Dynamical Cluster Quantum Monte Carlo Study of the Single Particle Spectra of Strongly Interacting Fermion Gases

We study the single-particle spectral function of resonantly-interacting fermions in the unitary regime, as described by the three-dimensional attractive Hubbard model in the dilute limit. Our approach, based on the Dynamical Cluster Approximation and the Maximum Entropy Method, shows the emergence of a gap with decreasing temperature, as reported in recent cold-atom photoemission experiments, for coupling values that span the BEC-BCS crossover. By comparing the behavior of the spectral function to that of the imaginary time dynamical pairing susceptibility, we attribute the development of the gap to the formation of local bound atom pairs.Comment: 4 pages, 4 figures, accepted by PRA Rapid Communication

Loschmidt echo and fidelity decay near an exceptional point

Non-Hermitian classical and open quantum systems near an exceptional point (EP) are known to undergo strong deviations in their dynamical behavior under small perturbations or slow cycling of parameters as compared to Hermitian systems. Such a strong sensitivity is at the heart of many interesting phenomena and applications, such as the asymmetric breakdown of the adiabatic theorem, enhanced sensing, non-Hermitian dynamical quantum phase transitions and photonic catastrophe. Like for Hermitian systems, the sensitivity to perturbations on the dynamical evolution can be captured by Loschmidt echo and fidelity after imperfect time reversal or quench dynamics. Here we disclose a rather counterintuitive phenomenon in certain non-Hermitian systems near an EP, namely the deceleration (rather than acceleration) of the fidelity decay and improved Loschmidt echo as compared to their Hermitian counterparts, despite large (non-perturbative) deformation of the energy spectrum introduced by the perturbations. This behavior is illustrated by considering the fidelity decay and Loschmidt echo for the single-particle hopping dynamics on a tight-binding lattice under an imaginary gauge field.Comment: 11 pages, 6 figures, to appear in Annalen der Physi

Microbubble Cavitation Imaging

Ultrasound cavitation of microbubble contrast agents has a potential for therapeutic applications such as sonothrombolysis (STL) in acute ischemic stroke. For safety, efficacy, and reproducibility of treatment, it is critical to evaluate the cavitation state (moderate oscillations, stable cavitation, and inertial cavitation) and activity level in and around a treatment area. Acoustic passive cavitation detectors (PCDs) have been used to this end but do not provide spatial information. This paper presents a prototype of a 2-D cavitation imager capable of producing images of the dominant cavitation state and activity level in a region of interest. Similar to PCDs, the cavitation imaging described here is based on the spectral analysis of the acoustic signal radiated by the cavitating microbubbles: ultraharmonics of the excitation frequency indicate stable cavitation, whereas elevated noise bands indicate inertial cavitation; the absence of both indicates moderate oscillations. The prototype system is a modified commercially available ultrasound scanner with a sector imaging probe. The lateral resolution of the system is 1.5 mm at a focal depth of 3 cm, and the axial resolution is 3 cm for a therapy pulse length of 20 mu s. The maximum frame rate of the prototype is 2 Hz. The system has been used for assessing and mapping the relative importance of the different cavitation states of a microbubble contrast agent. In vitro (tissue-mimicking flow phantom) and in vivo (heart, liver, and brain of two swine) results for cavitation states and their changes as a function of acoustic amplitude are presented

The future of Earth observation in hydrology

In just the past 5 years, the field of Earth observation has progressed beyond the offerings of conventional space-agency-based platforms to include a plethora of sensing opportunities afforded by CubeSats, unmanned aerial vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically of the order of 1 billion dollars per satellite and with concept-to-launch timelines of the order of 2 decades (for new missions). More recently, the proliferation of smart-phones has helped to miniaturize sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Start-up companies that did not exist a decade ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of traditional satellite missions. With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-metre resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via high-altitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the "internet of things" as an entirely new measurement domain. Such global access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparent is that the tools and techniques afforded by this array of novel and game-changing sensing platforms present our community with a unique opportunity to develop new insights that advance fundamental aspects of the hydrological sciences. To accomplish this will require more than just an application of the technology: in some cases, it will demand a radical rethink on how we utilize and exploit these new observing systems

The non-centrosymmetric lamellar phase in blends of ABC triblock and ac diblock copolymers

The phase behaviour of blends of ABC triblock and ac diblock copolymers is examined using self-consistent field theory. Several equilibrium lamellar structures are observed, depending on the volume fraction of the diblocks, phi_2, the monomer interactions, and the degrees of polymerization of the copolymers. For segregations just above the order-disorder transition the triblocks and diblocks mix together to form centrosymmetric lamellae. As the segregation is increased the triblocks and diblocks spatially separate either by macrophase-separating, or by forming a non-centrosymmetric (NCS) phase of alternating layers of triblock and diblock (...ABCcaABCca...). The NCS phase is stable over a narrow region near phi_2=0.4. This region is widest near the critical point on the phase coexistence curve and narrows to terminate at a triple point at higher segregation. Above the triple point there is two-phase coexistence between almost pure triblock and diblock phases. The theoretical phase diagram is consistent with experiments.Comment: 9 pages, 8 figures, submitted to Macromolecule

Effects Of Attenuation And Thrombus Age On The Success Of Ultrasound And Microbubble-Mediated Thrombus Dissolution

The purpose of this study was to examine the effects of applied mechanical index, incident angle, attenuation and thrombus age on the ability of 2-D vs. 3-D diagnostic ultrasound and microbubbles to dissolve thrombi. A total of 180 occlusive porcine arterial thrombi of varying age (3 or 6 h) were examined in a flow system. A tissue-mimicking phantom of varying thickness (5 to 10 cm) was placed over the thrombosed vessel and the 2-D or 3-D diagnostic transducer aligned with the thrombosed vessel using a positioning system. Diluted lipid-encapsulated microbubbles were infused during ultrasound application. Percent thrombus dissolution (%TD) was calculated by comparison of clot mass before and after treatment. Both 2-D and 3-D-guided ultrasound increased %TD compared with microbubbles alone, but %TD achieved with 6-h-old thrombi was significantly less than 3-h-old thrombi. Thrombus dissolution was achieved at 10 cm tissue-mimicking depths, even without inertial cavitation. In conclusion, diagnostic 2-D or 3-D ultrasound can dissolve thrombi with intravenous nontargeted microbubbles, even at tissue attenuation distances of up to 10 cm. This treatment modality is less effective, however, for older aged thrombi. (E-mail: [email protected]) (C) 2011 World Federation for Ultrasound in Medicine & Biology

Pose-Normalized Image Generation for Person Re-identification

Person Re-identification (re-id) faces two major challenges: the lack of cross-view paired training data and learning discriminative identity-sensitive and view-invariant features in the presence of large pose variations. In this work, we address both problems by proposing a novel deep person image generation model for synthesizing realistic person images conditional on the pose. The model is based on a generative adversarial network (GAN) designed specifically for pose normalization in re-id, thus termed pose-normalization GAN (PN-GAN). With the synthesized images, we can learn a new type of deep re-id feature free of the influence of pose variations. We show that this feature is strong on its own and complementary to features learned with the original images. Importantly, under the transfer learning setting, we show that our model generalizes well to any new re-id dataset without the need for collecting any training data for model fine-tuning. The model thus has the potential to make re-id model truly scalable.Comment: 10 pages, 5 figure