An excited-state approach within full configuration interaction quantum Monte Carlo.

We present a new approach to calculate excited states with the full configuration interaction quantum Monte Carlo (FCIQMC) method. The approach uses a Gram-Schmidt procedure, instantaneously applied to the stochastically evolving distributions of walkers, to orthogonalize higher energy states against lower energy ones. It can thus be used to study several of the lowest-energy states of a system within the same symmetry. This additional step is particularly simple and computationally inexpensive, requiring only a small change to the underlying FCIQMC algorithm. No trial wave functions or partitioning of the space is needed. The approach should allow excited states to be studied for systems similar to those accessible to the ground-state method due to a comparable computational cost. As a first application, we consider the carbon dimer in basis sets up to quadruple-zeta quality and compare to existing results where available.N.S.B. gratefully acknowledges Trinity College, Cambridge for funding. G.H.B. gratefully acknowledges the Royal Society for funding via a university research fellowship. This work has been supported by the EPSRC under grant no. EP/J003867/1.This is the accepted manuscript. The final version is available at http://scitation.aip.org/content/aip/journal/jcp/143/13/10.1063/1.4932595

Semi-stochastic full configuration interaction quantum Monte Carlo: Developments and application.

We expand upon the recent semi-stochastic adaptation to full configuration interaction quantum Monte Carlo (FCIQMC). We present an alternate method for generating the deterministic space without a priori knowledge of the wave function and present stochastic efficiencies for a variety of both molecular and lattice systems. The algorithmic details of an efficient semi-stochastic implementation are presented, with particular consideration given to the effect that the adaptation has on parallel performance in FCIQMC. We further demonstrate the benefit for calculation of reduced density matrices in FCIQMC through replica sampling, where the semi-stochastic adaptation seems to have even larger efficiency gains. We then combine these ideas to produce explicitly correlated corrected FCIQMC energies for the beryllium dimer, for which stochastic errors on the order of wavenumber accuracy are achievable.N.S.B. gratefully acknowledges Trinity College, Cambridge for funding. J.S.S. acknowledges the research environment provided by the Thomas Young Centre under Grant No. TYC-101. G.H.B. gratefully acknowledges the Royal Society for a university research fellowship. This work has been supported by the EPSRC under grant no. EP/J003867/1.This is the author accepted manuscript. The final version is available from AIP at http://scitation.aip.org/content/aip/journal/jcp/142/18/10.1063/1.4920975

Unbiased reduced density matrices and electronic properties from full configuration interaction quantum Monte Carlo.

Properties that are necessarily formulated within pure (symmetric) expectation values are difficult to calculate for projector quantum Monte Carlo approaches, but are critical in order to compute many of the important observable properties of electronic systems. Here, we investigate an approach for the sampling of unbiased reduced density matrices within the full configuration interaction quantum Monte Carlo dynamic, which requires only small computational overheads. This is achieved via an independent replica population of walkers in the dynamic, sampled alongside the original population. The resulting reduced density matrices are free from systematic error (beyond those present via constraints on the dynamic itself) and can be used to compute a variety of expectation values and properties, with rapid convergence to an exact limit. A quasi-variational energy estimate derived from these density matrices is proposed as an accurate alternative to the projected estimator for multiconfigurational wavefunctions, while its variational property could potentially lend itself to accurate extrapolation approaches in larger systems

Cellular Radiosensitivity: How much better do we understand it?

Purpose: Ionizing radiation exposure gives rise to a variety of lesions in DNA that result in genetic instability and potentially tumorigenesis or cell death. Radiation extends its effects on DNA by direct interaction or by radiolysis of H2O that generates free radicals or aqueous electrons capable of interacting with and causing indirect damage to DNA. While the various lesions arising in DNA after radiation exposure can contribute to the mutagenising effects of this agent, the potentially most damaging lesion is the DNA double strand break (DSB) that contributes to genome instability and/or cell death. Thus in many cases failure to recognise and/or repair this lesion determines the radiosensitivity status of the cell. DNA repair mechanisms including homologous recombination (HR) and non-homologous end-joining (NHEJ) have evolved to protect cells against DNA DSB. Mutations in proteins that constitute these repair pathways are characterised by radiosensitivity and genome instability. Defects in a number of these proteins also give rise to genetic disorders that feature not only genetic instability but also immunodeficiency, cancer predisposition, neurodegeneration and other pathologies. Conclusions: In the past fifty years our understanding of the cellular response to radiation damage has advanced enormously with insight being gained from a wide range of approaches extending from more basic early studies to the sophisticated approaches used today. In this review we discuss our current understanding of the impact of radiation on the cell and the organism gained from the array of past and present studies and attempt to provide an explanation for what it is that determines the response to radiation

Patterns of Chemical Diversity in the Mediterranean Sponge Spongia lamella

The intra-specific diversity in secondary metabolites can provide crucial information for understanding species ecology and evolution but has received limited attention in marine chemical ecology. The complex nature of diversity is partially responsible for the lack of studies, which often target a narrow number of major compounds. Here, we investigated the intra-specific chemical diversity of the Mediterranean sponge Spongia lamella. The chemical profiles of seven populations spreading over 1200 km in the Western Mediterranean were obtained by a straightforward SPE-HPLC-DAD-ELSD process whereas the identity of compounds was assessed by comparison between HPLC-MS spectra and literature data. Chemical diversity calculated by richness and Shannon indexes differed significantly between sponge populations but not at a larger regional scale. We used factor analysis, analysis of variance, and regression analysis to examine the chemical variability of this sponge at local and regional scales, to establish general patterns of variation in chemical diversity. The abundance of some metabolites varied significantly between sponge populations. Despite these significant differences between populations, we found a clear pattern of increasing chemical dissimilarity with increasing geographic distance. Additional large spatial scale studies on the chemical diversity of marine organisms will validate the universality or exclusivity of this pattern

Secondary Metabolites of Marine Microbes: From Natural Products Chemistry to Chemical Ecology

Marine natural products (MNPs) exhibit a wide range of pharmaceutically relevant bioactivities, including antibiotic, antiviral, anticancer, or anti-inflammatory properties. Besides marine macroorganisms such as sponges, algae, or corals, specifically marine bacteria and fungi have shown to produce novel secondary metabolites (SMs) with unique and diverse chemical structures that may hold the key for the development of novel drugs or drug leads. Apart from highlighting their potential benefit to humankind, this review is focusing on the manifold functions of SMs in the marine ecosystem. For example, potent MNPs have the ability to exile predators and competing organisms, act as attractants for mating purposes, or serve as dye for the expulsion or attraction of other organisms. A large compilation of literature on the role of MNPs in marine ecology is available, and several reviews evaluated the function of MNPs for the aforementioned topics. Therefore, we focused the second part of this review on the importance of bioactive compounds from crustose coralline algae (CCA) and their role during coral settlement, a topic that has received less attention. It has been shown that certain SMs derived from CCA and their associated bacteria are able to induce attachment and/or metamorphosis of many benthic invertebrate larvae, including globally threatened reef-building scleractinian corals. This review provides an overview on bioactivities of MNPs from marine microbes and their potential use in medicine as well as on the latest findings of the chemical ecology and settlement process of scleractinian corals and other invertebrate larvae

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Open-Source Development Experiences in Scientific Software: The HANDE Quantum Monte Carlo Project

The HANDE quantum Monte Carlo project offers accessible stochastic algorithms for general use for scientists in the field of quantum chemistry. HANDE is an ambitious and general high-performance code developed by a geographically-dispersed team with a variety of backgrounds in computational science. In the course of preparing a public, open-source release, we have taken this opportunity to step back and look at what we have done and what we hope to do in the future. We pay particular attention to development processes, the approach taken to train students joining the project, and how a flat hierarchical structure aids communicatio

Krylov-Projected Quantum Monte Carlo Method.

We present an approach to the calculation of arbitrary spectral, thermal, and excited state properties within the full configuration interaction quzantum Monte Carlo framework. This is achieved via an unbiased projection of the Hamiltonian eigenvalue problem into a space of stochastically sampled Krylov vectors, thus, enabling the calculation of real-frequency spectral and thermal properties and avoiding explicit analytic continuation. We use this approach to calculate temperature-dependent properties and one- and two-body spectral functions for various Hubbard models, as well as isolated excited states in ab initio systems.G.H.B gratefully acknowledges funding from the Royal Society. N.S.B acknowledges Trinity College, Cambridge for funding. This work has been supported by the EPSRC under grant no. EP/J003867/1.This is the author accepted manuscript. The final version is available from APS at http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.115.050603

Density-matrix quantum Monte Carlo method

We present a quantum Monte Carlo method capable of sampling the full density matrix of a many-particle system at finite temperature. This allows arbitrary reduced density matrix elements and expectation values of complicated nonlocal observables to be evaluated easily. The method resembles full configuration interaction quantum Monte Carlo but works in the space of many-particle operators instead of the space of many-particle wave functions. One simulation provides the density matrix at all temperatures simultaneously, from T = ∞ to T = 0 , allowing the temperature dependence of expectation values to be studied. The direct sampling of the density matrix also allows the calculation of some previously inaccessible entanglement measures. We explain the theory underlying the method, describe the algorithm, and introduce an importance-sampling procedure to improve the stochastic efficiency. To demonstrate the potential of our approach, the energy and staggered magnetization of the isotropic antiferromagnetic Heisenberg model on small lattices, the concurrence of one-dimensional spin rings, and the Renyi S 2 entanglement entropy of various sublattices of the 6 × 6 Heisenberg model are calculated. The nature of the sign problem in the method is also investigated