Improved Fast Randomized Iteration Approach to Full Configuration Interaction

We present three modifications to our recently introduced fast randomized iteration method for full configuration interaction (FCI-FRI) and investigate their effects on the method's performance for Ne, H$_2$O, and N$_2$. The initiator approximation, originally developed for full configuration interaction quantum Monte Carlo, significantly reduces statistical error in FCI-FRI when few samples are used in compression operations, enabling its application to larger chemical systems. The semi-stochastic extension, which involves exactly preserving a fixed subset of elements in each compression, improves statistical efficiency in some cases but reduces it in others. We also developed a new approach to sampling excitations that yields consistent improvements in statistical efficiency and reductions in computational cost. We discuss possible strategies based on our findings for improving the performance of stochastic quantum chemistry methods more generally.Comment: 13 pages, 5 figure

Approximating matrix eigenvalues by subspace iteration with repeated random sparsification

Traditional numerical methods for calculating matrix eigenvalues are prohibitively expensive for high-dimensional problems. Iterative random sparsification methods allow for the estimation of a single dominant eigenvalue at reduced cost by leveraging repeated random sampling and averaging. We present a general approach to extending such methods for the estimation of multiple eigenvalues and demonstrate its performance for several benchmark problems in quantum chemistry.Comment: 31 pages, 7 figure

A simulation model of river ice cover thermodynamics

A model of ice cover thermodynamics was used to simulate ice growth and decay along the international section of the St. Lawrence River for winter 1980-1981. This winter was chosen because of the exceptionally cold weather in December and January, and because of the abnormally warm air temperatures during the second half of February. At the air-ice interface, the model computes the surface energy transfer components and a resulting equilibrium surface temperature. At the lower boundary, an empirical algorith simulates the turbulent transfer of heat from the water. Within the ice, and implicit numerical solution to the general heat diffusion equation is used, permitting stable solutions for a variety of time intervals and node distances within the model. The model was used to simulate ice growth and decay at five sites characterized by their flow velocity, the date of ice-cover formation, and the water temperature regime. The model adequately represented growth rates at all five sites, but produced decay rates slower than those observed. Simulated breakup was 1-7 days later than observed, presumably because mechanical weakening of the ice was not taken into consideration. During the growth period, the model is far more sensitive to the values assigned to ice properties than it is to the error range in the meteorological variables. During the breakup period, the most sensitive boundary variable is water temperature.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/25721/1/0000278.pd

Beyond Walkers in Stochastic Quantum Chemistry: Reducing Error using Fast Randomized Iteration

We introduce a family of methods for the full configuration interaction problem in quantum chemistry, based on the fast randomized iteration (FRI) framework [L.-H. Lim and J. Weare, SIAM Rev. 59, 547 (2017)]. These methods, which we term "FCI-FRI," stochastically impose sparsity during iterations of the power method and can be viewed as a generalization of full configuration interaction quantum Monte Carlo (FCIQMC) without walkers. In addition to the multinomial scheme commonly used to sample excitations in FCIQMC, we present a systematic scheme where excitations are not sampled independently. Performing ground-state calculations on five small molecules at fixed cost, we find that the systematic FCI-FRI scheme is 11 to 45 times more statistically efficient than the multinomial FCI-FRI scheme, which is in turn 1.4 to 178 times more statistically efficient than the original FCIQMC algorithm.Comment: 19 pages, 7 figure

Fluorescence-Activated Cell Sorting of EGFP-Labeled Neural Crest Cells From Murine Embryonic Craniofacial Tissue

During the early stages of embryogenesis, pluripotent neural crest cells (NCC) are known to migrate from the neural folds to populate multiple target sites in the embryo where they differentiate into various derivatives, including cartilage, bone, connective tissue, melanocytes, glia, and neurons of the peripheral nervous system. The ability to obtain pure NCC populations is essential to enable molecular analyses of neural crest induction, migration, and/or differentiation. Crossing Wnt1-Cre and Z/EG transgenic mouse lines resulted in offspring in which the Wnt1-Cre transgene activated permanent EGFP expression only in NCC. The present report demonstrates a flow cytometric method to sort and isolate populations of EGFP-labeled NCC. The identity of the sorted neural crest cells was confirmed by assaying expression of known marker genes by TaqMan Quantitative Real-Time Polymerase Chain Reaction (QRT-PCR). The molecular strategy described in this report provides a means to extract intact RNA from a pure population of NCC thus enabling analysis of gene expression in a defined population of embryonic precursor cells critical to development

Utilizing logistic regression to compare risk factors in disease modeling with imbalanced data: a case study in vitamin D and cancer incidence

Imbalanced data, a common challenge encountered in statistical analyses of clinical trial datasets and disease modeling, refers to the scenario where one class significantly outnumbers the other in a binary classification problem. This imbalance can lead to biased model performance, favoring the majority class, and affecting the understanding of the relative importance of predictive variables. Despite its prevalence, the existing literature lacks comprehensive studies that elucidate methodologies to handle imbalanced data effectively. In this study, we discuss the binary logistic model and its limitations when dealing with imbalanced data, as model performance tends to be biased towards the majority class. We propose a novel approach to addressing imbalanced data and apply it to publicly available data from the VITAL trial, a large-scale clinical trial that examines the effects of vitamin D and Omega-3 fatty acid to investigate the relationship between vitamin D and cancer incidence in sub-populations based on race/ethnicity and demographic factors such as body mass index (BMI), age, and sex. Our results demonstrate a significant improvement in model performance after our undersampling method is applied to the data set with respect to cancer incidence prediction. Both epidemiological and laboratory studies have suggested that vitamin D may lower the occurrence and death rate of cancer, but inconsistent and conflicting findings have been reported due to the difficulty of conducting large-scale clinical trials. We also utilize logistic regression within each ethnic sub-population to determine the impact of demographic factors on cancer incidence, with a particular focus on the role of vitamin D. This study provides a framework for using classification models to understand relative variable importance when dealing with imbalanced data

Measurement of Branching Fraction and Dalitz Distribution for B0->D(*)+/- K0 pi-/+ Decays

We present measurements of the branching fractions for the three-body decays B0 -> D(*)-/+ K0 pi^+/-$and their resonant submodes$B0 -> D(*)-/+ K*+/- using a sample of approximately 88 million BBbar pairs collected by the BABAR detector at the PEP-II asymmetric energy storage ring. We measure: B(B0->D-/+ K0 pi+/-)=(4.9 +/- 0.7(stat) +/- 0.5 (syst)) 10^{-4} B(B0->D*-/+ K0 pi+/-)=(3.0 +/- 0.7(stat) +/- 0.3 (syst)) 10^{-4} B(B0->D-/+ K*+/-)=(4.6 +/- 0.6(stat) +/- 0.5 (syst)) 10^{-4} B(B0->D*-/+ K*+/-)=(3.2 +/- 0.6(stat) +/- 0.3 (syst)) 10^{-4} From these measurements we determine the fractions of resonant events to be : f(B0-> D-/+ K*+/-) = 0.63 +/- 0.08(stat) +/- 0.04(syst) f(B0-> D*-/+ K*+/-) = 0.72 +/- 0.14(stat) +/- 0.05(syst)Comment: 7 pages, 3 figures submitted to Phys. Rev. Let

Study of e+e- --> pi+ pi- pi0 process using initial state radiation with BABAR

The process e+e- --> pi+ pi- pi0 gamma has been studied at a center-of-mass energy near the Y(4S) resonance using a 89.3 fb-1 data sample collected with the BaBar detector at the PEP-II collider. From the measured 3pi mass spectrum we have obtained the products of branching fractions for the omega and phi mesons, B(omega --> e+e-)B(omega --> 3pi)=(6.70 +/- 0.06 +/- 0.27)10-5 and B(phi --> e+e-)B(phi --> 3pi)=(4.30 +/- 0.08 +/- 0.21)10-5, and evaluated the e+e- --> pi+ pi- pi0 cross section for the e+e- center-of-mass energy range 1.05 to 3.00 GeV. About 900 e+e- --> J/psi gamma --> pi+ pi- pi0 gamma events have been selected and the branching fraction B(J/psi --> pi+ pi- pi0)=(2.18 +/- 0.19)% has been measured.Comment: 21 pages, 37 postscript figues, submitted to Phys. Rev.