Human emotional response to steering wheel vibration in automobiles

This is the post-print (final draft post-refereeing) version of the final published paper that is available from the link below. Copyright @ 2013 Inderscience Enterprises Ltd.This study investigates what form of correlation may exist between measures of the valence and the arousal dimensions of the human emotional response to steering wheel vibration and the vibration intensity metrics obtained by means of the unweighted and the frequency weighted root mean square (rms). A laboratory experiment was performed with 30 participants who were presented 17 acceleration time histories in random order and asked to rate their emotional feelings of valence and arousal using a self-assessment manikin (SAM) scale. The results suggest a highly linear correlation between the unweighted, Wh weighted and Ws weighted vibration intensity metrics and the arousal measures of the human emotional response. The results also suggest that while vibration intensity plays a significant role in eliciting emotional feelings, there are other factors which influence the human emotional response to steering wheel vibration such as the presence of high peaks or high frequency band amplitudes

Numerical Evidence for Robustness of Environment-Assisted Quantum Transport

Recent theoretical studies show that decoherence process can enhance transport efficiency in quantum systems. This effect is known as environment-assisted quantum transport (ENAQT). The role of ENAQT in optimal quantum transport is well investigated, however, it is less known how robust ENAQT is with respect to variations in the system or its environment characteristic. Toward answering this question, we simulated excitonic energy transfer in Fenna-Matthews-Olson (FMO) photosynthetic complex. We found that ENAQT is robust with respect to many relevant parameters of environmental interactions and Frenkel-exciton Hamiltonian including reorganization energy, bath frequency cutoff, temperature, and initial excitations, dissipation rate, trapping rate, disorders, and dipole moments orientations. Our study suggests that the ENAQT phenomenon can be exploited in robust design of highly efficient quantum transport systems.Comment: arXiv admin note: substantial text overlap with arXiv:1104.481

Vanishing quantum discord is necessary and sufficient for completely positive maps

Two long standing open problems in quantum theory are to characterize the class of initial system-bath states for which quantum dynamics is equivalent to (1) a map between the initial and final system states, and (2) a completely positive (CP) map. The CP map problem is especially important, due to the widespread use of such maps in quantum information processing and open quantum systems theory. Here we settle both these questions by showing that the answer to the first is "all", with the resulting map being Hermitian, and that the answer to the second is that CP maps arise exclusively from the class of separable states with vanishing quantum discord.Comment: 4 pages, no figures. v2: Accepted for publication in Phys. Rev. Let

Robust Quantum Error Correction via Convex Optimization

We present a semidefinite program optimization approach to quantum error correction that yields codes and recovery procedures that are robust against significant variations in the noise channel. Our approach allows us to optimize the encoding, recovery, or both, and is amenable to approximations that significantly improve computational cost while retaining fidelity. We illustrate our theory numerically for optimized 5-qubit codes, using the standard [5,1,3] code as a benchmark. Our optimized encoding and recovery yields fidelities that are uniformly higher by 1-2 orders of magnitude against random unitary weight-2 errors compared to the [5,1,3] code with standard recovery. We observe similar improvement for a 4-qubit decoherence-free subspace code.Comment: 4 pages, including 3 figures. v2: new example

Bayesian bilinear neural network for predicting the mid-price dynamics in limit-order book markets

The prediction of financial markets is a challenging yet important task. In modern electronically driven markets, traditional time-series econometric methods often appear incapable of capturing the true complexity of the multilevel interactions driving the price dynamics. While recent research has established the effectiveness of traditional machine learning (ML) models in financial applications, their intrinsic inability to deal with uncertainties, which is a great concern in econometrics research and real business applications, constitutes a major drawback. Bayesian methods naturally appear as a suitable remedy conveying the predictive ability of ML methods with the probabilistically oriented practice of econometric research. By adopting a state-of-the-art second-order optimization algorithm, we train a Bayesian bilinear neural network with temporal attention, suitable for the challenging time-series task of predicting mid-price movements in ultra-high-frequency limit-order book markets. We thoroughly compare our Bayesian model with traditional ML alternatives by addressing the use of predictive distributions to analyze errors and uncertainties associated with the estimated parameters and model forecasts. Our results underline the feasibility of the Bayesian deep-learning approach and its predictive and decisional advantages in complex econometric tasks, prompting future research in this direction

Efficient measurement of quantum dynamics via compressive sensing

The resources required to characterise the dynamics of engineered quantum systems-such as quantum computers and quantum sensors-grow exponentially with system size. Here we adapt techniques from compressive sensing to exponentially reduce the experimental configurations required for quantum process tomography. Our method is applicable to dynamical processes that are known to be nearly-sparse in a certain basis and it can be implemented using only single-body preparations and measurements. We perform efficient, high-fidelity estimation of process matrices on an experiment attempting to implement a photonic two-qubit logic-gate. The data base is obtained under various decoherence strengths. We find that our technique is both accurate and noise robust, thus removing a key roadblock to the development and scaling of quantum technologies.Comment: New title and authors. A new experimental section. Significant rewrite of the theor