Protecting Two-Qubit Quantum States by π\pi-Phase Pulses

We study the state decay of two qubits interacted with a common harmonic oscillator reservoir. There are both decoherence error and the error caused by the amplitude change of the superradiant state. We show that frequent $\pi$-phase pulses can eliminate both typpes of errors therefore protect a two-qubit odd-parity state more effectively than the frequent measurement method. This shows that the the methods using dynamical decoupling and the quantum Zeno effects actually can give rather {\em different} results when the operation frequency is finite

Thermal States as Universal Resources for Quantum Computation with Always-On Interactions

Measurement-based quantum computation utilizes an initial entangled resource state and proceeds with subsequent single-qubit measurements. It is implicitly assumed that the interactions between qubits can be switched off so that the dynamics of the measured qubits do not affect the computation. By proposing a model spin Hamiltonian, we demonstrate that measurement-based quantum computation can be achieved on a thermal state with always-on interactions. Moreover, computational errors induced by thermal fluctuations can be corrected and thus the computation can be executed fault tolerantly if the temperature is below a threshold value

Resource-efficient high-dimensional subspace teleportation with a quantum autoencoder.

Quantum autoencoders serve as efficient means for quantum data compression. Here, we propose and demonstrate their use to reduce resource costs for quantum teleportation of subspaces in high-dimensional systems. We use a quantum autoencoder in a compress-teleport-decompress manner and report the first demonstration with qutrits using an integrated photonic platform for future scalability. The key strategy is to compress the dimensionality of input states by erasing redundant information and recover the initial states after chip-to-chip teleportation. Unsupervised machine learning is applied to train the on-chip autoencoder, enabling the compression and teleportation of any state from a high-dimensional subspace. Unknown states are decompressed at a high fidelity (~0.971), obtaining a total teleportation fidelity of ~0.894. Subspace encodings hold great potential as they support enhanced noise robustness and increased coherence. Laying the groundwork for machine learning techniques in quantum systems, our scheme opens previously unidentified paths toward high-dimensional quantum computing and networking

Evidence-based guidelines for the pharmacological treatment of postmenopausal osteoporosis: a consensus document by the Belgian Bone Club

Several drugs are available for the management of postmenopausal osteoporosis. This may, in daily practice, confuse the clinician. This manuscript offers an evidence-based update of previous treatment guidelines, with a critical assessment of the currently available efficacy data on all new chemical entities which were granted a marketing authorization. Osteoporosis is widely recognized as a major public health concern. The availability of new therapeutic agents makes clinical decision-making in osteoporosis more complex. Nation-specific guidelines are needed to take into consideration the specificities of each and every health care environment. The present manuscript is the result of a National Consensus, based on a systematic review and a critical appraisal of the currently available literature. It offers an evidence-based update of previous treatment guidelines, with the aim of providing clinicians with an unbiased assessment of osteoporosis treatment effect

Implementation of evolutionary active force control in a 5-link biped robot

In this paper, the application of Active Force Control (AFC) incorporated with a conventional Proportional-Derivative (PD) controller to a five-link biped robot has been studied and simulated. The efficacy and robustness of the AFC strategy in suppressing external disturbances was examined on a model using Crude Approximation (CA) method. However, the task of tuning the PD controller parameters and the inertia matrix coefficient is tedious and time-consuming. Thus, an evolutionary strategy - Differential Evolution (DE) has been proposed in order to tune automatically the parameter gains in a systematic approach. The effectiveness of the proposed method is investigated, and it is found that the system is robust and stable even under influence of disturbances

On direct detection of entanglement properties of unknown states

The recent development of methods for detecting entanglement of unknown quantum state is described. In particular, the fundamental limitations due to the linearity of quantum mechanics axe discussed. Then both qualitative and quantitative methods of entanglement detection are shortly presented

Robust state transfer and rotation through a spin chain via dark passage

Quantum state transfer through a spin chain via adiabatic dark passage is proposed. This technique is robust against control field fluctuations and unwanted environmental coupling of intermediate spins. Our method can be applied to spin chains with more than three spins. We also propose single qubit rotation using this technique

Squeezing Enhances Quantum Synchronization

It is desirable to observe synchronization of quantum systems in the quantum regime, defined by the low number of excitations and a highly nonclassical steady state of the self-sustained oscillator. Several existing proposals of observing synchronization in the quantum regime suffer from the fact that the noise statistics overwhelm synchronization in this regime. Here, we resolve this issue by driving a self-sustained oscillator with a squeezing Hamiltonian instead of a harmonic drive and analyze this system in the classical and quantum regime. We demonstrate that strong entrainment is possible for small values of squeezing, and in this regime, the states are nonclassical. Furthermore, we show that the quality of synchronization measured by the FWHM of the power spectrum is enhanced with squeezing

Efficient option pricing with a unary-based photonic computing chip and generative adversarial learning

202311 bckwVersion of RecordOthersHong Kong Polytechnic University; National Research Foundation Singapore; Ministry of Education - SingaporePublishe