United States

NSF Workshop on Software-Hardware Co-Design for Quantum Computing

Approaches to fault tolerance and error mitigation on near-term systems and beyond - panel discussion

workshop paper


### WELCOME

#### NSF Workshop on software-hardware Co-Design for Quantum Computing

This workshop will function as a hub to spur a large, synergistic, and convergent effort for building a common technological ecosystem that quantum-enabled technologies and classical technologies can live together for mutual benefit and progress in the long term. In this workshop, experts from both industry and academia will gather together and discuss the key challenges that need to be addressed for an end-to-end quantum computing infrastructure. In particular, we advocate the importance of taking a computer engineering perspective. We envision that classic computer engineering techniques (at both software and hardware levels) have the potential to enable transformative scientific and industrial progress for quantum computing. The key is to figure out the grand challenges in the new quantum context. This workshop is to help the computer engineering community better understand and focus on these grand challenges rather than incremental changes, form a stronger collaboration, and propose transformative ideas to achieve significant progress in quantum computing. To this end, experts will be invited to get together to report the latest research progress and discuss their visions of the critical challenges that need to be addressed in the near future and how to tackle these challenges in a synergistic manner. <br><br>

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You can register for the workshop here.  Please use **[this link](https://nsfworkshop2022reg.paperform.co/)**.

This workshop will function as a hub to spur a large, synergistic, and convergent effort for building a common technological ecosystem that quantum-enabled technologies and classical technologies can live together for mutual benefit and progress in the long term.

Quantum computing is at an inflection point, where 127-qubit machines are deployed, and 1000-qubit machines are perhaps only a few years away. These machines have the potential to fundamentally change our concept of what is computable and demonstrate practical applications in areas such as quantum chemistry, optimization, and quantum simulation. Yet a significant resource gap remains between practical quantum algorithms and real machines. A promising approach to closing this gap is to design software that is aware of the key physical properties of emerging quantum technologies. I will illustrate this approach with some of our recent work that focuses on techniques that break traditional abstractions and inform hardware design, including compiling programs directly to analog control pulses, computing with ternary quantum bits, 2.5D architectures for surface codes, and exploiting long-distance communication and tolerating atom loss in neutral-atom machines.

Resource-Efficient Quantum Computing by Breaking Abstractions

We will discuss the recent advances involving programmable, coherent manipulation of quantum systems based on neutral atom arrays excited into Rydberg states, allowing the control over several hundred qubits in two dimensions. Recent developments involving both analog and digital quantum simulations and quantum information processing will be described. In particular, the realization of novel quantum processing architecture based on dynamically reconfigurable entanglement and the steps towards quantum error correction will be discussed. Finally, we will discuss opportunities for optimizing these techniques towards realization of useful, large-scale quantum processors.

Quantum processors based on reconfigurable atom arrays

Quantum Computer architecture design and optimization - panel discussion

In recent years there has been a growing realization that simulation of physical systems is perhaps the killer application for quantum computers. Towards this end new techniques have been developed that aim to build a quantum simulation into a subspace of a larger quantum system. This block-encoding provides us with more flexibility than we would have with existing methods and allows quantum simulations to be performed at the limits of what physics permits for the speed of simulation. In this talk, I will discuss two recent results that use this formalism. The first uses block encodings to represent chemical dynamics within a larger unitary matrix allowing for sublinear scaling with the total number of electrons. The second approach shows that time itself can be block encoded in a quantum simulation allowing us to simulate the dynamics of time-dependent quantum systems as time-independent Hamiltonians. This will allow us to demonstrate the first truly optimal algorithm for simulating time dependent Hamiltonians (with linear time-dependence) and opens a path towards a broader understanding of how space and time dependence should be tackled within quantum simulations.

Quantum algorithms for simulation using block encodings

We give an overview of Microsoft's Azure Quantum cloud platform https://aka.ms/aq/ that allows users to develop in several quantum programming languages--including Q#, Qiskit, and Cirq--and to target several backends from a rapidly expanding ecosystem of hardware and software partners. The talk highlights also the Quantum Intermediate Representation (QIR) alliance, a joint effort that today consists of Microsoft, NVIDIA, Oak Ridge National Labs, Quantinuum, Quantum Circuits Inc., and Rigetti. The growing QIR Alliance aims at increasing interoperability between platforms, building of state-of-the-art compiler tools, and leveraging the unique capabilities of quantum computing that are distinct from the classical model.

Azure Quantum and the road to scalable quantum computing

Design automation and software for quantum computing - panel discussion

The invention of programmable quantum annealers was motivated in part by magnetism experiments on disordered Ising magnets---spin glasses. These experiments suggested that spin glasses could be brought into low-energy states faster by quantum annealing than by thermal annealing. Reproducing this phenomenon in a programmable quantum annealer has remained a central goal in the field. In this talk I will discuss a demonstration of this quantum critical speedup in a D-Wave Advantage processor, which is made possible by expanded qubit connectivity. I will then discuss a simple hybrid framework for extending the reach of quantum annealers to larger-than-chip optimization problems.

Quantum annealing: Coherent and hybrid approaches to spin glasses

Codesign for quantum sensors

For wireless network designers, user demand for increasing amounts of capacity continues to outpace supply, and while 5G has made progress, even higher-performance remains impractical in part because baseband algorithms are extremely computationally demanding: there is elasticity in the relationship between spectral efficiency and expended compute cycles. With a team of collaborators from industry and academia, this line of work aims to transform the current research landscape by leveraging quantum computation to overcome previous computational limitations, enabling new levels of wireless network performance, with the eventual outcome of incorporating quantum computation into tomorrow's Next Generation standards. We have implemented a series of such designs on quantum annealer and gate model computers: I will touch on a Large MIMO detector, an LDPC decoder, and work on a Polar code decoder. I will conclude with a roadmap for future progress in this area.

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Approaches to fault tolerance and error mitigation on near-term systems and beyond - panel discussion

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Resource-Efficient Quantum Computing by Breaking Abstractions

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