Quantum computational advantage with a programmable photonic processor.

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.

Scalable Generation of Multiphoton Entangled States by Active Feed-Forward and Multiplexing.

Multiphoton entangled quantum states are key to advancing quantum technologies such as multiparty quantum communications, quantum sensing, or quantum computation. Their scalable generation, however, remains an experimental challenge. Current methods for generating these states rely on stitching together photons from probabilistic sources, and state generation rates drop exponentially in the number of photons. Here, we implement a system based on active feed-forward and multiplexing that addresses this challenge. We demonstrate the scalable generation of four-photon and six-photon Greenberger-Horne-Zeilinger states, increasing generation rates by factors of 9 and 35, respectively. This is consistent with the exponential enhancement compared to the standard nonmultiplexed approach that is predicted by our theory. These results facilitate the realization of practical multiphoton protocols for photonic quantum technologies.

Quantum computational advantage via high-dimensional Gaussian boson sampling.

Photonics is a promising platform for demonstrating a quantum computational advantage (QCA) by outperforming the most powerful classical supercomputers on a well-defined computational task. Despite this promise, existing proposals and demonstrations face challenges. Experimentally, current implementations of Gaussian boson sampling (GBS) lack programmability or have prohibitive loss rates. Theoretically, there is a comparative lack of rigorous evidence for the classical hardness of GBS. In this work, we make progress in improving both the theoretical evidence and experimental prospects. We provide evidence for the hardness of GBS, comparable to the strongest theoretical proposals for QCA. We also propose a QCA architecture we call high-dimensional GBS, which is programmable and can be implemented with low loss using few optical components. We show that particular algorithms for simulating GBS are outperformed by high-dimensional GBS experiments at modest system sizes. This work thus opens the path to demonstrating QCA with programmable photonic processors.

Robust optical polarization of nuclear spin baths using Hamiltonian engineering of nitrogen-vacancy center quantum dynamics.

Dynamic nuclear polarization (DNP) is an important technique that uses polarization transfer from electron to nuclear spins to achieve nuclear hyperpolarization. Combining efficient DNP with optically polarized nitrogen-vacancy (NV) centers offers promising opportunities for novel technological applications, including nanoscale nuclear magnetic resonance spectroscopy of liquids, hyperpolarized nanodiamonds as magnetic resonance imaging contrast agents, and the initialization of nuclear spin-based diamond quantum simulators. However, none of the current realizations of polarization transfer are simultaneously robust and sufficiently efficient, making the realization of the applications extremely challenging. We introduce the concept of systematically designing polarization sequences by Hamiltonian engineering, resulting in polarization sequences that are robust and fast. We theoretically derive sequences and experimentally demonstrate that they are capable of efficient polarization transfer from optically polarized NV centers in diamond to the surrounding 13C nuclear spin bath even in the presence of control errors, making the abovementioned novel applications possible.