About QRE
This is the fifth international workshop on the emerging field of Quantum Resource Estimation (QRE), benchmarking and performance analytics. The previous editions were QRE2022, QRE2021, QRE2020 and QRE2019.
We hope to encourage participation from those working in quantum algorithm optimization, error-correction, architecture design, quantum compilation, classical control and resource benchmarking.
The workshop is focused around developing techniques and tools that aid quantum software and algorithm design, informed by the realities of the hardware architectures. QRE shifts the perspective from complexity theoretic arguments to quantitative computer architecture arguments.
The goal is to reduce the physical resource1 costs for interesting quantum algorithms as quickly as possible. Small-scale, cloud-based NISQ machines sparked the interest of exact, realistic and non asymptotic resource estimations. It is still uncertain if any valuable quantum algorithm2 is possible without incorporating costly error-correction protocols that make estimation, benchmarking and optimization far more complex. QRE is the forum to share research on the near term feasibility of interesting2 quantum algorithms.
Organisers
Alexandru Paler, Aalto University, Espoo, Finland
Simon Devitt, University of Technology, Sydney, Australia
Daniel Herr, d-fine, Zurich, Switzerland
Technical Program Committee
- Mariia Mykhailova, Microsoft
- Ryo Wakizaka, Kyoto University
- Shin Nishio, National Institute of Informatics
- Srikar Kasi, Princeton University
- Austin Adams, Georgia Institute of Technology
- Siyuan Niu, LIRMM, University of Montpellier
- Kunihiro Wasa, Hosei Universy
- Elton Pinto, Georgia Institute of Technology
- Milad Marvian, University of New Mexico
- Kyle Jamieson, Princeton University
- Eugene Dumitrescu, Oak Ridge National Laboratory
- Robert Basmadjian, TU Clausthal
1Physical resources for executing a quantum algorithm can vary significantly. Resource costs are influenced by the resultant quantum circuits through their structure and designed precision. Additional overheads are introduced by the physical constraints of the quantum hardware. Quantum error correction is also resource hungry. Even the design and the performance of the classical control software that compiles algorithms and controls the quantum computer has a non-negligible impact on resources.
2Algorithm that outperforms classical supercomputers either in a theoretical or monetary sense.
Quantum computation has a growing number of promising application areas such as quantum chemistry, quantum optimisation and finance. However, the first industrially relevant and scalable quantum computer seems to be at least a decade away. Therefore, one of the most pressing questions is "How many physical qubits and how much time is necessary to execute a quantum algorithm on a selected hardware platform where the algorithmic output is more important than the fact a quantum computer was used to calculate it?"
By examining this question in depth we can motivate continued investment for quantum computing, further enable resource friendly quantum algorithm development and continue to push technological advances that will lead to a scalable quantum computing ecosystem.
The workshop will bring together researchers to discuss new methods and directions needed to develop, as soon as possible, the tools to:
- accurately analyze and benchmark complex quantum algorithms
- adapt error-correction techniques
- refine classical control and hardware microarchitectures
- enable scientifically and commercially relavant quantum applications
Research papers, tutorials, software and other demonstrations, and work-in-progress reports are within the scope of the workshop. Invited talks by leading international experts will complete the program. Contributions on all areas of quantum performance analytics are welcome:
- High level quantum circuit analytics.
- Fault-tolerant quantum circuit analytics.
- Clifford+T optimisation strategies.
- Resource efficient surface code implementations.
- Surface code decoders.
- Practical quantitative analysis of surface code alternatives.
- Noisy Intermediate Scale Quantum (NISQ) evaluation.
Initial submission for QRE2023 will consist of an extended abstract, limited to 2+epsilon-pages (including figures and references, please don't go nuts with the epsilon!). Contributions must be written in English and report on original, unpublished work, not submitted for publication elsewhere.
Upon acceptance, researchers are invited to submit full research papers to Research Directions: Quantum Technologies (Cambridge University Press).
Important Dates
Invited Speakers
TBA
TBA
Event Schedule - all times are EDT
Architectures and Design Methods (1)
To attend the talks, please Register
Panel: Large scale quantum computations (... and machine learning)
Scott Aaronson (UT Austin), Kate Smith (Northwestern University), Cristoph Sunderhauf (Riverlane)
Single-Step Parity Check Gate Set for Quantum Error Correction
Gozde Ustun, Andrea Morello and Simon Devitt
Cirq-FT: Cirq for Fault-Tolerant Quantum Algorithms
Tanuj Khattar, Matthew P. Harrigan, Fionn D. Malone, Nour Yosri and Nicholas Rubin.
Novel Design of Modulo 2n + 1 Adder for Quantum Computing
Bhaskar Gaur and Himanshu Thapliyal
Break
Architectures and Design Methods (2)
To attend the talks, please Register
Microarchitectures for Heterogeneous Superconducting Quantum Computers (invited)
Samuel Stein, Sara Sussman, Teague Tomesh, Charles Guinn, Esin Tureci, Sophia Fuhui Lin, Wei Tang, James Ang, Srivatsan Chakram, Ang Li, Margaret Martonosi, Fred Chong, Andrew Houck, Isaac Chuang and Michael DeMarco.
Learning a quantum computer's capability using convolutional neural networks
Daniel Hothem, Kevin Young, Tommie Catanach and Timothy Proctor
Minimizing the energy consumption of scalable full-stack quantum computers
Marco Fellous-Asiani, Jing Hao Chai, Yvain Thonnart, Hui Khoon Ng, Robert Whitney and Alexia Auffèves.
Lunch
Resource Estimation and Decoding (1)
To attend the talks, please Register
Quantum computation for periodic solids in second quantization (invited)
Christoph Suenderhauf (Riverlane)
Quantum resource estimation for protein conformation prediction
Bryan Raubenolt, Hakan Doga, Jun Qin, Daniel Blankenberg and Omar Shehab
Soft-Input Soft-Output Window Decoder for Surface Codes
Michele Pacenti, Asit Pradhan and Bane Vasic
Resource Estimation for Trapped-Ion Lattice Surgery
Hudson Leone, Srikara Shankara and Simon Devitt
Break
Resource Estimation and Decoding (2 -- online, link to videos TBA)
To attend the talks, please Register
Quantum Random Access Memory For Dummies
Koustubh Phalak, Avimita Chatterjee and Swaroop Ghosh
Numerical assessment of Quantum Singular Value Transform in Quantum Phase Estimation
Sean Greenaway, Dylan Sim and William Pol
Hassle-free Extra Randomness from quantum state’s identicalness with untrusted components
Hamid Tebyanian.
End
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