44 research outputs found
Narrow optical linewidths in erbium implanted in TiO
Atomic and atom-like defects in the solid-state are widely explored for
quantum computers, networks and sensors. Rare earth ions are an attractive
class of atomic defects that feature narrow spin and optical transitions that
are isolated from the host crystal, allowing incorporation into a wide range of
materials. However, the realization of long electronic spin coherence times is
hampered by magnetic noise from abundant nuclear spins in the most widely
studied host crystals. Here, we demonstrate that Er ions can be
introduced via ion implantation into TiO, a host crystal that has not been
studied extensively for rare earth ions and has a low natural abundance of
nuclear spins. We observe efficient incorporation of the implanted Er
into the Ti site (40% yield), and measure narrow inhomogeneous spin and
optical linewidths (20 and 460 MHz, respectively) that are comparable to
bulk-doped crystalline hosts for Er. This work demonstrates that ion
implantation is a viable path to studying rare earth ions in new hosts, and is
a significant step towards realizing individually addressed rare earth ions
with long spin coherence times for quantum technologies
Measurement-Induced State Transitions in a Superconducting Qubit: Within the Rotating Wave Approximation
Superconducting qubits typically use a dispersive readout scheme, where a
resonator is coupled to a qubit such that its frequency is qubit-state
dependent. Measurement is performed by driving the resonator, where the
transmitted resonator field yields information about the resonator frequency
and thus the qubit state. Ideally, we could use arbitrarily strong resonator
drives to achieve a target signal-to-noise ratio in the shortest possible time.
However, experiments have shown that when the average resonator photon number
exceeds a certain threshold, the qubit is excited out of its computational
subspace, which we refer to as a measurement-induced state transition. These
transitions degrade readout fidelity, and constitute leakage which precludes
further operation of the qubit in, for example, error correction. Here we study
these transitions using a transmon qubit by experimentally measuring their
dependence on qubit frequency, average photon number, and qubit state, in the
regime where the resonator frequency is lower than the qubit frequency. We
observe signatures of resonant transitions between levels in the coupled
qubit-resonator system that exhibit noisy behavior when measured repeatedly in
time. We provide a semi-classical model of these transitions based on the
rotating wave approximation and use it to predict the onset of state
transitions in our experiments. Our results suggest the transmon is excited to
levels near the top of its cosine potential following a state transition, where
the charge dispersion of higher transmon levels explains the observed noisy
behavior of state transitions. Moreover, occupation in these higher energy
levels poses a major challenge for fast qubit reset
Overcoming leakage in scalable quantum error correction
Leakage of quantum information out of computational states into higher energy
states represents a major challenge in the pursuit of quantum error correction
(QEC). In a QEC circuit, leakage builds over time and spreads through
multi-qubit interactions. This leads to correlated errors that degrade the
exponential suppression of logical error with scale, challenging the
feasibility of QEC as a path towards fault-tolerant quantum computation. Here,
we demonstrate the execution of a distance-3 surface code and distance-21
bit-flip code on a Sycamore quantum processor where leakage is removed from all
qubits in each cycle. This shortens the lifetime of leakage and curtails its
ability to spread and induce correlated errors. We report a ten-fold reduction
in steady-state leakage population on the data qubits encoding the logical
state and an average leakage population of less than
throughout the entire device. The leakage removal process itself efficiently
returns leakage population back to the computational basis, and adding it to a
code circuit prevents leakage from inducing correlated error across cycles,
restoring a fundamental assumption of QEC. With this demonstration that leakage
can be contained, we resolve a key challenge for practical QEC at scale.Comment: Main text: 7 pages, 5 figure
Population and fertility by age and sex for 195 countries and territories, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017
Background Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods.
Methods We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10–54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10–14 years and 50–54 years was estimated from data on fertility in women aged 15–19 years and 45–49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories.Background Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods.
Methods We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10–54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10–14 years and 50–54 years was estimated from data on fertility in women aged 15–19 years and 45–49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories
Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016
Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016.Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0–100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0–100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita.Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016.Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0–100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0–100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita
Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017
Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally.
Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950.Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally.
Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950
Measurement-induced entanglement and teleportation on a noisy quantum processor
Measurement has a special role in quantum theory: by collapsing the
wavefunction it can enable phenomena such as teleportation and thereby alter
the "arrow of time" that constrains unitary evolution. When integrated in
many-body dynamics, measurements can lead to emergent patterns of quantum
information in space-time that go beyond established paradigms for
characterizing phases, either in or out of equilibrium. On present-day NISQ
processors, the experimental realization of this physics is challenging due to
noise, hardware limitations, and the stochastic nature of quantum measurement.
Here we address each of these experimental challenges and investigate
measurement-induced quantum information phases on up to 70 superconducting
qubits. By leveraging the interchangeability of space and time, we use a
duality mapping, to avoid mid-circuit measurement and access different
manifestations of the underlying phases -- from entanglement scaling to
measurement-induced teleportation -- in a unified way. We obtain finite-size
signatures of a phase transition with a decoding protocol that correlates the
experimental measurement record with classical simulation data. The phases
display sharply different sensitivity to noise, which we exploit to turn an
inherent hardware limitation into a useful diagnostic. Our work demonstrates an
approach to realize measurement-induced physics at scales that are at the
limits of current NISQ processors
Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: A systematic analysis from the Global Burden of Disease Study 2016
Background A key component of achieving universal health coverage is ensuring that all populations have access to
quality health care. Examining where gains have occurred or progress has faltered across and within countries is
crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries,
and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access
and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from
1990 to 2016.
Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which
death should not occur in the presence of effective care to approximate personal health-care access and quality by
location and over time. To better isolate potential effects of personal health-care access and quality from underlying
risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local
joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion
of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised
death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We
transformed each cause to a scale of 0–100, with 0 as the first percentile (worst) observed between 1990 and 2016, and
100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational
locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values,
providing an overall score of 0–100 of personal health-care access and quality by location over time. We then compared
HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall
development. As derived from the broader GBD study and other data sources, we examined relationships between
national HAQ Index scores and potential correlates of performance, such as total health spending per capita.
Findings In 2016, HAQ Index performance spanned from a high of 97·1 (95% UI 95·8–98·1) in Iceland, followed by
96·6 (94·9–97·9) in Norway and 96·1 (94·5–97·3) in the Netherlands, to values as low as 18·6 (13·1–24·4) in
the Central African Republic, 19·0 (14·3–23·7) in Somalia, and 23·4 (20·2–26·8) in Guinea-Bissau. The pace of
progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and
2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and
elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000.
Striking subnational disparities emerged in personal health-care access and quality, with China and India having
particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged
from 91·5 (89·1–93·6) in Beijing to 48·0 (43·4–53·2) in Tibet (a 43·5-point difference), while India saw a 30·8-point
disparity, from 64·8 (59·6–68·8) in Goa to 34·0 (30·3–38·1) in Assam. Japan recorded the smallest range in
subnational HAQ performance in 2016 (a 4·8-point difference), whereas differences between subnational locations
with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high
for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20·9-point
to 17·0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17·2-point
to 20·4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high
and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases.
Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from
2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was
positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these
relationships were quite heterogeneous, particularly among low-to-middle SDI countries.
Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving
personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-
SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or
minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities
of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium
Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health
coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive
view—and subsequent provision—of quality health care for all populations.info:eu-repo/semantics/publishedVersio
Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017
Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2\ub75th percentile and 100 as the 97\ub75th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59\ub74 (IQR 35\ub74–67\ub73), ranging from a low of 11\ub76 (95% uncertainty interval 9\ub76–14\ub70) to a high of 84\ub79 (83\ub71–86\ub77). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030