Layered architecture for quantum computing

We develop a layered quantum computer architecture, which is a systematic framework for tackling the individual challenges of developing a quantum computer while constructing a cohesive device design. We discuss many of the prominent techniques for implementing circuit-model quantum computing and introduce several new methods, with an emphasis on employing surface code quantum error correction. In doing so, we propose a new quantum computer architecture based on optical control of quantum dots. The timescales of physical hardware operations and logical, error-corrected quantum gates differ by several orders of magnitude. By dividing functionality into layers, we can design and analyze subsystems independently, demonstrating the value of our layered architectural approach. Using this concrete hardware platform, we provide resource analysis for executing fault-tolerant quantum algorithms for integer factoring and quantum simulation, finding that the quantum dot architecture we study could solve such problems on the timescale of days.Comment: 27 pages, 20 figure

Scalability of quantum computation with addressable optical lattices

We make a detailed analysis of error mechanisms, gate fidelity, and scalability of proposals for quantum computation with neutral atoms in addressable (large lattice constant) optical lattices. We have identified possible limits to the size of quantum computations, arising in 3D optical lattices from current limitations on the ability to perform single qubit gates in parallel and in 2D lattices from constraints on laser power. Our results suggest that 3D arrays as large as 100 x 100 x 100 sites (i.e., $\sim 10^6$ qubits) may be achievable, provided two-qubit gates can be performed with sufficiently high precision and degree of parallelizability. Parallelizability of long range interaction-based two-qubit gates is qualitatively compared to that of collisional gates. Different methods of performing single qubit gates are compared, and a lower bound of $1 \times 10^{-5}$ is determined on the error rate for the error mechanisms affecting $^{133}$Cs in a blue-detuned lattice with Raman transition-based single qubit gates, given reasonable limits on experimental parameters.Comment: 17 pages, 5 figures. Accepted for publication in Physical Review

Multiscale modeling of circular and elliptical particles in laminar shear flow

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POS0361 DNA METHYLATION SIGNATURES CHARACTERIZE PSORIASIS AND PSORIATIC ARTHRITIS IN MONOZYGOTIC TWINS DISCORDANT FOR THE DISEASE

Background:Psoriatic disease is a chronic inflammatory disorder spanning from skin disease (psoriasis) to psoriatic arthritis (PsA). The genetic background is insufficient to explain disease onset as illustrated by not very informative Genome Wide Association Studies and monozygotic (MZ) twin studies recently performed. It is strongly assumed that epigenetics may contribute to disease susceptibility modulating gene expression. DNA methylation has been found involved in several autoimmune inflammatory rheumatic diseases. Here we have analysed the DNA methylation profile of a selected cohort of MZ twins discordant for psoriasis/PsA.Objectives:To identify the methylome associated with psoriasis and PsA in the peripheral blood of MZ twins discordant for these conditions.Methods:Peripheral blood from 7 couples of MZ twins discordant for psoriatic disease was collected and DNA extracted for a genome-wide evaluation of the DNA methylation profile, with the Infinium MethylationEPIC BeadChip. Minfi and the packages of the Bioconductor were used to analyse the data obtained. Quality control and exclusion criteria were applied to the raw data having a final number of 762.451 probes, which accounts for 88% of the total.Results:The approach first identified 2564 differentially methylated positions (DMPs; *p<0.005) with 19 genes potentially affected (with at least two DMPs within 1 kb of distance), including SMAD3 and SMARCA4/BRG1 involved in the Interferon and TGFβ pathways. Gene Ontology (GO) analysis of DMP-associated genes showed a significative enrichment (*p<0.005) in transcription factor binding, transcription corepressor and transcription coactivator activity, SMAD binding and histone -lysine-N-methyltransferase activity. To further validate the results, 5'-methylcytosine immunoprecipitation (MedIP) followed by Real Time PCR was performed to assess the methylation level of SMAD3 and SMARCA4/BRG1 promoters in the same cohort of MZ twins. We found significantly DNA methylation enrichment in SMARCA4/BRG1 promoter in psoriatic disease twins (p<0.05). SMAD3 and SMARCA4/BRG1 mRNA expression was also assessed to evaluate any inverse correlation with promoter methylation level, on the MZ cohort used for the EPIC array (n=4) and on a cohort of PsA/Ps patients (n=8) and appropriate healthy controls (n=3). Reduced mRNA expression (p<0.05) was demonstrated for SMARCA4/BRG1 (n=4). Conversely, no changes were found for SMAD3.Conclusion:We report the first DNA methylation approach in MZ twins discordant for psoriatic disease. We believe that the observed changes in SMAD3 and SMARCA/BRG1 genes may suggest an epigenetic imbalance of chromatin remodelling factors involved in inflammation pathways with a potential role in PsA/psoriasis immunopathogenesis.Disclosure of Interests:None declare

It Is the time to think about a treat-to-target strategy for knee osteoarthritis

Osteoarthritis (OA) is a rheumatic disease that affects the well-being of the patient, compromises physical and mental function, and affects other quality of life aspects. In the literature, several evidence-based guidelines and recommendations for the management of knee osteoarthritis (KOA) are available. These recommendations list the different therapeutic options rather than addressing a hierarchy between the treatments and defining the real target. Therefore, a question arises: are patients and physicians satisfied with the current management of KOA? Actually, the answer may be negative, thus suggesting a change in our therapeutic strategies. In this article, we address this challenge by suggesting that it is time to develop a “treat to target strategy” for KO

Personalized medicine in rheumatology : the paradigm of serum autoantibodies

The sequencing of the human genome is now well recognized as the starting point of personalized medicine. Nonetheless, everyone is unique and can develop different phenotypes of the same disease, despite identical genotypes, as well illustrated by discordant monozygotic twins. To recognize these differences, one of the easiest and most familiar examples of biomarkers capable of identifying and predicting the outcome of patients is represented by serum autoantibodies. In this review, we will describe the concept of personalized medicine and discuss the predictive, prognostic and preventive role of antinuclear antibodies (ANA), anti-citrullinated peptide antibodies (ACPA), rare autoantibodies and anti-drug antibodies (ADA), to evaluate how these can help to identify different disease immune phenotypes and to choose the best option for treating and monitoring rheumatic patients in everyday practice. The importance of ANA resides in the prediction of clinical manifestations in systemic sclerosis and systemic lupus erythematosus and their association with malignancies. ACPA have a predictive role in rheumatoid arthritis, they are associated with the development of a more aggressive disease, extra-articular manifestations and premature mortality in RA patients; moreover, they are capable of predicting therapeutic response. Rare autoantibodies are associated with different disease manifestations and also with a greater incidence of cancer. The determination of ADA levels may be useful in patients where the clinical efficacy of TNF-\u3b1 inhibitor has dropped, for the assessment of a right management. The resulting scenario supports serum autoantibodies as the cornerstone of personalized medicine in autoimmune diseases

Simulating chemistry efficiently on fault-tolerant quantum computers

Quantum computers can in principle simulate quantum physics exponentially faster than their classical counterparts, but some technical hurdles remain. Here we consider methods to make proposed chemical simulation algorithms computationally fast on fault-tolerant quantum computers in the circuit model. Fault tolerance constrains the choice of available gates, so that arbitrary gates required for a simulation algorithm must be constructed from sequences of fundamental operations. We examine techniques for constructing arbitrary gates which perform substantially faster than circuits based on the conventional Solovay-Kitaev algorithm [C.M. Dawson and M.A. Nielsen, \emph{Quantum Inf. Comput.}, \textbf{6}:81, 2006]. For a given approximation error $\epsilon$, arbitrary single-qubit gates can be produced fault-tolerantly and using a limited set of gates in time which is $O(\log \epsilon)$ or $O(\log \log \epsilon)$; with sufficient parallel preparation of ancillas, constant average depth is possible using a method we call programmable ancilla rotations. Moreover, we construct and analyze efficient implementations of first- and second-quantized simulation algorithms using the fault-tolerant arbitrary gates and other techniques, such as implementing various subroutines in constant time. A specific example we analyze is the ground-state energy calculation for Lithium hydride.Comment: 33 pages, 18 figure

Nailfold videocapillaroscopy and serum VEGF levels in scleroderma are associated with internal organ involvement

Purpose: Nailfold videocapillaroscopy (NVC) identifies the microvascular hallmarks of systemic sclerosis (SSc) and vascular endothelial growth factor (VEGF) and may play a pivotal role in the associated vasculopathy. The aim of the present study was to compare NVC alterations with clinical subsets, internal organ involvement, and serum VEGF levels in a cohort of selected SSc cases. Methods: We studied 44 patients with SSc who were evaluated within 3\ua0months from enrollment by NVC, skin score, severity index, pulmonary function tests, carbon monoxide diffusing capacity (DLCO), echocardiography, pulmonary high-resolution computed tomography (HRCT), gastroesophageal (GE) endoscopy or manometry or X-ray, and serum autoantibodies. Serum VEGF-A levels were determined by ELISA in 72 SSc patients and 31 healthy controls. Results: Giant capillaries were inversely correlated with age (p\ua0=\ua00.034, r\ua0=\ua0 120.34) and to the extent of reticular pattern at HRCT (p\ua0=\ua00.04, r\ua0=\ua0 120.5). Avascular areas were directly correlated with capillaroscopy skin ulcer risk index (CSURI) (p\ua0=\ua00.006, r\ua0=\ua0+0.4) and severity index (p\ua0=\ua00.004, r\ua0=\ua0+0.5). The mean capillary density was directly correlated to the ulcer number (p\ua0=\ua00.02, r\ua0=\ua0+0.4) and to DLCO/alveolar volume (p\ua0=\ua00.02, r\ua0=\ua0+0.4) and inversely correlated with severity index (p\ua0=\ua00.01, r\ua0=\ua0 120.4) and skin score (p\ua0=\ua00.02, r\ua0=\ua0 120.4). Serum VEGF levels were higher in the SSc population vs controls (p\ua0=\ua00.03) and inversely correlated with DLCO (p\ua0=\ua00.01, r\ua0= 120.4) and directly with ground-glass and reticular pattern at HRCT (p\ua0=\ua00.04, r\ua0=\ua0+0.4 for both). Conclusions: Our data suggest the importance of NVC not only for the diagnosis, but also for the global evaluation of SSc patients. Of note, serum VEGF levels may act as a biomarker of interstitial lung involvement

Path Selection for Quantum Repeater Networks

Quantum networks will support long-distance quantum key distribution (QKD) and distributed quantum computation, and are an active area of both experimental and theoretical research. Here, we present an analysis of topologically complex networks of quantum repeaters composed of heterogeneous links. Quantum networks have fundamental behavioral differences from classical networks; the delicacy of quantum states makes a practical path selection algorithm imperative, but classical notions of resource utilization are not directly applicable, rendering known path selection mechanisms inadequate. To adapt Dijkstra's algorithm for quantum repeater networks that generate entangled Bell pairs, we quantify the key differences and define a link cost metric, seconds per Bell pair of a particular fidelity, where a single Bell pair is the resource consumed to perform one quantum teleportation. Simulations that include both the physical interactions and the extensive classical messaging confirm that Dijkstra's algorithm works well in a quantum context. Simulating about three hundred heterogeneous paths, comparing our path cost and the total work along the path gives a coefficient of determination of 0.88 or better.Comment: 12 pages, 8 figure