47 research outputs found
The size of macroscopic superposition states in flux qubits
The question as to whether or not quantum mechanics is applicable to the
macroscopic scale has motivated efforts to generate superposition states of
macroscopic numbers of particles and to determine their effective size.
Superpositions of circulating current states in flux qubits constitute
candidate states that have been argued to be at least mesoscopic. We present a
microscopic analysis that reveals the number of electrons participating in
these superpositions to be surprisingly but not trivially small, even though
differences in macroscopic observables are large.Comment: 7 pages, no figure
Electronic structure of superposition states in flux qubits
Flux qubits, small superconducting loops interrupted by Josephson junctions,
are successful realizations of quantum coherence for macroscopic variables.
Superconductivity in these loops is carried by --
electrons, which has been interpreted as suggesting that coherent
superpositions of such current states are macroscopic superpositions analogous
to Schr\"odinger's cat. We provide a full microscopic analysis of such qubits,
from which the macroscopic quantum description can be derived. This reveals
that the number of microscopic constituents participating in superposition
states for experimentally accessible flux qubits is surprisingly but not
trivially small. The combination of this relatively small size with large
differences between macroscopic observables in the two branches is seen to
result from the Fermi statistics of the electrons and the large disparity
between the values of superfluid and Fermi velocity in these systems.Comment: Minor cosmetic changes. Published version
Quantum dynamics of local phase differences between reservoirs of driven interacting bosons separated by simple aperture arrays
We present a derivation of the effective action for the relative phase of
driven, aperture-coupled reservoirs of weakly-interacting condensed bosons from
a (3+1)-D microscopic model with local U(1) gauge symmetry. We show that
inclusion of local chemical potential and driving velocity fields as a gauge
field allows derivation of the hydrodynamic equations of motion for the driven
macroscopic phase differences across simple aperture arrays. For a single
aperture, the current-phase equation for driven flow contains sinusoidal,
linear, and current-bias contributions. We compute the renormalization group
(RG) beta function of the periodic potential in the effective action for small
tunneling amplitudes and use this to analyze the temperature dependence of the
low-energy current-phase relation, with application to the transition from
linear to sinusoidal current-phase behavior observed in experiments by
Hoskinson et al. \cite{packard} for liquid He driven through nanoaperture
arrays. Extension of the microscopic theory to a two-aperture array shows that
interference between the microscopic tunneling contributions for individual
apertures leads to an effective coupling between apertures which amplifies the
Josephson oscillations in the array. The resulting multi-aperture current-phase
equations are found to be equivalent to a set of equations for coupled pendula,
with microscopically derived couplings.Comment: 16 pages, 5 figures v2: typos corrected, RG phase diagram correcte
Carbon dioxide emissions continue to grow amidst slowly emerging climate policies
This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this record A failure to recognize the factors behind continued emissions growth could limit the world’s ability to shift to a
pathway consistent with 1.5 °C or 2 °C of global warming. Continued support for low-carbon technologies needs to
be combined with policies directed at phasing out the use of fossil fuels.European Union’s Horizon 202
Global energy growth is outpacing decarbonization
Recent reports have highlighted the challenge of keeping global average temperatures below 2 °C and—even more so—1.5 °C (IPCC 2018). Fossil-fuel burning and cement production release ~90% of all CO2 emissions from human activities. After a three-year hiatus with stable global emissions (Jackson et al 2016; Le Quéré C et al 2018a ; IEA 2018), CO2 emissions grew by 1.6% in 2017 to 36.2 Gt (billion tonnes), and are expected to grow a further 2.7% in 2018 (range: 1.8%–3.7%) to a record 37.1 ± 2 Gt CO2 (Le Quéré et al 2018b). Additional increases in 2019 remain uncertain but appear likely because of persistent growth in oil and natural gas use and strong growth projected for the global economy. Coal use has slowed markedly in the last few years, potentially peaking, but its future trajectory remains uncertain. Despite positive progress in ~19 countries whose economies have grown over the last decade and their emissions have declined, growth in energy use from fossil-fuel sources is still outpacing the rise of low-carbon sources and activities. A robust global economy, insufficient emission reductions in developed countries, and a need for increased energy use in developing countries where per capita emissions remain far below those of wealthier nations will continue to put upward pressure on CO2 emissions. Peak emissions will occur only when total fossil CO2 emissions finally start to decline despite growth in global energy consumption, with fossil energy production replaced by rapidly growing low- or no-carbon technologies
Global Carbon Budget 2015
Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (E-FF) are based on energy statistics and cement production data, while emissions from land-use change (E-LUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (G(ATM)) is computed from the annual changes in concentration. The mean ocean CO2 sink (S-OCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in S-OCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (S-LAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover change (some including nitrogen-carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as +/- 1 sigma, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (20052014), E-FF was 9.0 +/- 0.5 GtC yr(-1) E-LUC was 0.9 +/- 0.5 GtC yr(-1), GATM was 4.4 +/- 0.1 GtC yr(-1), S-OCEAN was 2.6 +/- 0.5 GtC yr(-1), and S LAND was 3.0 +/- 0.8 GtC yr(-1). For the year 2014 alone, E FF grew to 9.8 +/- 0.5 GtC yr(-1), 0.6% above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2% yr(-1) that took place during 2005-2014. Also, for 2014, E-LUC was 1.1 +/- 0.5 GtC yr(-1), G(ATM) was 3.9 +/- 0.2 GtC yr(-1), S-OCEAN was 2.9 +/- 0.5 GtC yr(-1), and S-LAND was 4.1 +/- 0.9 GtC yr(-1). G(ATM) was lower in 2014 compared to the past decade (2005-2014), reflecting a larger S-LAND for that year. The global atmospheric CO2 concentration reached 397.15 +/- 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in E-FF will be near or slightly below zero, with a projection of 0.6 [ range of 1.6 to C 0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of E-FF and assumed constant E LUC for 2015, cumulative emissions of CO2 will reach about 555 +/- 55 GtC (2035 +/- 205 GtCO(2)) for 1870-2015, about 75% from E FF and 25% from E LUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quere et al., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi: 10.3334/CDIAC/GCP_2015)
Global fossil carbon emissions rebound near pre-COVID-19 levels
Fossil CO2 emissions in 2021 grew an estimated 4.2% (3.5%–4.8%) to 36.2 billion metric tons compared with 2020, pushing global emissions back close to 2019 levels (36.7 Gt CO2)
Key indicators to track current progress and future ambition of the Paris Agreement
Current emission pledges to the Paris Agreement appear insufficient to hold the global average temperature increase to well below 2 °C above pre-industrial levels. Yet, details are missing on how to track progress towards the â € Paris goal', inform the five-yearly â € global stocktake', and increase the ambition of Nationally Determined Contributions (NDCs). We develop a nested structure of key indicators to track progress through time. Global emissions track aggregated progress, country-level decompositions track emerging trends that link directly to NDCs, and technology diffusion indicates future reductions. We find the recent slowdown in global emissions growth is due to reduced growth in coal use since 2011, primarily in China and secondarily in the United States. The slowdown is projected to continue in 2016, with global CO 2 emissions from fossil fuels and industry similar to the 2015 level of 36 GtCO 2. Explosive and policy-driven growth in wind and solar has contributed to the global emissions slowdown, but has been less important than economic factors and energy efficiency. We show that many key indicators are currently broadly consistent with emission scenarios that keep temperatures below 2 °C, but the continued lack of large-scale carbon capture and storage threatens 2030 targets and the longer-term Paris ambition of net-zero emissions
Global Carbon Budget 2020
Accurate assessment of anthropogenic carbon dioxide (CO) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO emissions (E) are based on energy statistics and cement production data, while emissions from land-use change (E), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO concentration is measured directly and its growth rate (G) is computed from the annual changes in concentration. The ocean CO sink (S) and terrestrial CO sink (S) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (B), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2010–2019), E was 9.6 ± 0.5 GtC yr excluding the cement carbonation sink (9.4 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and E was 1.6 ± 0.7 GtC yr. For the same decade, G was 5.1 ± 0.02 GtC yr (2.4 ± 0.01 ppm yr), S 2.5 ± 0.6 GtC yr, and S 3.4 ± 0.9 GtC yr, with a budget imbalance B of −0.1 GtC yr indicating a near balance between estimated sources and sinks over the last decade. For the year 2019 alone, the growth in E was only about 0.1 % with fossil emissions increasing to 9.9 ± 0.5 GtC yr excluding the cement carbonation sink (9.7 ± 0.5 GtC yr when cement carbonation sink is included), and E was 1.8 ± 0.7 GtC yr, for total anthropogenic CO emissions of 11.5 ± 0.9 GtC yr (42.2 ± 3.3 GtCO). Also for 2019, G was 5.4 ± 0.2 GtC yr (2.5 ± 0.1 ppm yr), S was 2.6 ± 0.6 GtC yr, and S was 3.1 ± 1.2 GtC yr, with a B of 0.3 GtC. The global atmospheric CO concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminary data for 2020, accounting for the COVID-19-induced changes in emissions, suggest a decrease in E relative to 2019 of about −7 % (median estimate) based on individual estimates from four studies of −6 %, −7 %, −7 % (−3 % to −11 %), and −13 %. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2019, but discrepancies of up to 1 GtC yr persist for the representation of semi-decadal variability in CO fluxes. Comparison of estimates from diverse approaches and observations shows (1) no consensus in the mean and trend in land-use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO flux in the northern extra-tropics, and (3) an apparent discrepancy between the different methods for the ocean sink outside the tropics, particularly in the Southern Ocean. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Friedlingstein et al., 2019; Le Quéré et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2020 (Friedlingstein et al., 2020)