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

Simulating multimodal seasonality in extreme daily precipitation occurrence

Floods pose multi-dimensional hazards to critical infrastructure and society and these hazards may increase under climate change. While flood conditions are dependent on catchment type and soil conditions, seasonal precipitation extremes also play an important role. The extreme precipitation events driving flood occurrence may arrive non-uniformly in time. In addition, their seasonal and inter-annual patterns may also cause sequences of several events and enhance likely flood responses. Spatial and temporal patterns of extreme daily precipitation occurrence are characterized across the UK. Extreme and very heavy daily precipitation is not uniformly distributed throughout the year, but exhibits spatial differences, arising from the relative proximity to the North Atlantic Ocean or North Sea. Periods of weeks or months are identified during which extreme daily precipitation occurrences are most likely to occur, with some regions of the UK displaying multimodal seasonality. A Generalized Additive Model is employed to simulate extreme daily precipitation occurrences over the UK from 1901-2010 and to allow robust statistical testing of temporal changes in the seasonal distribution. Simulations show that seasonality has the strongest correlation with intra-annual variations in extreme event occurrence, while Sea Surface Temperature (SST) and Mean Sea Level Pressure (MSLP) have the strongest correlation with inter-annual variations. The north and west of the UK are dominated by MSLP in the mid-North Atlantic and the south and east are dominated by local SST. All regions now have a higher likelihood of autumnal extreme daily precipitation than earlier in the twentieth century. This equates to extreme daily precipitation occurring earlier in the autumn in the north and west, and later in the autumn 41 in the south and east. The change in timing is accompanied by increases in the probability of extreme daily precipitation occurrences during the autumn, and in the number of days with a very high probability of an extreme event. These results indicate a higher probability of several extreme occurrences in succession and a potential increase in floodingNCAR is sponsored by the National Science Foundation. M.R.T. was partially supported by NSF EASM grant S1048841, the NCAR Weather and Climate Assessment Science Program and a NERC funded Postgraduate Research Studentship NE/G523498/1 (2008-2012). H.J.F. was supported by a NERC Postdoctoral Fellowship Award NE/D009588/1 (2006−2010) and is now funded by the Wolfson Foundation and the Royal Society as a Royal Society Wolfson Research Merit Award holder (WM140025)

Observations of Non-radial Pulsations in Radio Pulsars

We introduce a model for pulsars in which non-radial oscillations of high spherical degree (l) aligned to the magnetic axis of a spinning neutron star reproduce the morphological features of pulsar beams. In our model, rotation of the pulsar carries a pattern of pulsation nodes underneath our sightline, reproducing the longitude stationary structure seen in average pulse profiles, while the associated time-like oscillations reproduce "drifting subpulses"--features that change their longitude between successive pulsar spins. We will show that the presence of nodal lines can account for observed 180 degree phase jumps in drifting subpulses and their otherwise poor phase stability, even if the time-like oscillations are strictly periodic. Our model can also account for the "mode changes" and "nulls" observed in some pulsars as quasiperiodic changes between pulsation modes of different l or radial overtone n, analogous to pulsation mode changes observed in oscillating white dwarf stars. We will discuss other definitive and testable requirements of our model and show that they are qualitatively supported by existing data. While reserving judgment until the completion of quantitative tests, we are inspired enough by the existing observational support for our model to speculate about the excitation mechanism of the non-radial pulsations, the physics we can learn from them, and their relationship to the period evolution of pulsars.Comment: 28 pages, 9 figures (as separate png files), Astrophysical Journal, in pres

Low Electron Temperatures Observed at Mars by MAVEN on Dayside Crustal Magnetic Field Lines

An edited version of this paper was published by AGU. Copyright 2019 American Geophysical Union.The ionospheric electron temperature is important for determining the neutral/photochemical escape rate from the Martian atmosphere via the dissociative recombination of O2+. The Langmuir Probe and Waves instrument onboard MAVEN (Mars Atmosphere and Volatile EvolutioN) measures electron temperatures in the ionosphere. The current paper studies electron temperatures in the dayside for two regions where (1) crustal magnetic fields are dominant and (2) draped magnetic fields are dominant. Overall, the electron temperature is lower in the crustal‐field regions, namely, the strong magnetic field region, which is due to a transport of cold electrons along magnetic field lines from the lower to upper atmosphere. The electron temperature is also greater for high solar extreme ultraviolet conditions, which is associated with the local extreme ultraviolet energy deposition. The current models underestimate the electron temperature above 250‐km altitude in the crustal‐field region. Electron heat conduction associated with a photoelectron transport in the crustal‐field regions is altered due to kinetic effects, such the magnetic mirror and/or ambipolar electric field because the electron mean free path exceeds the relevant length scale for electron temperature. The mirror force can affect the electron and heat transport between low altitudes, where the neutral density and related electron cooling rates are the greatest, and high altitudes, while the ambipolar electric field decelerates the electron's upward motion. These effects have not been included in current models of the electron energetics, and consideration of such effects on the electron temperature in the crustal‐field region should be considered for future numerical simulations

Evaluating the discriminating capacity of cell death (apoptotic) biomarkers in sepsis.

Background: Sepsis biomarker panels that provide diagnostic and prognostic discrimination in sepsis patients would be transformative to patient care. We assessed the mortality prediction and diagnostic discriminatory accuracy of two biomarkers reflective of cell death (apoptosis), circulating cell-free DNA (cfDNA), and nucleosomes. Methods: The cfDNA and nucleosome levels were assayed in plasma samples acquired in patients admitted from four emergency departments with suspected sepsis. Subjects with non-infectious systemic inflammatory response syndrome (SIRS) served as controls. Samples were acquired at enrollment (T0) and 24 h later (T24). We assessed diagnostic (differentiating SIRS from sepsis) and prognostic (28-day mortality) predictive power. Models incorporating procalcitonin (diagnostic prediction) and APACHE II scores (mortality prediction) were generated. Results: Two hundred three subjects were included (107 provided procalcitonin measurements). Four subjects exhibited uncomplicated sepsis, 127 severe sepsis, 35 septic shock, and 24 had non-infectious SIRS. There were 190-survivors and 13 non-survivors. Mortality prediction models using cfDNA, nucleosomes, or APACHEII yielded AUC values of 0.61, 0.75, and 0.81, respectively. A model combining nucleosomes with the APACHE II score improved the AUC to 0.84. Diagnostic models distinguishing sepsis from SIRS using procalcitonin, cfDNA(T0), or nucleosomes(T0) yielded AUC values of 0.64, 0.65, and 0.63, respectively. The three parameter model yielded an AUC of 0.74. Conclusions: To our knowledge, this is the first head-to-head comparison of cfDNA and nucleosomes in diagnosing sepsis and predicting sepsis-related mortality. Both cfDNA and nucleosome concentrations demonstrated a modest ability to distinguish sepsis survivors and non-survivors and provided additive diagnostic predictive accuracy in differentiating sepsis from non-infectious SIRS when integrated into a diagnostic prediction model including PCT and APACHE II. A sepsis biomarker strategy incorporating measures of the apoptotic pathway may serve as an important component of a sepsis diagnostic and mortality prediction tool

Tumour Cannabinoid CB1 Receptor and Phosphorylated Epidermal Growth Factor Receptor Expression Are Additive Prognostic Markers for Prostate Cancer

BACKGROUND: In cultured prostate cancer cells, down-regulation of epidermal growth factor receptor (EGFR) has been implicated in mediating the antiproliferative effect of the endogenous cannabinoid (CB) ligand anandamide. Using a well-characterised cohort of prostate cancer patients, we have previously reported that expression levels of phosphorylated EGFR (pEGFR-IR) and CB(1) receptor (CB(1)IR) in tumour tissue at diagnosis are markers of disease-specific survival, but it is not known whether the two markers interact in terms of their influence on disease severity at diagnosis and disease outcome. METHODOLOGY/PRINCIPAL FINDINGS: Data from a cohort of 419 patients who were diagnosed with prostate cancer at transurethral resection for voiding difficulties was used. Scores for both tumour CB(1)IR and pEGFR-IR were available in the database. Of these, 235 had been followed by expectancy until the appearance of metastases. For patients scored for both parameters, Cox proportional-hazards regression analyses using optimal cut-off scores indicated that the two measures provided additional diagnostic information not only to each other, but to that provided by the tumour stage and the Gleason score. When the cases were divided into subgroups on the basis of these cut-off scores, the patients with both CB(1)IR and pEGFR-IR scores above their cut-off had a poorer disease-specific survival and showed a more severe pathology at diagnosis than patients with high pEGFR-IR scores but with CB(1)IR scores below the cut-off. CONCLUSIONS/SIGNIFICANCE: These data indicate that a high tumour CB(1) receptor expression at diagnosis augments the deleterious effects of a high pEGFR expression upon disease-specific survival

Dusp3 and Psme3 are associated with murine susceptibility to Staphylococcus aureus infection and human sepsis.

Using A/J mice, which are susceptible to Staphylococcus aureus, we sought to identify genetic determinants of susceptibility to S. aureus, and evaluate their function with regard to S. aureus infection. One QTL region on chromosome 11 containing 422 genes was found to be significantly associated with susceptibility to S. aureus infection. Of these 422 genes, whole genome transcription profiling identified five genes (Dcaf7, Dusp3, Fam134c, Psme3, and Slc4a1) that were significantly differentially expressed in a) S. aureus -infected susceptible (A/J) vs. resistant (C57BL/6J) mice and b) humans with S. aureus blood stream infection vs. healthy subjects. Three of these genes (Dcaf7, Dusp3, and Psme3) were down-regulated in susceptible vs. resistant mice at both pre- and post-infection time points by qPCR. siRNA-mediated knockdown of Dusp3 and Psme3 induced significant increases of cytokine production in S. aureus-challenged RAW264.7 macrophages and bone marrow derived macrophages (BMDMs) through enhancing NF-κB signaling activity. Similar increases in cytokine production and NF-κB activity were also seen in BMDMs from CSS11 (C57BL/6J background with chromosome 11 from A/J), but not C57BL/6J. These findings suggest that Dusp3 and Psme3 contribute to S. aureus infection susceptibility in A/J mice and play a role in human S. aureus infection

Potential Cost-effectiveness of Early Identification of Hospital-acquired Infection in Critically Ill Patients

Limitations in methods for the rapid diagnosis of hospital-acquired infections often delay initiation of effective antimicrobial therapy. New diagnostic approaches offer potential clinical and cost-related improvements in the management of these infections. We developed a decision modeling framework to assess the potential cost-effectiveness of a rapid biomarker assay to identify hospital-acquired infection in high-risk patients earlier than standard diagnostic testing. The framework includes parameters representing rates of infection, rates of delayed appropriate therapy, and impact of delayed therapy on mortality, along with assumptions about diagnostic test characteristics and their impact on delayed therapy and length of stay. Parameter estimates were based on contemporary, published studies and supplemented with data from a four-site, observational, clinical study. Extensive sensitivity analyses were performed. The base-case analysis assumed 17.6% of ventilated patients and 11.2% of nonventilated patients develop hospital-acquired infection and that 28.7% of patients with hospital-acquired infection experience delays in appropriate antibiotic therapy with standard care. We assumed this percentage decreased by 50% (to 14.4%) among patients with true-positive results and increased by 50% (to 43.1%) among patients with false-negative results using a hypothetical biomarker assay. Cost of testing was set at $110/d. In the base-case analysis, among ventilated patients, daily diagnostic testing starting on admission reduced inpatient mortality from 12.3 to 11.9$1,640 per patient, resulting in an incremental cost-effectiveness ratio of $21,389 per life-year saved. Among nonventilated patients, inpatient mortality decreased from 7.3 to 7.1$1,381 with diagnostic testing. The resulting incremental cost-effectiveness ratio was $42,325 per life-year saved. Threshold analyses revealed the probabilities of developing hospital-acquired infection in ventilated and nonventilated patients could be as low as 8.4 and 9.8$50,000 per life-year saved. Development and use of serial diagnostic testing that reduces the proportion of patients with delays in appropriate antibiotic therapy for hospital-acquired infections could reduce inpatient mortality. The model presented here offers a cost-effectiveness framework for future test development