Deterministic Source Research Articles

Deterministic Ultracold Ion Source Targeting the Heisenberg Limit

The major challenges to fabricate quantum processors and future nano-solid-state devices are material modification techniques with nanometer resolution and suppression of statistical fluctuations of dopants or qubit carriers. Based on a segmented ion trap with mK laser-cooled ions we have realized a deterministic single-ion source which could operate with a huge range of sympathetically cooled ion species, isotopes or ionic molecules. We have deterministically extracted a predetermined number of ions on demand and have measured a longitudinal velocity uncertainty of 6.3 m/s and a spatial beam divergence of 600 microrad. We show in numerical simulations that if the ions are cooled to the motional ground state (Heisenberg limit) nanometer spatial resolution can be achieved.

Quantum interfaces using nanoscale surface plasmons

The strong coupling between individual optical emitters and propagating surface plasmons confined to a conducting nanotip make this system act as an ideal interface for quantum networks, through which a stationary qubit and a flying photon (surface plasmon) qubit can be interconverted via a Raman process. This quantum interface paves the way for many essential functions of a quantum network, including sending, receiving, transferring, swapping, and entangling qubits at distributed quantum nodes as well as a deterministic source and an efficient detector of a single-photon. Numerical simulation shows that this scheme is robust against experimental imperfections and has high fidelity. Furthermore, being smaller this interface would significantly facilitate the scalability of quantum computers.

Accurate System Voltage and Timing Margin Simulation in High-Speed I/O System Designs

Accurate analysis of system timing and voltage margin including deterministic and random jitter is crucial in high-speed I/O system designs. Traditional SPICE-based simulation techniques can precisely simulate various deterministic jitter sources, such as intersymbol interference (ISI) and crosstalk from passive channels. The inclusion of random jitter in SPICE simulations, however, results in long simulation time. Innovative simulation techniques based on a statistical simulation framework have been recently introduced to cosimulate deterministic and random jitter effects efficiently. This paper presents new improvements on this statistical simulation framework. In particular, we introduce an accurate jitter modeling technique which accounts for bounded jitter with arbitrary spectrum in addition to Gaussian jitter. We also present a rigorous approach to model duty cycle distortion (DCD). A number of I/O systems are considered as examples to validate the proposed modeling methodology.

Towards the implanting of ions and positioning of nanoparticles with nm spatial resolution

Decreasing structure sizes in both conventional and quantum solid state devices require novel fabrication methods: we present a technology which allows to implant ions through a small hole in the tip of an atomic force microscope. This technique offers a maskless addressing of small structures using different projectiles at kinetic energies between 0.5 and 5.0 keV. Our method aims to implant single atomic ions, molecular ions or charged nanoparticles with nm resolution. We test the method by implanting N+ ions into diamond and generating nitrogen-vacancy color centers. The system is operated with a conventional ion gun. However, in future we will employ an ion trap as a deterministic source of cold single ions.

Developments in nano-oscillators based upon spin-transfer point-contact devices

We review the current status of research on microwave nano-oscillators that utilize spin transfer devices with point-contact geometry, with an emphasis on the open questions that still prevent our full understanding of device properties. In particular, we examine those aspects that might affect irreproducibility of device performance. While there is a clear picture of the general principles that underlie the properties of the spin torque nano-oscillator, there are a number of details complicating the picture. We suggest that these details are potentially responsible for adversely affecting uniformity of performance from device to device. These details include (1) nonlinearities, (2) the Oersted field, (3) thermal and deterministic noise sources, and (4) non-uniformity of the spin accumulation. We suggest what role that these details might have in determining spin torque dynamics, and suggest particular avenues of investigation that might clarify whether or not these details are indeed responsible for device variability. This article is one of a series devoted to the subject of spin torque in this issue of the Journal of Magnetism and Magnetic Materials.

Retrieving reflection responses by crosscorrelating transmission responses from deterministic transient sources: Application to ultrasonic data

By crosscorrelating transmission recordings of acoustic or elastic wave fields at two points, one can retrieve the reflection response between these two points. This technique has previously been applied to measured elastic data using diffuse wave-field recordings. These recordings should be relatively very long. The retrieval can also be achieved by using deterministic transient sources with the advantage of using short recordings, but with the necessity of using many P-wave and S-wave sources. Here, it is shown how reflections were retrieved from the cross correlation of transient ultrasonic transmission data measured on a heterogeneous granite sample.

A critique of the stochastic transition matrix formalism

The Stochastic Transition Matrix (STM) formalism has been introduced by Akcasu to compute the ensemble average flux of bimaterial stochastic density statistics with deterministic sources. The method uses an integral flux representation based on a stochastic propagator and as boundary conditions the entering and exiting fluxes at the left of a finite slab. In this paper we generalize the STM formalism to the energy-dependent continuous transport equation, analyze and discuss basic issues of the formalism and compare it to the classical Levermore–Pomranig model and to reference calculations for simplified rod problems. We also extend the formalism in two different ways to consistently compute the ensemble and the material averages flux.

InP/GaInP Quantum Dots as Single-Photon Sources for Quantum Information Processing

Many important realizations and proposals for applications in quantum information processing require single photons as carriers of quantum information. Here, we review different demonstrations of quantum applications using a deterministic single-photon source based on InP/GaInP quantum dots. First, the single-photon generation is described and verified by autocorrelation measurements. A modification of the correlation setup allows the simultaneous observation of wave and particle properties of the photons. Additional to single-photon emission, photon pairs and triplets from multiexciton cascades were observed, as well. Using a Michelson interferometer an efficient separation of photon pairs can be achieved allowing multiplexing on a single-photon level. The applicability was demonstrated in a quantum key distribution experiment. As another application, different degrees of freedom of a single photon were used to realize a two-qubit Deutsch-Jozsa algorithm. Encoding the quantum information in appropriate bases, an operation of the setup resistant to phase fluctuation was demonstrated.

PREDICTING EXTINCTION RISK IN SPITE OF PREDATOR–PREY OSCILLATIONS

Most population viability analyses (PVA) assume that the effects of species interactions are subsumed by population-level parameters. We examine how robust five commonly used PVA models are to violations of this assumption. We develop a stochastic, stage-structured predator-prey model and simulate prey population vital rates and abundance. We then use simulated data to parameterize and estimate risk for three demographic models (static projection matrix, stochastic projection matrix, stochastic vital rate matrix) and two time series models (diffusion approximation [DA], corrupted diffusion approximation [CDA]). Model bias is measured as the absolute deviation between estimated and observed quasi-extinction risk. Our results highlight three generalities about the application of single-species models to multi-species conservation problems. First, our collective model results suggest that most single-species PVA models overestimate extinction risk when species interactions cause periodic variation in abundance. Second, the DA model produces the most (conservatively) biased risk forecasts. Finally, the CDA model is the most robust PVA to population cycles caused by species interactions. CDA models produce virtually unbiased and relatively precise risk estimates even when populations cycle strongly. High performance of simple time series models like the CDA owes to their ability to effectively partition stochastic and deterministic sources of variation in population abundance.

Contrasting stochastic and support theory accounts of subadditivity

Numerous studies have found that likelihood judgment typically exhibits subadditivity in which judged probabilities of events are less than the sum of judged probabilities of constituent events. Whereas traditional accounts of subadditivity attribute this phenomenon to deterministic sources, this paper demonstrates both formally and empirically that subadditivity is systematically influenced by the stochastic variability of judged probabilities. First, making rather weak assumptions, we prove that regressive error (or variability) in mapping covert probability judgments to overt responses is sufficient to produce subadditive judgments. Experiments follow in which participants provided repeated probability estimates. The results support our model assumption that stochastic variability is regressive in probability estimation tasks and show the contribution of such variability to subadditivity. The theorems and the experiments focus on within-respondent variability, but most studies use between-respondent designs. Numerical simulations extend the work to contrast within- and between-respondent measures of subadditivity. Methodological implications of all the results are discussed, emphasizing the importance of taking stochastic variability into account when estimating the role of other factors (such as the availability bias) in producing subadditive judgments.

Correlations of Random Binary Sequences with Pre-Stated Operator Intention: A Review of a 12-Year Program

Strong correlations between output distribution means of a variety of random binary processes and pre-stated intentions of some 100 individual human operators have been established over a 12-year experimental program. More than 1000 experimental series, employing four different categories of random devices and several distinctive protocols, show comparable magnitudes of anomalous mean shifts from chance expectation, with similar distribution structures. Although the absolute effect sizes are quite small, of the order of 10 −4 bits deviation per bit processed, over the huge databases accumulated, the composite effect exceeds 7σ (p ≈ 3.5 × 10 −13). These data display significant disparities between female and male operator performances, and consistent serial position effects in individual and collective results. Data generated by operators far removed from the machines and exerting their efforts at times other than those of machine operation show similar effect sizes and structural details to those of the local, on-time experiments. Most other secondary parameters tested are found to have little effect on the scale and character of the results, with one important exception: studies performed using fully deterministic pseudorandom sources, either hard-wired or algorithmic, yield null overall mean shifts, and display no other anomalous features.

Run-to-run control and state estimation in high-mix semiconductor manufacturing

In the modeling and control of semiconductor manufacturing, the control engineer must be aware of all influences on the performance of each process. Upstream processes may affect the wafer substrate in a manner that alters performance in downstream operations, and the context within which a process is run may fundamentally change the way the process behaves. Incorporating these influences into a control method ultimately leads to better predictability and improved control performance. Control threads are a way of incorporating these effects into the control of a process by partitioning historical data into groups within which the deterministic sources of variation are uniform. However, if there are many products, which require many threads to be defined, there may be insufficient data to model each thread. This multi-product–multi-tool manufacturing environment (“high-mix”) requires advanced methodologies based on state estimation and recursive least squares. Several such approaches are compared in this paper based on simulation models for a high-mix fab.

Real-time audio rendering system for virtual reality

Systems of virtual acoustics are more and more coming into the focus of research and application. Creating a virtual sound scene with spatially distributed sources requires a technique for adding spatial cues to audio signals and an appropriate reproduction. A real-time audio rendering system is introduced that combines room acoustics, dynamic crosstalk cancellation, and multitrack binaural synthesis for virtual acoustical imaging. The room acoustics component takes into account the full up-to-date algorithmic approach of specular reflections and scattering, but with real-time processing. The real-time performance of the software was reached by introduction of a flexible framework for the interactive auralisation of virtual environments. The concept of scene graphs for the efficient and flexible linkage of autonomous-operating subscenes by means of so-called portals has been incorporated into the existing framework, combined with an underlying BSP-tree structure for processing geometry issues very fast. Using this framework enables a significant reduction of computation time for both applied algorithms (deterministic image sources and a stochastic ray tracer). This enables the simulation of indoor or outdoor spatial distributed sources and, in addition to that, near-to-head sources for a freely moving listener in room-mounted virtual environments without the use of headphones.

Deterministic and Storable Single-Photon Source Based on a Quantum Memory

A single-photon source is realized with a cold atomic ensemble (87Rb atoms). A single excitation, written in an atomic quantum memory by Raman scattering of a laser pulse, is retrieved deterministically as a single photon at a predetermined time. It is shown that the production rate of single photons can be enhanced considerably by a feedback circuit while the single-photon quality is conserved. Such a single-photon source is well suited for future large-scale realization of quantum communication and linear optical quantum computation.

Neural Network Modeling of Deterministic Unsteadiness Source Terms

A neural-network-based lumped deterministic source term technique is presented that results in the prediction of an approximate time-average solution when used to modify a steady-state solver. Three different neural networks are developed for simple cavity flows using Mach number, cavity length-to-depth ratio, and aft wall translation as parameters. The results indicate that axial force data can be reproduced with less than 15% error as compared to the time average of a fully unsteady calculation. Computation times for the resultant neural network lumped deterministic source term approach were up to two orders of magnitude less than the comparable unsteady solution and were essentially identical to that of a steady-state calculation, although it must be noted that a database of unsteady calculations is required to develop the technique. The lumped deterministic source terms did not appear to affect the robustness of the steady-state solver adversely.

Blind Estimation of the Ocean Acoustic Channel by Time–Frequency Processing

A blind estimator of the ocean acoustic channel impulse response envelope is presented. The signal model is characterized by a deterministic multipath channel excited by a highly nonstationary deterministic source signal. The time-frequency (TF) representation of the received signal allows for the separation between the channel and the source signal. The proposed estimator proceeds in two steps: First, the unstable initial arrivals allow for the estimation of the source signal instantaneous frequency (IF) by maximization of the radially Gaussian kernel distribution; then, the Wigner-Ville distribution (WV) is sequentially windowed and integrated, where the window is defined by the previously estimated IF. The integral gives the channel impulse response envelope, which turns to be an approximation to the blind conventional matched filter (MF). The blind channel estimator (CE) is applicable upon the following conditions: that the multipath channel contains at least one dominant arrival well separated from the others, and that the IF of the source signal is a one-to-one function. Results obtained on real data from the INternal TIde Measurements with Acoustic Tomography Experiments (INTIMATE'96), where the acoustic channel was driven by an linear frequency modulation signal, show that the channel's envelope detailed structure could be accurately and consistently recovered, with the correlation of the estimates ranging from 0.796 to 0.973, as compared to the MF result

Definitive number of atoms on demand: Controlling the number of atoms in a few-atom magneto-optical trap

A few Rb85 atoms were trapped in a micron-size magneto-optical trap with a high quadrupole magnetic-field gradient and the number of atoms was precisely controlled by suppressing stochastic loading and loss events via real-time feedback on the magnetic-field gradient. The measured occupation probability of a single atom was as high as 99%. Atoms up to five were also trapped with high occupation probabilities. The present technique could be used to make a deterministic atom source.

Error Analysis and Stochastic Modeling of Low-cost MEMS Accelerometer

This paper presents the error analysis and stochastic modeling of commercial low-cost MEMS Accelerometer. Although Micro Electro Mechanical Systems (MEMS) based sensors have been utilized for the development of low-cost integrated navigation systems on the benefits of low inherent cost, small size, low power consumption, and solid reliability, it is significantly important to characterize the error behaviors of MEMS-based sensors and to construct more sophisticated mathematical modeling methods. The errors of MEMS-based accelerometer have been identified into deterministic and stochastic error sources and the stochastic error part was the focus to be discussed in this paper using discrete parameter models of stationary random process. Appropriate Autoregressive (AR) models have been analyzed which can be used to help the development of appropriate optimal algorithm for multiple sensor integration.

Ambiguity-function-based techniques to estimate DOA of broadband chirp signals

Various methods are available to perform direction-of-arrival (DOA) estimation for random sources. However, the work on DOA estimation of deterministic sources, such as broadband chirp signals, is quite limited. This paper proposes two novel methods for broadband chirp DOA estimation (BCD), namely the incoherent broadband chirp DOA estimation (BCD-I) and coherent broadband chirp DOA estimation (BCD-C). The proposed methods exploit the time-frequency structure of the chirp signal via the ambiguity function, which converts the absolute time and frequency of the chirp signal into relative time lag and frequency difference. The algorithms can be applied to arrays of any aperture size and arbitrary chirp rate signals. The signal frequency of the source can be higher than the conventional array design frequency, and the number of sources can be greater than the number of sensors as long as the signals are separable in the ambiguity function plane. These methods can be applied to single or multiple chirps with the same or different chirp rates. The performance analysis shows that our algorithms generally provide improvements in the DOA estimation of the broadband chirp sources.

Median-based clustering for underdetermined blind signal processing

In underdetermined blind source separation, more sources are to be extracted from less observed mixtures without knowing both sources and mixing matrix. k-means-style clustering algorithms are commonly used to do this algorithmically given sufficiently sparse sources, but in any case other than deterministic sources, this lacks theoretical justification. After establishing that mean-based algorithms converge to wrong solutions in practice, we propose a median-based clustering scheme. Theoretical justification as well as algorithmic realizations (both online and batch) are given and illustrated by some examples.