Every electronic system
has a regime.
We tell you which one you are in.
Quantum-Clarity's ELSD platform uses GPU-accelerated ensemble VQE to classify electronic regimes across batteries, catalysis, drug discovery, and advanced materials — revealing when a system is stable, multi-basin, open-shell coherent, or model-pathologic in ways that conventional single-state workflows often miss.
completed
domains
per system
per condition
Conventional workflows often return a number. ELSD returns a classification — whether the underlying electronic model is stable enough to trust, sensitive to perturbation, open-shell coherent, or too truncated to support decision-making.
Four distinct domains, one classification engine
The same ensemble VQE diagnostic framework is applied across chemically distinct systems. Each domain has its own named platform and published or in-preparation dataset, at different stages of validation maturity.
Energy storage — NMC811 battery cathodes
Ni-rich NMC811 cathodes degrade fastest near 50% state of charge. ELSD maps the electronic energy landscape under symmetry-breaking perturbation, directly revealing bifurcation, multi-basin structure, and dopant-response mechanisms that are not accessible from a single ground-state picture.
Drug discovery — metalloenzyme active sites
Most computational drug discovery tools optimize on top of target models that were never validated for electronic reliability. Prometheus classifies whether a metal-centered active-site model is stable, coherent, multi-basin, or model-pathologic — before a single ligand screen begins.
Catalysis — nitrogen fixation and FeMoCo
Ensemble VQE diagnostics applied to Fe/Mo catalytic active-site models reveal structurally distinct electronic regimes across the redox series. Results suggest a stabilising electronic role for Mo across the catalytic landscape, supporting a more mechanistic interpretation of cofactor selection.
Materials science — cuprate superconductors
Cuprate superconductivity is one of the most electronically complex problems in condensed matter physics. ELSD is being applied to Cu–O plane cluster models to map correlation regimes and regime transitions in a classically difficult strongly correlated system.
Four electronic landscape regimes, across all domains
ELSD produces a regime classification, not just an energy value. The same four-class framework applies whether the system is a battery cathode, a metalloenzyme active site, a catalytic cluster, or a strongly correlated material — making results comparable across domains.
Perturbation finds nothing to split. Single basin retained across all ensemble seeds. The model is reliable enough to support downstream decision-making — ligand screening, dopant selection, or synthesis.
Multi-reference character present but well-structured. The ensemble converges within a single electronic family. Results are reproducible and the model is usable with appropriate care.
Two or more distinct electronic basins coexist under the same scaffold. The system cannot reliably resolve its electronic state. Results depend on starting conditions and should not be trusted without landscape diagnosis.
The active space or scaffold is too truncated or underconstrained to produce reliable results. Ensemble seeds diverge in ways that reflect model failure rather than physical electronic structure. Not safe to optimize against.
How ELSD is built
Four layers connecting industry problems to validated quantum computation. Each layer is purpose-built: the diagnostic engine, the GPU-native simulation infrastructure, and the QuantaCore™ hardware-validation architecture that underpins the simulation stack.
1 classification engine
~3–4 GPU hrs per target
UCCSD · 20-qubit operating point
Patent pending
Partner with us on electronically difficult targets
We work with battery developers, pharmaceutical R&D teams, catalyst designers, and materials scientists who need reliable electronic landscape classification before committing resources to synthesis, screening, or clinical-stage decisions.
Submit a candidate composition, active-site model, or dopant strategy. We return a full ELS classification report: regime, basin structure, trapped fraction, and design recommendations. No source code shared.
A defined evaluation campaign against your internal targets, with results benchmarked against your existing computational workflows. Designed for R&D teams assessing ELSD fit before a broader deployment decision.
Full platform deployed in your environment, running across your candidate pipeline on your hardware. For organizations screening many compositions or targets on an ongoing basis.
For organizations interested in platform rights, IP integration, or long-term strategic access. Details available under mutual NDA.
Bring us your electronically difficult target.
Whether it is a cathode composition, a metalloenzyme active site, a catalytic cluster, or a strongly correlated material — if conventional workflows are not giving you a reliable picture, ELSD is designed for exactly that problem.
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