7,365 research outputs found
Optimal tracking for pairs of qubit states
In classical control theory, tracking refers to the ability to perform
measurements and feedback on a classical system in order to enforce some
desired dynamics. In this paper we investigate a simple version of quantum
tracking, namely, we look at how to optimally transform the state of a single
qubit into a given target state, when the system can be prepared in two
different ways, and the target state depends on the choice of preparation. We
propose a tracking strategy that is proved to be optimal for any input and
target states. Applications in the context of state discrimination, state
purification, state stabilization and state-dependent quantum cloning are
presented, where existing optimality results are recovered and extended.Comment: 15 pages, 8 figures. Extensive revision of text, optimality results
extended, other physical applications include
Quantum Heating of a nonlinear resonator probed by a superconducting qubit
We measure the quantum fluctuations of a pumped nonlinear resonator, using a
superconducting artificial atom as an in-situ probe. The qubit excitation
spectrum gives access to the frequency and temperature of the intracavity field
fluctuations. These are found to be in agreement with theoretical predictions;
in particular we experimentally observe the phenomenon of quantum heating
Partial mixing and the formation of 13C pockets in AGB stars: effects on the s-process elements
The production of the elements heavier than iron via slow neutron captures
(the s process) is a main feature of the contribution of asymptotic giant
branch (AGB) stars of low mass (< 5 Msun) to the chemistry of the cosmos.
However, our understanding of the main neutron source, the 13C(alpha,n)16O
reaction, is still incomplete. It is commonly assumed that in AGB stars mixing
beyond convective borders drives the formation of 13C pockets. However, there
is no agreement on the nature of such mixing and free parameters are present.
By means of a parametric model we investigate the impact of different mixing
functions on the final s-process abundances in low-mass AGB models. Typically,
changing the shape of the mixing function or the mass extent of the region
affected by the mixing produce the same results. Variations in the relative
abundance distribution of the three s-process peaks (Sr, Ba, and Pb) are
generally within +/-0.2 dex, similar to the observational error bars. We
conclude that other stellar uncertainties - the effect of rotation and of
overshoot into the C-O core - play a more important role than the details of
the mixing function. The exception is at low metallicity, where the Pb
abundance is significantly affected. In relation to the composition observed in
stardust SiC grains from AGB stars, the models are relatively close to the data
only when assuming the most extreme variation in the mixing profile.Comment: 17 pages, 8 figures, 6 tables, accepted for publications on Monthly
Notices of the Royal Astronomical Societ
Projections of future air quality are uncertain. But which source of uncertainty is most important?
Understanding how air pollution events may change in the future is of key importance to decision makers. Multi-model intercomparison projects focusing on atmospheric chemistry and air quality have been performed to inform the latest IPCC assessments. Future anthropogenic emission changes have generally been the foci of such model experiments, envisaged as the dominant driver of future atmospheric composition. The latest model assessments such as AerChemMIP utilize multi-model ensembles but also have limited individual model ensembles which permit different sources of uncertainty to be characterized. The recent study by Fiore et al. (2022, https://doi.org/10.1029/2021JD035985) specifically considers a multi-model and multi-member ensemble approach. It adds to the quantification of uncertainty in future projections through delineating uncertainty due to model diversity and due to internal or natural climate variability within the climate system, for mean and high PM2.5 air pollution events over the Eastern USA in the 21st century. Exploring the separate roles of internal climate variability and model diversity adds further value to the important research issue of quantifying how future anthropogenic climate change impacts air quality. Future multi-model intercomparisons need to balance the additional knowledge gained from research into understanding multiple sources of uncertainty that can inform decision making vs. the resource costs of performing these experiments using Earth System Models with interactive chemistry
Low Gain Avalanche Detectors (LGAD) for particle physics and synchrotron applications
A new avalanche silicon detector concept is introduced with a low gain in the region of ten, known as a Low Gain Avalanche Detector, LGAD. The detector's characteristics are simulated via a full process simulation to obtain the required doping profiles which demonstrate the desired operational characteristics of high breakdown voltage (500 V) and a gain of 10 at 200 V reverse bias for X-ray detection. The first low gain avalanche detectors fabricated by Micron Semiconductor Ltd are presented. The doping profiles of the multiplication junctions were measured with SIMS and reproduced by simulating the full fabrication process which enabled further development of the manufacturing process. The detectors are 300 μm thick p-type silicon with a resistivity of 8.5 kΩcm, which fully depletes at 116 V. The current characteristics are presented and demonstrate breakdown voltages in excess of 500 V and a current density of 40 to 100 nAcm−2 before breakdown measured at 20oC. The gain of the LGAD has been measured with a red laser (660 nm) and shown to be between 9 and 12 for an external bias voltage range from 150 V to 300 V
Circuit QED with a Nonlinear Resonator : ac-Stark Shift and Dephasing
We have performed spectroscopic measurements of a superconducting qubit
dispersively coupled to a nonlinear resonator driven by a pump microwave field.
Measurements of the qubit frequency shift provide a sensitive probe of the
intracavity field, yielding a precise characterization of the resonator
nonlinearity. The qubit linewidth has a complex dependence on the pump
frequency and amplitude, which is correlated with the gain of the nonlinear
resonator operated as a small-signal amplifier. The corresponding dephasing
rate is found to be close to the quantum limit in the low-gain limit of the
amplifier.Comment: Paper : 4 pages, 3 figures; Supplementary material : 1 page, 1 figur
Sensitivity optimization in quantum parameter estimation
We present a general framework for sensitivity optimization in quantum
parameter estimation schemes based on continuous (indirect) observation of a
dynamical system. As an illustrative example, we analyze the canonical scenario
of monitoring the position of a free mass or harmonic oscillator to detect weak
classical forces. We show that our framework allows the consideration of
sensitivity scheduling as well as estimation strategies for non-stationary
signals, leading us to propose corresponding generalizations of the Standard
Quantum Limit for force detection.Comment: 15 pages, RevTe
The neutral silicon-vacancy center in diamond: spin polarization and lifetimes
We demonstrate optical spin polarization of the neutrally-charged
silicon-vacancy defect in diamond (), an defect which
emits with a zero-phonon line at 946 nm. The spin polarization is found to be
most efficient under resonant excitation, but non-zero at below-resonant
energies. We measure an ensemble spin coherence time
at low-temperature, and a spin relaxation limit of . Optical
spin state initialization around 946 nm allows independent initialization of
and within the same optically-addressed
volume, and emits within the telecoms downconversion band to
1550 nm: when combined with its high Debye-Waller factor, our initial results
suggest that is a promising candidate for a long-range
quantum communication technology
Agent-Based Modeling of Intracellular Transport
We develop an agent-based model of the motion and pattern formation of
vesicles. These intracellular particles can be found in four different modes of
(undirected and directed) motion and can fuse with other vesicles. While the
size of vesicles follows a log-normal distribution that changes over time due
to fusion processes, their spatial distribution gives rise to distinct
patterns. Their occurrence depends on the concentration of proteins which are
synthesized based on the transcriptional activities of some genes. Hence,
differences in these spatio-temporal vesicle patterns allow indirect
conclusions about the (unknown) impact of these genes.
By means of agent-based computer simulations we are able to reproduce such
patterns on real temporal and spatial scales. Our modeling approach is based on
Brownian agents with an internal degree of freedom, , that represents
the different modes of motion. Conditions inside the cell are modeled by an
effective potential that differs for agents dependent on their value .
Agent's motion in this effective potential is modeled by an overdampted
Langevin equation, changes of are modeled as stochastic transitions
with values obtained from experiments, and fusion events are modeled as
space-dependent stochastic transitions. Our results for the spatio-temporal
vesicle patterns can be used for a statistical comparison with experiments. We
also derive hypotheses of how the silencing of some genes may affect the
intracellular transport, and point to generalizations of the model
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