University at Buffalo Study Decodes Quantum Material’s ‘Optical Dingerprints’

thequantuminsider.com Nov 13, 2026

University at Buffalo Study Decodes Quantum Material’s ‘Optical Dingerprints’

Curated by Shubham · TechCapsules · Nov 13, 2026

AI-summarised brief · reviewed before publication

University at Buffalo researchers used computer simulations to predict the optical fingerprints of ten atomic defects in hexagonal boron nitride (h‑BN). The models show how defect composition and atomic arrangement alter the intensity and polarization of light emitted at double or triple the laser frequency. Some configurations generate markedly stronger signals, making their fingerprints easier to detect. By distinguishing defects that emit single photons, the work provides a roadmap for experimentally identifying and engineering quantum‑light sources in h‑BN. The study, published in Nano Letters, was led by PhD student Olga Savkina and postdoctoral associate Davoud Adinehloo, with co‑corresponding authors Vasili Perebeinos and Paras N. Prasad. Funding came from the U.S. Air Force, NSF, Australian Research Council and UB Quantum Institute.

💡 Why It Matters

· Identifying defect-specific optical signatures lets researchers target the few h‑BN imperfections that can emit single photons, a prerequisite for building scalable quantum‑light arrays.

Capsules Quantum Computing

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Classical Light Dynamics Could Help Simulate Quantum Interactions

Researchers from Saint Louis University, the Max Born Institute and Humboldt‑Universität zu Berlin demonstrated that classical nonlinear light can induce effective photon‑photon interactions and thermalize quantum light. Using multimode nonlinear optical simulations, they showed that single‑ and two‑photon states propagating alongside intense classical fields evolve into statistical distributions matching Rayleigh‑Jeans and Boltzmann forms. The study, published in Science Advances, proves that standard nonlinear optical platforms can mimic quantum thermodynamic behavior without requiring exotic single‑photon nonlinear materials. Lead authors Şahin K. Özdemir, Ramy El‑Ganainy and Armando Perez‑Leija highlighted the method’s potential as a controllable testbed for open‑quantum‑system and many‑body thermodynamics research. Funding came from the U.S. Air Force Office of Scientific Research and the Army Research Office.

💡 By turning readily available classical optics into a quantum‑simulation tool, the work removes a major experimental bottleneck, enabling rapid exploration of complex quantum thermodynamics in ordinary labs.

quantumcomputingreport.com · Nov 13

PsiQuantum and AMD Expand Partnership with Equity Investment to Co-Design Utility-Scale Quantum…

PsiQuantum and AMD announced an expanded partnership that includes an equity investment from AMD to co‑design classical and quantum infrastructure for fault‑tolerant photonic quantum computers. The collaboration builds on PsiQuantum’s use of AMD Versal SoCs, adding AMD Instinct GPUs, EPYC CPUs, and the ROCm software stack. Engineers tailored PsiQuantum’s PRISM decoder to integrate machine‑learning logic with photonic control loops, eliminating latency. The joint effort targets pharmaceutical research and molecular simulation, delivering immediate GPU‑accelerated chemistry while preparing drug‑discovery pipelines for future quantum hardware. The companies will showcase their roadmap at SC26 in Chicago.

💡 The alliance bridges high‑performance classical computing with emerging photonic quantum technology, accelerating practical applications in drug discovery and setting a blueprint for scalable quantum‑classical integration.

quantumcomputingreport.com · Nov 13

Kipu Quantum Launches Rimay Quantum Feature Extraction in IBM Quantum Functions Catalog

Kipu Quantum has added its Rimay quantum feature‑extraction service to the IBM Quantum Functions Catalog, enabling IBM Quantum Flex, Premium, and On‑Prem users to access quantum‑enhanced machine learning via API. Rimay serves as a preprocessing layer that maps normalized numerical features to qubits, encodes mutual information into Hamiltonian couplings, and returns an enriched CSV matrix for use with scikit‑learn, XGBoost, CatBoost, or LightGBM. The service supports repeatable inference by storing the trained Hamiltonian topology and can pair with Kipu’s offline surrogate framework. A Fortune 100 client has deployed Rimay on an IBM Quantum Nighthawk processor for customer‑intent prediction, and IBM Quantum documentation includes a credit‑risk classification tutorial.

💡 By embedding quantum‑derived feature engineering directly into conventional data‑science pipelines, Rimay lowers the barrier for enterprises to experiment with quantum advantages without replacing existing models. This integration demonstrates a practical pathway for quantum hardware to augment, rather than overhaul, current machine‑learning workflows.

quantumcomputingreport.com · Nov 13

LTM Becomes First Global Systems Integrator to Launch Function in IBM Quantum…

Larsen & Toubro’s technology arm, LTM, has become the first global systems integrator to publish a circuit function on IBM’s Quantum Functions Catalog. Its AI‑QEM software, accessible via the lt‑m/ai‑qeminterface, integrates with Qiskit Estimator workflows to reduce hardware noise using deep‑learning inference. The approach bypasses extra quantum sampling by rescaling noisy expectation values with trained neural networks, achieving a mean absolute error of 0.343 across 80‑ to 150‑qubit tests, outperforming traditional mitigation baselines. IBM Quantum provides tutorials and API documentation for the new function.

💡 By eliminating the need for costly circuit ensembles, LTM’s AI‑QEM could lower quantum runtime costs and accelerate practical applications on noisy hardware. The integration demonstrates a scalable, software‑centric path to higher‑fidelity quantum computations.

quantumcomputingreport.com · Nov 13

Cleveland Clinic, RIKEN, and IBM Cross 12,000-Atom Barrier in Heterogeneous Quantum-Classical Drug…

A joint effort by Cleveland Clinic, RIKEN and IBM Quantum has performed the largest heterogeneous quantum‑classical (HQC) electronic‑structure simulation to date, modeling solvated protein‑ligand complexes of more than 12,000 atoms. The team linked two 156‑qubit IBM Heron r2 processors with three leading supercomputers, executing 21,006 circuits and collecting 3 billion measurement shots. Their Embedded Wavefunction (EWF) formalism partitions macromolecules into bounded atomic neighborhoods, reducing fragment‑construction cost from cubic to constant scaling. For fragments containing 13‑45 molecular orbitals, the new TrimSQD algorithm iteratively filters and merges configurations across GPU clusters before a final subspace diagonalization. An automated Prefect workflow coordinated IBM Quantum Runtime and the ROQ supercomputer, processing 608 million samples in 62.4 hours without human intervention. The work, detailed in an arXiv preprint, was funded by NSF, NIH, NEDO and Japan’s MEXT Fugaku program.

💡 By breaking the 12,000‑atom barrier, the study shows quantum‑enhanced simulations can tackle realistic drug‑binding problems that were previously out of reach for classical methods.

thequantuminsider.com · Nov 13

The Geometry of Quantum Memory: How Anyons Rewrite the Rules of Remembering…

Topological quantum computing seeks to encode information in a system’s global topology, making it immune to local noise that plagues conventional qubits. The approach relies on anyons—quasiparticles first theorized in the late 1970s and observed as Abelian varieties in 2020—whose braiding in two‑dimensional media can implement logical operations without disturbing the stored state. While Abelian anyons have been detected, the non‑Abelian anyons required for fault‑tolerant computation remain elusive, keeping their experimental verification a central challenge. If realized, topological qubits would dramatically reduce the physical‑to‑logical qubit ratio, potentially eliminating the need for thousands of physical qubits per logical unit. Researchers trace the concept to early work on particle exchange in two dimensions and to Alexei Kitaev’s 1997 proposal linking anyons to quantum gates.

💡 Demonstrating non‑Abelian anyons would provide a hardware‑level error‑resilience that could accelerate scalable quantum computers far beyond current error‑correction schemes.