Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Learning many-body Hamiltonians with Heisenberg-limited scaling
Hsin-Yuan Huang, Yu Tong, Di Fang +1 more·Oct 6, 2022
Learning a many-body Hamiltonian from its dynamics is a fundamental problem in physics. In this Letter, we propose the first algorithm to achieve the Heisenberg limit for learning an interacting N-qubit local Hamiltonian. After a total evolution time...
Scalability of Superconductor Electronics: Limitations Imposed by AC Clock and Flux Bias Transformers
S. K. Tolpygo·Oct 6, 2022
Flux transformers are the necessary component of all superconductor digital integrated circuits utilizing flux biasing and ac power excitation and clocking of logic cells, e.g., adiabatic quantum flux parametron (AQFP), reciprocal quantum logic (RQL)...
Variational quantum non-orthogonal optimization
Pablo Bermejo, R. Orús·Oct 6, 2022
Current universal quantum computers have a limited number of noisy qubits. Because of this, it is difficult to use them to solve large-scale complex optimization problems. In this paper we tackle this issue by proposing a quantum optimization scheme ...
Automated Synthesis of Quantum Circuits using Neural Network
Kentaro Murakami, Jianjun Zhao·Oct 6, 2022
While the ability to build quantum computers is improving dramatically, developing quantum algorithms is very limited and relies on human insight and ingenuity. Although several quantum programming languages have been developed, it is challenging for...
Variational quantum one-class classifier
Gunhee Park, Joonsuk Huh, D. Park·Oct 6, 2022
One-class classification (OCC) is a fundamental problem in pattern recognition with a wide range of applications. This work presents a semi-supervised quantum machine learning algorithm for such a problem, which we call a variational quantum one-clas...
Fault-Tolerant Coding for Entanglement-Assisted Communication
Paula Belzig, M. Christandl, Alexander Müller-Hermes·Oct 6, 2022
Channel capacities quantify the optimal rates of sending information reliably over noisy channels. Usually, the study of capacities assumes that the circuits which the sender and receiver use for encoding and decoding consist of perfectly noiseless g...
Probabilistic partition of unity networks for high‐dimensional regression problems
Tiffany Fan, N. Trask, M. D'Elia +1 more·Oct 6, 2022
We explore the probabilistic partition of unity network (PPOU‐Net) model in the context of high‐dimensional regression problems and propose a general framework focusing on adaptive dimensionality reduction. With the proposed framework, the target fun...
Studying chirality imbalance with quantum algorithms
Alexander M. Czajka, Zhong-Bo Kang, Y. Tee +1 more·Oct 6, 2022
To describe the chiral magnetic effect, the chiral chemical potential µ 5 is introduced to imitate the impact of topological charge changing transitions in the quark-gluon plasma under the influence of an external magnetic field. We employ the (1+1) dim...
Quantum computation for periodic solids in second quantization
A. V. Ivanov, Christoph Sünderhauf, Nicole Holzmann +4 more·Oct 5, 2022
In this work, we present a quantum algorithm for ground-state energy calculations of periodic solids on error-corrected quantum computers. The algorithm is based on the sparse qubitization approach in second quantization and developed for Bloch and W...
No invariant perfect qubit codes
Refik Mansuroglu, H. Sahlmann·Oct 5, 2022
Perfect tensors describe highly entangled quantum states that have attracted particular attention in the fields of quantum information theory and quantum gravity. In loop quantum gravity, the natural question arises whether SU(2) invariant tensors, w...
Robust Qubit Mapping Algorithm via Double-Source Optimal Routing on Large Quantum Circuits
Chin-Yi Cheng, Chien-Yi Yang, Yi-Hsiang Kuo +3 more·Oct 4, 2022
Qubit mapping is a critical aspect of implementing quantum circuits on real hardware devices. Currently, the existing algorithms for qubit mapping encounter difficulties when dealing with larger circuit sizes involving hundreds of qubits. In this art...
Improving Quantum Classifier Performance in NISQ Computers by Voting Strategy from Ensemble Learning
Ruiyang Qin, Zhiding Liang, Jinglei Cheng +2 more·Oct 4, 2022
Due to the immense potential of quantum computers and the significant computing overhead required in machine learning applications, the variational quantum classifier (VQC) has received a lot of interest recently for image classification. The perform...
Quantum Communication Complexity of Linear Regression
A. Montanaro, Changpeng Shao·Oct 4, 2022
Quantum computers may achieve speedups over their classical counterparts for solving linear algebra problems. However, in some cases—such as for low-rank matrices—dequantized algorithms demonstrate that there cannot be an exponential quantum speedup....
Quantum circuits for toric code and X-cube fracton model
Penghua Chen, B. Yan, Shawn X. Cui·Oct 4, 2022
We propose a systematic and efficient quantum circuit composed solely of Clifford gates for simulating the ground state of the surface code model. This approach yields the ground state of the toric code in ⌈2L+2+log2(d)+L2d⌉ time steps, where L refer...
Perturbation theory with quantum signal processing
K. Mitarai, Kiichiro Toyoizumi, W. Mizukami·Oct 3, 2022
Perturbation theory is an important technique for reducing computational cost and providing physical insights in simulating quantum systems with classical computers. Here, we provide a quantum algorithm to obtain perturbative energies on quantum comp...
SDC-based Resource Constrained Scheduling for Quantum Control Architectures
R. Nane·Oct 3, 2022
Instruction scheduling is a key transformation in backend compilers that take an untimed description of an algorithm and assigns time slots to the algorithm’s instructions so that they can be executed as efficiently as possible while tak-ing into accou...
Optimization of the memory reset rate of a quantum echo-state network for time sequential tasks
Riccardo Molteni, C. Destri, E. Prati·Oct 3, 2022
Quantum reservoir computing is a class of quantum machine learning algorithms involving a reservoir of an echo state network based on a register of qubits, but the dependence of its memory capacity on the hyperparameters is still rather unclear. In o...
Learning with Limited Samples - Meta-Learning and Applications to Communication Systems
Lisha Chen, Sharu Theresa Jose, I. Nikoloska +3 more·Oct 3, 2022
Deep learning has achieved remarkable success in many machine learning tasks such as image classification, speech recognition, and game playing. However, these breakthroughs are often difficult to translate into real-world engineering systems because...
Interpreting convolutional neural networks' low-dimensional approximation to quantum spin systems
Yilong Ju, S. Alam, Jonathan Minoff +3 more·Oct 3, 2022
Convolutional neural networks (CNNs) have been employed along with variational Monte Carlo methods for finding the ground state of quantum many-body spin systems with great success. However, it remains uncertain how CNNs, with a model complexity that...
Q2Graph: a modelling tool for measurement-based quantum computing
Greg Bowen, S. Devitt·Oct 3, 2022
The quantum circuit model is the default for encoding an algorithm intended for a NISQ computer or a quantum computing simulator. A simple graph and through it, a graph state - quantum state physically manifesting an abstract graph structure - is syn...