Ehrenfest Modeling of Cavity Vacuum Fluctuations and How to Achieve Emission from a Three-Level Atom

A much-needed solution for the efficient modeling of strong coupling between matter and optical cavity modes is offered by mean-field mixed quantum--classical dynamics, where a classical cavity field interacts self-consistently with quantum states of matter through Ehrenfest's theorem. We previously introduced a modified mean-field approach, referred to as decoupled mean-field (DC-MF) dynamics, wherein vacuum fluctuations of the cavity field are decoupled from the quantum-mechanical ground state as a means to resolve an unphysical drawing of energy from the vacuum fluctuations by a two-level atom. Here, we generalize DC-MF dynamics for an arbitrary number of (nondegenerate) atomic levels, and show that it resolves an unphysical lack of emission from a three-level atom predicted by conventional mean-field dynamics. We furthermore show DC-MF to provide an improved description of reabsorption and two-photon emission processes.Comment: 5 pages, 3 figure

Army-NASA aircrew/aircraft integration program (A3I) software detailed design document, phase 3

The capabilities and design approach of the MIDAS (Man-machine Integration Design and Analysis System) computer-aided engineering (CAE) workstation under development by the Army-NASA Aircrew/Aircraft Integration Program is detailed. This workstation uses graphic, symbolic, and numeric prototyping tools and human performance models as part of an integrated design/analysis environment for crewstation human engineering. Developed incrementally, the requirements and design for Phase 3 (Dec. 1987 to Jun. 1989) are described. Software tools/models developed or significantly modified during this phase included: an interactive 3-D graphic cockpit design editor; multiple-perspective graphic views to observe simulation scenarios; symbolic methods to model the mission decomposition, equipment functions, pilot tasking and loading, as well as control the simulation; a 3-D dynamic anthropometric model; an intermachine communications package; and a training assessment component. These components were successfully used during Phase 3 to demonstrate the complex interactions and human engineering findings involved with a proposed cockpit communications design change in a simulated AH-64A Apache helicopter/mission that maps to empirical data from a similar study and AH-1 Cobra flight test

Theta oscillations promote temporal sequence learning.

Many theoretical models suggest that neural oscillations play a role in learning or retrieval of temporal sequences, but the extent to which oscillations support sequence representation remains unclear. To address this question, we used scalp electroencephalography (EEG) to examine oscillatory activity over learning of different object sequences. Participants made semantic decisions on each object as they were presented in a continuous stream. For three "Consistent" sequences, the order of the objects was always fixed. Activity during Consistent sequences was compared to "Random" sequences that consisted of the same objects presented in a different order on each repetition. Over the course of learning, participants made faster semantic decisions to objects in Consistent, as compared to objects in Random sequences. Thus, participants were able to use sequence knowledge to predict upcoming items in Consistent sequences. EEG analyses revealed decreased oscillatory power in the theta (4-7 Hz) band at frontal sites following decisions about objects in Consistent sequences, as compared with objects in Random sequences. The theta power difference between Consistent and Random only emerged in the second half of the task, as participants were more effectively able to predict items in Consistent sequences. Moreover, we found increases in parieto-occipital alpha (10-13 Hz) and beta (14-28 Hz) power during the pre-response period for objects in Consistent sequences, relative to objects in Random sequences. Linear mixed effects modeling revealed that single trial theta oscillations were related to reaction time for future objects in a sequence, whereas beta and alpha oscillations were only predictive of reaction time on the current trial. These results indicate that theta and alpha/beta activity preferentially relate to future and current events, respectively. More generally our findings highlight the importance of band-specific neural oscillations in the learning of temporal order information.This work was supported by a Vannevar Bush Fellowship (Office of Naval Research Grant N00014-15-1-0033) and a Multi-University Research Initiative Grant (Office of Naval Research Grant N00014-17-1-2961) from the Office of Naval Research

Effects of excluded volume and hydrodynamic interactions on the behavior of isolated bead‐rod polymer chains in shearing flow

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106769/1/aic14317.pd

Effective Robustness against Natural Distribution Shifts for Models with Different Training Data

"Effective robustness" measures the extra out-of-distribution (OOD) robustness beyond what can be predicted from the in-distribution (ID) performance. Existing effective robustness evaluations typically use a single test set such as ImageNet to evaluate the ID accuracy. This becomes problematic when evaluating models trained on different data distributions, e.g., comparing models trained on ImageNet vs. zero-shot language-image pre-trained models trained on LAION. In this paper, we propose a new evaluation metric to evaluate and compare the effective robustness of models trained on different data. To do this, we control for the accuracy on multiple ID test sets that cover the training distributions for all the evaluated models. Our new evaluation metric provides a better estimate of effective robustness when there are models with different training data. It may also explain the surprising effective robustness gains of zero-shot CLIP-like models exhibited in prior works that used ImageNet as the only ID test set, while the gains diminish under our new evaluation. Additional artifacts including interactive visualizations are provided at https://shizhouxing.github.io/effective-robustness.Comment: NeurIPS 202

PhenDisco: phenotype discovery system for the database of genotypes and phenotypes.

The database of genotypes and phenotypes (dbGaP) developed by the National Center for Biotechnology Information (NCBI) is a resource that contains information on various genome-wide association studies (GWAS) and is currently available via NCBI's dbGaP Entrez interface. The database is an important resource, providing GWAS data that can be used for new exploratory research or cross-study validation by authorized users. However, finding studies relevant to a particular phenotype of interest is challenging, as phenotype information is presented in a non-standardized way. To address this issue, we developed PhenDisco (phenotype discoverer), a new information retrieval system for dbGaP. PhenDisco consists of two main components: (1) text processing tools that standardize phenotype variables and study metadata, and (2) information retrieval tools that support queries from users and return ranked results. In a preliminary comparison involving 18 search scenarios, PhenDisco showed promising performance for both unranked and ranked search comparisons with dbGaP's search engine Entrez. The system can be accessed at http://pfindr.net

Atmospheric trace metal concentrations, solubility and deposition fluxes in remote marine air over the south-east Atlantic

Total and soluble trace metal concentrations were determined in atmospheric aerosol and rainwater samples collected during seven cruises in the south-east Atlantic. Back trajectories indicated the samples all represented remote marine air masses, consistent with climatological expectations. Aerosol trace metal loadings were similar to previous measurements in clean, marine air masses. Median total Fe, Al, Mn, V, Co and Zn concentrations were 206, 346, 5, 3, 0.7 and 11 pmol m-3 respectively. Solubility was operationally defined as the fraction extractable using a pH4.7 ammonium acetate leach. Median soluble Fe, Al, Mn, V, Co, Zn, Cu, Ni, Cd and Pb concentrations were 6, 55, 1, 0.7, 0.06, 24, 2, 1, 0.05 and 0.3 pmol m-3 respectively. Large ranges in fractional solubility were observed for all elements except Co; median solubility values for Fe, Al and Mn were below 20% while the median for Zn was 74%. Volume weighted mean rainwater concentrations were 704, 792, 32, 10, 3, 686, 25, 0.02, 0.3 and 10 nmol L-1 for Fe, Al, Mn, V, Co, Zn, Cu, Ni, Cd and Pb respectively (n = 6). Wet deposition fluxes calculated from these values suggest rain makes a significant contribution to total deposition in the study area for all elements except perhaps Ni