Cancer Moonshot Data and Technology Team: Enabling a National Learning Healthcare System for Cancer to Unleash the Power of Data.

The Cancer Moonshot emphasizes the need to learn from the experiences of cancer patients to positively impact their outcomes, experiences, and qualities of life. To realize this vision, there has been a concerted effort to identify the fundamental building blocks required to establish a National Learning Healthcare System for Cancer, such that relevant data on all cancer patients is accessible, shareable, and contributing to the current state of knowledge of cancer care and outcomes.

Charting a Course for Precision Oncology.

The fields of science have undergone dramatic reorganizations as they have come to terms with the realities of the growing complexities of their problem set, the costs, and the breadth of skills needed to make major progress. A field such as particle physics transformed from principal investigator-driven research supported by an electron synchrotron in the basement of your physics building in the 1950s, to regional centers when costs became prohibitive to refresh technology everywhere, driving larger teams of scientists to cooperate in the 1970s, to international centers where multinational teams work together to achieve progress. The 2013 Nobel Prize winning discovery of the Higgs boson would have been unlikely without such team science. Other fields such as the computational sciences are well on their way through such a transformation. Today, we see precision medicine as a field that will need to come to terms with new organizational principles in order to make major progress, including everyone from individual medical researchers to pharma. Interestingly, the Cancer Moonshot has helped move thinking in that direction for part of the community and now the initiative has been transformed into law.

Fermi-Pasta-Ulam beta model: boundary jumps, Fourier's law, and scaling.

We examine the interplay of surface and volume effects in systems undergoing heat flow. In particular, we compute the thermal conductivity in the Fermi-Pasta-Ulam beta model as a function of temperature and lattice size, and scaling arguments are used to provide analytic guidance. From this we show that boundary temperature jumps can be quantitatively understood, and that they play an important role in determining the dynamics of the system, relating soliton dynamics, kinetic theory, and Fourier transport.

Two-body random ensembles: from nuclear spectra to random polynomials

The two-body random ensemble for a many-body bosonic theory is mapped to a problem of random polynomials on the unit interval. In this way one can understand the predominance of 0(+) ground states, and analytic expressions can be derived for distributions of lowest eigenvalues, energy gaps, density of states, and so forth. Recently studied nuclear spectroscopic properties are addressed.

Robust nuclear observables and constraints on random interactions

The predictions of the interacting boson model two-body random ensemble are compared to empirical results on nuclei from Z = 8-100. Heretofore unrecognized but robust empirical trends are identified and related both to the distribution of valence nucleon numbers and to the need for and applicability of specific, nonrandom interactions. Applications to expected trends in exotic nuclei are discussed.