Python orchestration, primitive compilation, deterministic simulation, TTL/photon emulation and traceable outputs.
Quantum Control Software Engineer
Trapped-ion control software from pulse intent to measurable evidence.
Deterministic timing, hardware adapters, photon acquisition, and evidence-gated calibration.
Measurement-aware pulse validation
Specify what real captures must prove across pulse width, alignment, phase window and repeatability.
Width · alignment · phase · repeatability 02 · ARCHITECTURERegistry and adapter-driven control
Keep device I/O, qubit growth and future transport or photonic links outside orchestration branches.
Maintainable · extensible · observable 03 · VERIFICATIONSoftware simulation + electrical emulation
Exercise the same contracts through deterministic simulation and TTL/photon hardware before any ion claim.
No-ion failure-path coverage 04 · FULL STACKOpenQASM → hardware → PMT evidence
Preserve circuit identity through primitive compilation, backend execution, photon acquisition and analysis.
Traceable circuit-to-photon ownershipM4i.66xx AWG/DDS adapter, multi-tone carrier control, SSB upconversion and hardware-specific APIs.
No personal Spectrum operation, eleQtron proprietary topology or physical-ion gate-fidelity claim.
01 · Measurement-aware timing validation
A timing claim is not complete until the scope agrees.
The interactive trace is a literature-informed model of the intended sequence. It defines the signals, timing relationships and acceptance questions that a real capture would need to verify.
- A / ΩAmplitude
- Ω1 / 2π = 94.8 kHz
- f / ωFrequency
- fμw ≈ 12.6 GHz
- τDuration
- 313 µs
- φPhase
- φ(t) = 0.749 sin(2π · 94.8 kHz · t)
Notation: A amplitude · Ω/2π Rabi rate · f frequency · ω/2π angular-frequency form · τ duration · φ phase · Δ detuning
Each channel has a fixed color. Pulse height is an ON/OFF envelope unless a paper reports intensity or Rabi frequency; stage widths are visually compressed.Evidence boundary: this is a composite literature model, not one experimental shot and not eleQtron proprietary calibration. Ref [1] reports the cooling sequence at an axial frequency of 117.48(11) kHz; Ref [2] reports the MAGIC gate in a different setup at 98.08 kHz. Unpublished hardware settings are shown as N/R (not reported).
References: [1] Sriarunothai et al., J. Mod. Opt. 65, 560–567 (2018) · [2] Nünnerich et al., Phys. Rev. X 15, 021079 (2025) · [3] eleQtron · MAGIC uses radio-frequency control
The scope is an engineering sidecar—not the shot-loop data plane.
University of Siegen apparatus descriptions place deterministic sequencing, detector acquisition and state discrimination inside the experiment loop. Oscilloscopes observe selected electrical nodes through probes or splitters for commissioning, validation and debugging.
- Laser lockPhotodiode, cavity transmission and error signal.
- RF / microwaveIF envelope, trigger, mixer or crystal-detector output.
- Clock / triggerTTL fan-out, camera-ready and AWG trigger alignment, skew and jitter.
- Detector front endPulse amplitude, noise, threshold, saturation and signal integrity.
Python/SCPI can configure the scope, acquire waveforms and emit commissioning, calibration or monitoring artifacts. The real-time controller still owns shot scheduling, while detector interfaces and analysis software own structured photon counts, frames, timestamps and bright/dark decisions.
Not claimed: eleQtron's current oscilloscope vendor, bandwidth, sample rate, channel count or installed topology are not public.System-study references: [4] Piltz, 2016 · EMCCD/PMT triggering and ADwin sequencing · [5] Huber, 2024 · AWG hand-off and image feedback · [6] eleQtron · Python control software and programmatic device control · [7] DLR QSea II · SPAD and control-electronics integration direction
Requested window, sample depth and scope readback must agree. A plausible trace from a shortened pre-trigger record is rejected.
All channels must share one record length, and the expected dark window must prove that the capture contains the intended shot phase.
Repeated captures must agree numerically. A conflicting capture stays a disagreement; it is never averaged into a green result.
02 · Extensibility and maintainability
Scale qubits by adding contracts—not branches.
The orchestration core should not care whether control stays in one zone, crosses a shuttling boundary or reaches another module through a photonic link. Hardware-specific behavior belongs behind registries and adapters.
Core mechanisms implemented Shuttling & photonic links: architecture targetsOne source of truth
Process, dataset and backend registries define what exists. A new lane cannot silently omit its timing probe, readback contract or safety gate.
Hardware owns its I/O
The implemented control contract keeps orchestration separate from device I/O. Spectrum M4i.66xx/DDS is modelled as an eleQtron-facing adapter target; shuttling and photonic links enter through the same seam—not an if qubits > N rewrite.
Agents can change it safely
Code maps identify ownership; contract tests detect registry drift; fail-closed admission blocks incomplete capability or stale runtime evidence before execution.
- 1 · Read contractLocate registry, dataset owner and evidence boundary.
- 2 · Add adapterKeep device-specific I/O outside orchestration.
- 3 · Run guardsCatch drift, stale mappings and unsupported paths.
- 4 · Emit evidenceRetain provenance, limitation and terminal outcome.
03 · Timing verification system
Test the same contract through two independent realities.
A fast deterministic simulator checks logic and data contracts. An electrically live lane runs the production hardware-timed control core with real TTL/DDS envelopes and a controlled photon source—still without ions.
Verification lanes implementedDeterministic software simulation
Compile the exact primitive OpenQASM, execute synthetic counts and verify repeatable evidence without lab network access.
- Same primitive circuit and execution contract
- Mid-circuit measurement and reset on a Clifford stabilizer lane, per-shot syndrome history hash-bound in evidence — no classical feedback yet
- Deterministic replay and evidence hash
- Freshness, all-dark and capability failures are injectable
- Proves software behavior—not RTIO or wiring
Electrically live control path
The production control core runs on the test master; a scope observes physical 369/935 envelopes while controlled TTL photon pulses exercise the counter/readout chain.
- Real FPGA-backed scheduling and deterministic timeline
- Scope-visible DDS/TTL timing envelopes
- Controlled photon counts through the acquisition boundary
- Proves electrical/dataflow integration—not ion physics
Fail-closed evidence ladder: software-sim results cannot enter calibration; electrically live results cannot claim state preparation or gate fidelity; physical-ion verified capability remains explicitly separate.
Mid-circuit measurement & reset, honestly scoped: a measured qubit is retired until a reset, so without classical feedback the joint statistics are provably those of deferred measurement and the ideal statevector lane is untouched. reset is a discard-and-prepare channel (not a projection) and runs only on the Clifford stabilizer lane, where every shot collapses; the aggregate counts keep each qubit's last measurement while the full per-shot syndrome history is a hash-bound evidence artifact and a bounded summary feeds the desktop view. None of this models per-ion reset on hardware — global pumping and detection beams, shelving and shuttling stay hardware boundaries, and classical feedback is still out of scope.
04 · Circuit-to-photon full stack
Own every boundary from algorithm to evidence.
The system does not stop at compilation or pulse generation. It carries circuit identity through execution, photon acquisition, analysis and a claim that includes its own limitation.
OpenQASM → control contract → counts implemented Spectrum M4i.66xx AWG/DDS: integration targetThe diagram distinguishes implemented software contracts from the publicly documented eleQtron microwave backend, which is presented as an integration target rather than personal hands-on evidence. Horizontal scrolling is available on narrow screens.
Python contract to microwave carrier.
Python / control services
↓
Spectrum M4i.66xx AWG + M4i.66xx-DDS
↓
SSB mixer + microwave LO
↓
fμw ≈ 12.64 GHz → 171Yb+ MAGIC processor
Spectrum’s official eleQtron case study identifies the M4i.66xx series as the microwave qubit-control AWG family. The control-software and FPGA boundaries are consistent with eleQtron’s public engineering roles: Python APIs/data interfaces above hardware-specific I/O, and FPGA signal generation plus real-time feedback below.
References: [4] Spectrum Instrumentation · DDS technology enables microwave ion control for quantum computing · [5] eleQtron · Senior Software Engineer—Python control software · [6] eleQtron · FPGA Engineer—Quantum Computing
Claim boundary: the public source confirms the M4i.66xx series, not an exact installed submodel. M4i.6631 appears in the article image caption only. No claim is made about eleQtron’s laser, camera, trap-DAC or laboratory-wide sequencer stack.
Selected research · application bridge
Translate application questions into executable quantum workflows.
Collaborations across quantum machine learning, generative chemistry and quantum chemistry gave me a working vocabulary on both sides of the interface: domain objectives and benchmarks on one side; circuits, simulators, hardware constraints and defensible evidence on the other. Google Scholar profile ↗
Unentangled quantum reinforcement learning agents in the OpenAI Gym
Application → experimentTurned standard reinforcement-learning tasks and metrics into a single-qubit variational workflow, classical post-processing and execution on real IBM quantum machines.
Read the arXiv preprintExploring the Advantages of Quantum Generative Adversarial Networks in Generative Chemistry
Domain objective → hybrid modelConnected small-molecule generation goals to hybrid quantum-classical GAN components, then compared physicochemical, goal-directed and validity trade-offs.
Read the ACS paperQuantum simulation of preferred tautomeric state prediction
Scientific workflow → resource constraintsMapped a drug-discovery question through active-space selection, qubit-efficient encoding and VQE while retaining benchmark and hardware-resource limits.
Publisher-stated contribution: performed noiseless and noisy quantum simulations with Yu Shee.
Read the npj paperThese publications evidence cross-domain collaboration in quantum applications. They complement—but do not replace—the separately labelled software and electrical evidence for the trapped-ion control system above.