Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Incremental Data-Uploading for Full-Quantum Classification
Maniraman Periyasamy, Nico Meyer, Christian Ufrecht +3 more·May 6, 2022
The data representation in a machine-learning model strongly influences its performance. This becomes even more important for quantum machine learning models implemented on noisy intermediate scale quantum (NISQ) devices. Encoding high dimensional da...
Transition state search and geometry relaxation throughout chemical compound space with quantum machine learning.
Stefan N. Heinen, G. von Rudorff, O. A. von Lilienfeld·May 5, 2022
We use energies and forces predicted within response operator based quantum machine learning (OQML) to perform geometry optimization and transition state search calculations with legacy optimizers but without the need for subsequent re-optimization w...
Improved quantum computing with higher-order Trotter decomposition
Xiaodong Yang, Xinfang Nie, Yunlan Ji +3 more·May 5, 2022
In designing quantum control, it is generally required to simulate the controlled system evolution with a classical computer. However, computing the time evolution operator can be quite resource-consuming since the total Hamiltonian is often hard to ...
Quantum annealing for jet clustering with thrust
Andrea Delgado, J. Thaler·May 5, 2022
Quantum computing holds the promise of substantially speeding up computationally expensive tasks, such as solving optimization problems over a large number of elements. In high-energy collider physics, quantum-assisted algorithms might accelerate the...
Quantum state preparation and nonunitary evolution with diagonal operators
A. Schlimgen, Kade Head-Marsden, LeeAnn M. Sager-Smith +2 more·May 5, 2022
Realizing non-unitary transformations on unitary-gate based quantum devices is critically important for simulating a variety of physical problems including open quantum systems and subnormalized quantum states. We present a dilation based algorithm t...
LAWS: Look Around and Warm-Start Natural Gradient Descent for Quantum Neural Networks
Zeyi Tao, Jindi Wu, Qi Xia +1 more·May 5, 2022
Variational quantum algorithms (VQAs) have recently received much attention due to their promising performance in Noisy Intermediate-Scale Quantum computers (NISQ). However, VQAs run on parameterized quantum circuits (PQC) with randomly initialized p...
New Techniques Based On Odd-Edge Total Colorings In Topological Cryptosystem
Bing Yao, Mingjun Zhang, Sihua Yang +1 more·May 5, 2022
: For building up twin-graphic lattices towards topological cryptograph, we define four kinds of new odd-magic-type colorings: odd-edge graceful-difference total coloring, odd-edge edge-difference total coloring, odd-edge edge-magic total coloring, and ...
Robust Quantum Control for the Manipulation of Solid-State Spins
Yi-fan Zhang, Hao Wu, Xiao-dong Yang +6 more·May 5, 2022
Robust and high-fidelity control of electron spins in solids is the cornerstone for facilitating applications of solid-state spins in quantum information processing and quantum sensing. However, precise control of spin systems is always challenging d...
Quantum extremal learning
Savvas Varsamopoulos, E. Philip, H. Vlijmen +6 more·May 5, 2022
We propose a quantum algorithm for “extremal learning,” which is the process of finding the input to a hidden function that extremizes the function output, without having direct access to the hidden function, given only partial input–output (training...
Post-selection in noisy Gaussian boson sampling: part is better than whole
Tian-Yu Yang, Yiyun Shen, Zhoulei Cao +1 more·May 5, 2022
Gaussian boson sampling (GBS) is originally proposed to show quantum advantage with quantum linear optical elements. Recently, several experimental breakthroughs based on GBS pointing to quantum computing supremacy have been presented. However, due t...
Vector Field Visualization of Single-Qubit State Tomography
Adrien Suau, Marc Vuffray, A. Lokhov +2 more·May 5, 2022
As the variety of commercially available quantum computers continues to increase, so does the need for tools that can characterize, verify, and validate these computers. This work explores using quantum state tomography for characterizing the perform...
Variational Quantum Optimization of Nonlocality in Noisy Quantum Networks
Brian Doolittle, T. Bromley, N. Killoran +1 more·May 5, 2022
The noise and complexity inherent to quantum communication networks leads to technical challenges in designing quantum network protocols using classical methods. We address this issue with a hybrid variational quantum optimization (VQO) framework tha...
A Tool For Debugging Quantum Circuits
Sara Ayman Metwalli, R. V. Meter·May 4, 2022
As the scale of quantum programs grows to match that of classical software, the nascent field of quantum software engineering must mature and tools such as debuggers will become increasingly important. However, developing a quantum debugger is challe...
qLEET: visualizing loss landscapes, expressibility, entangling power and training trajectories for parameterized quantum circuits
Utkarsh Azad, Animesh Sinha·May 4, 2022
We present qLEET, an open-source Python package for studying parameterized quantum circuits (PQCs), which are widely used in various variational quantum algorithms (VQAs) and quantum machine learning (QML) algorithms. qLEET enables computation of pro...
A Hybrid Classical-Quantum framework for solving Free Boundary Value Problems and Applications in Modeling Electric Contact Phenomena
Merey M.Sarsengeldin·May 4, 2022
In this paper we elaborate a hybrid classical-quantum framework which allows one to model and solve heat and mass transfer problems occurring in electric contacts. We utilize special functions and Harrow-Hassidim-Lloyd (HHL) quantum algorithm for fin...
Quantum Computing Approaches for Mission Covering Optimization
Massimiliano Cutugno, A. Giani, P. Alsing +2 more·May 4, 2022
Quantum computing has the potential to revolutionize the way hard computational problems are solved in terms of speed and accuracy. Quantum hardware is an active area of research and different hardware platforms are being developed. Quantum algorithm...
Integrable deformations of superintegrable quantum circuits
Tamás Gombor, B. Pozsgay·May 4, 2022
Superintegrable models are very special dynamical systems: they possess more conservation laws than what is necessary for integrability. This severely constrains their dynamical processes, and it often leads to their exact solvability, even in non-eq...
Improved Algorithms of Quantum Imaginary Time Evolution for Ground and Excited States of Molecular Systems.
T. Tsuchimochi, Yoohee Ryo, S. Ten-no +1 more·May 4, 2022
Quantum imaginary time evolution (QITE) is a recently proposed quantum-classical hybrid algorithm that is guaranteed to reach the lowest state of systems. In this study, we present several improvements on QITE, mainly focusing on molecular applicatio...
The landscape of the quantum start-up ecosystem
Z. Seskir, Ramis Korkmaz, A. Aydinoğlu·May 4, 2022
The second quantum revolution has been producing groundbreaking scientific and technological outputs since the early 2000s; however, the scientific literature on the impact of this revolution on the industry, specifically on start-ups, is limited. In...
Group-Invariant Quantum Machine Learning
Martín Larocca, F. Sauvage, Faris M. Sbahi +3 more·May 4, 2022
Quantum Machine Learning (QML) models are aimed at learning from data encoded in quantum states. Recently, it has been shown that models with little to no inductive biases (i.e., with no assumptions about the problem embedded in the model) are likely...