Including Quantum Noise Research Articles

Quantum coherent control in pulsed waveguide optomechanics

Coherent control of traveling acoustic excitations in a waveguide system is an interesting way to manipulate and transduce classical and quantum information. So far, these interactions, often based on optomechanical resonators or Brillouin scattering, have been studied in the steady-state regime using continuous waves. However, waveguide experiments are often based on optical pump pulses, which require treatment in a dynamic framework. In this paper, we present an effective Hamiltonian formalism in the dynamic regime using optical pulses that links waveguide optomechanics and cavity optomechanics, which can be used in the classical and quantum regime including quantum noise. Based on our formalism, a closed solution for coupled-mode equation under the undepleted assumption is provided and we found that the strong coupling regime is already accessible in current Brillouin waveguides by using pulses. We further investigate several possible experiments within waveguide optomechanics, including Brillouin-based coherent transfer, Brillouin cooling, and optoacoustic entanglement.

Solution of the Schrödinger Equation on a Quantum Computer by the Zalka–Wiesner Method Including Quantum Noise

Solution of the Schrödinger Equation on a Quantum Computer by the Zalka–Wiesner Method Including Quantum Noise

Thermal charge carrier driven noise in transmissive semiconductor optics

Several sources of noise limit the sensitivity of current gravitational wave detectors. Currently, dominant noise sources include quantum noise and thermal Brownian noise, but future detectors will also be limited by other thermal noise channels. In this paper, we study a thermal noise source which is caused by spatial charge carrier density variations in semiconductor materials. We provide an analytical model for the understanding of charge carrier fluctuations under the presence of screening effects and show that charge carrier noise will not be a limiting noise source for third-generation gravitational wave detectors.

Unified analysis of coherence property of a Stokes wave generated via a stimulated Raman process in optical fiber.

We investigate the evolution of coherence property of a noise-seeded Stokes wave in short (<1ps) and long pulse (>1ps) regimes numerically through a set of coupled nonlinear equations. The simulations include quantum noise by incorporating noise seed in the pump field. The spectral phase fluctuations of the Stokes wave for both regimes are characterized, and the degrees of first-order mutual spectral coherence are calculated for different conditions. Statistical analysis demonstrates the effect of spectral coherence of the Stokes wave in optical fiber on pump power, fiber length, and pump pulse width for short and long pulse regimes. It is observed that the noise-seeded stimulated Raman process causes degradation of spectral coherence with the increase in pump power, fiber length, and pulse width of the pump wave. The degradation of the spectral coherence is manifested by the transition of the Stokes wave from a quasi-coherent to incoherent spectrum.

Parametric effects in circuit quantum electrodynamics

We review recent advances in the research on quantum parametric phenomena in superconducting circuits with Josephson junctions. We discuss physical processes in parametrically driven tunable cavity and outline theoretical foundations for their description. Amplification and frequency conversion are discussed in detail for degenerate and nondegenerate parametric resonance, including quantum noise squeezing and photon entanglement. Experimental advances in this area played decisive role in successful development of quantum limited parametric amplifiers for superconducting quantum information technology. We also discuss nonlinear down-conversion processes and experiments on self-sustained parametric and subharmonic oscillations.

A statistically defined anthropomorphic software breast phantom

Digital anthropomorphic breast phantoms have emerged in the past decade because of recent advances in 3D breast x-ray imaging techniques. Computer phantoms in the literature have incorporated power-law noise to represent glandular tissue and branching structures to represent linear components such as ducts. When power-law noise is added to those phantoms in one piece, the simulated fibroglandular tissue is distributed randomly throughout the breast, resulting in dense tissue placement that may not be observed in a real breast. The authors describe a method for enhancing an existing digital anthropomorphic breast phantom by adding binarized power-law noise to a limited area of the breast. Phantoms with (0.5 mm)(3) voxel size were generated using software developed by Bakic et al. Between 0% and 40% of adipose compartments in each phantom were replaced with binarized power-law noise (β = 3.0) ranging from 0.1 to 0.6 volumetric glandular fraction. The phantoms were compressed to 7.5 cm thickness, then blurred using a 3 × 3 boxcar kernel and up-sampled to (0.1 mm)(3) voxel size using trilinear interpolation. Following interpolation, the phantoms were adjusted for volumetric glandular fraction using global thresholding. Monoenergetic phantom projections were created, including quantum noise and simulated detector blur. Texture was quantified in the simulated projections using power-spectrum analysis to estimate the power-law exponent β from 25.6 × 25.6 mm(2) regions of interest. Phantoms were generated with total volumetric glandular fraction ranging from 3% to 24%. Values for β (averaged per projection view) were found to be between 2.67 and 3.73. Thus, the range of textures of the simulated breasts covers the textures observed in clinical images. Using these new techniques, digital anthropomorphic breast phantoms can be generated with a variety of glandular fractions and patterns. β values for this new phantom are comparable with published values for breast tissue in x-ray projection modalities. The combination of conspicuous linear structures and binarized power-law noise added to a limited area of the phantom qualitatively improves its realism.

TU‐D‐204C‐03: Machine Learning for Medical Image Processing and Pattern Recognition

Machine learning plays an essential role in medical image analysis, because objects such as lesions and organs in medical images cannot be modeled accurately by simple equations; thus, tasks in medical image analysis require essentially “learning from examples.” One of the most popular uses of machine learning in medical image analysis is the classification of objects such as lesions into certain categories (e.g., abnormal or normal, lesions or non‐lesions). This class of machine leaning uses features (e.g., diameter, contrast, and circularity) extracted from segmented objects as information for classifying the objects. Machine learning techniques in this class include linear discriminant analysis, a k‐nearest neighbor classifier, an artificial neural network, and a support vector machine.Recently, as available computational power increased dramatically, a new class of machine learning called pixel/voxel‐based machine learning emerged in medical image processing and analysis, which uses pixel/voxel values in images directly instead of calculated features as input information; thus, feature calculation is not required. Because pixel/voxel‐based machine learning can avoid errors caused by inaccurate segmentation and feature calculation, the performance of the pixel/voxel‐based machine learning can be better than common feature‐based machine learning. Such advanced machine‐learning techniques in this class include neural filters, neural edge enhancers, massive‐training artificial neural networks, convolution neural networks, and shift‐invariant neural networks. This lecture will provide an overview of techniques, methodologies, and applications of machine learning used in medical image processing and pattern recognition, which have been developed and advanced mainly in the field of diagnostic radiology in the past two decades or so. The applications of these machine‐learning techniques include quantum noise reduction, enhancement of the boundary of an organ, lesion enhancement, classification of lesions, and computer‐aided diagnosis. Once we have learned such machine‐learning techniques and methodologies, they can be translated quickly into new techniques for solution of problems in radiation therapy.Learning Objectives:1. Understand the basic principle of machine‐learning techniques2. Learn various techniques in the two major classes of feature‐based and mitationsof machine learning3. Understand the advantages and limitations of machine‐learning techniques4. Learn applications of machine‐learning techniques in medical image processing and pattern recognition5. Consider applications of machine‐learning techniques and methodologies in the field of radiation therapy

Asymptotic Spectral Measures, Quantum Mechanics, and E -Theory

We study the relationship between POV-measures in quantum theory and asymptotic morphisms in the operator algebra E-theory of Connes–Higson. This is done by introducing the theory of “asymptotic” PV-measures and their integral correspondence with positive asymptotic morphisms on locally compact spaces. Examples and applications involving various aspects of quantum physics, including quantum noise models, semiclassical limits, strong deformation quantizations, and pure half-spin particles, are also discussed.

Quantum Maxwell-Bloch equations for spatially inhomogeneous semiconductor lasers

We present quantum Maxwell-Bloch equations (QMBE) for spatially inhomogeneous semiconductor laser devices. The QMBE are derived from fully quantum mechanical operator dynamics describing the interaction of the light field with the quantum states of the electrons and the holes near the band gap. By taking into account field-field correlations and field-dipole correlations, the QMBE include quantum noise effects which cause spontaneous emission and amplified spontaneous emission. In particular, the source of spontaneous emission is obtained by factorizing the dipole-dipole correlations into a product of electron and hole densities. The QMBE are formulated for general devices, for edge emitting lasers and for vertical cavity surface emitting lasers, providing a starting point for the detailed analysis of spatial coherence in the near field and far field patterns of such laser diodes. Analytical expressions are given for the spectra of gain and spontaneous emission described by the QMBE. These results are applied to the case of a broad area laser, for which the frequency and carrier density dependent spontaneous emission factor beta and the evolution of the far field pattern near threshold are derived.

Quantum noise initiation and macroscopic fluctuations in optical parametric oscillators

The signals in an optical parametric oscillator (OPO) build up from quantum noise. In pulsed OPO’s this can lead to fluctuations in such macroscopic signal properties as rise time, pulse energy, frequency spectrum, and transverse profile. The strength of these fluctuations is investigated by use of simulation models that include quantum noise, multiple longitudinal modes, dispersion, birefringence, arbitrary output coupling, and transverse pump profile. The results are compared with results obtained with classical deterministic models to find out how well such models can estimate expectation values of signal observables.

Properties of the linearized quantum optical bus

A formalism is developed that allows one to calculate the propagation of quantum noise, technical noise, and signals through a linearized quantum optical bus, i.e., a complex composite multibeam optical quantum system. General expressions for the output squeezing, the correlation coefficient, and quantum correlation coefficient between output observables and the transfer coefficients are derived and discussed in detail. The total correlation is introduced as a measure of the overall correlation of a set of output quadratures. From its geometric interpretation a multidimensional uncertainty relation is derived. Direct quantum-state preparation (QSP) is introduced as a method complementary to the conventional, indirect QSP. The minimal variance achievable by direct QSP is shown to provide superior noise suppression, including quantum noise suppression, than the conditional variance provided by indirect QSP. As an application we calculate and discuss the properties of a balanced bus of beam splitters with squeezed vacua at the usually unused ports. An important experimental effect is imperfect beam mode match, which is shown to lead to dramatic effects. A theory is derived which quantitatively matches measurements. Analytic expressions for the imperfectly modematched squeezed-light beam splitter including detection losses are given. Finally, a direct method is used to calculate the input-output matrix for the multiport subthreshold degenerate optical parametric amplifier for arbitrary parametric and mirror coupling strengths and detuning.

Quantitative characterization of multiple delaminations in laminated composites using the compton backscatter technique

A Compton X-ray backscatter technique was used to supplement ultrasonic pulse-echo C-scan imaging to quantitatively assess the impact damage in quasi-isotropic laminated composites which were impacted by a drop-weight tester. A Compton backscatter imaging system with a slit-type camera was developed to obtain a cross-sectional profile of impact-damaged laminated composites from the density variation of the cross-section. A nonlinear reconstruction model is introduced to overcome distortion of the Compton backscatter image due to attenuation effects, beam hardening, and irregular distributions of the fibers and the matrix in composites. An adaptive filter is used to reduce noise from many sources including quantum noise, especially when the SNR (signal-to-noise ratio) of the image is relatively low. Delaminations masked or distorted by the first few delaminations in an ultrasonic C-scan image are detected and characterized by the Compton back-scatter technique, both in width and location.

Analysis of a dye-laser model including quantum noise.

An analytical study of a dye-laser model which includes quantum white noise and nonwhite pump fluctuations is presented. The extension of an earlier approximation to include quantum noise gives a unified picture of the statistical properties of the laser light for negative pump parameters. These include intensity fluctuations and discontinuous changes of the most probable intensity. An alternative approximation (obtained within the same scheme) is discussed for situations above threshold.

Noise analysis of a digital radiography system.

The sources of noise in a digital video subtraction angiography system were identified and analyzed. Signal-to-noise ratios of digital radiography systems were measured using the digital image data recorded in the computer. The major sources of noise include quantum noise, TV camera electronic noise, quantization noise from the analog-to-digital converter, time jitter, structure noise in the image intensifier, and video recorder electronic noise. A new noise source was identified, which results from the interplay of fixed pattern noise and the lack of image registration. This type of noise may result from image-intensifier structure noise in combination with TV camera time jitter or recorder time jitter. A similar noise source is generated from the interplay of patient absorption inhomogeneities and patient motion or image re-registration. Signal-to-noise ratios were measured for a variety of experimental conditions using subtracted digital images. The measured signal-to-noise ratios were found to fluctuate on repeat trials with about a 10% standard deviation. Averaging of video frames was found to reduce the noise level by the expected square root N relation, where N is the number of frames averaged. Image-intensifier structure noise was shown to be a dominant noise source in unsubtracted images at medium to high radiation exposure levels. A total-system signal-to-noise ratio (SNR) of 750:1 was measured for an input exposure of 1 mR/frame at the image intensifier input. The effect of scattered radiation on subtracted image SNR was found to be greater than previously reported. The detail SNR was found to vary approximately as one plus the scatter degradation factor. Quantization error noise with 8-bit image processors (signal-to-noise ratio of 890:1) was shown to be of increased importance after recent improvements in TV cameras. The results of the analysis are useful both in the design of future digital radiography systems and the selection of optimum clinical techniques.