scholarly journals Floquet maser

2021 ◽  
Vol 7 (8) ◽  
pp. eabe0719 ◽  
Author(s):  
Min Jiang ◽  
Haowen Su ◽  
Ze Wu ◽  
Xinhua Peng ◽  
Dmitry Budker
Keyword(s):  
Dark Matter ◽  
Magnetic Fields ◽  
State Of The Art ◽  
Low Frequency ◽  
Atomic Clocks ◽  
Periodically Driven ◽  
Time Periodic ◽  
Better Than ◽  
Time Crystals ◽  
Floquet States

The invention of the maser stimulated revolutionary technologies such as lasers and atomic clocks. Yet, realizations of masers are still limited; in particular, the physics of masers remains unexplored in periodically driven (Floquet) systems, which are generally defined by time-periodic Hamiltonians and enable observation of many exotic phenomena such as time crystals. Here, we investigate the Floquet system of periodically driven 129Xe gas under damping feedback and unexpectedly observe a multimode maser that oscillates at frequencies of transitions between Floquet states. Our findings extend maser techniques to Floquet systems and open avenues to probe Floquet phenomena unaffected by decoherence, enabling a previously unexplored class of maser sensors. As a first application, our maser offers the capability of measuring low-frequency (1 to 100 mHz) magnetic fields with subpicotesla-level sensitivity, which is substantially better than state-of-the-art magnetometers and can be applied to, for example, ultralight dark matter searches.

Practical High Resolution Microscopy

1968 ◽  
Vol 26 ◽  
pp. 302-303
Author(s):  
P. A. Marsh ◽  
T. Mullens ◽  
D. Price
Keyword(s):  
High Resolution ◽  
Magnetic Fields ◽  
Low Frequency ◽  
Resolving Power ◽  
Careful Attention ◽  
Electron Microscopes ◽  
The Relationship ◽  
High Resolution Microscopy ◽  
New Facilities

It is possible to exceed the guaranteed resolution on most electron microscopes by careful attention to microscope parameters essential for high resolution work. While our experience is related to a Philips EM-200, we hope that some of these comments will apply to all electron microscopes.The first considerations are vibration and magnetic fields. These are usually measured at the pre-installation survey and must be within specifications. It has been our experience, however, that these factors can be greatly influenced by the new facilities and therefore must be rechecked after the installation is completed. The relationship between the resolving power of an EM-200 and the maximum tolerable low frequency interference fields in milli-Oerstedt is 10 Å - 1.9, 8 Å - 1.4, 6 Å - 0.8.

Search for weakly interacting massive dark matter particles: state of the art and prospects

2020 ◽  
Author(s):  
Andrei B. Aleksandrov ◽  
Aigerim B. Dashkina ◽  
Nina S. Konovalova ◽  
Natal'ya M. Okat'eva ◽  
Natal'ya G. Polukhina ◽  
...  
Keyword(s):  
Dark Matter ◽  
State Of The Art ◽  
Weakly Interacting

Natural and man-made low-frequency magnetic fields as a potential health hazard

1998 ◽  
Vol 168 (07) ◽  
pp. 767-791 ◽  
Author(s):  
N.G. Ptitsyna ◽  
G. Villoresi ◽  
L.I. Dorman ◽  
N. Iucci ◽  
Marta I. Tyasto
Keyword(s):  
Magnetic Fields ◽  
Health Hazard ◽  
Low Frequency ◽  
Potential Health ◽  
Potential Health Hazard

The characteristics and present state for Extremely Low Frequency-Magnetic Fields of metropolitan subway

2015 ◽  
Vol 14 (1) ◽  
pp. 7-15
Author(s):  
Dae-kwan Jung ◽  
◽  
Joon-sig Jung ◽  
Kyu-mok Lee ◽  
Hyung-kyu Park ◽  
...  
Keyword(s):  
Magnetic Fields ◽  
Present State ◽  
Low Frequency ◽  
Extremely Low Frequency

Occupational Exposure to Electric Shocks and Extremely Low-Frequency Magnetic Fields and Motor Neurone Disease

2020 ◽  
Author(s):  
Grace X Chen ◽  
Andrea’t Mannetje ◽  
Jeroen Douwes ◽  
Leonard H Berg ◽  
Neil Pearce ◽  
...  
Keyword(s):  
Occupational Exposure ◽  
Magnetic Fields ◽  
Low Frequency ◽  
Population Based ◽  
Motor Neurone ◽  
Motor Neurone Disease ◽  
Cumulative Exposure ◽  
Spine Injury ◽  
Extremely Low Frequency ◽  
Electric Shocks

Abstract In a New Zealand population-based case-control study we assessed associations with occupational exposure to electric shocks, extremely low-frequency magnetic fields (ELF-MF) and motor neurone disease using job-exposure matrices to assess exposure. Participants were recruited between 2013 and 2016. Associations with ever/never, duration, and cumulative exposure were assessed using logistic regression adjusted for age, sex, ethnicity, socioeconomic status, education, smoking, alcohol consumption, sports, head or spine injury and solvents, and mutually adjusted for the other exposure. All analyses were repeated stratified by sex. An elevated risk was observed for having ever worked in a job with potential for electric shocks (odds ratio (OR)=1.35, 95% confidence interval (CI): 0.98, 1.86), with the strongest association for the highest level of exposure (OR=2.01, 95%CI: 1.31, 3.09). Analysis by duration suggested a non-linear association: risk was increased for both short-duration (<3 years) (OR= 4.69, 95%CI: 2.25, 9.77) and long-duration in a job with high level of electric shock exposure (>24 years; OR=1.88; 95%CI: 1.05, 3.36), with less pronounced associations for intermediate durations. No association with ELF-MF was found. Our findings provide support for an association between occupational exposure to electric shocks and motor neurone disease but did not show associations with exposure to work-related ELF-MF.

A new approach based on graph matching and evolutionary approach for sport scheduling problem

2020 ◽  
pp. 1-16
Author(s):  
Meriem Khelifa ◽  
Dalila Boughaci ◽  
Esma Aïmeur
Keyword(s):  
Graph Matching ◽  
State Of The Art ◽  
Travel Cost ◽  
Round Robin ◽  
New Approach ◽  
Traveling Tournament Problem ◽  
Significant Interest ◽  
National League ◽  
Better Than

The Traveling Tournament Problem (TTP) is concerned with finding a double round-robin tournament schedule that minimizes the total distances traveled by the teams. It has attracted significant interest recently since a favorable TTP schedule can result in significant savings for the league. This paper proposes an original evolutionary algorithm for TTP. We first propose a quick and effective constructive algorithm to construct a Double Round Robin Tournament (DRRT) schedule with low travel cost. We then describe an enhanced genetic algorithm with a new crossover operator to improve the travel cost of the generated schedules. A new heuristic for ordering efficiently the scheduled rounds is also proposed. The latter leads to significant enhancement in the quality of the schedules. The overall method is evaluated on publicly available standard benchmarks and compared with other techniques for TTP and UTTP (Unconstrained Traveling Tournament Problem). The computational experiment shows that the proposed approach could build very good solutions comparable to other state-of-the-art approaches or better than the current best solutions on UTTP. Further, our method provides new valuable solutions to some unsolved UTTP instances and outperforms prior methods for all US National League (NL) instances.

scholarly journals Fighting Together against the Pandemic: Learning Multiple Models on Tomography Images for COVID-19 Diagnosis

AI ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 261-273
Author(s):  
Mario Manzo ◽  
Simone Pellino
Keyword(s):  
Network Architecture ◽  
State Of The Art ◽  
Ensemble Classification ◽  
Effective Vaccine ◽  
Rt Pcr ◽  
Neural Network Architecture ◽  
Experimental Phase ◽  
Different Types ◽  
Polymerase Chain ◽  
Better Than

COVID-19 has been a great challenge for humanity since the year 2020. The whole world has made a huge effort to find an effective vaccine in order to save those not yet infected. The alternative solution is early diagnosis, carried out through real-time polymerase chain reaction (RT-PCR) tests or thorax Computer Tomography (CT) scan images. Deep learning algorithms, specifically convolutional neural networks, represent a methodology for image analysis. They optimize the classification design task, which is essential for an automatic approach with different types of images, including medical. In this paper, we adopt a pretrained deep convolutional neural network architecture in order to diagnose COVID-19 disease from CT images. Our idea is inspired by what the whole of humanity is achieving, as the set of multiple contributions is better than any single one for the fight against the pandemic. First, we adapt, and subsequently retrain for our assumption, some neural architectures that have been adopted in other application domains. Secondly, we combine the knowledge extracted from images by the neural architectures in an ensemble classification context. Our experimental phase is performed on a CT image dataset, and the results obtained show the effectiveness of the proposed approach with respect to the state-of-the-art competitors.

scholarly journals Cache-efficient sweeping-based interval joins for extended Allen relation predicates

2021 ◽  
Author(s):  
Danila Piatov ◽  
Sven Helmer ◽  
Anton Dignös ◽  
Fabio Persia
Keyword(s):  
Data Structure ◽  
Experimental Evaluation ◽  
State Of The Art ◽  
Temporal Databases ◽  
Access Method ◽  
Wide Range ◽  
Interval Relation ◽  
Cache Efficient ◽  
Join Algorithms ◽  
Better Than

AbstractWe develop a family of efficient plane-sweeping interval join algorithms for evaluating a wide range of interval predicates such as Allen’s relationships and parameterized relationships. Our technique is based on a framework, components of which can be flexibly combined in different manners to support the required interval relation. In temporal databases, our algorithms can exploit a well-known and flexible access method, the Timeline Index, thus expanding the set of operations it supports even further. Additionally, employing a compact data structure, the gapless hash map, we utilize the CPU cache efficiently. In an experimental evaluation, we show that our approach is several times faster and scales better than state-of-the-art techniques, while being much better suited for real-time event processing.

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