Papers
Live trends in quantum computing research, updated daily from arXiv.
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Hardware platform mentions in abstracts — Photonic leads
Performance Study of Variational Quantum Algorithms for Solving the Poisson Equation on a Quantum Computer
Mazen Ali, M. Kabel·Nov 25, 2022
Recent advances in quantum computing and their increased availability has led to a growing interest in possible applications. Among those is the solution of partial differential equations (PDEs) for, e.g., material or flow simulation. Currently, the ...
Gradient Estimation with Constant Scaling for Hybrid Quantum Machine Learning
Thomas Hoffmann, Douglas Brown·Nov 25, 2022
We present a novel method for determining gradients of parameterised quantum circuits (PQCs) in hybrid quantum-classical machine learning models by applying the multivariate version of the simultaneous perturbation stochastic approximation (SPSA) alg...
A quantum algorithm to estimate the closeness to the Strict Avalanche criterion in Boolean functions
C. A. Jothishwaran, A. Chakraborty, V. Poonia +2 more·Nov 25, 2022
We propose a quantum algorithm (in the form of a quantum oracle) that estimates the closeness of a given Boolean function to one that satisfies the ``strict avalanche criterion'' (SAC). This algorithm requires $n$ queries of the Boolean function orac...
Efficient and fail-safe quantum algorithm for the transport equation
Merel A. Schalkers, Matthias Möller·Nov 25, 2022
We present a scalable algorithm for solving the transport equation in two and three spatial dimensions for variable grid sizes and discrete velocities on a fault-tolerant universal quantum computer. As a proof of concept of our quantum transport meth...
Two-dimensional isometric tensor networks on an infinite strip
Yantao Wu, Sajant Anand, Sheng-Hsuan Lin +2 more·Nov 25, 2022
The exact contraction of a generic two-dimensional (2D) tensor network state (TNS) is known to be exponentially hard, making simulation of 2D systems difficult. The recently introduced class of isometric TNS (isoTNS) represents a subset of TNS that a...
Unbalanced penalization: a new approach to encode inequality constraints of combinatorial problems for quantum optimization algorithms
J. A. Montañez-Barrera, Alberto Maldonado-Romo, D. Willsch +1 more·Nov 25, 2022
Solving combinatorial optimization problems of the kind that can be codified by quadratic unconstrained binary optimization (QUBO) is a promising application of quantum computation. Some problems of this class suitable for practical applications such...
Limitations of Quantum Measurements and Operations of Scattering Type under the Energy Conservation Law
Ryota Katsube, Masanao Ozawa, Masahiro Hotta·Nov 24, 2022
It is important to improve the accuracy of quantum measurements and operations both in engineering and fundamental physics. It is known, however, that the achievable accuracy of measurements and unitary operations are generally limited by conservatio...
Implicit differentiation of variational quantum algorithms
Shahnawaz Ahmed, N. Killoran, J. Álvarez·Nov 24, 2022
Several quantities important in condensed matter physics, quantum information, and quantum chemistry, as well as quantities required in meta-optimization of machine learning algorithms, can be expressed as gradients of implicitly defined functions of...
Number Theoretic Transform and Its Applications in Lattice-based Cryptosystems: A Survey
Zhichuang Liang, Yunlei Zhao·Nov 24, 2022
Number theoretic transform (NTT) is the most efficient method for multiplying two polynomials of high degree with integer coefficients, due to its series of advantages in terms of algorithm and implementation, and is consequently widely-used and part...
Electrical Control of Uniformity in Quantum Dot Devices
M. Meyer, Corentin D'eprez, Timo R van Abswoude +10 more·Nov 24, 2022
Highly uniform quantum systems are essential for the practical implementation of scalable quantum processors. While quantum dot spin qubits based on semiconductor technology are a promising platform for large-scale quantum computing, their small size...
Quantum Adversarial Learning in Emulation of Monte-Carlo Methods for Max-cut Approximation: QAOA is not optimal
Cem M. Unsal, L. Brady·Nov 24, 2022
One of the leading candidates for near-term quantum advantage is the class of Variational Quantum Algorithms, but these algorithms suffer from classical difficulty in optimizing the variational parameters as the number of parameters increases. Theref...
Race for Quantum Advantage using Random Circuit Sampling
Sangchul Oh, S. Kais·Nov 23, 2022
Random circuit sampling, the task to sample bit strings from a random unitary operator, has been performed to demonstrate quantum advantage on the Sycamore quantum processor with 53 qubits and on the Zuchongzhi quantum processor with 56 and 61 qubits...
SnCQA: A hardware-efficient equivariant quantum convolutional circuit architecture
Han Zheng, Gokul Subramanian Ravi, Hanrui Wang +3 more·Nov 23, 2022
We propose SnCQA, a set of hardware-efficient variational circuits of equivariant quantum convolutional circuits respective to permutation symmetries and spatial lattice symmetries with the number of qubits n. By exploiting permutation symmetries of ...
Software for Massively Parallel Quantum Computing
Thien Nguyen, Daanish Arya, M. Doherty +5 more·Nov 23, 2022
Quantum computing has the potential to offer substantial computational advantages over conventional computing. Recent advances in quantum computing hardware and algorithms have enabled a class of classically parallel quantum workloads, whereby indivi...
Faster Stochastic First-Order Method for Maximum-Likelihood Quantum State Tomography
C. Tsai, Hao-Chung Cheng, Yen-Huan Li·Nov 23, 2022
In maximum-likelihood quantum state tomography, both the sample size and dimension grow exponentially with the number of qubits. It is therefore desirable to develop a stochastic first-order method, just like stochastic gradient descent for modern ma...
A didactic approach to quantum machine learning with a single qubit
Elena Peña Tapia, G. Scarpa, Alejandro Pozas-Kerstjens·Nov 23, 2022
This paper presents, via an explicit example with a real-world dataset, a hands-on introduction to the field of quantum machine learning (QML). We focus on the case of learning with a single qubit, using data re-uploading techniques. After a discussi...
Approximate complex amplitude encoding algorithm and its application to data classification problems
Naoki Mitsuda, Tatsuhiro Ichimura, Kouhei Nakaji +6 more·Nov 23, 2022
Quantum computing has a potential to accelerate the data processing efficiency, especially in machine learning, by exploiting special features such as the quantum interference. The major challenge in this application is that, in general, the task of ...
The NISQ Complexity of Collision Finding
Yassine Hamoudi, Qipeng Liu, Makrand Sinha·Nov 23, 2022
Collision-resistant hashing, a fundamental primitive in modern cryptography, ensures that there is no efficient way to find distinct inputs that produce the same hash value. This property underpins the security of various cryptographic applications, ...
Benchmarking Adversarially Robust Quantum Machine Learning at Scale
Maxwell T. West, S. Erfani, C. Leckie +3 more·Nov 23, 2022
Machine learning (ML) methods such as artificial neural networks are rapidly becoming ubiquitous in modern science, technology and industry. Despite their accuracy and sophistication, neural networks can be easily fooled by carefully designed malicio...
Using a quantum computer to solve a real-world problem -- what can be achieved today?
R. Cumming, Tim Thomas·Nov 23, 2022
Quantum computing is an important developing technology with the potential to revolutionise the landscape of scientific and business problems that can be practically addressed. The widespread excitement derives from the potential for a fault tolerant...