RESUMEN
A quantum computer attains computational advantage when outperforming the best classical computers running the best-known algorithms on well-defined tasks. No photonic machine offering programmability over all its quantum gates has demonstrated quantum computational advantage: previous machines1,2 were largely restricted to static gate sequences. Earlier photonic demonstrations were also vulnerable to spoofing3, in which classical heuristics produce samples, without direct simulation, lying closer to the ideal distribution than do samples from the quantum hardware. Here we report quantum computational advantage using Borealis, a photonic processor offering dynamic programmability on all gates implemented. We carry out Gaussian boson sampling4 (GBS) on 216 squeezed modes entangled with three-dimensional connectivity5, using a time-multiplexed and photon-number-resolving architecture. On average, it would take more than 9,000 years for the best available algorithms and supercomputers to produce, using exact methods, a single sample from the programmed distribution, whereas Borealis requires only 36 µs. This runtime advantage is over 50 million times as extreme as that reported from earlier photonic machines. Ours constitutes a very large GBS experiment, registering events with up to 219 photons and a mean photon number of 125. This work is a critical milestone on the path to a practical quantum computer, validating key technological features of photonics as a platform for this goal.
RESUMEN
We present the Python Red Pitaya Lockbox (PyRPL), an open source software package that allows the implementation of automatic digital feedback controllers for quantum optics experiments on commercially available, affordable Field-Programmable Gate Array (FPGA) boards. Our software implements the digital generation of various types of error signals, from an analog input through the application of loop filters of high complexity and real-time gain adjustment for multiple analog output signals, including different algorithms for resonance search, lock acquisition sequences, and in-loop gain optimization. Furthermore, all necessary diagnostic instruments, such as an oscilloscope, a network analyzer, and a spectrum analyzer, are integrated into our software. Apart from providing a quickly scalable, automatic feedback controller, the lock performance that can be achieved by using PyRPL with imperfect equipment, such as piezoelectric transducers and noisy amplifiers, is better than the one achievable with standard analog controllers due to the higher complexity of implementable filters and possibilities of nonlinear operations in the FPGA. This drastically reduces the cost of added complexity when introducing additional feedback loops to an experiment. The open-source character also distinguishes PyRPL from commercial solutions, as it allows users to customize functionalities at various levels, ranging from the easy integration of PyRPL-based feedback controllers into existing setups to the modification of the FPGA functionality. A community of developers provides fast and efficient implementation and testing of software modifications.
RESUMEN
A new method of probing mechanical losses and comparing the corresponding deposition processes of metallic and dielectric coatings in 1-100 MHz frequency range and cryogenic temperatures is presented. The method is based on the use of high-quality quartz acoustic cavities whose internal losses are orders of magnitude lower than any available coating nowadays. The approach is demonstrated for chromium, chromium/gold, and multilayer tantala/silica coatings. The Ta2O5/SiO2 coating has been found to exhibit a loss angle lower than 1.6 × 10-5 near 30 MHz at 4 K. The results are compared to the previous measurements.