WISER Quantum Program 2025

Get grounded in the fundamentals of quantum computing across these two beginner-friendly sessions. We’ll introduce the mathematical foundations (state spaces, tensors, and computational complexity), core quantum operations (gates, circuits, measurement), and essential principles like superposition, entanglement, and the no-cloning theorem. You'll also explore basic programming concepts to understand how quantum algorithms are structured. These sessions are ideal for newcomers or anyone looking to refresh their foundations.

This session explores why quantum algorithms are critical today, how IBM is working to bring useful QC to the world and what this means for researchers, developers, and industries preparing for a quantum future.

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This session explores how quantum teleportation enables the transfer of quantum states without moving particles, and how Grover’s algorithm offers a powerful way to speed up search problems.

This session explores how quantum teleportation enables the transfer of quantum states without moving particles, and how Grover’s algorithm offers a powerful way to speed up search problems.

This session offers a practical introduction to PennyLane, a leading software library for quantum computing and machine learning. We’ll cover how to build and run quantum circuits, set up a basic environment, and explore simple examples to get you familiar with the interface. Whether you're new to PennyLane or looking for a quick refresher, this session will help you get comfortable programming with PennyLane. 

High-level introduction to the industry projects for the participants from our partners. Participants will learn how the skills they learn this summer will be applied directly to industry applications by the completion of the training program. After the training, all participants will move on to participate in these industry projects, and the best teams will proceed to win QSL fellowships for the next 6 months.

Many natural and engineered systems, from quantum mechanics to fluid dynamics, are governed by partial differential equations (PDEs). Efficiently solving these equations is central to scientific discovery and technological progress. In this tutorial, we’ll explore various quantum algorithmic approaches to solving PDEs, and discuss how these techniques could offer advantages over classical methods.

This fireside chat will spotlight the thriving quantum entrepreneurship ecosystem in the Elevate region. We’ll explore the unique challenges and opportunities quantum startups face, from early-stage research to bringing technologies to market. Join us for a conversation with key players in the quantum space as they share insights on how they’ve navigated the entrepreneurial journey, fostered innovation, and contributed to the growing quantum landscape. 

Step inside the Ion-Photon lab, where they research how to scale up trapped ion quantum computers using single photons! In this lab tour you'll learn how they are adopting a modular approach in which they connect smaller trapped ion modules, or "nodes", via photonic interconnects. The single photons act as information links between the modules, enabling remote entanglement of spatially separated ions. 

This session unpacks two powerful techniques at the heart of many modern quantum algorithms, Linear Combination of Unitaries (LCU) and block encoding. We’ll walk through how these methods let us represent complex matrix operations with efficient quantum circuits, and how they’re used in areas like Hamiltonian simulation and solving linear systems. Whether you're seeing these tools for the first time or need a refresher, this tutorial-style session will get you hands-on with the core ideas.     

Lie algebras offer a powerful and elegant lens for understanding quantum systems. Long central to high-energy and condensed matter physics, they’re now becoming increasingly relevant in quantum computing. In this tutorial, we’ll introduce core Lie-theoretic ideas behind recent advances in quantum simulation, including shadow and fixed-depth Hamiltonian simulation techniques. 

Explore how quantum computing is being applied to real-world optimization challenges. This session will cover emerging use cases, best practices across quantum methods and hardware, and what makes an optimization problem a good fit for quantum approaches. You'll also gain insight into how to choose the right technique for solving different classes of problems, and what’s coming next in the field.

This keynote examines the evolving relationship between quantum computing, high-performance computing (HPC), and artificial intelligence (AI), and how these technologies are increasingly working in tandem to tackle today’s most demanding computational challenges. Join us for a forward-looking discussion on the architectures, algorithms, and breakthroughs shaping the future of computational science.

This keynote examines the evolving relationship between quantum computing, high-performance computing (HPC), and artificial intelligence (AI), and how these technologies are increasingly working in tandem to tackle today’s most demanding computational challenges. Join us for a forward-looking discussion on the architectures, algorithms, and breakthroughs shaping the future of computational science.

From July 5, teams will develop their solutions in their team repository. The final state of this repository at the deadline will serve as the official submission for judging.

A deep dive into structure-aware quantum algorithm design, grounded in practical applications like the heat equation. This session introduces a new approach to applying quantum linear solvers that takes advantage of the structure and sparsity in PDE-derived matrices. A fresh look at how clever algorithm design can push quantum efficiency further.

Nonlinear differential equations are everywhere, and solving them on quantum computers is no small feat. This session looks at how techniques like Carleman linearization and Koopman operator theory can help translate nonlinear problems into linear ones that quantum algorithms can handle. We’ll also dive into recent improvements that make these methods more practical, including higher-order solvers, smarter rescaling, and tighter error bounds.

This keynote explores a different angle on tackling nonlinearity. By using multiple copies of quantum states and introducing Quantum Nonlinear Processing Units (QNPUs), the approach offers a flexible framework for solving nonlinear PDEs. With a blend of tensor networks, numerical benchmarks, and early hardware results, this talk highlights new possibilities for solving nonlinear problems on quantum devices.

Weather prediction requires modeling scales from the molecular up to the planetary, exceeding the capabilities of even the most powerful supercomputers to explicitly resolve all physical processes. This talk explores a potential approach for quantum computers to accelerate solutions of differential equations, which are fundamental for weather prediction. A novel method for efficiently loading classical data onto a quantum computer will be presented as a key step towards this goal.

Simulating non-unitary dynamics is a central challenge in quantum algorithm design, and this session introduces a flexible and efficient approach that makes it more tractable. By expressing solutions as a linear combination of Hamiltonian simulations (LCHS), we can bypass the need for spectral mapping and complex quantum linear system solvers. The method keeps state preparation costs low, simplifies circuit construction, and scales well. 

A beginner-friendly introduction to the fabrication of Rigetti's quantum processors, including visuals of cleanroom facilities and hardware assembly. This session explores key challenges - scalability, error rates, and material limits - and highlights how Rigetti is addressing them. It will conclude by connecting hardware advances to real-world gains in quantum algorithm performance.

Solving nonlinear partial differential equations (PDEs) remains one of the most challenging tasks in scientific computing, especially at scale. This session introduces a quantum-inspired framework based on tensor networks for efficiently representing and solving nonlinear PDEs.

In this session, we’ll explore the intersection of quantum computing and quantum chemistry. Leading experts will discuss how quantum algorithms are being developed to solve complex problems in chemistry that are intractable for classical computers. 

This keynote session will highlight how scalable fault-tolerant quantum computing could unlock accurate simulations of complex molecular systems, with far-reaching implications for materials science, pharmaceuticals, and beyond.

ColibriTD’s H-DES is a universal quantum solver designed to tackle partial differential equations for real-world applications like fluid dynamics, combustion, mechanics, and climate modeling. Built as a hybrid quantum-classical solver based on a variational quantum algorithm (VQA), H-DES works on both current and future quantum devices. 

Current implementations of qubits continue to exhibit too many errors to be scaled into useful quantum machines. An emerging approach is to encode quantum information in the two metastable states of an oscillator exchanging pairs of photons with its environment, a mechanism shown to provide protection against bit flips, at the modest cost of a linear deterioration of phase flips. In this talk, we will introduce the concept of this so-called dissipative cat qubit and explore how it can be implemented in the context of superconducting circuits.

Turbulence is one of the most complex and fascinating phenomena in classical physics, influencing everything from weather systems to aircraft design. This session explores a novel approach to analyzing and simulating turbulent flows using tools inspired by quantum many-body physics and tensor networks.

In this session we’ll dive into the exciting intersection of quantum computing and high-performance computing (HPC). The discussion will cover the challenges of integrating quantum algorithms into existing HPC workflows, the opportunities for synergy between the two, and what the future holds as quantum technology matures. Our panel will share insights on how we can bridge the gap and leverage the strengths of both quantum and classical computing to solve some of the most complex problems in science and industry.

Join us hear how Nestlé is exploring the Quantum Approximate Optimization Algorithm (QAOA) to enhance order fulfillment processes. Discover how one of the world’s largest consumer goods companies is using quantum.

We'll explore QubitSolve's approach to advancing Computational Fluid Dynamics (CFD) with quantum computing. By developing innovative quantum algorithms to solve the Navier-Stokes equations, QubitSolve aims to overcome the limitations of classical CFD simulations, potentially revolutionizing industries like aerospace, automotive, and energy where CFD is essential for optimizing designs and minimizing the need for expensive physical prototypes.

Teams must submit their project by the deadline to qualify for Demo Day on the 29th August. Judging is based on originality, technical depth, impact, and clarity.