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Cierra

Today’s issue includes:

• Researchers explored the use of quantum hardware to simulate lower-dimensional supersymmetric quantum mechanics and study phenomena like spontaneous supersymmetry breaking.

• An end-to-end quantum-enhanced framework for unsupervised segmentation of mammography images is designed to detect breast cancer.

• A quantum algorithm determines the connectivity of undirected graphs using a constant number of measurements.

QUANTUM APPLICATION HEADLINES

✨ Using Quantum Hardware to Simulate Supersymmetric Models And Address Classical Limitations in Physics

APPLICATION: Researchers at the University of Liverpool explored the use of quantum hardware to simulate lower-dimensional supersymmetric quantum mechanics to evaluate how quantum computing can address limitations of classical methods in studying phenomena like spontaneous supersymmetry breaking.

SIGNIFICANCE: Supersymmetric models are used by some theoretical physicists to extend the Standard Model of particle physics and establish connections to quantum gravity. However, the exponential complexity of classical simulations limits the study of these models. A major challenge is the sign problem, where calculations involve oscillating terms that cancel each other out, making it difficult for classical methods to produce reliable results. This issue is especially problematic for investigating phenomena like supersymmetry breaking. Quantum computing may provide a solution by enabling polynomial resource scaling and directly encoding quantum states, bypassing the sign problem and making the simulations more possible.

HOW: The researchers encoded a 0+1 dimensional SQM model—zero spatial dimensions and one time dimension—on quantum hardware using qubits to explore supersymmetry. They used the variational quantum eigensolver to compute ground state energies which is a metric used for determining whether supersymmetry is preserved or spontaneously broken. To achieve this, boson and fermion interactions were represented through the Jordan-Wigner transformation and truncated digitization techniques. Using IBM’s Qiskit platform, they conducted simulations with and without shot noise. Overall, results showed that the simulations accurately confirmed supersymmetry preservation and breaking for different superpotentials in noiseless conditions. However, the introduction of shot noise led to deviations which indicates the need for more robust optimization methods and error mitigation techniques.

BY THE NUMBERS:

• 2 qubits — Minimum requirement to represent the simplest system.

• 10,000 shots — Performed for each noisy simulation to replicate quantum randomness.

• 3 superpotentials tested — Harmonic Oscillator (HO), Double Well (DW), and Anharmonic Oscillator (AHO).

• 64 bosonic modes — Largest configuration tested, requiring 7 qubits.

⚕️ Quantum Enhanced Breast Cancer Imaging Achieves Supervised Level Accuracy with Unsupervised Efficiency

APPLICATION: Researchers from Ingenii Inc. proposed and tested the first end-to-end quantum-enhanced framework for unsupervised segmentation of mammography images, specifically designed to detect breast cancer. The framework uses quantum-inspired image representations and optimization techniques to create segmentation masks without requiring labeled data.

SIGNIFICANCE: Breast cancer diagnosis relies heavily on accurate and efficient image segmentation, but current methods face challenges. Supervised approaches demand extensive, annotated datasets, while unsupervised classical methods often lack precision or require significant computational resources. This quantum-enhanced pipeline is designed to balance accuracy with computational efficiency in order to provide a scalable alternative for complex medical imaging tasks.

HOW: The pipeline starts with a quantum-inspired image transformation that emphasizes key features, followed by framing the segmentation task as a quadratic unconstrained binary optimization problem. Several methods, including quantum annealing, variational quantum algorithms, and classical benchmarks like Gurobi and UNet, were evaluated. The quantum annealing approach was shown to be particularly effective, achieving segmentation quality comparable to state-of-the-art supervised models and faster execution times.

BY THE NUMBERS:

• 10x faster — Quantum annealing was an order of magnitude faster than the Gurobi solver for segmentation tasks.

• 84% Dice coefficient — Achieved comparable performance to supervised methods like UNet (85%).

• 42x42 pixels — Downsized images to fit quantum hardware requirements.

• 4 methods compared — Quantum annealing, VQAs, simulated annealing, and classical optimization.

💹 Quantum Algorithm for Graph Connectivity Detection with Minimal Measurements

APPLICATION: Researchers LMU Munich and SUNY Buffalo have introduced a quantum algorithm designed to determine the connectivity of undirected graphs using a constant number of measurements as well as ZX calculus with non-unitary gates to handle graphs with repeated edges and self-loops to extend its utility to various graph types.

SIGNIFICANCE: Graph connectivity is a foundational problem in computer science, relevant for applications in network reliability, clustering, and routing. Classical algorithms for graph connectivity often require linear runtime or more when scaling to large graphs. The proposed quantum algorithm provides an advantage by reducing the number of measurements required, potentially providing faster and more resource-efficient solutions in specific contexts.

HOW: The algorithm maps graph nodes to qubits and edges to non-unitary gates based on ZX calculus, creating entangled states for each connected graph component. Using GHZ states as markers, the algorithm determines connectivity with high probability after only two measurements. While the method involves state decay due to its non-unitary nature, the study notes that this can be mitigated by incorporating ancilla qubits to preserve information.

BY THE NUMBERS:

• 2 measurements — Minimum required to distinguish graph connectivity.

• 75% success probability — Achieved with just two measurements in identifying connectivity.

• 1 measurement type — Non-unitary gates based on ZX calculus are used.

RESEARCH HIGHLIGHTS

🧠 Scientists from Google Quantum AI and DeepMind developed AlphaQubit, a transformer-based neural network, to decode errors in quantum processors more accurately. By combining synthetic data pretraining and experimental fine-tuning, it outperformed traditional decoders on Google's Sycamore processor across multiple code distances.

🤖 Researchers from IBM Quantum demonstrated that machine learning can notably improve quantum error mitigation by reducing overhead and improving efficiency. Using methods like random forest regression, their ML-QEM approach was tested on diverse quantum circuits and outperformed traditional methods like zero-noise extrapolation in terms of runtime and accuracy.

✅ A team from Q-CTRL demonstrates that applying quantum error correction primitives can improve the computational capabilities of current quantum computers without the high overhead of full logical encoding. Using efficient error-detection protocols, the researchers achieved state-of-the-art fidelities for long-range CNOT gates and generated a record 75-qubit GHZ state with genuine multipartite entanglement.

NEWS QUICK BYTES

🍃 The Uplink "Quantum for Society" Challenge invites startups to leverage quantum technologies to address global challenges aligned with the UN Sustainable Development Goals. Focused areas include climate resilience, sustainable manufacturing, equitable healthcare, food security, and freshwater management, with selected startups gaining access to technical support, strategic networking, and global visibility. Winners, announced on World Quantum Day 2025, will showcase how quantum innovation can drive impactful, scalable solutions for a sustainable future.

🖥️ The Taiwan Semiconductor Research Institute has procured its first full-stack superconducting quantum computer, the IQM Spark. The 5-qubit system, set for delivery in 2025, will support education, research, and advancements in quantum and low-temperature CMOS technologies, essential for scaling quantum processors.

💵 Rigetti Computing has generated $100 million through its "at-the-market" equity offering program to support its focus on superconducting quantum computing, including improving 2-qubit gate fidelity and scaling qubit count systems. Rigetti believes its current funds will sustain operations through 2026 while evaluating future funding needs to maintain its leadership in the quantum sector.

🚀 AWS has launched the Quantum Embark Program, an advisory initiative to help businesses explore quantum computing opportunities tailored to their needs. The program offers modules for use case discovery, technical enablement, and application-specific deep dives, empowering customers to build informed quantum roadmaps without long-term commitments.

🍊 Orange Quantum Systems has launched the OrangeQS Max, a full-stack system that accelerates quantum chip testing, reducing R&D resource requirements and speeding up chip development for next-generation quantum computers. Designed in collaboration with IQM, the system automates the characterization of quantum chips with 100+ qubits and tunable couplers, eliminating the need for expert operation.

🔌 Toshiba and RIKEN have experimentally demonstrated the Double-Transmon Coupler, achieving a two-qubit gate fidelity of 99.90%, a key performance metric for quantum computation. This tunable coupler suppresses residual coupling, enables high-speed gate execution in 48 ns, and extends coherence time to support the development of scalable, high-performance quantum computers.

🤝 IBM and Pasqal announced their collaboration to develop a unified programming model for integration of quantum and classical computing resources. This framework will enable interoperability across IBM's quantum systems, Pasqal's neutral atom quantum devices, and classical HPC resources like CPUs and GPUs, accelerating hybrid workflows and usability.

💰️ Sony Ventures is investing in deep tech sectors like quantum computing and renewable energy, using its semiconductor expertise to support scalable, emerging technologies. One key investment includes Quantum Motion, which focuses on semiconductor-based qubits for scalable quantum computers.

🌐 Quantum Corridor Inc., a fiber-optic communications network connecting Chicago and Northwest Indiana, has closed a $10 million Series A funding round, bringing its total funding to over $27 million. The funds will support a $140 million expansion to extend the network across Indiana, featuring Quantum Commercialization Centers with entanglement nodes for efficient data transmission and quantum-safe capabilities.

🎇 TOBB University of Economics and Technology unveiled QuanT, Turkey's first quantum computer. Developed at the TOBB ETÜ Technology Center, QuanT is intended to enhance Turkey's capacity in quantum technologies and accelerate the national technology initiative alongside plans for a Superconducting Quantum Chip Production House.

QUANTUM MEDIA

LISTEN

Yuval Boger interviews Jannes Stubbeman, co-founder and CEO of Aqora, a platform aimed at creating a “Kaggle for Quantum” by providing an operating system for both in-person and online hackathons in the quantum computing space. Jannes and Yuval discuss the origins of Aqora, how it supports hardware vendors in organizing impactful hackathons, the intricacies of benchmarking quantum use cases, the challenges and logistics of hosting competitions, and much more.

THAT’S A WRAP.