Minimising biases in Full Configuration Interaction Quantum Monte Carlo

We show that Full Configuration Interaction Quantum Monte Carlo (FCIQMC) is a Markov Chain in its present form. We construct the Markov matrix of FCIQMC for a two determinant system and hence compute the stationary distribution. These solutions are used to quantify the dependence of the population dynamics on the parameters defining the Markov chain. Despite the simplicity of a system with only two determinants, it still reveals a population control bias inherent to the FCIQMC algorithm. We investigate the effect of simulation parameters on the population control bias for the neon atom and suggest simulation setups to in general minimise the bias. We show a reweighting scheme to remove the bias caused by population control commonly used in Diffusion Monte Carlo [J. Chem. Phys. 99, 2865 (1993)] is effective and recommend its use as a post processing step.Comment: Supplementary material available as 'Ancillary Files

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 communicationComment: 6 pages. Submission to WSSSPE

The HANDE-QMC Project: Open-Source Stochastic Quantum Chemistry from the Ground State Up.

Building on the success of Quantum Monte Carlo techniques such as diffusion Monte Carlo, alternative stochastic approaches to solve electronic structure problems have emerged over the past decade. The full configuration interaction quantum Monte Carlo (FCIQMC) method allows one to systematically approach the exact solution of such problems, for cases where very high accuracy is desired. The introduction of FCIQMC has subsequently led to the development of coupled cluster Monte Carlo (CCMC) and density matrix quantum Monte Carlo (DMQMC), allowing stochastic sampling of the coupled cluster wave function and the exact thermal density matrix, respectively. In this Article, we describe the HANDE-QMC code, an open-source implementation of FCIQMC, CCMC and DMQMC, including initiator and semistochastic adaptations. We describe our code and demonstrate its use on three example systems; a molecule (nitric oxide), a model solid (the uniform electron gas), and a real solid (diamond). An illustrative tutorial is also included

Carcinoembryonic antigen is the preferred biomarker for in vivo colorectal cancer targeting.

BACKGROUND: Colorectal cancer-specific biomarkers have been used as molecular targets for fluorescent intra-operative imaging, targeted PET/MRI, and selective cytotoxic drug delivery yet the selection of biomarkers used is rarely evidence-based. We evaluated sensitivities and specificites of four of the most commonly used markers: carcinoembryonic antigen (CEA), tumour-associated glycoprotein-72 (TAG-72), folate receptor-α (FRα) and Epithelial growth factor receptor (EGFR). METHODS: Marker expression was evaluated semi-quantitatively in matched mucosal and colorectal cancer tissues from 280 patients using immunohistochemistry (scores of 0-15). Matched positive and negative lymph nodes from 18 patients were also examined. RESULTS: Markers were more highly expressed in tumour tissue than in matched normal tissue in 98.8%, 79.0%, 37.1% and 32.8% of cases for CEA, TAG-72, FRα and EGFR, respectively. Carcinoembryonic antigen showed the greatest differential expression, with tumours scoring a mean of 10.8 points higher than normal tissues (95% CI 10.31-11.21, P<0.001). Similarly, CEA showed the greatest differential expression between positive and negative lymph nodes. Receiver operating characteristic analyses showed CEA to have the best sensitivity (93.7%) and specificity (96.1%) for colorectal cancer detection. CONCLUSION: Carcinoembryonic antigen has the greatest potential to allow highly specific tumour imaging and drug delivery; future translational research should aim to exploit this

Understanding and Improving the Efficiency of Full Configuration Interaction Quantum Monte Carlo

Data and Python Scripts required to produce the figures in: Understanding and Improving the Efficiency of Full Configuration Interaction Quantum Monte Carlo http://arxiv.org/abs/1601.00865 Reanaylisis requires pyhande (part of the HANDE package) available from: https://github.com/hande-qmc/hande.git To reproduce the figures by reanalysing the data from scratch modify sys.path.append() in ./bin/Efficiency.py and in ./figure4/figure4.py. To point to hande_top_level_dir/tools.Data and Python Scripts required to produce the figures in: Understanding and Improving the Efficiency of Full Configuration Interaction Quantum Monte Carlo http://arxiv.org/abs/1601.00865 Reanaylisis requires pyhande (part of the HANDE package) available from: https://github.com/hande-qmc/hande.git To reproduce the figures by reanalysing the data from scratch modify sys.path.append() in ./bin/Efficiency.py and in ./figure4/figure4.py. To point to hande_top_level_dir/tools

The HANDE-QMC Project: Open-Source Stochastic Quantum Chemistry from the Ground State Up.

Building on the success of Quantum Monte Carlo techniques such as diffusion Monte Carlo, alternative stochastic approaches to solve electronic structure problems have emerged over the last decade. The full configuration interaction quantum Monte Carlo (FCIQMC) method allows one to systematically approach the exact solution of such problems, for cases where very high accuracy is desired. The introduction of FCIQMC has subsequently led to the development of coupled cluster Monte Carlo (CCMC) and density matrix quantum Monte Carlo (DMQMC), allowing stochastic sampling of the coupled cluster wave function and the exact thermal density matrix, respectively. In this article we describe the HANDE-QMC code, an open-source implementation of FCIQMC, CCMC and DMQMC, including initiator and semi-stochastic adaptations. We describe our code and demonstrate its use on three example systems; a molecule (nitric oxide), a model solid (the uniform electron gas), and a real solid (diamond). An illustrative tutorial is also included