Computational models are an essential tool for the design, characterization, and discovery
of novel materials. Computationally hard tasks in materials science stretch the limits of …

Quantum computing promises to provide the next step up in computational power for diverse
application areas. In this review, we examine the science behind the quantum hype and …

Quantum computing promises to provide the next step up in computational power for diverse
application areas. In this review, we examine the science behind the quantum hype, and the …

In ab initio electronic structure simulations, fermion-to-qubit mappings represent the initial
encoding step from the problem of fermions into a problem of qubits. This work introduces a …

In this paper, we introduce an algorithm for extracting topological data from translation
invariant generalized Pauli stabilizer codes in two-dimensional systems, focusing on the …

Utilizing the framework of $\mathbb {Z} _2 $ lattice gauge theories in the context of Pauli
stabilizer codes, we present methodologies for simulating fermions via qubit systems on a …

Quantum computers offer the potential to simulate nuclear processes that are classically
intractable. With the goal of understanding the necessary quantum resources, we employ …

To implement a quantum error-correction protocol, we first need a scheme to prepare our
state in the correct subspace of the code, and this can be done using a unitary encoding …

The most scalable proposed methods of simulating lattice fermions on noisy quantum
computers employ encodings that eliminate nonlocal operators using a constant factor more …

Quantum computers hold great promise for efficiently simulating Fermionic systems,
benefiting fields like quantum chemistry and materials science. To achieve this, algorithms …