DecaQ Launches Cloud Beta 2 with 400 Logical Digital Qubits and Six Quantum Algorithm Families
DecaQ Launches Cloud Beta 2 with 400 Logical Digital Qubits, Six Quantum Algorithm Families and up to 200,000 digital
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DecaQ Launches Cloud Beta 2 with 400 Logical Digital Qubits, Six Quantum Algorithm Families and up to 200,000 digital oracle gates.
QPU-free, NO quantum noise.
PETACH TIKVA, ISRAEL, September 29, 2026 /EINPresswire.com/ — DecaQ Launches Cloud Beta 2 with 400 Logical Digital Qubits and Six Quantum Algorithm Families
Powered by a Digital Quantum Oracle, the platform supports up to 200,000 digital oracle gates on general-purpose hardware – without physical qubits, a QPU, or quantum hardware noise.
ISRAEL, September 29, 2026 — DecaQ today announced the availability of DecaQ Cloud Beta 2, bringing 400 logical digital qubits, six quantum algorithm families, and up to 200,000 digital oracle gates to its cloud platform.
DecaQ is deterministic digital quantum computation powered by a Digital Quantum Oracle. Supported workloads run on general-purpose hardware without physical qubits, a quantum processing unit (QPU), or quantum hardware noise. The platform is not a quantum simulator, a state-vector simulator, or a tensor-network simulator.
Cloud Beta 2 brings together oracle evaluation, phase estimation, and energy and optimization capabilities in a single cloud platform for researchers, developers, and enterprise R&D teams.
## Six Families, Three Areas of Capability
Oracle evaluation:
Bernstein–Vazirani (BV) and Deutsch–Jozsa (DJ) support parity-mask identification and function classification, providing capabilities for examining oracle logic, parity relationships, and constant-versus-balanced function behavior.
Phase estimation:
Iterative Phase Estimation (IPE) and Quantum Phase Estimation (QPE) provide sequential phase-bit and phase-word readout, supporting the investigation of phase information and eigenvalue-related properties in supported models.
Energy and optimization:
The Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimization Algorithm (QAOA) support local-energy and graph-partitioning reference workloads, providing a basis for exploring energy-estimation and optimization applications.
## Research and Application Development
These six families provide research pathways toward chemistry and materials, physical-system analysis, timing and phase readout, operations and network allocation, and rule diagnostics.
The release’s reference examples include local-field energy, encoded delay readout, and wireless-channel partitioning. These examples give users concrete starting points for evaluating the platform’s supported capabilities and exploring their relevance to research and application development.
## Cloud Availability
DecaQ Cloud Beta 2 is now live. Researchers, developers, and enterprise R&D teams can contact DecaQ through DecaQ.ai to discuss beta access and supported workloads.
## About DecaQ
DecaQ develops deterministic digital quantum computation powered by a Digital Quantum Oracle. Its technology executes supported quantum workloads on general-purpose hardware without physical qubits, a QPU, or quantum hardware noise. DecaQ Cloud provides access to this architecture for research, development, and evaluation.
**Media and beta access enquiries: DecaQ.ai**
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