Quantum Industry Day 2025

The 4th annual Quantum Industry Day will bring together scientists from academia and industry for an interactive exchange on directions and opportunities in quantum computing.

This is an invitation-only event and registration will be required for all participants.

Schedule Overview (this schedule is subject to change):

8:50 a.m.-9:20 a.m.      Breakfast

9:20 a.m.-9:30 a.m.       Welcome and Introductory remarks

9:30 a.m.-10:00 a.m.      Craig Gidney (Google Quantum)

Title: Optimizing the Annoying Stuff: Reducing Costs Obscured by the Abstract Circuit Model
 

10:00 a.m.-10:30 a.m.    Dolev Bluvstein (Caltech)

Title: Atomic Quantum Processors and the Error-Correction Frontier

10:30 a.m.-11:00a.m.     Break

11:00 a.m. -11:30 a.m.    Dan Stamper-Kum (CIQC, UC Berkeley)

Title:

11:30 a.m.-12:00 p.m.    Anthony Chen (Simons-CIQC)

Title: Quantum Thermal Simulation

12:00 p.m.-1:45 p.m.      Lunch (catered)

1:45 p.m.-2:30 p.m.        John Martinis (Qolab)

Title: How to Build a Quantum Supercomputer

2:30 p.m.-2:45 p.m.        Break

2:45 p.m.-3:15 p.m.         William Kretchmer (UT Austin)

Title: Demonstrating an Unconditional Separation Between Quantum and Classical Information Resources

3:15 p.m.-3:45 p.m.         Andru Gheorghiu (IBM Quantum)

Title: Can We Get Verifiable Quantum Advantage from Forrelation

3:45 p.m.-4:15 p.m.        Break

4:15 p.m.-5:00 p.m.         Panel Discussion

Abstracts

Craig Gidney (Google Quantum) 

Title: Optimizing the Annoying Stuff: Reducing Costs Obscured by the Abstract Circuit Model

Abstract: It's common for optimization to focus on easily quantified metrics, like gate count and depth. However, factors not typically expressed in quantum logic circuits are arguably more important. For example, [Litinski 2022] reduced algorithm cost more than 10x compared to [Litinski 2018] purely by changing routing (i.e. without changing the logical gates). Similarly, [Webber et al 2022] found that switching from [Litinski 2018] compilation to [Gidney/Fowler 2019] compilation improves total algorithm cost by more than 10x.

In this talk, I'll describe improvements to the ripple carry adder that don't correspond to doing fewer logical gates. Improvements to the annoying stuff: the routing, the magic consumption, and so forth. I'll also be advocating for diagrammatic languages (like ZX graphs and defect diagrams) that make these improvements easier to express.

References:
[Litinski 2018]: https://arxiv.org/abs/1808.02892
[Gidney/Fowler 2019]: https://arxiv.org/abs/1905.08916
[Litinski 2022]: https://arxiv.org/abs/2211.15465
[Webber et al 2022]: https://pubs.aip.org/view-large/figure/88447142/013801_1_f1.jpg

Video:

Dolev Bluvstein (Caltech)

Title: Atomic Quantum Processors and the Error-Correction Frontier

Abstract: Quantum computers open new scientific avenues, from exploring complex quantum mechanical systems to new computational paradigms, but face the fundamental challenge of decoherence. Remarkably, decoherence can be prevented by creating highly entangled states of physical qubits that encode an error-corrected “logical” qubit. Here we will describe the development of quantum computing with reconfigurable arrays of neutral atoms and their use for quantum processing with logical qubits. Quantum processing in this approach is based on the coherent transport of atoms shuttled by optical tweezers, enabling any-to-any connectivity, high-fidelity programmable logic, and mid-circuit processing within a zoned architecture. Logical qubit processing is greatly facilitated by parallel control and transversal operations, and is used for experiments ranging from entangling logical qubits to their use for precise simulation of quantum scrambling. Core physical mechanisms for achieving deep-circuit, universal algorithms with logical qubits are identified, and these are leveraged into new techniques that greatly reduce overheads for large-scale computation. These results, alongside other recent advances, herald a transition to error-corrected quantum processing, establishing foundations that can enable future large-scale quantum computers and their useful applications.

Video:

Dan Stamper-Kum (CIQC, UC Berkeley)

Title:

Abstract:

Video:

Anthony Chen (Simons-CIQC)

Title: Quantum Thermal Simulation

Abstract: Everyone says that quantum computers can simulate many-body quantum systems, but what exact problem are we trying to solve? Today, we explore the theme of thermal simulation, revisit the origin of physically existing states, and formulate a feasible and structured target for quantum simulation. 

Video:

 John Martinis (Qolab)

Title: How to Build a Quantum Supercomputer

Abstract: In the span of four decades, quantum computation has evolved from an intellectual curiosity to a potentially realizable technology. Today, small-scale demonstrations have become possible on hundreds of physical qubits and proof-of-principle error-correction on a single logical qubit. Nevertheless, the path toward a full-stack scalable technology is a work in progress. There are significant outstanding quantum hardware, fabrication, software architecture, and algorithmic challenges that are either unresolved or overlooked. Here, we show how the road to scaling could be paved by adopting existing semiconductor technology to build much higher-quality qubits and employing system engineering approaches. 

Video:

William Kretchmer (UT Austin)

Title: Demonstrating an Unconditional Separation Between Quantum and Classical Information Resources

Abstract: I'll speak about a recent collaboration between the Simons Institute, Quantinuum, and UT Austin in which we demonstrated a new, unconditional form of quantum advantage. Leveraging quantum-classical separations in communication complexity, we performed a task using 12 trapped-ion qubits that would provably require at least 62 bits of storage to replicate using classical information resources. Our separation does not rely on any unproven conjectures, and demonstrates how today's quantum processors can generate and manipulate entangled states of sufficient complexity to access the exponentiality of Hilbert space. Based on arXiv:2509.07255.

Video:

Andru Gheorghiu (IBM Quantum)

Title: Can We Get Verifiable Quantum Advantage from Forrelation

Abstract: Forrelation (Aaronson '09) is the problem of determining whether a function is correlated with the Fourier transform of another function. This problem has been shown to have many nice properties, such as not being contained in the polynomial hierarchy (relative to an oracle) and being easily generalizable to a BQP-complete problem. In addition, the quantum circuit for solving it is relatively simple, whereas classical algorithms for it require exponential time. For these reasons and others, in this talk I will argue that Forrelation is a good candidate for a verifiable quantum advantage test. I'll present some ideas for how to (potentially) achieve this using bent functions, obfuscation-like ideas and connections to certain group membership problems.

Video: