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Optimal Quantum Computing Architecture through Deep Co-Design

Much like classical computing, quantum computers follow an abstraction model for their architecture. The performance of a quantum computer is dependent on the performance of each layer of this abstraction model, as well as the model itself. Due to its centrality in the quantum computing stack, the control system (consisting of hardware, firmware, and software) plays a strategically outsized role in the problem of quantum architecture.

Introduction to Quantum Computing (CMSC457/PHYS457, Spring 2025)

Cross-listed with CMSC457.  Credit only granted for: PHYS457 or CMSC457. Additional information: No previous background in quantum mechanics is required.
An introduction to the concept of a quantum computer, including algorithms that outperform classical computation and methods for performing quantum computation reliably in the presence of noise. As this is a multidisciplinary subject, the course will cover basic concepts in theoretical computer science and physics in addition to introducing core quantum computing topics.

Parallel-sequential circuits for quantum state preparation

Abstract: We introduce parallel-sequential (PS) circuits, a family of quantum circuits characterized by a tunable degree of entanglement and maximum correlation length, which interpolates between brickwall and sequential circuits. We provide evidence that on noisy devices, properly chosen PS circuits suppress error proliferation and exhibit superior trainability and evaluation accuracy when employed as variational circuits, thus outperforming brickwall, sequential, and log-depth circuits in [Malz*, Styliaris*, Wei*, Cirac, PRL 2024] across most parameter regimes.