Question 1

9:00 AM – 9:45 AM   |   Registration

Accepted Answer

Join us for registration

Question 2

9:50 AM – 10:00 AM | Opening Remarks

Accepted Answer

Opening remarks from a guest speaker, to be announced.

Question 3

10:05 AM – 10:55 AM | Technical Talk (Anupam Mazumdar)

Accepted Answer

Join us for an insightful technical talk by Anupam Mazumdar!

Question 4

11:00 AM – 11:25 AM | Lightning Talk (IonQ)

Accepted Answer

Join us for an insightful lightning talk by IonQ!

Question 5

11:30 AM – 1:30 PM | Lunch, Poster Session, Open Challenge, Grad Fair, Networking

Accepted Answer

Join us for some yummy lunch and networking, all while participating in the open challenge, poster session and grad fair!

Question 6

1:35 PM – 2:30 PM | Technical Talk (Dr. Grier M. Jones)

Accepted Answer

Dr. Grier M. Jones is a Postdoctoral Fellow with the Quantum Software Consortium (QSC), co-advised by Hans-Arno Jacobsen, Scientific Director and Principal Investigator of the QSC in the Edward S. Rogers Sr. Department of Electrical & Computer Engineering, and Ulrich Fekl, Principal Investigator in the QSC in the Department of Chemical & Physical Sciences at the University of Toronto. His research focuses on quantum machine learning and distributed quantum algorithms for quantum chemical applications. He received his PhD in Physical Chemistry from the University of Tennessee, Knoxville, under the supervision of Konstantinos D. Vogiatzis.
In recent years, technological advances in quantum hardware and algorithms have sparked growing interest in quantum computing. Despite the promises of quantum advantage, the practicality of quantum devices has been limited by hardware constraints, such as the number of qubits and noise-induced decoherence. One proposed method to address this challenge is distributed quantum computing (DQC). Like classical distributed computing, DQC aims to increase computational power by distributing computation across multiple devices, thereby minimizing noise and reducing circuit depth. Additionally, quantum-centric supercomputing, which combines classical distributed hardware with quantum processing units (QPUs), has proven to be a successful and practical approach to solving the molecular electronic structure problem using the local unitary cluster Jastrow (LUCJ) ansatz. The key limitation in implementing this algorithm arises from the limited number of available qubits per quantum device, which in turn restricts the size of the complete active space (CAS). To bypass this limitation, the LUCJ ansatz can be partitioned across multiple QPUs within a quantum-centric supercomputing framework, enabling the exploration of the electronic structure of chemical systems beyond the scale of current QPU topologies. We benchmark the distributed LUCJ (dLUCJ) method across three system types: diatomic molecules, hydrogen chains, and polyacenes (or n-acenes). Using these systems, we highlight a path towards massively parallel quantum chemistry calculations, limited only by the length of the longest chain of connected qubits and the demands of classical postprocessing.

As a classically trained computational chemist, my motivation for exploring DQC for quantum chemical calculations is twofold. First, acceleration hardware, such as GPUs, and high-performance computing are proven strategies for solving chemically relevant electronic structure problems efficiently and accurately. Exploiting parallelism, when possible, on current hardware is one of my primary motivations for performing research on DQC. Second, as many quantum computing companies move towards scalable, modular quantum hardware,  quantum algorithms need to be developed that can scale natively with the available hardware resources.

Question 7

2:35 PM – 2:55 PM | Group Photo

Accepted Answer

Join us for a group photo.

Question 8

3:00 PM – 3:55 PM | Peter Love — Contextuality and Magic in hybrid quantum-classical algorithms

Accepted Answer

Join us for an insightful technical talk by Peter Love!What properties of quantum mechanics are responsible for the power of quantum computers? How can we most effectively use quantum and classical computing together in hybrid approaches such as variational quantum algorithms or quantum-centric supercomputing?  In this talk I will describe an approach to these questions based on contextuality that has led to the contextual subspace method. This enables the separation of ground state problems into classical and quantum pieces, reducing the quantum resource requirements by only solving the quantum part on the quantum computer.

Question 9

4:00 PM – 4:25 PM | Lightning Talk (IQC)

Accepted Answer

Join us for an insightful lightning talk by IQC!

Question 10

4:30 PM – 4:55 PM | Lightning Talk

Accepted Answer

Join us for an insightful keynote talk! Speaker to be announced soon.

Question 11

5:00 PM – 6:00 PM | Grad Talk Panel

Accepted Answer

Come together to ask our speakers questions!

Question 12

6:05 PM | Departure

Accepted Answer

End of Day 1

Program

Schedule (Subject to change)

9:00 AM – 9:45 AM | Registration