Many interesting but practically intractable problems can be reduced to that of finding the ground state of a system of interacting spins; however, finding such a ground state remains computationally difficult. It is believed that the ground state of some naturally occurring spin systems can be effectively attained through a process called quantum annealing. If it could be harnessed, quantum annealing might improve on known methods for solving certain types of problem. However, physical investigation of quantum annealing has been largely confined to microscopic spins in condensed-matter systems. Here we use quantum annealing to find the ground state of an artificial Ising spin system comprising an array of eight superconducting flux quantum bits with programmable spin-spin couplings. We observe a clear signature of quantum annealing, distinguishable from classical thermal annealing through the temperature dependence of the time at which the system dynamics freezes. Our implementation can be configured in situ to realize a wide variety of different spin networks, each of which can be monitored as it moves towards a low-energy configuration. This programmable artificial spin network bridges the gap between the theoretical study of ideal isolated spin networks and the experimental investigation of bulk magnetic samples. Moreover, with an increased number of spins, such a system may provide a practical physical means to implement a quantum algorithm, possibly allowing more-effective approaches to solving certain classes of hard combinatorial optimization problems.

With the increasing incidence of prostate cancer, identifying common genetic variants that confer risk of the disease is important. Here we report such a variant on chromosome 8q24, a region initially identified through a study of Icelandic families. Allele -8 of the microsatellite DG8S737 was associated with prostate cancer in three case-control series of European ancestry from Iceland, Sweden and the US. The estimated odds ratio (OR) of the allele is 1.62 (P = 2.7 x 10(-11)). About 19% of affected men and 13% of the general population carry at least one copy, yielding a population attributable risk (PAR) of approximately 8%. The association was also replicated in an African American case-control group with a similar OR, in which 41% of affected individuals and 30% of the population are carriers. This leads to a greater estimated PAR (16%) that may contribute to higher incidence of prostate cancer in African American men than in men of European ancestry.

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BackgroundCurrent prostate cancer prognostic models are based on pre-treatment prostate specific antigen (PSA) levels, biopsy Gleason score, and clinical staging but in practice are inadequate to accurately predict disease progression. Hence, we sought to develop a molecular panel for prostate cancer progression by reasoning that molecular profiles might further improve current clinical models.MethodsWe analyzed a Swedish Watchful Waiting cohort with up to 30 years of clinical follow up using a novel method for gene expression profiling. This cDNA-mediated annealing, selection, ligation, and extension (DASL) method enabled the use of formalin-fixed paraffin-embedded transurethral resection of prostate (TURP) samples taken at the time of the initial diagnosis. We determined the expression profiles of 6100 genes for 281 men divided in two extreme groups: men who died of prostate cancer and men who survived more than 10 years without metastases (lethals and indolents, respectively). Several statistical and machine learning models using clinical and molecular features were evaluated for their ability to distinguish lethal from indolent cases.ResultsSurprisingly, none of the predictive models using molecular profiles significantly improved over models using clinical variables only. Additional computational analysis confirmed that molecular heterogeneity within both the lethal and indolent classes is widespread in prostate cancer as compared to other types of tumors.ConclusionsThe determination of the molecularly dominant tumor nodule may be limited by sampling at time of initial diagnosis, may not be present at time of initial diagnosis, or may occur as the disease progresses making the development of molecular biomarkers for prostate cancer progression challenging.

A superconducting chip containing a regular array of flux qubits, tunable interqubit inductive couplers, an XY-addressable readout system, on-chip programmable magnetic memory, and a sparse network of analog control lines has been studied. The architecture of the chip and the infrastructure used to control it were designed to facilitate the implementation of an adiabatic quantum optimization algorithm. The performance of an eight-qubit unit cell on this chip has been characterized by measuring its success in solving a large set of random Ising spin glass problem instances as a function of temperature. The experimental data are consistent with the predictions of a quantum mechanical model of an eight-qubit system coupled to a thermal environment. These results highlight many of the key practical challenges that we have overcome and those that lie ahead in the quest to realize a functional large scale adiabatic quantum information processor.

TMPRSS2-ERG fusion prostate cancer is a distinct molecular subclass. TMPRSS2-ERG expression is regulated by a novel ER-dependent mechanism.

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A rf-superconducting quantum interference device ͑SQUID͒ flux qubit that is robust against fabrication variations in Josephson-junction critical currents and device inductance has been implemented. Measurements of the persistent current and of the tunneling energy between the two lowest-lying states, both in the coherent and incoherent regimes, are presented. These experimental results are shown to be in agreement with predictions of a quantum-mechanical Hamiltonian whose parameters were independently calibrated, thus justifying the identification of this device as a flux qubit. In addition, measurements of the flux and critical current noise spectral densities are presented that indicate that these devices with Nb wiring are comparable to the best Al wiring rf SQUIDs reported in the literature thus far, with a 1 / f flux noise spectral density at 1 Hz of 1.3 −0.5 +0.7 ⌽ 0 / ͱ Hz. An explicit formula for converting the observed flux noise spectral density into a freeinduction-decay time for a flux qubit biased to its optimal point and operated in the energy eigenbasis is presented. I. MOTIVATIONExperimental efforts to develop useful solid-state quantum information processors have encountered a host of practical problems that have substantially limited progress. While the desire to reduce noise in solid-state qubits appears to be the key factor that drives much of the recent work in this field, it must be acknowledged that there are formidable challenges related to architecture, circuit density, fabrication variation, calibration, and control that also deserve attention. For example, a qubit that is inherently exponentially sensitive to fabrication variations with no recourse for in situ correction holds little promise in any large-scale architecture, even with the best of modern fabrication facilities. Likewise, a qubit that requires an inordinate number of custom-tuned time-dependent control signals to be launched onto the chip, in order to correct for fabrication variations or to compensate for unintended on-chip crosstalk, would also not be useful in a large-scale processor. Thus, a qubit designed in the absence of information concerning its ultimate use in a larger-scale system may prove to be of little utility in the future. In what follows, we present an experimental demonstration of a superconducting flux qubit 1 that has been specifically designed to address several issues that pertain to the implementation of a large-scale quantum information processor. While noise is not the central focus of this paper, we nonetheless present experimental evidence that, despite its physical size and relative complexity, the observed flux noise in this flux qubit is comparable to the quietest such devices reported on in the literature to date.It has been well established that rf superconducting quantum interference devices ͑SQUIDs͒ can be used as qubits given an appropriate choice of device parameters. Such devices can be operated as a flux-biased phase qubit using two intrawell energy levels 2 or as a flux qubit using...