Two-dimensional Subspace Research Articles

Sequential Subspace Reliability Method with Univariate Revolving Integration

A new computational framework called the sequential subspace reliability method (SSRM) is presented. This method decomposes the multidimensional random space into multiple two-dimensional subspaces. In this manner, SSRM is able to approximate bivariate interaction effects. When the reliability estimate contribution is calculated subspace by subspace, the final assessment is updated in a progressive manner. The iterative history of sequential reliability assessment can be used to understand the complexity and convergence behavior of the limit state function of interest. In a decision-making situation, the flexibility of the proposed SSRM to provide iterative updates on reliability estimation becomes especially valuable in dealing with large-scale and complex problems under the constraints of limited time and resources. To calculate the individual subspace contributions, a novel univariate revolving integration (URI) method is proposed. The URI method takes advantage of the axisymmetric nature of a joint probability density function and provides an additional layer of flexibility in updating the reliability contribution within each subspace. This flexibility allows the estimation of bivariate and high-order effects to be addressed if resources allow. Additionally, URI is composed of multiple one-dimensional integrals that allow the use of regression models to be used with high confidence. The computational benefits of using the proposed method is demonstrated with several numerical examples of mathematical, structural, and an aircraft conceptual sizing problem.

Degenerate approach to the mean field Bose-Hubbard Hamiltonian

A degenerate variant of mean field perturbation theory for the on-site Bose-Hubbard Hamiltonian is presented. We split the perturbation into two terms and perform exact diagonalization in the two-dimensional subspace corresponding to the degenerate states. The final relations for the second order ground state energy and first order wave function do not contain singularities at integer values of the chemical potentials. The resulting equation for the phase boundary between superfluid and Mott states coincides with the prediction based on the conventional mean field perturbation approach.

State flip at exceptional points in atomic spectra

We study the behavior of the non-adiabatic population transfer between resonances at an exceptional point in the spectrum of the hydrogen atom. It is known that, when the exceptional point is encircled, the system always ends up in the same state, independent of the initial occupation within the two-dimensional subspace spanned by the states coalescing at the exceptional point. We verify this behavior for a realistic quantum system, viz. the hydrogen atom in crossed electric and magnetic fields. It is also shown that the non-adiabatic hypothesis can be violated when resonances in the vicinity are taken into account. In addition, we study the non-adiabatic population transfer in the case of a third-order exceptional point, in which three resonances are involved.

Accelerating Markov Chain Monte Carlo with Active Subspaces

The Markov chain Monte Carlo (MCMC) method is the computational workhorse for Bayesian inverse problems. However, MCMC struggles in high-dimensional parameter spaces, since its iterates must sequentially explore the high-dimensional space. This struggle is compounded in physical applications when the nonlinear forward model is computationally expensive. One approach to accelerate MCMC is to reduce the dimension of the state space. Active subspaces are part of an emerging set of tools for subspace-based dimension reduction. An active subspace in a given inverse problem indicates a separation between a low-dimensional subspace that is informed by the data and its orthogonal complement that is constrained by the prior. With this information, one can run the sequential MCMC on the active variables while sampling independently according to the prior on the inactive variables. However, this approach to increase efficiency may introduce bias. We provide a bound on the Hellinger distance between the true posterior and its active subspace-exploiting approximation. And we demonstrate the active subspace-accelerated MCMC on two computational examples: (i) a two-dimensional parameter space with a quadratic forward model and one-dimensional active subspace and (ii) a 100-dimensional parameter space with a PDE-based forward model and a two-dimensional active subspace.

Sequential three-way decision and granulation for cost-sensitive face recognition

Many previous studies on face recognition attempted to seek a precise classifier to achieve a low misclassification error, which is based on an assumption that all misclassification costs are the same. In many real-world scenarios, however, this assumption is not reasonable due to the imbalanced misclassification cost and insufficient high-quality facial image information. To address this issue, we propose a sequential three-way decision method for cost-sensitive face recognition. The proposed method is based on a formal description of granular computing. It develops a sequential strategy in a decision process. In each decision step, it seeks a decision which minimizes the misclassification cost rather than misclassification error, and it incorporates the boundary decision into the decision set such that a delayed decision can be made if available high-quality facial image information is insufficient for a precise decision. To describe the granular information of the facial image in three-way decision steps, we develop a series of image granulation methods based on two-dimensional subspace projection methods including 2DPCA, 2DLDA and 2DLPP. The sequential three-way decisions and granulation methods present an applicable simulation on human decisions in face recognition, which simulate a sequential decision strategy from rough granule to precise granule. The experiments were conducted on two popular facial image database, which validated the effectiveness of the proposed methods.

Classical to quantum optical network link for orbital angular momentum-carrying light.

Using orbital angular momentum (OAM) conservation in second-order nonlinear interaction processes, we create a classical to quantum optical network link in the OAM degrees of freedom of light via sum frequency generation, followed by spontaneous parametric down-conversion. Coherent OAM-carrying beams at 1550 nm are up-converted to 525.5-nm OAM-carrying beams in the first crystal, and are used to pump a second crystal to generate non-degenerate OAM entangled photon pairs at 795 nm and 1550 nm. By switching the OAM carried by the classical part, OAM correlation in the quantum part is shifted. High-level OAM entanglements in two-dimensional subspaces are verified.

Orthogonal sampling in free-energy calculations of residue mutations in a tripeptide: TI versus λ-LEUS.

In a recent article (Bieler et al., J. Chem. Theory Comput. 2014, 10, 3006), we introduced a combination of λ-dynamics and local-elevation umbrella-sampling termed λ-LEUS to calculate free-energy changes associated with alchemical processes using molecular dynamics simulations. This method was suggested to be more efficient than thermodynamic integration (TI), because the dynamical variation of the alchemical variable λ opens up pathways to circumvent barriers in the orthogonal space (defined by the N - 1 degrees of freedom that are not subjected to the sampling enhancement), a feature λ-LEUS shares with Hamiltonian replica-exchange (HR) approaches. However, the mutation considered, hydroquinone to benzene in water, was no real challenge in terms of orthogonal-space properties, which were restricted to solvent-relaxation processes. In the present article, we revisit the comparison between TI and λ-LEUS considering non-trivial mutations of the central residue X of a KXK tripeptide in water (with X = G, E, K, S, F, or Y). Side-chain interactions that may include salt bridges, hydrogen bonds or steric clashes lead to slow relaxation in the orthogonal space, mainly in the two-dimensional subspace spanned by the central φ and ψ dihedral angles of the peptide. The efficiency enhancement afforded by λ-LEUS is confirmed in this more complex test system and can be attributed explicitly to the improved sampling of the orthogonal space. The sensitivity of the results to the nontrivial choices of a mass parameter and of a thermostat coupling time for the alchemical variable is also investigated, resulting in recommended ranges of 50 to 100 u nm(2) and 0.2 to 0.5 ps, respectively.

Stable cheapest nonconforming finite elements for the Stokes equations

We introduce two pairs of stable cheapest nonconforming finite element space pairs to approximate the Stokes equations. One pair has each component of its velocity field to be approximated by the P1 nonconforming quadrilateral element while the pressure field is approximated by the piecewise constant function with globally two-dimensional subspaces removed: one removed space is due to the integral mean-zero property and the other space consists of global checker-board patterns. The other pair consists of the velocity space as the P1 nonconforming quadrilateral element enriched by a globally one-dimensional macro bubble function space based on DSSY (Douglas–Santos–Sheen–Ye) nonconforming finite element space; the pressure field is approximated by the piecewise constant function with mean-zero space eliminated. We show that two element pairs satisfy the discrete inf–sup condition uniformly. And we investigate the relationship between them. Several numerical examples are shown to confirm the efficiency and reliability of the proposed methods.

Graph Controllability Classes for the Laplacian Leader-Follower Dynamics

In this paper, we consider the problem of obtaining graph-theoretic characterizations of controllability for the Laplacian-based leader-follower dynamics. Our developments rely on the notion of graph controllability classes, namely, the classes of essentially controllable, completely uncontrollable, and conditionally controllable graphs. In addition to the topology of the underlying graph, the controllability classes rely on the specification of the control vectors; our particular focus is on the set of binary control vectors. The choice of binary control vectors is naturally adapted to the Laplacian dynamics, as it captures the case when the controller is unable to distinguish between the followers and, moreover, controllability properties are invariant under binary complements. We prove that the class of essentially controllable graphs is a strict subset of the class of asymmetric graphs and provide numerical results that suggests that the ratio of essentially controllable graphs to asymmetric graphs increases as the number of vertices increases. Although graph symmetries play an important role in graph-theoretic characterizations of controllability, we provide an explicit class of asymmetric graphs that are completely uncontrollable, namely the class of block graphs of Steiner triple systems. We prove that for graphs on four and five vertices, a repeated Laplacian eigenvalue is a necessary condition for complete uncontrollability but, however, show through explicit examples that for eight and nine vertices, a repeated eigenvalue is not necessary for complete uncontrollability. For the case of conditional controllability, we give an easily checkable necessary condition that identifies a class of binary control vectors that result in a two-dimensional controllable subspace. Several constructive examples demonstrate our results.

Detecting bit-flip errors in a logical qubit using stabilizer measurements.

Quantum data are susceptible to decoherence induced by the environment and to errors in the hardware processing it. A future fault-tolerant quantum computer will use quantum error correction to actively protect against both. In the smallest error correction codes, the information in one logical qubit is encoded in a two-dimensional subspace of a larger Hilbert space of multiple physical qubits. For each code, a set of non-demolition multi-qubit measurements, termed stabilizers, can discretize and signal physical qubit errors without collapsing the encoded information. Here using a five-qubit superconducting processor, we realize the two parity measurements comprising the stabilizers of the three-qubit repetition code protecting one logical qubit from physical bit-flip errors. While increased physical qubit coherence times and shorter quantum error correction blocks are required to actively safeguard the quantum information, this demonstration is a critical step towards larger codes based on multiple parity measurements.

Discrimination and synthesis of recursive quantum states in high-dimensional Hilbert spaces

We propose an interferometric method for statistically discriminating between nonorthogonal states in high dimensional Hilbert spaces for use in quantum information processing. The method is illustrated for the case of photon orbital angular momentum (OAM) states. These states belong to pairs of bases that are mutually unbiased on a sequence of two-dimensional subspaces of the full Hilbert space, but the vectors within the same basis are not necessarily orthogonal to each other. Over multiple trials, this method allows distinguishing OAM eigenstates from superpositions of multiple such eigenstates. Variations of the same method are then shown to be capable of preparing and detecting arbitrary linear combinations of states in Hilbert space. One further variation allows the construction of chains of states obeying recurrence relations on the Hilbert space itself, opening a new range of possibilities for more abstract information-coding algorithms to be carried out experimentally in a simple manner. Among other applications, we show that this approach provides a simplified means of switching between pairs of high-dimensional mutually unbiased OAM bases.

Hausdorff dimension estimates for restricted families of projections in [formula omitted

This paper is concerned with restricted families of projections in R3. Let K⊂R3 be a Borel set with Hausdorff dimension dim⁡K=s>1. If G is a smooth and sufficiently well-curved one-dimensional family of two-dimensional subspaces, the main result states that there exists σ(s)>1 such that dim⁡πV(K)≥σ(s) for almost all V∈G. A similar result is obtained for some specific families of one-dimensional subspaces.

Pick's Theorem in two-dimensional subspace of ℝ3.

In the Euclidean space ℝ3, denote the set of all points with integer coordinate by ℤ3. For any two-dimensional simple lattice polygon P, we establish the following analogy version of Pick's Theorem, k(I(P) + (1/2)B(P) − 1), where B(P) is the number of lattice points on the boundary of P in ℤ3, I(P) is the number of lattice points in the interior of P in ℤ3, and k is a constant only related to the two-dimensional subspace including P.

Data-Driven Two-Dimensional LQG Benchmark Based Performance Assessment for Batch Processes under ILC

A novel data-driven control performance assessment (CPA) method is proposed for batch processes controlled by iterative learning control (ILC) based on two-dimensional linear quadratic Gaussian (LQG) benchmark. Previous studies on CPA for ILC are based on an assumption that the model of the controlled batch process is known, whereas this study proposes a model-free CPA method. Based on the two-dimensional system theory, the closed-loop batch process under ILC can be converted into a two-dimensional Roesser model. This study proposes a novel closed-loop two-dimensional subspace identification method for the converted parameters unknown two-dimensional Roesser model. Using the identified model, the two-dimensional LQG tradeoff performance assessment surface can be obtained. The proposed method is verified by performing some simulations.

Experimental protection against evolution of states in a subspace via a super-Zeno scheme on an NMR quantum information processor

We experimentally demonstrate the freezing of evolution of quantum states in one- and two-dimensional subspaces of two qubits, on an NMR quantum information processor. State evolution was frozen and leakage of the state from its subspace to an orthogonal subspace was successfully prevented using super-Zeno sequences, comprising of a set of inverting radio frequency (rf) pulses punctuated by pre-selected time intervals. We demonstrate the efficacy of the scheme by preserving different types of states, including separable and maximally entangled states in one- and two-dimensional subspaces of two qubits. The change in the experimental density matrices was tracked by carrying out full state tomography at several time points. We use the fidelity measure for the one-dimensional case and the leakage (fraction) into the orthogonal subspace for the two-dimensional case, as qualitative indicators to estimate the resemblance of the density matrix at a later time to the initially prepared density matrix. For the case of entangled states, we additionally compute an entanglement parameter to indicate the presence of entanglement in the state at different times. We experimentally demonstrate that the super-Zeno scheme is able to successfully confine state evolution to the one- or two-dimensional subspace being protected.

On the frame of the unit ball of Banach spaces

Abstract The notion of the frame of the unit ball of Banach spaces was introduced to construct a new calculation method for the Dunkl-Williams constant. In this paper, we characterize the frame of the unit ball by using k-extreme points and extreme points of the unit ball of two-dimensional subspaces. Furthermore, we show that the frame of the unit ball is always closed, and is connected if the dimension of the space is not less than three. As infinite dimensional examples, the frame of the unit balls of c 0 and ℓ p are determined.

Universal quantum computation with qudits

Quantum circuit model has been widely explored for various quantum applications such as Shors algorithm and Grovers searching algorithm. Most of previous algorithms are based on the qubit systems. Herein a proposal for a universal circuit is given based on the qudit system, which is larger and can store more information. In order to prove its universality for quantum applications, an explicit set of one-qudit and two-qudit gates is provided for the universal qudit computation. The one-qudit gates are general rotation for each two-dimensional subspace while the two-qudit gates are their controlled extensions. In comparison to previous quantum qudit logical gates, each primitive qudit gate is only dependent on two free parameters and may be easily implemented. In experimental implementation, multilevel ions with the linear ion trap model are used to build the qudit systems and use the coupling of neighbored levels for qudit gates. The controlled qudit gates may be realized with the interactions of internal and external coordinates of the ion.

A guide to hunting periodic three-body orbits

The recent discovery of thirteen new and distinct three-body periodic planar orbits suggests that many more such orbits remain undiscovered. Searches in two-dimensional subspaces of the full four-dimensional space of initial conditions require computing resources that are available to many students, and the required level of computational and numerical expertise is also at the advanced undergraduate level. We discuss the methods for solving the planar three-body equations of motion, as well as some basic strategies and tactics for searches of periodic orbits. Our discussion should allow interested undergraduates to start their own searches. Users can submit new three-body orbits to a wiki-based website.

Global Symmetry is Unnecessary for Fast Quantum Search

Grover's quantum search algorithm can be formulated as a quantum particle randomly walking on the (highly symmetric) complete graph, with one vertex marked by a nonzero potential. From an initial equal superposition, the state evolves in a two-dimensional subspace. Strongly regular graphs have a local symmetry that ensures that the state evolves in a \emph{three}-dimensional subspace, but most have no \emph{global} symmetry. Using degenerate perturbation theory, we show that quantum random walk search on known families of strongly regular graphs nevertheless achieves the full quantum speedup of $\Theta(\sqrt{N})$, disproving the intuition that fast quantum search requires global symmetry.

New coordinates for the amplitude parameter space of continuous gravitational waves

The parameter space for continuous gravitational waves (GWs) can be divided into amplitude parameters (signal amplitude, inclination and polarization angles describing the orientation of the source, and an initial phase) and phase-evolution parameters (signal frequency and frequency derivatives, and parameters such as sky position which determine the Doppler modulation of the signal). The division is useful in part because of the existence of a set of functions known as the Jaranowski–Królak–Schutz (JKS) coordinates, which are a set of four coordinates on the amplitude parameter space such that the GW signal can be written as a linear combination of four template waveforms (which depend on the phase-evolution parameters) with the JKS coordinates as coefficients. We define a new set of coordinates on the amplitude parameter space, with the same properties, which can be more closely connected to the physical amplitude parameters. These naturally divide into two pairs of Cartesian-like coordinates on two-dimensional subspaces, one corresponding to left- and the other to right-circular polarization. We thus refer to these as circular polarization factored (CPF) coordinates. The corresponding two sets of polar coordinates (known as CPF-polar) can be related in a simple way to the physical parameters. A further coordinate transformation can be made, within each subspace, between CPF and so-called root-radius coordinates, whose radial coordinate is the fourth root of the radial coordinate in CPF-polar coordinates. We illustrate some simplifying applications for these various coordinate systems, such as a calculation of the Jacobian for the transformation between JKS or CPF coordinates and the physical amplitude parameters (amplitude, inclination, polarization and initial phase); a demonstration that the Jacobian between root-radius coordinates and the physical parameters is a constant; an illustration of the signal coordinate singularities associated with left- and right-circular polarization, which correspond to the origins of the two two-dimensional subspaces; and an elucidation of the form of the log-likelihood ratio between hypotheses of Gaussian noise with and without a continuous GW signal. These are used to illustrate some of the prospects for approximate evaluation of a Bayesian detection statistic defined by marginalization over the physical parameter space. Additionally, in the presence of simplifying assumptions about the observing geometry, we are able, using CPF-polar coordinates, to explicitly evaluate the integral for the Bayesian detection statistic, and compare it to the approximate results.