Comment on D. Bernoulli (1738)

Probability theory emerged in the second half of the 17th century as a way to think about monetary gambles, and how to choose wisely when facing uncertainty. Early thinking suggested that people would act so as to maximise the expected change in wealth – an average over all possible outcomes. Read more

Detection and replenishment of missing data in marked point processes

Point processes offer a convenient mathematical representation of earthquakes, volcanic eruptions, crimes and many other processes which occur at random times and locations. The data available in these fields has exploded with modern recording technology, and yet many data sets suffer from significant incompleteness. Read more

Can Signal Delay Be Functional? Including Delay In Evolved Robot Controllers

Signals travel at finite speeds within the nerves of living organisms, between satellites and the Earth, or in computers and other technological devices. As a result, they incur delays in moving from one point to another, which engineers, roboticists, control-theorists and neuroscientists typically consider as a source of error. Read more

Anomalous Diffusion in Random Dynamical Systems

Brownian motion has long been the standard paradigm for modelling random, diffusive motion, such as the haphazard movement of a dust particle floating in a fluid. This is considered to be “normal” diffusion, in which the mean square particle displacement – calculated as an average over an ensemble of particles – increases linearly in the long-time limit. Read more

Mark Kirstein becomes a DAAD PRIME Fellow

LML Fellow Mark Kirstein has received a PRIME fellowship from DAAD (the German Academic Exchange Service). This will support a 12-month research visit to the London Mathematical Laboratory, followed by a postdoctoral position at Leipzig University for 6 months. Mark will use his time at LML to study The time resolution of the probability weighting puzzle as a member of the Ergodicity Economics (EE) research group. Read more

Toward understanding the impact of artificial intelligence on labour

Economists and policy makers worry that the rapid advance of artificial intelligence (AI) and automation technologies could seriously disrupt labour markets. Read more

Noisy network attractor models for transitions between EEG microstates

Electroencephalography (EEG) provides a direct measure of neuronal activity as reflected in the scalp electrical field. Empirically, global measures of EEG topography remain stable in so-called EEG microstates for brief periods (50–100 ms) before switching to another quasi-stable state. Read more

Limits to machine prediction, the psychology of Brexit fantasies and how biology exploits phase transitions – a few recent essays

Here are links to a few recent articles by LML Fellow Mark Buchanan. Read more

Normal and Anomalous Diffusion in Soft Lorentz Gases

Engineered nanoscale structures known as artificial graphene exhibit the properties of real graphene but in a setup where it is easy to tune features such as the electronic density, lattice constant, geometry or coupling with the environment. Read more

On reversals in 2D turbulent Rayleigh-Bénard convection: Insights from embedding theory and comparison with proper orthogonal decomposition analysis

In the 1980s, most researchers approached empirical analysis of low-dimensional dynamical systems through the famous Takens embedding theorem, which guarantees that the attractor of any dynamical system can be reconstructed from samples of the values of key variables. Read more