Recently, lithographic quantum dots in strained-Ge/SiGe have become a promising candidate for quantum computation, with a remarkably quick progression from demonstration of a quantum dot to qubit logic demonstrations. Here we present a measurement of the out-of-plane g-factor for single-hole quantum dots in this material.As this is a single-hole measurement, this is the first experimental result that avoids the strong orbital effects present in the out-of-plane configuration. In addition to verifying the expected g-factor anisotropy between in-plane and out-of-plane magnetic (B)-fields, variations in the g-factor dependent on the occupation of the quantum dot are observed. These results are in good agreement with calculations of the g-factor using the heavy-and light-hole spaces of the Luttinger Hamiltonian, especially the first two holes, showing a strong spin-orbit coupling and suggesting dramatic g-factor tunability through both the B-field and the charge state.
There has been a longstanding tradeoff in evaluating the quality or fidelity of sound recordings: subjective listening tests are time consuming and expensive, but objective measures often fail to capture the nuances of human perception. The research presented here seeks to address this problem by investigating the use of machine learning to evaluate the fidelity of acoustic simulations. To begin, we created a dataset of recordings representing varying levels of audio fidelity. Participants listened to each of the recordings and subjectively classified the perceived fidelity. Various audio features were extracted from the recordings, including several psychoacoustic sound quality metrics and other features commonly used in speech recognition/assessment and music genre classification. These features were input to various machine learning algorithms to test which best modeled the human classifications. A logistic regression model was initially determined to be the most advantageous, dependent on using binary classification. Introducing a reference sound, and calculating each feature relative to the reference, significantly improved accuracy.
A hybrid method for creating a unified broadband acoustic response from separate low-frequency and high-frequency simulation responses is proposed. This hybrid method is ideal for creating simple auralizable approximations of complex acoustic systems. The process consists of four steps: 1) creating separate low- frequency and high-frequency responses of the system of interest, 2) interpolating between the two responses to get a single broadband magnitude response, 3) introducing amplitude modulation to the high-frequency portion of the response, and 4) calculating approximate phase information. Once the appropriate frequency response is obtained, an inverse fast Fourier transform is applied to obtain an impulse response. An experimental setup of an acoustic cavity with one flexible wall is used to validate the hybrid method. The simulated and measured impulse responses are both convolved with various excitation signals, so the validity of the approach could be assessed by listening. Listening tests confirm that the method is able to produce realistic auralizations. The degree of realism is subject to a few limitations, such as pitch differences and dependence on the presence of transients in the excitation signal, but these limitations are incidental and only indirectly related to the proposed method.
Three-dimensional force plates are important tools for biomechanics discovery and sports performance practice. However, currently, available 3D force plates lack portability and are often cost-prohibitive. To address this, a recently discovered 3D force sensor technology was used in the fabrication of a prototype force plate. Thirteen participants performed bodyweight and weighted lunges and squats on the prototype force plate and a standard 3D force plate positioned in series to compare forces measured by both force plates and validate the technology. For the lunges, there was excellent agreement between the experimental force plate and the standard force plate in the X-, Y-, and Z-axes (r = 0.950–0.999, p < 0.001). For the squats, there was excellent agreement between the force plates in the Z-axis (r = 0.996, p < 0.001). Across axes and movements, root mean square error (RMSE) ranged from 1.17% to 5.36% between force plates. Although the current prototype force plate is limited in sampling rate, the low RMSEs and extremely high agreement in peak forces provide confidence the novel force sensors have utility in constructing cost-effective and versatile use-case 3D force plates.
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