Papers
Live trends in quantum computing research, updated daily from arXiv.
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Hardware platform mentions in abstracts — Photonic leads
Novel techniques for efficient quantum state tomography and quantum process tomography and their experimental implementation
Akshay Gaikwad·Jan 18, 2024
This thesis actively focuses on designing, analyzing, and experimentally implementing various QST and QPT protocols using an NMR ensemble quantum processor and superconducting qubit-based IBM cloud quantum processor. Part of the thesis also includes ...
A dual-species Rydberg array
Shraddha Anand, Conor E. Bradley, Ryan White +3 more·Jan 18, 2024
Large-scale Rydberg atom arrays are used for highly coherent analogue quantum simulations and for digital quantum computations. However, advanced quantum protocols, such as quantum error correction, require midcircuit qubit operations, including the ...
Power system fault diagnosis with quantum computing and efficient gate decomposition
Xiang Fei, Huan Zhao, Xiyuan Zhou +3 more·Jan 18, 2024
Power system fault diagnosis is crucial for identifying the location and causes of faults and providing decision-making support for power dispatchers. However, most classical methods suffer from significant time-consuming, memory overhead, and comput...
A Novel Noise-Aware Classical Optimizer for Variational Quantum Algorithms
Jeffrey M. Larson, M. Menickelly, Jiahao Shi·Jan 18, 2024
A key component of variational quantum algorithms (VQAs) is the choice of classical optimizer employed to update the parameterization of an ansatz. It is well recognized that quantum algorithms will, for the foreseeable future, necessarily be run on ...
Symmetry breaking in geometric quantum machine learning in the presence of noise
Cenk Tüysüz, Su Yeon Chang, Maria Demidik +3 more·Jan 17, 2024
Geometric quantum machine learning based on equivariant quantum neural networks (EQNNs) recently appeared as a promising direction in quantum machine learning. Despite encouraging progress, studies are still limited to theory, and the role of hardwar...
The generative quantum eigensolver (GQE) and its application for ground state search
Kouhei Nakaji, L. B. Kristensen, Ryota Kemmoku +14 more·Jan 17, 2024
We introduce the generative quantum eigensolver (GQE), a new quantum computational framework that operates outside the variational quantum algorithm paradigm by applying classical generative models to quantum simulation. The GQE algorithm optimizes a...
Towards large-scale quantum optimization solvers with few qubits
Marco Sciorilli, Lucas Borges, T. Patti +4 more·Jan 17, 2024
Quantum computers hold the promise of more efficient combinatorial optimization solvers, which could be game-changing for a broad range of applications. However, a bottleneck for materializing such advantages is that, in order to challenge classical ...
Benchmarking quantum computer simulation software packages
Amit Jamadagni, A. Läuchli, Cornelius Hempel·Jan 17, 2024
Rapid advances in quantum computing technology lead to an increasing need for software simulators that enable both algorithm design and the validation of results obtained from quantum hardware. This includes calculations that aim at probing regimes o...
Two-Stage Estimation and Variance Modeling for Latency-Constrained Variational Quantum Algorithms
Yunsoo Ha, Sara Shashaani, M. Menickelly·Jan 17, 2024
The quantum approximate optimization algorithm (QAOA) has enjoyed increasing attention in noisy, intermediate-scale quantum computing with its application to combinatorial optimization problems. QAOA has the potential to demonstrate a quantum advanta...
How to Design a Classically Difficult Random Quantum Circuit for Quantum Computational Advantage Experiments
He-Liang Huang, You-Wei Zhao, Chu Guo·Jan 16, 2024
Quantum computational advantage is a critical milestone for near-term quantum technologies and an essential step towards building practical quantum computers. Recent successful demonstrations of quantum computational advantage owe much to specificall...
Expanding Hardware-Efficiently Manipulable Hilbert Space via Hamiltonian Embedding
J. Leng, Joseph Li, Yuxiang Peng +1 more·Jan 16, 2024
Many promising quantum applications depend on the efficient quantum simulation of an exponentially large sparse Hamiltonian, a task known as sparse Hamiltonian simulation, which is fundamentally important in quantum computation. Although several theo...
Parent Hamiltonian for fully augmented matrix product states
Xiangjian Qian, Mingpu Qin·Jan 15, 2024
Density matrix renormalization group (DMRG) or matrix product states (MPS) is the most effective and accurate method for studying one-dimensional quantum many-body systems. However, the application of DMRG to two-dimensional systems is not as success...
Scaling Advantage in Approximate Optimization with Quantum Annealing.
H. Bauza, Daniel A. Lidar·Jan 14, 2024
Quantum annealing is a heuristic optimization algorithm that exploits quantum evolution to find low-energy states. Quantum annealers have scaled up in recent years to tackle increasingly larger and more highly connected discrete optimization and quan...
Quantum information processing with superconducting circuits: realizing and characterizing quantum gates and algorithms in open quantum systems
H. Sakhouf·Jan 14, 2024
This thesis focuses on quantum information processing using the superconducting device, especially, on realizing quantum gates and algorithms in open quantum systems. Such a device is constructed by transmon-type superconducting qubits coupled to a s...
Quantum computing for simulation of fluid dynamics
Claudio Sanavio, Sauro Succi·Jan 13, 2024
We present a pedagogical introduction to a series of quantum computing algorithms for the simulation of classical fluids, with special emphasis on the Carleman-Lattice Boltzmann method.
Simulating Quantum Systems with NWQ-Sim on HPC
In-Saeng Suh, Ang Li·Jan 12, 2024
NWQ-Sim is a cutting-edge quantum system simulation environment designed to run on classical multi-node, multi-CPU/GPU heterogeneous HPC systems. In this work, we provide a brief overview of NWQ-Sim and its implementation in simulating quantum circui...
State of practice: evaluating GPU performance of state vector and tensor network methods
Marzio Vallero, Flavio Vella, Paolo Rech·Jan 11, 2024
The frontier of quantum computing (QC) simulation on classical hardware is quickly reaching the hard scalability limits for computational feasibility. Nonetheless, there is still a need to simulate large quantum systems classically, as the Noisy Inte...
A new "gold standard": Perturbative triples corrections in unitary coupled cluster theory and prospects for quantum computing.
Zachary W. Windom, Daniel Claudino, R. J. Bartlett·Jan 11, 2024
A major difficulty in quantum simulation is the adequate treatment of a large collection of entangled particles, synonymous with electron correlation in electronic structure theory, with coupled cluster (CC) theory being the leading framework for dea...
Efficient and Robust Parameter Optimization of the Unitary Coupled-Cluster Ansatz.
Weitang Li, Yufei Ge, Shi-Xin Zhang +2 more·Jan 10, 2024
The variational quantum eigensolver (VQE) framework has been instrumental in advancing near-term quantum algorithms. However, parameter optimization remains a significant bottleneck for VQE, requiring a large number of measurements for successful alg...
Comparing Classical and Quantum Ground State Preparation Heuristics
Katerina Gratsea, Jakob S. Kottmann, Peter D. Johnson +1 more·Jan 10, 2024
One promising field of quantum computation is the simulation of quantum systems, and specifically, the task of ground state energy estimation (GSEE). Ground state preparation (GSP) is a crucial component in GSEE algorithms, and classical methods like...