In quantum mechanics, the probability distribution function (PDF) and full counting statistics (FCS) play a fundamental role in characterizing the fluctuations of quantum observables, as they encode the complete information about these fluctuations. In this letter, we measure these two quantities in a trapped-ion quantum simulator for the transverse and longitudinal magnetization within a subsystem. We utilize the toolbox of classical shadows to postprocess the measurements performed in random bases. The measurement scheme efficiently allows access to the FCS and PDF of all possible operators on desired choices of subsystems of an extended quantum system.

Quantum devices can process data in a fundamentally different way than classical computers. To leverage this potential, many algorithms require the aid of a quantum Random Access Memory (QRAM), i.e. a module capable of efficiently loading datasets (both classical and quantum) onto the quantum processor. However, a realization of this fundamental building block is still outstanding, since existing proposals require prohibitively many resources for reliable implementations, or are not compatible with current architectures. Moreover, present approaches cannot be scaled-up, as they do not allow for efficient quantum error-correction. Here we develop a QRAM design, that enables fast and robust QRAM calls, naturally allows for fault-tolerant and error-corrected operation, and can be integrated on present hardware. Our proposal employs a special quantum resource state that is consumed during the QRAM call: we discuss how it can be assembled and processed efficiently in a dedicated module, and give detailed blueprints for modern neutral-atom processors. Our work places a long missing, fundamental component of quantum computers within reach of currently available technology; this opens the door to algorithms featuring practical quantum advantage, including search or oracular problems, quantum chemistry and machine learning.