Adaptive variational preparation of the Fermi-Hubbard eigenstates

Approximating the ground states of strongly interacting electron systems in quantum chemistry and condensed matter physics is expected to be one of the earliest applications of quantum computers. In this paper, we prepare highly accurate ground states of the Fermi-Hubbard model for small grids up to 6 sites (12 qubits) by using an interpretable, adaptive variational quantum eigensolver(VQE) called ADAPT-VQE. In contrast with non-adaptive VQE, this algorithm builds a system-specific ansatz by adding an optimal gate built from one-body or two-body fermionic operators at each step. We show this adaptive method outperforms the non-adaptive counterpart in terms of fewer variational parameters, short gate depth, and scaling with the system size. The fidelity and energy of the prepared state appear to improve asymptotically with ansatz depth. We also demonstrate the application of adaptive variational methods by preparing excited states and Green functions using a proposed ADAPT-SSVQE algorithm. Lower depth, asymptotic convergence, noise tolerance of a variational approach, and a highly controllable, system-specific ansatz make the adaptive variational methods particularly well-suited for NISQ devices

Farmers' management of rice varietal diversity in the mid-hills of Nepal: implications for on-farm conservation and crop improvement

Season-long monitoring of on-farm rice (Oryza sativa, L.) plots in Nepal explored farmers' decision-making process on the deployment of varieties to agroecosystems, application of production inputs to varieties, agronomic practices and relationship between economic return and area planted per variety. Farmers deploy varieties [landraces (LRs) and modern varieties (MVs)] to agroecosystems based on their understanding of characteristics of varieties and agroecosystems, and the interaction between them. In marginal growing conditions, LRs can compete with MVs. Within an agroecosystem, economic return and area planted to varieties have positive relationship, but this is not so between agroecosystems. LRs are very diverse on agronomic and economic traits; therefore, they cannot be rejected a priori as inferior materials without proper evaluation. LRs have to be evaluated for useful traits and utilized in breeding programmes to generate farmer-preferred materials for marginal environments and for their conservation on-farm

Viewpoint – Pouring money down the drain: Can we break the habit by reconceiving wastes as resources?

As water-sector professionals re-discover the value in the 'waste' conveyed in 'waste'water, this Viewpoint argues that the theory of plural rationality (also known as Cultural Theory) may accelerate the switch from waste management to resource recovery. Accordingly, it extends the framing of plural rationality, from its traditional applications in matters of governance and social and economic analysis, to the beginnings of a set of plural schools of engineering thought. This sounds controversial. Indeed, we hope it is. For all too often ways to resolve water issues end up in the impasse of two deeply entrenched positions: the 'technocratic reductionism' of the 'quick engineering fix' to problem solving; and the 'participatory holism' of the 'local, socially sensitive, integrationist' approach. Plural rationality sees this is an impoverished duopoly. Our very strong preference is to find ways of promoting the creative interplay among plural (more than two), mutually opposed, contending ways of framing a problem and resolving it. This, we argue, should not only expand the portfolio of possible alternatives for technology-policy interventions, but also lead to the chosen alternative being preferable — in social, economic, and environmental terms — to what might otherwise have happened. Such solutions are called 'clumsy' in plural rationality theory. We use a synopsis of a case history of restoring water quality in the River Rhine in Europe, within a wider account of the sweep of resource recovery spanning two centuries (late 18th Century through early 21st Century), to illustrate how clumsiness works. This, however, does not extend to our elaborating our proposed set of plural schools of engineering thought beyond just its very beginnings. Our Viewpoint allows us merely to start framing the challenge of developing, and eventually applying, such a notion

Cervical cancer screening in Nepal: Ethical considerations

© 2015 Gyawali et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License. The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. Permissions beyond the scope of the License are administered by Dove Medical Press Limited. Information on how to request permission may be found at: http://www.dovepress.com/permissions.phpCervical cancer is the leading cause of cancer deaths for women worldwide. Cervical screening and early treatment can help to prevent cervical cancers. Cervical screening programs in Nepal are often associated with a number of socioeconomic, cultural, and ethical challenges. This paper discusses some central ethical challenges in providing cervical cancer screening in the Nepalese context and culture. It is necessary to address these challenges for successful implementation of such screening programs

Distributions of fecal markers in wastewater from different climatic zones for human fecal pollution tracking in Australian surface waters

Recreational and potable water supplies polluted with human wastewater can pose a direct health risk to humans. Therefore, sensitive detection of human fecal pollution in environmental waters is very important to water quality authorities around the globe. Microbial source tracking (MST) utilizes human fecal markers (HFMs) to detect human wastewater pollution in environmental waters. The concentrations of these markers in raw wastewater are considered important because it is likely that a marker whose concentration is high in wastewater will be more frequently detected in polluted waters. In this study, quantitative PCR (qPCR) assays were used to determine the concentrations of fecal indicator bacteria (FIB) Escherichia coli and Enterococcus spp., HFMs Bacteroides HF183, human adenoviruses (HAdVs), and polyomaviruses (HPyVs) in raw municipal wastewater influent from various climatic zones in Australia. E. coli mean concentrations in pooled human wastewater data sets (from various climatic zones) were the highest (3.2 × 10 gene copies per ml), followed by those of HF183 (8.0 × 10 gene copies per ml) and Enterococcus spp. (3.6 × 10 gene copies per ml). HAdV and HPyV concentrations were 2 to 3 orders of magnitude lower than those of FIB and HF183. Strong positive and negative correlations were observed between the FIB and HFM concentrations within and across wastewater treatment plants (WWTPs). To identify the most sensitive marker of human fecal pollution, environmental water samples were seeded with raw human wastewater. The results from the seeding experiments indicated that Bacteroides HF183 was more sensitive for detecting human fecal pollution than HAdVs and HPyVs. Since the HF183 marker can occasionally be present in nontarget animal fecal samples, it is recommended that HF183 along with a viral marker (HAdVs or HPyVs) be used for tracking human fecal pollution in Australian environmental waters

Revealing microcanonical phase diagrams of strongly correlated systems via time-averaged classical shadows

Quantum computers and simulators promise to enable the study of strongly correlated quantum systems. Yet surprisingly, it is hard for them to compute ground states[Kitaev]. They can, however, efficiently compute the dynamics of closed quantum systems. We introduce time-average classical shadows(TACS) and machine learning(ML) methods to take advantage of this efficiency to study microcanonical quantum thermodynamics. Using the one-dimensional transverse field Ising model(1DTFIM), we first validate the unsupervised ML method of diffusion maps on classical shadows data from ground state calculations on 100 qubit systems. We then show that diffusion maps applied to TACS data from quantum dynamics simulations beginning from cat states show distinct phase-defining features and correctly identifies the quantum phase transition. Finally, we introduce a Bayesian inference method to compute the second Renyi entropy, a stand in for entropy, the primary thermodynamic potential of microcanonical ensemble. Our results provide evidence that quantum simulators and computers capable of outperforming classical computers at dynamics simulations can also produce quantum thermodynamic data with quantum advantage

Plant breeding can be made more efficient by having fewer, better crosses

BACKGROUND: Crop yields have to increase to provide food security for the world’s growing population. To achieve these yield increases there will have to be a significant contribution from genetic gains made by conventional plant breeding. However, the breeding process is not efficient because crosses made between parental combinations that fail to produce useful varieties consume over 99% of the resources. RESULTS: We tested in a rice-breeding programme if its efficiency could be improved by using many fewer, but more judiciously chosen crosses than usual. In a 15-year programme in Nepal, with varietal testing also in India and Bangladesh, we made only six crosses that were stringently chosen on complementary parental performance. We evaluated their success by the adoption and official release of the varieties they produced. We then modelled optimum cross number using assumptions based on our experimental results. Four of the six crosses succeeded. This was a fifty-fold improvement over breeding programmes that employ many crosses where only about one, or fewer, crosses in 200 succeed. Based on these results, we modelled the optimum number of crosses by assuming there would be a decline in the reliability of the breeder’s prediction of the value of each cross as more crosses were made (because there is progressively less information on the traits of the parents). Fewer-cross programmes were more likely to succeed and did so using fewer resources. Making more crosses reduced the overall probability of success of the breeding programme. CONCLUSIONS: The efficiency of national and international breeding programmes would be increased by making fewer crosses among more carefully chosen parents. This would increase the number of higher yielding varieties that are delivered to farmers and hence help to improve food security

Toolbox approaches using molecular markers and 16S rRNA gene amplicon data sets for identification of fecal pollution in surface water

In this study, host-associated molecular markers and bacterial 16S rRNA gene community analysis using high-throughput sequencing were used to identify the sources of fecal pollution in environmental waters in Brisbane, Australia. A total of 92 fecal and composite wastewater samples were collected from different host groups (cat, cattle, dog, horse, human, and kangaroo), and 18 water samples were collected from six sites (BR1 to BR6) along the Brisbane River in Queensland, Australia. Bacterial communities in the fecal, wastewater, and river water samples were sequenced. Water samples were also tested for the presence of bird-associated (GFD), cattle-associated (CowM3), horse-associated, and human-associated (HF183) molecular markers, to provide multiple lines of evidence regarding the possible presence of fecal pollution associated with specific hosts. Among the 18 water samples tested, 83%, 33%, 17%, and 17% were real-time PCR positive for the GFD, HF183, CowM3, and horse markers, respectively. Among the potential sources of fecal pollution in water samples from the river, DNA sequencing tended to show relatively small contributions from wastewater treatment plants (up to 13% of sequence reads). Contributions from other animal sources were rarely detected and were very small

Simulation-based flood fragility and vulnerability analysis for expanding cities

Accurately quantifying flood-induced impacts on buildings and other infrastructure systems is essential for risk-sensitive planning and decision-making in expanding urban regions. Flood-induced impacts are directly related to the physical components of assets damaged due to contact with water. Such components include building contents (e.g., appliances, furniture) and other non-structural components whose damage/unavailability can severely impact the buildingsﾒ functionality. Conventional fragility analysis approaches for flooding do not account for the physical damage to the individual components, mostly relying on empirical methods based on historical data. However, recent studies proposed simulation-based, assembly-based fragility models that account for the damage to the building components. Such fragility models require developing detailed inventories of vulnerable components of households and identifying building archetypes to be considered in a building portfolio for the region of interest. Content inventories and building portfolios have so far been obtained for specific socio-economic contexts such as the United States of America. However, building types and their content can significantly differ between countries, making the available fragility models and computational frameworks unsuitable for flood vulnerability analysis in rapidly expanding cities characterised by extensive informal settlements, such as low- and middle-income countries. This paper details how to adapt the available methodologies for flood vulnerability assessment to the context of formal and informal settlements of expanding cities in the global south. It also details the development of content inventories for households in these cities using field surveys. The proposed survey is deployed in various areas vulnerable to floods in Kathmandu, Nepal. Based on the survey results, each component within the household is associated with a corresponding flood capacity (resistance) distribution (in terms of water height and flood duration). These distributions are then employed in a simulation-based probabilistic framework to obtain fragility relationship and consequence models. The relevant differences between the results obtained in this study and those from previous studies are then investigated for a case-study building type. In addition, the influence of socio-economic factors (e.g., household income) and past flood experience (possibly resulting in various flood-risk mitigation strategies at a household level) on the resulting flood impacts is also included in the model