Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Upper bounding the quantum space complexity for computing class group and principal ideal problem
Iu-Iong Ng·May 21, 2024
In this paper, we calculate the upper bound on quantum space complexity of the quantum algorithms proposed by Biasse and Song (SODA'16) for solving class group computation and the principal ideal problem using the reductions to $S$-unit group computa...
Quantum Non-Identical Mean Estimation: Efficient Algorithms and Fundamental Limits
Jiachen Hu, Tongyang Li, Xinzhao Wang +3 more·May 21, 2024
We systematically investigate quantum algorithms and lower bounds for mean estimation given query access to non-identically distributed samples. On the one hand, we give quantum mean estimators with quadratic quantum speed-up given samples from diffe...
Simulating optically active spin defects with a quantum computer
Jack S. Baker, Pablo Antonio Moreno Casares, Modjtaba Shokrian Zini +5 more·May 21, 2024
There is a pressing need for more accurate computational simulations of the opto-electronic properties of defects in materials to aid in the development of quantum sensing platforms. In this work, we explore how quantum computers could be effectively...
Quantum Computing for Databases: Overview and Challenges
Gongsheng Yuan, Yuxing Chen, Jiaheng Lu +4 more·May 21, 2024
In the decades, the general field of quantum computing has experienced remarkable progress since its inception. A plethora of researchers not only proposed quantum algorithms showing the power of quantum computing but also constructed the prototype o...
Quantum Software Ecosystem Design
Achim Basermann, Michael Epping, Benedikt Fauseweh +7 more·May 21, 2024
The rapid advancements in quantum computing necessitate a scientific and rigorous approach to the construction of a corresponding software ecosystem, a topic underexplored and primed for systematic investigation. This chapter takes an important step ...
Quantum resonant dimensionality reduction
Fan Yang, Furong Wang, Xusheng Xu +4 more·May 21, 2024
Quantum computing is a promising candidate for accelerating machine learning tasks. Limited by the control accuracy of current quantum hardware, reducing the consumption of quantum resources is the key to achieving quantum advantage. Here, we propose...
Statistical Qubit Freezing Extending Physical Limit of Quantum Annealers
Jeung Rac Lee, June-Koo Kevin Rhee, Changjun Kim +1 more·May 21, 2024
Adiabatic quantum annealers encounter scalability challenges due to exponentially fast diminishing energy gaps between ground and excited states with qubit-count increase. This introduces errors in identifying ground states compounded by a thermal no...
Non-Abelian Self-Correcting Quantum Memory and Transversal Non-Clifford Gate beyond the $n^{1/3}$ Distance Barrier
Po-Shen Hsin, Ryohei Kobayashi, Guanyu Zhu·May 20, 2024
We construct a family of infinitely many new candidate non-Abelian self-correcting topological quantum memories in $D\geq 5+1$ spacetime dimensions without particle excitations using local commuting non-Pauli stabilizer lattice models and field theor...
A Study on Optimization Techniques for Variational Quantum Circuits in Reinforcement Learning
Michael Kölle, Timo Witter, Tobias Rohe +3 more·May 20, 2024
Quantum Computing aims to streamline machine learning, making it more effective with fewer trainable parameters. This reduction of parameters can speed up the learning process and reduce the use of computational resources. However, in the current pha...
An Improved Design for All-Photonic Quantum Repeaters
A. Patil, Saikat Guha·May 20, 2024
All-photonic quantum repeaters use multi-qubit photonic graph states, called repeater graph states (RGS), instead of matter-based quantum memories, for protection against predominantly loss errors. The RGS comprises tree-graph-encoded logical qubits ...
Formulation and evaluation of ocean dynamics problems as optimization problems for quantum annealing machines
Takuro Matsuta, Ryo Furue·May 20, 2024
Recent advancements in quantum computing suggest the potential to revolutionize computational algorithms across various scientific domains including oceanography and atmospheric science. The field is still relatively young and quantum computation is ...
Noise-tolerant learnability of shallow quantum circuits from statistics and the cost of quantum pseudorandomness
Chirag Wadhwa, Mina Doosti·May 20, 2024
In this work, we study the learnability of quantum circuits in the near term. We demonstrate the natural robustness of quantum statistical queries for learning quantum processes, motivating their use as a theoretical tool for near-term learning probl...
Accurate Learning of Equivariant Quantum Systems from a Single Ground State
Štěpán Šmíd, Roberto Bondesan·May 20, 2024
Predicting properties across system parameters is an important task in quantum physics, with applications ranging from molecular dynamics to variational quantum algorithms. Recently, provably efficient algorithms to solve this task for ground states ...
Property-guided inverse design of metal-organic frameworks using quantum natural language processing
Shinyoung Kang, Jihan Kim·May 20, 2024
In this study, we explore the potential of using quantum natural language processing (QNLP) for property-guided inverse design of metal-organic frameworks (MOFs) with targeted properties. Specifically, by analyzing 450 hypothetical MOF structures con...
Post-Quantum Security: Origin, Fundamentals, and Adoption
Johanna Barzen, F. Leymann·May 20, 2024
Based on Shor’s quantum algorithm for computing discrete logarithms, powerful enough quantum computers will break current cryptographic protocols. While today’s quantum computers are not yet capable enough of running this algorithm successfully, it i...
Private Delegated Quantum Computing for User-Level and Industry-Level Settings
Alejandro Mata Ali, Adriano Mauricio Lusso, Edgar Mencia·May 19, 2024
We present a modular hierarchy of private delegated quantum computation protocols tailored to user-level and industry-level settings and parameterized by the quantum resources available to the client. For each protocol, we specify the client capabili...
Shortcut to chemically accurate quantum computing via density-based basis-set correction
Diata Traore, Olivier Adjoua, C'esar Feniou +8 more·May 19, 2024
Using GPU-accelerated state-vector emulation, we propose to embed a quantum computing ansatz into density-functional theory via density-based basis-set corrections to obtain quantitative quantum-chemistry results on molecules that would otherwise req...
Quantum sampling algorithms for quantum state preparation and matrix block-encoding
Jessica Lemieux, Matteo Lostaglio, Sam Pallister +4 more·May 19, 2024
The problems of quantum state preparation and matrix block-encoding are ubiquitous in quantum computing: they are crucial parts of various quantum algorithms for the purpose for initial state preparation as well as loading problem relevant data. We f...
Disturbance Evaluation Circuit in Quantum Measurement
Haruki Emori, M. Ozawa, Akihisa Tomita·May 19, 2024
According to the uncertainty principle, every quantum measurement accompanies disturbance. In particular, accurate sequential measurements need the accurate control of disturbance. However, the correct role of disturbance in the uncertainty principle...
Spectra of noisy parameterized quantum circuits: Single-Ring universality
Kristian Wold, P. Ribeiro, S. Denisov·May 19, 2024
Random unitaries are an important resource for quantum information processing. While their universal properties have been thoroughly analyzed, it is not known what happens to these properties when the unitaries are sampled on the present-day noisy in...