24 papers · ranked by Valyu relevance
Namasi G Sankar, Georgios Miliotis, Simon Caton
Genome assembly is important in infectious disease surveillance, antimicrobial resistance monitoring, and cancer genomics. The task of reconstructing full genomic sequences from fragmented reads, can be framed as a large scale combinatorial optimisation problem. Recent advances in quantum computing have introduced new…
Josh Cudby, James Bonfield, Chenxi Zhou, Richard Durbin + 1 more
De novo genome assembly is challenging in highly repetitive regions; however, reference-guided assemblers often suffer from bias. We propose a framework for pangenome-guided sequence assembly, which can resolve short-read data in complex regions without bias towards a single reference genome. Our method frames assembly…
Edric Matwiejew, Jason Pye, Jingbo Wang
Solving optimisation problems is a promising near-term application of quantum computers. Quantum variational algorithms leverage quantum superposition and entanglement to optimise over exponentially large solution spaces using an alternating sequence of classically tunable unitaries. However, prior work has primarily…
Benjamin C. B. Symons, David Galvin, Emre Sahin, Vassil Alexandrov + 1 more
'Stefano Mensa'] Quantum computing is gaining popularity across a wide range of scientific disciplines due to its potential to solve long-standing computational problems that are considered intractable with classical computers. One promising area where quantum computing has potential is in the speed-up of NP-hard…
M.-H. Yung, J. Casanova, A. Mezzacapo, J. McClean + 3 more
'A. Aspuru-Guzik' 'E. Solano'] Over the last few decades, quantum chemistry has progressed through the development of computational methods based on modern digital computers. However, these methods can hardly fulfill the exponentially-growing resource requirements when applied to large quantum systems. As pointed out…
Edric Matwiejew, Jingbo Wang
QuOp MPI is a Python package designed for parallel simulation of quantum variational algorithms. It presents an object-orientated approach to quantum variational algorithm design and utilises MPI-parallelised sparse-matrix exponentiation, the fast Fourier transform and parallel gradient evaluation to achieve the highly…
Finley Alexander Quinton, Per Arne Sevle Myhr, Mostafa Barani, Pedro Crespo del Granado + 1 more
'Pedro Crespo del Granado' 'Hongyu Zhang'] Quantum computing is rapidly advancing, harnessing the power of qubits’ superposition and entanglement for computational advantages over classical systems. However, scalability poses a primary challenge for these machines. By implementing a hybrid workflow between classical…
N. Slate, Edric Matwiejew, S. Marsh, Jingbo Wang
This paper proposes a highly efficient quantum algorithm for portfolio optimisation targeted at near-term noisy intermediate-scale quantum computers. Recent work by Hodson et al. (2019) explored potential application of hybrid quantum-classical algorithms to the problem of financial portfolio rebalancing. In…
Tom Krüger, Wolfgang Mauerer
non-Iterative Quantum Optimisation Authors: ['Tom Krüger' 'Wolfgang Mauerer'] The Quantum Approximate Optimisation Algorithm (qaoa) is a widely studied quantum-classical iterative heuristic for combinatorial optimisation. While qaoa targets problems in complexity class NP, the classical optimisation procedure required…
Ijaz Ahamed Mohammad, Matej Pivoluska, Martin Plesch
The current state of quantum computing is commonly described as the Noisy Intermediate-Scale Quantum era. Available computers contain a few dozens of qubits and can perform a few dozens of operations before the inevitable noise erases all information encoded in the calculation. Even if the technology advances fast…
Aritra Sarkar, Zaid Al-Ars, Koen Bertels, Archana Kamal
In this article, we present QuASeR, a reference-free DNA sequence reconstruction implementation via de novo assembly on both gate-based and quantum annealing platforms. This is the first time this important application in bioinformatics is modeled using quantum computation. Each one of the four steps of the…
Authors not listed
We develop a comprehensive theoretical framework for quantum-enhanced risk modeling in financial systems, establishing mathematical foundations for representing and computing risk factors using quantum states and operations. The theory begins by formulating portfolio risk as quantum observables, where correlations…
Oscar Montiel, Yoshio Rubio, Cynthia Olvera, Ajelet Rivera
Obtaining efficient optimisation algorithms has become the focus of much research interest since current developing trends in machine learning, traffic management, and other cutting-edge applications require complex optimised models containing a huge number of parameters. At present, computers based on the classical…
Muhammad AbuGhanem
In recent years, quantum computing has made significant strides, particularly in light-based technology. The introduction of quantum photonic chips has ushered in an era marked by scalability, stability, and cost-effectiveness, paving the way for innovative possibilities within compact footprints. This article provides…
Ashar J. Malik, David B. Ascher
Accurately modelling the potential energy landscapes that govern molecular interactions is a central challenge in computational biophysics. While quantum computers promise to solve such problems with high fidelity, a key bottleneck is the encoding of complex spatial information into low-qubit Hamiltonians suitable for…
Jing-Kai Fang, Yue-Feng Lin, Jun-Han Huang, Yibo Chen + 9 more
Computational biology holds immense promise as a domain that can leverage quantum advantages due to its involvement in a wide range of challenging computational tasks. Researchers have recently explored the applications of quantum computing in genome assembly implementation. However, the issue of repetitive sequences…
Authors not listed
We present a unified theoretical framework that classifies and analyzes quantum enhancement strategies for classical algorithms, establishing design paradigms that systematically combine quantum subroutines with classical procedures. The theory identifies four fundamental enhancement mechanisms: quantum search…
Daniel Gaissmaier, Matthias van den Borg, Donato Fantauzzi, Timo Jacob
In this work, we demonstrate the superior exploration capabilities of the population-based methods over the sequential one-parameter parabolic interpolation (SOPPI) approach to optimise ReaxFF force field parameters. Evolutionary algorithms (EAs) are heuristic-based approaches using a population of concurrent models in…
Zhihao Lan, WanZhen Liang
The variational quantum eigensolver (VQE) algorithm can simulate the chemical systems such as molecules in the noisy intermediate-scale quantum devices and shows promising applications in quantum chemistry simulations. The accuracy and computational cost of the VQE simulations are determined by the underlying Ansätze.…
Authors not listed
We describe a collaborative research project spanning the disciplines of quantum hardware, quantum algorithms, conventional computational chemistry, synthetic medicinal chemistry and life sciences. Our project seeks to demonstrate an impact of quantum computing on human health. It is one of several funded by Wellcome…
Authors not listed
One of the main applications for which quantum computers are hoped to find utility is in simulating ground state energies and other observables of molecular chemical systems. The recently proposed sample-based diagonalization method is a readily implementable method for this task on current-day hardware using short…
Patrícia Verdugo Pascoal, Deborah Bambil, Luisa Mayumi Arake de Tacca, Rayane Nunes Lima + 3 more
The accelerated exploration and engineering of nucleotide sequences are directed towards quantum mechanics and their intrinsic entanglements, implementing the qubits states, including the development of algorithms. The production rate of biological sequencing data has increased to approximately 1 Gb/h, but the ability…
Patrícia Verdugo Pascoal, Deborah Bambil, Rayane N. Lima, Marco Antônio de Oliveira + 3 more
Quantum biology is an emergent field that investigates quantum-mechanical phenomena, such as superposition, tunneling, and entanglement, in the context of data manipulation from living systems. The exploration and engineering of nucleotide sequences rely on quantum mechanical principles, particularly the use of qubit…
Yifan Wu, Aron Walsh, Alex Ganose
What is the minimum number of experiments, or calculations, required to find an optimal solution? Relevant chemical problems range from identifying a compound with target functionality within a given phase space to controlling materials synthesis and device fabrication conditions. A common feature in this application…