Scale interactions and anisotropy in stable boundary layers
Some of the strongest challenges for numerical weather prediction come from the unsteady nature of certain flows, in particular nocturnal and stable boundary layers. Read more →
Condensation of degrees emerging through a first-order phase transition in classical random graphs
When steam condenses from vapour into liquid, the water molecules move closely together and the system, from a mathematical point of view, comes to reside in an extremely small portion of the conceptually available phase space. Read more →
Effective bandwidth of non-Markovian packet traffic
Telecommunications engineers and operations researchers aim to manage complex and fluctuating traffic flows through extended networks. Among other techniques, they have exploited results from the theory of large deviations to estimate the likelihood that a demand in service will overflow the available resources. Read more →
Thermodynamic uncertainty for run-and-tumble type processes
Systems out of equilibrium typically carry macroscopic currents of particles, mass or energy. Thermodynamic uncertainty relations offer universal bounds linking such currents and their statistical fluctuations to other system properties, especially entropy production. Read more →
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 →
CONTACT
London Mathematical Laboratory
8 Margravine Gardens
London
W6 8RH
