The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
T Poutanen - One of the best experts on this subject based on the ideXlab platform.
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Residual Noise covariance for planck low resolution data analysis
Astronomy and Astrophysics, 2010Co-Authors: R Keskitalo, M Ashdown, P Cabella, T S Kisner, T PoutanenAbstract:Aims. We develop and validate tools for estimating Residual Noise covariance in Planck frequency maps, we also quantify signal error effects and compare different techniques to produce low-resolution maps. Methods. We derived analytical estimates of covariance of the Residual Noise contained in low-resolution maps produced using a number of mapmaking approaches. We tested these analytical predictions using both Monte Carlo simulations and by applying them to angular power spectrum estimation. We used simulations to quantify the level of signal errors incurred in the different resolution downgrading schemes considered in this work. Results. We find excellent agreement between the optimal Residual Noise covariance matrices and Monte Carlo Noise maps. For destriping mapmakers, the extent of agreement is dictated by the knee frequency of the correlated Noise component and the chosen baseline offset length. Signal striping is shown to be insignificant when properly dealt with. In map resolution downgrading, we find that a carefully selected window function is required to reduce aliasing to the subpercent level at multipoles, �> 2Nside ,w hereNside is the HEALPix resolution parameter. We show that, for a polarization measurement, reliable characterization of the Residual Noise is required to draw reliable constraints on large-scale anisotropy. Conclusions. Methods presented and tested in this paper allow for production of low-resolution maps with both controlled sky signal error level and a reliable estimate of covariance of the Residual Noise. We have also presented a method for smoothing the Residual Noise covariance matrices to describe the Noise correlations in smoothed, bandwidth-limited maps.
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Residual Noise covariance for planck low resolution data analysis
arXiv: Cosmology and Nongalactic Astrophysics, 2009Co-Authors: R Keskitalo, M Ashdown, P Cabella, T S Kisner, T PoutanenAbstract:Aims: Develop and validate tools to estimate Residual Noise covariance in Planck frequency maps. Quantify signal error effects and compare different techniques to produce low-resolution maps. Methods: We derive analytical estimates of covariance of the Residual Noise contained in low-resolution maps produced using a number of map-making approaches. We test these analytical predictions using Monte Carlo simulations and their impact on angular power spectrum estimation. We use simulations to quantify the level of signal errors incurred in different resolution downgrading schemes considered in this work. Results: We find an excellent agreement between the optimal Residual Noise covariance matrices and Monte Carlo Noise maps. For destriping map-makers, the extent of agreement is dictated by the knee frequency of the correlated Noise component and the chosen baseline offset length. The significance of signal striping is shown to be insignificant when properly dealt with. In map resolution downgrading, we find that a carefully selected window function is required to reduce aliasing to the sub-percent level at multipoles, ell > 2Nside, where Nside is the HEALPix resolution parameter. We show that sufficient characterization of the Residual Noise is unavoidable if one is to draw reliable contraints on large scale anisotropy. Conclusions: We have described how to compute the low-resolution maps, with a controlled sky signal level, and a reliable estimate of covariance of the Residual Noise. We have also presented a method to smooth the Residual Noise covariance matrices to describe the Noise correlations in smoothed, bandwidth limited maps.
R Keskitalo - One of the best experts on this subject based on the ideXlab platform.
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Residual Noise covariance for planck low resolution data analysis
Astronomy and Astrophysics, 2010Co-Authors: R Keskitalo, M Ashdown, P Cabella, T S Kisner, T PoutanenAbstract:Aims. We develop and validate tools for estimating Residual Noise covariance in Planck frequency maps, we also quantify signal error effects and compare different techniques to produce low-resolution maps. Methods. We derived analytical estimates of covariance of the Residual Noise contained in low-resolution maps produced using a number of mapmaking approaches. We tested these analytical predictions using both Monte Carlo simulations and by applying them to angular power spectrum estimation. We used simulations to quantify the level of signal errors incurred in the different resolution downgrading schemes considered in this work. Results. We find excellent agreement between the optimal Residual Noise covariance matrices and Monte Carlo Noise maps. For destriping mapmakers, the extent of agreement is dictated by the knee frequency of the correlated Noise component and the chosen baseline offset length. Signal striping is shown to be insignificant when properly dealt with. In map resolution downgrading, we find that a carefully selected window function is required to reduce aliasing to the subpercent level at multipoles, �> 2Nside ,w hereNside is the HEALPix resolution parameter. We show that, for a polarization measurement, reliable characterization of the Residual Noise is required to draw reliable constraints on large-scale anisotropy. Conclusions. Methods presented and tested in this paper allow for production of low-resolution maps with both controlled sky signal error level and a reliable estimate of covariance of the Residual Noise. We have also presented a method for smoothing the Residual Noise covariance matrices to describe the Noise correlations in smoothed, bandwidth-limited maps.
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Residual Noise covariance for planck low resolution data analysis
arXiv: Cosmology and Nongalactic Astrophysics, 2009Co-Authors: R Keskitalo, M Ashdown, P Cabella, T S Kisner, T PoutanenAbstract:Aims: Develop and validate tools to estimate Residual Noise covariance in Planck frequency maps. Quantify signal error effects and compare different techniques to produce low-resolution maps. Methods: We derive analytical estimates of covariance of the Residual Noise contained in low-resolution maps produced using a number of map-making approaches. We test these analytical predictions using Monte Carlo simulations and their impact on angular power spectrum estimation. We use simulations to quantify the level of signal errors incurred in different resolution downgrading schemes considered in this work. Results: We find an excellent agreement between the optimal Residual Noise covariance matrices and Monte Carlo Noise maps. For destriping map-makers, the extent of agreement is dictated by the knee frequency of the correlated Noise component and the chosen baseline offset length. The significance of signal striping is shown to be insignificant when properly dealt with. In map resolution downgrading, we find that a carefully selected window function is required to reduce aliasing to the sub-percent level at multipoles, ell > 2Nside, where Nside is the HEALPix resolution parameter. We show that sufficient characterization of the Residual Noise is unavoidable if one is to draw reliable contraints on large scale anisotropy. Conclusions: We have described how to compute the low-resolution maps, with a controlled sky signal level, and a reliable estimate of covariance of the Residual Noise. We have also presented a method to smooth the Residual Noise covariance matrices to describe the Noise correlations in smoothed, bandwidth limited maps.
Scott A Diddams - One of the best experts on this subject based on the ideXlab platform.
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photonic microwave generation with high power photodiodes
Optics Letters, 2013Co-Authors: Tara M Fortier, Jennifer Taylor, Franklyn Quinlan, Archita Hati, Craig W Nelson, J C Campbell, Scott A DiddamsAbstract:We utilized and characterized high-power, high-linearity modified unitraveling carrier (MUTC) photodiodes for low-phase-Noise photonic microwave generation based on optical frequency division (OFD). When illuminated with picosecond pulses from a repetition-rate-multiplied gigahertz Ti:sapphire modelocked laser, the photodiodes can achieve a 10 GHz signal power of +14 dBm. Using these diodes, we generated a 10 GHz microwave tone with less than 500 attoseconds absolute integrated timing jitter (1 Hz–10 MHz) and a phase Noise floor of −177 dBc/Hz.We also characterized the electrical response, amplitude-to-phase conversion, saturation, and Residual Noise of the MUTC photodiodes.
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photonic microwave generation with high power photodiodes
arXiv: Optics, 2013Co-Authors: Tara M Fortier, Jennifer Taylor, Franklyn Quinlan, Archita Hati, Craig W Nelson, J C Campbell, Scott A DiddamsAbstract:We utilize and characterize high-power, high-linearity modified uni-traveling carrier (MUTC) photodiodes for low-phase-Noise photonic microwave generation based on optical frequency division. When illuminated with picosecond pulses from a repetition-rate-multiplied gigahertz Ti:sapphire modelocked laser, the photodiodes can achieve 10 GHz signal power of +14 dBm. Using these diodes, a 10 GHz microwave tone is generated with less than 500 attoseconds absolute integrated timing jitter (1 Hz-10 MHz) and a phase Noise floor of -177 dBc/Hz. We also characterize the electrical response, amplitude-to-phase conversion, saturation and Residual Noise of the MUTC photodiodes.
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ultralow phase Noise microwave generation with an er fiber based optical frequency divider
Optics Letters, 2011Co-Authors: F Quinlan, Tara M Fortier, Matthew S Kirchner, Jennifer Taylor, Michael J Thorpe, Nathan D Lemke, Andrew D Ludlow, Yanyi Jiang, Scott A DiddamsAbstract:We present an optical frequency divider based on a 200 MHz repetition rate Er:fiber mode-locked laser that, when locked to a stable optical frequency reference, generates microwave signals with absolute phase Noise that is equal to or better than cryogenic microwave oscillators. At 1 Hz offset from a 10 GHz carrier, the phase Noise is below −100 dBc/Hz, limited by the optical reference. For offset frequencies >10 kHz, the phase Noise is shot Noise limited at −145 dBc/Hz. An analysis of the contribution of the Residual Noise from the Er:fiber optical frequency divider is also presented.
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impact of dispersion on amplitude and frequency Noise in a yb fiber laser comb
Optics Letters, 2011Co-Authors: Lora Nugentglandorf, Todd A Johnson, Yohei Kobayashi, Scott A DiddamsAbstract:We describe a Yb-fiber-based laser comb, with a focus on the relationship between the net-cavity dispersion and frequency Noise on the comb. While tuning the net-cavity dispersion from anomalous to normal, we measure the relative intensity Noise, offset frequency (fCEO) linewidth, and the resulting frequency Noise spectrum on the fCEO. We find that the laser operating at zero net-cavity dispersion has many advantages, including an approximately 100× reduction in free-running fCEO linewidth and frequency Noise power spectral density when compared to the normal-dispersion regime. At the zero-dispersion point, we demonstrate a phase-locked fCEO beat with low Residual Noise.
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the impact of dispersion on amplitude and frequency Noise in a yb fiber laser comb
arXiv: Optics, 2011Co-Authors: Lora Nugentglandorf, Todd A Johnson, Yohei Kobayashi, Scott A DiddamsAbstract:We describe a Yb-fiber based laser comb, with a focus on the relationship between net-cavity dispersion and the frequency Noise on the comb. While tuning the net cavity dispersion from anomalous to normal, we measure the amplitude Noise (RIN), offset frequency (f_CEO) linewidth, and the resulting frequency Noise spectrum on f_CEO. We find that the laser operating at zero net-cavity dispersion has many advantages, including an approximately 100x reduction in free-running f_CEO linewidth and frequency Noise power spectral density between laser operation at normal and zero dispersion. In this latter regime, we demonstrate a phase-locked f_CEO beat with low Residual Noise.
P Cabella - One of the best experts on this subject based on the ideXlab platform.
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Residual Noise covariance for planck low resolution data analysis
Astronomy and Astrophysics, 2010Co-Authors: R Keskitalo, M Ashdown, P Cabella, T S Kisner, T PoutanenAbstract:Aims. We develop and validate tools for estimating Residual Noise covariance in Planck frequency maps, we also quantify signal error effects and compare different techniques to produce low-resolution maps. Methods. We derived analytical estimates of covariance of the Residual Noise contained in low-resolution maps produced using a number of mapmaking approaches. We tested these analytical predictions using both Monte Carlo simulations and by applying them to angular power spectrum estimation. We used simulations to quantify the level of signal errors incurred in the different resolution downgrading schemes considered in this work. Results. We find excellent agreement between the optimal Residual Noise covariance matrices and Monte Carlo Noise maps. For destriping mapmakers, the extent of agreement is dictated by the knee frequency of the correlated Noise component and the chosen baseline offset length. Signal striping is shown to be insignificant when properly dealt with. In map resolution downgrading, we find that a carefully selected window function is required to reduce aliasing to the subpercent level at multipoles, �> 2Nside ,w hereNside is the HEALPix resolution parameter. We show that, for a polarization measurement, reliable characterization of the Residual Noise is required to draw reliable constraints on large-scale anisotropy. Conclusions. Methods presented and tested in this paper allow for production of low-resolution maps with both controlled sky signal error level and a reliable estimate of covariance of the Residual Noise. We have also presented a method for smoothing the Residual Noise covariance matrices to describe the Noise correlations in smoothed, bandwidth-limited maps.
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Residual Noise covariance for planck low resolution data analysis
arXiv: Cosmology and Nongalactic Astrophysics, 2009Co-Authors: R Keskitalo, M Ashdown, P Cabella, T S Kisner, T PoutanenAbstract:Aims: Develop and validate tools to estimate Residual Noise covariance in Planck frequency maps. Quantify signal error effects and compare different techniques to produce low-resolution maps. Methods: We derive analytical estimates of covariance of the Residual Noise contained in low-resolution maps produced using a number of map-making approaches. We test these analytical predictions using Monte Carlo simulations and their impact on angular power spectrum estimation. We use simulations to quantify the level of signal errors incurred in different resolution downgrading schemes considered in this work. Results: We find an excellent agreement between the optimal Residual Noise covariance matrices and Monte Carlo Noise maps. For destriping map-makers, the extent of agreement is dictated by the knee frequency of the correlated Noise component and the chosen baseline offset length. The significance of signal striping is shown to be insignificant when properly dealt with. In map resolution downgrading, we find that a carefully selected window function is required to reduce aliasing to the sub-percent level at multipoles, ell > 2Nside, where Nside is the HEALPix resolution parameter. We show that sufficient characterization of the Residual Noise is unavoidable if one is to draw reliable contraints on large scale anisotropy. Conclusions: We have described how to compute the low-resolution maps, with a controlled sky signal level, and a reliable estimate of covariance of the Residual Noise. We have also presented a method to smooth the Residual Noise covariance matrices to describe the Noise correlations in smoothed, bandwidth limited maps.
Benoit Champagne - One of the best experts on this subject based on the ideXlab platform.
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incorporating the human hearing properties in the signal subspace approach for speech enhancement
IEEE Transactions on Speech and Audio Processing, 2003Co-Authors: F Jabloun, Benoit ChampagneAbstract:The major drawback of most Noise reduction methods in speech applications is the annoying Residual Noise known as musical Noise. A potential solution to this artifact is the incorporation of a human hearing model in the suppression filter design. However, since the available models are usually developed in the frequency domain, it is not clear how they can be applied in the signal subspace approach for speech enhancement. In this paper, we present a Frequency to Eigendomain Transformation (FET) which permits to calculate a perceptually based eigenfilter. This filter yields an improved result where better shaping of the Residual Noise, from a perceptual perspective, is achieved. The proposed method can also be used with the general case of colored Noise. Spectrogram illustrations and listening test results are given to show the superiority of the proposed method over the conventional signal subspace approach.
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a perceptual signal subspace approach for speech enhancement in colored Noise
International Conference on Acoustics Speech and Signal Processing, 2002Co-Authors: F Jabloun, Benoit ChampagneAbstract:The major drawback of most Noise reduction methods is what is known as musical Noise. To cope with this problem, the masking properties of the human ear were used in the spectral subtraction methods. However, no similar approach is available for the signal subspace based methods. In a previous work, we presented a frequency to eigendomain transformation which provides a way to calculate a perceptually based upper bound for the Residual Noise. This bound, when used in the signal subspace approach, yields an improved result where better shaping of the Residual Noise is achieved. In this paper, we further improve this method and provide an easy way to generalize it to the colored Noise case. Listening tests results are given to show the superiority of the proposed method.
