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An upper bound on the rate of a binary code as a function of minimum code distance (using a Hamming code metric) is arrived at from Delsarte-MacWilliams inequalities. The upper bound so found is asymptotically less than Levenshtein's bound, and a fortiori less than Elias' bound. Appendices review properties of Krawtchouk polynomials and Q-polynomials utilized in the rigorous proofs.
This paper estimates the upper and lower bounds of the frame noise of a linear detector array that uses a one-dimensional scan pattern. Using chi-square distribution, it is analytically shown why it is necessary to use the average of the variances and not the average of the standard deviations to estimate these bounds. Also, a criteria for determining whether any excessively noisy lines exist among the detectors is derived from these bounds. Using a Gaussian standard random variable generator, these bounds are demonstrated to be accurate within the specified confidence interval. A silicon detector array is then used for actual dark current measurements. The criterion developed for determination of noisy detectors is checked on the experimentally obtained data.
We present a finite element technique for the efficient generation of lower and upper bounds to outputs which are linear functionals of the solutions to the incompressible Stokes equations in two space dimensions; the finite element discretization is effected by Crouzeix-Raviart elements, the discontinuous pressure approximation of which is central to our approach. The bounds are based upon the construction of an augmented Lagrangian: the objective is a quadratic "energy" reformulation of the desired output; the constraints are the finite element equilibrium equations (including the incompressibility constraint), and the intersubdomain continuity conditions on velocity. Appeal to the dual max-min problem for appropriately chosen candidate Lagrange multipliers then yields inexpensive bounds for the output associated with a fine-mesh discretization; the Lagrange multipliers are generated by exploiting an associated coarse-mesh approximation. In addition to the requisite coarse-mesh calculations, the bound technique requires solution only of local subdomain Stokes problems on the fine-mesh. The method is illustrated for the Stokes equations, in which the outputs of interest are the flowrate past, and the lift force on, a body immersed in a channel.
In this paper, we derive new Cramer-Rao bounds (CRBs) for the estimation of phase from a block of random M-PSK (M=8) symbols for the case where the phase to be estimated is a random variable(r.v.). Existing bounds for 2 and 4-PSK which model the phase as non-random are extended to obtain a new 8-PSK CRB. The new bound which models the phase as a r.v. is compared to the new 8-PSK bound which models the phase as non-random. With 8-PSK we see clearly that use of the random phase CRB more accurately models the behavior if the phase, as normally happens, is supposed to be constrained to the interval [-pi/M,pi/M).
In this paper, we derive new Cramer-Rao bounds (CRBs) for the estimation of phase from a block of random M-PSK (M=2,4,8) symbols where the phase to be estimated is a random variable. Existing bounds for 2 and 4-PSK which model the phase as non-random are extended to obtain a new 8-PSK CRB. The new random phase bounds are compared to the new 8-PSK and existing 2,4-PSK bounds which model the phase as non-random. We see that the random phase CRBs more accurately model the behavior if the phase, as normally happens, is suppose to be constrained to the interval [-pi/M,pi/M).
The rare-gas atoms are chemically inert, to an extent unique among all elements. This is due to the stable electronic structure of the atoms. Stable molecules with chemically bound rare-gas atoms are, however, known. A first such compound, XePtF6, W2S prepared in 1962 and since then a range of molecules containing radon, xenon and krypton have been obtained. Most recently, a first stable chemically bound compound of argon was prepared, leaving neon and helium as the only elements for which stable chemically bound molecules are not yet known. Electronic structure calculations predict that a metastable species HHeF exists, but significance of the result depends on the unknown lifetime. Here we report quantum dynamics calculations of the lifetime of HHeF, using accurate interactions computed from electronic structure theory. HHeF is shown to disintegrate by tunneling through energy barriers into He + HF and H + He + F the first channel greatly dominating. The lifetime of HHeF is more than 120 picoseconds, that of DHeF is 14 nanoseconds. The relatively long lifetimes are encouraging for the preparation prospects of this first chemically bound helium compound.
This report attempts to document the broad scope of issues that must be satisfactorily resolved before one can expect to methodically obtain, with a reasonable confidence, a near-optimal robust closed loop performance in physical applications. These include elements of signal processing, noise identification, system identification, model validation, and uncertainty modeling. Based on a recently developed methodology involving a parameterization of all model validating uncertainty sets for a given linear fractional transformation (LFT) structure and noise allowance, a new software, Uncertainty Bound Identification (UBID) toolbox, which conveniently executes model validation tests and determine uncertainty bounds from data, has been designed and is currently available. This toolbox also serves to benchmark the current state-of-the-art in uncertainty bound determination and in turn facilitate benchmarking of robust control technology. To help clarify the methodology and use of the new software, two tutorial examples are provided. The first involves the uncertainty characterization of a flexible structure dynamics, and the second example involves a closed loop performance validation of a ducted fan based on an uncertainty bound from data. These examples, along with other simulation and experimental results, also help describe the many factors and assumptions that determine the degree of success in applying robust control theory to practical problems.
This study is emphasized on search for signatures of chemically bound water in surface layer of Mars based on data acquired by High Energy Neutron Detector (HEND) which is part of the Mars Odyssey Gamma Ray Spectrometer (GRS). Fluxes of epithermal (probe the upper 1-2 m) and fast (the upper 20-30 cm) neutrons, considered in this work, were measured since mid February till mid June 2002. First analysis of this data set with emphasis of chemically bound water was made. Early publications of the GRS results reported low neutron flux at high latitudes, interpreted as signature of ground water ice, and in two low latitude areas: Arabia and SW of Olympus Mons (SWOM), interpreted as 'geographic variations in the amount of chemically and/or physically bound H2O and or OH...'. It is clear that surface materials of Mars do contain chemically bound water, but its amounts are poorly known and its geographic distribution was not analyzed.
A casein kinase II (CK II)-like protein kinase was identified and partially isolated from a purified envelope-matrix fraction of pea (Pisum sativum L.) nuclei. When [gamma-32P]ATP was directly added to the envelope-matrix preparation, the three most heavily labeled protein bands had molecular masses near 71, 48, and 46 kDa. Protein kinases were removed from the preparation by sequential extraction with Triton X-100, EGTA, 0.3 M NaCl, and a pH 10.5 buffer, but an active kinase still remained bound to the remaining lamina-matrix fraction after these treatments. This kinase had properties resembling CK II kinases previously characterized from animal and plant sources: it preferred casein as an artificial substrate, could use GTP as efficiently as ATP as the phosphoryl donor, was stimulated by spermine, was calcium independent, and had a catalytic subunit of 36 kDa. Some animal and plant CK II kinases have regulatory subunits near 29 kDa, and a lamina-matrix-bound protein of this molecular mass was recognized on immunoblot by anti-Drosophila CK II polyclonal antibodies. Also found associated with the envelope-matrix fraction of pea nuclei were p34cdc2-like and Ca(2+)-dependent protein kinases, but their properties could not account for the protein kinase activity bound to the lamina. The 71-kDa substrate of the CK II-like kinase was lamin A-like, both in its molecular mass and in its cross-reactivity with anti-intermediate filament antibodies. Lamin phosphorylation is considered a crucial early step in the entry of cells into mitosis, so lamina-bound CK II kinases may be important control points for cellular proliferation.
Probability Collectives (PC) provides the information-theoretic extension of conventional full-rationality game theory to bounded rational games. Here an explicit solution to the equations giving the bounded rationality equilibrium of a game is presented. Then PC is used to investigate games in which the players use bounded rational best-response strategies. Next it is shown that in the continuum-time limit, bounded rational best response games result in a variant of the replicator dynamics of evolutionary game theory. It is then shown that for team (shared-payoff) games, this variant of replicator dynamics is identical to Newton-Raphson iterative optimization of the shared utility function.
A family of upper bounds to error probabilities of coded systems on the additive white Gaussian noise channel was recently proposed by Divsalar. Their calculation depends only on the weight spectrum of the code words. We first elaborate upon these bounds to show how they can be further tightened by using numerical integration instead of a Chernoff bound, and by reducing the number of code words to be included in the bound. Next, we extend them to finding channels.
Many space applications such as sensor networks, on-board satellite-based platforms, on-board vehicle monitoring systems, etc. handle large amounts of data and analysis of such data is often critical for the scientific mission. Transmitting such large amounts of data to the remote control station for analysis is usually too expensive for time-critical applications. Instead, modern space applications are increasingly relying on autonomous on-board data analysis. All these applications face many resource constraints. A key requirement is to minimize energy consumption. Several approaches have been developed for estimating the energy consumption of such applications (e.g. [3, 1]) based on measuring actual consumption at run-time for large sets of random inputs. However, this approach has the limitation that it is in general not possible to cover all possible inputs. Using formal techniques offers the potential for inferring safe energy consumption bounds, thus being specially interesting for space exploration and safety-critical systems. We have proposed and implemented a general frame- work for resource usage analysis of Java bytecode [2]. The user defines a set of resource(s) of interest to be tracked and some annotations that describe the cost of some elementary elements of the program for those resources. These values can be constants or, more generally, functions of the input data sizes. The analysis then statically derives an upper bound on the amount of those resources that the program as a whole will consume or provide, also as functions of the input data sizes. This article develops a novel application of the analysis of [2] to inferring safe upper bounds on the energy consumption of Java bytecode applications. We first use a resource model that describes the cost of each bytecode instruction in terms of the joules it consumes. With this resource model, we then generate energy consumption cost relations, which are then used to infer safe upper bounds. How energy consumption for each bytecode instruction is measured is beyond the scope of this paper. Instead, this paper is about how to infer safe energy consumption estimations assuming that those energy consumption costs are provided. For concreteness, we use a simplified version of an existing resource model [1] in which an energy consumption cost for individual Java opcodes is defined.
Results from a numerical study of the buckling response of a thin-walled compressionloaded isotropic circular cylindrical shell with initial geometric and loading imperfections are used to determine a lower bound buckling load estimate suitable for preliminary design. The lower bound prediction techniques presented herein include an imperfection caused by a lateral perturbation load, an imperfection in the shape of a single stress-free dimple (similar to the lateral pertubation imperfection), and a distributed load imperfection that induces a nonuniform load in the shell. The ABAQUS finite element code is used for the analyses. Responses of the cylinders for selected imperfection amplitudes and imperfection types are considered, and the effect of each imperfection is compared to the response of a geometrically perfect cylinder. The results indicate that compression-loaded shells subjected to a lateral perturbation load or a single dimple imperfection, and a nonuniform load imperfection, exhibit similar buckling behavior and lower bound trends and the predicted lower bounds are much less conservative than the corresponding design recommendation NASA SP-8007 for the design of buckling-critical shells. In addition, the lateral perturbation technique and the distributed load imperfection produce response characteristics that are physically meaningful and can be validated via laboratory testing.
Upper bounds on high speed satellite collision probability, P (sub c), have been investigated. Previous methods assume an individual position error covariance matrix is available for each object. The two matrices being combined into a single, relative position error covariance matrix. Components of the combined error covariance are then varied to obtain a maximum P (sub c). If error covariance information for only one of the two objects was available, either some default shape has been used or nothing could be done. An alternative is presented that uses the known covariance information along with a critical value of the missing covariance to obtain an approximate but useful P (sub c) upper bound. There are various avenues along which an upper bound on the high speed satellite collision probability has been pursued. Typically, for the collision plane representation of the high speed collision probability problem, the predicted miss position in the collision plane is assumed fixed. Then the shape (aspect ratio of ellipse), the size (scaling of standard deviations) or the orientation (rotation of ellipse principal axes) of the combined position error ellipse is varied to obtain a maximum P (sub c). Regardless as to the exact details of the approach, previously presented methods all assume that an individual position error covariance matrix is available for each object and the two are combined into a single, relative position error covariance matrix. This combined position error covariance matrix is then modified according to the chosen scheme to arrive at a maximum P (sub c). But what if error covariance information for one of the two objects is not available? When error covariance information for one of the objects is not available the analyst has commonly defaulted to the situation in which only the relative miss position and velocity are known without any corresponding state error covariance information. The various usual methods of finding a maximum P (sub c) do no good because the analyst defaults to no knowledge of the combined, relative position error covariance matrix. It is reasonable to think, given an assumption of no covariance information, an analyst might still attempt to determine the error covariance matrix that results in an upper bound on the P (sub c). Without some guidance on limits to the shape, size and orientation of the unknown covariance matrix, the limiting case is a degenerate ellipse lying along the relative miss vector in the collision plane. Unless the miss position is exceptionally large or the at-risk object is exceptionally small, this method results in a maximum P (sub c) too large to be of practical use. For example, assuming that the miss distance is equal to the current ISS alert volume along-track (+ or -) distance of 25 kilometers and that the at-risk area has a 70 meter radius. The maximum (degenerate ellipse) P (sub c) is about 0.00136. At 40 kilometers, the maximum P (sub c) would be 0.00085 which is still almost an order of magnitude larger than the ISS maneuver threshold of 0.0001. In fact, a miss distance of almost 340 kilometers is necessary to reduce the maximum P (sub c) associated with this degenerate ellipse to the ISS maneuver threshold value. Such a result is frequently of no practical value to the analyst. Some improvement may be made with respect to this problem by realizing that while the position error covariance matrix of one of the objects (usually the debris object) may not be known the position error covariance matrix of the other object (usually the asset) is almost always available. Making use of the position error covariance information for the one object provides an improvement in finding a maximum P (sub c) which, in some cases, may offer real utility. The equations to be used are presented and their use discussed.
Recursive branch and bound algorithms are often used to refine and isolate solutions to several classes of global optimization problems. A rigorous computation framework for the solution of systems of equations and inequalities involving nonlinear real arithmetic over hyper-rectangular variable and parameter domains is presented. It is derived from a generic branch and bound algorithm that has been formally verified, and utilizes self-validating enclosure methods, namely interval arithmetic and, for polynomials and rational functions, Bernstein expansion. Since bounds computed by these enclosure methods are sound, this approach may be used reliably in software verification tools. Advantage is taken of the partial derivatives of the constraint functions involved in the system, firstly to reduce the branching factor by the use of bisection heuristics and secondly to permit the computation of bifurcation sets for systems of ordinary differential equations. The associated software development, Kodiak, is presented, along with examples of three different branch and bound problem types it implements.
A new method is presented that computes a pre{test estimate of the upper bound of the drag coefficient repeatability of a wind tunnel model. This upper bound is a conservative estimate of the precision error of the drag coefficient. For clarity, precision error contributions associated with the measurement of the dynamic pressure are analyzed separately from those that are associated with the measurement of the aerodynamic loads. The upper bound is computed by using information about the model, the tunnel conditions, and the balance in combination with an estimate of the expected output variations as input. The model information consists of the reference area and an assumed angle of attack. The tunnel conditions are described by the Mach number and the total pressure or unit Reynolds number. The balance inputs are the partial derivatives of the axial and normal force with respect to all balance outputs. Finally, an empirical output variation of 1.0 microV/V is used to relate both random instrumentation and angle measurement errors to the precision error of the drag coefficient. Results of the analysis are reported by plotting the upper bound of the precision error versus the tunnel conditions. The analysis shows that the influence of the dynamic pressure measurement error on the precision error of the drag coefficient is often small when compared with the influence of errors that are associated with the load measurements. Consequently, the sensitivities of the axial and normal force gages of the balance have a significant influence on the overall magnitude of the drag coefficient's precision error. Therefore, results of the error analysis can be used for balance selection purposes as the drag prediction characteristics of balances of similar size and capacities can objectively be compared. Data from two wind tunnel models and three balances are used to illustrate the assessment of the precision error of the drag coefficient.
Abstract The notion that phonons can carry pseudo‐angular momentum has many major consequences, including topologically protected phonon chirality, Berry curvature of phonon band structure, and the phonon Hall effect. When a phonon is resonantly coupled to an orbital state split by its crystal field environment, a so‐called vibronic bound state forms. Here, a vibronic bound state is observed in NaYbSe 2 , a quantum spin liquid candidate. In addition, field and polarization dependent Raman microscopy is used to probe an angular momentum transfer of Δ J z = ±ℏ between phonons and the crystalline electric field mediated by the vibronic bound stat. This angular momentum transfer between electronic and lattice subsystems provides new pathways for selective optical addressability of phononic angular momentum via electronic ancillary states.
The proximal Galerkin finite element method is a high-order, low iteration complexity, nonlinear numerical method that preserves the geometric and algebraic structure of pointwise bound constraints in infinite-dimensional function spaces. This paper introduces the proximal Galerkin method and applies it to solve free boundary problems, enforce discrete maximum principles, and develop a scalable, mesh-independent algorithm for optimal design with pointwise bound constraints. This paper also introduces the latent variable proximal point (LVPP) algorithm, from which the proximal Galerkin method derives. When analyzing the classical obstacle problem, we discover that the underlying variational inequality can be replaced by a sequence of second-order partial differential equations (PDEs) that are readily discretized and solved with, e.g., the proximal Galerkin method. Throughout this work, we arrive at several contributions that may be of independent interest. These include (1) a semilinear PDE we refer to as the entropic Poisson equation; (2) an algebraic/geometric connection between high-order positivity-preserving discretizations and certain infinite-dimensional Lie groups; and (3) a gradient-based, bound-preserving algorithm for two-field, density-based topology optimization. The complete proximal Galerkin methodology combines ideas from nonlinear programming, functional analysis, tropical algebra, and differential geometry and can potentially lead to new synergies among these areas as well as within variational and numerical analysis. Open-source implementations of our methods accompany this work to facilitate reproduction and broader adoption.