Search · four archives
Search · four archives
23 papers · ranked by Valyu relevance
Patrick Hopf, Nils Quetschlich, Laura Schulz, Robert Wille
—Quantum computing is an emerging technology that has seen significant software and hardware improvements in recent years. Executing a quantum program requires the compilation of its quantum circuit for a target Quantum Processing Unit (QPU). Various methods for qubit mapping, gate synthesis, and optimization of…
Hong-Ze Xu, Xu-Dan Chai, Meng-Jun Hu, Zheng-An Wang + 10 more
As quantum computing systems continue to scale up and become more clustered, efficiently compiling user quantum programs into high-fidelity executable sequences on real hardware remains a key challenge for current quantum compilation systems. In this study, we introduce a system-software framework that integrates…
Robert Wille, Lucas Berent, Tobias Förster, Jagatheesan Kunasaikaran + 9 more
Quantum Computing Authors: ['Robert Wille' 'Lucas Berent' 'Tobias Förster' 'Jagatheesan Kunasaikaran' 'Kevin Mato' 'Tom Peham' 'Nils Quetschlich' 'Damian Rovara' 'Aaron Sander' 'L. Schmid' 'Daniel Schönberger' 'Yannick Stade' 'Lukas Burgholzer'] Quantum computers are becoming a reality and numerous quantum computing…
Daniel Volya, Prabhat Mishra
—Qudit-based quantum computation offers unique advantages over qubit-based systems in terms of noise mitigation capabilities as well as algorithmic complexity improvements. However, the software ecosystem for multi-state quantum systems is severely limited. In this paper, we highlight a quantum workflow for describing…
Soshun Naito, Yoshihiko Hasegawa, Yoshiki Matsuda, Shu Tanaka
It is imperative to compile quantum circuits for Noisy Intermediate-Scale Quantum (NISQ) devices because of the limited connectivity of physical qubits and the high error rates of gate operations. One of the most critical steps in quantum circuit compilation is qubit routing, an NP-Hard problem that involves placing…
Nils Quetschlich, Lukas Burgholzer, Robert Wille
—In order to implement a quantum computing application, problem instances must be encoded into a quantum circuit and then compiled for a specific platform. The lengthy compilation process is a key bottleneck in this workflow, especially for problems that arise repeatedly with a similar yet distinct structure (each of…
Davide Ferrari, Ivano Tavernelli, Michele Amoretti
Current quantum processors are noisy, have limited coherence and imperfect gate implementations. On such hardware, only algorithms that are shorter than the overall coherence time can be implemented and executed successfully. A good quantum compiler must translate an input program into the most efficient equivalent of…
Zheng Shan, Yu Zhu, Bo Zhao
Quantum computers have already shown significant potential to solve specific problems more efficiently than conventional supercomputers. A major challenge towards noisy intermediate-scale quantum computing is characterizing and reducing the various control costs. Quantum programming describes the process of quantum…
Sebastian Brandhofer, Ilia Polian, Stefanie Barz, Daniel Bhatti
Highly entangled quantum states are an ingredient in numerous applications in quantum computing. However, preparing these highly entangled quantum states on currently available quantum computers at high fidelity is limited by ubiquitous errors. Besides improving the underlying technology of a quantum computer, the…
Madhav Krishnan Vijayan, Alexandru Paler, Jason Gavriel, Casey R. Myers + 2 more
'Casey R. Myers' 'Peter P. Rohde' 'Simon J. Devitt'] We present a quantum circuit compiler that prepares an algorithm-specific graph state from quantum circuits described in high level languages, such as Cirq and Q#. The computation can then be implemented using a series of non-Pauli measurements on this graph state.…
Vu Tuan Hai, Le Bin Ho
Universal compilation is a training process that compiles a trainable unitary into a target unitary. It has vast potential applications from depth-circuit compressing to device benchmarking and quantum error mitigation. Here we propose a universal compilation algorithm for quantum state tomography in low-depth quantum…
Hui Liu, Bingjie Zhang, Yu Zhu, Hanxiao Yang + 1 more
Quantum computing has already demonstrated great computational potential across multiple domains and has received more and more attention. However, due to the connectivity limitations of Noisy Intermediate-Scale Quantum (NISQ) devices, most of the quantum algorithms cannot be directly executed without the help of…
Debarshi Kundu, Archisman Ghosh, Srinivasan Ekambaram, Jian Wang + 2 more
Computational methods in drug discovery significantly reduce both time and experimental costs. Nonetheless, certain computational tasks in drug discovery can be daunting with classical computing techniques which can be potentially overcome using quantum computing. A crucial task within this domain involves the…
Edward Otieno, Katarzyna Matczyszyn, Nelson Mokaya
Quantum computing promises exponential advances in information processing, necessitating the development of appropriate materials for implementing quantum qubits and gates. Liquid crystals, known for their electro-optical characteristics and use in displays, have recently received attention as prospective candidates…
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.…
Rania Derouich, Nour El Houda Mathlouthi
We present the first systematic, hardware-executed benchmark of twelve distinct quantum data-encoding strategies for drug-response prediction on a real superconducting quantum processing unit (QPU). All experiments were conducted on the IQM Garnet 20-qubit QPU via the IQM Resonance cloud platform, using the Qrisp…
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Strong coupling and environmental memory render many open quantum systems intractable to classical computation. To overcome this barrier, we present a variational quantum algorithm capable of solving generalized form time-local quantum master equations directly on Noisy Intermediate-Scale Quantum (NISQ) processors. Our…
Weitang Li, Zhi Yin, Xiaoran Li, Dongqiang Ma + 8 more
Quantum computing, with its superior computational capabilities compared to classical approaches, holds the potential to revolutionize numerous scientific domains, including pharmaceuticals. However, the application of quantum computing for drug discovery has primarily been limited to proof-of-concept studies, which…
Azamat Salamatov, Gowtham Atluri
How long a drug stays bound to its target-the residence time - is now recognized as a stronger in vivo efficacy driver than binding affinity alone. Yet current machine learning (ML) models for dissociation kinetics (koff) ignore two critical sources of structure information: (1) the change in protein–ligand geometry…
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This work provides a rigorous theoretical investigation of selective error correction strategies for variational quantum algorithms, with focus on understanding the interplay between error suppression, circuit trainability, and computational resource requirements. We develop a mathematical framework that characterizes…
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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…
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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…
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Computational chemistry has entered a new era where machine learning (ML) models—particularly graph neural networks and machine learning force fields—routinely deliver quantum mechanical accuracy at classical speeds, scaling to millions of atoms and reshaping workflows in drug discovery, catalysis, and materials…