Variational quantum Monte Carlo simulations with tensor-network states

We show that the formalism of tensor-network states, such as the matrix product states (MPS), can be used as a basis for variational quantum Monte Carlo simulations. Using a stochastic optimization method, we demonstrate the potential of this approach by explicit MPS calculations for the transverse Ising chain with up to N=256 spins at criticality, using periodic boundary conditions and D*D matrices with D up to 48. The computational cost of our scheme formally scales as ND^3, whereas standard MPS approaches and the related density matrix renromalization group method scale as ND^5 and ND^6, respectively, for periodic systems.Comment: 4+ pages, 2 figures. v2: improved data, comparisons with exact results, to appear in Phys Rev Let

A simple interpretation of quantum mirages

In an interesting new experiment the electronic structure of a magnetic atom adsorbed on the surface of Cu(111), observed by STM, was projected into a remote location on the same surface. The purpose of the present paper is to interpret this experiment with a model Hamiltonian, using ellipses of the size of the experimental ones, containing about 2300 atoms. The charge distribution for the different wavefunctions is analyzed, in particular, for those with energy close to the Fermi energy of copper Ef. Some of them show two symmetric maxima located on the principal axis of the ellipse but not necessarily at the foci. If a Co atom is adsorbed at the site where the wavefunction with energy $E_F$ has a maximum and the interaction is small, the main effect of the adsorbed atom will be to split this particular wavefunction in two. The total charge density will remain the same but the local density of states will present a dip at Ef at any site where the charge density is large enough. We relate the presence of this dip to the observation of quantum mirages. Our interpretation suggests that other sites, apart from the foci of the ellipses, can be used for projecting atomic images and also indicates the conditions for other non magnetic adsorbates to produce mirages.Comment: 3 pages, 3 Fig

Systems approaches and algorithms for discovery of combinatorial therapies

Effective therapy of complex diseases requires control of highly non-linear complex networks that remain incompletely characterized. In particular, drug intervention can be seen as control of signaling in cellular networks. Identification of control parameters presents an extreme challenge due to the combinatorial explosion of control possibilities in combination therapy and to the incomplete knowledge of the systems biology of cells. In this review paper we describe the main current and proposed approaches to the design of combinatorial therapies, including the empirical methods used now by clinicians and alternative approaches suggested recently by several authors. New approaches for designing combinations arising from systems biology are described. We discuss in special detail the design of algorithms that identify optimal control parameters in cellular networks based on a quantitative characterization of control landscapes, maximizing utilization of incomplete knowledge of the state and structure of intracellular networks. The use of new technology for high-throughput measurements is key to these new approaches to combination therapy and essential for the characterization of control landscapes and implementation of the algorithms. Combinatorial optimization in medical therapy is also compared with the combinatorial optimization of engineering and materials science and similarities and differences are delineated.Comment: 25 page

The collateral damage of COVID-19 to cardiovascular services. A meta-Analysis

Aims: The effect of the COVID-19 pandemic on care and outcomes across non-COVID-19 cardiovascular (CV) diseases is unknown. A systematic review and meta-Analysis was performed to quantify the effect and investigate for variation by CV disease, geographic region, country income classification and the time course of the pandemic. Methods and results: From January 2019 to December 2021, Medline and Embase databases were searched for observational studies comparing a pandemic and pre-pandemic period with relation to CV disease hospitalisations, diagnostic and interventional procedures, outpatient consultations, and mortality. Observational data were synthesised by incidence rate ratios (IRR) and risk ratios (RR) for binary outcomes and weighted mean differences for continuous outcomes with 95% confidence intervals. The study was registered with PROSPERO (CRD42021265930). A total of 158 studies, covering 49 countries and 6 continents, were used for quantitative synthesis. Most studies (80%) reported information for high-income countries (HICs). Across all CV disease and geographies there were fewer hospitalisations, diagnostic and interventional procedures, and outpatient consultations during the pandemic. By meta-regression, in low-middle income countries (LMICs) compared to HICs the decline in ST-segment elevation myocardial infarction (STEMI) hospitalisations (RR 0.79, 95% confidence interval [CI] 0.66-0.94) and revascularisation (RR 0.73, 95% CI 0.62-0.87) was more severe. In LMICs, but not HICs, in-hospital mortality increased for STEMI (RR 1.22, 95% CI 1.10-1.37) and heart failure (RR 1.08, 95% CI 1.04-1.12). The magnitude of decline in hospitalisations for CV diseases did not differ between the first and second wave. Conclusions: There was substantial global collateral CV damage during the COVID-19 pandemic with disparity in severity by country income classification

Convex optimization of programmable quantum computers

A fundamental model of quantum computation is the programmable quantum gate array. This is a quantum processor that is fed by a program state that induces a corresponding quantum operation on input states. While being programmable, any finite-dimensional design of this model is known to be non-universal, meaning that the processor cannot perfectly simulate an arbitrary quantum channel over the input. Characterizing how close the simulation is and finding the optimal program state have been open questions for the past 20 years. Here, we answer these questions by showing that the search for the optimal program state is a convex optimization problem that can be solved via semi-definite programming and gradient-based methods commonly employed for machine learning. We apply this general result to different types of processors, from a shallow design based on quantum teleportation, to deeper schemes relying on port-based teleportation and parametric quantum circuits

Response of ocean ecosystems to climate warming

Author Posting. © American Geophysical Union, 2004. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 18 (2004): GB3003, doi:10.1029/2003GB002134.We examine six different coupled climate model simulations to determine the ocean biological response to climate warming between the beginning of the industrial revolution and 2050. We use vertical velocity, maximum winter mixed layer depth, and sea ice cover to define six biomes. Climate warming leads to a contraction of the highly productive marginal sea ice biome by 42% in the Northern Hemisphere and 17% in the Southern Hemisphere, and leads to an expansion of the low productivity permanently stratified subtropical gyre biome by 4.0% in the Northern Hemisphere and 9.4% in the Southern Hemisphere. In between these, the subpolar gyre biome expands by 16% in the Northern Hemisphere and 7% in the Southern Hemisphere, and the seasonally stratified subtropical gyre contracts by 11% in both hemispheres. The low-latitude (mostly coastal) upwelling biome area changes only modestly. Vertical stratification increases, which would be expected to decrease nutrient supply everywhere, but increase the growing season length in high latitudes. We use satellite ocean color and climatological observations to develop an empirical model for predicting chlorophyll from the physical properties of the global warming simulations. Four features stand out in the response to global warming: (1) a drop in chlorophyll in the North Pacific due primarily to retreat of the marginal sea ice biome, (2) a tendency toward an increase in chlorophyll in the North Atlantic due to a complex combination of factors, (3) an increase in chlorophyll in the Southern Ocean due primarily to the retreat of and changes at the northern boundary of the marginal sea ice zone, and (4) a tendency toward a decrease in chlorophyll adjacent to the Antarctic continent due primarily to freshening within the marginal sea ice zone. We use three different primary production algorithms to estimate the response of primary production to climate warming based on our estimated chlorophyll concentrations. The three algorithms give a global increase in primary production of 0.7% at the low end to 8.1% at the high end, with very large regional differences. The main cause of both the response to warming and the variation between algorithms is the temperature sensitivity of the primary production algorithms. We also show results for the period between the industrial revolution and 2050 and 2090.J. L. Sarmiento and R. Slater were supported by the NOAA Office of Global Programs grant NA56GP0439 to the Carbon Modeling Consortium for model development and by NSF grant OCE00973166 for model and observational interpretations as part of the JGOFS Synthesis and Modeling Project. R. Barber was supported by NSF grant OCE 0136270 as part of the JGOFS Synthesis and Modeling Project. S. Doney and J. Kleypas wish to thank the Community Climate System Model science team and the Climate Simulation Laboratory at NCAR and acknowledge support from NOAA-OGP grant NOAA-NA96GP0360S. Spall is funded through the UK Department for Environment, Food and Rural Affairs contract PECD 7/12/37

Economic evaluation of prescribing conventional and newer oral anticoagulants in older adults.

INTRODUCTION: Anticoagulants refer to a variety of agents that inhibit one or more steps in the coagulation cascade. Generally, clinical conditions that require the prescribing of an oral anticoagulant increase in frequency with age. However, a major challenge of anticoagulation use among older patients is that this group of patients also experience the highest bleeding risk. To date, economic evaluation of prescribing of anticoagulants that includes the novel or newer oral anticoagulants (NOACs) in older adults has not been conducted and is warranted. Areas covered: A review of articles that evaluated the cost of prescribing conventional (e.g. vitamin K antagonists) and NOACs (e.g. direct thrombin inhibitors and direct factor Xa inhibitors) in older adults. Expert commentary: While the use of NOACs significantly increases the cost of the initial treatment for thromboembolic disorders, they are still considered cost-effective relative to warfarin since they offer reduced risk of intracranial haemorrhagic events. The optimum anticoagulation with warfarin can be achieved by providing specialised care; clinics managed by pharmacists have been shown to be cost-effective relative to usual care. There are suggestions that genotyping the CYP2C9 and VKORC1 genes is useful for determining a more appropriate initial dose and thereby increasing the effectiveness and safety of warfarin