Quantum generative adversarial learning in photonics.

Quantum generative adversarial networks (QGANs), an intersection of quantum computing and machine learning, have attracted widespread attention due to their potential advantages over classical analogs. However, in the current era of noisy intermediate-scale quantum (NISQ) computing, it is essential to investigate whether QGANs can perform learning tasks on near-term quantum devices usually affected by noise and even defects. In this Letter, using a programmable silicon quantum photonic chip, we experimentally demonstrate the QGAN model in photonics for the first time to our knowledge and investigate the effects of noise and defects on its performance.

Experimental quantum natural gradient optimization in photonics.

Variational quantum algorithms (VQAs) combining the advantages of parameterized quantum circuits and classical optimizers, promise practical quantum applications in the noisy intermediate-scale quantum era. The performance of VQAs heavily depends on the optimization method. Compared with gradient-free and ordinary gradient descent methods, the quantum natural gradient (QNG), which mirrors the geometric structure of the parameter space, can achieve faster convergence and avoid local minima more easily, thereby reducing the cost of circuit executions.

Variational Quantum Process Tomography of Non-Unitaries.

Quantum process tomography is a fundamental and critical benchmarking and certification tool that is capable of fully characterizing an unknown quantum process. Standard quantum process tomography suffers from an exponentially scaling number of measurements and complicated data post-processing due to the curse of dimensionality. On the other hand, non-unitary operators are more realistic cases.

Variational Entanglement-Assisted Quantum Process Tomography with Arbitrary Ancillary Qubits.

Quantum process tomography is a pivotal technique in fully characterizing quantum dynamics. However, exponential scaling of the Hilbert space with the increasing system size extremely restrains its experimental implementations. Here, we put forward a more efficient, flexible, and error-mitigated method: variational entanglement-assisted quantum process tomography with arbitrary ancillary qubits.

Continuous-time quantum walk based centrality testing on weighted graphs.

Centrality measure is an essential tool in network analysis and widely used in the domain of computer science, biology and sociology. Taking advantage of the speedup offered by quantum computation, various quantum centrality measures have been proposed. However, few work of quantum centrality involves weighted graphs, while the weight of edges should be considered in certain real-world networks.

Optimization of quantum light sources and four-wave mixing based on a reconfigurable silicon ring resonator.

Being a key component on a photonic chip, the microring usually specializes in a certain nonlinear optical process and can not simultaneously meet different working conditions for different processes. Here, we theoretically and experimentally investigate a reconfigurable silicon microring resonator to act as a optimization strategy for both classical four-wave mixing and quantum light sources. Experimental results show that the four-wave mixing efficiency with continuous wave and pulsed pump can be both optimized to a high value well matching numerical analysis.

Implementing graph-theoretic quantum algorithms on a silicon photonic quantum walk processor.

Applications of quantum walks can depend on the number, exchange symmetry and indistinguishability of the particles involved, and the underlying graph structures where they move. Here, we show that silicon photonics, by exploiting an entanglement-driven scheme, can realize quantum walks with full control over all these properties in one device. The device we realize implements entangled two-photon quantum walks on any five-vertex graph, with continuously tunable particle exchange symmetry and indistinguishability.

Reconfigurable multiphoton entangled states based on quantum photonic chips.

Multipartite entanglement is one of the most prominent features of quantum mechanics and is the key ingredient in quantum information processing. Seeking for an advantageous way to generate it is of great value. Here we propose two different schemes to prepare multiphoton entangled states on a quantum photonic chip that are both based on the theory of entanglement on the graph.

General-Purpose Quantum Circuit Simulator with Projected Entangled-Pair States and the Quantum Supremacy Frontier.

Recent advances on quantum computing hardware have pushed quantum computing to the verge of quantum supremacy. Here, we bring together many-body quantum physics and quantum computing by using a method for strongly interacting two-dimensional systems, the projected entangled-pair states, to realize an effective general-purpose simulator of quantum algorithms. The classical computing complexity of this simulator is directly related to the entanglement generation of the underlying quantum circuit rather than the number of qubits or gate operations.

[Effects of different application rates of humic acid compound fertilizer on pepper and its mechanism of anti-senility and incremental yield].

The effects of different application rates of humic acid compound fertilizer (HA) on the yield and physiological characteristics of pepper (Capsicum frutescens L.) were studied in this paper. The results showed that different application rates of (HA) could affect the physiological activities and yield of pepper.