2026-09-25: IEEE Quantum Week 2026 in Toronto, Canada
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| IEEE Quantum Week 2026 in Toronto |
The main reason for the trip was to present our paper, "Distributed Quantum-Enhanced Optimization: A Topographical Preconditioning Approach for High-Dimensional Search". QCE was especially interesting for me because essentially everyone there was working somewhere in the quantum computing ecosystem. There were people with backgrounds in physics, computer science, electrical engineering, AI/ML, and pretty much everything in between.
Throughout the week, I attended keynotes and technical sessions, spent too much time walking around the exhibit hall, and had the chance to meet people working across quantum hardware, software, algorithms, HPC, and AI.
My parents and brother also tagged along for the trip, so outside the conference we had some time to explore Toronto together before eventually making our way to Niagara Falls after QCE.
Monday, September 14: Quantinuum and QUOPS
The conference started very strong.
The keynote that stood out the most to me during the week was given by Rajeeb Hazra, President and CEO of Quantinuum.
His talk focused on the next era of quantum error correction and how we should measure progress as the new systems move toward useful fault-tolerant quantum computing.
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| Quantinuum introducing QUOPS |
There was also an interesting connection that I had no idea about until the keynote. Dr. Hazra received both his master's and PhD in Computer Science from the College of William & Mary, which is very close to Old Dominion University.
Seeing someone who studied computer science basically down the road from ODU now runs one of the major quantum computing companies in the world was pretty inspiring.
The exhibit hall also opened on Monday night along with the posters. QCE had companies working on essentially every part of the quantum computing stack, from hardware and control systems to transpilers, software, and hybrid computing platforms.
Tuesday, September 15: IBM and the Road to Fault Tolerance
Tuesday had another keynote that I found interesting, although this one got technical very quickly.
Ali Javadi-Abhari, Head of Qiskit at IBM Research, talked about IBM's path from the noisy quantum computers we have today toward full fault-tolerant quantum computing.
One way he framed it that really stuck with me was as a complexity tradeoff between time (samples) and space (qubits).
Basically, there is no free lunch.
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| Complexity tradeoffs behind quantum error mitigation and correction |
IBM's roadmap includes several steps between those two extremes, including post-selected QEC, spacetime codes, conditional QEC, and eventually concatenated algebraic error-correcting codes.
I really liked this framing because fault tolerance is sometimes presented as a single jump from today's noisy machines to fully error-corrected quantum computers. In reality, it looks much more like a spectrum where different techniques make different trade-offs depending on what the hardware can support.
The other part that caught my attention was IBM's hardware roadmap.
IBM is building Quantum Starling at a new quantum data center in Poughkeepsie, New York, with the system planned for 2029. The architecture is highly modular, with multiple quantum systems working together instead of relying on one enormous (monster) processor.
The idea of connecting multiple systems also tied nicely into something that kept appearing throughout QCE: the future of quantum computing is probably going to be much more distributed and heterogeneous than a single QPU sitting by itself.
Wednesday, September 16: NVIDIA and the Quantum Supercomputer
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| Keynote by NVIDIA’s Krysta Svore |
Her keynote focused on NVIDIA's vision for an accelerated quantum supercomputer, where CPUs, GPUs, and QPUs work together rather than as completely separate systems.
She also discussed CUDA-Q Logical, which is NVIDIA's freshly announced infrastructure for developing and testing fault-tolerant quantum applications, along with support for the QUOPS benchmark introduced earlier in the week.
I also had the chance to ask her for advice as someone coming from a computer science background.
I really liked seeing that connection between keynotes. On Monday, QUOPS was introduced as a way to think about useful quantum performance. On Tuesday, IBM went deep into how we might actually reach fault-tolerance. Then on Wednesday, NVIDIA was showing how fault-tolerant quantum computers could fit into a much larger software and accelerated computing stack.
The AI and quantum connection can roughly go in two directions. The first is AI for quantum, where LLMs are used to improve things like circuit generation, calibration, transpilation, error correction, or optimization. The other is quantum for AI, where quantum computers are used to accelerate or change how we perform machine learning itself. Right now, the first direction seems much more mature, but I think there is a lot of potential in both.
This whole AI-HPC-Quantum integration space is probably one of the research directions I am most excited about right now.
Thursday, September 17: AI Meets Distributed Quantum Optimization
Thursday had one of the talks that was most directly connected to my own research interests.
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| Intersection of AI + Quantum + HPC |
The work combines distributed QAOA with a generative model that produces candidate circuits for smaller optimization problems.
What made this interesting to me was that it combined almost every theme I had been hearing throughout the week: distributed quantum computing, GPUs, AI, optimization, and HPC.
It was also really cool seeing work from ORNL at QCE while I am currently doing an internship there.
By Thursday, it was apparent that hardware, AI, HPC, quantum algorithms, and software systems are no longer being discussed as completely separate areas. They are increasingly becoming parts of the same computing stack.
Friday, September 18: Microsoft and Presenting D-QEO
The last day of the conference started with the final keynote before it was finally my turn to present.
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| From scalar computing to quantum |
He also discussed Microsoft's Majorana 2 approach using topological qubits with the long-term goal of scaling the system to one million qubits on a single chip using fast, digitally controlled hardware.
Then, after spending several days watching everyone else present, it was finally my turn, and I was definitely nervous.
After sitting through a week of talks from people across the largest quantum companies, national laboratories, and universities, getting up to present our own research at QCE felt like a pretty big moment for me.
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| Presenting our D-QEO work |
The main idea behind our work is different from the usual hybrid optimization approaches because we do not ask the quantum computer to directly find the final answer to a continuous optimization problem. Instead, we use it as a topographical preconditioner.
The quantum processor explores the discretized landscape and produces a probability distribution around the most promising regions of the search space before handing it back to the classical optimizer running on a GPU.
Rather than replacing the classical optimizer, the QPU helps it decide where it should search. For the separable functions studied in this work, we also decompose the problem into smaller independent subcircuits that can be evaluated separately. This allowed us to explore larger search spaces without requiring the entire problem to fit onto one very large quantum circuit.
What was funny was how well our work fit into the themes I had been hearing through QCE all week.
Again and again, people were talking about QPUs as accelerators inside larger classical workflows of CPUs and GPUs. Our approach follows a similar trend because we use the quantum processor for the part where it may provide something useful, and let the classical hardware handle what it already does well.
Presenting the work to a quantum-focused audience was also quite a bit different from presenting it to a more general computer science audience. The questions went immediately into things like circuit transpilation, hardware execution, decomposition, and scaling. I also had a chance to connect with other people afterwards for a potential collaboration.
Toronto and Niagara Falls
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| Niagara Falls from the Canada side |
My parents from Hungary came to Toronto with me, which made this trip a little different from most of my conference travels so far.
Whenever I had some free time, we walked around Toronto and explored the city a little bit.
Since the conference was right downtown, it was easy to leave QCE and immediately be in the middle of the city.
After the conference ended, we also drove to Niagara Falls together for a day.
I had obviously seen Niagara Falls in pictures countless times before, but seeing it in person up close is completely different. It was a great way to finish the trip after spending an entire week thinking about quantum computing.
Looking Back
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The CN Tower at night just outside of the conference venue |
The original reason for going to Toronto was to present our paper, but just like with my trip to KDD, the conference ended up being much more than the presentation itself.
I heard from people building some of the most advanced quantum systems in the world, saw where companies are currently investing their efforts, learned about research that overlaps with my own work, and met a lot of interesting people from both industry and academia.
If there was one technical theme I took away from the week, it was definitely the growing convergence of quantum computing, AI, and HPC. I do not think these technologies are going to develop independently from one another, but rather in ways that support each other.
QCE made it feel increasingly likely that useful quantum computing will become one component of a much larger computing ecosystem. That also happens to be the part of quantum computing that I find the most exciting. Add in presenting our own work at a conference I was honestly nervous to present at, meeting people from across the field, exploring Toronto with my parents and brother, and finishing the trip at Niagara Falls, and it was a pretty memorable week.
I would also like to thank Dr. Nikos Chrisochoides and IEEE Computer Society for making this trip possible.
Looking forward to what's next.
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