Integrated Calendar

Quantum field theory (QFT) is the universal language of theoretical physics, underlying the Standard Model of elementary particles, the physics of the early Universe and a host of condensed matter phenomena such as phase transitions and superconductivity. A great achievement of 20th-century physics was the understanding of weakly coupled quantum field theories where interactions can be treated as small perturbations of otherwise freely moving particles. Critical challenges for the 21st century include solving the problem of strong coupling and mapping the whole space of consistent QFTs.
In this lecture, I will overview the bootstrap approach, the idea that theory space can be determined from the general principles of symmetry and quantum mechanics. This strategy provides a new unifying language for QFT and has allowed researchers to make predictions for physical observables even in strongly coupled theories. By holographic duality, the bootstrap program has also implications for the space of consistent quantum gravity theories.

Recent technological advances such as next-generation sequencing and new capture and sampling techniques have enabled the retrieval of genomic information from archaeological human remains, even from regions previously known to have poor conditions for DNA preservation, such as the Near East. I will describe two studies in which these methods helped us in recording the past by tracing human mobility and disease. In the first study, we retrieved a high-coverage Y. pestis genome from the remains of a 6th century victim of the Justinianic Plague, the first of three historic pandemics caused by Y. pestis. The results confirmed a central or south Asian origin of the strain and demonstrated its presence in rural south Germany where no historical source records it. In a second study, genome-wide data was reconstructed from human remains recovered from the ancient seaport of Ashkelon, identified as “Philistine” during the Iron Age. The comparison of Bronze and Iron Age individuals was used to address whether the cultural transition observed in the archaeological record was mirrored by a foreign genetic influx.

Recent droughts and floods in California have drawn attention to the vulnerability of our water-supply system to present and future climate variability. A recent analysis of climate-model simulations suggests that wet and dry conditions in California may be predictably linked to tropical and high-latitude conditions, a hypothesis that should be testable using paleoclimate records. Abundant paleoclimate evidence indicates that natural whiplash between wet and dry conditions characterized California’s climate throughout the last 4000 years, especially during the Medieval Climate Anomaly (~AD 950 to 1250), but the chronologies of the records are not precise enough to correlate to tropical and high-latitude records in order to test the model prediction. Our recent work at Mono Lake, a climatically sensitive lake on the arid eastern side of the Sierra Nevada mountain range, has focused on exploring and developing radiocarbon dating of pollen purified by flow cytometry as a tool for high-resolution dating of lake records. Our results suggest that pollen can be reliably separated and dated, but (like everything in lakes) must be interpreted within the specific geologic system where it was produced, deposited, and preserved. If pollen dating proves robust in many lake systems, it may provide the high-precision chronologies required for spatial mapping of past terrestrial climate changes.

I will tell you two stories of adaptation of populations aided and enriched by statistical physics approaches.

The first story is about the adaptation of bacteria with CRISPR. CRISPR-Cas is a famous biology buzz word, due to its applications to gene editing. However, CRISPR-Cas is also a prokaryote immune system. It works as a “library” of previous infections. This library contains snippets of exogenous genetic material. With a new infection, the library is consulted, and if a match is found, the attempt will be made to neutralize the intruding genome. Bacteria use CRISPR-Cas as an immune system against phages and plasmids. Such immunity is hereditary and dynamic — it can be gained and lost during the lifetime of the single bacteria. Also, the process of acquiring snippets when exposed to the same phage is stochastic, and the same strain bacteria in a population contain different CRISPR loci content and thus variable immunity to the phage. We use dynamical systems approaches to predict the shape of this diverse distribution of CRISPR loci content within a bacterial population as a function of two crucial parameters — the rate of acquisition and the immunity to the phage.

The second story is about adaptation on a rugged fitness landscape. A crude measure of adaption to a new environment called fitness. Often one defines fitness as the expected growth rate. The higher the fitness, the more thriving is a population. What happens over long times for a population with a finite genome — when all beneficial, fitness mutations, are exhausted? Contrary to expectations, the experiments show that fitness does not reach a plateau. Here we introduce a spin-glass microscopic model, where a genome can be represented as a spin configuration, and individual spins are genes. The fitness plays the role of minus the Hamiltonian of the system. We use numerical approaches and estimates to study hopping between metastable states on a rugged fitness landscape. We show that with gene interactions (interacting spins), double beneficial mutations (flipping of pairs of spins) can lead to a slow, logarithmic increase of fitness in a wide class of cases.