Optimal quantum control with poor statistics

Control of quantum systems is a central element of high-precision experiments and the development of quantum technological applications. Control pulses that are typically temporally or spatially modulated are often designed based on theoretical simulations. As we gain control over larger and more complex quantum systems, however, we reach the limitations of our capabilities of theoretical modeling and simulations, and learning how to control a quantum system based exclusively on experimental data can help us to exceed those limitations. Due to the intrinsic probabilistic nature of quantum mechanics, it is fundamentally necessary to repeat measurements on individual quantum systems many times in order to estimate the expectation value of an observable with good accuracy. Control algorithms requiring accurate data can thus imply an experimental effort that negates the benefits of avoiding theoretical modeling. We present a control algorithm based on Bayesian optimization that finds optimal control solutions in the presence of large measurement shot noise and even in the limit of single-shot measurements. With several numerical and experimental examples we demonstrate that this method is capable of finding excellent control solutions with minimal experimental effor

Dynamical Modelling of a Wastewater Treatment Process of the Metallurgical Industry

In this paper we consider the dynamical modelling and parameter identification of a biological wastewater treatment process from the galvanisation industry used to remove a mixture of organic matter and surface-active agents. In the present study we have considered mainly the measurements of dissolved oxygen and COD (Chemical Oxygen Demand) collected on laboratory and pilot-scale processes. From the identification study, we can conclude that the degradation is characterized by two reactions: one part of the easily biodegradable effluent is degraded with fast kinetics while the remaining part of the effluent is degraded via a slower reaction. This has been modelled by considering two different classes of substrates that indeed correspond to real components of the mixture

Probing the Dust Properties of Galaxies up to Submillimetre Wavelengths I. The Spectral Energy Distribution of dwarf galaxies using LABOCA

We present 870 micron images of four low metallicity galaxies (NGC1705, Haro11, Mrk1089 and UM311) observed with the Large APEX BOlometer CAmera (LABOCA). We model their spectral energy distributions combining the submm observations of LABOCA, 2MASS, IRAS, Spitzer photometric data and the IRS data for Haro11. We find that a significant mass of dust is revealed when using submm constraints compared to that measured with only mid-IR to far-IR observations extending only to 160 microns. For NGC1705 and Haro11, an excess in submillimeter wavelengths is detected and we rerun our SED procedure adding a cold dust component (10K) to better describe the high 870 micron flux derived from LABOCA observations, which significantly improves the fit. We find that at least 70% of the dust mass of these two galaxies can reside in a cold dust component. We also show that the subsequent dust-to-gas mass ratios, considering HI and CO observations, can be strikingly high for Haro11 in comparison with what is usually expected for these low-metallicity environments. Furthermore, we derive the SFR of our galaxies and compare them to the Schmidt law. Haro11 falls anomalously far from the Schmidt relation. These results may suggest that a reservoir of hidden gas could be present in molecular form not traced by the current CO observations. We also derive the total IR luminosities derived from our models and compare them with relations that derive this luminosity from Spitzer bands. We find that the Draine & Li (2007) formula compares well to our direct IR determinations.Comment: 22 pages, 7 figures, 10 tables, accepted for publication in A&

Parasitic helminths induce fetal-like reversion in the intestinal stem cell niche.

Epithelial surfaces form critical barriers to the outside world and are continuously renewed by adult stem cells1. Whereas dynamics of epithelial stem cells during homeostasis are increasingly well understood, how stem cells are redirected from a tissue-maintenance program to initiate repair after injury remains unclear. Here we examined infection by Heligmosomoides polygyrus, a co-evolved pathosymbiont of mice, to assess the epithelial response to disruption of the mucosal barrier. H. polygyrus disrupts tissue integrity by penetrating the duodenal mucosa, where it develops while surrounded by a multicellular granulomatous infiltrate2. Crypts overlying larvae-associated granulomas did not express intestinal stem cell markers, including Lgr53, in spite of continued epithelial proliferation. Granuloma-associated Lgr5- crypt epithelium activated an interferon-gamma (IFN-γ)-dependent transcriptional program, highlighted by Sca-1 expression, and IFN-γ-producing immune cells were found in granulomas. A similar epithelial response accompanied systemic activation of immune cells, intestinal irradiation, or ablation of Lgr5+ intestinal stem cells. When cultured in vitro, granuloma-associated crypt cells formed spheroids similar to those formed by fetal epithelium, and a sub-population of H. polygyrus-induced cells activated a fetal-like transcriptional program, demonstrating that adult intestinal tissues can repurpose aspects of fetal development. Therefore, re-initiation of the developmental program represents a fundamental mechanism by which the intestinal crypt can remodel itself to sustain function after injury

Grking the Smoothened signal.

The kinase GRK2 has been linked to the clinically important Hedgehog (HH) signaling pathway, where it is paradoxically required for signal transduction yet also promotes internalization and degradation of the critical HH signal transducer Smoothened. Two reports by Liet aland Pusapatiet alin this issue ofScience Signalingprovide new insights into the role of GRK2 in HH signaling

Nanomaterials to avoid and destroy protein aggregates

Aggregation of proteins is involved in many disorders. Besides amyloid fibrils, which mostly form in the brain, other kind of protein aggregates can lead, for example, to clots in the blood or floaters in the vitreous of the eye. This review aims to overview on how nanomaterials could be employed to avoid and destroy most diverse protein aggregates. Indeed, thanks to their recognized versatility, (stimuli-responsive) nanomaterials may offer attractive features against harmful protein aggregates. However, despite the many conceptually interesting strategies it appears that most important information on both the in vivo efficacy and safety of nanotechnology based prevention or destruction of protein aggregates, which is highly needed to pave the way to clinically relevant therapies, remains missing

Inference-Based Quantum Sensing

In a standard Quantum Sensing (QS) task one aims at estimating an unknown parameter $\theta$, encoded into an $n$-qubit probe state, via measurements of the system. The success of this task hinges on the ability to correlate changes in the parameter to changes in the system response $\mathcal{R}(\theta)$ (i.e., changes in the measurement outcomes). For simple cases the form of $\mathcal{R}(\theta)$ is known, but the same cannot be said for realistic scenarios, as no general closed-form expression exists. In this work we present an inference-based scheme for QS. We show that, for a general class of unitary families of encoding, $\mathcal{R}(\theta)$ can be fully characterized by only measuring the system response at $2n+1$ parameters. In turn, this allows us to infer the value of an unknown parameter given the measured response, as well as to determine the sensitivity of the sensing scheme, which characterizes its overall performance. We show that inference error is, with high probability, smaller than $\delta$, if one measures the system response with a number of shots that scales only as $\Omega(\log^3(n)/\delta^2)$. Furthermore, the framework presented can be broadly applied as it remains valid for arbitrary probe states and measurement schemes, and, even holds in the presence of quantum noise. We also discuss how to extend our results beyond unitary families. Finally, to showcase our method we implement it for a QS task on real quantum hardware, and in numerical simulations.Comment: 5+10 pages, 3+5 figure

Dye-Sensitized Solar Cells Employing a Single Film of Mesoporous TiO2 Beads Achieve Power Conversion Efficiencies Over 10%

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Opposing Activities of Notch and Wnt Signaling Regulate Intestinal Stem Cells and Gut Homeostasis

SummaryProper organ homeostasis requires tight control of adult stem cells and differentiation through the integration of multiple inputs. In the mouse small intestine, Notch and Wnt signaling are required both for stem cell maintenance and for a proper balance of differentiation between secretory and absorptive cell lineages. In the absence of Notch signaling, stem cells preferentially generate secretory cells at the expense of absorptive cells. Here, we use function-blocking antibodies against Notch receptors to demonstrate that Notch blockade perturbs intestinal stem cell function by causing a derepression of the Wnt signaling pathway, leading to misexpression of prosecretory genes. Importantly, attenuation of the Wnt pathway rescued the phenotype associated with Notch blockade. These studies bring to light a negative regulatory mechanism that maintains stem cell activity and balanced differentiation, and we propose that the interaction between Wnt and Notch signaling described here represents a common theme in adult stem cell biology