111 research outputs found
Impact of ionizing radiation on superconducting qubit coherence
The practical viability of any qubit technology stands on long coherence
times and high-fidelity operations, with the superconducting qubit modality
being a leading example. However, superconducting qubit coherence is impacted
by broken Cooper pairs, referred to as quasiparticles, with a density that is
empirically observed to be orders of magnitude greater than the value predicted
for thermal equilibrium by the Bardeen-Cooper-Schrieffer (BCS) theory of
superconductivity. Previous work has shown that infrared photons significantly
increase the quasiparticle density, yet even in the best isolated systems, it
still remains higher than expected, suggesting that another generation
mechanism exists. In this Letter, we provide evidence that ionizing radiation
from environmental radioactive materials and cosmic rays contributes to this
observed difference, leading to an elevated quasiparticle density that would
ultimately limit superconducting qubits of the type measured here to coherence
times in the millisecond regime. We further demonstrate that introducing
radiation shielding reduces the flux of ionizing radiation and positively
correlates with increased coherence time. Albeit a small effect for today's
qubits, reducing or otherwise mitigating the impact of ionizing radiation will
be critical for realizing fault-tolerant superconducting quantum computers.Comment: 16 pages, 12 figure
High-Fidelity, Frequency-Flexible Two-Qubit Fluxonium Gates with a Transmon Coupler
We propose and demonstrate an architecture for fluxonium-fluxonium two-qubit
gates mediated by transmon couplers (FTF, for fluxonium-transmon-fluxonium).
Relative to architectures that exclusively rely on a direct coupling between
fluxonium qubits, FTF enables stronger couplings for gates using
non-computational states while simultaneously suppressing the static
controlled-phase entangling rate () down to kHz levels, all without
requiring strict parameter matching. Here we implement FTF with a flux-tunable
transmon coupler and demonstrate a microwave-activated controlled-Z (CZ) gate
whose operation frequency can be tuned over a 2 GHz range, adding frequency
allocation freedom for FTF's in larger systems. Across this range,
state-of-the-art CZ gate fidelities were observed over many bias points and
reproduced across the two devices characterized in this work. After optimizing
both the operation frequency and the gate duration, we achieved peak CZ
fidelities in the 99.85-99.9\% range. Finally, we implemented model-free
reinforcement learning of the pulse parameters to boost the mean gate fidelity
up to , averaged over roughly an hour between scheduled
training runs. Beyond the microwave-activated CZ gate we present here, FTF can
be applied to a variety of other fluxonium gate schemes to improve gate
fidelities and passively reduce unwanted interactions.Comment: 23 pages, 16 figure
Long-term functional health status and exercise test variables for patients with pulmonary atresia with intact ventricular septum: A Congenital Heart Surgeons Society study
Background: A bias favoring biventricular (BV) repair exists regarding choice of repair pathway for patients
with pulmonary atresia with intact ventricular septum (PAIVS). We sought to determine the implications of
moving borderline candidates down a BV route in terms of late functional health status (FHS) and exercise
capacity (EC).
Methods: Between 1987 and 1997, 448 neonates with PAIVS were enrolled in a multi-institutional study. Late
EC and FHS were assessed following repair (mean 14 years) using standardized exercise testing and 3 validated
FHS instruments. Relationships between FHS, EC, morphology, and 3 end states (ie, BV, univentricular [UV], or
1.5-ventricle repair [1.5V]) were evaluated.
Results: One hundred two of 271 end state survivors participated (63 BV, 25 UV, and 14 1.5V). Participants had
lower FHS scores in domains of physical functioning (P<.001) compared with age- and sex-matched normal
controls, but scored significantly higher in nearly all psychosocial domains. EC was higher in 1.5V-repair patients (P ¼ .02), whereas discrete FHS measures were higher in BV-repair patients. Peak oxygen consumption
was low across all groups, and was positively correlated with larger initial tricuspid valve z-score (P<.001), with
an enhanced effect within the BV-repair group.
Conclusions: Late patient-perceived physical FHS and measured EC are reduced, regardless of PAIVS repair
pathway, with an important dichotomy whereby patients with PAIVS believe they are doing well despite important physical impediments. For those with smaller initial tricuspid valve z-score, achievement of survival with
BV repair may be at a cost of late deficits in exercise capacity, emphasizing that better outcomes may be achieved
for borderline patients with a 1.5V- or UV-repair strategy. (J Thorac Cardiovasc Surg 2013;145:1018-27
Heart valve disease: investigation by cardiovascular magnetic resonance
Cardiovascular magnetic resonance (CMR) has become a valuable investigative tool in many areas of cardiac medicine. Its value in heart valve disease is less well appreciated however, particularly as echocardiography is a powerful and widely available technique in valve disease. This review highlights the added value that CMR can bring in valve disease, complementing echocardiography in many areas, but it has also become the first-line investigation in some, such as pulmonary valve disease and assessing the right ventricle. CMR has many advantages, including the ability to image in any plane, which allows full visualisation of valves and their inflow/outflow tracts, direct measurement of valve area (particularly for stenotic valves), and characterisation of the associated great vessel anatomy (e.g. the aortic root and arch in aortic valve disease). A particular strength is the ability to quantify flow, which allows accurate measurement of regurgitation, cardiac shunt volumes/ratios and differential flow volumes (e.g. left and right pulmonary arteries). Quantification of ventricular volumes and mass is vital for determining the impact of valve disease on the heart, and CMR is the 'Gold standard' for this. Limitations of the technique include partial volume effects due to image slice thickness, and a low ability to identify small, highly mobile objects (such as vegetations) due to the need to acquire images over several cardiac cycles. The review examines the advantages and disadvantages of each imaging aspect in detail, and considers how CMR can be used optimally for each valve lesion
Assumption-based argumentation with preferences and goals for patient-centric reasoning with interacting clinical guidelines
A paramount, yet unresolved issue in personalised medicine is that of automated reasoning with clinical guidelines in multimorbidity settings. This entails enabling machines to use computerised generic clinical guideline recommendations and patient-specific information to yield patient-tailored recommendations where interactions arising due to multimorbidities are resolved. This problem is further complicated by patient management desiderata, in particular the need to account for patient-centric goals as well as preferences of various parties involved. We propose to solve this problem of automated reasoning with interacting guideline recommendations in the context of a given patient by means of computational argumentation. In particular, we advance a structured argumentation formalism ABA+G (short for Assumption-Based Argumentation with Preferences (ABA+) and Goals) for integrating and reasoning with information about recommendations, interactions, patient’s state, preferences and prioritised goals. ABA+G combines assumption-based reasoning with preferences and goal-driven selection among reasoning outcomes. Specifically, we assume defeasible applicability of guideline recommendations with the general goal of patient well-being, resolve interactions (conflicts and otherwise undesirable situations) among recommendations based on the state and preferences of the patient, and employ patient-centered goals to suggest interaction-resolving, goal-importance maximising and preference-adhering recommendations. We use a well-established Transition-based Medical Recommendation model for representing guideline recommendations and identifying interactions thereof, and map the components in question, together with the given patient’s state, prioritised goals, and preferences over actions, to ABA+G for automated reasoning. In this, we follow principles of patient management and establish corresponding theoretical properties as well as illustrate our approach in realistic personalised clinical reasoning scenaria
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