Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Quantum state preparation for bell-shaped probability distributions using deconvolution methods
K. Sharma, Camille de Valk, Ankur Raina +1 more·Oct 8, 2023
Quantum systems are a natural choice for generating probability distributions due to the phenomena of quantum measurements. The data that we observe in nature from various physical phenomena can be modelled using quantum circuits. To load this data, ...
Hybrid Quantum-Classical Machine Learning for Sentiment Analysis
Abu Kaisar, Mohammad Masum, Anshul Maurya +3 more·Oct 8, 2023
The collaboration between quantum computing and classical machine learning offers potential advantages in natural language processing, particularly in the sentiment analysis of human emotions and opinions expressed in large-scale datasets. In this wo...
Quantum computing using floating electrons on cryogenic substrates: Potential and challenges
A. Jennings, Xianjing Zhou, I. Grytsenko +1 more·Oct 6, 2023
In this review, we introduce a developing qubit platform: floating-electron-based qubits. Electrons floating in a vacuum above the surface of liquid helium or solid neon emerge as promising candidates for qubits, especially due to their expected long...
Valley Pseudospin Polarized Evanescent Coupling between Microwave Ring Resonator and Waveguide in Phononic Topological Insulators.
D. Hatanaka, Hiroaki Takeshita, Motoki Kataoka +3 more·Oct 6, 2023
A coupled ring-waveguide structure is at the core of bosonic wave-based information processing systems, enabling advanced wave manipulations such as filtering, routing, and multiplexing. However, its miniaturization is challenging due to momentum con...
A Quantum-Classical Method Applied to Material Design: Photochromic Materials Optimization for Photopharmacology Applications
Qi Gao, M. Sugawara, P. Nation +4 more·Oct 6, 2023
Integration of quantum chemistry simulations, machine learning techniques, and optimization calculations is expected to accelerate material discovery by making large chemical spaces amenable to computational study; a challenging task for classical co...
Variational Coherent Quantum Annealing
N. Barraza, G. A. Barrios, I. Montalban +2 more·Oct 3, 2023
We present a hybrid classical-quantum computing paradigm where the quantum part strictly runs within the coherence time of a quantum annealer, a method we call variational coherent quantum annealing (VCQA). It involves optimizing the schedule functio...
An Architecture for Improved Surface Code Connectivity in Neutral Atoms
Joshua Viszlai, S. Lin, Siddharth Dangwal +2 more·Sep 24, 2023
In order to achieve error rates necessary for advantageous quantum algorithms, Quantum Error Correction (QEC) will need to be employed, improving logical qubit fidelity beyond what can be achieved physically. As today's devices begin to scale, co-des...
A hybrid algorithm for quadratically constrained quadratic optimization problems
Hongyi Zhou, Sirui Peng, Q. Li +1 more·Sep 19, 2023
Quadratically Constrained Quadratic Programs (QCQPs) are an important class of optimization problems with diverse real-world applications. In this work, we propose a variational quantum algorithm for general QCQPs. By encoding the variables in the am...
Quantum Algorithm for Imaginary-Time Green's Functions.
Diksha Dhawan, D. Zgid, Mario Motta·Sep 18, 2023
Green's function methods lead to ab initio, systematically improvable simulations of molecules and materials while providing access to multiple experimentally observable properties such as the density of states and the spectral function. The calculat...
Quantum computation of π → π* and n → π* excited states of aromatic heterocycles
Maria A. Castellanos, Mario Motta, Julia E Rice·Sep 18, 2023
The computation of excited electronic states is an important application for quantum computers. In this work, we simulate the excited state spectra of four aromatic heterocycles on IBM superconducting quantum computers, focussing on active spaces of ...
Hybrid Quantum Machine Learning Assisted Classification of COVID-19 from Computed Tomography Scans
Leo Sünkel, Darya Martyniuk, Julia J. Reichwald +5 more·Sep 17, 2023
Practical quantum computing (QC) is still in its in-fancy and problems considered are usually fairly small, especially in quantum machine learning when compared to its classical counterpart. Image processing applications in particular require models ...
Physics of the Majorana superconducting qubit hybrids
D. Karki, K. A. Matveev, Ivar Martin·Sep 15, 2023
Manipulation of decoupled Majorana zero modes (MZMs) could enable topologically-protected quantum computing. However, the practical realization of a large number of perfectly decoupled MZMs needed to perform nontrivial quantum computation has proven ...
S-QGPU: Shared quantum gate processing unit for distributed quantum computing
Shengwang Du, Yufei Ding, Chunming Qiao·Sep 15, 2023
We propose a distributed quantum computing (DQC) architecture in which individual small-sized quantum computers are connected to a shared quantum gate processing unit (S-QGPU). The S-QGPU comprises a collection of hybrid two-qubit gate modules for re...
Quantum computation of thermal averages for a non-Abelian D4 lattice gauge theory via quantum Metropolis sampling
Edoardo Ballini, Giuseppe Clemente, M. D’Elia +2 more·Sep 13, 2023
In this paper, we show the application of the Quantum Metropolis Sampling (QMS) algorithm to a toy gauge theory with discrete non-Abelian gauge group $D_4$ in (2+1)-dimensions, discussing in general how some components of hybrid quantum-classical alg...
Incentivizing Demand-Side Response Through Discount Scheduling Using Hybrid Quantum Optimization
David Bucher, Jonas Nusslein, Corey O’Meara +5 more·Sep 11, 2023
Demand-side response (DSR) is a strategy that enables consumers to actively participate in managing electricity demand. It aims to alleviate strain on the grid during high demand and promote a more balanced and efficient use of (renewable) electricit...
Hybrid algorithm for the time-dependent Hartree–Fock method using the Yang–Baxter equation on quantum computers
Sahil Gulania, Stephen K. Gray, Yuri Alexeev +2 more·Sep 1, 2023
The time-dependent Hartree–Fock (TDHF) method is an approach to simulate the mean field dynamics of electrons within the assumption that the electrons move independently in their self-consistent average field and within the space of single Slater det...
Hybrid quantum neural network structures for image multi-classification
Mingrui Shi, Haozhen Situ, Cai Zhang·Aug 30, 2023
Image classification is a fundamental problem in computer vision, and neural networks provide an effective solution. With the advancement of quantum technology, quantum neural networks have attracted a lot of attention. However, they are only suitabl...
Efficient digitized counterdiabatic quantum optimization algorithm within the impulse regime for portfolio optimization
Alejandro Gomez Cadavid, I. Montalban, Archismita Dalal +2 more·Aug 29, 2023
We propose a faster digital quantum algorithm for portfolio optimization using the digitized-counterdiabatic quantum optimization (DCQO) paradigm in the impulse regime, that is, where the counterdiabatic terms are dominant. Our approach notably reduc...
Quantum Computing for Solid Mechanics and Structural Engineering - a Demonstration with Variational Quantum Eigensolver
Yunya Liu, Jiakun Liu, J. Raney +1 more·Aug 28, 2023
Variational quantum algorithms exploit the features of superposition and entanglement to optimize a cost function efficiently by manipulating the quantum states. They are suitable for noisy intermediate-scale quantum (NISQ) computers that recently be...
Quantum-Informed Recursive Optimization Algorithms
Jernej Rudi Finžgar, Aron Kerschbaumer, M. Schuetz +2 more·Aug 25, 2023
We propose and implement a family of quantum-informed recursive optimization (QIRO) algorithms for combinatorial optimization problems. Our approach leverages quantum resources to obtain information that is used in problem-specific classical reductio...