SubsidieMeestersArtificial Scientific Discovery of advanced Quantum Hardware with high-performance Simulators
ARTDISQ aims to leverage AI and high-performance simulators to automate the design of advanced quantum experiments, enhancing discoveries in gravitational wave detection and imaging systems.
Projectdetails
Introduction
The experimental capabilities to generate, control, and measure complex quantum systems have dramatically improved over the last few years. With ingenious proposals for practical applications, a powerful new paradigm of technology emerges that exploits quantum superposition and quantum entanglement.
As these systems get more advanced, designing new quantum experiments and hardware becomes ever more intricate for human scientists. To exploit the full potential of quantum physics, researchers have started to involve artificial intelligence in the automated design of quantum experiments. Unfortunately, even the currently most powerful methodologies have severe limitations and therefore cannot cope with the enormous potential that quantum mechanics promises us.
Project Proposal
For that reason, in ARTDISQ, I propose to build high-performance physical simulators which are at the heart of all AI-driven discovery and design efforts. The key idea is to use a framework originally developed for the efficient training and execution of large neural networks, called JAX.
JAX Framework
JAX is powerful enough to encode not only neural networks but a wide range of computer algorithms. It allows for modern high-performance computational techniques such as:
- Just-in-time compilation
- Auto-differentiation
- Direct access to the GPU
In ARTDISQ, I will exploit this dramatic acceleration, which will open previously unchartered applications, including AI-driven:
- Design of highly sensitive and robust quantum-enhanced gravitational wave detectors
- Design of new quantum techniques for imaging systems, with a focus on optical telescopes
- Hardware-software co-design for quantum hardware with the potential of discovering highly unorthodox and exotic solutions with superior behavior.
Conclusion
As such, ARTDISQ aims to develop a revolutionary way to augment human researchers' ingenuity and creativity to accelerate scientific discoveries.
Financiële details & Tijdlijn
Financiële details
| Subsidiebedrag | € 1.499.221 |
| Totale projectbegroting | € 1.499.221 |
Tijdlijn
| Startdatum | 1-1-2025 |
| Einddatum | 31-12-2029 |
| Subsidiejaar | 2025 |
Partners & Locaties
Projectpartners
- MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EVpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
| Project | Regeling | Bedrag | Jaar | Actie |
|---|---|---|---|---|
Delineating the boundary between the computational power of quantum and classical devicesThis project aims to assess and leverage the computational power of quantum devices, identifying their advantages over classical supercomputers through interdisciplinary methods in quantum information and machine learning. | ERC Advanced... | € 1.807.721 | 2024 | Details |
FIrst NEar-TErm ApplicationS of QUAntum DevicesFINE-TEA-SQUAD aims to create a unifying framework for practical NISQ device applications by developing scalable protocols, certification tools, and a quantum network to enhance performance. | ERC Starting... | € 1.485.042 | 2022 | Details |
Beyond-classical Machine learning and AI for Quantum PhysicsThis project aims to identify quantum many-body problems with significant advantages over classical methods and develop new quantum machine learning techniques to solve them effectively. | ERC Consolid... | € 1.995.289 | 2024 | Details |
New superconducting quantum-electric device concept utilizing increased anharmonicity, simple structure, and insensitivity to charge and flux noiseConceptQ aims to develop a novel superconducting qubit with high fidelity and power efficiency, enhancing quantum computing and enabling breakthroughs in various scientific applications. | ERC Advanced... | € 2.498.759 | 2022 | Details |
Quantum Information Processing in High-Dimensional Ion Trap SystemsThis project aims to develop a trapped-ion quantum processor utilizing multi-level qudits to enhance quantum information processing and achieve quantum advantage over classical systems. | ERC Starting... | € 1.499.790 | 2023 | Details |
Delineating the boundary between the computational power of quantum and classical devices
This project aims to assess and leverage the computational power of quantum devices, identifying their advantages over classical supercomputers through interdisciplinary methods in quantum information and machine learning.
FIrst NEar-TErm ApplicationS of QUAntum Devices
FINE-TEA-SQUAD aims to create a unifying framework for practical NISQ device applications by developing scalable protocols, certification tools, and a quantum network to enhance performance.
Beyond-classical Machine learning and AI for Quantum Physics
This project aims to identify quantum many-body problems with significant advantages over classical methods and develop new quantum machine learning techniques to solve them effectively.
New superconducting quantum-electric device concept utilizing increased anharmonicity, simple structure, and insensitivity to charge and flux noise
ConceptQ aims to develop a novel superconducting qubit with high fidelity and power efficiency, enhancing quantum computing and enabling breakthroughs in various scientific applications.
Quantum Information Processing in High-Dimensional Ion Trap Systems
This project aims to develop a trapped-ion quantum processor utilizing multi-level qudits to enhance quantum information processing and achieve quantum advantage over classical systems.
Vergelijkbare projecten uit andere regelingen
| Project | Regeling | Bedrag | Jaar | Actie |
|---|---|---|---|---|
Spatial Quantum Optical Annealer for Spin HamiltoniansHEISINGBERG aims to enhance a spatial photonic spin simulator with squeezed light to achieve quantum advantage, enabling efficient solutions for NP-hard problems via advanced algorithms. | EIC Pathfinder | € 3.260.250 | 2023 | Details |
Quantum Generative Adversarial Networks with phoTonic Integrated Circuits (QuGANTIC)QuGANTIC aims to develop a scalable quantum computer using quDits on a photonic integrated chip to enhance data processing for critical global challenges, outperforming classical systems. | EIC Pathfinder | € 3.194.262 | 2023 | Details |
SCALABLE MULTI-CHIP QUANTUM ARCHITECTURES ENABLED BY CRYOGENIC WIRELESS / QUANTUM -COHERENT NETWORK-IN PACKAGEThe QUADRATURE project aims to develop scalable quantum computing architectures with distributed quantum cores and integrated wireless links to enhance performance and support diverse quantum algorithms. | EIC Pathfinder | € 3.420.513 | 2023 | Details |
Enabling efficient computation on fault tolerant quantum computersDevelop a suite of hardware-agnostic quantum algorithms to optimize quantum circuits, enabling faster solutions to complex business problems beyond classical computing capabilities. | EIC Accelerator | € 2.499.999 | 2023 | Details |
Scalable Hardware for Large-Scale Quantum ComputingDeveloping a scalable, fault-tolerant quantum computer using advanced cryo-CMOS technology to enhance precision and efficiency in processing complex data across various fields. | EIC Transition | € 2.499.998 | 2023 | Details |
Spatial Quantum Optical Annealer for Spin Hamiltonians
HEISINGBERG aims to enhance a spatial photonic spin simulator with squeezed light to achieve quantum advantage, enabling efficient solutions for NP-hard problems via advanced algorithms.
Quantum Generative Adversarial Networks with phoTonic Integrated Circuits (QuGANTIC)
QuGANTIC aims to develop a scalable quantum computer using quDits on a photonic integrated chip to enhance data processing for critical global challenges, outperforming classical systems.
SCALABLE MULTI-CHIP QUANTUM ARCHITECTURES ENABLED BY CRYOGENIC WIRELESS / QUANTUM -COHERENT NETWORK-IN PACKAGE
The QUADRATURE project aims to develop scalable quantum computing architectures with distributed quantum cores and integrated wireless links to enhance performance and support diverse quantum algorithms.
Enabling efficient computation on fault tolerant quantum computers
Develop a suite of hardware-agnostic quantum algorithms to optimize quantum circuits, enabling faster solutions to complex business problems beyond classical computing capabilities.
Scalable Hardware for Large-Scale Quantum Computing
Developing a scalable, fault-tolerant quantum computer using advanced cryo-CMOS technology to enhance precision and efficiency in processing complex data across various fields.