基于分割的热图压缩

热图作为一种专用图像，为了更好地传输和存储，必须进行压缩。本文依据热图的高频成分少，灰度较集中的特点，在借鉴模式识别思想的基础上，提出一种新的压缩方法——基于分割的热图压缩方法。该方法结合了小波变换编码与Ｒ－Ｃ分割方法对热图进行了压缩，并以传热学原理为依据，对其进行内插重建，获得了１０２４的高压缩比，并得到较好的可视性。这种方法尤其适用于仅具有目标和背景的红外热图。该方法有利于硬件的实现，且可以更好地利用硬件的实时性。     

The threaded BPM: A novel extension to the two-dimensional scalar beam propagation method

The two-dimensional scalar beam propagation method (BPM) is a widely used, computationally efficient tool for the analysis of planar optical waveguides and devices. The inherent paraxial limitations and rectilinear analysis grid limit its application to slightly curved structures and waveguides. In this novel extention to the BPM algorithm, the curvature restrictions are removed and in many cases the paraxial restrictions can be avoided, allowing for the first time, the efficient analysis of arbitrarily curved structures, such as S- or U-shaped bends, curved transitions of progressively varying curvature, and curved couplers. It can also handle concatenated devices and the curved interconnect sections between them. The process operates by the concatenation of micro-conformal maps, which progressively re-orientate the problem optimally towards a straight BPM analysis.     

Shaping of intense ion beams into hollow cylindrical form

A specifically tailored plasma lens could shape a high-energy, heavy-ion beam into the form of a hollow cylinder without loss of beam intensity. It has been experimentally confirmed that both a positive as well as a negative radial gradient of the current density in the active plasma lens can be the underlying principle. Calculations were performed that yield the ideal current density distribution for both cases. A numerical simulation of an experiment with an intense ion beam highlights that the shaping of the beam increases the achievable compression in a lead sample.     

Adaptive pulse compression by two-photon absorption in semiconductors

We investigate the adaptive optimization of broadband laser pulses, using a closed-loop learning algorithm in which the merit function is derived from two-photon absorption in semiconductors. Photoluminescence experiments with CdS thin films and photocurrent measurements of a GaAsP photodiode have been performed. The experimental data demonstrate that reliable and accurate pulse compression to the bandwidth limit can be achieved, unperturbed by nontrivial phase effects. Therefore two-photon absorption proves to be an easy-to-implement alternative to second-harmonic generation for the compression of broadband laser pulses.     

Rapid analysis of non-uniformly sampled pulsed field gradient data for velocity estimation.

Bretthorst's recent generalization of the Lomb-Scargle periodogram shows that a sufficient statistic for frequency estimation from non-uniformly, but simultaneously sampled quadrature data is equivalent to the FFT of those data with the missing samples replaced by zeros. We have applied this concept to the rapid analysis of pulsed field gradient MRI data which have been non-uniformly sampled in the velocity encoding wave vector q. For a small number of q samples, it is more computationally efficient to calculate the periodogram directly rather than using the FFT algorithm with a large number of zeros. The algorithm we have implemented for finding the peak of the generalized periodogram is simple and robust; it involves repeated apodization and grid searching of the periodogram until the desired velocity resolution is achieved. The final estimate is refined by quadratic interpolation. We have tested the method for fully developed Poiseuille flow of a Newtonian fluid and have demonstrated substantial improvement in the precision of velocity measurement achievable in a fixed acquisition time with non-uniform sampling. The method is readily extendible to multidimensional data. Analysis of a 256 by 256 pixel image with 8 q samples and an effective velocity resolution of better than 1/680 of the Nyquist range requires approximately 1 minute computation time on a 400 MHz SUN Ultrasparc II processor.     

Compression and extraction of stopped muons

Efficient conversion of a standard positive muon beam into a high-quality slow muon beam is shown to be achievable by compression of a muon swarm stopped in an extended gas volume. The stopped swarm can be squeezed into a mm-size swarm flow that can be extracted into vacuum through a small opening in the stop target walls. Novel techniques of swarm compression are considered. In particular, a density gradient in crossed electric and magnetic fields is used.     

Spin based heat engine: demonstration of multiple rounds of algorithmic cooling

We experimentally demonstrate multiple rounds of heat-bath algorithmic cooling in a 3 qubit solid-state nuclear magnetic resonance quantum information processor. By pumping entropy into a heat bath, we are able to surpass the closed system limit of the Shannon bound and purify a single qubit to 1.69 times the heat-bath polarization. The algorithm combines both high fidelity coherent control and a deliberate interaction with the environment. Given this level of quantum control in systems with larger reset polarizations, nearly pure qubits should be achievable.     

Limit of spin squeezing in finite-temperature Bose-Einstein condensates

We show that, at finite temperature, the maximum spin squeezing achievable using interactions in Bose-Einstein condensates has a finite limit when the atom number N→∞ at fixed density and interaction strength. We calculate the limit of the squeezing parameter for a spatially homogeneous system and show that it is bounded from above by the initial noncondensed fraction.     

Structural Entropy of the Stochastic Block Models

With the rapid expansion of graphs and networks and the growing magnitude of data from all areas of science, effective treatment and compression schemes of context-dependent data is extremely desirable. A particularly interesting direction is to compress the data while keeping the “structural information” only and ignoring the concrete labelings. Under this direction, Choi and Szpankowski introduced the structures (unlabeled graphs) which allowed them to compute the structural entropy of the Erdős–Rényi random graph model. Moreover, they also provided an asymptotically optimal compression algorithm that (asymptotically) achieves this entropy limit and runs in expectation in linear time. In this paper, we consider the stochastic block models with an arbitrary number of parts. Indeed, we define a partitioned structural entropy for stochastic block models, which generalizes the structural entropy for unlabeled graphs and encodes the partition information as well. We then compute the partitioned structural entropy of the stochastic block models, and provide a compression scheme that asymptotically achieves this entropy limit.     

Intrinsic noise of semiconductor lasers in optical communication systems

The upper limit of the achievable signal-to-noise ratio in optical communication systems is determined by the intrinsic laser noise due to quantum fluctuations inside the laser cavity. This achievable signal-to-noise ratio depends on the way in which different lasing modes are detected; wavelength filtering and material dispersion may yield a significant deterioration of the signal-to-noise ratio. It is concluded from theoretical calculations and from measurements on V-groove lasers that a d.c. signal-to-noise ratio of about 70 dB may be achieved for a noise bandwidth of 10 MHz.     

Rate limit for photoassociation of a Bose-Einstein condensate

We simulate numerically the photodissociation of molecules into noncondensate atom pairs that accompanies photoassociation of an atomic Bose-Einstein condensate into a molecular condensate. Such rogue photodissociation sets a limit on the achievable rate of photoassociation. Given the atom density rho and mass m, the limit is approximately 6(planck)rho(2/3)/m.     

Crystalline—amorphous interface packings for disks and spheres

We have employed a computer simulation method for uniaxial compression to create random, but spatially inhomogeneous, disk and sphere packings in contact with exposed faces of their own close-packed crystals. The disk calculations involved 7920 movable particles, while the sphere cases utilized over 4000 particles. Rates of compression to the jamming limit were varied over two orders of magnitude, and in three dimensions this produced a clear distinction between the cases of jamming against (001) and (111) faces of the sphere crystal. Specifically, epitaxial order next to the (001) face was markedly enhanced by slowing the compression; for the (111) face the epitaxial order was quite insensitive to the compression rate.     

Diagonalization-free implementation of spin relaxation theory for large spin systems

The Liouville space spin relaxation theory equations are reformulated in such a way as to avoid the computationally expensive Hamiltonian diagonalization step, replacing it by numerical evaluation of the integrals in the generalized cumulant expansion. The resulting algorithm is particularly useful in the cases where the static part of the Hamiltonian is dominated by interactions other than Zeeman (e.g. in quadrupolar resonance, low-field EPR and Spin Chemistry). When used together with state space restriction tools, the algorithm reported is capable of computing full relaxation superoperators for NMR systems with more than 15 spins.     

A new mixed self-consistent field procedure

A new approach for the calculation of three-centre electronic repulsion integrals (ERIs) is developed, implemented and benchmarked in the framework of auxiliary density functional theory (ADFT). The so-called mixed self-consistent field (mixed SCF) divides the computationally costly ERIs in two sets: far-field and near-field. Far-field ERIs are calculated using the newly developed double asymptotic expansion as in the direct SCF scheme. Near-field ERIs are calculated only once prior to the SCF procedure and stored in memory, as in the conventional SCF scheme. Hence the name, mixed SCF. The implementation is particularly powerful when used in parallel architectures, since all RAM available are used for near-field ERI storage. In addition, the efficient distribution algorithm performs minimal intercommunication operations between processors, avoiding a potential bottleneck. One-, two- and three-dimensional systems are used for benchmarking, showing substantial time reduction in the ERI calculation for all of them. A Born–Oppenheimer molecular dynamics calculation for the Na⁺₅₅ cluster is also shown in order to demonstrate the speed-up for small systems achievable with the mixed SCF.     

A multilayer method of fundamental solutions for Stokes flow problems

The method of fundamental solutions (MFS) is a meshless method for the solution of boundary value problems and has recently been proposed as a simple and efficient method for the solution of Stokes flow problems. The MFS approximates the solution by an expansion of fundamental solutions whose singularities are located outside the flow domain. Typically, the source points (i.e. the singularities of the fundamental solutions) are confined to a smooth source layer embracing the flow domain. This monolayer implementation of the MFS (monolayer MFS) depends strongly on the location of the user-defined source points: On the one hand, increasing the distance of the source points from the boundary tends to increase the convergence rate. On the other hand, this may limit the achievable accuracy. This often results in an unfavorable compromise between the convergence rate and the achievable accuracy of the MFS. The idea behind the present work is that a multilayer implementation of the MFS (multilayer MFS) can improve the robustness of the MFS by efficiently resolving different scales of the solution by source layers at different distances from the boundary. We propose a block greedy-QR algorithm (BGQRa) which exploits this property in a multilevel fashion. The proposed multilayer MFS is much more robust than the monolayer MFS and can compute Stokes flows on general two- and three-dimensional domains. It converges rapidly and yields high levels of accuracy by combining the properties of distant and close source points. The block algorithm alleviates the overhead of multiple source layers and allows the multilayer MFS to outperform the monolayer MFS.     

Control of modulated vibration using an enhanced adaptive filtering algorithm based on model-based approach

Conventional adaptive filtering algorithms, typically limited to the control of single or multiple sinusoids, are not appropriate to control modulated vibrations, especially in the presence of rich side band structures. To overcome this deficiency, a new control algorithm is proposed that introduces a feedback loop with the model predictive sliding mode control (MPSMC) in the adaptive filtering system. Several amplitude and frequency modulation cases are first computationally studied, and conventional and proposed methods are comparatively evaluated in terms of estimation error, performance in time and frequency domains, stability, and uncertainty in the reference signal. To experimentally validate the proposed algorithm, an active strut (with longitudinal vibrations) is constructed. Overall, the proposed adaptive algorithm yields superior reductions at the main frequencies and at side bands; also, good attenuation is found on a broadband basis.     

Periodic changes in the state of a 4f-metal compound under ultrahigh pressure

The statement is grounded that, at experimentally achievable pressures, rare-earth compounds belong to one of the following three states: an electronic state, a vibronic state, and a state of electronic-vibronic equilibrium. Calculations show that the 4f electron configuration sequentially loses all electrons under strong compression. As the number of electrons decreases, all three states are assumed to sequentially exhibit their properties.     

An image joint compression-encryption algorithm based on adaptive arithmetic coding

Through a series of studies on arithmetic coding and arithmetic encryption, a novel image joint compression- encryption algorithm based on adaptive arithmetic coding is proposed. The contexts produced in the process of image compression are modified by keys in order to achieve image joint compression encryption. Combined with the bit-plane coding technique, the discrete wavelet transform coefficients in different resolutions can be encrypted respectively with different keys, so that the resolution selective encryption is realized to meet different application needs. Zero-tree coding is improved, and adaptive arithmetic coding is introduced. Then, the proposed joint compression-encryption algorithm is simulated. The simulation results show that as long as the parameters are selected appropriately, the compression efficiency of proposed image joint compression-encryption algorithm is basically identical to that of the original image compression algorithm, and the security of the proposed algorithm is better than the joint encryption algorithm based on interval splitting.     

Developing an algorithm for compression, multiplexing and enhancement of multiple images

Image compression is one of the important fields that has useful applications in data storage and transmission. In this research a new algorithm is developed and tested for multiple-image compression and enhancement. The algorithm, in addition, is applied to multiple noisy images. Also, the effect of compression ratio on the peak signal to noise ratio (PSNR) is explored by applying different compression ratios. The developed algorithm gives good compression and noise immunity. It can be used for storage/transmission of encrypted and compressed information.