Controlling excitation avalanches in driven Rydberg gases

Recent experiments with strongly interacting, driven Rydberg ensembles have introduced a promising setup for the study of self-organized criticality (SOC) in cold atom systems. Based on this setup, we theoretically propose a control mechanism for the paradigmatic avalanche dynamics of SOC in the form of a time-dependent drive amplitude. This gives access to a variety of avalanche dominated, self-organization scenarios, prominently including self-organized criticality, as well as sub- and supercritical dynamics. We analyze the dependence of the dynamics on external scales and spatial dimensionality. It demonstrates the potential of driven Rydberg systems as a playground for the exploration of an extended SOC phenomenology and their relation to other common scenarios of SOC, such as, e.g., in neural networks and on graphs

Majorana Loop Models for Measurement-Only Quantum Circuits

Projective measurements in random quantum circuits lead to a rich breadth of entanglement phases and extend the realm of non-unitary quantum dynamics. Here we explore the connection between measurement-only quantum circuits in one spatial dimension and the statistical mechanics of loop models in two dimensions. While Gaussian Majorana circuits admit a microscopic mapping to loop models, for non-Gaussian, i.e., generic Clifford, circuits a corresponding mapping may emerge only on a coarse grained scale. We then focus on a fundamental symmetry of loop models: the orientability of world lines. We discuss how orientability enters in the measurement framework, acting as a separatrix for the universal long-wavelength behavior in a circuit. When orientability is broken, the circuit falls into the universality class of closely packed loops with crossings (CPLC) and features a Goldstone phase with a peculiar, universal $\log^2(L)$-scaling of the entanglement entropy. In turn, when orientability is preserved, the long-wavelength behavior of the circuit mimics that of (coupled) two-dimensional Potts models. We demonstrate the strength of the loop model approach by numerically simulating a variety of measurement-only Clifford circuits. Upon varying the set of measured operators, a rich circuit dynamics is observed, ranging from CPLC to the $1$-state Potts model (percolation), the $2$-state Potts model (Ising) and coupled Potts models (BKT) universality class. Loop models thus provide a handle to access a large class of measurement-only circuits and yield a blueprint on how to realize desired entanglement phases by measurement

Controlling excitation avalanches in driven Rydberg gases

Recent experiments with strongly interacting, driven Rydberg ensembles have introduced a promising setup for the study of self-organized criticality (SOC) in cold atom systems. Based on this setup, we theoretically propose a control mechanism for the paradigmatic avalanche dynamics of SOC in the form of a time-dependent drive amplitude. This gives access to a variety of avalanche dominated, self-organization scenarios, prominently including self-organized criticality, as well as sub- and supercritical dynamics. We analyze the dependence of the dynamics on external scales and spatial dimensionality. It demonstrates the potential of driven Rydberg systems as a playground for the exploration of an extended SOC phenomenology and their relation to other common scenarios of SOC, such as, e.g., in neural networks and on graphs

Time-domain anyon interferometry in Kitaev honeycomb spin liquids and beyond

Motivated by recent experiments on the Kitaev honeycomb magnet α-RuCl₃, we introduce time-domain probes of the edge and quasiparticle content of non-Abelian spin liquids. Our scheme exploits ancillary quantum spins that communicate via time-dependent tunneling of energy into and out of the spin liquid's chiral Majorana edge state. We show that the ancillary-spin dynamics reveals the edge-state velocity and, in suitable geometries, detects individual non-Abelian anyons and emergent fermions via a time-domain counterpart of quantum-Hall anyon interferometry. We anticipate applications to a wide variety of topological phases in solid-state and cold-atoms settings

Impact of surface structure and feed gas composition on Bacillus subtilis endospore inactivation during direct plasma treatment

This study investigated the inactivation efficiency of cold atmospheric pressure plasma treatment on Bacillus subtilis endospores dependent on the used feed gas composition and on the surface, the endospores were attached on. Glass petri-dishes, glass beads, and peppercorns were inoculated with the same endospore density and treated with a radio frequency plasma jet. Generated reactive species were detected using optical emission spectroscopy. A quantitative polymerase chain reaction (qPCR) based ratio detection system was established to monitor the DNA damage during the plasma treatment. Argon + 0.135% vol. oxygen + 0.2% vol. nitrogen as feed gas emitted the highest amounts of UV-C photons and considerable amount of reactive oxygen and nitrogen species. Plasma generated with argon + 0.135% vol. oxygen was characterized by the highest emission of reactive oxygen species (ROS), whereas the UV-C emission was negligible. The use of pure argon showed a negligible emission of UV photons and atomic oxygen, however, the emission of vacuum (V)UV photons was assumed. Similar maximum inactivation results were achieved for the three feed gas compositions. The surface structure had a significant impact on the inactivation efficiency of the plasma treatment. The maximum inactivation achieved was between 2.4 and 2.8 log10 on glass petri-dishes and 3.9 to 4.6 log10 on glass beads. The treatment of peppercorns resulted in an inactivation lower than 1.0 log10. qPCR results showed a significant DNA damage for all gas compositions. Pure argon showed the highest results for the DNA damage ratio values, followed by argon + 0.135% vol. oxygen + 0.2% vol. nitrogen. In case of argon + 0.135% vol. oxygen the inactivation seems to be dominated by the action of ROS. These findings indicate the significant role of VUV and UV photons in the inactivation process of B. subtilis endospores

Urinary T Cells Identify Renal Antineutrophil Cytoplasmic Antibody-Associated Vasculitis and Predict Prognosis: A Proof of Concept Study

INTRODUCTION: Necrotizing crescentic glomerulonephritis is a major contributor to morbidity and mortality in Antineutrophil cytoplasmic antibodies (ANCA)-associated vasculitis (AAV). Because therapy relies on immunosuppressive agents with potentially severe adverse effects, a reliable noninvasive biomarker of disease activity is needed to guide treatment. METHODS: We used flow cytometry to quantify T cell subsets in blood and urine samples from 95 patients with AAV and 8 controls to evaluate their biomarker characteristics. These were compared to soluble markers, monocyte chemoattractant protein-1 (MCP-1), soluble CD163 (sCD163), soluble CD25 (sCD25), and complement C5a (C5a), measured using multiplex analysis. Available kidney biopsies (n = 21) were classified according to Berden. RESULTS: Patients with active renal AAV (rAAV) showed significantly higher urinary cell counts than those in remission, or those with extrarenal manifestation, or healthy controls. Urinary T cells showed robust discrimination of disease activity with superior performance compared to MCP-1 and sCD163. Patients whose kidney biopsies had been classified as “crescentic” according to Berden classification showed higher urinary T cell counts. Discordant regulatory T cells (Treg) proportions and CD4+/CD8+ ratio in blood and urine suggested that urinary cells reflect tissue migration rather than mere micro-bleeding. Furthermore, urinary Treg and T helper cells (TH17) patterns were associated with clinical response and risk of renal relapse. CONCLUSION: Urinary T cells reflect the renal inflammatory milieu in AAV and provide further insights into the pathogenesis of this chronic condition. Their promising potential as noninvasive diagnostic and prognostic biomarkers deserves further exploitation

An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups