High Coherence Research Articles

Kinematic stability in cardiac locomotor synchronization during regular walking

In locomotion, previous studies have identified a phenomenon known as cardiac locomotor synchronization (CLS), characterized by the phenomenon where heartbeats consistently occur at a specific time within the locomotor cycle. While the physiological significance of CLS is well recognized, its kinematic benefits remain uncertain. Therefore, this study aimed to elucidate the kinematic benefits of CLS under regular walking. Smoothness of walking and local dynamic stability was assessed through the RMS of center of mass acceleration (RMS-CoMacc) and maximum Lyapunov exponent (maxL). It was hypothesized that stronger CLS would lead to reduced RMS-CoMacc and maxL. Thirteen participants performed a 10-minute walk at 5.0 km/h. The electrocardiogram and the motion capture data were recorded. To evaluate the CLS, phase coherence (λ) between cardiac and walking step rhythm was computed. The high and low-phase coherence was defined as λ ≥ 0.1 (λhigh) and λ < 0.01 (λlow); corresponding RMS-CoMacc and maxL values were compared for each state. Although the λhigh was significantly higher than λlow, no significant differences in RMS-CoMacc and maxL were observed between the high and low states. The relatively weak CLS observed herein might not have led to a reduction in RMS-CoMacc and maxL. In addition, regular walking speed might be a velocity at which it is challenging to generate intervention effects. Hence, the CLS appears to have negligible impact on the smoothness of walking or local dynamical stability at a 5.0 km/h.

Experimental Measurements of Explosion Effects Propagating in the Real Geological Environment—Correlation with Small-Scale Model

This research focuses on comparing small-scale and full-scale measurements of wave propagation from explosions by using scaling relationships to find significant correlations between the two. The study investigates how seismic waves generated by explosions behave in the geological environment. The research covers various aspects such as the development of the model, the explosive materials used, measurement methods, evaluation techniques, and relevant software. A scientific approach based on the principle of backward Fourier transform was used to process and evaluate the data, which helps to filter the frequencies. One of the important calculations discussed is the determination of the attenuation coefficient, which helps to describe how waves attenuate as they pass through a material. The research also deals with dynamic scaling, using the dynamic exponent as a scaling factor to provide a better understanding of the behavior of waves at different scales. By comparing real in situ data with results from small-scale models, the study provides a robust framework for predicting the effects of explosions in complex geological environments. The research results show a high correlation coherence of the statistical data files of up to 4.1%. For dynamic tasks and model scaling, an important result can be pointed out, namely the approximately fourfold decrease in the exponents of the dependence on the distance from the excitation source and the amplitudes between P-waves (0.4316) and R-waves (0.1219). Conclusions are targeted at the possibility of correlating three types of results: small-scale simulations, numerical simulations, and a real full-scale experiment.

Supramammillary Theta Oscillations in Water Maze Learning.

The supramammillary nucleus (SuM) in the hypothalamus, in conjunction with the hippocampus (HPC), has been implicated through theta oscillations in various brain functions ranging from locomotion to learning and memory. While the indispensable role of the SuM in HPC theta generation in anesthetized animals is well-characterized, the SuM is not always necessary for HPC theta in awake animals. This raises questions on the precise behavioral relevance of SuM theta activity and its interaction with HPC theta activity. We used simultaneously recorded SuM and HPC local field potentials (LFPs) in a one-day water maze (WM) learning paradigm in rats (n = 8), to show that theta activities recorded from the SuM itself were not positively correlated with locomotor (swimming) speed nor acceleration, but the individual relationship between acceleration and SuM theta frequency is correlated with WM learning rates. In contrast, we found that SuM-HPC theta phase coherence is strongly correlated with swimming speed and acceleration, but these do not relate to WM learning. SuM-HPC-directed coherence analysis demonstrated no swimming kinetics nor learning rate associations, but revealed that periods of high SuM-HPC theta phase coherence are driven by the SuM at relatively low (~6.2 Hz) frequencies. Additionally, we demonstrate that the SuM and the HPC also engage in non-random, non-coherent phase coupling modes where either structure preferentially displays a ± 2 Hz difference with the other. Our data indicate SuM theta LFPs do not appear to be related to either speed coding or spatial learning in swimming rats and display non-random out-of-phase theta frequency coupling with the HPC.

High-coherence quantum acoustics with planar superconducting qubits

Quantum acoustics is an emerging platform for hybrid quantum technologies enabling quantum coherent control of mechanical vibrations. High-overtone bulk acoustic resonators (HBARs) represent an attractive mechanical implementation of quantum acoustics due to their potential for exceptionally high mechanical coherence. Here, we demonstrate an implementation of high-coherence HBAR quantum acoustics integrated with a planar superconducting qubit architecture, demonstrating an acoustically induced-transparency regime of high cooperativity and weak coupling, analogous to the electrically induced transparency in atomic physics. Demonstrating high-coherence quantum acoustics with planar superconducting devices enables interesting applications for acoustic resonators in quantum technologies.

Exploring Sense of Coherence and Death Anxiety among patients with Chronic Illness in Greece

Abstract Introduction Chronic illness often brings about existential concerns, including fear of death, which can significantly impact individuals’ well-being. The concept of sense of coherence provides a framework for understanding how individuals perceive and cope with stressors, including those associated with chronic illness. Purpose This study investigated the correlation between Sense of Coherence, death anxiety, and chronic illness among Greek patients, aiming to understand how these factors interplay. Methods An electronic survey was distributed to chronic illness patients in Greece. Sense of Coherence was measured using the Sense of Coherence scale, while death anxiety was assessed using the Collett-Leste Fear of Death scale. Various chronic conditions were considered, and demographic data were collected. Results The final sample consisted of 118 participants (female 79.7%; death anxiety score=mean109.2, Sd = 19.2; sense of coherence score=mean55.12, Sd = 13.61). Women and the age group of 58-65 years presented higher death anxiety score followed by the group of 34-41 years. No differences were found between genders in terms of sense of coherence. The highest coherence was manifested in the age group of 50-57 years and the lowest in the age group of 42-49 years. A significant negative correlation was observed between sense of coherence and fear of death (rs(118)= -.299, p < .01). Further correlation tests were performed between axes of coherence, which indicated a stronger negative correlation in two of the three axes of the sense of coherence (Manageability and Meaningfulness) and among all the axes of fear of death, beyond the first, which concerns the loss of one’s own life. Conclusions The study suggests that individuals with a stronger sense of coherence experience lower death anxiety. Understanding these dynamics is crucial for tailored patient interventions and support strategies. Key messages • Gender and age-specific variations exist in how people approach and experience disease and mortality. • Understanding patients’ coping mechanisms and perceptions of illness is important in disease management.

Bistatic multi‐polarimetric synthetic aperture radar coherence investigation using spatially variant incoherence trimming

AbstractSynthetic Aperture Radar (SAR) Coherent Change Detection allows for the detection of very small scene changes. This is particularly useful for Intelligence, Surveillance and Reconnaissance as small changes such as vehicle tracks can be identified. Rapidly collecting repeat pass SAR imagery is important in these applications. For space‐borne platforms, such repeat passes may however have significant differences, or baselines. Coherent Change Detection products are reliant on high coherence for good interpretability. This work investigates the sources and levels of incoherence associated with bistatic SAR imagery for a variety of baselines using simulations and measured laboratory data for two ground types. Additionally, spatially variant incoherence trimming is implemented. The paper shows the importance of angle‐dependant backscatter on the coherence of sub‐resolution cell scatterers.

Identifying Potential Landslides in Low-Coherence Areas Using SBAS-InSAR: A Case Study of Ninghai County, China

The southeastern coastal regions of China are characterized by typical hilly terrain with abundant rainfall throughout the year, leading to frequent geological hazards. To investigate the measurement accuracy of surface deformation and the effectiveness of error correction methods using the small baselines subset–interferometry synthetic aperture radar (SBAS-InSAR) method in identifying potential geological hazards in such areas, this study processes and analyzes 129 SAR images covering Ninghai County, China. By processing coherence coefficients using the Stacking technique, errors introduced by low-coherence images during phase unwrapping are mitigated. Subsequently, interferograms with high coherence are selected for time-series deformation analysis based on the statistical parameters of coherence coefficients. The results indicate that, after mitigating errors from low-coherence images, applying the SBAS-InSAR method to only high-coherence SAR datasets provides reliable surface deformation results. Additionally, when combined with field geological survey data, this method successfully identified landslide boundaries and potential landslides not accurately detected in previous geological surveys. This study demonstrates that using the SBAS-InSAR method and selecting high-coherence SAR images based on interferogram coherence statistical parameters significantly improves measurement accuracy and effectively identifies potential geological hazards.

Multi-scale drought variability over West Africa and the associated large-scale circulation patterns

This study addresses the critical research gap in understanding regional drought dynamics in West Africa (WA) using advanced multivariate wavelet coherence (MWC) techniques, revealing critical insights into the complex interplay between large-scale climate indices and regional drought patterns. Utilizing the Standardized Precipitation Evapotranspiration Index (SPEI) and self-calibrating Palmer Drought Severity Index (scPDSI), we examined drought characteristics across WA from 1950 to 2018. Our analysis revealed significant drying trends across all seasons, with the Arid zone experiencing the most severe and prolonged drought (158 months) from August 1981 to September 1994, affecting 79.77% of the area. The entire WA region faced its most extensive drought during this period, impacting over 60% of the study area. MWC analysis demonstrated enhanced drought predictability when combining climate indices, particularly the Southern Oscillation Index with the Atlantic Multidecadal Oscillation, yielding high Average Wavelet Coherence values of 0.52 (SPEI) and 0.53 (scPDSI), with substantial Percentage Area of Significant Coherence of 40.19% and 43.68%, respectively. These findings highlight the crucial role of oceanic-atmospheric interactions in modulating drought conditions across WA. Our results provide valuable insights for improving drought forecasting and management strategies in the region, emphasizing the need for integrated approaches that consider multiple climate indices and their combined effects on drought dynamics.

Inter- and intra-annual carbon isotope fluctuations in Pinus sylvestris L. tree rings whole wood and cellulose in north-eastern Lithuania

In temperate regions trees typically exhibit growth sensitivity to climatic conditions during the growth season. Annual tree ring growth increments correlate with a variety of environmental factors. As an index of water use efficiency, δ13C is a preferred proxy to allow accurate interpretation of environmental factors critical for the tree growth, including changes in climate patterns, variation in the ambient temperature and precipitation. We assumed that isotopic differences within individual tree rings are likely to produce seasonal isotope fluctuations in the chronology that might be interpreted as response to environmental impacts. To verify the assumption, we measured δ13C in annual tree rings of Pinus Sylvestris L. split into 13 intra-annual segments each and checked δ13C correlations with temperature, precipitation, the number of sunshine hours and relative air humidity. For the investigation, we chose a site in north-eastern Lithuania, Zarasai, located in boreal latitude and remote from industrial pollution sources. The methodology of the research was based on high coherence of δ13C chronologies measured in the whole wood and α-cellulose extracted by means of two different methods. The experiment produced strong δ13C correlations with hydrometeorological parameters, especially in the earlywood formed in June

Student Pharmacists’ Reflections on Personal and Professional Development Following a Series of Longitudinal Faith-Based Courses

ObjectiveThis study aims to explore how integrating Judeo-Christian religious education into the pharmacy curriculum influences students’ spiritual and moral development, professional values, and mindset, preparing them for future holistic health care practice. MethodsA series of Judeo-Christian faith-based courses were integrated into the required Doctor of Pharmacy curriculum with the aim of developing student pharmacists’ moral foundation for future health care roles. Student reflections from these courses were compiled and analyzed using WordStat, combining natural language processing and statistical analysis. Content analysis included word cloud visualization, word co-occurrence, phrase extraction, and topic modeling. Thematic analysis with a deductive coding approach was applied. Descriptive statistics were used to analyze coding frequencies. ResultsWord cluster analysis revealed frequently cited and co-occurring words, including God, patient, care, life, love, ethics, personal, professional, health, and people. The frequently occurring phrases included patient care, professional ethics, personal ethics, and professional developments. The topics with high coherence values included love and compassion, empathetic care, caring health professionals, patient care, and leadership based on biblical principles. The major themes that emerged included spiritual growth and connection with God, the cultivation of virtues and ethical principles in personal development, and integration of faith into professional commitments for these aspiring professionals. ConclusionThe findings suggest that integrating spiritual and religious education into the pharmacy curriculum helps students develop a strong moral foundation, guiding their future practice with compassion and integrity.

Preoperative interhemispheric coherence as a potential predictive marker for seizure outcome after total corpus callosotomy in nonlesional generalized epilepsy: a scalp EEG study.

Corpus callosotomy (CC) is one of the palliative epilepsy surgical procedures available for nonlesional generalized epilepsy, but it is more invasive than other palliative surgical procedures. The main challenge is proper selection of suitable patients for CC. Coherence analysis is a method for evaluating brain connectivity, but the correlation between preoperative coherence and surgical outcomes has not previously been clarified. The authors aimed to evaluate correlations between preoperative interhemispheric coherence and surgical outcome in patients with nonlesional generalized epilepsy. This retrospective study investigated patients with nonlesional generalized epilepsy who underwent total CC. The authors collected data for patients with good seizure outcome (Oguni classification A or B) and bad seizure outcome (Oguni classification D). For coherence analysis, the authors selected a period without interictal discharges. Preoperative interhemispheric coherence values from 8 pairs of symmetrically opposite scalp electrodes were computed across 5 frequency bands. Then, the authors evaluated correlations between coherence and surgical outcomes. Forty patients were included (19 males and 21 females). The mean (range) age at the time of surgery was 5.1 (1-18) years. Seizure outcomes were good in 15 patients and bad in the other 25 patients. Age at onset of epilepsy, duration of epilepsy before surgery, age at time of surgery, and presence of epileptic spasm did not differ significantly between patients with good and bad seizure outcomes (p = 0.36, p = 0.14, p = 0.10, and p = 0.20, respectively). Significant correlations were identified between higher Fp1-Fp2 interhemispheric coherence values in the delta, theta, and alpha frequency bands and bad surgical outcomes (p = 0.0397, p = 0.0322, and p = 0.0476, respectively). The receiver operating characteristic curves of the Fp1-Fp2 coherence values in these frequency bands showed areas under the curve of 67%, 69%, and 67%, respectively. The optimal cutoff values for Fp1-Fp2 interhemispheric coherence to predict surgical outcomes were 55.6 for delta (66.7% sensitivity and 72.0% specificity), 55.9 for theta (60.0% sensitivity and 76.0% specificity), and 50.3 for alpha (53.3% sensitivity and 84.0% specificity). This is the first study to identify potential predictive factors for surgical outcomes based on preoperative interhemispheric coherence in nonlesional generalized epilepsy. Higher coherence between Fp1-Fp2 in the delta, theta, and alpha frequencies correlated with bad seizure outcome after CC.

Интеллектуальная обработка текстовой информации: обзор автоматизированных методов суммаризации

Interest in innovative technological strategies and modern digital tools has increased significantly due to the need to manage large amounts of unstructured data. This paper reviews current paradigms and services for automated summarization, developed based on interdisciplinary research in linguistics, computer technologies, and artificial intelligence. It focuses on syntactic and lexical techniques employed by neural network models for text compression. The paper presents performance examples of such AI-powered services as QuillBot, Summate.it, WordTune, SciSummary, Scholarcy, and OpenAI ChatGPT. The contemporary automated models proved effective in using extractive and abstractive methods to generate summaries of varying quality and length. The extractive approach relies on identifying the most significant sentences from the original text, while abstractive algorithms create new sentence structures that preserve the main idea of the original content. Automated summarizers effectively utilize text compression techniques that are inherent to human approach to text processing, e.g., they exclude redundant information, simplify complex structures, and generalize data. These technologies provide high accuracy and coherence in the generated summaries, though each summarization model has its limitations. Optimal results depend on the specifics of the task at hand: extractive models provide brevity and precision while abstractive ones allow for deeper semantic processing. Automated summarization is becoming an important tool in various fields that require effective analysis and processing of large text data.

Decoding Online Narratives and Unraveling Complexities in the Rohingya Refugee Crisis

The Rohingya refugee crisis, a humanitarian tribulation involving the persecution of the Rohingya Muslim ethnic minority group in Myanmar, has led to a massive exodus of refugees, primarily women and children, to neighboring Bangladesh. Analyzing public opinion toward the Rohingya crisis poses a challenge due to the time complexity of manually assessing individual expressions from the vast amount of text on online platforms. This research focuses on identifying hidden patterns in online discussions surrounding the Rohingya refugee crisis, employing topic modeling and a thematic sentiment analysis-based approach. It represents the first comprehensive exploration of public views on internet spaces to support this community. In the experiment, we identified 15 coherent topics from 6,840 unique documents with a high coherence score of about 0.60. The key themes explored encompass familial resilience, the urgency of addressing the refugee crisis, complexities within the Rohingya situation, religious and cultural elements, and geopolitical considerations. Sentiment analysis revealed nuanced emotional tones, with positive sentiments in discussions about refugee support and international aid and mixed or negative sentiments in topics concerning religious dynamics and women’s protection. The implications of this research extend to guiding policymakers, humanitarian organizations, and advocacy groups in developing targeted interventions, communication strategies, and informed policy initiatives. In addition, the findings emphasize the importance of understanding and responding effectively to the multifaceted challenges faced by the Rohingya community.

Patients with amnestic mild cognitive impairment have higher cerebrovascular impedance than cognitively normal older adults.

Brain hypoperfusion is associated with cognitive impairment. Higher cerebrovascular impedance modulus (Z) may contribute to brain hypoperfusion. We tested hypotheses that patients with amnestic mild cognitive impairment (aMCI) (i.e., those who have a high risk of developing Alzheimer's disease) have higher Z than age-matched cognitively normal individuals, and that high Z is correlated with brain hypoperfusion. Fifty-eight patients with aMCI (67 ± 7 yr) and 25 cognitively normal subjects (CN, 65 ± 6 yr) underwent simultaneous measurements of carotid artery pressure (CAP, via applanation tonometry) and middle cerebral arterial blood velocity (CBV, via transcranial Doppler). Z was quantified using cross-spectral and transfer function analyses between dynamic changes in CBV and CAP. Patients with aMCI exhibited higher Z than NC (1.18 ± 0.34 vs. 1.01 ± 0.35 mmHg/cm/s, P = 0.044) in the frequency range from 0.78 to 4.29 Hz. The averaged Z in the frequency range (0.78-3.13 Hz) of high coherence (>0.9) was inversely correlated with total cerebral blood flow measured with 2-D Doppler ultrasonography normalized by the brain tissue mass (via structural MRI) across both patients with aMCI and NC (r = -0.311, P = 0.007), and in patients with aMCI alone (r = -0.306, P = 0.007). Our findings suggest that patients with aMCI have higher cerebrovascular impedance than cognitively normal older adults and that increased cerebrovascular impedance is associated with brain hypoperfusion.NEW & NOTEWORTHY This is the first study to compare cerebrovascular impedance between patients with amnestic mild cognitive impairment (aMCI) and age-matched cognitively normal individuals. Patients with aMCI had higher cerebrovascular impedance modulus than age-matched cognitively normal individuals, which was correlated with brain hypoperfusion. These results suggest the presence of cerebrovascular dysfunction in the dynamic regulation of cerebral blood flow in older adults who have high risks of Alzheimer's disease.

Customizing subwavelength stochastic light fields via structured spatial coherence in a high-NA resonator

Interaction of light in the high-numerical aperture (high-NA) systems is crucial for theoretical advances and applications such as superresolution imaging and optical nanofabrication. High coherence is demanded at this scale for intensity and spin profile sculpturing, since the underlying physics being wave interference. Here we report that, even for low-coherence light, 3D light features in a nanometer range can be generated by employing structured coherence states of the light beam in a high-NA resonator system. The generated structures, e.g., 3D helix intensity and transverse spin texture, can survive in rather incoherent optical fields at nanoscale. We also found that, counterintuitively, despite the substantial decrease in spatial coherence of the light field, the longitudinal electric field component and transverse spin density are instead enhanced. The applications of the observed twisted spectral density and spin structures may range from high-resolution imaging to metrology.

Safe Havens Characteristics of Islamic Stock Indices During Bearish and Bullish Markets: A Case of Developed and Developing Countries

Purpose — This study examines the performance of Islamic and conventional indices during bullish (positive) and bearish (negative) markets while the economic and financial conditions are different. Design/Methodology/Approach — This study uses GARCH (1,1) and wavelet-assisted cross-spectral, cross-correlation analyses to investigate the performance of Islamic and conventional stock indices and study the presence of safe havens, which reflect low volatility in the indices during times of market turbulence, for investors during bearish and bullish periods from 2019–2021. Findings — The paper finds that there is high and persistent volatility in Islamic indices in bullish markets, while in bearish periods the Islamic indices show low volatility persistence; and conventional indices were highly volatile during crisis periods. Also, the impact of news shocks on Islamic indices was intense before COVID-19, while after that news, shocks had a high impact on the conventional indices. The wavelet coherence analysis shows that there is high coherency between Islamic and conventional indices in developed countries but in developing countries, the opposite prevails. Originality/Value — The study is the first to use both Generalised Autoregressive Conditional Heteroskedasticity (GARCH) and wavelet coherence models for examining Islamic and conventional stock indices during bearish and bullish markets, especially in the COVID-19 pandemic era. Practical Implications — The results conclude that there are safe havens present in Islamic indices in both developing and developed countries, especially the United States (US), the United Kingdom (UK), India, and Indonesia, while in other countries the presence is weak. Both GARCH and wavelet coherence models show the same results regarding the presence of volatility and safe havens for investors in different countries.

Efficient topic identification for urgent MOOC Forum posts using BERTopic and traditional topic modeling techniques

AbstractMOOC platforms provide a means of communication through forums, allowing learners to express their difficulties and challenges while studying various courses. Within these forums, some posts require urgent attention from instructors. Failing to respond promptly to these posts can contribute to higher dropout rates and lower course completion rates. While existing research primarily focuses on identifying urgent posts through various classification techniques, it has not adequately addressed the underlying reasons behind them. This research aims to delve into these reasons and assess the extent to which they vary. By understanding the root causes of urgency, instructors can effectively address these issues and provide appropriate support and solutions. BERTopic utilizes the advanced language capabilities of transformer models and represents an advanced approach in topic modeling. In this study, a comparison was conducted to evaluate the performance of BERTopic in topic modeling on MOOCs discussion forums, alongside traditional topic models such as LDA, LSI, and NMF. The experimental results revealed that the NMF and BERTopic models outperformed the other models. Specifically, the NMF model demonstrated superior performance when a lower number of topics was required, whereas the BERTopic model excelled in generating topics with higher coherence when a larger number of topics was needed.The results considering all urgent posts from the dataset were as follows: Optimal number of topics is 6 for NMF and 50 for BERTopic; coherence scores is 0.66 for NMF and 0.616 for BERTopic; and IRBO scores is 1 for both models. This highlights the BERTopic model capability to distinguish and extract diverse topics comprehensively and coherently, aiding in the identification of various reasons behind MOOC Forum posts.

Controllable lasing characteristics in Brillouin random fiber lasers by tailoring gain and random feedback fibers

Brillouin random fiber lasers (BRFLs), the combination of stimulated Brillouin scattering (SBS) gain and random distributed feedback, offer narrow linewidth lasing with simplicity and flexibility. However, BRFLs may not gain broad acceptance unless the fundamental lasing mechanisms governing their operation are fully understood and the lasing properties are effectively manipulated. Here, we demonstrate the control of lasing characteristics in BRFLs by tailoring the SBS gain fiber and the scattering pattern of the random feedback fiber. Experimental results show that BRFLs with 5 cm random fiber gratings (RFGs) feedback exhibit lower intensity fluctuation, longer coherence time, and more stable frequency compared to those with 6 km Rayleigh scattering fiber (RSF) feedback thanks to more correlated phase, lower mode density, and weaker dependence on external variations of RFGs. The low-randomness RFG feedback further improves the coherence time and intensity fluctuation attributed to the small period variation of sub-gratings. Moreover, the BRFL based on the high gain fiber and the strong scattering RFG feedback with low loss achieves high lasing efficiency and low threshold. The frequency jitter, intensity noise, and coherence time are also improved by reducing the gain fiber from 20 km to 1 km due to decreased mode hopping from mode competition. These results clarify the impact of gain and random feedback fibers on BRFL performance, offering insights for optimizing complex laser design for applications requiring high frequency stability and long coherence time.

Suppression of intensity noise and phase noise for thulium-holmium co-doped fiber laser by self-injection locking

The present study proposes and demonstrates a narrow-linewidth thulium-holmium co-doped fiber laser based on self-injection locking. The laser with single-longitudinal-mode operation is realized using a fiber Bragg grating as a wavelength-selection component and a dual-ring compound cavity as a mode-selection filter. The linewidth was compressed by increasing the photon lifetime by utilizing delay fibers of different lengths in the feedback cavity. The results show that the optical signal-to-noise ratio of the output laser is 57.2 dB, and the relative intensity noise is -130.43 dB/Hz with self-injection locking. The intrinsic linewidth is compressed from 39.45 kHz to 3.21 kHz, a reduction of nearly an order of magnitude. The linewidth compression mechanism solves the problems associated with deep linewidth compression in fiber lasers with long ring cavities and fosters the development of practical and reliable all-fiber structures. The laser source is characterized by low cost, high coherence, and low noise, which are highly desirable features in coherent optical detection, high-resolution spectrometers, microwave photonics, and optical sensing.

Frequency selective illumination for high aperture coherence scanning interferometry

Abstract Coherence scanning interferometry is a widely used optical topography measurement technique, which can achieve axial resolutions in the sub-nanometer regime. Nevertheless, in the lateral dimension it is inherently diffraction limited and multiple problems arise when approaching this limit. Especially for challenging surface topographies like steep slopes or small grating periods measurement artifacts start to cause massive deviations in the 3D reconstruction of the surface due to the increased influence of noise on increasingly weak signals. In this study we present an illumination approach for Linnik-type CSI, which highlights oblique incident angles of the illuminating light cone in high numerical aperture (0.95) systems. It is demonstrated, that this approach can significantly improve the signal-to-noise ratio for measurements at steep surface slopes and therefore increase the subsequent surface reconstruction.