296 citations · 404 across the 12 of their papers we have counts for
12 papers
Innovation Capacity of Dynamical Learning Systems
Anthony M. Polloreno
In noisy physical reservoirs, the classical information-processing capacity quantifies how well a linear readout can realize tasks measurable from the input histo…
Simple broadband signal detection at the fundamental limit
Anthony M. Polloreno, Graeme Smith
Broadband detection of a weak oscillatory field with unknown carrier frequency underlies magnetometry, axion searches and gravitational-wave sensing. We show that the Grover-like i…
Restrictions on Physical Stochastic Reservoir Computers
Anthony M. Polloreno
Reservoir computation is a recurrent framework for learning and predicting time series data, that benefits from extremely simple training and interpretability, often as the the dyn…
A Note on Noisy Reservoir Computation
Anthony M. Polloreno, Reuben R. W. Wang, Nikolas A. Tezak
In this note we extend the definition of the Information Processing Capacity (IPC) by Dambre et al [1] to include the effects of stochastic reservoir dynamics. We quantify the degr…
The QAOA with Few Measurements
Anthony M. Polloreno, Graeme Smith
The Quantum Approximate Optimization Algorithm (QAOA) was originally developed to solve combinatorial optimization problems, but has become a standard for assessing the performance…
Individual qubit addressing of rotating ion crystals in a Penning trap
Anthony M. Polloreno, Ana Maria Rey, John J. Bollinger
Trapped ions boast long coherence times and excellent gate fidelities, making them a useful platform for quantum information processing. Scaling to larger numbers of ion qubits in…
Opportunities and Limitations in Broadband Sensing
Anthony M. Polloreno, Jacob L. Beckey, Joshua Levin +5
We consider estimating the magnitude of a monochromatic AC signal that couples to a two-level sensor. For any detection protocol, the precision achieved depends on the signal's fre…
Towards Demonstrating Fault Tolerance in Small Circuits Using Bacon-Shor Codes
Ariel Shlosberg, Anthony M. Polloreno, Graeme Smith
Quantum error correction is necessary to perform large-scale quantum computations in the presence of noise and decoherence. As a result, several aspects of quantum error correction…
Robustly decorrelating errors with mixed quantum gates
Anthony M. Polloreno, Kevin C. Young
Coherent errors in quantum operations are ubiquitous. Whether arising from spurious environmental couplings or errors in control fields, such errors can accumulate rapidly and degr…
Demonstration of a Parametrically-Activated Entangling Gate Protected from Flux Noise
Sabrina S. Hong, Alexander T. Papageorge, Prasahnt Sivarajah +7
In state-of-the-art quantum computing platforms, including superconducting qubits and trapped ions, imperfections in the 2-qubit entangling gates are the dominant contributions of…
Quantum Kitchen Sinks: An algorithm for machine learning on near-term quantum computers
C. M. Wilson, J. S. Otterbach, N. Tezak +7
Noisy intermediate-scale quantum computing devices are an exciting platform for the exploration of the power of near-term quantum applications. Performing nontrivial tasks in such…
Demonstration of Universal Parametric Entangling Gates on a Multi-Qubit Lattice
M. Reagor, C. B. Osborn, N. Tezak +56
We show that parametric coupling techniques can be used to generate selective entangling interactions for multi-qubit processors. By inducing coherent population exchange between a…