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9:00am Symmetry-based Matrix Variational Quantum Eigensolver: Approach Resolving Circuit Depth Limitation, Non-orthogonality, Optimization, and Measurement Problems
Artur F. Izmaylov, University of Toronto
Symmetry-based Matrix Variational Quantum Eigensolver (SM-VQE) is a hybrid quantum-classical algorithm that interpolates between Variational Quantum Eigensolver (VQE) and Configuration Interaction (CI) by constructing Hamiltonian matrix elements on a quantum device and solving the resulting eigenvalue problem classically. This matrix-based approach reduces circuit depth requirements—one of the primary limitations of VQE on near-term quantum hardware—by trading circuit complexity for additional matrix elements. In contrast to traditional VQE, SM-VQE eliminates the need for nonlinear optimization over unitary parameters and significantly reduces measurement overhead. Unlike other recent expansion-based methods, such as Quantum Subspace Expansion (QSE), Quantum Krylov Subspace Expansion, and the Non-orthogonal Quantum Eigensolver, SM-VQE leverages symmetry-induced orthogonality to construct basis states belonging to distinct symmetry sectors. This not only guarantees orthogonality but also limits the number of Hamiltonian terms that need to be measured, as many terms vanish between different symmetry subspaces. By systematically combining symmetry principles with matrix-based techniques, SM-VQE offers a scalable and resource-efficient path for quantum simulations in the near-term and early fault-tolerant regimes.
9:45am TBD
[Academia] Nathan Wiebe
TBD
10:30am Coffee & Tea Break
11:30am The Grand Challenge of Developing Quantum Applications
Ryan Babbush, Google Quantum AI
In this talk, I will discuss how our team at Google understands and approaches the problems of developing new quantum algorithms and matching them to real-world applications. I will survey several recent results from our team across several domains including optimization, linear and differential equations, and quantum simulation. My talk will also touch on problems of emerging importance such as the design and compilation of algorithms for very small fault-tolerant quantum computers.
12:15pm From In Silico to In Vitro: Experimental Validation of Bioactive Molecules Designed by Hybrid Quantum-Classical Machine Learning Model
Christoph Gorgulla, St. Jude Children's Research Hospital
The identification of promising hit and lead compounds is a primary bottleneck in drug discovery, defined by the immense challenge of navigating a virtually limitless chemical space. To test if quantum computing offers a tangible advantage in this area, we developed a hybrid quantum-classical generative model and benchmarked it directly against a purely classical counterpart. Both models were tasked with designing novel inhibitors for KRAS, a key cancer target, with the quantum model using a 16-qubit quantum computer from IBM. Initial computational benchmarks demonstrated a superior performance for the quantum model regarding the quality of the generated molecules. This computational advantage translated into tangible experimental success: after synthesizing 15 promising candidates jointly from both models, the two molecules confirmed as the best biological hits, a broad-spectrum inhibitor and a distinct, mutant-selective compound, both originated from the quantum-generative model. To our knowledge, this work is the first to translate molecules designed by a quantum-generative model into experimentally validated biological hits. It demonstrates the practical potential of quantum-assisted computing for therapeutic design.
Noon Lunch
2:00pm Enabling Scientific Discovery through Quantum and HPC Workflows at NERSC
Katherine Klymko
The National Energy Research Scientific Computing Center (NERSC) is taking an active role in shaping the practical landscape of quantum computing. This talk will provide a snapshot of how NERSC is supporting near-term and future quantum applications through strategic programs and partnerships. I will highlight three key areas of focus: (1) the Quantum Computing Access at NERSC (QCAN) initiative, which offers researchers access to both quantum hardware and large-scale classical resources to explore hybrid workflows; (2) collaborative R&D efforts with QuEra Computing that target scientific use cases on neutral atom quantum systems; and (3) NERSC’s development of benchmarking and characterization tools to evaluate real-world quantum performance. I will close with a discussion of promising application domains, technical challenges, and NERSC’s strategy for supporting future computational workloads that leverage both HPC and quantum computing.
2:25pm TBD
Stefan Knecht
TBD
2:50pm Panel
TBD
TBD