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.
Projectdetails
Introduction
This project sets out to assess, make use of, and verify the computational power of realistic quantum devices. It comprehensively identifies quantum simulators and paradigmatic quantum devices that are computationally superior to classical supercomputers, based on presently available or plausible physical architectures.
Quantum Advantage Exploration
In doing so, it explores the fine line that discriminates regimes featuring a quantum advantage from ones that are accessible to efficient classical simulation. This naturally two-pronged approach is concerned with:
-
Novel Classical Simulation Tools
- Developing tools for seemingly deeply quantum prescriptions.
- Identifying limitations of variational approaches and quantum simulation schemes.
-
New Applications of Quantum Devices
- Identifying practically minded applications of quantum devices that exhibit a computational speed-up over classical machines.
- Exploring potentially game-changing applications emerging for learning tasks.
Methodology
To achieve this goal, the project digs deeply into computer science, which provides sophisticated tools of computational complexity and machine learning. This is instrumental in devising methods for the classical simulation of intricate quantum problems.
At the same time, it draws on the physics of complex systems.
Interdisciplinary Effort
This proposal suggests an interdisciplinary effort by bringing together ideas from:
- Quantum information
- Condensed matter physics
- Complexity theory
- Machine learning
- Tensor network theory
- Methods that are unusual in this context, such as signal processing
Individually, each objective substantially advances the respective field, but it is their combination that will permit a true breakthrough by delineating the delicate boundary between quantum and classical computations of synthetic quantum devices.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 1.807.721 |
Totale projectbegroting | € 1.807.721 |
Tijdlijn
Startdatum | 1-1-2024 |
Einddatum | 31-12-2028 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- FREIE UNIVERSITAET BERLINpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
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Verifiying Noisy Quantum Devices at ScaleThis project aims to develop scalable, secure methods for characterizing and certifying quantum devices using interactive proofs, facilitating reliable quantum computation and communication. | ERC Consolid... | € 1.997.250 | 2023 | Details |
Quantum Synthetic Models for Entangled Matter Out of EquilibriumThis project aims to identify and characterize new phases of matter exclusive to NISQ devices by studying quantum circuits and cellular automata, enhancing understanding of many-body physics. | ERC Starting... | € 1.405.750 | 2024 | Details |
Artificial Scientific Discovery of advanced Quantum Hardware with high-performance SimulatorsARTDISQ 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. | ERC Starting... | € 1.499.221 | 2025 | Details |
quantum-enhanced shadows: scalable quantum-to-classical convertersThis project aims to enhance quantum experiments by developing quantum-to-classical converters, enabling efficient data processing and learning through a unified framework that addresses scalability issues. | ERC Starting... | € 1.500.000 | 2024 | Details |
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.
Verifiying Noisy Quantum Devices at Scale
This project aims to develop scalable, secure methods for characterizing and certifying quantum devices using interactive proofs, facilitating reliable quantum computation and communication.
Quantum Synthetic Models for Entangled Matter Out of Equilibrium
This project aims to identify and characterize new phases of matter exclusive to NISQ devices by studying quantum circuits and cellular automata, enhancing understanding of many-body physics.
Artificial 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.
quantum-enhanced shadows: scalable quantum-to-classical converters
This project aims to enhance quantum experiments by developing quantum-to-classical converters, enabling efficient data processing and learning through a unified framework that addresses scalability issues.
Vergelijkbare projecten uit andere regelingen
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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 |
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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 |
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.
QUantum reservoir cOmputing based on eNgineered DEfect NetworkS in trAnsition meTal dichalcogEnides
This project aims to develop a proof-of-concept for Quantum Reservoir Computing using Quantum Materials defects to create advanced computing devices and enhance Quantum Technologies.
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.