Group theory of interferometric amplitudes in the limit of very many particles

Partial distinguishability is now recognized as important in quantum technologies because it directly controls the structure of multi-particle quantum interference, which underpins the advantage of many photonic platforms for computing, sensing, and communication. In realistic devices, photons (or other identical particles) are never perfectly identical: residual differences in time of arrival, spectrum, polarization, or spatial […]

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Automated Formalisation of Quantum Mathematical Proofs Using Machine Learning

This project aims to build an AI system that can turn regular, human-written math problems and solutions into fully checked, error-free formal proofs, with a special focus on quantum mathematics. The project will collect open-source quantum math problems, train a machine-learning model to translate them into formal proofs using the Lean proof assistant, and create […]

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ESROP – Global + Max Planck Institute, University of Hamburg

Laser-driven plume formation is a process relevant to fluid dynamics, laser surgery, and materials processing. In photomechanical spallation, high-intensity laser pulses rapidly deposit energy into a liquid, triggering shock waves, phase transitions, and bubble formation. Although much is known about these phenomena, significant gaps remain in understanding how Newtonian fluids (e.g., glycerol and water) behave […]

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Caractérisation de MEMS RF à des températures cryogéniques

Des microcommutateurs MEMS RF ont été fabriqués sur une ligne de prototypage industrielle de 200 mm. Compacts et à très faible consommation énergétique, ils sont particulièrement adaptés aux environnements cryogéniques où la dissipation thermique doit rester minimale. Le projet vise à qualifier ces dispositifs et des matrices de commutation à très basses températures dans un […]

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Évaluation, comparaison et optimisation de solutions de câblage cryogénique pour les communications numériques

L’émergence de l’informatique quantique marque une ère de transformation dans la science informatique, promettant une puissance de traitement sans précédent pour les problèmes complexes. Cependant, l’évolutivité de l’électronique de contrôle classique, à température ambiante, reste limitée pour les applications quantiques cryogéniques. L’équipe de Sherbrooke, en collaboration avec celle de Paris-Saclay, développe une plateforme électronique cryogénique […]

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Alignment and characterization of multimode-fibre compatible superconducting nano-wire single-photon detector

This project aims to couple a multimode optical fiber(MMF) to a superconducting nanowire single-photon detector(SNSPD) and characterize it. SNSPDs are currently the most sensitive single-photon detectors available. But most of the current SNSPDs are coupled using single-mode fibers(SMF), which collect photons in only one spatial mode. This is inefficient when collecting photons from biological samples, […]

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Benchmarking Post Quantum Cryptography in Internet of Things

In this project, students are expected to set up a testbed and run experiments to evaluate the impact of integrating post quantum cryptography (PQC) into IoT devices. The evaluation metrics include CPU usage, memory usage, bandwidth usage, and energy usage. Various PQC mechanisms will be evaluated on MQTT over TCP+TLS, including ML-KEM, HQC, ML-DSA, and […]

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Experimental Investigation of RuCl3 Electronic and Magnetic Properties Toward Spintronic and Quantum Computing Applications

Since their discovery in 2017, two-dimensional (2D) magnetic materials have emergedas a powerful platform for probing magnetism at reduced dimensionality, where thermal fluctuations challenge long-range order. Among them, RuCl3 is particularly compelling due to its unusual electronic and magnetic properties and its capacity to form heterostructures with potential ferroelectric effects, positioning it as a candidate […]

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Quantum Machine Learning for Computational Drug Discovery

Drug discovery is traditionally slow, costly, and high-risk, with timelines exceeding a decade and expenses reaching billions. This lag is particularly problematic for neglected diseases and cardiovascular conditions, which carry significant global burdens but attract limited research investment. To address this, the project proposes leveraging quantum computing and hybrid quantum-classical algorithms to accelerate drug discovery. […]

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Design and Development of Quantum Entanglement-Enabled Multiparty Key Distribution Protocol for Secure Communication

Quantum communication stands at the frontier of next-generation secure communication systems, leveraging the principles of quantum mechanics to address the limitations of classical cryptography. Among quantum-based techniques, Quantum Key Distribution (QKD) has emerged as a revolutionary solution enabling provably secure key exchange. While bipartite QKD protocols (such as BB84) are well-studied, there remains a significant […]

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Apprentissage machine quantique pour la prédiction de l’efficacité de nouveaux médicaments anti-inflammatoires : application pour la prédiction de l’affinité d’inhibiteurs de l’enzyme 5-lipoxygénase

Le développement d’une molécule de la conception jusqu’à l’obtention d’un médicament est un processus couteux. Dans ce processus, la première étape consiste à synthétiser une série de molécules qui inhibent une action biologique particulière, généralement médiée par un récepteur ou une enzyme. Les essais biologiques et cliniques peuvent être les étapes les plus couteuses de […]

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Quantum Machine learning for medical imaging – radiology, ophthalmology and diabetes prediction

This project explores how quantum computing and artificial intelligence (AI) can work together to improve how we detect diseases using medical images. Medical imaging, like X-rays, clinical photos, and eye scans, are essential for diagnosing many health conditions. However, analyzing these images quickly and accurately remains a challenge, especially as the amount of data continues […]

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