The phrase "wireless power transfer by quantum tunneling" is, read literally, a category error. Single-particle electron tunneling through a vacuum or dielectric barrier is suppressed as with for a metal–vacuum–metal junction. Delivering one coulomb across a one-metre gap by direct tunneling requires roughly attempts. This is not a hard engineering problem. It is not on the ledger at all.
But the no-go is not a prohibition — it is an invoice, and the invoice itemises what is being charged. The exponent decomposes into three purchasable quantities: barrier width , barrier height , and carrier effective mass . The first two are bounded by materials. The third is not: setting selects the photon, for which the identical 1D equation returns , set by resonator geometry rather than by the electron rest mass. The mass discount is nine orders of magnitude in the exponent, and it is the entire physical content of resonant near-field wireless power transfer (WPT).
Having taken that discount, the near-field grid then meets two further prices, which we derive: The reactive-power wall. Delivering across with coils of radius requires circulating reactive power with . A 1 GW / 100 km near-field link would circulate VA — roughly 500× global installed generating capacity. The exposure wall. We derive a previously unremarked scaling: the ICNIRP-compliant public exclusion radius of a magnetoquasistatic link is independent of coil radius. Aperture size, the designer's main free variable, cancels exactly. Exclusion zone is a function of the service (power, distance), not of the hardware.
Together these price near-field WPT into a specific and narrow envelope. We show the model retrodicts the observed deployment envelope without fitting: resonant coupling is aperture-competitive against 2.45 GHz beam-forming only below m for normal-conductor coils, which is precisely where all deployed WPT lives.
Tunneling then re-enters the grid decisively — but at the terminals, not in the link. Metal–insulator–metal tunnel junctions are the only rectifiers fast enough for infrared and terahertz rectennas (femtosecond transport, no minority-carrier transit). Band-to-band tunneling FETs break the 60 mV/decade Boltzmann floor that bounds all thermionic switching. Josephson junctions provide the voltage standard, the SQUID current sensor, and the cryogenic control logic. The unifying claim: Tunneling is not the wire. Tunneling is the terminal.
We close with seven dated falsifiable predictions and an open-problems list.
An essay. A thesis put forward by its author — an argument, specification, or design — and not a verified result.
1. The claim under test
The request that motivates this paper — build a wireless electric grid on quantum tunneling — is worth stating precisely enough to be wrong:
H₀. There exists a device architecture in which quantum-mechanical tunneling of charge carriers serves as the primary power-transport channel across macroscopic distances, at efficiency and power density competitive with conducted transmission.
We reject H₀ decisively in §2, and then argue that the rejection is more informative than an acceptance would have been, because the form of the rejection identifies exactly which currency the physics is demanding. This is the analytical move used throughout: a no-go theorem is a price list written in the imperative mood.
Three successor hypotheses survive:
- H₁ (evanescent). The 1D barrier equation governing tunneling also governs classical evanescent electromagnetic coupling; substituting a massless carrier converts an intractable exponent into a geometric one. Accepted, with quantified limits.
- H₂ (terminal). Tunneling enters the wireless grid as rectifier, switch, and sensor rather than as transport. Accepted.
- H₃ (layered). No single mechanism spans the wireless grid; the currency changes character at each length scale, so the wireless grid is necessarily heterogeneous. Accepted as the paper's synthetic claim.
2. The transport no-go, priced
2.1 The exponent
For a particle of effective mass and energy incident on a rectangular barrier of height and width , the WKB transmission is
For a free electron, evaluating the constants:
[T] For a metal–vacuum–metal junction with eV, .
Code
Gap 2κd T
0.5 nm 10.9 1.9 × 10^-5
1 nm 21.7 3.6 × 10^-10
10 nm 217 10^-94
1 µm 2.17×10^4 10^-9442
1 m 2.17×10^10 10^(-9.4×10^9)2.2 The invoice
[T] To deliver one coulomb ( electrons) across a 1 m vacuum gap by direct tunneling requires incidence attempts. For calibration: the observable universe contains baryons and has existed for Planck times, giving an absolute ceiling of elementary events in all of cosmic history. The requirement exceeds the budget by a factor of .
This is worth stating in this vulgar form because it forecloses a specific rhetorical move. There is no clever geometry, no array multiplicity, no resonance, and no material that recovers . Arrays buy linear factors. Resonances buy polynomial factors. The deficit is exponential in a quantity of order .
[T] Setting a marginal detection floor of , the maximum single-barrier electron tunneling gap is:
nm at eV (metal–vacuum) nm at eV (engineered low-barrier heterostructure)
Conclusion: H₀ is rejected. Charge tunneling is a nanometre-scale phenomenon and will remain one under any materials engineering consistent with known physics. [T]
2.3 Reading the invoice: three levers
The rejection came from a single number, and that number is a product of three factors:
: bounded below by atomic spacing (0.2 nm) and above by nothing — but the whole problem is that we need it large. : reducible from ~5 eV to ~0.1 eV by heterostructure design; buys in . Real, but a rounding error against . : here is the interesting term. It is the only factor in the exponent that is a property of the carrier rather than the barrier. Effective-mass engineering in semiconductors reaches
(InSb), buying .
But has a limit the others do not: it can be exactly zero.
This is the permission structure. The barrier problem does not say "no transport at range." It says: *the exponent is priced in
, and you may choose your carrier.*
3. The mass discount: Schrödinger–Helmholtz correspondence
3.1 The formal identity
Separate the Helmholtz equation for a monochromatic field in a source-free region, with transverse wavenumber
:
=(k ∥ 2
− c 2 ω 2
)ψ
Compare the time-independent Schrödinger equation in the classically forbidden region:
𝜓 ∂z 2 ∂ 2 ψ
= ℏ 2 2m ∗ (V−E)
ψ
[T] These are the same equation. The correspondence is exact:
(3.1) κ e 2
= ℏ 2 2m ∗ Φ
⟷κ γ 2
=k ∥ 2
− c 2 ω 2
(3.1)
This is not a metaphor. Frustrated total internal reflection is the optical realisation, and is correctly and standardly called photon tunneling. Evanescent decay across a sub-wavelength gap and electron decay across a barrier are the same boundary-value problem.
3.2 The epistemic firewall
This is the point at which the literature on "quantum wireless power" typically goes wrong, and it is worth being explicit.
The correspondence is exact at the level of the differential equation and empty at the level of the mechanism. Magnetoquasistatic coupling between two 85 kHz coils is a solution of Maxwell's equations with no quantum content whatsoever; the field is a coherent state with photon occupation numbers of order , and every observable is classical. Calling it "tunneling" is legitimate as a statement about the mathematical structure of the field decay, and illegitimate as a claim about quantum mechanics doing work in the device.
[T] The correspondence licenses the scaling analysis below. It licenses nothing about quantum advantage, entanglement, coherence, or any other quantum resource in the power link.
Any claim that a macroscopic WPT link derives performance from quantum mechanics — as opposed to from classical resonance — should be treated as false until the claimant exhibits a measurable that distinguishes it from the classical solution. [T]
3.3 Sizing the discount
For a sub-wavelength resonator of characteristic size , the near field is dominated by , and since we have :
- 𝜅
- 𝛾
- ≈
- 1
- 𝑎
(3.2) κ γ
≈ a 1
(3.2)
[T] The evanescent decay length equals the source size. A 30 cm coil has a 30 cm decay length. This single fact is the whole of resonant WPT.
The discount ratio:
m − 1 × 0.3 m ≈ 3.3 × 10 9 κ γ
κ e
= ℏ 2m e
Φ
a=1.09×10 10 m −1 ×0.3 m≈3.3×10 9
[T] Choosing a massless carrier reduces the decay coefficient by for a 30 cm resonator. The exponent goes from — a compound of the electron rest mass and the vacuum work function, neither of which is negotiable — to , which is a line item in a bill of materials.
This is the central result of Part I. The impossible thing becomes an engineering choice the moment the correct currency is identified. The currency was carrier mass.
4. The evanescent grid and its own no-gos
The mass discount is real but not unconditional. Having bought a geometric exponent, we now discover what geometry charges.
4.1 Coupled-mode theory
Two resonators with coupling rate and intrinsic loss rates . Define the strong-coupling figure of merit:
where is the magnetic coupling coefficient. [T] At optimal loading, the maximum end-to-end efficiency is
- :
- :
- :
- :
- :
- :
[T] Efficiency is a function of alone. Distance enters only through .
4.2 The Q¹⁄³ range law
For coaxial coils of radius at separation , with and (form factor ):
Substituting into (4.1) with and solving for range at fixed :
[T] Range scales as the cube root of quality factor.
With , ():
- - : — Litz copper, routine [E]
- - : — Optimised copper / low-loss dielectric [E]
- - : — HTS coil, 77 K [C]
- - : — Beyond any demonstrated low-frequency coil [O]
- - : — Exceeds best SRF cavities by [O]
[T] The cube root is the wall. Extending range from 1 m to 1 km at fixed aperture demands . Distribution feeders run 1–30 km. There is no that reaches them.
The alternative is to scale , which enters linearly. A 10 km link at requires — a superconducting resonator the footprint of a large generating station. This is where the second wall appears.
4.3 The reactive-power wall
Power crosses the gap through the mutual term; the primary must circulate the rest. To order of magnitude,
[T] (The prefactor depends on loading and is not pinned here; the scaling is robust.)
- EV pad: , , , ,
- Warehouse node: , , , ,
- Distribution feeder: , , , ,
- Transmission line: , , , ,
[T] A single 1 GW / 100 km near-field link would circulate VA of reactive power. Global installed electrical generating capacity is W. The circulating power exceeds it by a factor of .
This is the decisive result for H₀-adjacent proposals. Near-field WPT does not forbid grid-scale transmission; it prices it in circulating volt-amperes at , and no amount of touches that number — governs what fraction of the circulating power is lost, not how much must circulate. [T]
4.4 The exposure wall — a derived scaling
The circulating current produces a field, and the field is regulated. We derive the compliance geometry.
A coil of radius , turns, current has moment . From with :
(Note is independent of , as it must be.) The compliance radius where on-axis falls to the regulatory limit:
Substituting from (4.5), the coil radius cancels exactly:
[T] The public exclusion radius of a magnetoquasistatic power link depends only on delivered power and link distance — not on aperture size.
This deserves emphasis because it removes the designer's principal degree of freedom. One can trade coil size against , against current, against turns count — and the exclusion zone does not move. It is a property of the service being sold, not of the hardware selling it. : weakly sensitive to power, strongly sensitive to range.
Regulatory inputs. ICNIRP (2020) supersedes the 100 kHz–10 MHz range of ICNIRP (2010). General-public whole-body reference levels, 0.1–30 MHz, averaged over 30 min: A m⁻¹ and V m⁻¹. Local exposure (6 min): A m⁻¹. Peak instantaneous, 100 kHz–10 MHz: A m⁻¹. [E]
- 6.78 MHz (ISM): ,
- 13.56 MHz: ,
- 85 kHz (SAE J2954): below ICNIRP 2020 scope, [E, verify]
[T] Below 100 kHz, ICNIRP (2010) governs, with a general-public flux-density reference level roughly 66× more permissive than the 2020 value at 6.78 MHz. This is why deployed automotive WPT operates at 85 kHz. The frequency was not chosen by coupling physics — coupling is frequency-independent in — but by the shape of the regulatory curve immediately below its discontinuity. [C, strong] The industry standard sits where it does because of a boundary in a document.
Worked exclusion radii at 85 kHz, :
- - Warehouse node: , , , keep-out area 300 m²
- - Feeder: , , , keep-out area 6.8 ha
- - Transmission: , , , keep-out area 32 km²
[T] A 1 GW wireless transmission link would impose a 3.2 km public exclusion radius — 32 km² of uninhabitable right-of-way, against roughly 0.3 km² for a conventional 100 km overhead line at 60 m width. Wireless transmission is land-hungrier than wire by two orders of magnitude, which inverts its principal claimed advantage. [T]
4.5 The cryogenic break-even theorem
Superconductivity is the obvious route to the that buys range. It has a price with a closed form.
At fixed distance, resonator loss is . Raising by reduces loss by . But the refrigerator consumes watts of wall power per watt lifted. Break-even requires:
[T] With Carnot and practical machines at 10–20% of Carnot:
- - 77 K (LN₂/HTS): Carnot COP 0.345, practical COP ~0.07, required , range gain 2.5×
- - 20 K: Carnot COP 0.071, practical COP ~0.010, required , range gain 4.6×
- - 4 K (LHe/LTS): Carnot COP 0.014, practical COP ~0.002, required , range gain 7.9×
[T] At the break-even point, the range gain is exactly — because range goes as while the energy penalty goes as . A system operating at 20 K must find a advantage merely to break even energetically, and that purchases only in range.
[C] This is the honest verdict on superconducting near-field WPT: the cryogenic overhead scales faster than the benefit, by a power of three. HTS at 77 K is the only regime where the arithmetic is close, and it buys 2.5×.
4.6 Where the near-field niche actually ends
Compare aperture requirements against radiative beam-forming (developed in §6). Setting the near-field coil radius from (4.4) equal to the Fresnel-zone aperture radius and solving:
[T] At 2.45 GHz (), , :
- - (copper): crossover distance 0.40 m
- - : crossover distance 1.9 m
- - : crossover distance 40 m
Beyond ~0.4 m, microwave beam-forming needs a smaller aperture than resonant coupling to move the same power — with normal-conductor coils, which is what exists. [T]
This is a genuine retrodiction, not a fit. The model was constructed from first principles with no reference to deployment data, and it places the near-field/far-field crossover at ~0.4 m. Every commercially deployed WPT system — Qi phone charging (~5 mm), medical implant links (~1–3 cm), SAE J2954 automotive pads (~10–25 cm), industrial AGV charging (~5–15 cm) — operates below that line. [E] The single class of demonstrated systems approaching it is heavy-duty vehicle charging under SAE TIR J2954/2, specified to 500 kW with larger ground assemblies. [E]
The theory predicted the envelope. The envelope is what exists. This is the strongest available evidence that the pricing model is correct, and correspondingly the strongest evidence that proposals to extend near-field WPT to distribution ranges are not incremental but categorical.
5. Where tunneling actually enters the grid
Having excluded tunneling from transport, we now find it is load-bearing at both terminals — and in one place, structurally unavoidable.
5.1 The rectifier: MIM tunnel junctions
This is the strongest genuine claim in the paper. Above roughly 1 THz, conventional semiconductor rectification fails: minority-carrier transit times and junction capacitance impose an RC ceiling no doping profile evades. Metal–insulator–metal (MIM) tunnel diodes rectify by direct barrier tunneling, a process with femtosecond transport time, and are therefore the only known rectifying element viable for infrared and terahertz rectennas. [E]
Asymmetry arises from dissimilar electrode work functions producing a trapezoidal barrier; multi-insulator stacks (MIIM, MI³M) engineer step or resonant barriers for larger zero-bias nonlinearity. Reported figures of merit: asymmetry ~6 at 0.1 V and responsivity 4.3 A/W at 0.35 V for ALD-grown MI³M stacks; zero-bias responsivity A/W for Au/Al₂O₃/Ti. [E] Notably, one careful study found that resonant tunneling in triple-insulator stacks does not deliver the low-bias enhancement previously reported, and that dissimilar-metal asymmetry is the more promising route — a negative result worth more than the positive ones it corrects. [E]
The trilemma. Three requirements are mutually antagonistic, and the constraint is derivable:
- Impedance match to the nano-antenna:
- 𝑅 𝑑 ≈ 50 – 200
Ω R d
≈50–200 Ω. RC cutoff:
- .
- Responsivity : large nonlinearity requires thick or high barriers, which raise
exponentially.
With , (Al₂O₃), nm:
Junction area Max
at 28.3 THz (10.6 µm)
( 100 nm ) 2 (100 nm) 2 398 aF 14 Ω — unmatched, unbuildable
( 50 nm ) 2 (50 nm) 2 100 aF 56 Ω
( 20 nm ) 2 (20 nm) 2 16 aF 354 Ω — matchable
[T] Long-wave infrared rectification requires junction areas below ~ ( 30 nm ) 2 (30 nm) 2 . This caps power per element, forcing array multiplicity: a antenna under 1 kW m⁻² collects ~10 nW, so a 1 W panel requires elements, and 1 m² of collector requires junctions.
[C] The binding constraint on optical rectennas is therefore not the diode physics — which is understood — but interconnect and yield across devices per square metre, each delivering nanowatts at tens of millivolts. Series-parallel network losses and the statistics of junction-parameter dispersion will dominate system efficiency long before any single-device figure of merit does. This is a falsifiable prediction about where the field's effort will be misallocated. (See P3, §7.)
5.2 The switch: tunnel FETs and the Boltzmann floor
Every thermionic switch — every MOSFET ever built — is bounded by
min = 𝑘 𝑇 𝑞 ln 10 ≈ 60 mV/decade at 300 K SS min
= q kT
ln10≈60 mV/decade at 300 K
[T] This is a statistical-mechanical floor, not a fabrication limit. It follows from the Boltzmann tail of the source carrier distribution, and it is the reason supply-voltage scaling stalled in the mid-2000s: cutting
by 60 mV multiplies off-state leakage by ten.
TFETs switch by gate-modulated band-to-band tunneling rather than thermionic emission over a barrier. Because the tunneling window is bounded by band edges rather than by a thermal tail, the Boltzmann floor does not apply. [T] Sub-60 mV/decade operation has been demonstrated experimentally since 2007 (52.8 mV/dec, 70 nm Si n-channel); Ge-source S-TFETs report ~45 mV/dec with at V. [E] The persistent liability is low drive current and ambipolar conduction. [E]
Grid relevance — and this is the pivotal reframe of §5: tunneling is the only known mechanism that breaks a thermodynamic bound on switching energy. A wireless grid is not a link; it is a control problem. Dynamic road charging requires coil-segment switching at vehicle speeds; a resonant node requires continuous impedance retuning against a moving load; exclusion-zone interlocks require always-on presence sensing. All of it is switching energy, all of it is bounded by 60 mV/decade, and TFETs are the only announced escape.
[C] The efficiency ceiling of a distributed wireless grid will be set by its control electronics, not its links, once link efficiency exceeds ~95% — because control is continuous and always-on while transfer is intermittent.
5.3 The sensor and the clock: Josephson junctions
Cooper-pair tunneling through a weak link obeys and
, giving the exact frequency-voltage relation GHz/mV. [T] Consequences for grid instrumentation:
- Voltage metrology. The Josephson effect realises the SI volt. Every calibration chain in every grid meter terminates in a tunneling phenomenon. [E] Tunneling already defines the unit in which the grid is billed.
- Current sensing. SQUIDs offer non-contact, galvanically isolated current measurement at sensitivities inaccessible to Hall or Rogowski devices — directly relevant to fault location and to metering a link that has no conductor to clamp.
- Cryogenic control. Single-flux-quantum logic switches at J/gate, some four orders below CMOS, and is the natural control layer for any system already carrying a cryostat for HTS resonators.
[C] The structural connection. The that buys range in §4.2 comes from superconductivity. Superconductivity is macroscopic phase coherence of a Cooper-pair condensate. Josephson tunneling is that coherence made measurable. The tunneling and the range are not two technologies bolted together — they are the same physics observed at two scales. This is the one place where H₀'s intuition was pointing at something real, arriving by the wrong route.
5.4 Tunneling as the adversary
Symmetry demands the negative case. In today's grid, tunneling appears overwhelmingly as loss:
- Gate-oxide direct tunneling sets static leakage in every power-converter controller. [E]
- Fowler–Nordheim injection into gate dielectrics is a dominant wear-out mechanism in SiC and GaN power devices, and therefore a limit on converter lifetime. [T/E]
- Field emission from asperities initiates vacuum-interrupter breakdown in medium-voltage switchgear. [E]
[C] Integrated over installed base, tunneling currently costs the grid far more energy than it delivers, and will continue to for at least a decade. Any honest roadmap must show the crossover date at which tunneling becomes net-positive infrastructure. We do not believe that date is calculable with present data. [O]
6. The far-field complement
If the wireless grid is to reach beyond metres, it must radiate. The pricing changes character completely — from circulating VA to aperture area.
6.1 Aperture pricing
The Fresnel-zone beam-collection efficiency between two apertures is governed by the Goubau parameter:
(6.1) τ= λd A t
A r
,η beam
≈1−e −τ 2 (6.1)
[T] gives 98.2% capture. Equal apertures then require radius
:
- Link Aperture radius (each end)
- Campus 1 km 12.2 cm (2.45 GHz) 8.8 m
- Regional 100 km 12.2 cm 88 m
- Regional 100 km 1.06 µm (laser) 0.26 m GEO→ground 35,786 km 12.2 cm 1.67 km
[E, consistency check] The GEO figure of 1.67 km radius is independently corroborated: Space Solar's proposed Cassiopeia satellite is designed at 1.8 km span for GEO microwave delivery. The formalism reproduces the industry's own sizing without adjustment.
[T] Note the wavelength leverage. Aperture scales as
, so moving from microwave to optical buys 12.2 cm / 1.06
12.2 cm/1.06 μm
=339× in aperture radius. This — not efficiency — is why laser beaming is winning the demonstration race.
6.2 State of the art DARPA POWER / PRAD (May 2025): >800 W optical delivered over 8.6 km in a 30 s transmission, >1 MJ across the campaign, ~20% end-to-end conversion, through the dense lower atmosphere. Prior record: 230 W at 1.7 km. [E] Phase 2 targets relay-to-target transmission; Phase 3 targets 5 kW across 200 km via three airborne relays at ~60,000 ft. [E] Star Catcher (Nov 2025): >1.1 kW optical to commercial off-the-shelf solar panels, >10 MJ across the campaign, at NASA Kennedy. [E] Caltech SSPD-1 / MAPLE (2023): first space-to-Earth directed microwave power transfer; power detected at Pasadena; 10-month mission deliberately pushed to failure to expose weaknesses. [E] SAE J2954 (2024): light-duty WPT standardised to 11 kW at up to 93% efficiency, with differential inductive positioning for alignment; J2954/2 specifies heavy-duty to 500 kW static and dynamic; J2954/3 for dynamic transfer in preparation. [E]
[C] The gap between the near-field and far-field state of the art is instructive: deployed near-field systems move 10⁴ W at 10⁻¹ m; demonstrated far-field systems move 10³ W at 10⁴ m. Five orders of magnitude in distance for one order in power. The trade is exactly what (4.6) and (6.1) predict.
6.3 The far-field's own wall
Beaming replaces the reactive-power wall with a flux-density wall. Delivering 1 MW through the 244 m² aperture computed above implies 4.1 kW m⁻² at the aperture, against an ICNIRP 2020 general-public reference level of 10 W m⁻² at 2.45 GHz. [E] The main beam is 410× over limit and is intended to be — the entire safety architecture lives in sidelobe suppression, keep-out volumes, and interlock latency, not in the beam itself.
[C] Far-field power beaming is not regulated as a field-exposure problem but as an aiming problem. Its risk profile is therefore governed by control-system reliability and failure modes, not by exposure physics — which places it in a different regulatory category than anything the electricity sector currently administers, and probably in a different one than the one it will initially be assigned. [O]
7. Architecture: the layered wireless grid
The synthetic claim (H₃). Each length scale is denominated in a different currency, and the currencies are not convertible:
Layer Range Mechanism Price paid in Status L0 0–10 nm Electron/Cooper-pair tunneling Barrier exponent Deployed as rectifier/switch/sensor [E] L1 0–0.4 m Magnetoquasistatic coupling Alignment tolerance Commercial [E] L2 0.4–40 m Resonant coupling, high Circulating VA + cryogenics + exclusion radius Research [C] L3 40 m–10⁵ m Microwave/optical beam Aperture area + pointing reliability Demonstration [E] L4 >10⁵ m Space solar Aperture × launch mass Proof of concept [E]
[T/C] There is no wireless technology that spans the grid. Conducted transmission is uniquely privileged in that a single mechanism — Ohmic conduction in a guided TEM mode — covers 10⁻³ m to 10⁶ m with efficiency varying only logarithmically. No wireless mechanism does this, because every wireless mechanism prices range in a quantity that diverges: exponentially (L0), cubically (L2), or quadratically in aperture (L3/L4).
This is the paper's central architectural claim, and it is a reversal of the usual framing. Wireless power is normally presented as the successor to wire. The pricing analysis says it is a complement occupying the niches wire handles badly — moving interfaces, sealed volumes, hostile environments, and orbits — and that a "wireless grid" is not a grid rendered wireless but a wired grid with wireless terminations.
7.1 The metering problem
One consequence deserves separate statement, because it is not a physics problem and is therefore easy to miss.
A conductor is an excludable good: power flows where copper goes, and a meter can be clamped around it. A field is not excludable. Any receiver within
of a resonant node can extract power from the shared mode, and — because it loads the same resonance — its extraction is observable to the transmitter only as an aggregate change in
, not as an identified draw.
[C] Wireless power reintroduces a commons problem into a system that solved it physically in the nineteenth century. Every wireless node therefore requires cryptographic power accounting: authenticated load signatures, challenge-response modulation of receiver impedance, or per-receiver spread-spectrum keying. The metering layer of a wireless grid is a computing problem of comparable difficulty to the link, and it has no analogue in the wired grid. [O]
We flag this as the most under-analysed component of every wireless-grid proposal we are aware of, including the ones that are otherwise technically careful.
8. Falsifiable predictions
Dated, with the observation that would refute each.
Prediction Horizon Refuted by Confidence
P1 No demonstrated electron-tunneling power transfer across any gap > 100 nm at efficiency > 10⁻⁶ 2031 Any peer-reviewed demonstration >0.999 P2 No commercial near-field WPT product delivering > 1 kW at 2031 Product datasheet 0.95 P3 Full-system optical/IR rectenna DC conversion efficiency remains < 5% under broadband illumination 2031 Certified measurement 0.85 P4 The highest-power deployed wireless grid asset remains vehicle charging at m — not any long-range system 2031 Deployment record 0.90 P5 At least one optical beaming demonstration exceeds 10 kW at > 10 km 2031 (confirmed by) DARPA POWER Phase 3 or successor 0.70 P6 No superconducting near-field WPT system in public distribution service 2035 Utility deployment 0.93 P7 No space-solar system delivers > 1 MW continuous to a terrestrial grid 2035 Grid interconnection record 0.80
P3 is the load-bearing prediction. It follows from §5.1: if the binding constraint is interconnect statistics across nanowatt junctions rather than diode figures of merit, then continued improvement in reported asymmetry and responsivity will not translate into system efficiency. Should P3 fail while single-junction figures of merit stagnate, the trilemma analysis is wrong. Should P3 hold while single-junction figures of merit continue improving, it is confirmed in the informative direction.
9. What would change the verdict
Honest statement of the conditions under which this paper is wrong. [O]
Room-temperature superconductivity at low AC loss. Equation (4.7) collapses if . Range still scales only as , but the energy penalty vanishes and L2 extends to perhaps 100 m. This is the single development that most changes the analysis. Note the specific requirement: not merely a high
, but low hysteretic and coupling AC loss at 10⁴–10⁷ Hz, which is a distinct and less-studied property. Revision of exposure limits.
, so a 10× relaxation shrinks exclusion zones by 2.15×. ICNIRP (2020) already relaxed 100 kHz–30 MHz reference levels relative to ICNIRP (1998) on improved dosimetry [E]; further revision is plausible but the cube root blunts it. Metamaterial near-field enhancement. Negative-permeability slabs can amplify evanescent components, effectively reducing
below . Whether this survives realistic loss is unresolved; the general expectation is that loss in any passive negative-index medium eats the enhancement, but we are not aware of a proof for the magnetoquasistatic case. [O] A rectifier that is fast without being small. The trilemma of §5.1 assumes with parallel-plate . A geometry decoupling capacitance from junction area — travelling-wave rectification, distributed tunnel junctions, or a mechanism with no lumped junction at all — would remove the elements/m² requirement and with it P3. [O] The de Sitter caveat. We have used flat-space Maxwell throughout. Nothing here depends on cosmological structure, and we make no claim that it should.
10. Claims Ledger
T = theorem/derivable · E = empirical/cited · C = conjecture · O = open
Claim Tag Basis
nm⁻¹ for free electrons T Eq. 2.1, constants C2 Metal–vacuum tunneling gap ceiling ≈ 1 nm at T Eq. 2.1 C3 1 C across 1 m requires ~ attempts T Direct C4 H₀ (tunneling as macroscopic transport) is rejected T C2, C3 C5 Schrödinger–Helmholtz correspondence is exact T Eq. 3.1, standard C6 Correspondence licenses scaling, not quantum advantage T §3.2 C7 Evanescent decay length = source size for sub-λ resonators T Eq. 3.2 C8 Mass discount ≈ for m T §3.3 C9 T CMT, Eq. 4.2 C10 for coaxial coils, T Eq. 4.3, C11 Range T Eq. 4.4 C12 ; prefactor unpinned T Eq. 4.5 C13 1 GW/100 km link circulates ~4.5 PVA ≈ 560× global capacity T C12 C14 , independent of coil radius T Eq. 4.6, derived here C15 ICNIRP 2020 general public 0.1–30 MHz:
A/m E ICNIRP 2020 Table 5 C16 85 kHz chosen for regulatory discontinuity, not coupling physics C C15 + SAE J2954 C17 1 GW wireless transmission needs 3.2 km exclusion radius (32 km²) T C14 C18 Cryo break-even requires T Eq. 4.7 C19 At break-even, range gain is only T C11, C18 C20 Near-field/far-field aperture crossover ≈ 0.4 m at T Eq. 4.8 C21 All deployed WPT lies below the C20 crossover E Qi, J2954, implants C22 C21 is an unfitted retrodiction of C20 C §4.6 C23 MIM tunnel diodes are the only viable IR/THz rectifiers E Femtosecond transport C24 MI³M asymmetry ~6 @0.1 V, responsivity 4.3 A/W @0.35 V E ALD literature C25 Resonant tunneling does not enhance low-bias rectification E Negative result, cited C26 28.3 THz rectification requires junctions < ~(30 nm)² T RC + match, §5.1 C27 ~ junctions/m² required for IR rectenna collection T C26 + flux C28 Rectenna binding constraint is interconnect/yield, not diode FoM C C27 → P3 C29 60 mV/dec is a Boltzmann floor, not a fabrication limit T Statistical mechanics C30 TFETs demonstrated ~45–53 mV/dec; low
persists E 2007–2025 literature C31 Wireless grid efficiency ceiling set by control, not links, above ~95% C §5.2 C32 GHz/mV; Josephson realises the SI volt E/T Metrology C33 Superconducting and Josephson tunneling are the same physics C §5.3 C34 Tunneling is currently net-negative for grid energy balance C §5.4 C35 Crossover date for C34 not calculable with present data O §5.4 C36 , T Goubau C37 GEO link needs ~1.67 km aperture; matches Cassiopeia's 1.8 km T/E §6.1 C38 DARPA PRAD: >800 W over 8.6 km, ~20% conversion, May 2025 E DARPA C39 Star Catcher: >1.1 kW optical, >10 MJ, Nov 2025 E Press release [verify] C40 SAE J2954: 11 kW light-duty at up to 93%; /2 to 500 kW E SAE 2024 C41 Beaming main beam runs ~410× over ICNIRP by design T/E §6.3 C42 Beaming risk is an aiming problem, not an exposure problem C §6.3 C43 No wireless mechanism spans the grid; conducted transmission is unique T/C §7 C44 A "wireless grid" is a wired grid with wireless terminations C C43 C45 Fields are non-excludable; wireless power reopens the commons problem C §7.1 C46 Cryptographic metering is a first-order requirement, not an add-on O §7.1 C47 Metamaterial evanescent enhancement under loss: unresolved O §9.3 C48 A capacitance-decoupled fast rectifier would void P3 O §9.4
Ledger summary: 22 T, 12 E, 14 C/O. The paper's load is carried by derivable results; the conjectures are concentrated in architecture (C31, C43–C46) and in the rectenna bottleneck (C28), which is where the falsification effort should go.
11. Closing frame
The request was a wireless grid built on quantum tunneling. The literal version fails by nine orders of magnitude in an exponent, and the failure is not close.
But reading the failure correctly returns something better than a refusal. The exponent is not a wall; it is an itemised bill, and one of its line items is the carrier's rest mass. Set that to zero and the same equation describes resonant near-field power transfer, which is real, standardised, and in production. The physics never said no. It said: *this costs
, and you did not have to bring an electron.*
Then it presented three more invoices — circulating volt-amperes, exclusion radius, cryogenic overhead — and those turn out to be the ones that actually bound the technology. They price the near-field grid into a 40 cm envelope, which is exactly the envelope in which it has been deployed. The model was not fitted to that fact.
And tunneling, having been excluded from the link, turns out to be indispensable at the terminals: the only rectifier fast enough for infrared, the only switch that escapes the Boltzmann floor, the definition of the volt in which the whole grid is billed.
The cartoon closes. The toy models are internally consistent and they identify the structure of the problem: five layers, five incommensurable currencies, and one unsolved accounting problem that no one is working on. They do not resolve the real engineering. The question of what a genuinely non-excludable power commons does to a grid that has never had one remains entirely open.
Author
- Oleksii Vergunenko
References
- 1.Regulatory
- 2.ICNIRP. Guidelines for Limiting Exposure to Electromagnetic Fields (100 kHz to 300 GHz). Health Phys 118(5):483–524, 2020. [Tables 2–9]
- 3.ICNIRP. Guidelines for Limiting Exposure to Time-Varying Electric and Magnetic Fields (1 Hz–100 kHz). Health Phys 99:818–836, 2010.
- 4.IEEE Std C95.1-2019, Safety Levels with Respect to Human Exposure to Electric, Magnetic, and Electromagnetic Fields, 0 Hz to 300 GHz.
- 5.ITU-R Report SM.2452-1 (07/2022), Electromagnetic field measurements.
- 6.SAE J2954_202408, Wireless Power Transfer for Light-Duty Plug-in/Electric Vehicles and Alignment Methodology.
- 7.SAE TIR J2954/2, Wireless Power Transfer & Alignment for Heavy Duty Applications.
- 8.Near-field WPT theory
- 9.Karalis, Joannopoulos, Soljačić. Efficient wireless non-radiative mid-range energy transfer. Ann. Phys. 323:34–48, 2008.
- 10.Kurs et al. Wireless power transfer via strongly coupled magnetic resonances. Science 317:83–86, 2007.
- 11.Haus. Waves and Fields in Optoelectronics. Prentice-Hall, 1984. [coupled-mode theory]
- 12.Goubau & Schwering. On the guided propagation of electromagnetic wave beams. IRE Trans. Antennas Propag. 9:248–256, 1961.
- 13.Tunneling devices
- 14.Simmons. Generalized formula for the electric tunnel effect between similar electrodes separated by a thin insulating film. J. Appl. Phys. 34:1793, 1963.
- 15.Fowler & Nordheim. Electron emission in intense electric fields. Proc. R. Soc. A 119:173, 1928.
- 16.Josephson. Possible new effects in superconductive tunnelling. Phys. Lett. 1:251, 1962.
- 17.Choi, Park, Liu. Tunneling field-effect transistors (TFETs) with subthreshold swing less than 60 mV/dec. IEEE EDL 28(8):743–745, 2007.
- 18.Allemang et al. Next-generation tunnel FETs: material perspectives and areal tunneling configurations. Mater. Quantum Technol. 5:042002, 2025.
- 19.Single and triple insulator Metal-Insulator-Metal diodes for infrared rectennas. Solid-State Electronics, 2021.
- 20.Eckmann et al. MIM-diode-like rectification in lateral 1T/1H/1T-MoS₂ homojunctions. Adv. Electron. Mater., 2026.
- 21.Power beaming
- 22.DARPA. POWER program sets distance record for power beaming. 16 May 2025. [PRAD: >800 W @ 8.6 km]
- 23.Caltech. Space Solar Power Project ends first in-space mission. Jan 2024. [SSPD-1 / MAPLE]
- 24.Star Catcher Industries. Press release, 4 Nov 2025. [>1.1 kW optical] [verify against peer-reviewed source]
Experimentation loop
0. Loop topology
paper claim ──► simulation ──► [revised claim] ──► experiment ──► decision rule
▲ │
│ │
└──────────────── ledger update / claim retirement ◄─────────────┘Three claims are already one full turn around this loop (C14, C20, C26 → C26′). The experiments below start from the revised ledger, not the paper's.
E1 — Coupling law and its validity floor
Tests: C10 (bounded), and the A2 diagnosis that the floor is .
Apparatus. Two air-core coils, mm, on a non-metallic optical rail. VNA, 2-port -parameters, 10 kHz–10 MHz. Non-conductive spacers; rail and mounts outside 3.
Method. Measure from at 20 separations spanning . Extract from the split-resonance frequencies () as an independent cross-check on the route.
Pre-committed decision rule.
Outcome Action Fitted slope for and for Confirm the simulated floor. C10 promoted to [T/E, bounded] Slope in range at Simulation's floor is too conservative; revisit the elliptic-integral saturation Slope out of range at Coupling model wrong. Halt the loop — everything downstream depends on
Cost/time. Existing VNA; ~£400 in coil formers. 3 days. Falsifies: C10, and by inheritance the bounds on C14 and C20.
E2 — The aperture-cancellation test (highest value)
Tests: C14 (bounded) — the paper's novel result, and the one the simulation demoted.
This is the experiment worth doing first. It measures something no one has reported, and the theory makes a sharp, counterintuitive, invariance prediction.
Apparatus. Three coil pairs, , 100, 200 mm. Each driven to deliver the same at the same (choose m so — all inside the validated domain). Calibrated 3-axis isotropic field probe (Narda EHP-50 class or equivalent), traceable calibration. Anechoic or open-field site; no conductive structure within .
Method. For each pair, map on spherical shells and locate where T. Critically: normalise delivered power at the load, not drive current — the invariance is a statement about constant service, and normalising the wrong variable destroys the test.
Prediction. identical across all three apertures to within 1.3% (simulated spread at ), despite a 4× range in coil radius and a 64× range in .
Pre-committed decision rule.
Outcome Action Spread C14 promoted to [T/E, bounded]. This is a publishable invariance. Proceed to E3 Spread 5–20% Cancellation partial. Identify the residual term — likely finite conductor cross-section or coil self-capacitance Spread C14 killed. Retract §4.4 of the paper. The exclusion-radius result was an artefact of the dipole approximation surviving into the exact solve
ordered by monotonically Cancellation never held; look for a missed -dependence in
Cost/time. Field probe hire ~£2k/week; coils ~£1.5k. 2 weeks. Falsifies: C14, C51, and the entire §4.4.
E3 — Range law and the knob
Tests: C11 (), C18/C19 (cryo break-even).
Apparatus. E1 coils with a switched series-resistance bank to set at 6.78 MHz — the cleanest way to vary while holding all geometry fixed, which is exactly what the theory requires.
Method. At each , find at which end-to-end efficiency = 80%. Fit vs .
Decision rule. Slope → C11 confirmed [T/E]. Outside → the CMT efficiency relation (4.2) is failing; check for radiative loss contaminating , which is the most likely culprit above 10 MHz.
Cryo extension (E3b). Same geometry, HTS coil in LN₂ vs copper at 300 K. Measure wall-plug power including the compressor, not resonator loss. Decision rule: net advantage requires . If the measured advantage exceeds prediction, suspect a bug before claiming a result — the most likely cause is unaccounted eddy-current loss in the 300 K reference, not superconducting merit.
Cost/time. 1 week (E3); 6 weeks + cryostat (E3b).
E4 — MIM area-independence (sharpest test of a corrected claim)
Tests: C49 (new) — independent of junction area.
This tests the claim that replaced the paper's error, and it is a clean, cheap, decisive measurement.
Apparatus. One ALD Al₂O₃ barrier deposition (single run, so and are identical by construction) patterned into junctions of side 20, 50, 100, 200, 500 nm — a 625× range in area. Asymmetric electrodes (e.g. Au/Al₂O₃/Ti).
Method. DC – → at zero bias. Small-signal – at 1 MHz → . Form the product .
Prediction. constant to within measurement error across 625× in area, while and each vary by 625× in opposite directions.
Pre-committed decision rule.
Outcome Action
constant within 20% C49 confirmed [T/E]. C26 formally retired; §5.1 of the paper rewritten
varies systematically with area A real area-dependent term exists — almost certainly edge/fringing capacitance or perimeter leakage. Quantify it; it restores a geometric limit, and C26 may be partially rehabilitated in modified form Small junctions show anomalously low Pinhole/defect conduction dominating. Yield problem, not physics — reports on P3's real mechanism
Cost/time. One e-beam lithography run + ALD, ~£8k at a shared facility. 6–8 weeks. Falsifies: C49, C26′, and informs P3.
E5 — The cutoff / responsivity anti-correlation
Tests: C26′ — the emergent anti-correlation, and the strengthened basis of prediction P3.
Apparatus. Barrier ladder from E4's process: nm × two electrode pairs (high and low work-function contrast). Antenna-coupled at 10.6 μm (CO₂ laser) and at 1.5 THz for a second point on the frequency axis.
Method. For each barrier, measure (DC), (lock-in, second-harmonic), and optical response at both frequencies. Plot against .
Prediction. falls monotonically as rises, crossing zero near THz. The zero crossing is the sharp, falsifiable feature.
Decision rule.
Outcome Action Monotone anti-correlation with sign change C26′ confirmed. P3 confidence raised from 0.85 to ~0.95 Anti-correlation without sign change in range C26′ partially confirmed; the bound is softer than simulated Any barrier with THz and V⁻¹ C26′ killed and P3 refuted. This is the single most valuable possible outcome in the whole loop — it would reopen optical rectennas
Cost/time. Shares E4's fabrication. 3 months with laser access.
E6 — Wall-family separation
Tests: C43′ / C50 / C51 — the emergent two-family structure.
Apparatus. E1 rail, instrumented for four simultaneous channels: delivered power, primary VA (voltage×current with phase), loaded , and field at a fixed reference radius.
Method. Sweep from 2 to 200 in one continuous run, logging all four. Identify the at which each budget crosses a pre-declared threshold.
Prediction. Efficiency, reactive power, and required breach within a factor of 2 of each other; field/exclusion breaches 20× later.
Decision rule.
Outcome Action Family A span , gap to exclusion C43′, C50, C51 confirmed [T/E]. The layered-architecture claim rests on measured structure All four cluster Exposure is co-binding. C51 killed; the paper's original §4.4 framing is vindicated over the simulation's Family A does not cluster The three budgets are not a single failure mode. C50 killed; §7's architecture weakens to a coincidence of scales
Cost/time. Extends E1/E3 by ~1 week. Near-zero marginal cost. Best value-per-pound in the loop.
E7 — Thermal binding check (tests an untested unknown)
Tests: the open item from §7 of the results — no thermal model exists.
Method. During E3, log conductor temperature by IR camera and by winding-resistance thermometry. Determine the at which thermal limits bind.
Decision rule. If thermal binds before the Family A budgets, a fifth wall exists that neither the paper nor the simulation modelled, and the architecture in §7 needs a new row. Given – A-turns at metre scale, I consider this genuinely likely — which is why it is in the loop rather than in future work.
Sequencing and value Order Experiment Cost Time Kills if it fails 1 E1 coupling floor £0.4k 3 d everything downstream 2 E6 wall families ~£0 1 wk C43′, C50, C51 3 E3 range law £1k 1 wk C11 4 E7 thermal ~£0 (with E3) adds a wall 5 E2 aperture invariance £3.5k 2 wk C14, §4.4 6 E4 MIM area £8k 8 wk C49, C26′ 7 E5 anti-correlation shared 3 mo P3 8 E3b cryo £30k+ 6 wk C18/C19
E1, E6, E3, and E7 together cost under £1.5k and about three weeks, and between them can kill four claims including two of the three emergent ones. That is where the loop should start. E2 is the highest-value single result, but it should not run before E1 has validated the domain it depends on.
Loop-closure conditions
The loop is closed when every claim in the revised ledger is in one of three terminal states:
Promoted — simulated and measured, tagged [T/E] Retired — falsified, with the falsifying observation recorded (C26 is already here) Deferred — explicitly out of experimental reach, tagged [O] with the reason
The loop is open and running as long as any claim is tagged [C] without a scheduled experiment. On the current ledger that set is: C51 (scheduled → E6), C28 (scheduled → E5), C33, C34, C42, C44, C45 (unscheduled).
C45 (non-excludability of fields) has no experiment in this loop and is not a physics claim. It needs an entirely different instrument — a protocol design and an adversarial security analysis, not a bench. Flagging it as the largest unaddressed item, unchanged from the paper.
Simulation
Results
0. Headline Four of the seven tests failed. Every failure was informative, and three forced revisions to the paper. One test (A7) failed in a way that identifies an outright reasoning error in §5.1 of the paper — not a numerical discrepancy but a wrong mechanism. Test Claim Result Consequence A1 C11 range PASS (0.3417) confirmed A2 C10 FAIL → diagnosed validity floor raised to A3 C14 independent of FAIL → diagnosed C14 downgraded to bounded theorem A4 C14 exponents PASS (0.16694 / 0.50018) confirmed to 4 s.f. A5 C18 cryo break-even PASS (exact) confirmed A6 C20 crossover m FAIL C20 corrected to 0.267 m A7 C26 junction nm FAIL C26 mechanism is wrong A8 coupling of the four walls FAIL → diagnosed C43 revised: two wall families 1. Three numerical bugs found and fixed Recorded because two of them produced plausible-looking wrong answers rather than crashes. Catastrophic cancellation in . The closed form differs at between two terms. Below this returns noise. Replaced with the exact series limit , verified to reproduce the dipole result to 6 significant figures. Catastrophic cancellation in near the axis, producing spurious field spikes that corrupted the shell maximum and gave values up to 27× too large. This one is dangerous: it produced smooth, monotone, entirely wrong curves. Fixed by regrouping and then by excluding the singular region and adding the analytic on-axis point. Root-finding in linear space across a 6-decade bracket against an 18-decade function, giving non-monotonic — caught only by the pre-registered bug indicator " decreasing with ." Moved to log-log space. Validation after fixes: on-axis field exact to relative; shell maximum converges to the dipole limit as at ; matches the closed form to 0.1% in the far regime. The bug-indicator list earned its place. Bug 3 was invisible in every summary statistic and was caught only by a pre-committed monotonicity assertion. 2. A3 — the headline claim survives, but bounded C14 asserted that the exclusion radius is independent of coil radius. Across the full sweep m at kW, m, the exact field solve gives a spread of 1.372, against a pre-registered tolerance of 1.05. FAIL. Diagnosis by validity floor: restriction spread max deviation from Eq. 4.6 1.077 6.64% 1.067 6.28% 1.0127 1.25% 1.0035 0.35% The cancellation is real and near-exact — inside its domain. The mechanism of failure is not the one predicted in the pre-registration (I expected breakdown when , which never occurred). The actual mechanism is that the -cancellation depends on exactly; once the coils are close enough that exact saturates below the dipole value (ratio 0.577 at ), the cancellation breaks and rises. Revision: C14 goes from [T] to **[T, bounded: ]**. Within that bound it is confirmed to 1.3%, and A4 confirms the exponents to four significant figures ( vs ; vs ). The claim is stronger than the paper stated inside its domain and invalid outside it. 3. A6 — C20 is numerically wrong The paper computed the near/far crossover using the approximate . With exact Maxwell mutual inductance: crossover 0.267 m (paper said 0.40 m) 1.73 m 40.3 m Fitted slope vs : 0.723, not the predicted 2/3 — again because exact saturates at the small where these crossovers sit. Revision: C20 corrected from 0.40 m to 0.267 m. Note the direction: the qualitative claim in §4.6 strengthens. The crossover is even closer in than the paper claimed, so the margin by which all deployed WPT sits below it is larger. The retrodiction survives with a wider margin, on a corrected number. 4. A7 — the paper's reasoning is wrong, not just its number The paper argued: shrink the junction → lower → higher → therefore IR rectification requires sub-30 nm junctions. This is invalid. For a tunnel junction, and , so — independent of area. Confirmed numerically across a 900× range of junction area: side 10 nm 37.7 kΩ 7.97 aF 0.530 THz 30 nm 4.19 kΩ 71.7 aF 0.530 THz 100 nm 377 Ω 797 aF 0.530 THz 300 nm 41.9 Ω 7172 aF 0.530 THz is flat to four significant figures. You cannot buy bandwidth by shrinking the junction. Area sets the impedance match and nothing else; the cutoff is set entirely by the barrier through . Feasibility, correctly derived. Scanning 90 barrier configurations: zero satisfy ( THz) ∧ (). Maximum achievable without image-force lowering is 3.67 THz — LWIR is unreachable. A declared sensitivity study over image-force lowering and effective mass : image force best at that point 0.2 no 3.67 THz +0.072 0.3 no 3.06 THz +0.101 0.4 no 2.56 THz +0.130 0.2 yes 20.6 THz −0.059 0.3 yes 26.3 THz −0.081 0.4 yes 31.3 THz −0.099 The emergent result: image-force lowering is what makes LWIR rectification reachable at all, and at exactly the corner where clears 28.3 THz, the responsivity inverts sign. The two constraints are anti-correlated — every barrier modification that raises the cutoff flattens and then reverses the nonlinearity. (Sign inversion of responsivity is independently documented in the optical-rectenna literature, which is a useful external consistency check.) Revision: C26 replaced. The correct statement is not "junctions must be under 30 nm" but: C26′ [T] The MIM cutoff frequency is independent of junction area. LWIR rectification is bounded by a cutoff–responsivity anti-correlation in the barrier parameters, not by a geometric area limit. Junction area is set solely by impedance matching, . Prediction P3 survives and is strengthened — its stated mechanism changes from interconnect statistics to barrier-level anti-correlation, and the anti-correlation is a tighter bound. Declared model limitation: absolute is uncertain by roughly one decade (image-force treatment, , no trap-assisted or defect conduction). The area-independence result is an algebraic identity and carries none of that uncertainty. 5. A8 — the emergent result: there are two wall families, not one The single-knob test swept and monitored four budgets. All four breach, but spread over 51.9× in , against a pre-registered tolerance of 10×. FAIL. The structure of the failure is the most useful output of the whole exercise: budget breaches at family reactive power 2.58 A required 4.71 A efficiency 5.13 A exclusion radius 134.0 B Family A spans only 1.99× — three budgets breaking essentially simultaneously on one knob. Then a 26× gap. Then exclusion. Robustness. Tested across 108 threshold combinations spanning 3+ decades in each threshold: exclusion is the last wall to breach in 108 / 108 cases the other three cluster within 10× in 100% of cases (median span 2.83×) median gap to exclusion: 17.5× This is not an artefact of threshold choice. Interpretation. The exclusion wall scales as — extraordinarily weak in — while the coupling walls scale as . The coupling walls therefore always bind first, by more than an order of magnitude. Revision to C43: C43′ [T/C] The near-field walls form two structurally independent families. Family A (efficiency, circulating reactive power, required ) derives from the coupling coefficient and is tightly coupled — one geometric knob breaks all three within a factor of 2. Family B (regulatory exclusion radius) derives from an absolute field limit and is decoupled by 20×. Exposure is never the binding constraint on near-field WPT; circulating reactive power is. This partially reverses the paper, which presented the reactive-power and exposure walls as co-equal. They are not. §4.4's 3.2 km exclusion zone for a 1 GW / 100 km link is real, but that system is already dead by a factor of 560 on reactive power long before anyone measures a field. The exclusion-radius theorem retains its interest as a design rule for systems that have solved the reactive-power problem — a set which is currently empty. 6. Revised Claims Ledger (deltas only) # Status Change C10 [T, bounded] validity floor raised from to C11 [T] confirmed slope 0.3417 C14 [T] → [T, bounded] holds to 1.3% for ; fails (37%) at C18, C19 [T] confirmed break-even exact C20 [T] corrected 0.40 m → 0.267 m C22 [C] strengthened retrodiction margin widens on the corrected number C26 [T] → withdrawn replaced by C26′: cutoff is area-independent C28 [C] mechanism revised interconnect statistics → cutoff/responsivity anti-correlation C43 [T/C] → C43′ two independent wall families C49 [T] new independent of junction area (algebraic identity, confirmed to 4 s.f.) C50 [T] new Family A budgets breach within 2× on a single knob; robust over 108 threshold sets C51 [C] new Exposure is never binding for near-field WPT; reactive power dominates by 20× 7. What the simulation did not settle Absolute MIM remains uncertain by ~1 decade. [O] for superconducting coils at 10⁴–10⁷ Hz was assumed, not modelled — AC loss in filaments is the real unknown and is where C18 will actually be decided. [O] The prefactor in is still unpinned; only the scaling was tested. [O] No thermal model. Circulating currents of – A-turns imply conductor heating that may bind before any wall studied here. [O]
Codepython
"""
Wireless grid simulation instrument.
Built on exact Maxwell quantities to avoid confirming the paper's own approximations.
"""
import numpy as np
from scipy.special import ellipk, ellipe
from scipy.optimize import brentq
import json
MU0 = 4 * np.pi * 1e-7
EPS0 = 8.8541878128e-12
C0 = 299792458.0
# ---------------------------------------------------------------- exact EM ---
def L_loop(a, r_w):
"""Self-inductance of a single circular loop. G is DERIVED, not assumed."""
return MU0 * a * (np.log(8 * a / r_w) - 2.0)
def G_factor(a, r_w):
return np.log(8 * a / r_w) - 2.0
def M_coaxial(a1, a2, d):
"""Exact Maxwell mutual inductance of two coaxial circular loops.
No multipole truncation.
NOTE: the closed form (2/k - k)K(k) - (2/k)E(k) suffers catastrophic
cancellation as k -> 0 (two O(1/k) terms differing at O(k^3)). Below
k^2 = 1e-6 we use the exact leading term of the series, M -> mu0 sqrt(a1 a2)
pi k^3 / 16, which reproduces the dipole result mu0 pi a^4 / (2 d^3).
This is a numerical-stability fix, not an approximation change."""
k2 = 4 * a1 * a2 / ((a1 + a2) ** 2 + d ** 2)
k = np.sqrt(k2)
if k2 < 1e-6:
return MU0 * np.sqrt(a1 * a2) * np.pi * k ** 3 / 16.0
return MU0 * np.sqrt(a1 * a2) * ((2.0 / k - k) * ellipk(k2) - (2.0 / k) * ellipe(k2))
def coupling_k(a1, a2, d, r_w1, r_w2):
return M_coaxial(a1, a2, d) / np.sqrt(L_loop(a1, r_w1) * L_loop(a2, r_w2))
def B_loop(a, amp_turns, rho, z):
"""Exact off-axis B field of a circular loop (elliptic integrals).
Returns |B|. rho,z may be arrays."""
rho = np.atleast_1d(np.asarray(rho, dtype=float))
z = np.atleast_1d(np.asarray(z, dtype=float))
rho = np.maximum(rho, 1e-12)
alpha2 = a ** 2 + rho ** 2 + z ** 2 - 2 * a * rho
beta2 = a ** 2 + rho ** 2 + z ** 2 + 2 * a * rho
beta = np.sqrt(beta2)
m = 1.0 - alpha2 / beta2 # = k^2
m = np.clip(m, 0.0, 1.0 - 1e-15)
Kk, Ek = ellipk(m), ellipe(m)
C = MU0 * amp_turns / np.pi
S = a ** 2 + rho ** 2 + z ** 2
# B_rho bracket is S*E - alpha2*K, which vanishes as O(rho^2) near the axis
# while both terms are O(S). Evaluated directly this cancels catastrophically
# and, divided by rho, produced spurious near-axis spikes that corrupted the
# shell maximum (bug found in v2). Regroup as S*(E-K) + 2*a*rho*K and use the
# series for D = E-K at small m, where the cancellation actually lives.
D = np.where(m < 1e-6, -(np.pi / 2) * (m / 2 + 3 * m ** 2 / 16), Ek - Kk)
Brho = (C * z) / (2 * alpha2 * beta * rho) * (S * D + 2 * a * rho * Kk)
Bz = (C) / (2 * alpha2 * beta) * ((a**2 - rho**2 - z**2) * Ek + alpha2 * Kk)
return np.sqrt(Brho ** 2 + Bz ** 2)
def B_on_axis(a, amp_turns, z):
"""Exact on-axis field. B_rho vanishes identically by symmetry."""
return MU0 * amp_turns * a ** 2 / (2 * (a ** 2 + z ** 2) ** 1.5)
def max_B_on_shell(a, amp_turns, R, n=2001):
"""Max |B| over a sphere of radius R centred on the loop.
The off-axis expression for B_rho is a 0/0 form on the axis and cancels
catastrophically nearby, which produced spurious maxima (bug found in v3).
We therefore sample only where rho >= 1e-3 R -- outside which the field
differs from the axial value by O(rho^2/R^2) ~ 1e-6 -- and add the exact
analytic on-axis point separately."""
th_min = np.arcsin(min(1e-3, 0.5))
th = np.linspace(th_min, np.pi / 2, n)
off = np.max(B_loop(a, amp_turns, R * np.sin(th), R * np.cos(th)))
return float(max(off, B_on_axis(a, amp_turns, R)))
# ------------------------------------------------------------ link physics ---
def eta_max(U):
return U ** 2 / (1 + np.sqrt(1 + U ** 2)) ** 2
def U_from(k, Q1, Q2):
return k * np.sqrt(Q1 * Q2)
def amp_turns_for(P, a, d, f, r_w_frac=1e-3, a2=None, r_w2_frac=None):
"""Amp-turns required in the primary to deliver P across d.
P_circ = P/k ; P_circ = 0.5*omega*L*I^2 with L = mu0 N^2 a G -> (NI)^2 = 2 P_circ/(w mu0 a G)
Uses EXACT k."""
a2 = a if a2 is None else a2
r_w2_frac = r_w_frac if r_w2_frac is None else r_w2_frac
k = coupling_k(a, a2, d, r_w_frac * a, r_w2_frac * a2)
k = min(k, 0.999)
P_circ = P / k
w = 2 * np.pi * f
G = G_factor(a, r_w_frac * a)
return np.sqrt(2 * P_circ / (w * MU0 * a * G)), k, P_circ, G
def R_compliance(P, a, d, f, B_lim, r_w_frac=1e-3, exact=True):
"""Exclusion radius by FULL field solve (no dipole approximation).
Returns (R_c, flag) where flag notes whether R_c < a (dipole-invalid regime)."""
NI, k, P_circ, G = amp_turns_for(P, a, d, f, r_w_frac)
if exact:
# Solve in log-log space: g(u) = log|B|(e^u) - log B_lim is near-linear
# with slope -3, so the root find is well conditioned. Solving in linear
# space over a 6-decade bracket against an 18-decade range caused
# spurious non-monotonic roots (bug found in v1).
lo, hi = 1.001 * a, max(1e6, 1e3 * a)
g = lambda u: np.log(max_B_on_shell(a, NI, np.exp(u))) - np.log(B_lim)
while g(np.log(hi)) > 0 and hi < 1e14:
hi *= 10.0
if g(np.log(lo)) < 0:
# already compliant at the coil surface: the compliance boundary lies
# inside the coil footprint, where no dipole field exists.
return float(a), "INSIDE_COIL", NI, k, P_circ, G
if g(np.log(hi)) > 0:
return float(hi), "UNBOUNDED", NI, k, P_circ, G
Rc = np.exp(brentq(g, np.log(lo), np.log(hi), xtol=1e-10, rtol=1e-13, maxiter=200))
return float(Rc), "OK", NI, k, P_circ, G
else:
m = np.pi * a ** 2 * NI
Rc = (MU0 * m / (2 * np.pi * B_lim)) ** (1 / 3)
return float(Rc), "DIPOLE", NI, k, P_circ, G
def Rc_closed_form(P, d, f, B_lim):
"""Paper Eq. 4.6 — for comparison only."""
w = 2 * np.pi * f
return (MU0 / (2 * B_lim)) ** (1 / 3) * (4 * P / (np.pi * w * MU0)) ** (1 / 6) * np.sqrt(d)
def d_max_for_U(Q, a, U_target=19.0, r_w_frac=1e-3):
"""Solve exact U(d) = U_target for range."""
def g(d):
return U_from(coupling_k(a, a, d, r_w_frac * a, r_w_frac * a), Q, Q) - U_target
lo, hi = 1.001 * a, 1e7 * a
if g(lo) < 0:
return np.nan
return brentq(g, lo, hi, xtol=1e-9, rtol=1e-12)
"""Acceptance-test suite. Physics lives in wpt_core."""
import numpy as np, json
from wpt_core import *
import wpt_core as core
MU0 = core.MU0
# ------------------------------------------------------------------ tests ----
def slope(x, y):
return float(np.polyfit(np.log(x), np.log(y), 1)[0])
R = {} # results
FIG = {} # figure data
# --- A1: range law -----------------------------------------------------------
Qs = np.logspace(3, 9, 25)
dmax = np.array([d_max_for_U(q, 0.3) for q in Qs])
s_A1 = slope(Qs, dmax)
R["A1"] = dict(name="range ~ Q^(1/3)", slope=s_A1, target=[0.32, 0.35],
passed=bool(0.32 <= s_A1 <= 0.35),
dmax_Q1e3=float(dmax[0]), dmax_Q1e9=float(dmax[-1]))
FIG["A1"] = dict(Q=Qs.tolist(), dmax=dmax.tolist())
# --- A2: coupling scaling ----------------------------------------------------
a0, rwf = 0.3, 1e-3
ratios = np.logspace(np.log10(3), 2, 40)
ks = np.array([coupling_k(a0, a0, r * a0, rwf * a0, rwf * a0) for r in ratios])
s_A2 = slope(ratios, ks)
G0 = G_factor(a0, rwf * a0)
pref_pred = np.pi / (2 * G0)
pref_meas = float(np.median(ks * ratios ** 3))
R["A2"] = dict(name="k ~ 0.224 (a/d)^3", slope=s_A2, target=[-3.05, -2.95],
G_derived=float(G0), prefactor_predicted=float(pref_pred),
prefactor_measured=pref_meas,
prefactor_err_pct=float(100 * abs(pref_meas - pref_pred) / pref_pred),
passed=bool(-3.05 <= s_A2 <= -2.95 and
abs(pref_meas - pref_pred) / pref_pred < 0.10))
FIG["A2"] = dict(ratio=ratios.tolist(), k=ks.tolist())
# --- A3: aperture cancellation (THE novel claim) ----------------------------
P3, d3, f3, Blim3 = 1e5, 20.0, 85e3, 27e-6
a_sweep = np.logspace(-1, 1, 30)
Rc_ex, flags = [], []
for a in a_sweep:
rc, fl, *_ = R_compliance(P3, a, d3, f3, Blim3)
Rc_ex.append(rc); flags.append(fl)
Rc_ex = np.array(Rc_ex)
Rc_cf = Rc_closed_form(P3, d3, f3, Blim3)
ok = np.array([fl == "OK" for fl in flags])
spread_all = float(Rc_ex.max() / Rc_ex.min())
spread_ok = float(Rc_ex[ok].max() / Rc_ex[ok].min()) if ok.any() else np.nan
R["A3"] = dict(name="R_c independent of a", spread_full_sweep=spread_all,
spread_valid_regime=spread_ok, target_max=1.05,
closed_form_Rc=float(Rc_cf),
n_inside_coil=int((~ok).sum()), n_total=len(a_sweep),
a_breakdown_onset=float(a_sweep[~ok][0]) if (~ok).any() else None,
passed=bool(spread_all < 1.05),
passed_restricted=bool(spread_ok < 1.05) if ok.any() else False)
FIG["A3"] = dict(a=a_sweep.tolist(), Rc=Rc_ex.tolist(), flags=flags,
Rc_closed=float(Rc_cf))
# --- A4: R_c exponents (within valid regime) --------------------------------
Ps = np.logspace(4, 8, 12)
Rc_P = np.array([R_compliance(p, 0.5, 20.0, f3, Blim3)[0] for p in Ps])
ds = np.logspace(1, 4, 12)
Rc_d = np.array([R_compliance(1e5, 0.5, dd, f3, Blim3)[0] for dd in ds])
sP, sD = slope(Ps, Rc_P), slope(ds, Rc_d)
R["A4"] = dict(name="R_c ~ P^(1/6) d^(1/2)", slope_P=sP, slope_d=sD,
target_P=[0.160, 0.174], target_d=[0.48, 0.52],
passed=bool(0.160 <= sP <= 0.174 and 0.48 <= sD <= 0.52))
FIG["A4"] = dict(P=Ps.tolist(), Rc_P=Rc_P.tolist(), d=ds.tolist(), Rc_d=Rc_d.tolist())
# --- A5: cryogenic break-even ------------------------------------------------
def wall_power(Q, P, a, d, f, COP=None, rwf=1e-3):
_, k, P_circ, _ = amp_turns_for(P, a, d, f, rwf)
loss = P_circ / Q
return loss if COP is None else loss / COP
COP = 0.010
Q_cu = 1e3
ratio = brentq(lambda r: wall_power(Q_cu * r, 1e5, 5.0, 20.0, 85e3, COP)
- wall_power(Q_cu, 1e5, 5.0, 20.0, 85e3, None), 1.0, 1e6)
R["A5"] = dict(name="cryo break-even at 1/COP", COP=COP, predicted=1 / COP,
measured=float(ratio),
err_pct=float(100 * abs(ratio - 1 / COP) * COP),
range_gain_at_breakeven=float(ratio ** (1 / 3)),
passed=bool(abs(ratio - 1 / COP) / (1 / COP) < 0.05))
# --- A6: near/far crossover --------------------------------------------------
def a_nf(d, Q, U=19.0, a_guess=None):
"""Coil radius needed for U_target at distance d, using EXACT k."""
def g(a):
return U_from(coupling_k(a, a, d, 1e-3 * a, 1e-3 * a), Q, Q) - U
lo, hi = 1e-4 * d, 0.999 * d
if g(hi) < 0:
return np.nan
return brentq(g, lo, hi, xtol=1e-12, rtol=1e-12)
def a_ff(d, lam=0.1224, tau=2.0):
return np.sqrt(tau * lam * d / np.pi)
def crossover(Q):
def g(d):
anf = a_nf(d, Q)
return (np.inf if np.isnan(anf) else anf) - a_ff(d)
try:
return brentq(g, 1e-3, 1e4, xtol=1e-9, rtol=1e-12)
except Exception:
return np.nan
Qc = np.array([1e3, 1e4, 1e5, 1e6])
dx = np.array([crossover(q) for q in Qc])
s_A6 = slope(Qc, dx)
R["A6"] = dict(name="near/far crossover", d_cross_Q1e3=float(dx[0]),
target=[0.35, 0.45], slope_vs_Q=s_A6, target_slope=[0.65, 0.68],
all_crossovers=dx.tolist(),
passed=bool(0.35 <= dx[0] <= 0.45 and 0.65 <= s_A6 <= 0.68))
FIG["A6"] = dict(Q=Qc.tolist(), d_cross=dx.tolist())
# --- A8: failure-propagation (single knob = d/a) ----------------------------
P8, a8, f8, Q8 = 1e5, 1.0, 85e3, 1e4
rr = np.logspace(0.3, 2.5, 60)
budgets = dict(efficiency=[], reactive=[], exclusion=[], reqQ=[])
for r in rr:
d = r * a8
k = coupling_k(a8, a8, d, 1e-3 * a8, 1e-3 * a8)
U = U_from(k, Q8, Q8)
budgets["efficiency"].append(eta_max(U))
budgets["reactive"].append(P8 / k)
rc, _, *_ = R_compliance(P8, a8, d, f8, 27e-6)
budgets["exclusion"].append(rc)
budgets["reqQ"].append(19.0 / k)
TH = dict(efficiency=0.90, reactive=1e7, exclusion=25.0, reqQ=1e4) # thresholds
breach = {}
for kk, v in budgets.items():
v = np.array(v)
if kk == "efficiency":
idx = np.where(v < TH[kk])[0]
else:
idx = np.where(v > TH[kk])[0]
breach[kk] = float(rr[idx[0]]) if len(idx) else None
vals = [x for x in breach.values() if x is not None]
span = float(max(vals) / min(vals)) if len(vals) > 1 else np.inf
R["A8"] = dict(name="failure propagation on single knob d/a",
breach_points=breach, n_breached=len(vals),
decade_span=span,
passed=bool(len(vals) >= 3 and span <= 10.0))
FIG["A8"] = dict(ratio=rr.tolist(),
**{k: np.array(v).tolist() for k, v in budgets.items()},
thresholds=TH)
# --- bug indicators ----------------------------------------------------------
bugs = []
if (ks >= 1).any(): bugs.append("k >= 1")
if np.any(np.diff(Rc_P) < 0): bugs.append("R_c decreasing with P")
for a in [0.3, 1.0, 5.0]:
for d in [2.0, 10.0, 50.0]:
if M_coaxial(a, a, d) > np.sqrt(L_loop(a, 1e-3*a)**2):
bugs.append(f"M > sqrt(L1 L2) at a={a} d={d}")
R["bug_indicators"] = bugs
# ------------------------------------------------- DIAGNOSTICS (not tests) --
# These do NOT alter any pre-registered PASS/FAIL. They locate validity
# boundaries once a test has already been recorded as failed.
D = {}
# D2: where does k ~ (a/d)^3 actually become valid?
floors = [3, 5, 10, 20]
D["D2_k_scaling_by_floor"] = {}
for fl in floors:
sel = ratios >= fl
D["D2_k_scaling_by_floor"][f"d/a>={fl}"] = dict(
slope=slope(ratios[sel], ks[sel]),
pref_err_pct=float(100 * abs(np.median(ks[sel] * ratios[sel] ** 3) - pref_pred) / pref_pred))
# D3: aperture cancellation restricted to the far regime
D["D3_Rc_spread_by_floor"] = {}
for fl in floors:
sel = (d3 / a_sweep) >= fl
if sel.sum() > 1:
D["D3_Rc_spread_by_floor"][f"d/a>={fl}"] = dict(
spread=float(Rc_ex[sel].max() / Rc_ex[sel].min()),
n=int(sel.sum()),
max_dev_from_closed_pct=float(100 * np.max(np.abs(Rc_ex[sel] - Rc_cf) / Rc_cf)))
# D4: R_c exponents restricted to the far regime (a small enough that d/a>>1)
Rc_P2 = np.array([R_compliance(p, 0.1, 20.0, f3, Blim3)[0] for p in Ps])
ds2 = np.logspace(1.5, 4, 12)
Rc_d2 = np.array([R_compliance(1e5, 0.1, dd, f3, Blim3)[0] for dd in ds2])
D["D4_far_regime_exponents"] = dict(slope_P=slope(Ps, Rc_P2), slope_d=slope(ds2, Rc_d2))
# D8: are the four budgets clustered or split into families?
bp = {k: v for k, v in breach.items() if v is not None}
if len(bp) >= 2:
vv = sorted(bp.values())
gaps = [vv[i + 1] / vv[i] for i in range(len(vv) - 1)]
cut = int(np.argmax(gaps))
D["D8_clustering"] = dict(
sorted_breach=vv, gap_ratios=gaps,
largest_gap=float(max(gaps)),
family_A=[k for k, v in bp.items() if v <= vv[cut]],
family_B=[k for k, v in bp.items() if v > vv[cut]],
family_A_span=float(vv[cut] / vv[0]) if cut >= 0 else 1.0)
R["diagnostics"] = D
with open("results_wpt.json", "w") as fp:
json.dump({"tests": R, "figures": FIG}, fp)
# ---------------------------------------------------------------- report -----
print("=" * 74)
print("ACCEPTANCE TESTS (pre-registered)")
print("=" * 74)
for kk in ["A1", "A2", "A3", "A4", "A5", "A6", "A8"]:
t = R[kk]
mark = "PASS" if t.get("passed") else "FAIL"
print(f"\n[{mark}] {kk}: {t['name']}")
for f, v in t.items():
if f in ("name", "passed"): continue
print(f" {f}: {v}")
import pprint
print("\n"+"="*74); print("DIAGNOSTICS (post-hoc, do not affect PASS/FAIL)"); print("="*74)
pprint.pprint(R["diagnostics"], width=110)
print("\nBUG INDICATORS:", bugs if bugs else "none")
n_pass = sum(1 for kk in ["A1","A2","A3","A4","A5","A6","A8"] if R[kk].get("passed"))
print(f"\nSIMULTANEOUS PASS: {n_pass}/7 -> {'ACCEPT' if n_pass==7 else 'REJECT (see failures)'}")
"""
MIM tunnel-junction rectifier module — acceptance test A7.
Transport: Tsu-Esaki with numerically integrated WKB transmission through a
trapezoidal barrier. Responsivity and dynamic resistance are DERIVED by
numerical differentiation of I(V), not assumed. Image-force barrier lowering is
omitted (noted as a known optimism in the ledger).
"""
import numpy as np, json
from scipy.constants import e as QE, hbar, m_e, k as kB, epsilon_0, h as PLANCK
T_K = 300.0
kT = kB * T_K / QE # eV
def wkb_T(E, phi1, phi2, s, V, m_eff=0.4, n=200, EF=5.0):
"""WKB transmission at longitudinal energy E (eV, measured from the band
bottom) through a trapezoidal barrier.
NOTE: barrier heights phi are quoted relative to the Fermi level, so the
barrier in ABSOLUTE energy is EF + phi. Comparing E against phi directly
put most of the energy grid above the barrier and pinned asymmetry at
exactly 1.000 (bug found in v1 of this module)."""
x = np.linspace(0.0, s, n)
Vb = EF + phi1 + (phi2 - V - phi1) * (x / s) # eV, absolute
dV = Vb[None, :] - E[:, None] # eV
forb = np.clip(dV, 0.0, None)
integ = np.trapezoid(np.sqrt(2 * m_eff * m_e * QE * forb), x, axis=1)
return np.exp(-2.0 * integ / hbar)
def supply(E, V, EF=5.0):
"""Tsu-Esaki supply function (eV) at 300 K."""
a1 = np.clip((EF - E) / kT, -60, 60)
a2 = np.clip((EF - E - V) / kT, -60, 60)
return kT * np.log((1 + np.exp(a1)) / (1 + np.exp(a2)))
def current_density(V, phi1, phi2, s, m_eff=0.4, EF=5.0, nE=400):
"""A/m^2 at bias V (volts)."""
E = np.linspace(0.0, EF + max(phi1, phi2) + 2.0, nE)
Tr = wkb_T(E, phi1, phi2, s, V, m_eff, EF=EF)
integrand = Tr * supply(E, V, EF)
return (4 * np.pi * m_eff * m_e * QE / PLANCK ** 3) * np.trapezoid(integrand, E) * QE ** 2
def junction_metrics(phi1, phi2, s, m_eff=0.4, dV=0.02):
"""Returns specific resistance (Ohm.m^2), responsivity (1/V), asymmetry."""
Vs = np.array([-2 * dV, -dV, 0.0, dV, 2 * dV])
J = np.array([current_density(v, phi1, phi2, s, m_eff) for v in Vs])
Ip = (J[3] - J[1]) / (2 * dV) # dJ/dV
Ipp = (J[3] - 2 * J[2] + J[1]) / dV ** 2 # d2J/dV2
if Ip <= 0:
return np.nan, np.nan, np.nan
rho_spec = 1.0 / Ip # Ohm.m^2
beta = Ipp / (2 * Ip) # 1/V
Ja = current_density(0.3, phi1, phi2, s, m_eff)
Jb = current_density(-0.3, phi1, phi2, s, m_eff)
asym = abs(Ja / Jb) if Jb != 0 else np.nan
return rho_spec, beta, asym
# ------------------------------------------------------------------ scan -----
F_TARGET = 28.3e12 # 10.6 um LWIR
EPS_R = 9.0 # Al2O3
R_LO, R_HI = 50.0, 200.0 # antenna match window
BETA_MIN = 1.0 # 1/V
rows = []
for t_nm in [1.0, 1.5, 2.0, 2.5, 3.0, 4.0]:
for phi1 in [0.5, 1.0, 1.5, 2.0, 3.0, 4.0]:
for dphi in [0.2, 0.5, 1.0]:
phi2 = phi1 - dphi
if phi2 <= 0.05:
continue
s = t_nm * 1e-9
rho, beta, asym = junction_metrics(phi1, phi2, s)
if not np.isfinite(rho) or rho <= 0:
continue
# KEY STRUCTURAL FACT: R_d = rho/A and C = eps*A/t, so
# RC = rho*eps_0*eps_r/t is INDEPENDENT OF AREA.
RC = rho * epsilon_0 * EPS_R / s
f_c = 1.0 / (2 * np.pi * RC)
# area required to land in the antenna match window
A_lo, A_hi = rho / R_HI, rho / R_LO
side_lo, side_hi = np.sqrt(A_lo) * 1e9, np.sqrt(A_hi) * 1e9 # nm
rows.append(dict(t_nm=t_nm, phi1=phi1, phi2=round(phi2, 2),
rho_spec=rho, beta=beta, asym=asym,
RC_s=RC, f_c_THz=f_c / 1e12,
side_lo_nm=side_lo, side_hi_nm=side_hi,
feasible=bool(f_c > F_TARGET and beta > BETA_MIN)))
feas = [r for r in rows if r["feasible"]]
sides = [r["side_hi_nm"] for r in feas]
# --- A7 verdict --------------------------------------------------------------
A7 = dict(
name="IR rectification requires junction side < 30 nm",
n_configs=len(rows), n_feasible=len(feas),
max_feasible_side_nm=float(max(sides)) if sides else None,
min_feasible_side_nm=float(min(sides)) if sides else None,
all_under_30nm=bool(sides and max(sides) < 30.0),
passed=bool(sides and max(sides) < 30.0),
)
# --- the structural finding: is RC really area-independent? ------------------
r0 = rows[0]
check = []
for side_nm in [10, 30, 100, 300]:
A = (side_nm * 1e-9) ** 2
Rd = r0["rho_spec"] / A
C = epsilon_0 * EPS_R * A / (r0["t_nm"] * 1e-9)
check.append(dict(side_nm=side_nm, R_d_ohm=Rd, C_aF=C * 1e18,
f_c_THz=1 / (2 * np.pi * Rd * C) / 1e12))
out = dict(A7=A7, area_independence_check=check,
feasible_examples=sorted(feas, key=lambda r: -r["f_c_THz"])[:8],
all_rows=rows)
with open("results_mim.json", "w") as fp:
json.dump(out, fp, default=float)
print("=" * 74)
print("A7 — MIM RECTIFIER TRILEMMA")
print("=" * 74)
print(f"configurations scanned : {A7['n_configs']}")
print(f"feasible (f_c>28.3THz, beta>1/V) : {A7['n_feasible']}")
print(f"feasible junction side range: {A7['min_feasible_side_nm']:.1f} – "
f"{A7['max_feasible_side_nm']:.1f} nm" if sides else "none")
print(f"all feasible under 30 nm? {A7['all_under_30nm']} -> "
f"{'PASS' if A7['passed'] else 'FAIL'}")
print("\n--- STRUCTURAL CHECK: does shrinking the junction raise f_c? ---")
print(f"{'side(nm)':>9} {'R_d(ohm)':>14} {'C(aF)':>10} {'f_c(THz)':>10}")
for c in check:
print(f"{c['side_nm']:>9} {c['R_d_ohm']:>14.3e} {c['C_aF']:>10.3f} {c['f_c_THz']:>10.3f}")
print("\n--- top feasible configurations ---")
print(f"{'t(nm)':>6} {'phi1':>5} {'phi2':>5} {'f_c(THz)':>9} {'beta(1/V)':>10} "
f"{'asym':>7} {'side@50R':>9} {'side@200R':>10}")
for r in sorted(feas, key=lambda r: -r["f_c_THz"])[:8]:
print(f"{r['t_nm']:>6} {r['phi1']:>5} {r['phi2']:>5} {r['f_c_THz']:>9.1f} "
f"{r['beta']:>10.2f} {r['asym']:>7.2f} {r['side_hi_nm']:>9.1f} {r['side_lo_nm']:>10.1f}")
"""Sensitivity of A7 to the two declared model optimisms: image-force lowering
and tunneling effective mass. Bounds how model-limited the absolute f_c is."""
import numpy as np, json
from scipy.constants import e as QE, hbar, m_e, k as kB, epsilon_0, h as PLANCK
import mim_sim as M
def wkb_T_img(E, phi1, phi2, s, V, m_eff, EF=5.0, eps_r=9.0, image=True, n=300):
x = np.linspace(0.0, s, n)
Vb = EF + phi1 + (phi2 - V - phi1) * (x / s)
if image:
lam = QE * np.log(2) / (8 * np.pi * epsilon_0 * eps_r * s) # volts
xi = np.clip(x, 0.02 * s, 0.98 * s)
Vb = Vb - 1.15 * lam * s ** 2 / (xi * (s - xi))
dV = Vb[None, :] - E[:, None]
integ = np.trapezoid(np.sqrt(2 * m_eff * m_e * QE * np.clip(dV, 0, None)), x, axis=1)
return np.exp(-2.0 * integ / hbar)
def J(V, phi1, phi2, s, m_eff, image, EF=5.0, nE=400):
E = np.linspace(0.0, EF + max(phi1, phi2) + 2.0, nE)
Tr = wkb_T_img(E, phi1, phi2, s, V, m_eff, EF, image=image)
return (4*np.pi*m_eff*m_e*QE/PLANCK**3)*np.trapezoid(Tr*M.supply(E,V,EF),E)*QE**2
def metrics(phi1, phi2, s, m_eff, image, dV=0.02):
Vs=[-dV,0.0,dV]; j=[J(v,phi1,phi2,s,m_eff,image) for v in Vs]
Ip=(j[2]-j[0])/(2*dV); Ipp=(j[2]-2*j[1]+j[0])/dV**2
if Ip<=0: return np.nan,np.nan
rho=1/Ip; RC=rho*epsilon_0*9.0/s
return 1/(2*np.pi*RC)/1e12, Ipp/(2*Ip)
print(f"{'m_eff':>6} {'image':>6} {'t(nm)':>6} {'phi1':>5} {'f_c(THz)':>10} {'beta(1/V)':>10}")
best={}
for m_eff in [0.2,0.3,0.4]:
for image in [False,True]:
rec=(-1,None)
for t in [0.8,1.0,1.5,2.0]:
for p1 in [0.3,0.5,1.0,1.5,2.0]:
p2=max(p1-0.5,0.1)
fc,b=metrics(p1,p2,t*1e-9,m_eff,image)
if np.isfinite(fc) and fc>rec[0]: rec=(fc,(t,p1,b))
fc,(t,p1,b)=rec
best[(m_eff,image)]=fc
print(f"{m_eff:>6} {str(image):>6} {t:>6} {p1:>5} {fc:>10.2f} {b:>10.3f}")
print()
print("target for 10.6 um LWIR: 28.3 THz")
print("max f_c over the whole sensitivity envelope: %.2f THz"%max(best.values()))
print("reaches 28.3 THz anywhere?", max(best.values())>28.3)
import json, numpy as np
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
D = json.load(open("results_wpt.json"))
T, F = D["tests"], D["figures"]
plt.rcParams.update({"font.size": 8.5, "axes.grid": True, "grid.alpha": .25,
"figure.dpi": 150})
ACC, REJ, NEU = "#1b7f4f", "#b3261e", "#31527a"
fig = plt.figure(figsize=(13.5, 12.5))
gs = fig.add_gridspec(4, 3, hspace=.52, wspace=.30)
# --- A1 range law ------------------------------------------------------------
ax = fig.add_subplot(gs[0, 0])
Q, dm = np.array(F["A1"]["Q"]), np.array(F["A1"]["dmax"])
ax.loglog(Q, dm, "o-", ms=3, color=ACC)
ax.loglog(Q, dm[0] * (Q / Q[0]) ** (1 / 3), "--", color="k", lw=.9, label="$Q^{1/3}$")
ax.set(xlabel="quality factor $Q$", ylabel="$d_{max}$ [m]",
title=f"A1 PASS · range law\nfitted slope {T['A1']['slope']:.4f} (target 1/3)")
ax.legend(fontsize=7)
# --- A2 coupling -------------------------------------------------------------
ax = fig.add_subplot(gs[0, 1])
r, k = np.array(F["A2"]["ratio"]), np.array(F["A2"]["k"])
ax.loglog(r, k, "o-", ms=3, color=REJ)
ax.loglog(r, 0.2248 * r ** -3.0, "--", color="k", lw=.9, label=r"$0.225\,(a/d)^{-3}$")
ax.axvspan(3, 10, color=REJ, alpha=.10)
ax.text(4.0, k.min() * 30, "expansion\nnot yet valid", fontsize=6.5, color=REJ)
ax.set(xlabel="$d/a$", ylabel="coupling $k$",
title=f"A2 FAIL · slope {T['A2']['slope']:.3f} over $d/a\\geq3$\n"
f"$\\to$ {T['diagnostics']['D2_k_scaling_by_floor']['d/a>=10']['slope']:.3f} over $d/a\\geq10$")
ax.legend(fontsize=7)
# --- A3 the headline claim ---------------------------------------------------
ax = fig.add_subplot(gs[0, 2])
a, Rc = np.array(F["A3"]["a"]), np.array(F["A3"]["Rc"])
cf = F["A3"]["Rc_closed"]
ax.semilogx(a, Rc, "o-", ms=3, color=NEU, label="exact field solve")
ax.axhline(cf, ls="--", color="k", lw=.9, label="closed form (Eq. 4.6)")
ax.axhspan(cf * .95, cf * 1.05, color=ACC, alpha=.15, label="$\\pm5\\%$ band")
ax.axvline(20 / 10, color=REJ, ls=":", lw=1.2)
ax.text(2.15, Rc.max() * .97, "$d/a=10$", fontsize=6.5, color=REJ)
ax.set(xlabel="coil radius $a$ [m] ($P$=100 kW, $d$=20 m)", ylabel="$R_c$ [m]",
title=f"A3 FAIL · spread {T['A3']['spread_full_sweep']:.3f} full sweep\n"
f"but {T['diagnostics']['D3_Rc_spread_by_floor']['d/a>=10']['spread']:.4f} for $d/a\\geq10$")
ax.legend(fontsize=6.5, loc="lower left")
# --- A4 exponents ------------------------------------------------------------
ax = fig.add_subplot(gs[1, 0])
P, RP = np.array(F["A4"]["P"]), np.array(F["A4"]["Rc_P"])
ax.loglog(P, RP, "o-", ms=3, color=ACC)
ax.loglog(P, RP[0] * (P / P[0]) ** (1 / 6), "--k", lw=.9, label="$P^{1/6}$")
ax.set(xlabel="delivered power $P$ [W]", ylabel="$R_c$ [m]",
title=f"A4 PASS · $R_c\\propto P^{{{T['A4']['slope_P']:.4f}}}$, "
f"$d^{{{T['A4']['slope_d']:.4f}}}$")
ax.legend(fontsize=7)
# --- A5 cryo -----------------------------------------------------------------
ax = fig.add_subplot(gs[1, 1])
ratios = np.logspace(0, 4, 200)
for COP, lab in [(0.07, "77 K"), (0.010, "20 K"), (0.002, "4 K")]:
ax.loglog(ratios, ratios * COP, lw=1.2, label=f"{lab} (COP={COP})")
ax.axhline(1, color="k", ls="--", lw=.9)
ax.set(xlabel="$Q_{SC}/Q_{Cu}$", ylabel="wall-power advantage",
title="A5 PASS · cryo break-even at $1/$COP\nrange gain only $(1/COP)^{1/3}$")
ax.legend(fontsize=7)
# --- A6 crossover ------------------------------------------------------------
ax = fig.add_subplot(gs[1, 2])
Qc, dx = np.array(F["A6"]["Q"]), np.array(F["A6"]["d_cross"])
ax.loglog(Qc, dx, "o-", ms=4, color=REJ)
ax.axhline(0.40, ls="--", color="k", lw=.9, label="paper C20 = 0.40 m")
ax.plot(1e3, dx[0], "*", ms=14, color=REJ)
ax.annotate(f"{dx[0]:.3f} m", (1e3, dx[0]), textcoords="offset points",
xytext=(12, -10), fontsize=7, color=REJ)
ax.set(xlabel="$Q$", ylabel="crossover distance [m]",
title=f"A6 FAIL · exact $k$ gives {dx[0]:.3f} m, not 0.40 m\n"
f"slope {T['A6']['slope_vs_Q']:.3f} (target 2/3)")
ax.legend(fontsize=7)
# --- A8 FAILURE PROPAGATION PANEL (2 rows) ----------------------------------
rr = np.array(F["A8"]["ratio"])
TH = F["A8"]["thresholds"]
panels = [("efficiency", "$\\eta_{max}$", False, "family A"),
("reactive", "$P_{circ}$ [VA]", True, "family A"),
("reqQ", "required $Q$", True, "family A"),
("exclusion", "$R_c$ [m]", True, "family B")]
for i, (key, lab, logy, fam) in enumerate(panels):
ax = fig.add_subplot(gs[2, i] if i < 3 else gs[3, 0])
v = np.array(F["A8"][key])
col = REJ if fam == "family A" else NEU
ax.plot(rr, v, color=col, lw=1.4)
ax.axhline(TH[key], ls="--", color="k", lw=.9)
b = T["A8"]["breach_points"][key]
if b:
ax.axvline(b, color=col, ls=":", lw=1.4)
ax.annotate(f"breach\n$d/a$={b:.1f}", (b, np.median(v)),
textcoords="offset points", xytext=(8, 0), fontsize=6.5, color=col)
ax.set_xscale("log")
if logy: ax.set_yscale("log")
ax.set(xlabel="$d/a$ (single knob)", ylabel=lab,
title=f"A8 · {key} [{fam}]")
# --- A8 summary: the two families -------------------------------------------
ax = fig.add_subplot(gs[3, 1])
bp = T["A8"]["breach_points"]
names = list(bp.keys()); vals = [bp[n] for n in names]
cols = [NEU if n == "exclusion" else REJ for n in names]
ax.barh(names, vals, color=cols)
ax.set_xscale("log")
ax.axvspan(min(v for n, v in zip(names, vals) if n != "exclusion"),
max(v for n, v in zip(names, vals) if n != "exclusion"),
color=REJ, alpha=.15)
ax.set(xlabel="$d/a$ at which budget breaches",
title=f"A8 FAIL · span {T['A8']['decade_span']:.1f}$\\times$ (target $\\leq$10)\n"
f"but family A spans only "
f"{T['diagnostics']['D8_clustering']['family_A_span']:.2f}$\\times$")
# --- A7 MIM ------------------------------------------------------------------
M = json.load(open("results_mim.json"))
ax = fig.add_subplot(gs[3, 2])
chk = M["area_independence_check"]
s = [c["side_nm"] for c in chk]
ax.semilogx(s, [c["f_c_THz"] for c in chk], "o-", ms=6, color=REJ, lw=2,
label="$f_c$ (exactly flat)")
ax2 = ax.twinx()
ax2.loglog(s, [c["R_d_ohm"] for c in chk], "s--", ms=4, color=NEU, label="$R_d$")
ax2.loglog(s, [c["C_aF"] for c in chk], "^--", ms=4, color=ACC, label="$C$")
ax2.set_ylabel("$R_d$ [$\\Omega$] / $C$ [aF]", fontsize=7.5)
ax.set(xlabel="junction side [nm]", ylabel="$f_c$ [THz]",
title="A7 FAIL · $R_d\\propto1/A$, $C\\propto A$\n$\\Rightarrow RC$ area-INDEPENDENT")
ax.legend(fontsize=6.5, loc="center left"); ax2.legend(fontsize=6.5, loc="lower right")
fig.suptitle("Wireless Grid Simulation — Pre-Registered Acceptance Tests "
"(3 / 7 PASS · all failures diagnosed)", y=.995, fontsize=12)
fig.savefig("/mnt/user-data/outputs/acceptance_tests.png", bbox_inches="tight")
print("figure written")