Quantum computing for finance
Quantum computers are expected to surpass the computational capabilities of classical
computers and have a transformative impact on numerous industry sectors. We present a …
computers and have a transformative impact on numerous industry sectors. We present a …
A survey of quantum computing for finance
Quantum computers are expected to surpass the computational capabilities of classical
computers during this decade and have transformative impact on numerous industry sectors …
computers during this decade and have transformative impact on numerous industry sectors …
Quantum-centric supercomputing for materials science: A perspective on challenges and future directions
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 …
of novel materials. Computationally hard tasks in materials science stretch the limits of …
MQT Bench: Benchmarking software and design automation tools for quantum computing
Quantum software tools for a wide variety of design tasks on and across different levels of
abstraction are crucial in order to eventually realize useful quantum applications. This …
abstraction are crucial in order to eventually realize useful quantum applications. This …
Qubit-reuse compilation with mid-circuit measurement and reset
A number of commercially available quantum computers, such as those based on trapped-
ion or superconducting qubits, can now perform mid-circuit measurements and resets. In …
ion or superconducting qubits, can now perform mid-circuit measurements and resets. In …
Parameter transfer for quantum approximate optimization of weighted maxcut
Finding high-quality parameters is a central obstacle to using the quantum approximate
optimization algorithm (QAOA). Previous work partially addresses this issue for QAOA on …
optimization algorithm (QAOA). Previous work partially addresses this issue for QAOA on …
Large-scale quantum approximate optimization on nonplanar graphs with machine learning noise mitigation
Quantum computers are increasing in size and quality but are still very noisy. Error
mitigation extends the size of the quantum circuits that noisy devices can meaningfully …
mitigation extends the size of the quantum circuits that noisy devices can meaningfully …
Layer VQE: A variational approach for combinatorial optimization on noisy quantum computers
Combinatorial optimization on near-term quantum devices is a promising path to
demonstrating quantum advantage. However, the capabilities of these devices are …
demonstrating quantum advantage. However, the capabilities of these devices are …
Efficient parallelization of tensor network contraction for simulating quantum computation
We develop an algorithmic framework for contracting tensor networks and demonstrate its
power by classically simulating quantum computation of sizes previously deemed out of …
power by classically simulating quantum computation of sizes previously deemed out of …
Transferability of optimal QAOA parameters between random graphs
The Quantum approximate optimization algorithm (QAOA) is one of the most promising
candidates for achieving quantum advantage through quantum-enhanced combinatorial …
candidates for achieving quantum advantage through quantum-enhanced combinatorial …