Search

During a quantum measurement, superpositions of states with different observable properties probabilistically collapse into one with a sharp value of the measured observable. In macroscopic quantum systems, this collapse arises via a continuous measurement-induced phase transition (MIPT) at a critical value of the strength of interaction with the measurement apparatus. MIPTs lie outside established paradigms for equilibrium or nonequilibrium critical phenomena and delineate distinct, stable dynamical and computational phases of matter. Quantum computers enable programmable simulation of the interaction of a measurement apparatus with a dynamical quantum system, to explore MIPT phenomena over a range of system sizes while retaining quantum coherence. Yet, existing experimental protocols rely on fundamentally nonscalable postselection techniques or direct classical simulation of quantum circuits. Here, we report the scalable observation of finite-size scaling evidence for an observable-sharpening MIPT in monitored quantum circuits in a chain of ^{171}Yb^{+} ions in Quantinuum’s H1-1 trapped-ion quantum processor. By leveraging an equivalent description as a statistical physics problem, we implement scalable classical algorithms to infer the value of the measured observable from a single experimental shot. This technique enables a truly scalable protocol to observe observable-sharpening MIPTs in generic classes of circuits that cannot be directly classically simulated and also provides enhanced means to detect and suppress errors in the quantum simulation.

Safely opening university campuses has been a major challenge during the COVID-19 pandemic. Here, the authors describe a program of public health measures employed at a university in the United States which, combined with other non-pharmaceutical interventions, allowed the university to stay open in fall 2020 with limited evidence of transmission.

Abstract Background Street sex workers (SSWs) are a highly marginalised and stigmatised group who carry an extremely high burden of unmet health need. They experience multiple and interdependent health and social problems and extreme health inequality. Despite high levels of chronic physical and mental ill-health, there is little evidence of effective healthcare provision for this group. They are often considered ‘hard to reach’, but many individuals and organisations have extensive experience of working with this group. Methods We conducted a cross-sectional survey of professionals who work with SSWs in the UK on their perspectives on their access to primary care, mental health, sexual health and drug and alcohol services, how well these services met the needs of SSWs and suggestions of best practice. Results 50 professionals mostly from England, responded. Mainstream general practice and mental health services were found to be largely inaccessible to SSWs. Sexual health, drug and alcohol services and homeless health services better met their needs; this was mostly attributed to flexible services and collaborations with organisations who work closely with SSWs. The main challenges in providing healthcare to SSWs were services being inflexible, under-resourced services and services not being trauma-informed. Best practice in providing healthcare to SSWs includes- seamless partnership working between agencies with case worker support; peer-involvement in service development and engagement, a range of health provision including outreach, presence in community spaces and fast-track access into mainstream services; trauma-informed, gender-sensitive health services in a welcoming environment with flexible, responsive appointment and drop-in systems and consistent clinicians with specialist knowledge of substance misuse, mental health, domestic violence and homelessness. Conclusions Access to healthcare for SSWs in the UK is highly variable but largely inadequate with regards to primary care and mental health provision. The examples of positive healthcare provision and partnership working presented here demonstrate the feasibility of accessible healthcare that meets the needs of SSWs. These need to be systematically implemented and evaluated to understand their impact and implications. As we build back from COVID-19 there is an urgent need to make accessible healthcare provision for marginalised groups the norm, not the exception.

Background Abnormal renal hemodynamic responses to salt‐loading are thought to contribute to salt‐sensitive (SS) hypertension. However, this is based largely on studies in anesthetized animals, and little data are available in conscious SS and salt‐resistant rats. Methods and Results We assessed arterial blood pressure, renal function, and renal blood flow during administration of a 0.4% NaCl and a high‐salt (4.0% NaCl) diet in conscious, chronically instrumented 10‐ to 14‐week‐old Dahl SS and consomic SS rats in which chromosome 1 from the salt‐resistant Brown‐Norway strain was introgressed into the genome of the SS strain (SS.BN1). Three weeks of high salt intake significantly increased blood pressure (20%) and exacerbated renal injury in SS rats. In contrast, the increase in blood pressure (5%) was similarly attenuated in Brown‐Norway and SS.BN1 rats, and both strains were completely protected against renal injury. In SS.BN1 rats, 1 week of high salt intake was associated with a significant decrease in renal vascular resistance (−8%) and increase in renal blood flow (15%). In contrast, renal vascular resistance failed to decrease, and renal blood flow remained unchanged in SS rats during high salt intake. Finally, urinary sodium excretion and glomerular filtration rate were similar between SS and SS.BN1 rats during 0.4% NaCl and high salt intake. Conclusions Our data support the concept that renal vasodysfunction contributes to blood pressure salt sensitivity in Dahl SS rats, and that genes on rat chromosome 1 play a major role in modulating renal hemodynamic responses to salt loading and salt‐induced hypertension.

This study assesses the impact of different state of the art global biospheric CO2 flux models, when applied as prior information, on inverse model “top-down” estimates of terrestrial CO2 fluxes obtained when assimilating Orbiting Carbon Observatory 2 (OCO-2) observations. This is done with a series of observing system simulation experiments (OSSEs) using synthetic CO2 column-average dry air mole fraction (XCO2) retrievals sampled at the OCO-2 satellite spatiotemporal frequency. The OSSEs utilized a 4-D variational (4D-Var) assimilation system with the GEOS-Chem global chemical transport model (CTM) to estimate CO2 net ecosystem exchange (NEE) fluxes using synthetic OCO-2 observations. The impact of biosphere models in inverse model estimates of NEE is quantified by conducting OSSEs using the NASA-CASA, CASA-GFED, SiB-4, and LPJ models as prior estimates and using NEE from the multi-model ensemble mean of the Multiscale Synthesis and Terrestrial Model Intercomparison Project as the “truth”. Results show that the assimilation of simulated XCO2 retrievals at OCO-2 observing modes over land results in posterior NEE estimates which generally reproduce “true” NEE globally and over terrestrial TransCom-3 regions that are well-sampled. However, we find larger spread among posterior NEE estimates, when using different prior NEE fluxes, in regions and seasons that have limited OCO-2 observational coverage and a large range in “bottom-up” NEE fluxes. Seasonally averaged posterior NEE estimates had standard deviations (SD) of ∼10 % to ∼50 % of the multi-model-mean NEE for different TransCom-3 land regions with significant NEE fluxes (regions/seasons with a NEE flux ≥0.5 PgC yr−1). On a global average, the seasonally averaged residual impact of the prior model NEE assumption on the posterior NEE spread is ∼10 %–20 % of the posterior NEE mean. Additional OCO-2 OSSE simulations demonstrate that posterior NEE estimates are also sensitive to the assumed prior NEE flux uncertainty statistics, with spread in posterior NEE estimates similar to those when using variable prior model NEE fluxes. In fact, the sensitivity of posterior NEE estimates to prior error statistics was larger than prior flux values in some regions/times in the tropics and Southern Hemisphere where sufficient OCO-2 data were available and large differences between the prior and truth were evident. Overall, even with the availability of spatiotemporally dense OCO-2 data, noticeable residual differences (up to ∼20 %–30 % globally and 50 % regionally) in posterior NEE flux estimates remain that were caused by the choice of prior model flux values and the specification of prior flux uncertainties.

While the citizen science approach has gained prominence in water and ecosystem services management, methodological limitations, insufficient resources invested in monitoring practices and a lack of effective mechanisms for integrating the approach into existing monitoring and decision making processes means that its full potential has yet to be realized. Nevertheless, the concept offers a real opportunity to address data gaps and assist decision makers operating under a wide range of socio-ecological and environmental uncertainties. In this paper, we report findings from a project in which low-cost sensors were deployed to collect hydrological data in two study locations in Nepal. We found evidence that the citizen science has potential to generate locally relevant data and knowledge which can enrich a much more polycentric governance of water ecosystem services management. However, some major challenges need to be overcome, in particular developing locally-tailored monitoring sensors, standardizing monitoring and data sharing practice, improving local capabilities to collect quality data and making the approach more sustainable and adaptive to emerging environmental threats and uncertainties. If sufficient attention can be given to these key challenges, citizen science looks set to play a significant future role in water and ecosystem services management.

We characterize the variational power of quantum circuit tensor networks in the representation of physical many-body ground states. Such tensor networks are formed by replacing the dense block unitaries and isometries in standard tensor networks by local quantum circuits. We explore both quantum circuit matrix product states and the quantum circuit multiscale entanglement renormalization Ansatz, and introduce an adaptive method to optimize the resulting circuits to high fidelity with more than 10^{4} parameters. We benchmark their expressiveness against standard tensor networks, as well as other common circuit architectures, for the 1D and 2D Heisenberg and 1D Fermi-Hubbard models. We find quantum circuit tensor networks to be substantially more expressive than other quantum circuits for these problems, and that they can even be more compact than standard tensor networks. Extrapolating to circuit depths which can no longer be emulated classically, this suggests a region of advantage in quantum expressiveness in the representation of physical ground states.

We present a suite of “holographic” quantum algorithms for efficient ground-state preparation and dynamical evolution of correlated spin systems, which require far fewer qubits than the number of spins being simulated. The algorithms exploit the equivalence between matrix-product states (MPS) and quantum channels, along with partial measurement and qubit reuse, in order to simulate a D-dimensional spin system using only a (D−1)-dimensional subset of qubits along with an ancillary qubit register whose size scales logarithmically in the amount of entanglement present in the simulated state. Ground states can either be directly prepared from a known MPS representation or obtained via a holographic variational quantum eigensolver (holoVQE). Dynamics of MPS under local Hamiltonians for time t can also be simulated with an additional (multiplicative) poly(t) overhead in qubit resources. These techniques open the door to efficient quantum simulation of MPS with exponentially large bond dimension, including ground states of two- and three-dimensional systems, or thermalizing dynamics with rapid entanglement growth. As a demonstration of the potential resource savings, we implement a holoVQE simulation of the antiferromagnetic Heisenberg chain on a trapped-ion quantum computer, achieving within 10(3)% of the exact ground-state energy of an infinite chain using only a pair of qubits.

Abstract Background Measurement of blood oxygen saturation (O2 saturation) is of great importance for evaluation of patients with many cardiovascular diseases, but currently there are no established non-invasive methods to measure blood O2 saturation in the heart. While T2-based CMR oximetry methods have been previously described, these approaches rely on technique-specific calibration factors that may not generalize across patient populations and are impractical to obtain in individual patients. We present a solution that utilizes multiple T2 measurements made using different inter-echo pulse spacings. These data are jointly processed to estimate all unknown parameters, including O2 saturation, in the Luz-Meiboom (L-M) model. We evaluated the accuracy of the proposed method against invasive catheterization in a porcine hypoxemia model. Methods Sufficient data diversity to estimate the various unknown parameters of the L-M model, including O2 saturation, was achieved by acquiring four T2 maps, each at a different τ 180 (12, 15, 20, and 25 ms). Venous and arterial blood T2 values from these maps, together with hematocrit and arterial O2 saturation, were jointly processed to derive estimates for venous O2 saturation and other nuisance parameters in the L-M model. The technique was validated by a progressive graded hypoxemia experiment in seven pigs. CMR estimates of O2 saturation in the right ventricle were compared against a reference O2 saturation obtained by invasive catheterization from the right atrium in each pig, at each hypoxemia stage. O2 saturation derived from the proposed technique was also compared against the previously described method of applying a global calibration factor (K) to the simplified L-M model. Results Venous O2 saturation results obtained using the proposed CMR oximetry method exhibited better agreement (y = 0.84× + 12.29, R2 = 0.89) with invasive blood gas analysis when compared to O2 saturation estimated by a global calibration method (y = 0.69× + 27.52, R2 = 0.73). Conclusions We have demonstrated a novel, non-invasive method to estimate O2 saturation using quantitative T2 mapping. This technique may provide a valuable addition to the diagnostic utility of CMR in patients with congenital heart disease, heart failure, and pulmonary hypertension.

Quantum simulators are a promising technology on the spectrum of quantum devices from specialized quantum experiments to universal quantum computers. These quantum devices utilize entanglement and many-particle behavior to explore and solve hard scientific, engineering, and computational problems. Rapid development over the last two decades has produced more than 300 quantum simulators in operation worldwide using a wide variety of experimental platforms. Recent advances in several physical architectures promise a golden age of quantum simulators ranging from highly optimized special purpose simulators to flexible programmable devices. These developments have enabled a convergence of ideas drawn from fundamental physics, computer science, and device engineering. They have strong potential to address problems of societal importance, ranging from understanding vital chemical processes, to enabling the design of new materials with enhanced performance, to solving complex computational problems. It is the position of the community, as represented by participants of the National Science Foundation workshop on “Programmable Quantum Simulators,” that investment in a national quantum simulator program is a high priority in order to accelerate the progress in this field and to result in the first practical applications of quantum machines. Such a program should address two areas of emphasis: (1) support for creating quantum simulator prototypes usable by the broader scientific community, complementary to the present universal quantum computer effort in industry; and (2) support for fundamental research carried out by a blend of multi-investigator, multidisciplinary collaborations with resources for quantum simulator software, hardware, and education.This document is a summary from a U.S. National Science Foundation supported workshop held on 16–17 September 2019 in Alexandria, VA. Attendees were charged to identify the scientific and community needs, opportunities, and significant challenges for quantum simulators over the next 2–5 years.

The topological character of electrons in semimetals subtly influences their bulk properties, leading typically to weak experimental signatures. Here, Moll et al. report a distinctive anomaly in the magnetic torque upon entering quantum limit state in the Weyl semimetal NbAs, which only appears due to the presence of Weyl fermions.