We demonstrate quantum logic enhanced sensitivity for a macroscopic ensemble of solid-state, hybrid two-qubit sensors. We achieve over a factor of 30 improvement in the single-shot signal-to-noise ratio, translating t...
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We demonstrate quantum logic enhanced sensitivity for a macroscopic ensemble of solid-state, hybrid two-qubit sensors. We achieve over a factor of 30 improvement in the single-shot signal-to-noise ratio, translating to an ac magnetic field sensitivity enhancement exceeding an order of magnitude for time-averaged measurements. Using the electronic spins of nitrogen vacancy (NV) centers in diamond as sensors, we leverage the on-site nitrogen nuclear spins of the NV centers as memory qubits, in combination with homogeneous and stable bias and control fields, ensuring that all of the ∼109 two-qubit sensors are sufficiently identical to permit global control of the NV ensemble spin states. We find quantum logic sensitivity enhancement for multiple measurement protocols with varying optimal sensing intervals, including XY8 and DROID-60 dynamical decoupling, as well as correlation spectroscopy, using an applied ac magnetic field signal. The results are independent of the nature of the target signal and broadly applicable to measurements using NV centers and other solid-state spin ensembles. This work provides a benchmark for macroscopic ensembles of quantum sensors that employ quantum logic or quantum error correction algorithms for enhanced sensitivity.
Despite national efforts in increasing representation of minority students in STEM disciplines, disparities prevail. Hispanics account for 17.4% of the U.S. population, and nearly 20% of the youth population (21 years...
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Despite national efforts in increasing representation of minority students in STEM disciplines, disparities prevail. Hispanics account for 17.4% of the U.S. population, and nearly 20% of the youth population (21 years and below) in the U.S. is Hispanic, yet they account for just 7% of the STEM workforce. To tackle these challenges, the National Science Foundation (NSF) has granted a 5-year project - ASSURE-US, that seeks to improve undergraduate education in engineering and computer Science (ECS) at California State University, Fullerton. The project seeks to advance student success during the first two years of college for ECS students. Towards that goal, the project incorporates a very diverse set of approaches, such as socio-cultural and academic interventions. Multiple strategies including developing early intervention strategies in gateway STEM courses, creating a nurturing faculty-student interaction and collaborative learning environment, providing relevant, contextual-based learning experiences, integrating project-based learning with engineering design in lower-division courses, exposing lower-division students to research to sustain student interests, and helping students develop career-readiness skills. The project also seeks to develop an understanding of the personal, social, cognitive, and contextual factors contributing to student persistence in STEM learning that can be used by STEM faculty to improve their pedagogical and student-interaction approaches. This paper summarizes the major approaches the ASSURE-US project plans to implement to reduce the achievement gap and motivate ECS students to remain in the program. Preliminary findings from the first-year implementation of the project including pre- and post- data were collected and analyzed from about one hundred freshmen and sophomore ECS students regarding their academic experience in lower-division classes and their feedback for various social support events held by the ASSURE-US project during
This study aims to know the comparison design of electric motorcycle using hybrid systems (BLDC Motor) based on parameter testing, i.e., with and without load. The design of electric motorcycles is centered on determi...
This study aims to know the comparison design of electric motorcycle using hybrid systems (BLDC Motor) based on parameter testing, i.e., with and without load. The design of electric motorcycles is centered on determining a feasibility study comparing engine drive with electric drive. Electric vehicles are the answer to decreasing petroleum supplies and environmental concerns that are worsening every year due to oil-fueled cars’ exhaust emissions. The proportion of motor vehicle exhaust as an air pollution source is between 60 and 70 percent. The global decrease of fossil fuels is also a critical issue that has yet to be handled. A descriptive statistic methodology was employed in this work as an analytical tool. The results showed when the speed increases, the efficiency of the BLDC motor would increase; this is, of course, following the principle of Orsted’s law and Lorentz force. When compared to the no-load test, the efficiency by using the load will be greater because when the BLDC motor works with a load, it will require greater torque due to an increase in load so that it takes a large amount of power so that it will increase the efficiency of the BLDC motor. When compared in terms of using the battery, the time of using the battery with no load will be longer because it does not require too much current.
Rice is the most important food crop in Indonesia, one of the plants that is quite significant and as a daily staple food for the people of Indonesia. The Indonesia government through the ministry of Agriculture tries...
Rice is the most important food crop in Indonesia, one of the plants that is quite significant and as a daily staple food for the people of Indonesia. The Indonesia government through the ministry of Agriculture tries to maintain the rice production by maintaining of the rice field. One the challenging situation that can involve the rice production is pest. Pests became one of the reasons which can reduce rice production. The decrease in rice production due to pest attack is an important problem in rice plant care. In this work, a pest detection system in rice plants developed using an intelligent system technique. The system involved image processing and intelligent technique. The system recognizes the kind of pests of the rice plant based on the feature of the image of the pets. Rice plant pest detection systems based on the pest image proceed by image procession technique and Convolution Neural Network (CNN). The system is working properly, since it resulting the training and testing accuracy of 99% and 90%, respectively.
For a sustainable future, efficient, compact, and solid-state energy converters are critical. Thermophotovoltaics (TPV)—a solid-state scheme to convert heat into electricity—is promising for thermal storage and gene...
For a sustainable future, efficient, compact, and solid-state energy converters are critical. Thermophotovoltaics (TPV)—a solid-state scheme to convert heat into electricity—is promising for thermal storage and generation1. TPV systems employing selective thermal emitters allow compact designs for various terrestrial and space applications and, hence, have garnered much attention. Despite significant research efforts, these systems have low efficiency. The selective thermal emitter and the low-bandgap photovoltaic cell contribute to this problem. Here, we solve the shortcomings of the thermal emitter by using a novel approach inspired by non-Hermitian optics. We demonstrate a hybrid metal-dielectric non-Hermitian selective emitter (NHE) with high spectral efficiency (> 60%) and employ the NHE in a TPV system operating at 1273 K. We show that a maximum TPV conversion efficiency of 12% is possible at 1273 K, though our preliminary experiments employing an uncooled PV cell showed a much lower efficiency.
Nitrogen vacancy diamonds have emerged as sensitive solid-state magnetic field sensors capable of producing diffraction limited and sub-diffraction field ***,for the first time,to our knowledge,we extend those measure...
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Nitrogen vacancy diamonds have emerged as sensitive solid-state magnetic field sensors capable of producing diffraction limited and sub-diffraction field ***,for the first time,to our knowledge,we extend those measurements to high-speed imaging,which can be readily applied to analyze currents and magnetic field dynamics in circuits on a microscopic *** overcome detector acquisition rate limitations,we designed an optical streaking nitrogen vacancy microscope to acquire two-dimensional spatiotemporal *** demonstrate magnetic field wave imaging with micro-scale spatial extent and~400μs temporal *** validating this system,we detected magnetic fields down to 10μT for 40 Hz magnetic fields using single-shot imaging and captured the spatial transit of an electromagnetic needle at streak rates as high as 110μm/*** design has the capability to be readily extended to full 3D video acquisition by utilizing compressed sensing techniques and a potential for further improvement of spatial resolution,acquisition speed,and *** device opens opportunities to many potential applications where transient magnetic events can be isolated to a single spatial axis,such as acquiring spatially propagating action potentials for brain imaging and remotely interrogating integrated circuits.
Topology can manifest itself in colloids when quantified by invariants like Euler characteristics of nonzero-genus colloidal surfaces, albeit spherical colloidal particles are most often studied, and colloidal particl...
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Accurate assessment of dietary intake requires improved tools to overcome limitations of current methods including user burden and measurement error. Emerging technologies such as image-based approaches using advanced...
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This paper introduces ZETA, a new MATLAB library for Zonotope-based EsTimation and fAult diagnosis of discrete-time systems. It features user-friendly implementations of set representations based on zonotopes, namely ...
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