Multilevel blocking approach to the fermion sign problem in path-integral Monte Carlo simulations

A general algorithm toward the solution of the fermion sign problem in finite-temperature quantum Monte Carlo simulations has been formulated for discretized fermion path integrals with nearest-neighbor interactions in the Trotter direction. This multilevel approach systematically implements a simple blocking strategy in a recursive manner to synthesize the sign cancellations among different fermionic paths throughout the whole configuration space. The practical usefulness of the method is demonstrated for interacting electrons in a quantum dot.Comment: 4 pages RevTeX, incl. two figure

Distinguishing impurity concentrations in GaAs and AlGaAs, using very shallow undoped heterostructures

We demonstrate a method of making a very shallow, gateable, undoped 2-dimensional electron gas. We have developed a method of making very low resistivity contacts to these structures and systematically studied the evolution of the mobility as a function of the depth of the 2DEG (from 300nm to 30nm). We demonstrate a way of extracting quantitative information about the background impurity concentration in GaAs and AlGaAs, the interface roughness and the charge in the surface states from the data. This information is very useful from the perspective of molecular beam epitaxy (MBE) growth. It is difficult to fabricate such shallow high-mobility 2DEGs using modulation doping due to the need to have a large enough spacer layer to reduce scattering and switching noise from remote ionsied dopants.Comment: 4 pages, 5 eps figure

Time use and mental health in UK adults during an 11-week COVID-19 lockdown: a panel analysis

Background: There is currently major concern about the impact of the global COVID-19 outbreak on mental health. But it remains unclear how individual behaviours could exacerbate or protect against adverse changes in mental health. / Aims: To examine the associations between specific activities (or time use) and mental health and well-being among people during the COVID-19 pandemic. / Method: Data were from the UCL COVID-19 Social Study, a panel study collecting data weekly during the COVID-19 pandemic. The analytical sample consisted of 55 204 adults living in the UK who were followed up for the 11-week strict lockdown period from 21 March to 31 May 2020. Data were analysed using fixed-effects and Arellano–Bond models. / Results: Changes in time spent on a range of activities were associated with changes in mental health and well-being. After controlling for bidirectionality, behaviours involving outdoor activities such as gardening and exercising predicted subsequent improvements in mental health and well-being, whereas increased time spent following news about COVID-19 predicted declines in mental health and well-being. / Conclusions: These results are relevant to the formulation of guidance for people obliged to spend extended periods in isolation during health emergencies and may help the public to maintain well-being during future lockdowns and pandemics

Dynamical simulation of transport in one-dimensional quantum wires

Transport of single-channel spinless interacting fermions (Luttinger liquid) through a barrier has been studied by numerically exact quantum Monte Carlo methods. A novel stochastic integration over the real-time paths allows for direct computation of nonequilibrium conductance and noise properties. We have examined the low-temperature scaling of the conductance in the crossover region between a very weak and an almost insulating barrier.Comment: REVTex, 4 pages, 2 uuencoded figures (submitted to Phys. Rev. Lett.

Effect of next-nearest neighbor coupling on the optical spectra in bilayer graphene

We investigate the dependence of the optical conductivity of bilayer graphene (BLG) on the intra- and inter-layer interactions using the most complete model to date. We show that the next nearest-neighbor intralayer coupling introduces new features in the low-energy spectrum that are highly sensitive to sample doping, changing significantly the ``universal'' conductance. Further, its interplay with interlayer couplings leads to an anisotropy in conductance in the ultraviolet range. We propose that experimental measurement of the optical conductivity of intrinsic and doped BLG will provide a good benchmark for the relative importance of intra- and inter-layer couplings at different doping levels.Comment: 5 pages, 5 figure

Additive Multi-Index Gaussian process modeling, with application to multi-physics surrogate modeling of the quark-gluon plasma

The Quark-Gluon Plasma (QGP) is a unique phase of nuclear matter, theorized to have filled the Universe shortly after the Big Bang. A critical challenge in studying the QGP is that, to reconcile experimental observables with theoretical parameters, one requires many simulation runs of a complex physics model over a high-dimensional parameter space. Each run is computationally very expensive, requiring thousands of CPU hours, thus limiting physicists to only several hundred runs. Given limited training data for high-dimensional prediction, existing surrogate models often yield poor predictions with high predictive uncertainties, leading to imprecise scientific findings. To address this, we propose a new Additive Multi-Index Gaussian process (AdMIn-GP) model, which leverages a flexible additive structure on low-dimensional embeddings of the parameter space. This is guided by prior scientific knowledge that the QGP is dominated by multiple distinct physical phenomena (i.e., multiphysics), each involving a small number of latent parameters. The AdMIn-GP models for such embedded structures within a flexible Bayesian nonparametric framework, which facilitates efficient model fitting via a carefully constructed variational inference approach with inducing points. We show the effectiveness of the AdMIn-GP via a suite of numerical experiments and our QGP application, where we demonstrate considerably improved surrogate modeling performance over existing models

CVaR minimization by the SRA algorithm

Using the risk measure CV aR in �nancial analysis has become more and more popular recently. In this paper we apply CV aR for portfolio optimization. The problem is formulated as a two-stage stochastic programming model, and the SRA algorithm, a recently developed heuristic algorithm, is applied for minimizing CV aR

Crossover from Fermi liquid to Wigner molecule behavior in quantum dots

The crossover from weak to strong correlations in parabolic quantum dots at zero magnetic field is studied by numerically exact path-integral Monte Carlo simulations for up to eight electrons. By the use of a multilevel blocking algorithm, the simulations are carried out free of the fermion sign problem. We obtain a universal crossover only governed by the density parameter $r_s$. For $r_s>r_c$, the data are consistent with a Wigner molecule description, while for $r_s<r_c$, Fermi liquid behavior is recovered. The crossover value $r_c \approx 4$ is surprisingly small.Comment: 4 pages RevTeX, 3 figures, corrected Tabl