Quantum state transfer via the ferromagnetic chain in a spatially modulated field

We show that a perfect quantum state transmission can be realized through a spin chain possessing a commensurate structure of energy spectrum, which is matched with the corresponding parity. As an exposition of the mirror inversion symmetry discovered by Albanese et. al (quant-ph/0405029), the parity matched the commensurability of energy spectra help us to present the novel pre-engineered spin systems for quantum information transmission. Based on the these theoretical analysis, we propose a protocol of near-perfect quantum state transfer by using a ferromagnetic Heisenberg chain with uniform coupling constant, but an external parabolic magnetic field. The numerical results shows that the initial Gaussian wave packet in this system with optimal field distribution can be reshaped near-perfectly over a longer distance.Comment: 5 pages, 2 figure

Unbalance Compensation of a Full Scale Test Rig Designed for HTR-10GT: A Frequency-Domain Approach Based on Iterative Learning Control

Unbalance vibrations are crucial problems in heavy rotational machinery, especially for the systems with high operation speed, like turbine machinery. For the program of 10 MW High Temperature gas-cooled Reactor with direct Gas-Turbine cycle (HTR-10GT), the rated operation speed of the turbine system is 15000 RPM which is beyond the second bending frequency. In that case, even a small residual mass will lead to large unbalance vibrations. Thus, it is of great significance to study balancing methods for the system. As the turbine rotor is designed to be suspended by active magnetic bearings (AMBs), unbalance compensation could be achieved by adequate control strategies. In the paper, unbalance compensation for the Multi-Input and Multi-Output (MIMO) active magnetic bearing (AMB) system using frequency-domain iterative learning control (ILC) is analyzed. Based on the analysis, an ILC controller for unbalance compensation of the full scale test rig, which is designed for the rotor and AMBs in HTR-10GT, is designed. Simulation results are reported which show the efficiency of the ILC controller for attenuating the unbalance vibration of the full scale test rig. This research can offer valuable design criterion for unbalance compensation of the turbine machinery in HTR-10GT

Quantum state transmission via a spin ladder as a robust data bus

We explore the physical mechanism to coherently transfer the quantum information of spin by connecting two spins to an isotropic antiferromagnetic spin ladder system as data bus. Due to a large spin gap existing in such a perfect medium, the effective Hamiltonian of the two connected spins can be archived as that of Heisenberg type, which possesses a ground state with maximal entanglement. We show that the effective coupling strength is inversely proportional to the distance of the two spins and thus the quantum information can be transferred between the two spins separated by a longer distance, i.e. the characteristic time of quantum state transferring linearly depends on the distance.Comment: 7 pages, 5 figures, 1 tabl

Searching for Product-Market Fit with Externally Developed Components: Effects on Time to Product-Market Fit

Nascent digital start-ups that leverage digital technology (DT) could use externally developed components (EDCs) to search for DT features needed for product-market fit (PMF). Drawing on the organizational search literature, we investigate the relationship between nascent digital start-ups\u27 search breadth and search depth (in terms of EDCs use) on their time to achieve PMF (proxied by the receipt of Series A funding). We employ a survival analysis using data on startups and their EDC use from Crunchbase and LinkedIn. Our results reveal that higher search breadth reduces the time to PMF, whereas higher search depth increases it. Higher levels of interdependency between the DT and nascent digital start-ups’ business strengthen search breadth’s time reduction effect. Our findings contribute to the literature on digital entrepreneurship and organizational search and offer suggestions for how nascent digital start-ups should develop their DT in the early years

(2E,6E)-2,6-Difurfurylidenecyclo­hexa­none

The complete mol­ecule of the title compound, C16H14O3, is generated by crystallographic mirror symmetry, with two C atoms and one O atom lying on the mirror plane. The mol­ecule adopts an E configuration about the C=C bond and the dihedral angle between the furan rings is 16.1 (2)°

On the Robustness, Generalization, and Forgetting of Shape-Texture Debiased Continual Learning

Tremendous progress has been made in continual learning to maintain good performance on old tasks when learning new tasks by tackling the catastrophic forgetting problem of neural networks. This paper advances continual learning by further considering its out-of-distribution robustness, in response to the vulnerability of continually trained models to distribution shifts (e.g., due to data corruptions and domain shifts) in inference. To this end, we propose shape-texture debiased continual learning. The key idea is to learn generalizable and robust representations for each task with shape-texture debiased training. In order to transform standard continual learning to shape-texture debiased continual learning, we propose shape-texture debiased data generation and online shape-texture debiased self-distillation. Experiments on six datasets demonstrate the benefits of our approach in improving generalization and robustness, as well as reducing forgetting. Our analysis on the flatness of the loss landscape explains the advantages. Moreover, our approach can be easily combined with new advanced architectures such as vision transformer, and applied to more challenging scenarios such as exemplar-free continual learning