NV centers are great magnetometers, but their amazing sensitivity is lost outside cryogenic environments. But what is lost can sometimes be found, and today's guests, Raffaele Santagati and Antonio Andres Gentile, have just discovered how to fix the situation. 

We discuss: NV centers, Hamiltonian learning, quantum sensors and machine learning. Basically, all the good stuff.

R. Santagati, A. A. Gentile et al, Magnetic-Field Learning Using a Single Electronic Spin in Diamond with One-Photon Readout at Room Temperature, Phys. Rev. X 9, 021019 (open access paper)

Papers referenced during conversation:

(~ 3:50) Scale-free correlations in starling flocks (paper)

(~ 6:30) Experimental quantum Hamiltonian learning (paper, preprint)

(~ 9:00) Experimental quantum Hamiltonian learning (paper, preprint)

(~ 18:45) Quantum measurement and orientation tracking of fluorescent nanodiamonds inside living cells (paper)

(~ 30:00) Efficient Bayesian Phase Estimation (paper, preprint)

(~ 33:00) Quantum-Enhanced Measurements: Beating the Standard Quantum Limit (paper, preprint)

(~ 33:15) Optimized quantum sensing with a single electron spin using real-time adaptive measurements (paper, pdf)

(~ 33:50) Robust online Hamiltonian learning (open access paper)

(~ 33:50) Hamiltonian Learning and Certification Using Quantum Resources (paper, preprint)

Big review of everything:

C. L. Degen, F. Reinhard, and P. Cappellaro, Quantum sensing, Rev. Mod. Phys. 89, 035002 (paper, preprint)

Over the last few years, optical tweezers have been capturing the attention of the quantum world. Recent experiments pushed the ball forward by extending this trapping technique alkaline-earth atoms (atoms with two, rather than one, valence electrons). We talk to Alexandre Cooper about those state-of-the-art results.

A. Cooper et al, Alkaline-Earth Atoms in Optical Tweezers, PRX 8, 041055 (2018) (paper, preprint)

J. P. Covey et al, 2000-Times Repeated Imaging of Strontium Atoms in Clock-Magic Tweezer Arrays, PRL 122, 173201 (2019) (paper, preprint)

Quantum computers are expected to help in chemistry, but how exactly? In this episode, Alessandro Chiesa and Francesco Tacchino tell us about their recent work using IBM chips to predict results of neutron scattering experiments on magnetic molecules. 

A. Chiesa, F. Tacchino, M. Grossi, P. Santini, I. Tavernelli, D. Gerace & S. Carretta, Quantum hardware simulating four-dimensional inelastic neutron scattering, Nature Physics, March 2019 (paper, preprint)

Jayadev Vijayan develops a Fermi quantum gas microscope in the Quantum Optics group in Munich. He prepares an ordered lattice with one atom per site, and then dopes it by adding another atom into the system. This allows him to observe how doping affects the spin ordering of the gas. They claim their images reveal polarons - a quasi-particle important to understanding high-temperature superconductivity.

Vlad Negnevitsky is working towards serious quantum error correction. He prepares a Bell state of two Beryllium ions, and measures its parity with an ancilla Calcium ion. He then uses this result to correct for any errors in real time.

V. Negnevitsky et al, Repeated multi-qubit readout and feedback with a mixed-species trapped-ion register, Nature volume 563, pages 527–531 (2018) (paper, preprint)

Christopher Axline works in circuit QED. He prepares arbitrary quantum states in one microwave cavity, then transfers it into another cavity with a press of a button.

C. Axline et al, On-demand quantum state transfer and entanglement between remote microwave cavity memories, Nature Physics vol 14, pp 705–710 (2018) (Paper, preprint)