📋 Tender Overview
Optoelectronic And All-Optical Hyperspin Machines For Large-Scale Computing
Efficient Hardware For Combinatorial Optimization And Machine Learning Impacts Science, Engineering, And Society. With New Computational Models, Photonics Tackle Problems Intractable With Conventional Computing Systems. However, Existing Devices Only Scale Up To Thousands Of Spins And Operate At The Second Timescale.
I Demonstrate Photonic Machines For Ultrafast Parallel Processing Of Millions Of Spins With Microsecond Timescale. The Strategy Is Minimizing A Class Of Functions, The Ising Hamiltonian, By A New Computational System That Uses A High-Dimensional Feature Space And Speeds Up Optimization By Orders Of Magnitude By Ultrafast Nonlinear Optical Processes. I Build Digital, Optoelectronics, And All-Optical Classical And Quantum Devices And Benchmark With Real-World, Large-Scale Problems.
By Spatial Modulation Technology And A Cheap, Simple, And Scalable Design, Light Propagation Is Recurrently Trained Towards The Ground State Of A Programmable Ising Hamiltonian. Starting From My Proof-Of-Concept, First, I Aim At The Energetically Efficient Computing Of Large-Scale Hamiltonians. Second, I Include Self-Optimizing All-Optical Nonlinear Ultrafast Phase-Locking Processes. Third, I Demonstrate Record Combinatorial Optimization By Letting The Spins Evolve In A High Dimensional Space To Guarantee High Success Probability.
Hyperspim Leverages The Interplay Of Classical And Quantum Dynamics Through The Onset Of Entanglement And Squeezing. The Unprecedented Scale And Versatility Allow The First Quantum Optimization Tests For Real-World Complex Computational Tasks.
Hyperspim Achieves The Fastest And Biggest Optical Computing Device Operating In Classical And Quantum Regimes In An Interdisciplinary Route Towards New Photonic Artificial Intelligence, Large-Scale All-Optical Computing, And Fundamental Science.
Funded Under
European Research Council (Erc)
Total Cost
€ 2 490 000,00
Eu Contribution
€ 2 490 000,00
Coordinated By
Universita Degli Studi Di Roma La Sapienza
Italy
Start Date
1 January 2025
End Date
31 December 2029
Objective
Efficient hardware for combinatorial optimization and machine learning impacts science, engineering, and society. With new computational models, photonics tackle problems intractable with conventional computing systems. However, existing devices only scale up to thousands of spins and operate at the second timescale.
I demonstrate photonic machines for ultrafast parallel processing of millions of spins with microsecond timescale. The strategy is minimizing a class of functions, the Ising Hamiltonian, by a new computational system that uses a high-dimensional feature space and speeds up optimization by orders of magnitude by ultrafast nonlinear optical processes. I build digital, optoelectronics, and all-optical classical and quantum devices and benchmark with real-world, large-scale problems.
By spatial modulation technology a
