Functional control of network dynamics using designed Laplacian spectra

Complex real-world phenomena across a wide range of scales, from aviation and internet traffic to signal propagation in electronic and gene regulatory circuits, can be efficiently described through dynamic network models. In many such systems, the spectrum of the underlying graph Laplacian plays a key role in controlling the matter or information flow. Spectral graph theory has traditionally prioritized unweighted networks. Here, we introduce a complementary framework, providing a mathematically rigorous weighted graph construction that exactly realizes any desired spectrum. We illustrate the broad applicability of this approach by showing how designer spectra can be used to control the dynamics of various archetypal physical systems. Specifically, we demonstrate that a strategically placed gap induces chimera states in Kuramoto-type oscillator networks, completely suppresses pattern formation in a generic Swift-Hohenberg model, and leads to persistent localization in a discrete Gross-Pitaevskii quantum network. Our approach can be generalized to design continuous band gaps through periodic extensions of finite networks.Comment: 9 pages, 5 figure

Clinical review: Influenza pandemic – physicians and their obligations

An influenza pandemic threatens to be the most lethal public health crisis to confront the world. Physicians will have critical roles in diagnosis, containment and treatment of influenza, and their commitment to treat despite increased personal risks is essential for a successful public health response. The obligations of the medical profession stem from the unique skills of its practitioners, who are able to provide more effective aid than the general public in a medical emergency. The free choice of profession and the societal contract from which doctors derive substantial benefits affirm this commitment. In hospitals, the duty will fall upon specialties that are most qualified to deal with an influenza pandemic, such as critical care, pulmonology, anesthesiology and emergency medicine. It is unrealistic to expect that this obligation to treat should be burdened with unlimited risks. Instead, risks should be minimized and justified against the effectiveness of interventions. Institutional and public cooperation in logistics, remuneration and psychological/legal support may help remove the barriers to the ability to treat. By stepping forward in duty during such a pandemic, physicians will be able to reaffirm the ethical center of the profession and lead the rest of the healthcare team in overcoming the medical crisis

Stochastic cycle selection in active flow networks

Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such nonequilibrium networks. Here we connect concepts from lattice field theory, graph theory, and transition rate theory to understand how topology controls dynamics in a generic model for actively driven flow on a network. Our combined theoretical and numerical analysis identifies symmetry-based rules that make it possible to classify and predict the selection statistics of complex flow cycles from the network topology. The conceptual framework developed here is applicable to a broad class of biological and nonbiological far-from-equilibrium networks, including actively controlled information flows, and establishes a correspondence between active flow networks and generalized ice-type models. Keywords: networks; active transport; stochastic dynamics; topologyNational Science Foundation (U.S.) (Award CBET-1510768

A Doctor’s First, and Last, Responsibility is to Care Comment on “Denial of Treatment to Obese Patients—the Wrong Policy on Personal Responsibility for Health”

The obesity epidemic raises important and complex issues for clinicians and policy-makers, such as what clinical and public health measures will be most effective and most ethically-sound. While Nir Eyal’s analysis of these issues is very helpful and while he correctly concludes that “conditioning the very aid that patients need in order to become healthier on success in becoming healthier” is wrong, further discussions of these issues must include unequivocal support for safeguarding the fundamental moral basis of the doctor-patient relationship. Regardless of any patients’ failures to demonstrate effective responsibility for their own health, each patient needs and deserves a physician whose caring is never in doubt. Policy- makers need to ensure that our health systems always make this a top priority

Stochastic cycle selection in active flow networks.

Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such nonequilibrium networks. Here we connect concepts from lattice field theory, graph theory, and transition rate theory to understand how topology controls dynamics in a generic model for actively driven flow on a network. Our combined theoretical and numerical analysis identifies symmetry-based rules that make it possible to classify and predict the selection statistics of complex flow cycles from the network topology. The conceptual framework developed here is applicable to a broad class of biological and nonbiological far-from-equilibrium networks, including actively controlled information flows, and establishes a correspondence between active flow networks and generalized ice-type models.This is the accepted manuscript. It is currently embargoed pending publication