46 research outputs found
Characterizing sampling biases in the trace gas climatologies of the SPARC Data Initiative
Monthly zonal mean climatologies of atmospheric measurements from satellite instruments can have biases due to the non-uniform sampling of the atmosphere by the instruments. We characterize potential sampling biases in stratospheric trace gas climatologies of the Stratospheric Processes and their Role in Climate (SPARC) Data Initiative using chemical fields from a chemistry climate model simulation and sampling patterns from 16 satellite-borne instruments. The exercise is performed for the long-lived stratospheric trace gases O3 and H2O. Monthly sample biases for O3 exceed 10% for many instruments in the high latitude stratosphere and in the upper troposphere/lower stratosphere, while annual mean sampling biases reach values of up to 20% in the same regions for some instruments. Sampling biases for H2O are generally smaller than for O3, although still notable in the upper troposphere/lower stratosphere and Southern Hemisphere high latitudes. The most important mechanism leading to monthly sampling bias is the non-uniform temporal sampling of many instruments, i.e., the fact that for many instruments, monthly means are produced from measurements which span less than the full month in question. Similarly, annual mean sampling biases are well explained by non-uniformity in the month-to-month sampling by different instruments. Non-uniform sampling in latitude and longitude are shown to also lead to non-negligible sampling biases, which are most relevant for climatologies which are otherwise free of sampling biases due to non-uniform temporal sampling
Stratospheric aerosol - Observations, processes, and impact on climate
Interest in stratospheric aerosol and its role in climate have increased over the last decade due to the observed increase in stratospheric aerosol since 2000 and the potential for changes in the sulfur cycle induced by climate change. This review provides an overview about the advances in stratospheric aerosol research since the last comprehensive assessment of stratospheric aerosol was published in 2006. A crucial development since 2006 is the substantial improvement in the agreement between in situ and space-based inferences of stratospheric aerosol properties during volcanically quiescent periods. Furthermore, new measurement systems and techniques, both in situ and space based, have been developed for measuring physical aerosol properties with greater accuracy and for characterizing aerosol composition. However, these changes induce challenges to constructing a long-term stratospheric aerosol climatology. Currently, changes in stratospheric aerosol levels less than 20% cannot be confidently quantified. The volcanic signals tend to mask any nonvolcanically driven change, making them difficult to understand. While the role of carbonyl sulfide as a substantial and relatively constant source of stratospheric sulfur has been confirmed by new observations and model simulations, large uncertainties remain with respect to the contribution from anthropogenic sulfur dioxide emissions. New evidence has been provided that stratospheric aerosol can also contain small amounts of nonsulfate matter such as black carbon and organics. Chemistry-climate models have substantially increased in quantity and sophistication. In many models the implementation of stratospheric aerosol processes is coupled to radiation and/or stratospheric chemistry modules to account for relevant feedback processes
Readout of a quantum processor with high dynamic range Josephson parametric amplifiers
We demonstrate a high dynamic range Josephson parametric amplifier (JPA) in
which the active nonlinear element is implemented using an array of rf-SQUIDs.
The device is matched to the 50 environment with a Klopfenstein-taper
impedance transformer and achieves a bandwidth of 250-300 MHz, with input
saturation powers up to -95 dBm at 20 dB gain. A 54-qubit Sycamore processor
was used to benchmark these devices, providing a calibration for readout power,
an estimate of amplifier added noise, and a platform for comparison against
standard impedance matched parametric amplifiers with a single dc-SQUID. We
find that the high power rf-SQUID array design has no adverse effect on system
noise, readout fidelity, or qubit dephasing, and we estimate an upper bound on
amplifier added noise at 1.6 times the quantum limit. Lastly, amplifiers with
this design show no degradation in readout fidelity due to gain compression,
which can occur in multi-tone multiplexed readout with traditional JPAs.Comment: 9 pages, 8 figure
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
Suppressing quantum errors by scaling a surface code logical qubit
Practical quantum computing will require error rates that are well below what
is achievable with physical qubits. Quantum error correction offers a path to
algorithmically-relevant error rates by encoding logical qubits within many
physical qubits, where increasing the number of physical qubits enhances
protection against physical errors. However, introducing more qubits also
increases the number of error sources, so the density of errors must be
sufficiently low in order for logical performance to improve with increasing
code size. Here, we report the measurement of logical qubit performance scaling
across multiple code sizes, and demonstrate that our system of superconducting
qubits has sufficient performance to overcome the additional errors from
increasing qubit number. We find our distance-5 surface code logical qubit
modestly outperforms an ensemble of distance-3 logical qubits on average, both
in terms of logical error probability over 25 cycles and logical error per
cycle ( compared to ). To investigate
damaging, low-probability error sources, we run a distance-25 repetition code
and observe a logical error per round floor set by a single
high-energy event ( when excluding this event). We are able
to accurately model our experiment, and from this model we can extract error
budgets that highlight the biggest challenges for future systems. These results
mark the first experimental demonstration where quantum error correction begins
to improve performance with increasing qubit number, illuminating the path to
reaching the logical error rates required for computation.Comment: Main text: 6 pages, 4 figures. v2: Update author list, references,
Fig. S12, Table I
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