About this Research Topic
Quantum computation and simulation represent a cutting-edge field in modern physics and computer science, focusing on leveraging quantum phenomena such as superposition and entanglement to achieve computational capabilities far beyond classical systems. Superposition allows quantum states to process information in parallel, while entanglement provides stronger correlations among multiple measurement outcomes, enabling true parallel computational power. Recent advancements in noisy intermediate-scale quantum (NISQ) devices have shown promising prototype demonstrations of quantum algorithms using a few dozen physical qubits, hinting at practical quantum advantages. Despite these strides, significant gaps remain in fully understanding and harnessing these phenomena, particularly in the context of error correction and scalability. Addressing these gaps is crucial for advancing towards fully fault-tolerant quantum computers capable of simulating larger quantum systems and achieving quantum breakthroughs.
This Research Topic aims to explore the latest research ideas and state-of-the-art developments in quantum computation and simulation, particularly within the context of NISQ machines. The primary objectives include investigating how quantum algorithms can be effectively implemented on NISQ devices, understanding the limitations and potential of these systems, and developing methods to mitigate errors. Specific questions to be addressed include: How can we optimize quantum algorithms for NISQ devices? What are the most effective error-correction techniques for these systems? How can we leverage NISQ devices to simulate complex quantum systems in fields such as chemistry and high-energy physics?
To gather further insights into the boundaries of quantum computation and simulation in NISQ machines, we welcome articles addressing, but not limited to, the following themes:
- Quantum computation in NISQ systems
- Error-correctable quantum computation
- Variational quantum algorithms on quantum computers
- Demonstration of superconducting, photonic, and ion-trap quantum computing
- Analog quantum simulation in noisy models
- Error-mitigated quantum simulation on NISQ computers
- Quantum simulation for many-body and/or high-energy physics
- NISQ simulation of chemical and biological structures
This Research Topic aims to explore the latest research ideas and state-of-the-art developments in quantum computation and simulation, particularly within the context of NISQ machines. The primary objectives include investigating how quantum algorithms can be effectively implemented on NISQ devices, understanding the limitations and potential of these systems, and developing methods to mitigate errors. Specific questions to be addressed include: How can we optimize quantum algorithms for NISQ devices? What are the most effective error-correction techniques for these systems? How can we leverage NISQ devices to simulate complex quantum systems in fields such as chemistry and high-energy physics?
To gather further insights into the boundaries of quantum computation and simulation in NISQ machines, we welcome articles addressing, but not limited to, the following themes:
- Quantum computation in NISQ systems
- Error-correctable quantum computation
- Variational quantum algorithms on quantum computers
- Demonstration of superconducting, photonic, and ion-trap quantum computing
- Analog quantum simulation in noisy models
- Error-mitigated quantum simulation on NISQ computers
- Quantum simulation for many-body and/or high-energy physics
- NISQ simulation of chemical and biological structures
Keywords: Quantum Computation, Quantum Simulation, Noisy Intermediate-Scale Quantum (NISQ), Quantum Algorithm, Quantum Information Theory
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
