Lippmann-Schwinger description of multiphoton ionization

We outline a formalism and develop a computational procedure to treat the process of multiphoton ionization (MPI) of atomic targets in strong laser fields. We treat the MPI process nonperturbatively as a decay phenomenon by solving a coupled set of the integral Lippmann-Schwinger equations. As basic building blocks of the theory we use a complete set of field-free atomic states, discrete and continuous. This approach should enable us to provide both the total and differential cross-sections of MPI of atoms with one or two electrons. As an illustration, we apply the proposed procedure to a simple model of MPI from a square well potential and to the hydrogen atom.Comment: 25 pages, 3 figure

Extensive variation in synonymous substitution rates in mitochondrial genes of seed plants

<p>Abstract</p> <p>Background</p> <p>It has long been known that rates of synonymous substitutions are unusually low in mitochondrial genes of flowering and other land plants. Although two dramatic exceptions to this pattern have recently been reported, it is unclear how often major increases in substitution rates occur during plant mitochondrial evolution and what the overall magnitude of substitution rate variation is across plants.</p> <p>Results</p> <p>A broad survey was undertaken to evaluate synonymous substitution rates in mitochondrial genes of angiosperms and gymnosperms. Although most taxa conform to the generality that plant mitochondrial sequences evolve slowly, additional cases of highly accelerated rates were found. We explore in detail one of these new cases, within the genus <it>Silene</it>. A roughly 100-fold increase in synonymous substitution rate is estimated to have taken place within the last 5 million years and involves only one of ten species of <it>Silene </it>sampled in this study. Examples of unusually slow sequence evolution were also identified. Comparison of the fastest and slowest lineages shows that synonymous substitution rates vary by four orders of magnitude across seed plants. In other words, some plant mitochondrial lineages accumulate more synonymous change in 10,000 years than do others in 100 million years. Several perplexing cases of gene-to-gene variation in sequence divergence within a plant were uncovered. Some of these probably reflect interesting biological phenomena, such as horizontal gene transfer, mitochondrial-to-nucleus transfer, and intragenomic variation in mitochondrial substitution rates, whereas others are likely the result of various kinds of errors.</p> <p>Conclusion</p> <p>The extremes of synonymous substitution rates measured here constitute by far the largest known range of rate variation for any group of organisms. These results highlight the utility of examining absolute substitution rates in a phylogenetic context rather than by traditional pairwise methods. Why substitution rates are generally so low in plant mitochondrial genomes yet occasionally increase dramatically remains mysterious.</p

Cavity-enabled high-dimensional quantum key distribution

High-dimensional quantum key distribution (QKD) offers the possibility of encoding multiple bits of key on a single entangled photon pair. An experimentally promising approach to realizing this is to use energy–time entanglement. Currently, however, the control of very high-dimensional entangled photons is challenging. We present a simple and experimentally compact approach, which is based on a cavity that allows one to measure two different bases: the time of arrival and another that is approximately mutually unbiased to the arrival time. We quantify the errors in the setup, due both to the approximate nature of the mutually unbiased measurement and as a result of experimental errors. It is shown that the protocol can be adapted using a cut-off so that it is robust against the considered errors, even within the regime of up to 10 bits per photon pair

Efficient generation of single and entangled photons on a silicon photonic integrated chip

We present a protocol for generating on-demand, indistinguishable single photons on a silicon photonic integrated chip. The source is a time-multiplexed spontaneous parametric down-conversion element that allows optimization of single-photon versus multiphoton emission while realizing high output rate and indistinguishability. We minimize both the scaling of active elements and the scaling of active element loss with multiplexing. We then discuss detection strategies and data processing to further optimize the procedure. We simulate an improvement in single-photon-generation efficiency over previous time-multiplexing protocols, assuming existing fabrication capabilities. We then apply this system to generate heralded Bell states. The generation efficiency of both nonclassical states could be increased substantially with improved fabrication procedures.Comment: 7 pages, 4 figure

Microwave Gaseous Discharges

Contains reports on five research projects.United States Atomic Energy Commission (Contract AT (30-1) 1842

Snow water equivalent retrieval over Idaho – Part 2: Using L-band UAVSAR repeat-pass interferometry

This study evaluates using interferometry on low-frequency synthetic aperture radar (SAR) images to monitor snow water equivalent (SWE) over seasonal and synoptic scales. We retrieved SWE changes from nine pairs of SAR images, mean 8 d temporal baseline, captured by an L-band aerial platform, NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), over central Idaho as part of the NASA SnowEx 2020 and 2021 campaigns. The retrieved SWE changes were compared against coincident in situ measurements (SNOTEL and snow pits from the SnowEx field campaign) and to 100 m gridded SnowModel modeled SWE changes. The comparison of in situ to retrieved measurements shows a strong Pearson correlation (R=0.80) and low RMSE (0.1 m, n=64) for snow depth change and similar results for SWE change (RMSE = 0.04 m, R=0.52, n=57). The comparison between retrieved SWE changes to SnowModel SWE change also showed good correlation (R=0.60, RMSD = 0.023 m, n=3.2×106) and especially high correlation for a subset of pixels with no modeled melt and low tree coverage (R=0.72, RMSD = 0.013 m, n=6.5×104). Finally, we bin the retrievals for a variety of factors and show decreasing correlation between the modeled and retrieved values for lower elevations, higher incidence angles, higher tree percentages and heights, and greater cumulative melt. This study builds on previous interferometry work by using a full winter season time series of L-band SAR images over a large spatial extent to evaluate the accuracy of SWE change retrievals against both in situ and modeled results and the controlling factors of the retrieval accuracy.</p

Deep Reinforcement Learning Based System for Intraoperative Hyperspectral Video Autofocusing

Hyperspectral imaging (HSI) captures a greater level of spectral detail than traditional optical imaging, making it a potentially valuable intraoperative tool when precise tissue differentiation is essential. Hardware limitations of current optical systems used for handheld real-time video HSI result in a limited focal depth, thereby posing usability issues for integration of the technology into the operating room. This work integrates a focus-tunable liquid lens into a video HSI exoscope, and proposes novel video autofocusing methods based on deep reinforcement learning. A first-of-its-kind robotic focal-time scan was performed to create a realistic and reproducible testing dataset. We benchmarked our proposed autofocus algorithm against traditional policies, and found our novel approach to perform significantly ($p<0.05$) better than traditional techniques ($0.070\pm.098$ mean absolute focal error compared to $0.146\pm.148$). In addition, we performed a blinded usability trial by having two neurosurgeons compare the system with different autofocus policies, and found our novel approach to be the most favourable, making our system a desirable addition for intraoperative HSI.Comment: To be presented at MICCAI 202

Genetic algorithm learning as a robust approach to RNA editing site prediction

BACKGROUND: RNA editing is one of several post-transcriptional modifications that may contribute to organismal complexity in the face of limited gene complement in a genome. One form, known as C → U editing, appears to exist in a wide range of organisms, but most instances of this form of RNA editing have been discovered serendipitously. With the large amount of genomic and transcriptomic data now available, a computational analysis could provide a more rapid means of identifying novel sites of C → U RNA editing. Previous efforts have had some success but also some limitations. We present a computational method for identifying C → U RNA editing sites in genomic sequences that is both robust and generalizable. We evaluate its potential use on the best data set available for these purposes: C → U editing sites in plant mitochondrial genomes. RESULTS: Our method is derived from a machine learning approach known as a genetic algorithm. REGAL (RNA Editing site prediction by Genetic Algorithm Learning) is 87% accurate when tested on three mitochondrial genomes, with an overall sensitivity of 82% and an overall specificity of 91%. REGAL's performance significantly improves on other ab initio approaches to predicting RNA editing sites in this data set. REGAL has a comparable sensitivity and higher specificity than approaches which rely on sequence homology, and it has the advantage that strong sequence conservation is not required for reliable prediction of edit sites. CONCLUSION: Our results suggest that ab initio methods can generate robust classifiers of putative edit sites, and we highlight the value of combinatorial approaches as embodied by genetic algorithms. We present REGAL as one approach with the potential to be generalized to other organisms exhibiting C → U RNA editing

Effective toughness of heterogeneous brittle materials

A heterogeneous brittle material characterized by a random field of local toughness Kc(x) can be represented by an equivalent homogeneous medium of toughness, Keff. Homogenization refers to a process of estimating Keff from the local field Kc(x). An approach based on a perturbative expansion of the stress intensity factor along a rough crack front shows the occurrence of different regimes depending on the correlation length of the local toughness field in the direction of crack propagation. A `"weak pinning" regime takes place for long correlation lengths, where the effective toughness is the average of the local toughness. For shorter correlation lengths, a transition to "strong pinning" occurs leading to a much higher effective toughness, and characterized by a propagation regime consisting in jumps between pinning configurations

Microwave Gaseous Disharges

Contains reports on seven research projects.Atomic Energy Commission under Contract AT(30-1)184