Lifting problem for universal quadratic forms over totally real cubic number fields

Lifting problem for universal quadratic forms asks for totally real number fields $K$ that admit a positive definite quadratic form with coefficients in $\mathbb{Z}$ that is universal over the ring of integers of $K$. In this paper, we show that $K=\mathbb{Q}(\zeta_7+\zeta_7^{-1})$ is the only such totally real cubic field. Moreover, we show that there is no such biquadratic field.Comment: 12 page

Differentiable Artificial Reverberation

Artificial reverberation (AR) models play a central role in various audio applications. Therefore, estimating the AR model parameters (ARPs) of a target reverberation is a crucial task. Although a few recent deep-learning-based approaches have shown promising performance, their non-end-to-end training scheme prevents them from fully exploiting the potential of deep neural networks. This motivates to introduce differentiable artificial reverberation (DAR) models which allows loss gradients to be back-propagated end-to-end. However, implementing the AR models with their difference equations "as is" in the deep-learning framework severely bottlenecks the training speed when executed with a parallel processor like GPU due to their infinite impulse response (IIR) components. We tackle this problem by replacing the IIR filters with finite impulse response (FIR) approximations with the frequency-sampling method (FSM). Using the FSM, we implement three DAR models -- differentiable Filtered Velvet Noise (FVN), Advanced Filtered Velvet Noise (AFVN), and Feedback Delay Network (FDN). For each AR model, we train its ARP estimation networks for analysis-synthesis (RIR-to-ARP) and blind estimation (reverberant-speech-to-ARP) task in an end-to-end manner with its DAR model counterpart. Experiment results show that the proposed method achieves consistent performance improvement over the non-end-to-end approaches in both objective metrics and subjective listening test results.Comment: Manuscript submitted to TASL

Long distance fiber Bragg grating strain sensor interrogation using a high speed Raman-based Fourier domain mode-locked fiber laser with recycled residual Raman pump

We propose a novel fiber Bragg grating (FBG) sensor interrogation using a Raman-based Fourier-domain mode locking (FDML) fiber laser for a high speed and long distance measurement. A residual Raman pump after the generation of the Raman-based FDML fiber laser is recycled for secondary signal amplification in a 2-m erbium-doped fiber (EDF) to further enhance the output power. The chromatic dispersion is precisely controlled to suppress the phase noise in the FDML laser cavity, resulting in the improvement of an R-number of 1.43 mm/dB. After recycling residual pump, we achieve the 40-km round trip transmission of the sensing probe signal with a high scan rate of 30.8 kHz. With 205-mW residual pump power, the bandwidth and the maximum gain are measured to be more than 50 nm, 10.3 dB at 1550 nm, respectively. The sensitivity of the proposed Raman-based FDML fiber laser to strain is also measured, which are 0.81 pm/μstrain in the spectral domain and 0.19 ns/μstrain in the time domain, respectively

High-efficiency Bidirectional Buck-Boost Converter for Residential Energy Storage System

This paper proposes a bidirectional dc-dc converter for residential micro-grid applications. The proposed converter can operate over an input voltage range that overlaps the output voltage range. This converter uses two snubber capacitors to reduce the switch turn-off losses, a dc-blocking capacitor to reduce the input/output filter size, and a 1:1 transformer to reduce core loss. The windings of the transformer are connected in parallel and in reverse-coupled configuration to suppress magnetic flux swing in the core. Zero-voltage turn-on of the switch is achieved by operating the converter in discontinuous conduction mode. The experimental converter was designed to operate at a switching frequency of 40-210 kHz, an input voltage of 48 V, an output voltage of 36-60 V, and an output power of 50-500 W. The power conversion efficiency for boost conversion to 60 V was >= 98.3% in the entire power range. The efficiency for buck conversion to 36 V was >= 98.4% in the entire power range. The output voltage ripple at full load was <3.59 V-p.p for boost conversion (60 V) and 1.35 V-p.p for buck conversion (36 V) with the reduced input/output filter. The experimental results indicate that the proposed converter is well-suited to smart-grid energy storage systems that require high efficiency, small size, and overlapping input and output voltage ranges.11Ysciescopu