Amplified thermal state: Properties and decoherence

2021 ◽  
pp. 2150448
Author(s):  
Zheng-Yin Zhao ◽  
Xue-Xiang Xu
Keyword(s):  
Light Intensity ◽  
Amplification Factor ◽  
Thermal State ◽  
Signal To Noise Ratio ◽  
Photon Number ◽  
Gaussian State ◽  
Matrix Elements ◽  
Number Operator ◽  
Signal To Noise ◽  
Photon Loss

In this paper, we introduce the amplified thermal state (ATS) by operating [Formula: see text] on the thermal state (TS). Here, [Formula: see text] is the amplification factor and [Formula: see text] is the photon number operator. We study its properties, such as light intensity, signal-to-noise ratio (SNR), Fock matrix elements and Wigner function. In addition, we study its decoherence in photon-loss channel by analyzing evolution of all above properties. All considered properties are derived analytically and simulated numerically. Compared with the original TS, the amplification can enhance light intensity and SNR, remain the mixed character, and exhibit non-Gaussianity. While the decoherence will weaken light intensity and SNR, remain the mixed character, and return to Gaussian state.

Comparative analysis of properties for amplified coherent state and amplified squeezed vacuum

2020 ◽  
Vol 34 (33) ◽  
pp. 2050377
Author(s):  
Yan-Bei Cheng ◽  
Sheng-Guo Guan ◽  
Zu-Jian Wang ◽  
Xue-Xiang Xu
Keyword(s):  
Comparative Analysis ◽  
Coherent State ◽  
Amplification Factor ◽  
Annihilation Operator ◽  
Photon Number ◽  
Matrix Elements ◽  
Squeezed Vacuum ◽  
Quadrature Squeezing ◽  
Antibunching Effect ◽  
Analytical Expressions

Two “amplified” quantum states, that is, amplified coherent state (ACS) and amplified squeezed vacuum (ASV), are considered in this paper by applying operator [Formula: see text] on coherent state (CS) and squeezed vacuum (SV), respectively. Here [Formula: see text] [Formula: see text] denotes a amplification factor and [Formula: see text]) denote the creation (annihilation) operator. Along these two lines, we make a comparative analysis of properties for ACS and ASV. The considered properties include density matrix elements, Wigner function, mean photon number, second-order autocorrelation function, and quadrature squeezing. We derive analytical expressions and make numerical simulations for all the properties. The noteworthy results include: (1) the ACS has antibunching and squeezing characters; (2) the ASV will have the bunching and antibunching effect in small initial squeezing.

scholarly journals Phase diffusion and the small-noise approximation in linear amplifiers: Limitations and beyond

Quantum ◽  
2019 ◽  
Vol 3 ◽  
pp. 200 ◽  
Author(s):  
Andy Chia ◽  
Michal Hajdušek ◽  
Rosario Fazio ◽  
Leong-Chuan Kwek ◽  
Vlatko Vedral
Keyword(s):  
Signal To Noise Ratio ◽  
Noise Analysis ◽  
Photon Number ◽  
Optical Field ◽  
Signal To Noise ◽  
Small Noise ◽  
Phase Diffusion ◽  
Small Noise Approximation ◽  
Linear Amplifier ◽  
Phase Uncertainty

The phase of an optical field inside a linear amplifier is widely known to diffuse with a diffusion coefficient that is inversely proportional to the photon number. The same process occurs in lasers which limits its intrinsic linewidth and makes the phase uncertainty difficult to calculate. The most commonly used simplification is to assume a narrow photon-number distribution for the optical field (which we call the small-noise approximation). For coherent light, this condition is determined by the average photon number. The small-noise approximation relies on (i) the input to have a good signal-to-noise ratio, and (ii) that such a signal-to-noise ratio can be maintained throughout the amplification process. Here we ask: For a coherent input, how many photons must be present in the input to a quantum linear amplifier for the phase noise at the output to be amenable to a small-noise analysis? We address these questions by showing how the phase uncertainty can be obtained without recourse to the small-noise approximation. It is shown that for an ideal linear amplifier (i.e. an amplifier most favourable to the small-noise approximation), the small-noise approximation breaks down with only a few photons on average. Interestingly, when the input strength is increased to tens of photons, the small-noise approximation can be seen to perform much better and the process of phase diffusion permits a small-noise analysis. This demarcates the limit of the small-noise assumption in linear amplifiers as such an assumption is less true for a nonideal amplifier.

An assessment of light-based geoposition estimates from archival tags

1999 ◽  
Vol 56 (7) ◽  
pp. 1317-1327 ◽  
Author(s):  
David W Welch ◽  
J Paige Eveson
Keyword(s):  
Light Intensity ◽  
Large Scale ◽  
Signal To Noise Ratio ◽  
Digital Signal ◽  
Rate Of Change ◽  
Average Error ◽  
Maximal Rate ◽  
Signal To Noise ◽  
Archival Tags ◽  
Migration Pathways

Archival tags record information about the environment of tagged animals over long periods of time (months to years). In theory, position can be estimated from a record of changes in light intensity with time. We describe two approaches to estimating geoposition based on estimating either the time of maximal rate of change in light intensity or the time that a reference light intensity is reached. Digital signal processing is investigated as a method of increasing the signal-to-noise ratio of the light record. Our test data suggest that the daily position of a tagged animal can potentially be estimated within an average error of about 140 km (SD's of 0.9° of longitude and 1.2° of latitude), approaching the resolution of the best eddy-resolving physical oceanographic models of ocean currents. The source of the remaining large-scale errors in geoposition appears to be extrinsic to the tags and may be related to large-scale weather systems. The accuracy of current archival tags is sufficient to permit an assessment of the open-ocean migration pathways of animals such as maturing salmon and may be sufficient for use in some parts of the continental shelf as well.

scholarly journals High Sensitivity Snapshot Spectrometer Based on Deep Network Unmixing

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7038
Author(s):  
Hui Xie ◽  
Zhuang Zhao ◽  
Jing Han ◽  
Lianfa Bai ◽  
Yi Zhang
Keyword(s):  
Neural Network ◽  
Light Intensity ◽  
Signal To Noise Ratio ◽  
High Sensitivity ◽  
Hadamard Transform ◽  
High Signal ◽  
Signal To Noise ◽  
Compact Structure ◽  
Reconstructed Signal ◽  
Noise Ratio

Spectral detection provides rich spectral–temporal information with wide applications. In our previous work, we proposed a dual-path sub-Hadamard-s snapshot Hadamard transform spectrometer (Sub-s HTS). In order to reduce the complexity of the system and improve its performance, we present a convolution neural network-based method to recover the light intensity distribution from the overlapped dispersive spectra, rather than adding an extra light path to capture it directly. In this paper, we construct a network-based single-path snapshot Hadamard transform spectrometer (net-based HTS). First, we designed a light intensity recovery neural network (LIRNet) with an unmixing module (UM) and an enhanced module (EM) to recover the light intensity from the dispersive image. Then, we used the reconstructed light intensity as the original light intensity to recover high signal-to-noise ratio spectra successfully. Compared with Sub-s HTS, the net-based HTS has a more compact structure and high sensitivity. A large number of simulations and experimental results have demonstrated that the proposed net-based HTS can obtain a better-reconstructed signal-to-noise ratio spectrum than the Sub-s HTS because of its higher light throughput.

scholarly journals Higher-Order Amplitude Squeezing in Six-Wave Mixing Process

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Sunil Rani ◽  
Jawahar Lal ◽  
Nafa Singh
Keyword(s):  
Fundamental Mode ◽  
Signal To Noise Ratio ◽  
Photon Number ◽  
Higher Order ◽  
Field Amplitude ◽  
Fourth Power ◽  
Wave Mixing ◽  
Mixing Process ◽  
Signal To Noise ◽  
Noise Ratio

We investigate theoretically the generation of squeezed states in spontaneous and stimulated six-wave mixing process quantum mechanically. It has been found that squeezing occurs in field amplitude, amplitude-squared, amplitude-cubed, and fourth power of field amplitude of fundamental mode in the process. It is found to be dependent on coupling parameter “g” (characteristics of higher-order susceptibility tensor) and phase values of the field amplitude under short-time approximation. Six-wave mixing is a process which involves absorption of three pump photons and emission of two probe photons of the same frequency and a signal photon of different frequency. It is shown that squeezing is greater in a stimulated interaction than the corresponding squeezing in spontaneous process. The degree of squeezing depends upon the photon number in first and higher orders of field amplitude. We study the statistical behaviour of quantum field in the fundamental mode and found it to be sub-Poissonian in nature. The signal-to-noise ratio has been studied in different orders. It is found that signal-to-noise ratio is higher in lower orders. This study when supplemented with experimental observations offers possibility of improving performance of many optical devices and optical communication networks.

Determination of the Best Emulsion for the Microscopy of Crystals

1981 ◽  
Vol 39 ◽  
pp. 32-33
Author(s):  
David A. Grano ◽  
Kenneth H. Downing
Keyword(s):  
Spatial Frequency ◽  
Information Transfer ◽  
Signal To Noise Ratio ◽  
Experimental Situation ◽  
Photographic Emulsion ◽  
Modulation Transfer ◽  
Signal To Noise ◽  
Frequency Space ◽  
Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

Experiments in Bright-Field Imaging with Hollow-Cone Illumination

1981 ◽  
Vol 39 ◽  
pp. 226-227
Author(s):  
W. Kunath ◽  
K. Weiss ◽  
E. Zeitler
Keyword(s):  
Signal To Noise Ratio ◽  
Carbon Support ◽  
Electronic System ◽  
Optic Axis ◽  
Hollow Cone ◽  
Signal To Noise ◽  
Bright Field ◽  
Noise Ratio ◽  
Single Field ◽  
Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

Correlation averaging of two-dimensional crystals: basic strategy and refinements

1986 ◽  
Vol 44 ◽  
pp. 136-139
Author(s):  
W. Baumeister ◽  
R. Rachel ◽  
R. Guckenberger ◽  
R. Hegerl
Keyword(s):  
Low Dose ◽  
Signal To Noise Ratio ◽  
Real Space ◽  
Fourier Domain ◽  
Two Dimensional ◽  
Signal To Noise ◽  
Unit Cells ◽  
Lateral Displacements ◽  
Established Technique ◽  
Crystalline Array

IntroductionCorrelation averaging (CAV) is meanwhile an established technique in image processing of two-dimensional crystals /1,2/. The basic idea is to detect the real positions of unit cells in a crystalline array by means of correlation functions and to average them by real space superposition of the aligned motifs. The signal-to-noise ratio improves in proportion to the number of motifs included in the average. Unlike filtering in the Fourier domain, CAV corrects for lateral displacements of the unit cells; thus it avoids the loss of resolution entailed by these distortions in the conventional approach. Here we report on some variants of the method, aimed at retrieving a maximum of information from images with very low signal-to-noise ratios (low dose microscopy of unstained or lightly stained specimens) while keeping the procedure economical.

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