HELIOS-3D
Current Updated 2026-06-03

Targets Comparators And Projections

The following analysis contextualizes the HELIOS-3D research hypothesis against established and upcoming neuromorphic architectures. These comparisons represent theoretical aspirations and are intende

SPECULATIVE

Write speed (log scale, ps)

Mn3Sn AFM (Tsai 2026)
40 ps
Optical-to-SOT (Tsai 2026)
60 ps
Polaritonic switch (Wang 2026)
~1 ps regime
CMOS baseline
~5 ns

Energy density (pJ/µm²)

Mn3Sn AFM (Tsai 2026)
1.700
Polaritonic (Wang 2026)
0.004
HELIOS target
1.000

Intel Loihi 2 / Hala Point

pJ / op

4nm CMOS spiking. Active cooling required. Established neuromorphic baseline.

IBM NorthPole

~pJ / op

12nm near-memory SRAM inference accelerator, 288-card prototype. Active cooling required.

HELIOS-3D (hypothesis)

fJ range

Topological magnonics, heat-scavenging BRC. Aspiration only — not yet demonstrated end-to-end.

Aspiration vs. demonstration

Standalone spintronic components have demonstrated low switching energy in isolated laboratory conditions. Achieving those metrics in a volumetric, multi-core integrated system remains an unverified research goal. Any projected improvements depend on the exact material stack, readout path, and thermal regime — treat the fJ targets as a research envelope, not a forecast.

Write speed (log scale, ps)

Mn3Sn AFM (Tsai 2026)
40 ps
Optical-to-SOT (Tsai 2026)
60 ps
Polaritonic switch (Wang 2026)
~1 ps regime
CMOS baseline
~5 ns

Energy density (pJ/µm²)

Mn3Sn AFM (Tsai 2026)
1.700
Polaritonic (Wang 2026)
0.004
HELIOS target
1.000

🏆 Comparative Potential and Research Projections

The following analysis contextualizes the HELIOS-3D research hypothesis against established and upcoming neuromorphic architectures. These comparisons represent theoretical aspirations and are intended to define the research “hypothesis envelope.”

📊 Comparative Scaling Potential (Conceptual)

FeatureIntel Loihi 2 / Hala Point-classIBM NorthPoleHELIOS-3D (Hypothesis)Status
Mechanism4nm CMOS Spiking12nm Near-Memory SRAM Inference AcceleratorTopological Magnonics[SPECULATIVE]
ThermodynamicsJoule-constrainedJoule-constrainedHeat-scavenging[SPECULATIVE]
Efficiency TargetpJ range~pJ/op (measured, 288-card prototype)fJ range aspiration[SPECULATIVE]
Power ScalingActive cooling req.Active cooling req.Thermally assisted[SPECULATIVE]

Mechanism is demonstrated only for related standalone physical experiments, not for the full HELIOS-3D system.

⚠️ Aspiration vs. Demonstration

While standalone spintronic components have demonstrated low switching energy in isolated laboratory conditions, achieving those metrics in a volumetric, multi-core integrated system remains an unverified research goal. Any projected improvements depend on the exact material stack, readout path, and thermal regime.

📚 Evidence Mapping

🧪 Section A: Foundational Physics and Device Papers

  1. [Topological Spintronics] Magnetic skyrmions: materials, manipulation, detection, and applications. (2024). [Evidence: room-temperature skyrmion stability in specific multilayers].
  2. [3D Magnonics] Breathing modes of skyrmion strings in a synthetic antiferromagnet multilayer. (2025). [Evidence: microwave-detectable collective modes in 3D-like textures].
  3. [Thermodynamic Computing] Nonlinear thermodynamic computing out of equilibrium. (2024). [Evidence: noise-powered logic in nano-scale reservoirs].
  4. [van der Waals Magnets] Room-temperature single-layer 2D van der Waals ferromagnetic ferromagnet hosting skyrmions. (2024). [Evidence: Curie temperature for Fe3GaTe2 on flat substrates].
  5. [Dynamics] Current-driven dynamics of antiferromagnetic skyrmions. [Evidence: neutralization of SkHE in SAF systems].

📈 Section B: Benchmark and Context Assumptions

  1. [Grid Demand] International Energy Agency. (2024). Electricity 2024: Analysis and forecast to 2026. [Context: data center energy trajectory].
  2. [Intel Loihi 2] Loihi 2: A 4nm Neuromorphic Research Chip. [Context: competitive pJ-scale baseline].
  3. [IBM NorthPole] A Scalable NorthPole System with End-to-End Vertical Integration for Low-Latency and Energy-Efficient LLM Inference. (2025). [Context: SRAM-based near-memory inference accelerator, 288-card prototype].
  4. [IEA 2026] Energy demand from AI. [Context: LLM power consumption projections].

📰 Section C: Commentary Only

  1. IBM’s new North Pole Chip is a big deal. Medium commentary. [Context only].
  2. Thermodynamic Computing Breakthrough. Berkeley Today summary. [Context only].