The discussion is about nanowires for interconnect. The Landauer model correctly predicted—in advance—a nanowire capacitance of 1 electron charge per 1 volt per 1 electron radius, ie 1.602 e-19 F / 1.23 nm, or 1.3026 e-10 F/m. This is near exactly the same as the capacitance wire spherical cow model:
assumption that all wires in a chip are half as capacitive as ideal coax cables, and the dielectric is the same thickness as the wires. Then the capacitance is about 1.3*10^-10 Farads/m (note: this drops as you make chips bigger, but only logarithmically).
“and the dielectric is the same thickness as the wires.” is doing the work there. It makes sense to do that if You’re packing everything tightly but with an 8 OOM increase in conductivity we can choose to change the ratio (by quite a lot) in the existing brain design. In a clean slate design you would obviously do some combination of wire thinning and increasing overall density to reduce wire length.
The figures above show that (ignoring integration problems like copper toxicity and NA/K vs e- charge carrier differences) Assuming you do a straight saltwater to copper swap in white matter neurons and just change the core diameter (replacing most of it with insulation), energy/switch event goes down by 12.5x.
I’m pretty sure for non-superconductive electrical interconnects the reliability is set by the Johnson-Nyquist_noise and figuring out the output noise distribution for an RC transmission line is something I don’t feel like doing right now. Worth noting is that the above scenario preserves the R:C ratio of the transmission line (IE: 1 ohm worth of line has the same distributed capacitance) so thermal noise as seen from the end should be unchanged.
The brain is already close to the landauer limit for irreversible interconnect in terms of energy per bit per nm; swapping out materials is irrelevant.
Consider a Nanoelectromechanical relay. These are usually used for RF switching so switching voltage isn’t important, but switching voltage can be brought arbitrarily low. Mass of the cantilever determines frequency response. A NEMR with a very long light low-stiffness cantilever could respond well at 20khz and be sensitive to thermal noise. Adding mass to the end makes it less sensitive to transients (lower bandwidth, slower response) without affecting switching voltage.
In a NEMS computer there’s the option of dropping (stiffness, voltage, operating frequency) and increasing inertia (all proportionally) which allows for quadratic reductions in power consumption.
IE: Moving closer to the ideal zero effective resistance by taking clock speed to zero.
The bit erasure Landauer limit still applies but we’re ~10^6 short of that right now.
Caveats:
NEM relays currently have limits to voltage scaling due to adhesion. Assume the hypothetical relay has a small enough contact point that thermal noise can unstick it. Operation frequency may have to be a bit lower to wait for this to happen.
The discussion is about nanowires for interconnect. The Landauer model correctly predicted—in advance—a nanowire capacitance of 1 electron charge per 1 volt per 1 electron radius, ie 1.602 e-19 F / 1.23 nm, or 1.3026 e-10 F/m. This is near exactly the same as the capacitance wire spherical cow model:
“and the dielectric is the same thickness as the wires.” is doing the work there. It makes sense to do that if You’re packing everything tightly but with an 8 OOM increase in conductivity we can choose to change the ratio (by quite a lot) in the existing brain design. In a clean slate design you would obviously do some combination of wire thinning and increasing overall density to reduce wire length.
The figures above show that (ignoring integration problems like copper toxicity and NA/K vs e- charge carrier differences) Assuming you do a straight saltwater to copper swap in white matter neurons and just change the core diameter (replacing most of it with insulation), energy/switch event goes down by 12.5x.
I’m pretty sure for non-superconductive electrical interconnects the reliability is set by the Johnson-Nyquist_noise and figuring out the output noise distribution for an RC transmission line is something I don’t feel like doing right now. Worth noting is that the above scenario preserves the R:C ratio of the transmission line (IE: 1 ohm worth of line has the same distributed capacitance) so thermal noise as seen from the end should be unchanged.
The brain is already close to the landauer limit for irreversible interconnect in terms of energy per bit per nm; swapping out materials is irrelevant.
Consider trying to do the reverse for computers. Swap copper for saltwater.
You can of course drop operation frequency by 10^8 for a 10-50 hz clock speed. Same energy efficiency.
But you could get added energy efficiency in any design by scaling down the wires to increase resistance/reduce capacitance and reducing clock speed.
In the limit, Adiabatic Computing is reversible because in the limit, moving charge carriers more slowly eliminates resistance.
Thermal noise voltage is proportional to bandwidth. Put another way if the logic element responds slowly enough it see lower noise by averaging.
Consider a Nanoelectromechanical relay. These are usually used for RF switching so switching voltage isn’t important, but switching voltage can be brought arbitrarily low. Mass of the cantilever determines frequency response. A NEMR with a very long light low-stiffness cantilever could respond well at 20khz and be sensitive to thermal noise. Adding mass to the end makes it less sensitive to transients (lower bandwidth, slower response) without affecting switching voltage.
In a NEMS computer there’s the option of dropping (stiffness, voltage, operating frequency) and increasing inertia (all proportionally) which allows for quadratic reductions in power consumption.
IE: Moving closer to the ideal zero effective resistance by taking clock speed to zero.
The bit erasure Landauer limit still applies but we’re ~10^6 short of that right now.
Caveats:
NEM relays currently have limits to voltage scaling due to adhesion. Assume the hypothetical relay has a small enough contact point that thermal noise can unstick it. Operation frequency may have to be a bit lower to wait for this to happen.