The Classification of Reversible Bit Operations

We present a complete classification of all possible sets of classical reversible gates acting on bits, in terms of which reversible transformations they generate, assuming swaps and ancilla bits are available for free. Our classification can be seen as the reversible-computing analogue of Post\u27s lattice, a central result in mathematical logic from the 1940s. It is a step toward the ambitious goal of classifying all possible quantum gate sets acting on qubits. Our theorem implies a linear-time algorithm (which we have implemented), that takes as input the truth tables of reversible gates G and H, and that decides whether G generates H. Previously, this problem was not even known to be decidable (though with effort, one can derive from abstract considerations an algorithm that takes triply-exponential time). The theorem also implies that any n-bit reversible circuit can be "compressed" to an equivalent circuit, over the same gates, that uses at most 2^{n}poly(n) gates and O(1) ancilla bits; these are the first upper bounds on these quantities known, and are close to optimal. Finally, the theorem implies that every non-degenerate reversible gate can implement either every reversible transformation, or every affine transformation, when restricted to an "encoded subspace." Briefly, the theorem says that every set of reversible gates generates either all reversible transformations on n-bit strings (as the Toffoli gate does); no transformations; all transformations that preserve Hamming weight (as the Fredkin gate does); all transformations that preserve Hamming weight mod k for some k; all affine transformations (as the Controlled-NOT gate does); all affine transformations that preserve Hamming weight mod 2 or mod 4, inner products mod 2, or a combination thereof; or a previous class augmented by a NOT or NOTNOT gate. Prior to this work, it was not even known that every class was finitely generated. Ruling out the possibility of additional classes, not in the list, requires involved arguments about polynomials, lattices, and Diophantine equations

Random Feature Models for Learning Interacting Dynamical Systems

Particle dynamics and multi-agent systems provide accurate dynamical models for studying and forecasting the behavior of complex interacting systems. They often take the form of a high-dimensional system of differential equations parameterized by an interaction kernel that models the underlying attractive or repulsive forces between agents. We consider the problem of constructing a data-based approximation of the interacting forces directly from noisy observations of the paths of the agents in time. The learned interaction kernels are then used to predict the agents behavior over a longer time interval. The approximation developed in this work uses a randomized feature algorithm and a sparse randomized feature approach. Sparsity-promoting regression provides a mechanism for pruning the randomly generated features which was observed to be beneficial when one has limited data, in particular, leading to less overfitting than other approaches. In addition, imposing sparsity reduces the kernel evaluation cost which significantly lowers the simulation cost for forecasting the multi-agent systems. Our method is applied to various examples, including first-order systems with homogeneous and heterogeneous interactions, second order homogeneous systems, and a new sheep swarming system

Pesticide Certification Training Series: First Aid for Pesticide Poisoning

The Oklahoma Cooperative Extension Service periodically issues revisions to its publications. The most current edition is made available. For access to an earlier edition, if available for this title, please contact the Oklahoma State University Library Archives by email at [email protected] or by phone at 405-744-6311.Entomology and Plant Patholog

Acoustic telemetry.

Broadcasting messages through the earth is a daunting task. Indeed, broadcasting a normal telephone conversion through the earth by wireless means is impossible with todays technology. Most of us don't care, but some do. Industries that drill into the earth need wireless communication to broadcast navigation parameters. This allows them to steer their drill bits. They also need information about the natural formation that they are drilling. Measurements of parameters such as pressure, temperature, and gamma radiation levels can tell them if they have found a valuable resource such as a geothermal reservoir or a stratum bearing natural gas. Wireless communication methods are available to the drilling industry. Information is broadcast via either pressure waves in the drilling fluid or electromagnetic waves in the earth and well tubing. Data transmission can only travel one way at rates around a few baud. Given that normal Internet telephone modems operate near 20,000 baud, these data rates are truly very slow. Moreover, communication is often interrupted or permanently blocked by drilling conditions or natural formation properties. Here we describe a tool that communicates with stress waves traveling through the steel drill pipe and production tubing in the well. It's based on an old idea called Acoustic Telemetry. But what we present here is more than an idea. This tool exists, it's drilled several wells, and it works. Currently, it's the first and only acoustic telemetry tool that can withstand the drilling environment. It broadcasts one way over a limited range at much faster rates than existing methods, but we also know how build a system that can communicate both up and down wells of indefinite length

Impact of the SPOP Mutant Subtype on the Interpretation of Clinical Parameters in Prostate Cancer.

Purpose: Molecular characterization of prostate cancer, including The Cancer Genome Atlas, has revealed distinct subtypes with underlying genomic alterations. One of these core subtypes, SPOP (speckle-type POZ protein) mutant prostate cancer, has previously only been identifiable via DNA sequencing, which has made the impact on prognosis and routinely used risk stratification parameters unclear. Methods: We have developed a novel gene expression signature, classifier (Subclass Predictor Based on Transcriptional Data), and decision tree to predict the SPOP mutant subclass from RNA gene expression data and classify common prostate cancer molecular subtypes. We then validated and further interrogated the association of prostate cancer molecular subtypes with pathologic and clinical outcomes in retrospective and prospective cohorts of 8,158 patients. Results: The subclass predictor based on transcriptional data model showed high sensitivity and specificity in multiple cohorts across both RNA sequencing and microarray gene expression platforms. We predicted approximately 8% to 9% of cases to be SPOP mutant from both retrospective and prospective cohorts. We found that the SPOP mutant subclass was associated with lower frequency of positive margins, extraprostatic extension, and seminal vesicle invasion at prostatectomy; however, SPOP mutant cancers were associated with higher pretreatment serum prostate-specific antigen (PSA). The association between SPOP mutant status and higher PSA level was validated in three independent cohorts. Despite high pretreatment PSA, the SPOP mutant subtype was associated with a favorable prognosis with improved metastasis-free survival, particularly in patients with high-risk preoperative PSA levels. Conclusion: Using a novel gene expression model and a decision tree algorithm to define prostate cancer molecular subclasses, we found that the SPOP mutant subclass is associated with higher preoperative PSA, less adverse pathologic features, and favorable prognosis. These findings suggest a paradigm in which the interpretation of common risk stratification parameters, particularly PSA, may be influenced by the underlying molecular subtype of prostate cancer

Effects of compressibility on driving zonal flow in gas giants

The banded structures observed on the surfaces of the gas giants are associated with strong zonal winds alternating in direction with latitude. We use three-dimensional numerical simulations of compressible convection in the anelastic approximation to explore the properties of zonal winds in rapidly rotating spherical shells. Since the model is restricted to the electrically insulating outer envelope, we therefore neglect magnetic effects. A systematic parametric study for various density scaleheights and Rayleigh numbers allows to explore the dependence of convection and zonal jets on these parameters and to derive scaling laws. While the density stratification affects the local flow amplitude and the convective scales, global quantities and zonal jets properties remain fairly independent of the density stratification. The zonal jets are maintained by Reynolds stresses, which rely on the correlation between zonal and cylindrically radial flow components. The gradual loss of this correlation with increasing supercriticality hampers all our simulations and explains why the additional compressional source of vorticity hardly affects zonal flows. All these common features may explain why previous Boussinesq models were already successful in reproducing the morphology of zonal jets in gas giants.Comment: 17 pages, 15 figures, 2 tables, accepted for publication in Icaru