The structure of the asteroid 4 Vesta as revealed by models of planet-scale collisions

Asteroid 4Vesta seems to be a major intact protoplanet, with a surface composition similar to that of the HED (howardite-eucrite-diogenite) meteorites. The southern hemisphere is dominated by a giant impact scar, but previous impact models have failed to reproduce the observed topography. The recent discovery that Vesta's southern hemisphere is dominated by two overlapping basins provides an opportunity to model Vesta's topography more accurately. Here we report three-dimensional simulations of Vesta's global evolution under two overlapping planet-scale collisions. We closely reproduce its observed shape, and provide maps of impact excavation and ejecta deposition. Spiral patterns observed in the younger basin Rheasilvia, about one billion years old, are attributed to Coriolis forces during crater collapse. Surface materials exposed in the north come from a depth of about 20kilometres, according to our models, whereas materials exposed inside the southern double-excavation come from depths of about 60-100kilometres. If Vesta began as a layered, completely differentiated protoplanet, then our model predicts large areas of pure diogenites and olivine-rich rocks. These are not seen, possibly implying that the outer 100kilometres or so of Vesta is composed mainly of a basaltic crust (eucrites) with ultramafic intrusions (diogenites).

Ultracold Quantum Gases and Lattice Systems: Quantum Simulation of Lattice Gauge Theories

Abelian and non-Abelian gauge theories are of central importance in many areas of physics. In condensed matter physics, AbelianU(1) lattice gauge theories arise in the description of certain quantum spin liquids. In quantum information theory, Kitaev’s toric code is a Z(2) lattice gauge theory. In particle physics, Quantum Chromodynamics (QCD), the non-Abelian SU(3) gauge theory of the strong interactions between quarks and gluons, is nonperturbatively regularized on a lattice. Quantum link models extend the concept of lattice gauge theories beyond the Wilson formulation, and are well suited for both digital and analog quantum simulation using ultracold atomic gases in optical lattices. Since quantum simulators do not suffer from the notorious sign problem, they open the door to studies of the real-time evolution of strongly coupled quantum systems, which are impossible with classical simulation methods. A plethora of interesting lattice gauge theories suggests itself for quantum simulation, which should allow us to address very challenging problems, ranging from confinement and deconfinement, or chiral symmetry breaking and its restoration at finite baryon density, to color superconductivity and the real-time evolution of heavy-ion collisions, first in simpler model gauge theories and ultimately in QCD.

Glacial–interglacial dynamics of Antarctic firn columns: comparison between simulations and ice core air-δ15N measurements

Correct estimation of the firn lock-in depth is essential for correctly linking gas and ice chronologies in ice core studies. Here, two approaches to constrain the firn depth evolution in Antarctica are presented over the last deglaciation: outputs of a firn densification model, and measurements of δ15N of N2 in air trapped in ice core, assuming that δ15N is only affected by gravitational fractionation in the firn column. Since the firn densification process is largely governed by surface temperature and accumulation rate, we have investigated four ice cores drilled in coastal (Berkner Island, BI, and James Ross Island, JRI) and semi-coastal (TALDICE and EPICA Dronning Maud Land, EDML) Antarctic regions. Combined with available ice core air-δ15N measurements from the EPICA Dome C (EDC) site, the studied regions encompass a large range of surface accumulation rates and temperature conditions. Our δ15N profiles reveal a heterogeneous response of the firn structure to glacial–interglacial climatic changes. While firn densification simulations correctly predict TALDICE δ15N variations, they systematically fail to capture the large millennial-scale δ15N variations measured at BI and the δ15N glacial levels measured at JRI and EDML – a mismatch previously reported for central East Antarctic ice cores. New constraints of the EDML gas–ice depth offset during the Laschamp event (~41 ka) and the last deglaciation do not favour the hypothesis of a large convective zone within the firn as the explanation of the glacial firn model–δ15N data mismatch for this site. While we could not conduct an in-depth study of the influence of impurities in snow for firnification from the existing datasets, our detailed comparison between the δ15N profiles and firn model simulations under different temperature and accumulation rate scenarios suggests that the role of accumulation rate may have been underestimated in the current description of firnification models.

Is the Atlantic subpolar gyre bistable in comprehensive coupled climate models?

The Atlantic subpolar gyre (SPG) is one of the main drivers of decadal climate variability in the North Atlantic. Here we analyze its dynamics in pre-industrial control simulations of 19 different comprehensive coupled climate models. The analysis is based on a recently proposed description of the SPG dynamics that found the circulation to be potentially bistable due to a positive feedback mechanism including salt transport and enhanced deep convection in the SPG center. We employ a statistical method to identify multiple equilibria in time series that are subject to strong noise and analyze composite fields to assess whether the bistability results from the hypothesized feedback mechanism. Because noise dominates the time series in most models, multiple circulation modes can unambiguously be detected in only six models. Four of these six models confirm that the intensification is caused by the positive feedback mechanism.

Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.

Hybrid stochastic simulations of intracellular reaction-diffusion systems.

With the observation that stochasticity is important in biological systems, chemical kinetics have begun to receive wider interest. While the use of Monte Carlo discrete event simulations most accurately capture the variability of molecular species, they become computationally costly for complex reaction-diffusion systems with large populations of molecules. On the other hand, continuous time models are computationally efficient but they fail to capture any variability in the molecular species. In this study a hybrid stochastic approach is introduced for simulating reaction-diffusion systems. We developed an adaptive partitioning strategy in which processes with high frequency are simulated with deterministic rate-based equations, and those with low frequency using the exact stochastic algorithm of Gillespie. Therefore the stochastic behavior of cellular pathways is preserved while being able to apply it to large populations of molecules. We describe our method and demonstrate its accuracy and efficiency compared with the Gillespie algorithm for two different systems. First, a model of intracellular viral kinetics with two steady states and second, a compartmental model of the postsynaptic spine head for studying the dynamics of Ca+2 and NMDA receptors.

The Value of Adding Optics to Ecosystem Models: A Case Study

Many ecosystem models have been developed to study the ocean's biogeochemical properties, but most of these models use simple formulations to describe light penetration and spectral quality. Here, an optical model is coupled with a previously published ecosystem model that explicitly represents two phytoplankton (picoplankton and diatoms) and two zooplankton functional groups, as well as multiple nutrients and detritus. Surface ocean color fields and subsurface light fields are calculated by coupling the ecosystem model with an optical model that relates biogeochemical standing stocks with inherent optical properties (absorption, scattering); this provides input to a commercially available radiative transfer model (Ecolight). We apply this bio-optical model to the equatorial Pacific upwelling region, and find the model to be capable of reproducing many measured optical properties and key biogeochemical processes in this region. Our model results suggest that non-algal particles largely contribute to the total scattering or attenuation (> 50% at 660 nm) but have a much smaller contribution to particulate absorption (< 20% at 440 nm), while picoplankton dominate the total phytoplankton absorption (> 95% at 440 nm). These results are consistent with the field observations. In order to achieve such good agreement between data and model results, however, key model parameters, for which no field data are available, have to be constrained. Sensitivity analysis of the model results to optical parameters reveals a significant role played by colored dissolved organic matter through its influence on the quantity and quality of the ambient light. Coupling explicit optics to an ecosystem model provides advantages in generating: (1) a more accurate subsurface light-field, which is important for light sensitive biogeochemical processes such as photosynthesis and photo-oxidation, (2) additional constraints on model parameters that help to reduce uncertainties in ecosystem model simulations, and (3) model output which is comparable to basic remotely-sensed properties. In addition, the coupling of biogeochemical models and optics paves the road for future assimilation of ocean color and in-situ measured optical properties into the models.

Search for resonant diboson production in the lvjj decay channels with the ATLAS detector at 7 TeV

A search for resonant diboson production using a data sample corresponding to 4.7 fb(-1) of integrated luminosity collected by the ATLAS experiment at the Large Hadron Collider in pp collisions at root s = 7 TeV is presented. The search for a narrow resonance in the WW or WZ mass distribution is conducted in a final state with an electron or a muon, missing transverse momentum, and at least two jets. No significant excess is observed and limits are set using three benchmark models: WW resonance masses below 940 and 710 GeV are excluded at 95% confidence level for spin-2 Randall-Sundrum and bulk Randall-Sundrum gravitons, respectively; WZ resonance masses below 950 GeV are excluded at 95% confidence level for a spin-1 extended gauge model W' boson.

Two-dimensional Lattice Gauge Theories with Superconducting Quantum Circuits

A quantum simulator of U(1) lattice gauge theories can be implemented with superconducting circuits. This allows the investigation of confined and deconfined phases in quantum link models, and of valence bond solid and spin liquid phases in quantum dimer models. Fractionalized confining strings and the real-time dynamics of quantum phase transitions are accessible as well. Here we show how state-of-the-art superconducting technology allows us to simulate these phenomena in relatively small circuit lattices. By exploiting the strong non-linear couplings between quantized excitations emerging when superconducting qubits are coupled, we show how to engineer gauge invariant Hamiltonians, including ring-exchange and four-body Ising interactions. We demonstrate that, despite decoherence and disorder effects, minimal circuit instances allow us to investigate properties such as the dynamics of electric flux strings, signaling confinement in gauge invariant field theories. The experimental realization of these models in larger superconducting circuits could address open questions beyond current computational capability.

O(N) Models with Topological Lattice Actions

A variety of lattice discretisations of continuum actions has been considered, usually requiring the correct classical continuum limit. Here we discuss “weird” lattice formulations without that property, namely lattice actions that are invariant under most continuous deformations of the field configuration, in one version even without any coupling constants. It turns out that universality is powerful enough to still provide the correct quantum continuum limit, despite the absence of a classical limit, or a perturbative expansion. We demonstrate this for a set of O(N) models (or non-linear σ-models). Amazingly, such “weird” lattice actions are not only in the right universality class, but some of them even have practical benefits, in particular an excellent scaling behaviour.

Towards quantum simulating QCD

Quantum link models provide an alternative non-perturbative formulation of Abelian and non-Abelian lattice gauge theories. They are ideally suited for quantum simulation, for example, using ultracold atoms in an optical lattice. This holds the promise to address currently unsolvable problems, such as the real-time and high-density dynamics of strongly interacting matter, first in toy-model gauge theories, and ultimately in QCD.

Loop formulation of supersymmetric Yang-Mills quantum mechanics

We derive the fermion loop formulation of N=4 supersymmetric SU(N) Yang-Mills quantum mechanics on the lattice. The loop formulation naturally separates the contributions to the partition function into its bosonic and fermionic parts with fixed fermion number and provides a way to control potential fermion sign problems arising in numerical simulations of the theory. Furthermore, we present a reduced fermion matrix determinant which allows the projection into the canonical sectors of the theory and hence constitutes an alternative approach to simulate the theory on the lattice.

Are We Sims? How Computer Simulations Represent and What this Means for the Simulation Argument

N. Bostrom’s simulation argument and two additional assumptions imply that we are likely to live in a computer simulation. The argument is based upon the following assumption about the workings of realistic brain simulations: The hardware of a computer on which a brain simulation is run bears a close analogy to the brain itself. To inquire whether this is so, I analyze how computer simulations trace processes in their targets. I describe simulations as fictional, mathematical, pictorial, and material models. Even though the computer hardware does provide a material model of the target, this does not suffice to underwrite the simulation argument because the ways in which parts of the computer hardware interact during simulations do not resemble the ways in which neurons interact in the brain. Further, there are computer simulations of all kinds of systems, and it would be unreasonable to infer that some computers display consciousness just because they simulate brains rather than, say, galaxies.

Supersymmetric quantum mechanics on the lattice: I. Loop formulation

Simulations of supersymmetric field theories on the lattice with (spontaneously) broken supersymmetry suffer from a fermion sign problem related to the vanishing of the Witten index. We propose a novel approach which solves this problem in low dimensions by formulating the path integral on the lattice in terms of fermion loops. For N=2 supersymmetric quantum mechanics the loop formulation becomes particularly simple and in this paper – the first in a series of three – we discuss in detail the reformulation of this model in terms of fermionic and bosonic bonds for various lattice discretisations including one which is Q-exact.

gems: An R Package for Simulating from Disease Progression Models

Mathematical models of disease progression predict disease outcomes and are useful epidemiological tools for planners and evaluators of health interventions. The R package gems is a tool that simulates disease progression in patients and predicts the effect of different interventions on patient outcome. Disease progression is represented by a series of events (e.g., diagnosis, treatment and death), displayed in a directed acyclic graph. The vertices correspond to disease states and the directed edges represent events. The package gems allows simulations based on a generalized multistate model that can be described by a directed acyclic graph with continuous transition-specific hazard functions. The user can specify an arbitrary hazard function and its parameters. The model includes parameter uncertainty, does not need to be a Markov model, and may take the history of previous events into account. Applications are not limited to the medical field and extend to other areas where multistate simulation is of interest. We provide a technical explanation of the multistate models used by gems, explain the functions of gems and their arguments, and show a sample application.