Engaging Students Engaging Industry Engaging Enterprise

A reflective piece on how a small team of students and academics gained more awareness of their own sense of enterprise and creativity. The case study examines the phases and crisis points of the whole event process and identifies some of the key learning outcomes for all involved

Many-particle Majorana bound states: derivation and signatures in superconducting double quantum dots

We consider two interacting quantum dots coupled by standard superconductors. We derive an effective Hamiltonian, and show that over a wide parameter range a degenerate ground state can be obtained. An exotique form of Majorana bound states are supported at these degeneracies, and the system can be adiabatically tuned to a limit in which it is equivalent to the one-dimensional wire model of Kitaev. We give the form of a Majorana bound state in this system in the strong interaction limit in the many-particle picture. We also study the Josephson current in this system, and demonstrate that a double slit-like pattern emerges in the presence of an extra magnetic field. This pattern is shown to disappear with increasing interaction strength, which is able to be explained as the current being carried by chargeless Majorana modes.Comment: 13 pages, 7 figures. Updated paper includes more details regarding the derivation of the effective Hamiltonia

Optimizing the information extracted by a single qubit measurement

We consider a quantum computation that only extracts one bit of information per quantum state preparation. This is relevant for error mitigation schemes where the remainder of the system is measured to detect errors. We optimize the estimation of the expectation value of an operator by its linear decomposition into bitwise-measurable terms. We prove that optimal decompositions must be in terms of reflections with eigenvalues $\pm1$. We find the optimal reflection decomposition of a fast-forwardable operator, and show a numerical improvement over a simple Pauli decomposition by a factor $N^{0.7}$.Comment: 14 pages, 4 figure

Probability modelling to reduce decision uncertainty in environmental niche identification and driving factor analysis: CaNaSTA case studies

Hillside agro-ecosystems have a complex spatial and temporal distribution of natural resources. Farmers generally possess a vast body of knowledge about environmental resources on their farms but this knowledge is largely based on locally observable features rather than generalized knowledge. The lack of process-based knowledge concerning agro-ecosystem function creates uncertainty that obstructs sound decision-making under conditions of rising economic and ecologic pressure in many developing countries. Since the past decade, Precision Agriculture provides tools to reduce uncertainty caused by environmental variation. By describing spatial and temporal variation of the environment, Geographic Information Systems help to detect suitable crops for specific environmental niches and support farmers to find optimal management practices for their plot of land. Hence Precision Agriculture helps to raise the economic benefits of farming, ensures consistent product quality and reduces negative environmental impacts caused by inappropriate management practices. A spatial decision support system called CaNaSTA was developed to aid the decision making process of crop adoption in tropical agriculture. Using Bayesian probability statistics, CaNaSTA integrates trial data, spatial data and expert knowledge and provides maps, tables and graphs analyzing and interpreting the probability distributions of spatial phenomena. The International Centre for Tropical Agriculture (CIAT) has applied CaNaSTA to three case studies related to tropical agriculture. The first case study identifies niches for specialty coffee production, the second analyses the potential of cowpea (Vigna unguiculata (L.) Walp.) for tropical hillside environments in Colombia. Finally, Canasta was applied to a non-crop related area by performing a study of carbon concentration in tropical soils.

Active control of aircraft engine inlet noise using compact sound sources and distributed error sensors

An active noise control system using a compact sound source is effective to reduce aircraft engine duct noise. The fan noise from a turbofan engine is controlled using an adaptive filtered-x LMS algorithm. Single multi channel control systems are used to control the fan blade passage frequency (BPF) tone and the BPF tone and the first harmonic of the BPF tone for a plane wave excitation. A multi channel control system is used to control any spinning mode. The multi channel control system to control both fan tones and a high pressure compressor BPF tone simultaneously. In order to make active control of turbofan inlet noise a viable technology, a compact sound source is employed to generate the control field. This control field sound source consists of an array of identical thin, cylindrically curved panels with an inner radius of curvature corresponding to that of the engine inlet. These panels are flush mounted inside the inlet duct and sealed on all edges to prevent leakage around the panel and to minimize the aerodynamic losses created by the addition of the panels. Each panel is driven by one or more piezoelectric force transducers mounted on the surface of the panel. The response of the panel to excitation is maximized when it is driven at its resonance; therefore, the panel is designed such that its fundamental frequency is near the tone to be canceled, typically 2000-4000 Hz

Active control of aircraft engine inlet noise using compact sound sources and distributed error sensors

An active noise control system using a compact sound source is effective to reduce aircraft engine duct noise. The fan noise from a turbofan engine is controlled using an adaptive filtered-x LMS algorithm. Single multi channel control systems are used to control the fan blade passage frequency (BPF) tone and the BPF tone and the first harmonic of the BPF tone for a plane wave excitation. A multi channel control system is used to control any spinning mode. The multi channel control system to control both fan tones and a high pressure compressor BPF tone simultaneously. In order to make active control of turbofan inlet noise a viable technology, a compact sound source is employed to generate the control field. This control field sound source consists of an array of identical thin, cylindrically curved panels with an inner radius of curvature corresponding to that of the engine inlet. These panels are flush mounted inside the inlet duct and sealed on all edges to prevent leakage around the panel and to minimize the aerodynamic losses created by the addition of the panels. Each panel is driven by one or more piezoelectric force transducers mounted on the surface of the panel. The response of the panel to excitation is maximized when it is driven at its resonance; therefore, the panel is designed such that its fundamental frequency is near the tone to be canceled, typically 2000-4000 Hz

Validation of Floating Node Method Using Three-Point Bend Doubler Under Quasi-Static Loading

The NASA Advanced Composite Project (ACP), an industry/government/university partnership, has embarked upon the task of developing technology that can aid in reducing the time line for structural certification of aircraft composite parts using a combination of technologies, one of which is high fidelity damage progression computational methods. Phase II of this project included a task for validating an approach based on the Floating Node Method combined with Directional Cohesive Elements (FNM-DCZE). This paper discusses predicted damage onset and growth in a three-point bend doubler specimen compared to experimental results. Sensitivity of the simulations to mesh refinement as well as key material properties and thermal effects are studied and reported. Overall, qualitative results suggest the main aspects of the damage progression have been captured, with the simulated damage morphology and sequence of events resembling closely what was observed experimentally. Quantitatively, the first load-peak is predicted. However, the re-loading observed in the experiments, after the first load peak, is not captured numerically, suggesting further investigation may be worth pursuing

Direct injection liquid chromatography-tandem mass spectrometry as a sensitive and high-throughput method for the quantitative surveillance of antimicrobials in wastewater

Environmental antimicrobial pollution and antimicrobial resistance pose a threat to environmental and human health. Wastewater analysis has been identified as a promising tool for antimicrobial monitoring and the back-estimation of antimicrobial consumption, but current pretreatment methods are tedious and complicated, limiting their scope for high-throughput analysis. A sensitive direct injection method for the quantification of 109 antimicrobials and their metabolites in wastewater samples was developed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The method was validated for both wastewater influent and effluent in terms of specificity, calibration range, matrix effect, filtration loss, accuracy, precision, limit of detection (LOD), and limit of quantification (LOQ). Most analytes achieved calibration of R2 &gt; 0.99, and the calibration range was from 0.0002 to 150 μg L−1. Recoveries ranged consistently between ~50 % and ~100 % and losses were attributed to sample filtration. Method LOQs were determined as low as 0.0003 μg L−1, and acceptable accuracy (75 %–125 %) and precision (within 25 %) were achieved for &gt;90 % of the analytes. The method was subsequently further assessed using wastewater of raw influent and treated effluent collected from 6 Australian wastewater treatment plants in 2021. In total, 37 analytes were detected in influent and 22 in effluent. Most of them could be quantified at concentrations ranging from 0.0053 to 160 μg L−1, with benzalkonium chloride-C12, amoxicilloic acid, and cephalexin detected at the highest concentrations. The current study provides a straightforward analytical method for antimicrobial monitoring in wastewater with a fast and simple pretreatment procedure.</p