An integrated optical modulator operating at cryogenic temperatures.

Photonic integrated circuits (PICs) operating at cryogenic temperatures are fundamental building blocks required to achieve scalable quantum computing and cryogenic computing technologies1,2. Silicon PICs have matured for room-temperature applications, but their cryogenic performance is limited by the absence of efficient low-temperature electro-optic modulation. Here we demonstrate electro-optic switching and modulation from room temperature down to 4 K by using the Pockels effect in integrated barium titanate (BaTiO3) devices3. We investigate the temperature dependence of the nonlinear optical properties of BaTiO3, showing an effective Pockels coefficient of 200 pm V-1 at 4 K. The fabricated devices show an electro-optic bandwidth of 30 GHz, ultralow-power tuning that is 109 times more efficient than thermal tuning, and high-speed data modulation at 20 Gbps. Our results demonstrate a missing component for cryogenic PICs, removing major roadblocks for the realization of cryogenic-compatible systems in the field of quantum computing, supercomputing and sensing, and for interfacing those systems with instrumentation at room temperature.

Witnessing eigenstates for quantum simulation of Hamiltonian spectra.

The efficient calculation of Hamiltonian spectra, a problem often intractable on classical machines, can find application in many fields, from physics to chemistry. We introduce the concept of an "eigenstate witness" and, through it, provide a new quantum approach that combines variational methods and phase estimation to approximate eigenvalues for both ground and excited states. This protocol is experimentally verified on a programmable silicon quantum photonic chip, a mass-manufacturable platform, which embeds entangled state generation, arbitrary controlled unitary operations, and projective measurements. Both ground and excited states are experimentally found with fidelities >99%, and their eigenvalues are estimated with 32 bits of precision. We also investigate and discuss the scalability of the approach and study its performance through numerical simulations of more complex Hamiltonians. This result shows promising progress toward quantum chemistry on quantum computers.

Reconstruction of a Real World Social Network using the Potts Model and Loopy Belief Propagation.

The scope of this paper is to test the adoption of a statistical model derived from Condensed Matter Physics, for the reconstruction of the structure of a social network. The inverse Potts model, traditionally applied to recursive observations of quantum states in an ensemble of particles, is here addressed to observations of the members' states in an organization and their (anti)correlations, thus inferring interactions as links among the members. Adopting proper (Bethe) approximations, such an inverse problem is showed to be tractable. Within an operational framework, this network-reconstruction method is tested for a small real-world social network, the Italian parliament. In this study case, it is easy to track statuses of the parliament members, using (co)sponsorships of law proposals as the initial dataset. In previous studies of similar activity-based networks, the graph structure was inferred directly from activity co-occurrences: here we compare our statistical reconstruction with such standard methods, outlining discrepancies and advantages.