312 research outputs found
Self-Excitation and Feedback Cooling of an Isolated Proton
The first one-proton self-excited oscillator (SEO) and one-proton feedback
cooling are demonstrated. In a Penning trap with a large magnetic gradient, the
SEO frequency is resolved to the high precision needed to detect a one-proton
spin flip. This is after undamped magnetron motion is sideband-cooled to a 14
mK theoretical limit, and despite random frequency shifts (larger than those
from a spin flip) that take place every time sideband cooling is applied in the
gradient. The observations open a possible path towards a million-fold improved
comparison of the antiproton and proton magnetic moments
Feedback-Optimized Operations with Linear Ion Crystals
We report on transport operations with linear crystals of 40Ca+ ions by
applying complex electric time-dependent potentials. For their control we use
the information obtained from the ions' fluorescence. We demonstrate that by
means of this feedback technique, we can transport a predefined number of ions
and also split and unify ion crystals. The feedback control allows for a robust
scheme, compensating for experimental errors as it does not rely on a precisely
known electrical modeling of the electric potentials in the ion trap
beforehand. Our method allows us to generate a self-learning voltage ramp for
the required process. With an experimental demonstration of a transport with
more than 99.8 % success probability, this technique may facilitate the
operation of a future ion based quantum processor
Implications of surface noise for the motional coherence of trapped ions
Electric noise from metallic surfaces is a major obstacle towards quantum
applications with trapped ions due to motional heating of the ions. Here, we
discuss how the same noise source can also lead to pure dephasing of motional
quantum states. The mechanism is particularly relevant at small ion-surface
distances, thus imposing a new constraint on trap miniaturization. By means of
a free induction decay experiment, we measure the dephasing time of the motion
of a single ion trapped 50~m above a Cu-Al surface. From the dephasing
times we extract the integrated noise below the secular frequency of the ion.
We find that none of the most commonly discussed surface noise models for ion
traps describes both, the observed heating as well as the measured dephasing,
satisfactorily. Thus, our measurements provide a benchmark for future models
for the electric noise emitted by metallic surfaces.Comment: (5 pages, 4 figures
Precision measurement and compensation of optical Stark shifts for an ion-trap quantum processor
Using optical Ramsey interferometry, we precisely measure the laser-induced
AC-stark shift on the -- "quantum bit" transition near 729
nm in a single trapped Ca ion. We cancel this shift using an
additional laser field. This technique is of particular importance for the
implementation of quantum information processing with cold trapped ions. As a
simple application we measure the atomic phase evolution during a rotation of the quantum bit.Comment: 4 pages, 4 figure
Production of entanglement in Raman three-level systems using feedback
We examine the theoretical limits of the generation of entanglement in a
damped coupled ion-cavity system using jump-based feedback. Using Raman
transitions to produce entanglement between ground states reduces the necessary
feedback bandwidth, but does not improve the overall effect of the spontaneous
emission on the final entanglement. We find that the fidelity of the resulting
entanglement will be limited by the asymmetries produced by vibrations in the
trap, but that the concurrence remains above 0.88 for realistic ion trap sizes.Comment: 8 pages, 8 figure
Optimal, reliable estimation of quantum states
Accurately inferring the state of a quantum device from the results of
measurements is a crucial task in building quantum information processing
hardware. The predominant state estimation procedure, maximum likelihood
estimation (MLE), generally reports an estimate with zero eigenvalues. These
cannot be justified. Furthermore, the MLE estimate is incompatible with error
bars, so conclusions drawn from it are suspect. I propose an alternative
procedure, Bayesian mean estimation (BME). BME never yields zero eigenvalues,
its eigenvalues provide a bound on their own uncertainties, and it is the most
accurate procedure possible. I show how to implement BME numerically, and how
to obtain natural error bars that are compatible with the estimate. Finally, I
briefly discuss the differences between Bayesian and frequentist estimation
techniques.Comment: RevTeX; 14 pages, 2 embedded figures. Comments enthusiastically
welcomed
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