Papers
Live trends in quantum computing research, updated daily from arXiv.
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Hardware platform mentions in abstracts — Photonic leads
Schrödingerisation based computationally stable algorithms for ill-posed problems in partial differential equations
Shi Jin, Nana Liu, Chuwen Ma·Mar 28, 2024
We introduce a simple and stable computational method for ill-posed partial differential equation (PDE) problems. The method is based on Schr\"odingerization, introduced in [S. Jin, N. Liu and Y. Yu, arXiv:2212.13969][S. Jin, N. Liu and Y. Yu, Phys. ...
Theory of quantum error mitigation for non-Clifford gates
David Layden, Bradley Mitchell, Karthik Siva·Mar 27, 2024
Quantum error mitigation techniques mimic noiseless quantum circuits by running several related noisy circuits and combining their outputs in particular ways. How well such techniques work is thought to depend strongly on how noisy the underlying gat...
Optimal Coherent Quantum Phase Estimation via Tapering
Dhrumil Patel, Shi Jie Samuel Tan, Yigit Subasi +1 more·Mar 27, 2024
Due to its significance as a subroutine, in this work, we consider the coherent version of the quantum phase estimation problem, where given an arbitrary input state and black-box access to unitaries $U$ and controlled-$U$, the goal is to estimate th...
qIoV: A Quantum-Driven Internet-of-Vehicles-Based Approach for Environmental Monitoring and Rapid Response Systems
Ankur Nahar, Koustav Kumar Mondal, Debasis Das +1 more·Mar 27, 2024
This research addresses the critical necessity for advanced rapid response operations in managing a spectrum of environmental hazards. We propose a novel framework, qIoV that integrates quantum computing with the Internet-of-Vehicles (IoV) to leverag...
Quantum-to-Classical Neural Network Transfer Learning Applied to Drug Toxicity Prediction.
Anthony M. Smaldone, Victor S. Batista·Mar 27, 2024
Toxicity is a roadblock that prevents an inordinate number of drugs from being used in potentially life-saving applications. Deep learning provides a promising solution to finding ideal drug candidates; however, the vastness of chemical space coupled...
Efficient generation of multi-partite entanglement between non-local superconducting qubits using classical feedback
A. Hashim, Ming Yuan, P. Gokhale +8 more·Mar 27, 2024
Quantum entanglement is one of the primary features which distinguish quantum computers from classical computers. In gate-based quantum computing, the creation of entangled states or the distribution of entanglement across a quantum processor often r...
Effective Embedding of Integer Linear Inequalities for Variational Quantum Algorithms
Maximilian Hess, Lilly Palackal, Abhishek Awasthi +1 more·Mar 27, 2024
In variational quantum algorithms, constraints are usually added to the problem objective via penalty terms. Already for linear inequality constraints, this procedure requires additional slack qubits. These extra qubits tend to blow up the search spa...
A Quantum Fuzzy-based Approach for Real-Time Detection of Solar Coronal Holes
Sanmoy Bandyopadhyay, Suman Kundu·Mar 27, 2024
The detection and analysis of the solar coronal holes (CHs) is an important field of study in the domain of solar physics. Mainly, it is required for the proper prediction of the geomagnetic storms which directly or indirectly affect various space an...
On the Communication Complexity of Approximate Pattern Matching
Tomasz Kociumaka, Jakob Nogler, Philip Wellnitz·Mar 27, 2024
The decades-old Pattern Matching with Edits problem, given a length-n string T (the text), a length-m string P (the pattern), and a positive integer k (the threshold), asks to list all fragments of T that are at edit distance at most k from P. The on...
Leveraging Quantum Superposition to Infer the Dynamic Behavior of a Spatial-Temporal Neural Network Signaling Model
G. A. Silva·Mar 27, 2024
The exploration of new problem classes for quantum computation is an active area of research. In this paper, we introduce and solve a novel problem class related to dynamics on large-scale networks relevant to neurobiology and machine learning. Speci...
Benchmarking Quantum Generative Learning: A Study on Scalability and Noise Resilience using QUARK
Florian J. Kiwit, Maximilian A. Wolf, M. Marso +4 more·Mar 27, 2024
Quantum computing promises a disruptive impact on machine learning algorithms, taking advantage of the exponentially large Hilbert space available. However, it is not clear how to scale quantum machine learning (QML) to industrial-level applications....
Modelling the Impact of Quantum Circuit Imperfections on Networks and Computer Applications
S. Glisic·Mar 27, 2024
Post Quantum and Quantum Cryptography schemes are feasible quantum computer applications for 7G networks. These schemes could possibly replace existing schemes. These algorithms have been compromised by advances in quantum search algorithms run on qu...
An experimentally validated feasible quantum protocol for identity-based signature
Tapaswini Mohanty, Vikas Srivastava, S. Debnath +3 more·Mar 27, 2024
Digital signatures are one of the most basic cryptographic building blocks, which are utilized to provide attractive security features such as authenticity, unforgeability, and undeniability. To make public key infrastructure more simple and to circu...
Molecular groundstate determination via short pulses on superconducting qubits
Noga Entin, Mor M. Roses, Reuven Cohen +2 more·Mar 26, 2024
Quantum computing is currently hindered by hardware noise. We present a freestyle superconducting pulse optimization method, incorporating two-qubit channels, which enhances flexibility, execution speed, and noise resilience. A minimal 0.22 ns pulse ...
Comment on “Recovering noise-free quantum observables”
Josu Etxezarreta Martinez, Olatz Sanz Larrarte, Javier Oliva del Moral +2 more·Mar 26, 2024
Zero-noise extrapolation (ZNE) stands as the most widespread quantum error mitigation technique used in the recovery of noise-free expectation values of observables of interest by means of noisy intermediate-scale quantum (NISQ) machines. Recently, O...
Quadratic Speed‐ups in Quantum Kernelized Binary Classification
Jungyun Lee, Daniel K. Park·Mar 26, 2024
Classification is at the core of data‐driven prediction and decision‐making, representing a fundamental task in supervised machine learning. Recently, several quantum machine learning algorithms that use quantum kernels as a measure of similarities b...
Fast quantum integer multiplication with zero ancillas
Gregory D. Kahanamoku-Meyer, N. Yao·Mar 26, 2024
The multiplication of superpositions of numbers is a core operation in many quantum algorithms. The standard method for multiplication (both classical and quantum) has a runtime quadratic in the size of the inputs. Quantum circuits with asymptoticall...
Quantum Optimization for the Future Energy Grid: Summary and Quantum Utility Prospects
Jonas Blenninger, David Bucher, G. Cortiana +6 more·Mar 26, 2024
In this project summary paper, we summarize the key results and use-cases explored in the German Federal Ministry of Education and Research (BMBF) funded project"Q-GRID"which aims to assess potential quantum utility optimization applications in the e...
EinExprs: Contraction Paths of Tensor Networks as Symbolic Expressions
Sergio Sánchez Ramírez, Jofre Vallès-Muns, Artur García-Sáez·Mar 26, 2024
Tensor Networks are graph representations of summation expressions in which vertices represent tensors and edges represent tensor indices or vector spaces. In this work, we present EinExprs.jl, a Julia package for contraction path optimization that o...
Quantum accelerated cross regression algorithm for multiview feature extraction
Hailing Liu, Yaqian Zhao, Ren-Gang Li +1 more·Mar 26, 2024
Multi-view Feature Extraction (MvFE) has wide applications in machine learning, image processing and other fields. When dealing with massive high-dimensional data, the performance of classical computer faces severe challenges due to MvFE involves exp...