered that Pluto and Charon's minor satellites Styx, Nix,
Kerberos, and Hydra, are rapidly spinning, but surprisingly they have
spin axis tilted into the orbital plane (they have high obliquities).
Simulations of the minor satellites in a drifting Pluto-Charon binary
system exhibit rich resonant spin dynamics, including spin-orbit
resonance capture, tumbling resonance and spin-binary resonances. We
have found a type of spin-precession mean-motion resonance with Charon
that can lift obliquities of the minor satellites in the Pluto/Charon
system.

__12 April 2018__

**Paul-Christian Bürkner** (University of Münster):

Why not to be afraid of priors (too much)

Talk given at Bayes@Lund 2018. Click __here__ for videos and slides from the event.

__26 March 2018__

**Martin Turbet** (Laboratoire de Météorologie Dynamique, Paris):

Exploring the diversity of planetary atmospheres with Global Climate Models

Abstract:

More than 50 years ago, scientists created the first Global Climate Models
(GCMs) to study the atmosphere of the Earth. Since then, the complexity and
the level of realism of these models (that can now include the effect of
oceans, clouds, aerosols, chemistry, vegetation, etc.) have considerably
increased. The large success of these models have recently motivated the
development of an entire family of GCMs designed to study extra-terrestrial
environments in our solar system (Venus, Mars, Titan, Pluto) and even beyond
(extrasolar planets).

I will first show various GCM applications on Venus, Mars, Titan and Pluto.
Solar system GCMs successes and sometimes failures teach us useful lessons to
investigate and possibly predict the possible climates on planets where no
(or almost no) observations are available. I will then present several examples
of studies recently performed using a 'generic' Global Climate Model developed
at the Laboratoire de Météorologie Dynamique in Paris, designed to explore the
possible atmospheres and the habitability of ancient planets or extrasolar
planets.

__1 December 2017__

**Bojana Rosić** (TU Braunschweig): Uncertainty quantification in
a Bayesian setting

Abstract:

Concrete and human bone tissue are typical examples of materials which exhibit
randomness in the mechanical response due to an uncertain heterogeneous
micro-structure. In order to develop an appropriate probabilistic macro-scale
mathematical description, the essential step is to address the material as well
as possible other sources of uncertainties (e.g. excitations, change in geometry
, etc.) in the model. By extending already existing deterministic models derived
from Helmholtz free energy and the dissipation functions characterising
ductile or quasi-brittle behaviour, the goal of this talk is to identify and
quantify
uncertainty in the system response. For this purpose a Bayesian probabilistic
setting is considered in which the modeller's a priori knowledge about the model
parameters and the available set of data obtained by experiments are taken into
account when identifying the corresponding probability distribution functions
of unknown parameters. Identification in the form of Bayesian inverse
problems -
in particular when experiments are performed repeatedly - requires an
effcient solution and representation of possibly high dimensional probabilistic
forward problems, i.e. the estimation of the measurement prediction given prior
assumption. An emergent idea is to propagate parameter uncertainties through
the model in a Galerkin manner in which the solution of the corresponding
differential
equations is represented by a set of stochastic basis polynomials, the
cardinality of which grows exponentially. To allow an effcient solution of
high-dimensional
problems this talk will present the new low-rank Galerkin schemes
combined with Bayesian machine learning approaches.

__30 May 2017__

**Michel Defrise** (Vrije Universiteit, Brussel):
Statistical reconstruction methods in medical imaging

Abstract:

Statistical reconstruction methods are probably today the most common methods to obtain tomographic images from SPECT/PET measurements. The methods are based on modelling the camera systems and thereby iteratively find a good estimate of the internal radionuclide distribution from the similarity of the calculated and measured projection data. The main advantage is here that if physical problems, associated with the measurement of the radiation, such as, non-homogeneous photon attenuation, contribution from scattered photons, partial volume problems due to collimator resolution, septal penetration etc, can be modelled accurately then this naturally comes out as a compensation for the problems. The lecture will cover the fundamental mathematical parts of the procedures describe above.

__14 November 2016__

**INTEGRATE meeting** -- see the INTEGRATE website for more details.

__26 October 2016__

**INTEGRATE math-hack day** -- see the INTEGRATE website for more details.

__5 October 2016__

**INTEGRATE hack day** -- see the INTEGRATE website for more details.

__26 September 2016__

**INTEGRATE meeting** -- see the INTEGRATE website for more details.

__11 May 2016__

**INTEGRATE meeting** -- see the INTEGRATE website for more details.

__25 April 2016__

**INTEGRATE math-hack day** -- see the INTEGRATE website for more details.

__12 April 2016__

**Patrick Farrell** (Oxford University): Automated adjoint simulations with FEniCS and dolfin-adjoint

Abstract:

The derivatives of PDE models are key ingredients in many important algorithms of computational science. They find applications in diverse areas such as sensitivity analysis, PDE-constrained optimisation, continuation and bifurcation analysis, error estimation, and generalised stability theory.

These derivatives, computed using the so-called tangent linear and adjoint models, have made an enormous impact in certain scientific fields (such as aeronautics, meteorology, and oceanography). However, their use in other areas has been hampered by the great practical difficulty of the derivation and implementation of tangent linear and adjoint models. Naumann (2011) describes the problem of the robust automated derivation of parallel tangent linear and adjoint models as ``one of the great open problems in the field of high-performance scientific computing''.

In this talk, we present an elegant solution to this problem for the (common) case where the original discrete forward model may be written in variational form, and discuss some of its applications.

__11 April 2016__

**INTEGRATE hack day** -- see the INTEGRATE website for more details.

__14 March__

**INTEGRATE meeting** -- see the INTEGRATE website for more details.

__12 October 2015__

**Volker Springel** (Heidelberg Institute for Theoretical Studies): Cosmic structure formation on a moving
mesh

Abstract:

Recent years have seen impressive progress towards hydrodynamic
cosmological simulations of galaxy formation that try to account for
much of the relevant physics in a realistic fashion. At the same time,
numerical uncertainties and scaling limitations in the available
simulation codes have been recognized as important challenges. I will
review the state of the field in this area, highlighting a number of
recent results obtained with large particle-based and mesh based
simulations. I will in particularly describe a novel moving-mesh
methodology for gas dynamics in which a fully dynamic and adaptive
Voronoi tessellation is used to formulate a finite volume
discretization of hydrodynamics which offers numerous advantages
compared with traditional techniques. The new approach is fully
Galilei-invariant and gives much smaller advection errors than
ordinary Eulerian codes, while at the same time offering comparable
accuracy for treating shocks and an improved treatment of contact
discontinuities. The scheme adjusts its spatial resolution to the
local clustering of the flow automatically and continuously, and hence
retains a principle advantage of SPH for simulations of cosmological
structure growth. Applications of the method in large production
calculations that aim to produce disc galaxies similar to the Milky
Way will be discussed.

__16 April 2015__

**Derek Richardson** (University of Maryland):
Asteroids: Modeling the future of space exploration

Abstract:

Over the past 2 decades since the first spacecraft images were returned from an asteroid, we have learned that these potentially hazardous objects not only often support satellites but are likely themselves loose collections of fragmented material. Numerical simulations assist in understanding the evolution of these leftover building blocks of the terrestrial planets, planning for the mitigation of their threat to Earth, and for advising space mission designers on the challenges of sample return and possible astronaut landing. Our group uses an adapted high-performance parallelized gravity tree code (PKDGRAV) to simulate gravitational and collisional processes among small bodies in space. Basic features of the code will be presented, along with their application to selected topics in small-body evolution. The talk will feature our latest simulations of granular flow in microgravity, a key tool for modeling sample-return mechanisms.

__23 March 2015__

**Thomas Neuhaus** (Jülich Supercomputing Centre):
Quantum computing via quantum annealing from a physics point of view

Abstract:

I present an overview on the theory of quantum annealing for the use of solving so called intractable mathematical problems. I will introduce satisfiability problems consisting of a number of simple constraints (clauses) on a set of Boolean variables (e.g., 2SAT and 3SAT) and report on today's knowledge on the usefulness of quantum annealing in such theories. I will also give an introduction to the existing Dwave Quantum Computer and present a few computer experiments on the machine. As of today theoretical physics has not yet identified a class of mathematical problems, nor physical theories, that really benefits from quantum annealing with certainty. A search for such problems is under way.

__16 February 2015__

**Gregor Gassner** (University of Cologne): A massively parallel model for fluid dynamics simulations

Abstract:

In this talk, I will consider the numerical simulation of non-linear advection-diffusion problems, particularly of the compressible Navier-Stokes equations used to model turbulent fluid flows in engineering applications and problems appearing in natural sciences.

For this, we develop stable and accurate methods for conservation laws and incorporate other important physical aspects, such as e.g. entropy stability. Examples include the Burgers equation, the shallow water equations, Maxwell's equations and the Euler equations.

A special emphasis is on the computational implementation of these mathematical models such that they are well suited for realistic applications. Due to the multi-scale character of the considered problems, a large amount of spatial and temporal resolution is needed for an accurate approximation. The number of spatial degrees of freedom are as high as one billion with over one hundred thousand time steps. Such simulations are only feasible, when the power of today's largest supercomputers are unleashed.

I will present a special parallelization strategy which is tailored directly to the mathematical model in use and allows simulations on over one hundred thousand cores with near perfect parallel efficiency. Scaling results on different machines are demonstrated, where the absolute limit of MPI is tested with only one grid cell left on a processor.

At the end of the talk, some applications simulated with this framework are illustrated.

__15 December 2014__

**Anna-Karin Tornberg** (KTH): Accelerated boundary integral simulations of particulate and two-phase flows

Abstract:

In micro-fluidic applications where the scales are small and viscous effects
dominant, the Stokes equations are often applicable. The suspension dynamics
of fluids with immersed rigid particles and fibers are very complex also in
this Stokesian regime, and surface tension effects are strongly pronounced
at interfaces of immiscible fluids - such as surfaces of water drops in oil.

Simulation methods can be developed based on boundary integral equations,
which leads to discretizations of the boundaries of the domain only, and
hence fewer unknowns compared to a discretization of the PDE. This involves
evaluating integrals containing the fundamental solution (Green's function)
for the PDE. This will result in both singular and nearly singular integrals
that need to be evaluated, and the construction of accurate quadrature methods
is a main challenge. The Green's functions decay slowly, which results in
dense or full system matrices. To reduce the cost of the solution of the
linear system, an acceleration method must be used. If these two issues -
accurate quadrature methods and acceleration of the solution of the linear
system - are properly addressed, boundary integral based simulations can be
both highly accurate and very efficient.

I will give an introduction to boundary integral methods - discussing the
concepts starting with the simplest formulation for rigid particles, before
discussing the more well-conditioned formulations that we actually use. I
will give the main ideas for a spectrally accurate FFT based Ewald method
developed for the purpose of accelerating simulations, and for quadrature
treatment in two and three dimensions. I will show results for periodic
suspensions of rigid particles in 3D and of interacting drops in 2D.

__17 November 2014__

**Debora Sijacki** (University of Cambridge): Simulating galaxy formation: numerical and physical uncertainties

Abstract:

Hydrodynamical cosmological simulations are one of the most powerful tools to
study the formation and evolution of galaxies in the fully non-linear
regime. Despite several recent successes in simulating Milky Way look-alikes,
self-consistent, ab-initio models are still a long way off. In this talk I will
review numerical and physical uncertainties plaguing current state-of-the-art
cosmological simulations of galaxy formation. I will then present global
properties of galaxies as obtained with novel cosmological simulations with
the moving mesh code Arepo and discuss which physical mechanisms are needed to
reproduce realistic galaxy morphologies in the present day Universe.

__20 October 2014__

Lund University Humanities Lab — Why the humanities needs a lab and what we
do in it

**Marianne Gullberg**, Director of the Humanities Lab:

Why on earth do the Humanities need a lab?

Tea/coffee

**Annika Andersson**:

What the recording of brainwaves can tell us about language processing

**Marcus Nyström**:

What are eye movements? Looking into the elastic eye

**Victoria Johansson**:

Are we reading during writing? What does the combination of keystroke logging and eyetracking reveal?

**Nicolo dell'Unto**:

The use of 3D models for intra-site investigation in Archaeology

Abstract:

Lund University Humanities Lab is an interdisciplinary research and training facility whose aim is to enable scholars (mainly) in the humanities to combine traditional and novel methods, and to interact with other disciplines in order to meet the scientific challenges ahead. The Lab hosts technology, methodological know-how, and archiving expertise, and a wide range of research projects. Activities are centered around issues of communication, culture, cognition and learning, but many projects are interdisciplinary and conducted in collaboration with the social sciences, medicine, the natural sciences, engineering, and e-Science locally (Lund University), nationally, and internationally. We start with a brief overview of the lab and its facilities, followed by four short talks exemplifying the kind of research that takes place in the Lab.

__27 May 2014__

**Freddy Ståhlberg** (Dept. of Medical Radiation Physics):
What is LBIC?

Abstract:

The overall goal of Lund University Bioimaging Center (LBIC) is to pursue in-depth knowledge of human metabolism and function by developing and combining advanced imaging techniques, primarily high-field MRI, PET and SPECT). The goal is accomplished by a step-by-step establishment of the above mentioned bio-imaging center at our University, using already well-established research groups in the field as the core structure.

To achieve this goal, we provide technical platforms, knowledge and support in the development of new diagnostic methods from experimental models, while at the same time taking unmet clinical problems to device patient-specific tailored therapies. Technically, MRI and PET will be advanced both as individual modalities and also towards a merged use. We envision future simultaneous extraction of physiological and molecular information in a multimodal imaging environment for better understanding the impact of molecular events on cellular/tissue behavior. We believe that the development of the Lund University Bioimaging Center will have a significant impact on the research at Lund University. Locally, the center is a powerful resource for translational research at the medical faculty and at Skåne university hospital, with strong connections to planned larger research facilities in Lund, e.g. MAXIV and ESS Scandinavia. On a national and international level, the buildup of the proposed center can be foreseen to become an asset to the whole biomedical research community.

__5 May 2014__

**Martin Rosvall** (Umeå University):
Memory in network flows and its effects on community detection, ranking, and spreading

Abstract:

It is a paradigm to capture the spread of information and disease with random flow on networks. This conventional approach ignores an important feature of the dynamics: where flow moves to depends on where it comes from. That is, memory matters. We analyze multi-step pathways from different systems and show that ignoring memory has profound consequences for community detection. Compared to analysis without memory, community detection with memory generally reveals system organizations with more and smaller modules that overlap to a greater extent. For example, we show that including memory reveals actual travel patterns in air traffic and multidisciplinary journals in scientific communication. These results suggest that we can use only more data and not more elaborate algorithms to identify real modules in integrated systems.

__23 April 2014__

**Paul Segars** (Duke University):
The XCAT phantom based on NURBS to create realistic anatomical
computer models for use in Medical Imaging simulations

Talks on research involving voxel-based phantoms
at Dept of Medical Radiation Physics, Lund University:

1) Michael Ljungberg: Nuclear medicine
and the use of voxel-phantoms in Monte Carlo research

2) Gustav Brolin: A
national quality assurance study of dynamic 99Tcm-MAG3 renography using Monte
Carlo simulations and the XCAT phantom

3) Katarina Sjögreen Gleisner: An
introduction to image-based dosimetry

4) Johan Gustafsson:
A procedure for evaluation of accuracy in Image-Based dosimetrical
caculations using the XCAT Phantom

__9 December 2013__

**Thomas Curt** (Irstea):
Modelling fire behaviour and simulating fire-landscape
relationships: Possibilities and Challenges

Abstract:

Fire is one of the major disturbances on the global scale, shaping landscapes
and vegetation, and affecting the global carbon cycle (Gill et al., 2013).
Global changes (land use changes and climate change) are predicted to modify
fire regimes and fire distribution in many parts of the world (Krawchuk et al.,
2009). In this context assessing fire risk and simulating fire-landscape
interactions become crucial to sustainable land management.
In the recent period, important progress has been made to model fire behavior
and to simulate fires on various spatial scales. A variety of models and
simulators now exist, which have specific abilities and limitations (see
http://www.fire.org/). We propose to review some of these models, and to sum up
their purpose, potential, and challenges. Fire behavior models (e.g.
BehavePlus, Firetec) allow simulating fire behavior for almost all ecosystems
using quite simple field data. They also permit to assess fire effects on the
ecosystems, notably postfire tree mortality. Some of these models are fully
physics-based (2D or 3D), while others use empirical equations. They have been
used or adapted to a large array of ecosystems and climate conditions
worldwide, and examples will be presented. Landscape-fire models (e.g. Farsite,
FlamMap) are spatially-explicit and designed to simulate fires with different
weather scenarios in sufficiently realistic landscapes (Cary et al., 2006).
Thus they consider the combined effects of weather, fuels, and topography.
Recently, high performance fire simulation systems have been developed to
permit the simulation of hundreds of thousands of fires. They provides
large-scale maps of burn probability or flame length, thus allowing to assess
which ecosystems and areas are at risk and should be monitored and managed
preferentially. Some applications based on this type of models will be
presented. Coupling fire behavior models with vegetation into Dynamic Global
Vegetation Model (e.g. LPJ, Sierra) allows studying the role of fire
disturbance for global vegetation dynamics. Their application at regional scale
requires an approach which is explicit enough to simulate geographical
patterns, but general enough to be applicable to each vegetation type at large
scales. We shall present how the Sierra model can be used at local scale, in
order to predict vegetation shifts according to different scenarios of future
fire regime.

__27 May 2013__

**Kevin Heng** (University of Bern):
Exoplanetary Atmospheres and Climates: Theory and Simulation

Abstract:

Exoplanet discovery is now an established enterprise. The next
frontier is the in-depth characterization of the atmospheres and
interiors of exoplanets, in preparation for next-generation
observatories such as CHEOPS, TESS and JWST. In this presentation, I
will review the astronomical, astrophysical and computational aspects
of this nascent field of exoplanet science. I will begin by reviewing
the observations of transit (absorption) and eclipse (emission) spectra
and phase curves, emphasizing the importance of understanding
clouds/hazes. Next, I will review the astrophysical aspects of
understanding exoplanetary atmospheres, including the need to elucidate
the complex interplay between dynamics, radiation and magnetic fields.
Finally, I will discuss the Exoclimes Simulation Platform (ESP), an
open-source set of simulational tools currently being constructed by my
Exoplanets and Exoclimes Group at the University of Bern, reviewing the
technical challenges faced by the ESP team. Advancing the theoretical
state of the art requires a hierarchical (1D models versus 3D
simulations) and multi-disciplinary approach, drawing from astronomy,
astrophysics, geophysics, atmospheric and climate science, applied
mathematics and planetary science.

__7 May 2013__

** Susanna C. Manrubia** (Centro de Astrobiología,
Madrid):
Tinkering in an RNA world and the origins of life

Abstract:

Life arose on Earth some 3.8 billion years ago. Despite tremendous
experimental and theoretical efforts in the last 60 years to uncover how the
first protocells could have originated from abiotic matter, we are still
facing many more unknowns than answers. Two main players in the process are
self-replicating molecules and metabolic cycles, whose emergence requires the
presence of chemical species with the ability to code genetic information and
catalyze chemical reactions. In current living organisms, DNA performs the
former function and proteins the latter. But there is one molecule, RNA, able
to perform both functions. This fact has led to the hypothesis that an ancient
RNA world could have preceded modern cellular organization. That attractive
scenario opens the possibility of carrying out computational studies on issues
such as how RNA molecules could have been selected for simple chemical
functions, what is the probability that such a molecule would arise in
prebiotic environments in the absence of faithful template replication, or how
populations of molecules explore the space of sequences and disclose
evolutionary innovations.

__10 December 2012__

**Bernhard Mehlig** (Göteborg University):
Turbulent aerosols: clustering, caustics, and collisions

Abstract:

Turbulent aerosols (particles suspended in a turbulent fluid
or a random flow) are fundamental to understanding chemical and kinetic
processes in many areas in the Natural Sciences, and in technology. Examples
are the problem of rain initiation in turbulent clouds, and the problem of
describing the collisions and aggregation of dust grains in circumstellar
accretion disks.

In this talk I summarise recent progress in our understanding of the dynamics
of turbulent aerosols. I discuss how the suspended particles may cluster
together, and describe their collision dynamics in terms of singularities in
the particle motion (so-called caustics).

__25 October 2012 __

**Chris Lintott** (Oxford University):
What to do with 600,000 scientists

Abstract:

'Citizen science' - the involvement of hundreds of thousands of
internet-surfing volunteers in the scientific process - is a radical solution
to the problem of Big Data. The largest and most successful such project,
Galaxy Zoo, has seen volunteers provided more than 200 million classifications
of more than 1 million galaxies, going beyond simple classification task to
make and even follow-up serendipitous discoveries of their own. As PI of
Zooniverse.org, astronomer Chris Lintott leads a team that has enabled
volunteers to sort through a million galaxies, discover planets of their own,
determine whether whales have accents and even transcribe ancient papyri. In
this talk, he will review some of the highlights of their work, explore the
technology needed to keep such a large group of volunteers busy and look
forward to a future when man and machine can work in harmony once more...

__7 June 2012 __

**Cristian Micheletti** (International School for Advanced Studies, Trieste):
Coarse-grained simulations of DNA in confined geometries.

Abstract:

Biopolymers in vivo are typically subject to spatial restraints, either as a
result of molecular crowding in the cellular medium or of direct spatial
confinement. DNA in living organisms provides a prototypical example of a
confined biopolymer. Confinement prompts a number of biophysics questions. For
instance, how can the high level of packing be compatible with the necessity to
access and process the genomic material? What mechanisms can be adopted in vivo
to avoid the excessive geometrical and topological entanglement of dense phases
of biopolymers? These and other fundamental questions have been addressed in
recent years by both experimental and theoretical means. Based on the recent
reviews of refs. [1,2] we shall given an overview of these studies and report
on general simulation techniques that can be effectively used to characterize
the equilibrium properties of coarse-grained models of confined biomolecules.

References:

[1] D. Marenduzzo et al. J. Phys.: Condens. Matter 22 (2010) 283102

http://iopscience.iop.org/0953-8984/22/28/283102/

[2] C. Micheletti et al. Physics Reports, 504 (2011) 1-73

http://www.sciencedirect.com/science/article/pii/S0370157311000640

Download a **PDF of the slides** __here__.

Back to **Upcoming seminars**.

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