Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
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 ...
Optimistic Entanglement Purification in Quantum Networks
Mohammad Mobayenjarihani, Gayane Vardoyan, Donald F. Towsley·Sep 17, 2023
Noise and photon loss encountered on quantum channels pose a major challenge for reliable entanglement generation in quantum networks. In near-term networks, heralding is required to inform endpoints of successfully generated entanglement. If after h...
Quantum Simulations for Carbon Capture on Metal-Organic Frameworks
Gopal Ramesh Dahale·Sep 17, 2023
Direct air capture of Carbon Dioxide is a technical solution that does not rely on natural processes to capture CO2 from the atmosphere. In DAC, the filter material is designed to specifically bind CO2 molecules. Hence a high-capacity filter is sough...
Computational capabilities and compiler development for neutral atom quantum processors—connecting tool developers and hardware experts
Ludwig Schmid, David F. Locher, M. Rispler +4 more·Sep 15, 2023
Neutral Atom Quantum Computing (NAQC) emerges as a promising hardware platform primarily due to its long coherence times and scalability. Additionally, NAQC offers computational advantages encompassing potential long-range connectivity, native multi-...
Quantum Machine Learning in the Cognitive Domain: Alzheimer's Disease Study
Emine Akpinar·Sep 15, 2023
Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder, primarily affecting the elderly population and leading to significant cognitive decline. This decline manifests in various mental faculties such as attention, memory, and high...
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 ...
Implementing fault-tolerant non-Clifford gates using the [[8,3,2]] color code
Daniel Honciuc Menendez, A. Ray, M. Vasmer·Sep 15, 2023
Quantum computers promise to solve problems that are intractable for classical computers, but qubits are vulnerable to many sources of error, limiting the depth of the circuits that can be reliably executed on today's quantum hardware. Quantum error ...
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...
Postprocessing Variationally Scheduled Quantum Algorithm for Constrained Combinatorial Optimization Problems
T. Shirai, N. Togawa·Sep 15, 2023
In this article, we propose a postprocessing variationally scheduled quantum algorithm (pVSQA) for solving constrained combinatorial optimization problems (COPs). COPs are typically transformed into ground-state search problems of the Ising model on ...
Benchmarking machine learning models for quantum state classification
Edoardo Pedicillo, Andrea Pasquale, S. Carrazza·Sep 14, 2023
Quantum computing is a growing field where the information is processed by two-levels quantum states known as qubits. Current physical realizations of qubits require a careful calibration, composed by different experiments, due to noise and decoheren...
Mitigating controller noise in quantum gates using optimal control theory
Aviv Aroch, R. Kosloff, S. Kallush·Sep 14, 2023
All quantum systems are subject to noise from the environment or external controls. This noise is a major obstacle to the realization of quantum technology. For example, noise limits the fidelity of quantum gates. Employing optimal control theory, we...
Overhead-constrained circuit knitting for variational quantum dynamics
G. Gentinetta, Friederike Metz, Giuseppe Carleo·Sep 14, 2023
Simulating the dynamics of large quantum systems is a formidable yet vital pursuit for obtaining a deeper understanding of quantum mechanical phenomena. While quantum computers hold great promise for speeding up such simulations, their practical appl...
All you need is spin: SU(2) equivariant variational quantum circuits based on spin networks
Richard D. P. East, Guillermo Alonso-Linaje, Chae-Yeun Park·Sep 13, 2023
Variational algorithms require architectures that naturally constrain the optimization space to run efficiently. Geometric quantum machine learning achieves this goal by encoding group structure into parameterized quantum circuits to include the symm...
Entanglement of Sections: The pushout of entangled and parameterized quantum information
Hisham Sati, Urs Schreiber·Sep 13, 2023
A question raised by Freedman & Hastings (2023) still stands: To produce a mathematical theory that would unify quantum entanglement/tensor-structure with parameterized/bundle-structure via their amalgamation (a hypothetical pushout) along bare quant...
Fast Flux-Activated Leakage Reduction for Superconducting Quantum Circuits.
N. Lacroix, Luca Hofele, A. Remm +14 more·Sep 13, 2023
Quantum computers will require quantum error correction to reach the low error rates necessary for solving problems that surpass the capabilities of conventional computers. One of the dominant errors limiting the performance of quantum error correcti...
Analysis of Superconducting Qubit Layouts Using InductEx
Sean Crowe, Benjamin J. Taylor, Nicholas B. Ferrante +2 more·Sep 13, 2023
InductEx [1] is a software tool used for the analysis of integrated circuit designs and extraction of design parameters by way of numerical electromagnetic field solving. This tool was originally developed with Rapid Single Flux Quantum (RSFQ) chips ...
Predicting Expressibility of Parameterized Quantum Circuits Using Graph Neural Network
Shamminuj Aktar, Andreas Bärtschi, Abdel-Hameed A. Badawy +2 more·Sep 13, 2023
Parameterized Quantum Circuits (PQCs) are essential to quantum machine learning and optimization algorithms. The expressibility of PQCs, which measures their ability to represent a wide range of quantum states, is a critical factor influencing their ...
Interconnect Fabrics for Multi-Core Quantum Processors: A Context Analysis
Pau Escofet, Sahar Ben Rached, Santiago Rodrigo +3 more·Sep 13, 2023
Quantum computing has revolutionized the field of computer science with its extraordinary ability to handle classically intractable problems. To realize its potential, however, quantum computers need to scale to millions of qubits, a feat that will r...
Parity Measurements using Dispersive Shifts for Surface Codes
Aneirin J. Baker·Sep 13, 2023
Parity measurements are central to quantum error correction (QEC). In current implementations measurements of stabilizers are performed using a number of Controlled Not (CNOT) gates. This implementation suffers from an exponential decrease in fidelit...
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...