Application of a Novel Nd:YAG/PPMgLN Laser Module Speckle-Suppressed by Multi-Mode Fibers in an Exhibition Environment

Laser exhibition technology has been widely used in the virtual environment of exhibitions and shows, as well as in the physical conference and exhibition centers. However, the speckle issue due to the high coherence of laser sources has caused harmful impacts on image quality, which is one of the obstacles to exhibition effects. In this paper, we design a compact Nd:YAG/PPMgLN laser module at 561.5 nm and use two different types of big-core multi-mode fibers to lower the spatial coherence. According to our experiment, the speckle contrasts relating to these two types reduce to 7.9% and 4.1%, respectively. The results of this paper contribute to improving the application effects of key optical components in the exhibitions. Only in this way can we provide technical supports and service guarantee for the development of the exhibition activities, and an immersive interactive experience for the audiences.

Enhancing Coherence Images for Coherent Change Detection: An Example on Vehicle Tracks in Airborne SAR Images

In Synthetic Aperture Radar (SAR) interferometry, one of the most widely used measures for the quality of the interferometric phase is coherence. However, in favorable conditions coherence can also be used to detect subtle changes on the ground, which are not visible in the amplitude images. For such applications, i.e., coherent change detection, it is important to have a good contrast between the unchanged (high-coherence) parts of the scene and the changed (low-coherence) parts. In this paper, an algorithm is introduced that aims at enhancing this contrast. The enhancement is achieved by a combination of careful filtering of the amplitude images and the interferometric phase image. The algorithm is applied to an airborne interferometric SAR image pair recorded by the SmartRadar experimental sensor of Hensoldt Sensors GmbH. The data were recorded during a measurement campaign over the Bann B installations of POLYGONE Range in southern Rhineland-Palatinate (Germany), with a time gap of approximately four hours between the overflights. In-between the overflights, several vehicles were moved on the site and the goal of this work is to enhance the coherence image such that the tracks of these vehicles can be detected as completely as possible in an automated way. Several coherence estimation schemes found in the literature are explored for the enhancement, as well as several commonly used speckle filters. The results of these filtering steps are evaluated visually and quantitatively, showing that the mean gray-level difference between the low-coherence tracks and their high-coherence surroundings could be enhanced by at least 28%. Line extraction is then applied to the best enhancement. The results show that the tracks can be detected much more completely using the coherence contrast enhancement scheme proposed in this paper.

Structural transformation trajectories: Evidence from successful exporting countries

This paper identifies and examines several success criteria for the structural transformation of exports. Some detailed facts for the leading countries in structural transformation are presented, and the paper is the first in social sciences literature to calculate the Fréchet distances between the structural transformation trajectories according to various criteria. The paper introduces the concept of structural transformation trajectory that is defined as the path in the two coordinates — per capita income and one of the success criteria for the structural transformation of exports. Based on the brief review of the literature, four criteria for the empirical research are selected: (i) an increase in the ratio of exports of capital to consumer products, (ii) an enhancement of the export share of high-tech products, (iii) a decrease in export concentration, and (iv) an expansion of export complexity. In most cases, countries leading structural transformation succeed due to a limited number of specific factors, such as foreign direct investment in a limited number of sectors, participation in the assembly of telecom products, automobiles or similar consumer products, and re-export of products from other countries. However, high per capita income growth rates are typically observed in countries with high coherence of the success criteria for the structural transformation of exports, that is, in countries that made progress on a whole range of criteria.

Structural transformation trajectories: Evidence from successful exporting countries

This paper identifies and examines several success criteria for the structural transformation of exports. Some detailed facts for the leading countries in structural transformation are presented, and the paper is the first in social sciences literature to calculate the Fréchet distances between the structural transformation trajectories according to various criteria. The paper introduces the concept of structural transformation trajectory that is defined as the path in the two coordinates — per capita income and one of the success criteria for the structural transformation of exports. Based on the brief review of the literature, four criteria for the empirical research are selected: (i) an increase in the ratio of exports of capital to consumer products, (ii) an enhancement of the export share of high-tech products, (iii) a decrease in export concentration, and (iv) an expansion of export complexity. In most cases, countries leading structural transformation succeed due to a limited number of specific factors, such as foreign direct investment in a limited number of sectors, participation in the assembly of telecom products, automobiles or similar consumer products, and re-export of products from other countries. However, high per capita income growth rates are typically observed in countries with high coherence of the success criteria for the structural transformation of exports, that is, in countries that made progress on a whole range of criteria.

Epidemiological associations with genomic variation in SARS-CoV-2

SARS-CoV-2 (CoV) is the etiological agent of the COVID-19 pandemic and evolves to evade both host immune systems and intervention strategies. We divided the CoV genome into 29 constituent regions and applied novel analytical approaches to identify associations between CoV genomic features and epidemiological metadata. Our results show that nonstructural protein 3 (nsp3) and Spike protein (S) have the highest variation and greatest correlation with the viral whole-genome variation. S protein variation is correlated with nsp3, nsp6, and 3′-to-5′ exonuclease variation. Country of origin and time since the start of the pandemic were the most influential metadata associated with genomic variation, while host sex and age were the least influential. We define a novel statistic—coherence—and show its utility in identifying geographic regions (populations) with unusually high (many new variants) or low (isolated) viral phylogenetic diversity. Interestingly, at both global and regional scales, we identify geographic locations with high coherence neighboring regions of low coherence; this emphasizes the utility of this metric to inform public health measures for disease spread. Our results provide a direction to prioritize genes associated with outcome predictors (e.g., health, therapeutic, and vaccine outcomes) and to improve DNA tests for predicting disease status.

Miniaturizing transmon qubits using van der Waals materials

Quantum computers can potentially achieve an exponential speedup versus classical computers on certain computational tasks, recently demonstrated in systems of superconducting qubits. However, the capacitor electrodes that comprise these qubits must be large in order to avoid lossy dielectrics. This tactic hinders scaling by increasing parasitic coupling among circuit components, degrading individual qubit addressability, and limiting the spatial density of qubits. Here, we take advantage of the unique properties of van der Waals (vdW) materials to reduce the qubit area by $>1000$ times while preserving the required capacitance without increasing substantial loss. Our qubits combine conventional aluminum-based Josephson junctions with parallel-plate capacitors composed of crystalline layers of superconducting niobium diselenide and insulating hexagonal-boron nitride. We measure a vdW transmon $T_1$ relaxation time of 1.06 $\mu$s, which demonstrates a path to achieve high-qubit-density quantum processors with long coherence times, and the broad utility of layered heterostructures in low-loss, high-coherence quantum devices.

Proposal for a continuous wave laser with linewidth well below the standard quantum limit

Due to their high coherence, lasers are ubiquitous tools in science. We show that by engineering the coupling between the gain medium and the laser cavity as well as the laser cavity and the output port, it is possible to eliminate most of the noise due to photons entering as well as leaving the laser cavity. Hence, it is possible to reduce the laser linewidth by a factor equal to the number of photons in the laser cavity below the standard quantum limit. We design and theoretically analyze a superconducting circuit that uses Josephson junctions, capacitors and inductors to implement a microwave laser, including the low-noise couplers that allow the design to surpass the standard quantum limit. Our proposal relies on the elements of superconducting quantum information, and thus is an example of how quantum engineering techniques can inspire us to re-imagine the limits of conventional quantum systems.

Seasonal and Decadal Variations of the Variance of the Synoptic and Mesoscale Sea Level Variability in the Baltic Sea

The present study examines the seasonal and decadal changes of the variance of the synoptic (periods from 2 days to 30 days) and mesoscale (periods from 2 h to 2 days) sea level oscillations in the Baltic Sea. Long-term hourly sea level records were used at 12 tide gauges located in different parts of the sea. We used spectral analysis to estimate the variance for different time scales. The spectral density of sea level oscillations in the Baltic Sea has maximum values in winter when the cyclonic activity in the atmosphere is more intensive. The maximum variances of synoptic σsyn2 and mesoscale σmes2 sea level oscillations are observed in winter, except for the heads of the Gulf of Finland (Gorny Institute) and Gulf of Riga (Pärnu), where the absolute maximum of σsyn2 is reached in November. The variances σsyn2 and σmes2 from November to February are 2–3 and 5 times higher than in the summer. The values of σsyn2 and σmes2 are characterized by high correlation up to 0.7–0.75 with wind variations and atmospheric indices (NAO, AO, and SCAND) in winter and low correlation in summer. The zonal wind and σmes2 in Gorny Institute are characterized by wide areas of high coherence at periods of 0.7–4 years. At Gedser, σsyn2 decreased by 19%, and at Ratan it increased by 17% over 90 years. The values of σmes2 over 90 years increased by 32% at Klagshamn, 36% at Ratan, and up to 60% at Kungsholmsfort.

Coherent category training enhances generalization and increases reliance on prototype representations

A major question for the study of learning and memory is how to tailor learning experiences to promote knowledge that generalizes to new situations. Using category learning as a representative domain, the present study tested two factors thought to influence acquisition of conceptual knowledge: the number of training examples (set size) and the similarity of training examples to the category average (set coherence). Across participants, size and coherence of category training sets were varied in a fully-crossed design. After training, participants demonstrated the breadth of their category knowledge by categorizing novel examples varying in their distance from the category center. Results showed better generalization following more coherent training sets, even when categorizing items furthest from the category center. There was little effect of set size. We also tested the types of representations underlying categorization decisions by fitting formal prototype and exemplar models. Prototype models posit abstract category representations based on the category’s central tendency, whereas exemplar models posit that categories are represented by individual category members. We show that more subjects rely on a prototype strategy following high coherence training, suggesting that more coherent training sets facilitate extraction of the category average. Together, these results provide strong evidence for the benefit of training on examples that are similar to one another and to the category center.