27 research outputs found
A duplication-free quantum neural network for universal approximation
The universality of a quantum neural network refers to its ability to
approximate arbitrary functions and is a theoretical guarantee for its
effectiveness. A non-universal neural network could fail in completing the
machine learning task. One proposal for universality is to encode the quantum
data into identical copies of a tensor product, but this will substantially
increase the system size and the circuit complexity. To address this problem,
we propose a simple design of a duplication-free quantum neural network whose
universality can be rigorously proved. Compared with other established
proposals, our model requires significantly fewer qubits and a shallower
circuit, substantially lowering the resource overhead for implementation. It is
also more robust against noise and easier to implement on a near-term device.
Simulations show that our model can solve a broad range of classical and
quantum learning problems, demonstrating its broad application potential.Comment: 15 pages, 10 figure
Narrow-linewidth 852-nm DBR-LD with self-injection lock based on high-fineness optical cavity filtering
Narrow-linewidth lasers have high spectral purity, long coherent length and
low phase noise, so they have important applications in cold atom physics,
quantum communication, quantum information processing and optical precision
measurement. We inject transmitted laser from a narrow-linewidth (15 kHz)
flat-concave Fabry-Perot (F-P) cavity made of ultra-low expansion (ULE) optical
glass into 852-nm distributed-Bragg-reflector type laser diode (DBR-LD), of
which the comprehensive linewidth of 1.67 MHz for the free running case. With
the increase of self-injection power, the laser linewidth is gradually
narrowed, and the inject-locking current range is gradually increased. The
narrowest linewidth measured by the delayed frequency-shifted self-heterodyne
(DFSSH) method is 263 Hz. Moreover, to characterize the laser phase noise, we
use a detuned F-P cavity to measure the conversion signal from laser phase
noise to intensity noise for both the free running case and self-injection lock
case. Laser phase noise for the self-injection lock case is significantly
suppressed in the analysis frequency range of 0.1-10 MHz compared to the free
running case. Especially, the phase noise is suppressed by more than 30dB at
the analysis frequency of 100 kHz.Comment: 12 pages, 5 figure
Suppression of laser beam's polarization and intensity fluctuation via a Mach-Zehnder interferometer with proper feedback
Long ground-Rydberg coherence lifetime is interesting for implementing
high-fidelity quantum logic gates, many-body physics, and other quantum
information protocols. However, the potential well formed by a conventional
far-off-resonance red-detuned optical-dipole trap that is attractive for
ground-state cold atoms is usually repulsive for Rydberg atoms, which will
result in the rapid loss of atoms and low repetition rate of the experimental
sequence. Moreover, the coherence time will be sharply shortened due to the
residual thermal motion of cold atoms. These issues can be addressed by a
one-dimensional magic lattice trap, which can form a deeper potential trap than
the traveling wave optical dipole trap when the output power is limited. In
addition, these common techniques for atomic confinement generally have certain
requirements for the polarization and intensity stability of the laser. Here,
we demonstrated a method to suppress both the polarization drift and power
fluctuation only based on the phase management of the Mach-Zehnder
interferometer for a one-dimensional magic lattice trap. With the combination
of three wave plates and the interferometer, we used the instrument to collect
data in the time domain, analyzed the fluctuation of laser intensity, and
calculated the noise power spectral density. We found that the total intensity
fluctuation comprising laser power fluctuation and polarization drift was
significantly suppressed, and the noise power spectral density after
closed-loop locking with a typical bandwidth of 1-3000 Hz was significantly
lower than that under the free running of the laser system. Typically, at 1000
Hz, the noise power spectral density after locking was about 10 dB lower than
that under the free running of a master oscillator power amplifier system.The
intensity-polarization control technique provides potential applications
Quantum architecture search via truly proximal policy optimization
Abstract Quantum Architecture Search (QAS) is a process of voluntarily designing quantum circuit architectures using intelligent algorithms. Recently, Kuo et al. (Quantum architecture search via deep reinforcement learning. arXiv preprint arXiv:2104.07715, 2021) proposed a deep reinforcement learning-based QAS (QAS-PPO) method, which used the Proximal Policy Optimization (PPO) algorithm to automatically generate the quantum circuit without any expert knowledge in physics. However, QAS-PPO can neither strictly limit the probability ratio between old and new policies nor enforce well-defined trust domain constraints, resulting in poor performance. In this paper, we present a new deep reinforcement learning-based QAS method, called Trust Region-based PPO with Rollback for QAS (QAS-TR-PPO-RB), to automatically build the quantum gates sequence from the density matrix only. Specifically, inspired by the research work of Wang, we employ an improved clipping function to implement the rollback behavior to limit the probability ratio between the new strategy and the old strategy. In addition, we use the triggering condition of the clipping based on the trust domain to optimize the policy by restricting the policy within the trust domain, which leads to guaranteed monotone improvement. Experiments on several multi-qubit circuits demonstrate that our presented method achieves better policy performance and lower algorithm running time than the original deep reinforcement learning-based QAS method
Quantum spectral clustering algorithm for unsupervised learning
Clustering is one of the most crucial problems in unsupervised learning, and
the well-known -means clustering algorithm has been shown to be
implementable on a quantum computer with a significant speedup. However, many
clustering problems cannot be solved by -means, and a powerful method called
spectral clustering is introduced to solve these problems. In this work, we
propose a circuit design to implement spectral clustering on a quantum
processor with a substantial speedup, by initializing the processor into a
maximally entangled state and encoding the data information into an
efficiently-simulatable Hamiltonian. Compared with the established quantum
-means algorithms, our method does not require a quantum random access
memory or a quantum adiabatic process. It relies on an appropriate embedding of
quantum phase estimation into Grover's search to gain the quantum speedup.
Simulations demonstrate that our method is effective in solving clustering
problems and will serve as an important supplement to quantum -means for
unsupervised learning.Comment: 7 pages, 12 figure
Narrow-Linewidth 852-nm DBR-LD with Self-Injection Lock Based on High-Finesse Optical Cavity Filtering
Narrow-linewidth lasers have a high spectral purity, long coherent length, and low phase noise, so they have important applications in atomic clocks, precision measurement, and quantum computing. We inject a transmitted laser from a narrow-linewidth (∼15 kHz) flat-concave Fabry–Perot (F-P) cavity made from ultra-low expansion (ULE) optical glass into an 852 nm distributed Bragg reflector-type laser diode (DBR-LD), of which the comprehensive linewidth is 1.67 MHz for the free running case. With an increase in the self-injection power, the laser linewidth gradually narrows, and the injection locking current range gradually increases. The narrowest linewidth measured by the delayed frequency-shifted self-heterodyne (DFSSH) method is about 365 Hz, which is about 1/4500 of the linewidth for the free running case. Moreover, to characterize the laser phase noise, we use a detuned F-P cavity to measure the conversion signal from the laser phase noise to the intensity noise for both the free running case and the self-injection lock case. The laser phase noise for the self-injection lock case is significantly suppressed in the analysis frequency range of 0.1–10 MHz compared to the free running case. In particular, the phase noise is suppressed by more than 30 dB at an analysis frequency of 100 kHz
Angle-Dependent Magic Optical Trap for the 6S1/2↔nP3/2 Rydberg Transition of Cesium Atoms
The existence of an anisotropic tensor part of atomic states with an angular momentum greater than 1/2 causes their dynamic polarizabilities to be very sensitive to the polarization direction of the laser field. Therefore, the magic wavelength of the transition between two atomic states also depends on the polarization angle between the quantized axis and the polarization vector. We perform a calculation of the magic conditions of the 6S1/2↔nP3/2 (n = 50–90) Rydberg transition of cesium atoms by introducing an auxiliary electric diople transition connected to the target Rydberg state and a low-excited state. The magic condition is determined by the intersection of dynamic polarizabilities of the 6S1/2 ground state and the nP3/2 Rydberg state. The dynamic polarizability is calculated by using the sum-over-states method. Furthermore, we analyze the dependence of magic detuning on the polarization angle for a linearly polarized trapping laser and establish the relationship between magic detuning and a principal quantum number of the Rydberg state at the magic angle. The magic optical dipole trap can confine the ground-state and Rydberg-state atoms simultaneously, and the differential light shift in the 6S1/2↔nP3/2 transition can be canceled under the magic condition. It is of great significance for the application of long-lifetime high-repetition-rate accurate manipulation of Rydberg atoms on high-fidelity entanglement and quantum logic gate operation
Narrow-linewidth 852-nm DBR-LD with self-injection lock based on high-fineness optical cavity filtering
Narrow-linewidth lasers have high spectral purity, long coherent length and low phase noise, so they have important applications in cold atom physics, quantum communication, quantum information processing and optical precision measurement. We inject transmitted laser from a narrow-linewidth (15 kHz) flat-concave Fabry-Perot (F-P) cavity made of ultra-low expansion (ULE) optical glass into 852-nm distributed-Bragg-reflector type laser diode (DBR-LD), of which the comprehensive linewidth of 1.67 MHz for the free running case. With the increase of self-injection power, the laser linewidth is gradually narrowed, and the inject-locking current range is gradually increased. The narrowest linewidth measured by the delayed frequency-shifted self-heterodyne (DFSSH) method is 263 Hz. Moreover, to characterize the laser phase noise, we use a detuned F-P cavity to measure the conversion signal from laser phase noise to intensity noise for both the free running case and self-injection lock case. Laser phase noise for the self-injection lock case is significantly suppressed in the analysis frequency range of 0.1-10 MHz compared to the free running case. Especially, the phase noise is suppressed by more than 30dB at the analysis frequency of 100 kHz
Robust resource-efficient quantum variational ansatz through evolutionary algorithm
Variational quantum algorithms (VQAs) are promising methods to demonstrate
quantum advantage on near-term devices as the required resources are divided
between a quantum simulator and a classical optimizer. As such, designing a VQA
which is resource-efficient and robust against noise is a key factor to achieve
potential advantage with the existing noisy quantum simulators. It turns out
that a fixed VQA circuit design, such as the widely-used hardware efficient
ansatz, is not necessarily robust against imperfections. In this work, we
propose a genome-length-adjustable evolutionary algorithm to design a robust
VQA circuit that is optimized over variations of both circuit ansatz and gate
parameters, without any prior assumptions on circuit structure or depth.
Remarkably, our method not only generates a noise-effect-minimized circuit with
shallow depth, but also accelerates the classical optimization by substantially
reducing the number of parameters. In this regard, the optimized circuit is far
more resource-efficient with respect to both quantum and classical resources.
As applications, based on two typical error models in VQA, we apply our method
to calculate the ground energy of the hydrogen and the water molecules as well
as the Heisenberg model. Simulations suggest that compared with conventional
hardware efficient ansatz, our circuit-structure-tunable method can generate
circuits apparently more robust against both coherent and incoherent noise, and
hence is more likely to be implemented on near-term devices.Comment: 12 pages, 10 figure