5 papers · 1 filter
On the average-case complexity of learning output distributions of quantum circuits
Alexander Nietner, Marios Ioannou, Ryan Sweke +4
In this work, we show that learning the output distributions of brickwork random quantum circuits is average-case hard in the statistical query model. This learning model is widely…
Efficient distributed inner product estimation via Pauli sampling
Marcel Hinsche, Marios Ioannou, Sofiene Jerbi +3
Cross-platform verification is the task of comparing the output states produced by different physical platforms using solely local quantum operations and classical communication. W…
Interactive proofs for verifying (quantum) learning and testing
Matthias C. Caro, Jens Eisert, Marcel Hinsche +3
We consider the problem of testing and learning from data in the presence of resource constraints, such as limited memory or weak data access, which place limitations on the effici…
Shallow shadows: Expectation estimation using low-depth random Clifford circuits
Christian Bertoni, Jonas Haferkamp, Marcel Hinsche +3
We provide practical and powerful schemes for learning many properties of an unknown n-qubit quantum state using a sparing number of copies of the state. Specifically, we present a…
Benchmarking bosonic and fermionic dynamics
Jadwiga Wilkens, Marios Ioannou, Ellen Derbyshire +4
Analog quantum simulation allows for assessing static and dynamical properties of strongly correlated quantum systems to high precision. To perform simulations outside the reach of…