Introduction

MicroQuantum is a general-purpose Python quantum computing SDK foundation. It is implemented independently, from scratch, with NumPy as the only hard dependency — it is not a wrapper around Qiskit, Cirq or OpenQASM.

MicroQuantum 1.1.0 ships a complete local stack:

Problem
   │   SamplingProblem · OptimizationProblem · HamiltonianProblem ·
   │   EigenvalueProblem · SearchProblem
   ▼
Algorithm
   │   VQE · QAOA · GroverSearch · PhaseEstimation · QFT · HHL · ...
   ▼
ExecutionPlan
   │   declarative, JSON-safe: work + backend + shots + bindings + seed
   ▼
ExecutionRuntime
   │   prepare · compile · submit · collect (batch / sweep / hybrid)
   ▼
Backend
   │   capability-driven contract: validate · supports · execute
   ▼
BackendResult
   │   statevector · density matrix · counts · expectations · samples
   ▼
Experiment / Analysis
       ExecutionRecord · ParameterSweep · SamplingAnalysis ·
       ExpectationAnalysis · StateAnalysis · ResultAggregator

Goals of this release

• A usable public SDK: pip install microquantum and go.

• A single dependency (NumPy) and an independent implementation.

• A capability-oriented backend architecture ready for future real hardware / cloud providers without rearchitecting the SDK.

• Reproducible, serializable results end to end.

What it is not

MicroQuantum does not provide hardware execution, a cloud platform, an enterprise database-backed experiment service, or an analytics dashboard. The architecture contains the boundaries where those would plug in later.

See the General Availability (v1.0.0) page for the full status and release notes.