1,500 research outputs found
Adult migration, population replenishment and geographic structure for snapper in SA
No full textFowler, A.J, Gillanders, B.M and Hall, K.C
Notes on the population structure of the piked spurdog (Squalus megalops) in southeastern Australia
No full textOpportunistic sampling suggested a complex population structure for Squalus megalops in southeastern Australia. A total of 929 sharks were analyzed. The sex ratio was biased towards females and there was sexual size dimorphism, with females attaining a larger maximum size than males. Individual analysis of selected fishing shots suggested that S. megalops had a complex population structure, and was segregated by sex, size and breeding condition. Small females and males segregated from large females. In addition, large females in the first year of pregnancy seemed to be separated from those in the second year of pregnancy.J.M. Braccini, B.M. Gillanders, T.I. Walke
What can migratory shorebirds tell us about the quality of intertidal mudflats in Australia?
No full textWhat can migratory shorebirds tell us about the quality of intertidal mudflats in Australia?
No full textWhat can migratory shorebirds tell us about the quality of intertidal mudflats in Australia?
No full textOptimizing quantum error correction for superconducting qubit processors
No full textThe theory of quantum mechanics describes many phenomena that may initially seem to be counter-intuitive and, in some cases, impossible, given the understanding of classical mechanics that most of us are more intimately familiar with. Following its initial introduction, there was a great deal of debate among scientists regarding the predictions made by this theory. The strange nature of quantum mechanics has led to many memorable quotes and the use of “spooky” to describe some of these predictions. Since its initial introduction, quantum mechanics has been rigorously tested and has proven to be quite a successful theory. Quantum mechanics has found many different applications and has led to the existence of devices and technologies we use daily. Another potential application of quantum mechanics is quantum computation, which Richard Feynman first put forward as an idea in 1982. Quantum computers have the potential to solve specific problems that can be infeasible for even the most powerful (classical) supercomputers and have potential applications in many different areas, such as quantum chemistry, cryptography, and optimization. However, performing a quantum computation is challenging and requires overcoming the inherent fragility of quantum systems. Storing information in a quantum system requires it to be well isolated from the environment to avoid any unwanted interactions that can corrupt the stored data. Unfortunately, at the same time, we need the ability to control this system, make it interact with other such systems, and ultimately measure it for us to perform an actual computation. This is a universal issue and all of the systems we have so far developed to be used as quantum bits (qubits) have been plagued by noise. Each operation applied to the qubit or even the act of leaving the qubit idling for some time generally leads to an error with a non-negligible probability. The impact of this noise has so far prevented quantum computers from performing any practical computation. While substantial efforts have been made to reduce these physical error rates over the past several years, we are still far from the universal fault-tolerant quantum computers we ultimately strive for. Fortunately, quantum error correction can help us reach the low error rates necessary for quantum computers to realize their potential applications in the future. This can be achieved by storing the quantum information in a logical qubit instead of a noisy physical one. When using a stabilizer code, which will be the focus of this dissertation, this logical information is distributed over many (noisy) physical qubits, referred to as data qubits. Another set of qubits, the so-called ancilla qubits, is used to perform indirect parity measurements, which do not destroy the stored information but give some information about whether an error has occurred. We then try to interpret this information to identify what errors have happened and correct them, which is done by a classical algorithm referred to as the decoder. Increasing the number of physical qubits used to encode the logical qubits allows more physical errors to be detected and corrected. The number of correctable errors is captured by the distance of the code, defined as the minimum number of physical single-qubit errors that constitute a logical error. One of the critical properties of error correction is the ability to reduce the logical error rate by increasing the code distance, which requires the physical error rates to be below some threshold value. The valiant experimental effort over the years has led to several recent experiments that implement various error-correcting codes and demonstrate the reduction of the error rates promised by error correction. In particular, these experiments (and the experiments leading up to them) identified several noise sources that had not been explored in sufficient detail and could significantly impact the logical performance of the code. In this dissertation, we explore the impact of the noise encountered in transmon-qubit devices on the performance of error-correcting codes, namely the surface code. Transmon qubits are, in practice, multi-level systems, and only the lowest two energy levels are used for computation. Unfortunately, they are also weakly anharmonic, leading to the applied operations having some probability of exciting the qubit outside of this computational subspace, referred to as a leakage error. We explore the impact of leakage in both simulations and experiments and develop schemes to mitigate it. We also consider other approaches to improve the logical performance or to reduce unwanted interactions. In Chapter 2, we develop a realistic model of leakage induced by the two-qubit gates between flux-tunable transmon qubits. We show that leaked qubits effectively spread errors on their neighboring qubits, which are then detected by the parity measurements. We show that a Hidden Markov model can detect the increased error rate due to leakage. This enables us to post-select out runs during which any qubit has leaked to restore the code performance. Unfortunately, post-selection is ultimately not scalable. Instead, it is desirable to have operations that return leaked qubits to the computational subspace. These operations are called leakage-reduction units and convert leakage into a regular error. In Chapter 3, we propose a leakage-reduction scheme, which does not require any overhead in the time needed to perform the parity measurements or an overhead in the quantum hardware. For data qubits, we propose an operation that transfers the leakage to a dedicated readout resonator, where it can quickly decay. This operation is designed to not disturb the computational states, allowing it to be applied unconditionally. For the ancilla qubit, we use the fact that measurements can determine if a qubit is in the leaked state. We then apply a conditional operation to return the qubit to the computational subspace whenever it is measured to be leaked. Using detailed density-matrix simulation, we show that this scheme can be easily implemented to remove qubit leakage from the system, mitigating its impact on the logical performance of the code. In Chapter 4, we realize the data-qubit leakage reduction unit in an experiment and show it can also be used to remove ancilla-qubit leakage, removing the need for fast conditional operations and readout that distinguishes the leaked states. We show that these operations can remove most of the leaked population in about a hundred nanoseconds while having a negligible impact on the computational subspace. We also demonstrate that these operations decrease the number of observed errors by a two-qubit parity check, showing that the effect of leakage can be mitigated. Chapter 5 considers an architecture employing two types of superconducting qubits, the transmon qubit and the fluxonium qubit. These qubits have very different frequencies, making it unclear whether these qubits can even interact with each other in the first place. We show that the interactions with the higher-excited states can be utilized to perform operations between them, and we propose two types of gates. In practice, qubit frequencies are targeted with only a certain precision in fabrication. In certain cases, this can lead to unwanted interaction between qubits that increase the physical error rates, referred to as frequency collisions. We show that the large detuning between these qubits reduces the frequency of frequency collision, thereby increasing the expected fabrication yield. In Chapter 6, we realize a distance-two surface code experiment and perform repeated parity measurements to detect and post-select errors, given that it’s impossible to correct them when using such a small code. We implement a suite of logical operations for this code, including initialization, measurement, and several single-qubit gates. In the context of error detection, a logical operation is said to be fault-tolerant if the errors produced by each operation are detectable. We show that fault-tolerant variants of operations perform better than non-fault-tolerant ones. We also characterize the impact of various noise sources on the code performance. In Chapter 7, we look at another small-distance code, in this case, the distance-seven repetition code. We show that increasing the distance weakly suppresses the logical error rate of the code. We investigate the limiting factors behind the observed logical performance by analyzing the correlation between the observed parity measurements and performing simulations using noise models parameterized by the measured physical error rates. Chapter 8 considers a decoder that can perform the error inference more accurately. In particular, we implement a neural network decoder and investigate how it performs on experimental data from surface code experiments. We show that the accuracy of this decoder approaches what can be achieved by an optimal and computationally inefficient tensor network decoder. Transmon measurement produces analog outcomes. These are then typically converted to binary ones, leading to some information loss. We show how a neural network can also use this analog information to improve the achieved logical performance further. We have investigated the impact of non-conventional errors in simulation and in several experiments, demonstrating the importance of characterizing and mitigating these errors. We expect the methods introduced in this dissertation to lead to lower logical error rates. In the short term, this can aid in demonstrations of the usefulness of error correction. In the long term, addressing such errors is important to ensure the ability to suppress logical error rates to sufficiently low levels. We finish this dissertation with a brief conclusion of each chapter. We also outline several potential challenges that can impact future error-correction experiments, namely how to reduce the larger qubit overhead needed for fault-tolerant computation and several error sources that might become a limiting factor for future error-correction experiments.QCD/Terhal Grou
Marine nurseries and effective juvenile habitats
No full textCraig A. Layman, Craig P. Dahlgren, G. Todd Kellison, Aaron J. Adams, Bronwyn M. Gillanders, Matthew S. Kendall, Janet A. Ley, Ivan Nagelkerken and Joseph E. Seraf
A muddy time capsule: Using sediment environmental DNA for the long-term monitoring of coastal vegetated ecosystems
No full textPublished online 16 March 2020Seagrass, saltmarsh and mangrove habitats are declining around the world as anthropogenic activity and climate change intensify. To be able to effectively restore and maintain healthy coastal-vegetation communities, we must understand how and why they have changed in the past. Identifying shifts in vegetation communities, and the environmental or human drivers of these, can inform successful management and restoration strategies. Unfortunately, long-term data (i.e. decades to hundreds of years) on coastal vegetated ecosystems that can discern community-level changes are mostly non-existent in the scientific record. We propose implementing DNA extracted from coastal sediments to provide an alternative approach to long-term ecological reconstruction for coastal vegetated ecosystems. This type of DNA is called ‘environmental DNA’ and has previously been used to generate long-term datasets for other vegetated systems but has not yet been applied to vegetation change in coastal settings. In this overview, we explore the idea of using sediment eDNA as a long-term monitoring tool for seagrass, saltmarsh and mangrove communities. We see real potential in this approach for reconstructing long-term ecological histories of coastal vegetated ecosystems, and advocate that further research be undertaken to develop appropriate methods for its use.N. R. Foster, B. M. Gillanders, A. R. Jones, J. M. Young and M. Waycot
Longitudinal variation and effects of habitat on biodiversity of Australasian temperate reef fishes
No full textAim Latitudinal gradients in marine biodiversity of fishes are well documented but comparatively little is known about longitudinal patterns. The objective of this study was to describe the distributional patterns in biodiversity and assemblage structure of temperate reef-associated fishes in two habitats (kelp forests and open reefs) in each of four regions at comparable latitudes spanning a large longitudinal range (> 5000 km; 117.91° E–174.81° E). Location New Zealand, New South Wales, South Australia and Western Australia. Methods Total abundance, species richness, evenness, average taxonomic distinctness and variation in taxonomic distinctness were calculated from underwater visual counts of individual fish species and were analysed using ANOVA. Compositional change in fish communities was analysed using PERMANOVA and non-metric multi-dimensional scaling at the species level and at the family level. Results Patterns in univariate diversity measures did not show a clear longitudinal gradient and depended on the particular variable being considered. There was, however, a clear longitudinal gradient of turnover in species composition but this disappeared in family-level analyses. The effects of habitat were also relatively stronger in family-level analyses. Main conclusions We propose that ecological communities in similar habitats may be assembled according to a general ‘village hypothesis’, whereby an assemblage contains certain essential functional components. Regions having similar environmental characteristics are expected to have a full suite of these functional components. Thus, provided families reflect functional forms, this may explain the similarity among communities from vastly different regions when analysed at the family level. In contrast, the radiation of species within families may be regionally specific, depending on the history of oceanographic connectivity, microclimate and finer niche specialization, thus yielding strong regional differences in composition at this finer taxonomic level.Helen L. Smith, Marti J. Anderson, Bronwyn M. Gillanders, and Sean D. Connel
A meta-analysis of multiple stressors on seagrasses in the context of marine spatial cumulative impacts assessment
No full textPublished online: 20 July 2020Humans are placing more strain on the world’s oceans than ever before. Furthermore, marine ecosystems are seldom subjected to single stressors, rather they are frequently exposed to multiple, concurrent stressors. When the combined effect of these stressors is calculated and mapped through cumulative impact assessments, it is often assumed that the effects are additive. However, there is increasing evidence that different combinations of stressors can have non-additive impacts, potentially leading to synergistic and unpredictable impacts on ecosystems. Accurately predicting how stressors interact is important in conservation, as removal of certain stressors could provide a greater benefit, or be more detrimental than would be predicted by an additive model. Here, we conduct a meta-analysis to assess the prevalence of additive, synergistic, and antagonistic stressor interaction effects using seagrasses as case study ecosystems. We found that additive interactions were the most commonly reported in seagrass studies. Synergistic and antagonistic interactions were also common, but there was no clear way of predicting where these non-additive interactions occurred. More studies which synthesise the results of stressor interactions are needed to be able to generalise interactions across ecosystem types, which can then be used to improve models for assessing cumulative impacts.Jackson Stockbridge, Alice R. Jones and Bronwyn M. Gillander
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