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Imagine two instruments designed to distinguish between several competing explanations of a physical system. Both produce noisy observations. Which instrument gives us more information? One way to compare them is to pick a particular task and see which performs better. … Continue reading →

The strong converse problem What happens if we try to communicate quantum information through a noisy quantum channel at a rate above its capacity? At first sight, the answer seems obvious: it should not work. After all, this is what … Continue reading →

The basic model in distribution testing is that we receive independent and identically distributed samples of an unknown (discrete) distribution, and aim to decide whether it possesses a certain property or not. Here we are interested in how many samples … Continue reading →

Optimization problems involving quantum relative entropies are ubiquitous in quantum information theory. Some prominent examples include the optimization of the fidelity function or the Umegaki relative entropy over a set of states satisfying some specific constraints. In our work, we … Continue reading →

The no-cloning theorem states that within the framework of quantum mechanics, there does not exist any universal procedure that can replicate an unknown quantum state reliably. This fundamental principle was initially formalized in 1982 and later extended in various directions. … Continue reading →

Homomorphic encryption, which allows a server to compute on encrypted data of a client without first decrypting it, is like a “Swiss army knife” of classical cryptography. Namely, by treating homomorphic encryption as a cryptographic primitive, a broad range of … Continue reading →

Quantum state transformation is a fundamental problem in quantum resource theories. Resource theories offer a general framework to quantify the usefulness of quantum states and their inconvertibility under free operations. A resource theory is defined by a subset of quantum … Continue reading →

The (classical) multi-armed bandit problem The multi-armed bandit problem is a simple model of decision-making with uncertainty that lies in the class of classical reinforcement learning problems. Given a set of arms, a learner interacts sequentially with these arms sampling … Continue reading →

As larger and larger prototypes of quantum computers are being developed, one of the most exciting challenges in the theory of quantum computing is to find computational problems that can be solved by an noisy intermediate-scale noisy quantum devices, but … Continue reading →