The Future of Quantum Computing

Breaking news, scored company profiles, and ecosystem intelligence across the global quantum sector — plus the deepest coverage of India's National Quantum Mission.

Tiny Flaws in Diamonds Could Unlock a Quantum Computing Revolution
Featured Story

Tiny Flaws in Diamonds Could Unlock a Quantum Computing Revolution

A new computational technique could accelerate the search for diamond materials capable of powering future quantum computers and highly sensitive sensors. Developed by a researcher at the U.S. Department of Energy's (DOE) Princeton Plasma Physics Laboratory (PPPL), the method makes it much easier to identify promising materials for quantum technology, potentially opening the door to advances across many areas of science.The approach has already revealed new candidates for quantum computing and sensing applications. The findings were recently published in ACS Central Science and have attracted attention from other researchers in the field.One of the biggest challenges in developing quantum technology is finding materials that can maintain delicate quantum states under practical conditions. Many candidates require extremely low temperatures to function reliably. Diamond materials stand out because certain quantum properties can remain useful even at room temperature.This capability could help advance technologies that are important to national research priorities and the development of next-generation computing. Quantum sensors promise levels of sensitivity and precision beyond those of conventional instruments, while quantum computers could eventually solve certain extraordinarily complex problems much faster than today's most powerful supercomputers.Why Imperfect Diamonds Could Be the Key to Quantum ComputingAlthough diamonds are made of carbon atoms, a flawless diamond crystal is not enough to create a useful quantum computing system. The key lies in tiny irregularities within the crystal structure.These imperfections, known as defects, can occur when a carbon atom is absent from its normal position, when another element replaces a carbon atom, or when both changes occur together. The atoms surrounding these defects can form qubits, the basic units used to store and process quantum information in quantum computers and sensors.Finding the most useful defects, howeve

Nov 13, 2026

Featured Stories

View All Stories
LTM Becomes First Global Systems Integrator to Launch Function in IBM Quantum Functions Catalog with AI-QEM
Featured
quantum-computing

LTM Becomes First Global Systems Integrator to Launch Function in IBM Quantum Functions Catalog with AI-QEM

Global technology services firm LTM (a Larsen & Toubro Group company) has deployed its proprietary AI-QEM (AI-powered Quantum Error Mitigation) software in the IBM Quantum Functions Catalog, becoming the first global systems integrator to publish a circuit function on the platform. Available to IBM Quantum Premium, Flex, and On-Prem Plan users via the ltm/ai-qem interface, the function integrates into Qiskit Estimator workflows to suppress hardware noise through classical deep-learning inference. LTM AI-QEM Circuit Function Specifications & BenchmarksSystem DimensionTechnical SpecificationMeasured Benchmark / Platform ImpactModel ArchitectureGraph Convolutional Network (GCN)-TransformerPredicts per-Pauli correction factors (ζi) from circuit structure, backend topology, and qubit calibrations.Hardware OverheadZero additional QPU runtime, circuit repetitions, or ancilla qubitsMatches native IBM EstimatorV2 QPU times (12 s commuting / 23 s non-commuting on ibm_kingston).Hardware BenchmarksUp to 100 qubits on IBM Heron r2 processorsAchieved 95.06% accuracy on 100-qubit Clifford circuits (depth 45) and 90.29% on 96-qubit 2D Ising runs.Current Scope & LimitsIBM Heron processor family; applied when |⟨O⟩noisy| ≥ 0.1Targets non-trivial expectation values while avoiding noise amplification near zero. Physical quantum processors remain constrained by gate errors and environmental decoherence that bias expectation values as circuit depth and qubit counts increase. Conventional error-mitigation protocols such as zero-noise extrapolation (ZNE) and probabilistic error cancellation (PEC) compensate for noise by executing ensembles of modified circuits, introducing exponential sampling overheads that inflate quantum runtime costs. AI-QEM workflow. LTM’s circuit-agnostic approach bypasses additional quantum sampling by decomposing observables into Pauli operators and applying trained classical neural networks to rescale each noisy expectation value (⟨Pi⟩mitigated = ⟨Pi⟩no

Quantum Computing ReportLoading...0

From Quantum Authors

View Guest Articles

Trending Stories

View All Trending
Quantum News

Get the Quantum News Newsletter

Weekly insights • No spam • Unsubscribe anytime

India National Quantum Mission

Explore India's ₹6,003 Crore quantum initiative: 4 thematic hubs, leading startups, and the latest developments in India's quantum ecosystem

View All India NQM Content