Name: large scale energy efficient sensor network routing using a quantum processor unit
Uploaded: 2023-09-08T14:35:00
Description: Watch this Scientific Journal Video about Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit at JoVE.com

The work is supported by the Engineering and Physical Sciences Research Council of the UK (EPSRC) Grant number EP/W032643/1.

1. Setting up Dwave Ocean Environment
<ol>
	<li>Download and install the ocean tools from the link: https://docs.ocean.dwavesys.com/en/stable/overview/install.html
	<ol>
		<li>At the terminal, type python -m venv ocean.</li>
		<li>At the terminal, type . ocean/bin/activate, as shown in Figure 1.</li>
		<li>At the terminal, type git clone https://github.com/dwavesystems/dwave-ocean-sdk.git 
		Next, type&#160;cd...

<ol>
	<li>Chen, J., Date, P., Chancellor, N., Atiquazzaman, M., Cormac, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Controller-based+energy-aware+wireless+sensor+network+routing+using+quantum+algorithms.">Controller-based energy-aware wireless sensor network routing using quantum algorithms.</a> IEEE Transactions on Quantum Engineering. 3, 1-12 (2022).</li><li>Lin, H., Uster, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Exact+and+heuristic+algorithms+for+data-gathering+cluster-based+wireless+sensor+network+design+problem.">Exact and heuristic algorithms for data-gathering cluster-based wireless sensor network design problem.</a> IEEE/ACM Transactions on Networking. 22 (3), 903-916 (2014).</li><li>Zhou, Y., Wang, N., Xiang, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clustering+hierarchy+protocol+in+wireless+sensor+networks+using+an+improved+PSO+algorithm.">Clustering hierarchy protocol in wireless sensor networks using an improved PSO algorithm.</a> IEEE Access. 5, 2241-2253 (2017).</li><li>Seah, W. K. G., Mak, N. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+long+is+the+lifetime+of+a+wireless+sensor+network.">How long is the lifetime of a wireless sensor network.</a> , 763-770 (2009).</li><li>Salahud din, M., Rehman, M. A. U., Ullah, R., Park, C., Kim, B. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Towards+network+lifetime+enhancement+of+resource+constrained+IoT+devices+in+heterogeneous+wireless+sensor+networks+Sensors.">Towards network lifetime enhancement of resource constrained IoT devices in heterogeneous wireless sensor networks Sensors.</a> 20, 4156 (2020).</li><li>Wu, W., Xiong, N., Wu, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Improved+clustering+algorithm+based+on+energy+consumption+in+wireless+sensor+networks.">Improved clustering algorithm based on energy consumption in wireless sensor networks.</a> IET Network. 6 (3), 7-53 (2017).</li><li>Kumar, N., Kumar, V., Ali, T., Ayaz, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prolong+network+lifetime+in+the+wireless+sensor+networks:+An+improved+approach.">Prolong network lifetime in the wireless sensor networks: An improved approach.</a> Arabian Journal for Science and Engineering. 46, 3631-3651 (2021).</li><li>Faris, H., Aljarah, I., Al-Betar, M. A., Mirjalili, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Grey+wolf+optimizer:+A+review+of+recent+variants+and+applications.">Grey wolf optimizer: A review of recent variants and applications.</a> Neural Computing and Applications. 30, 413-435 (2018).</li><li>Kaur, J., Arifkhan, M., Iftikhar, M., Imran, M., Haq, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Machine+learning+techniques+for+5G+and+beyond.">Machine learning techniques for 5G and beyond.</a> IEEEAccess. 9, 23472-23488 (2021).</li><li>Shor, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Polynomial-time+algorithms+for+prime+factorization+and+discrete+logarithms+on+a+quantum+computer.">Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer.</a> SIAMJournalonComputing. 26 (5), 1484-1509 (1997).</li><li>Qabouche, H., Sahel, A., Badri, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hybrid+energy+efficient+static+routing+protocol+for+homogeneous+and+heterogeneous+large+scale+WSN.">Hybrid energy efficient static routing protocol for homogeneous and heterogeneous large scale WSN.</a> Wireless Networks. 27, 575-587 (2021).</li><li>Farooq, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=POWER:+probabilistic+weight-based+energy-efficient+cluster+routing+for+large-scale+wireless+sensor+networks.">POWER: probabilistic weight-based energy-efficient cluster routing for large-scale wireless sensor networks.</a> The Journal of Supercomputing. 78, 12765-12791 (2022).</li><li>Maddams, W. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+scope+and+limitations+of+curve+fitting.">The scope and limitations of curve fitting.</a> Applied Spectroscopy. 34 (3), 245-267 (1980).</li><li>Wang, X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+dynamic+opportunistic+routing+protocol+for+asynchronous+duty-cycled+WSNs.">A dynamic opportunistic routing protocol for asynchronous duty-cycled WSNs.</a> IEEE Transactions on Sustainable Computing. , (2023).</li><li>Ismail, A. S., Wang, X., Hawbani, A., Alsamhi, S., Aziz, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Routing+protocols+classification+for+underwater+wireless+sensor+networks+based+on+localization+and+mobility.">Routing protocols classification for underwater wireless sensor networks based on localization and mobility.</a> Wireless Networks. 28, 797-826 (2022).</li><li>Garcia-Martin, E., Rodrigues, C. F., Riley, G., Grahn, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Estimation+of+energy+consumption+in+machine+learning.">Estimation of energy consumption in machine learning.</a> Journal of Parallel Distributed Computing. 134, 75-88 (2019).</li><li>Egger, D. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantum+computing+for+finance:+State-of-the-art+and+future+prospects.">Quantum computing for finance: State-of-the-art and future prospects.</a> IEEE Transactions on Quantum Engineering. 1, 1-24 (2020).</li><li>Rasool, R. U., Ahmad, H. F., Rafique, W., Qayyum, A., Qadir, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantum+computing+for+healthcare+:+A+review.">Quantum computing for healthcare : A review.</a> TechRxiv. , (2021).</li></ol>

The current state-of-the-art commercial quantum processor can be used in computational problems of any network topology1. Quantum processor application is not constrained by the number of physical qbits any of the quantum processors has been able to implement. 
In sensor network lifetime prolongation design, the results show an advancement in method to achieve even longer network life by using a quantum processor. The results imply that quantum advantage is ready to be ...

Energy conservation in sensor networks has been a very critical issue in design1. Classical methods normally tackle the problem using an ad hoc approach2,3,4,5,6. That said, these methods emulate the sensor nodes as individually managed intelligent assets that could also cooperate to serve both the interests of the individual and the community. Due to the volatile environment where sensors work, in some works, random algorithms are introduced in order to capture the environmental uncertainties, while in others, bio-intelligence is borrowed to devise heuristic algorithms that could achieve common sense acceptable results7. To illustrate further, for those random algorithms, for one hand, environmental uncertainties might not be as random as the random sequence generated by a classical CPU, for the other hand, even if the environmental uncertainties are absolutely random, they could not be captured by the random process simulator generated by classical CPU; for those bio-intelligence algorithms, first of all, no rigorous mathematical analysis has been derived to make a conceptual proof work, secondly, the convergence to truth or the error tolerance boundary can only be configured given an informed ground truth - though a significant amount of works in literature have demonstrated to some extent these heuristic algorithms work, for one thing, these algorithms are analyzed (not simulated) against well-defined use case scenarios, they stops at certain criteria that are still worth pondering in further research, for another, as said before, a majority of the algorithms have not been validated against software simulation that can be more readily deployed in the microprocessors that make a sensor into its being8.
We do not consider machine learning (ML) here because it needs to employ data analytics which requires a relatively large volume of computational power that is not portable in sensor devices9.
To address the above-mentioned concerns, we provide a hybrid quantum algorithm. The algorithm is hybrid in that the cluster head selection mechanism is implemented using a classical random algorithm during the routing computations conducted using a quantum processor once the network topology is set up. The method is justified as follows: (1) As discussed in the first paragraph regarding the environmental uncertainties, we do not want to endeavor further to apply a quantum sequence generator to capture the environmental dynamic because it might be historically traceable. The environmental dynamic that can be historically traceable has been justified by various machine learning research works in network science. For the current stage, we stay with the classical approach. (2) The exact method that relies on abstract mathematical analysis guarantees to arrive at ground truth. Quantum experimental physics has so far been sophisticatedly supported by physical mathematics. Moreover, algorithm applications like the Shor algorithm10 have existed to prove this rounded theory.
An adequate amount of literature survey is provided below for comparison. The HEESR protocol proposed11 has demonstrable merits in results, but the authors have specified the simulation configuration parameters well, for example, the exact random distribution function of the node position, the proper justification of the cluster head percentage p (0.2%), and the scaling parameter for distribution of energy level (1-2 joules) among nodes a_i. It prohibited the author from proceeding further to duplicate the experiments and conduct the comparison. The Power routing mechanism12 employs the curve fitting method to approximate converged continuous functions from discrete data sets obtained from unspecified sample space for determinants that impact the decision process of the optimal network routing. The curve fitting method13 requires prior information on the network topology. Real circumstances might not have prior information readily available. Even when prior information exists, network topology might not be regular enough to be able to be mapped onto fitting curves that are able to facilitate derivable computation. Following the same logic, DORAF protocol14 has not justified how and why to borrow the Boltzmann function and Logistic Function to approximate the network determinants. Ismail et al.15 have provided a sound reference for future research endeavors into energy-efficient routing protocol design in the underwater network.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
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			<td>Dell Laptop</td>
			<td>Dell</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>Ubuntu 18.04.6 LTS</td>
			<td>Canonical Ltd</td>
			<td>18.04.6 LTS</td>
			<td></td>
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		<tr>
			<td>Python3.8</td>
			<td>Python Software Foundation</td>
			<td>3.8.0</td>
			<td></td>
		</tr>
		<tr>
			<td>Dwave QPU</td>
			<td>Dwave</td>
			<td>https://docs.ocean.dwavesys.com/en/stable/overview/install.html</td>
			<td></td>
		</tr>
	</tbody>
</table>

large scale energy efficient sensor network routing using a quantum processor unit

The sensor network energy conservation method, which is a usage hybrid of a classical computer and quantum processor, has proved to perform better than the heuristic algorithm using a classical computer. In this manuscript, the technical context for the significance of the method is presented and justified. Then the experimental steps are demonstrated in an operational sequence with illustrations if ever needed. The method has been validated by positive results across a randomly generated sample set of network topologies. The successful experimental results of this method have provided a better approach for sensor network lifetime maximization problems and demonstrated that the current state of art quantum processor has been able to solve large practical engineering problems with merits that override current methods in the literature. In other words, quantum advantage can be exploited to best efforts. It has gone beyond the stage of proof of concept to proof of feasibility.

Results from one run sample are shown in Table 2, Table 3, and Table 4. The detailed datasets for the three batches of data are available in the Supplementary Data 1 folder.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td colspan="3">Dataset 1</td>
		</tr>
		<tr>
			<td>198 nodes in a circular area with a radius of 50m</td>
			<td>Hybrid Quantum Algorithm</td>
			<td>A...

Watch this Scientific Journal Video about Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit at JoVE.com

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

This study provides a method to use a quantum processor unit to compute the routes for various traffic dynamics that work to outperform classical methods in literature to maximize network lifetime.

The sensor network energy conservation method, which is a usage hybrid of a classical computer and quantum processor, has proved to perform better than ...

This protocol proves to be more energy-wise than legacy protocols. From a content computing research perspective, this protocol shows that current bottleneck of noisy qubit issue does not hold ceiling for the commerciality of content computing technology. This techniques demonstrates the feasibility of applying current state art content computing methods to network problems.Furthermore, it presents the merits of applying content computing methods to network problems over legacy methods. To begin, download and install the Ocean tools from the given link. At the terminal, type python space minus m space venv space ocean then ocean/bin/activate.Next, type git space clone space https:github.com/dwavesystems/dwave-ocean-sdk. git then cd space dwave-ocean-sdk, followed by python space setup. py space install.After downloading and installing Cplex, at the terminal, type pip space install space cplex. Using Python programming notation script, set up the experiment configuration parameters. Once the script is executed, the underlying language will process to store the variables in RAM.Next, create the Python scripts to generate 198 sensor node 2D positions that are equally scattered into six sectors, and divide the circular area with a radius of 50 meters. Within each sector, ensure that the 33 sensor nodes are scattered randomly by a normal distribution. Save the 2D positions into text files by each sector under the name spelling rule as posdata with single quotation mark, plus sector underscore no plus txt with single quotation.Segment the circular area with a radius of 50 meters into six sectors. For sector index I, set the pole length for the jth sensor node by entering the indicated command. If the sector index is L, set the angular value for the jth sensor node.Then set the Cartesian coordinates of the jth sensor node in the ith sector. To prepare the initial energy levels for all 198 sensor nodes, divide them equally, allocating an initial energy of 0.5 joules to half of the sensor nodes and one joule to the other half. Proceed to create an array to store each node's energy level and use a loop to assign cells sequenced in even numbers the value of one and those sequenced in odd numbers the value of 0.5.Next, prepare a functional script to select the cluster head. For each sensor node, attain a random number between zero and one, threshold_rm equal to random. random bracket.If threshold_RM is less than t_n, select this sensor node as the cluster head. For each noncluster_head node, select the closest cluster head sensor node to it as its cluster head. Prepare the command lines to calculate the energy depletion process across the whole network for this round.Finally, calculate the required transmission round metrics. To prepare a hybrid quantum algorithm script, run the selection procedure in a loop to ensure that the amount of cluster heads is six. Following this, for each of the non-cluster_head_valid nodes, calculate the distance to each selected cluster head and assign it to the cluster head whose cluster size hasn't exceeded six and where the distance value was smallest.Next, prepare a sub-function script where the rooting optimization problem per cluster is formed and submitted to the Dwave API. Using Python script, calculate the energy depletion across the entire network to quantitatively evaluate the algorithm by network lifetime in terms of the number of transmission rounds. Then record the moment when the first node is drained out and when half the nodes are drained out.In this study, it was observed that the hybrid quantum algorithm has more efficiency than the advanced_leach algorithm. The time complexity of the hybrid quantum algorithm and the hybrid quantum algorithm that complies with the advanced_leach are also shown here. These methods can be applied to other systems in objective optimization.For instance, machine-to-machine communication in manufacturing industry. According to content physics, the in content theory has paved issues for each fixed game setting. It can lead to new research in social science and economy.

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Engineering

Terahertz Microfluidic Sensing Using a Parallel-plate Waveguide Sensor

Refractive index (RI) sensing is a powerful noninvasive and label-free sensing technique for the identification, detection and monitoring of microfluidic samples with a wide range of possible sensor designs such as interferometers and resonators 1,2. Most of the existing RI sensing applications focus on biological materials in aqueous solutions in visible and IR frequencies, such as DNA hybridization and genome sequencing. At terahertz frequencies, applications include quality control, monitoring of industrial processes and sensing and detection applications involving nonpolar materials.
Several potential designs for refractive index sensors in the terahertz regime exist, including photonic crystal waveguides 3, asymmetric split-ring resonators 4, and photonic band gap structures integrated into parallel-plate waveguides 5. Many of these designs are based on optical resonators such as rings or cavities. The resonant frequencies of these structures are dependent on the refractive index of the material in or around the resonator. By monitoring the shifts in resonant frequency the refractive index of a sample can be accurately measured and this in turn can be used to identify a material, monitor contamination or dilution, etc.
The sensor design we use here is based on a simple parallel-plate waveguide 6,7. A rectangular groove machined into one face acts as a resonant cavity (Figures 1 and 2). When terahertz radiation is coupled into the waveguide and propagates in the lowest-order transverse-electric (TE1) mode, the result is a single strong resonant feature with a tunable resonant frequency that is dependent on the geometry of the groove 6,8. This groove can be filled with nonpolar liquid microfluidic samples which cause a shift in the observed resonant frequency that depends on the amount of liquid in the groove and its refractive index 9.
Our technique has an advantage over other terahertz techniques in its simplicity, both in fabrication and implementation, since the procedure can be accomplished with standard laboratory equipment without the need for a clean room or any special fabrication or experimental techniques. It can also be easily expanded to multichannel operation by the incorporation of multiple grooves 10. In this video we will describe our complete experimental procedure, from the design of the sensor to the data analysis and determination of the sample refractive index.

The procedure for implementing a refractive index sensor for terahertz frequencies based on a grooved parallel-plate waveguide geometry is described here. The method yields a measurement of the refractive index of a small volume of liquid through monitoring of the shift in the resonant frequency of the waveguide structure

Refractive index (RI) sensing is a powerful noninvasive and label-free sensing technique for the identification, detection and monitoring of microfluidic ...

Analysis of Contact Interfaces for Single GaN Nanowire Devices

Single GaN nanowire (NW) devices fabricated on SiO2 can exhibit a strong degradation after annealing due to the occurrence of void formation at the contact/SiO2 interface. This void formation can cause cracking and delamination of the metal film, which can increase the resistance or lead to a complete failure of the NW device. In order to address issues associated with void formation, a technique was developed that removes Ni/Au contact metal films from the substrates to allow for the examination and characterization of the contact/substrate and contact/NW interfaces of single GaN NW devices. This procedure determines the degree of adhesion of the contact films to the substrate and NWs and allows for the characterization of the morphology and composition of the contact interface with the substrate and nanowires. This technique is also useful for assessing the amount of residual contamination that remains from the NW suspension and from photolithographic processes on the NW-SiO2 surface prior to metal deposition. The detailed steps of this procedure are presented for the removal of annealed Ni/Au contacts to Mg-doped GaN NWs on a SiO2 substrate.

A technique was developed that removes Ni/Au contact metal films from their substrate to allow for the examination and characterization of the contact/substrate and contact/NW interfaces of single GaN nanowire devices.

Single GaN nanowire (NW) devices fabricated on SiO2 can exhibit  a strong degradation after annealing due to the  occurrence of void formation at the ...

Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages

Synchrotron radiation micro-tomography (SR&#181;T) is a non-destructive three-dimensional (3D) imaging technique that offers high flux for fast data acquisition times with high spatial resolution. In the electronics industry there is serious interest in performing failure analysis on 3D microelectronic packages, many which contain multiple levels of high-density interconnections. Often in tomography there is a trade-off between image resolution and the volume of a sample that can be imaged. This inverse relationship limits the usefulness of conventional computed tomography (CT) systems since a microelectronic package is often large in cross sectional area 100-3,600 mm2, but has important features on the micron scale. The micro-tomography beamline at the Advanced Light Source (ALS), in Berkeley, CA USA, has a setup which is adaptable and can be tailored to a sample&#39;s properties, i.e., density, thickness, etc., with a maximum allowable cross-section of 36 x 36 mm. This setup also has the option of being either monochromatic in the energy range ~7-43 keV or operating with maximum flux in white light mode using a polychromatic beam. Presented here are details of the experimental steps taken to image an entire 16 x 16 mm system within a package, in order to obtain 3D images of the system with a spatial resolution of 8.7 &#181;m all within a scan time of less than 3 min. Also shown are results from packages scanned in different orientations and a sectioned package for higher resolution imaging. In contrast a conventional CT system would take hours to record data with potentially poorer resolution. Indeed, the ratio of field-of-view to throughput time is much higher when using the synchrotron radiation tomography setup. The description below of the experimental setup can be implemented and adapted for use with many other multi-materials.

For this study synchrotron radiation micro-tomography, a non-destructive three-dimensional imaging technique, is employed to investigate an entire microelectronic package with a cross-sectional area of 16 x 16 mm. Due to the synchrotron&#39;s high flux and brightness the sample was imaged in just 3 min&#160;with an 8.7 &#181;m spatial resolution.

Synchrotron radiation micro-tomography (SR&#181;T) is a non-destructive three-dimensional (3D) imaging technique that offers high flux for fast data ...

How to Build a Vacuum Spring-transport Package for Spinning Rotor Gauges

The spinning rotor gauge (SRG) is a high-vacuum gauge often used as a secondary or transfer standard for vacuum pressures in the range of 1.0 x 10-4 Pa to 1.0 Pa. In this application, the SRGs are frequently transported to laboratories for calibration. Events can occur during transportation that change the rotor surface conditions, thus changing the calibration factor. To assure calibration stability, a spring-transport mechanism is often used to immobilize the rotor and keep it under vacuum during transport. It is also important to transport the spring-transport mechanism using packaging designed to minimize the risk of damage during shipping. In this manuscript, a detailed description is given on how to build a robust spring-transport mechanism and shipping container. Together these form a spring-transport package. The spring-transport package design was tested using drop-tests and the performance was found to be excellent. The present spring-transport mechanism design keeps the rotor immobilized when experiencing shocks of several hundred g (g = 9.8 m/sec2 and is the acceleration due to gravity), while the shipping container assures that the mechanism will not experience shocks greater than about 100 g during common shipping mishaps (as defined by industry standards).

Here we describe how to build a robust spring-transport mechanism for a spinning rotor gauge. This device securely immobilizes the rotor and keeps it under vacuum during transportation. We also describe packaging that minimizes the risk of damage during transport. Tests show our design works for typical shocks during transport.

The spinning rotor gauge (SRG) is a high-vacuum gauge often used as a secondary or transfer standard for vacuum pressures in the range of 1.0 x 10-4 Pa to ...

Resonance Fluorescence of an InGaAs Quantum Dot in a Planar Cavity Using Orthogonal Excitation and Detection

The ability to perform simultaneous resonant excitation and fluorescence detection is important for quantum optical measurements of quantum dots (QDs). Resonant excitation without fluorescence detection &#8211; for example, a differential transmission measurement &#8211; can determine some properties of the emitting system, but does not allow applications or measurements based on the emitted photons. For example, the measurement of photon correlations, observation of the Mollow triplet, and realization of single photon sources all require collection of the fluorescence. Incoherent excitation with fluorescence detection &#8211; for example, above band-gap excitation &#8211; can be used to create single photon sources, but the disturbance of the environment due to the excitation reduces the indistinguishability of the photons. Single photon sources based on QDs will have to be resonantly excited to have high photon indistinguishability, and simultaneous collection of the photons will be necessary to make use of them. We demonstrate a method to resonantly excite a single QD embedded in a planar cavity by coupling the excitation beam into this cavity from the cleaved face of the sample while collecting the fluorescence along the sample&#39;s surface normal direction. By carefully matching the excitation beam to the waveguide mode of the cavity, the excitation light can couple into the cavity and interact with the QD. The scattered photons can couple to the Fabry-Perot mode of the cavity and escape in the surface normal direction. This method allows complete freedom in the detection polarization, but the excitation polarization is restricted by the propagation direction of the excitation beam. The fluorescence from the wetting layer provides a guide to align the collection path with respect to the excitation beam. The orthogonality of the excitation and detection modes enables resonant excitation of a single QD with negligible laser scattering background.

Resonant excitation of a single self-assembled quantum dot can be achieved using an excitation mode orthogonal to the fluorescence collection mode. We demonstrate a method using the waveguide and Fabry-Perot modes of a planar microcavity surrounding the quantum dots. The method allows complete freedom in the detection polarization.

The ability to perform simultaneous resonant excitation and fluorescence detection is important for quantum optical measurements of quantum dots (QDs). ...

Generation and Coherent Control of Pulsed Quantum Frequency Combs

We present a method for the generation and coherent manipulation of pulsed quantum frequency combs. Until now, methods of preparing high-dimensional states on-chip in a practical way have remained elusive due to the increasing complexity of the quantum circuitry needed to prepare and process such states. Here, we outline how high-dimensional, frequency-bin entangled, two-photon states can be generated at a stable, high generation rate by using a nested-cavity, actively mode-locked excitation of a nonlinear micro-cavity. This technique is used to produce pulsed quantum frequency combs. Moreover, we present how the quantum states can be coherently manipulated using standard telecommunications components such as programmable filters and electro-optic modulators. In particular, we show in detail how to accomplish state characterization measurements such as density matrix reconstruction, coincidence detection, and single photon spectrum determination. The presented methods form an accessible, reconfigurable, and scalable foundation for complex high-dimensional state preparation and manipulation protocols in the frequency domain.

A protocol is presented for the practical generation and coherent manipulation of high-dimensional frequency-bin entangled photon states using integrated micro-cavities and standard telecommunications components, respectively.

We present a method for the generation and coherent manipulation of pulsed quantum frequency combs. Until now, methods of preparing high-dimensional ...

An Efficient Method for Selective Desalination of Radioactive Iodine Anions by Using Gold Nanoparticles-Embedded Membrane Filter

Here, we demonstrate a detail protocol for the preparation of nanomaterials-embedded composite membranes and its application to the efficient and ion-selective removal of radioactive iodines. By using citrate-stabilized gold nanoparticles (mean diameter: 13 nm) and cellulose acetate membranes, gold nanoparticle-embedded cellulose acetate membranes (Au-CAM) have easily been fabricated. The nano-adsorbents on Au-CAM were highly stable in the presence of high concentration of inorganic salts and organic molecules. The iodide ions in aqueous solutions could rapidly be captured by this engineered membrane. Through a filtration process using an Au-CAM containing filter unit, excellent removal efficiency (&gt;99%) as well as ion-selective desalination result was achieved in a short time. Moreover, Au-CAM provided good reusability without significant decrease of its performances. These results suggested that the present technology using the engineered hybrid membrane will be a promising process for the large-scale decontamination of radioactive iodine from liquid wastes.

An efficient method for the rapid and ion-selective desalination of radioactive iodine in several aqueous solutions is described by using gold nanoparticles-immobilized cellulose acetate membrane filters.

Here, we demonstrate a detail protocol for the preparation of nanomaterials-embedded composite membranes and its application to the efficient and ...

Measuring Sub-23 Nanometer Real Driving Particle Number Emissions Using the Portable DownToTen Sampling System

The current particle size threshold of the European Particle Number (PN) emission standards is 23 nm. This threshold could change because future combustion engine vehicle technology may emit large amounts of sub-23 nm particles. The Horizon 2020 funded project DownToTen (DTT) developed a sampling and measurement method to characterize particle emissions in this currently unregulated size range. A PN measurement system was developed based on an extensive review of the literature and laboratory experiments testing a variety of PN measurement and sampling approaches. The measurement system developed is characterized by high particle penetration and versatility, which enables the assessment of primary particles, delayed primary particles, and secondary aerosols, starting from a few nanometers in diameter. This paper provides instruction on how to install and operate this Portable Emission Measurement System (PEMS) for Real Drive Emissions (RDE) measurements and assess particle number emissions below the current legislative limit of 23 nm.

Presented here is the DownToTen (DTT) portable emission measurement system to assess real driving automotive emissions of sub-23 nm particles.

The current particle size threshold of the European Particle Number (PN) emission standards is 23 nm. This threshold could change because future ...

Simulating Imaging of Large Scale Radio Arrays on the Lunar Surface

In recent years there has been a renewed interest in returning to the Moon for reasons both scientific and exploratory in nature. The Moon provides the perfect training ground for building large scale bases that one may apply to other planets like Mars. The existence of a radio quiet zone on the lunar far side has promise for early universe studies and exoplanet searches, while the near side provides a stable base that may be used to observe low frequency emissions from Earth&#8217;s magnetosphere that may help gauge its response to incoming space weather. The construction of a large-scale radio array would provide large scientific returns as well as acting as a test of humanity&#8217;s ability to build structures on other planets. This work focuses on simulating the response of small to large-scale radio arrays on the Moon consisting of hundreds or thousands of antennas. The response of the array is dependent on the structure of the emission along with the configuration and sensitivity of the array. A set of locations are selected for the simulated radio receivers, using Digital Elevation Models from the Lunar Orbiter Laser Altimeter instrument on Lunar Reconnaissance Orbiter to characterize the elevation of the receiver locations. A custom Common Astronomy Software Applications code is described and used to process the data from the simulated receivers, aligning the lunar and sky coordinate frames using SPICE to ensure the proper projections are used for imaging. This simulation framework is useful for iterating array design for imaging any given scientific target in a small field of view. This framework does not currently support all sky imaging.

A simulation framework for testing the imaging capabilities of large-scale radio arrays on the lunar surface is presented. Major noise components are discussed, and a software pipeline is walked through with details on how to customize it for novel scientific uses.

In recent years there has been a renewed interest in returning to the Moon for reasons both scientific and exploratory in nature. The Moon provides the ...

Performing In Situ Closed-Cell Gas Reactions in the Transmission Electron Microscope

Gas reactions studied by in situ electron microscopy can be used to capture the real-time morphological and microchemical transformations of materials at length scales down to the atomic level. In situ closed-cell gas reaction (CCGR) studies performed using (scanning) transmission electron microscopy (STEM) can separate and identify localized dynamic reactions, which are extremely challenging to capture using other characterization techniques. For these experiments, we used a CCGR holder that utilizes microelectromechanical systems (MEMS)-based heating microchips (hereafter referred to as &#34;E-chips&#34;). The experimental protocol described here details the method for performing in situ gas reactions in dry and wet gases in an aberration-corrected STEM. This method finds relevance in many different materials systems, such as catalysis and high-temperature oxidation of structural materials at atmospheric pressure and in the presence of various gases with or without water vapor. Here, several sample preparation methods are described for various material form factors. During the reaction, mass spectra obtained with a residual gas analyzer (RGA) system with and without water vapor further validates gas exposure conditions during reactions. Integrating an RGA with an in situ CCGR-STEM system can, therefore, provide critical insight to correlate gas composition with the dynamic surface evolution of materials during reactions. In situ/operando studies using this approach allow&#160;for detailed investigation of the fundamental reaction mechanisms and kinetics that occur at specific environmental conditions (time, temperature, gas, pressure), in real-time, and at high spatial resolution.

Performing In Situ Closed-Cell Gas Reactions in the Transmission Electron Microscope

Here, we present a protocol for performing in situ TEM closed-cell gas reaction experiments while detailing several commonly used sample preparation methods.

Gas reactions studied by in situ electron microscopy can be used to capture the real-time morphological and microchemical transformations of materials at ...