Spatial mode detection by frequency upconversion

The efficient creation and detection of spatial modes of light has become topical of late, driven by the need to increase photon-bit-rates in classical and quantum communications. Such mode creation/detection is traditionally achieved with tools based on linear optics. Here we put forward a new spatial mode detection technique based on the nonlinear optical process of sum-frequency generation. We outline the concept theoretically and demonstrate it experimentally with intense laser beams carrying orbital angular momentum and Hermite-Gaussian modes. Finally, we show that the method can be used to transfer an image from the infrared band to the visible, which implies the efficient conversion of many spatial modes.Comment: Published version, 4 pages, 5 figure

Bichromatic Local Oscillator for Detection of Two-Mode Squeezed States of Light

We present a new technique for the detection of two-mode squeezed states of light that allows for a simple characterization of these quantum states. The usual detection scheme, based on heterodyne measurements, requires the use of a local oscillator with a frequency equal to the mean of the frequencies of the two modes of the squeezed field. As a result, unless the two modes are close in frequency, a high-frequency shot-noise-limited detection system is needed. We propose the use of a bichromatic field as the local oscillator in the heterodyne measurements. By the proper selection of the frequencies of the bichromatic field, it is possible to arbitrarily select the frequency around which the squeezing information is located, thus making it possible to use a low-bandwidth detection system and to move away from any excess noise present in the system.Comment: 11 pages, 3 figure

Detection of variable frequency signals using a fast chirp transform

The detection of signals with varying frequency is important in many areas of physics and astrophysics. The current work was motivated by a desire to detect gravitational waves from the binary inspiral of neutron stars and black holes, a topic of significant interest for the new generation of interferometric gravitational wave detectors such as LIGO. However, this work has significant generality beyond gravitational wave signal detection. We define a Fast Chirp Transform (FCT) analogous to the Fast Fourier Transform (FFT). Use of the FCT provides a simple and powerful formalism for detection of signals with variable frequency just as Fourier transform techniques provide a formalism for the detection of signals of constant frequency. In particular, use of the FCT can alleviate the requirement of generating complicated families of filter functions typically required in the conventional matched filtering process. We briefly discuss the application of the FCT to several signal detection problems of current interest

A temporally-constrained convolutive probabilistic model for pitch detection

A method for pitch detection which models the temporal evolution of musical sounds is presented in this paper. The proposed model is based on shift-invariant probabilistic latent component analysis, constrained by a hidden Markov model. The time-frequency representation of a produced musical note can be expressed by the model as a temporal sequence of spectral templates which can also be shifted over log-frequency. Thus, this approach can be effectively used for pitch detection in music signals that contain amplitude and frequency modulations. Experiments were performed using extracted sequences of spectral templates on monophonic music excerpts, where the proposed model outperforms a non-temporally constrained convolutive model for pitch detection. Finally, future directions are given for multipitch extensions of the proposed model

Data Detection and Code Channel Allocation for Frequency-Domain Spread ACO-OFDM Systems Over Indoor Diffuse Wireless Channels

Future optical wireless communication systems promise to provide high-speed data transmission in indoor diffuse environments. This paper considers frequency-domain spread asymmetrically clipped optical orthogonal frequency-division multiplexing (ACOOFDM) systems in indoor diffuse channels and aims to develop efficient data detection and code channel allocation schemes. By exploiting the frequency-domain spread concept, a linear multi-code detection scheme is proposed to maximize the signal to interference plus noise ratio (SINR) at the receiver. The achieved SINR and bit error ratio (BER) performance are analyzed. A computationally efficient code channel allocation algorithm is proposed to improve the BER performance of the frequency-domain spread ACO-OFDM system. Numerical results show that the frequency-domain spread ACO-OFDM system outperforms conventional ACO-OFDM systems in indoor diffuse channels. Moreover, the proposed linear multi-code detection and code channel allocation algorithm can improve the performance of optical peak-to-average power ratio (PAPR

Detection of cochlear hearing loss applying wavelet packets and support vector machines

The aim of this paper is to evaluate the application of the wavelet packet transform (WP) and support vector machines (SVM) to transient evoked otoacoustic emissions (TEOAE) in order to achieve a detection of frequency-specific hearing loss. We introduce a system to determine detection rates between groups of persons with normal hearing, high frequency hearing loss, and pantonal hearing loss. The validity and use of our approach is verified on a different patient group

Homo economicus in visual search

How do reward outcomes affect early visual performance? Previous studies found a suboptimal influence, but they ignored the non-linearity in how subjects perceived the reward outcomes. In contrast, we find that when the non-linearity is accounted for, humans behave optimally and maximize expected reward. Our subjects were asked to detect the presence of a familiar target object in a cluttered scene. They were rewarded according to their performance. We systematically varied the target frequency and the reward/penalty policy for detecting/missing the targets. We find that 1) decreasing the target frequency will decrease the detection rates, in accordance with the literature. 2) Contrary to previous studies, increasing the target detection rewards will compensate for target rarity and restore detection performance. 3) A quantitative model based on reward maximization accurately predicts human detection behavior in all target frequency and reward conditions; thus, reward schemes can be designed to obtain desired detection rates for rare targets. 4) Subjects quickly learn the optimal decision strategy; we propose a neurally plausible model that exhibits the same properties. Potential applications include designing reward schemes to improve detection of life-critical, rare targets (e.g., cancers in medical images)