See Drexler's mechanical nanotechnology from 1989.[1]
There's a minimum size at which such mechanisms will work, and it's bigger than transistors. This won't scale down to single atoms, according to chemists.
It seems like you've misremembered the situation somewhat.
Merkle developed several of his families of mechanical logic, including this one, in order to answer some criticisms of Drexler's earliest mechanical nanotechnology proposals. Specifically:
1. Chemists were concerned that rod logic knobs touching each other would form chemical bonds and remain stuck together, rather than disengaging for the next clock cycle. (Macroscopic metal parts usually don't work this way, though "cold welding" is a thing, especially in space.) So this proposal‚ like some earlier ones like Merkle's buckling-spring logic, avoids any contact between unconnected parts of the mechanism, whether sliding or coming into and out of contact.
2. Someone calculated the power density of one of Drexler's early proposals and found that it exceeded the power density of high explosives during detonation, which obviously poses significant challenges for mechanism durability. You could just run them many orders of magnitude slower, but Merkle tackled the issue instead by designing reversible logic families which can dissipate arbitrarily little power per logic operation, only dissipating energy to erase stored bits.
So, there's nothing preventing this kind of mechanism from scaling down to single atoms, and we already have working mechanisms like the atomic force microscope which demonstrate that even intermittent single-atom contact can work mechanically in just the way you'd expect it to from your macroscopic intuition. Moreover, the de Broglie wavelength of a baryon is enormously shorter than the de Broglie wavelength of an electron, so in fact mechanical logic (which works by moving around baryons) can scale down further than electronic logic, which is already running into Heisenberg problems with current semiconductor fabrication technology.
Also, by the way, thanks to the work for which Boyer and Walker got part of the 01997 Nobel Prize in Chemistry, we probably know how ATP synthase works now, and it seems to work in a fairly similar way: https://www.youtube.com/watch?v=kXpzp4RDGJI
zozbot234 · 1h ago
The interesting question is how much energy is lost to mechanical friction for a single logic operation, and how this compares to static leakage losses in electronic circuits. It should also be noted that mechanical logic may turn out to be quite useful for specialized purposes as part of ordinary electronic devices, such as using nano-relay switches for power gating or as a kind of non-volatile memory.
kragen · 27m ago
That's one of many interesting questions, but avoiding it is why Merkle designed his reversible logic families in such a way that no mechanical friction is involved, because there is no sliding contact. There are still potentially other kinds of losses, though.
gene-h · 3h ago
And why wouldn't it work? Linear slide like mechanisms consisting of a silver surface and single molecule have been demonstrated[0]. The molecule only moved along rows of the silver surface. It was demonstrated to stay in one of these grooves up to 150 nm. A huge distance at this scale.
It can work (see my sibling comment) but it's tricky. The experiment you link was done under ultra-high vacuum and at low temperatures (below 7 K), using a quite exotic molecule which is, as I understand it, covered in halogens to combat the "sticky fingers" problem.
gradschool · 1h ago
You seem to be knowledgeable about this topic. The reversible
component designs in the article appear to presuppose a clock signal
without much else said about it. I get that someone might be able to
prototype an individual gate, but is the implementation of a practical
clock distribution network at molecular scales reasonable to take for granted?
kragen · 1h ago
I'm only acquainted with the basics of the topic, not really knowledgeable. It's an interesting question. I don't think the scale poses any problem—the smaller the scale is, the easier it is to distribute the clock—but there might be some interesting problems related to distributing the clock losslessly.
gsf_emergency · 56m ago
Not an expert, but would this count as molecular scale :)?
To your question: I suppose all you need is for the halide moieties (Br) in your gates to also couple to the halide ions (Br clock?). The experiment you link was conducted at 7K for the benefit of being able to observe it with STM?
kragen · 29m ago
That's a different kind of clock, and its clock mechanism is a gradual and somewhat random decrease in the concentration of one reagent until it crosses a threshold which changes the equilibrium constant of iodine. It isn't really related to the kind of clock you use for digital logic design, which is a periodic oscillation whose purpose is generally to make your design insensitive to glitches. Usually you care about glitches because they could cause incorrect state transitions, but in this case the primary concern is that they would cause irreversible power dissipation.
The experiment was conducted at 7K so the molecule would stick to the metal instead of shaking around randomly like a punk in a mosh pit and then flying off into space.
gsf_emergency · 17m ago
Yeah you're probably right about the clocks but I hope that wouldn't stop people from trying :)
>The experiment was conducted at 7K so the molecule
Br is good at sticking to Ag so I suspect the 7K is mainly (besides issues connected to their AFM^W STM setup) because the Euro dudes love ORNL's cryo engineering :)
kragen · 5m ago
Br's orbitals are filled here because it's covalently bonded to a carbon, so it's basically krypton. Experiments with moving atoms around on surfaces with STMs are always done at cryogenic temperatures because that's the only way to do them.
gsf_emergency · 25m ago
Not entirely.. terminal Br were also required to keep the molecule on the Silver tracks..
kragen · 4m ago
Those are some of the halogens I'm talking about. It's a little more polarizable than the covalently-bonded fluorine, so you get more of a van der Waals attraction, but still only a very weak one.
7373737373 · 1h ago
I'd love to see a watch manufacturer try to build a watch-sized purely mechanical computer
qoez · 4h ago
For things like machine learning I wonder how much extra performance could be squeezed out by simply working with continuous floating values on the analog level instead of encoding them as bits through a big indirect network of nands.
tails4e · 3h ago
This is something that has been tried, basically constructing an analog matrix multiply/dot product and it gives reasonable power efficiency at into levels of precision. More precision and the analog accuracy leads to dramatic power efficiey losses (each bit is about 2x the power), so int8 is probably the sweet spot. The main issues are it is pretty inflexible and costly to design vs a digital int8 mac array, and hard to port to newer nodes, etc
hermitShell · 3h ago
I have wondered this and occasionally seen some related news.
Transistors can do more than on and off, there is also the linear region of operation where the gate voltage allows a proportional current to flow.
So you would be constructing an analog computer. Perhaps in operation it would resemble a meat computer (brain) a little more, as the activation potential of a neuron is some analog signal from another neuron. (I think? Because a weak activation might trigger half the outputs of a neuron, and a strong activation might trigger all outputs)
I don’t think we know how to construct such a computer, or how it would perform set computations. Like the weights in the neural net become something like capacitance at the gates of transistors. Computation is I suppose just inference, or thinking?
Maybe with the help of LLM tools we will be able to design such things. So far as I know there is nothing like an analog FPGA where you program the weights instead of whatever you do to an FPGA… making or breaking connections and telling LUTs their identity
It's possible, but analog multiplication is hard and small analog circuits tend to be very noisy. I think there is a startup working on making an accelerator chip that is based on this principle, though.
Calwestjobs · 2h ago
TLC,QLC,MLC in ssd is it. so it is used already. and it gives you limits of current technology.
ziddoap · 2h ago
>*TLC,QLC,MLC"
For those unaware of these acronyms (me):
TLC = Triple-Layer Cell
QLC = Quad-Level Cell
MLC = Multi-Level Cell
thrance · 2h ago
You lose a lot of stability. Each operation's result is slightly off, and the error accumulates and compounds. For deep learning in particular, many operations are carried in sequence and the error rates can become inacceptable.
Legend2440 · 2h ago
Deep learning is actually very tolerant to imprecision, which is why it is typically given as an application for analog computing.
It is already common practice to deliberately inject noise into the network (dropout) at rates up to 50% in order to prevent overfitting.
red75prime · 1h ago
Isn't it just for inference? Also, differentiating thru an analog circuit looks... interesting. Keep inputs constant, wiggle one weight a bit, store how the output changed, go to the next weight, repeat. Is there something more efficient, I wonder.
PendulumSegment · 3h ago
This is very interesting because according to one of the authors of the mechanical computing paper(personal communication) they never dynamically simulated the mechanisms. It was purely kinematic. So this web browser simulation is new work. Reversibility might disappear once dynamics are modelled.
mitthrowaway2 · 3h ago
Indeed. The web simulation clearly applies damping, which is an irreversible element. A truly reversible process should probably be built around minimally-damped oscillating elements, so that the stored energy never needs to dissipate.
PendulumSegment · 3h ago
Even if damping is removed they might not be reversible. Logic gates that were found to be individually reversible, were found to have difficulties operating when connected in a circuit:
https://core.ac.uk/download/pdf/603242297.pdf
rkp8000 · 3h ago
A great pedagogical article on thermodynamic vs logical reversibility, for those interested: https://arxiv.org/abs/1311.1886 (Sagawa 2014).
coumbaya · 2h ago
This is the concept behind the computers in The Diamond Age right ? Or am I mistaken ?
fintler · 2h ago
It's very similiar. The rod logic in diamond age (Eric Drexler was the one who originally came up with it) moves linearly -- not rotationally like this does. It's also reversible.
danbmil99 · 1h ago
Now that I think of it, if using damped springs, the system would not be reversible. Energy is dissipated through the damping, and the system will increase in entropy and converge on a local energy minimum point.
Another way of looking at it: there are 4 states going in (0 or 1 on 2 pushers) but there are only 2 states of the 'memory' contraption, so you lose a bit on every iteration (like classical Boolean circuits)
fintler · 2h ago
Classical reversible computing feels like it would be a good way to interface with a quantum computer (since it's also reversible in theory).
danbmil99 · 1h ago
Quantum computation came directly out of reversible computing. Look for example at the Fredkin and Toffoli gates.
jstanley · 4h ago
> Specifically, the Landauer’s principle states that all non-physically-reversible computation operations consume at least 10^21 J of energy at room temperature (and less as the temperature drops).
Wow! What an absurd claim!
I checked the Wikipedia page and I think you actually meant 10^-21 J :)
tennysont · 9m ago
Fix! Ty!
P.S. I once calculated the mass of the sun as 0.7kg and got 9/10 points on the questions.
godelski · 2h ago
FYI, total global energy production is a lot less than 10^21 J. It's south of 10^19 from what I can google...
kragen · 2h ago
Depends on which aspects of energy production you're concerned with and over what time period. Global marketed energy production is about 18 terawatts, which is about 10²¹ J every year and 9 months. The energy globally produced by sunlight hitting the Earth, mostly as low-grade heat, is on the order of 100 petawatts, which is 10²¹ J every hour and a half or so. Global agriculture is in between these numbers.
mathgradthrow · 2h ago
A big problem with the idea of physical reversible computing is the assumption that you get to start with a blank tape. Blank tapes are trivial to acquire if I can erase bits, but if I start with a tape in some state, creating working space in memory reverisbly is equivalent (identical) to lossless compression, which is not generally achievable.
If you start with blank tape then it isn't really reversible computing, you're just doing erasure up front.
kragen · 2h ago
I don't think your criticism is applicable to any reversible-computing schemes that I've seen proposed, including this one. They don't assume that you get to start with a blank memory (tapelike or otherwise); rather, they propose approaches to constructing a memory device in a known state, out of atoms.
mathgradthrow · 1h ago
What do you think you're saying here? Building a memory
device in a known configuration is erasing bits.
kragen · 1h ago
Yes, building a memory device in a known configuration is erasing bits. Once you've built it, you can use it until it breaks. As long as you decompute the bits you've temporarily stored in it, restoring it to its original configuration, you don't inherently have to dissipate any energy to use it. You can reuse it an arbitrarily large number of times after building it once. If you want to compute some kind of final result that you store, rather than decomputing it, that does cost you energy in the long run, but that energy can be arbitrarily small compared to the computation that was required to reach it.
Consider the case, for example, of cracking an encryption key; each time you try an incorrect key, you reverse the whole computation. It's only when you hit on the right key that you store a 1 bit indicating success and a copy of the cracked key; then you reverse the last encryption attempt, leaving only the key. Maybe you've done 2¹²⁸ trial encryptions, each requiring 2¹³ bit operations, for a total of 2¹⁴¹ bit operations of reversible computation, but you only need to store 2⁷ bits to get the benefit, a savings of 2¹³⁵×.
Most practical computations don't enjoy quite such a staggering reduction in thermodynamic entropy from reversible computation, but a few orders of magnitude is commonplace.
It sounds like you could benefit from reading an introduction to the field. Though I may be biased, I can recommend Michael Frank's introduction from 20 years ago: https://web1.eng.famu.fsu.edu/~mpf/ip1-Frank.pdf
rcxdude · 1h ago
Yes, but erasing the tape once is much better than erasing the tape many times over.
There's a minimum size at which such mechanisms will work, and it's bigger than transistors. This won't scale down to single atoms, according to chemists.
[1] http://www.nanoindustries.com/nanojbl/NanoConProc/nanocon2.h...
Merkle developed several of his families of mechanical logic, including this one, in order to answer some criticisms of Drexler's earliest mechanical nanotechnology proposals. Specifically:
1. Chemists were concerned that rod logic knobs touching each other would form chemical bonds and remain stuck together, rather than disengaging for the next clock cycle. (Macroscopic metal parts usually don't work this way, though "cold welding" is a thing, especially in space.) So this proposal‚ like some earlier ones like Merkle's buckling-spring logic, avoids any contact between unconnected parts of the mechanism, whether sliding or coming into and out of contact.
2. Someone calculated the power density of one of Drexler's early proposals and found that it exceeded the power density of high explosives during detonation, which obviously poses significant challenges for mechanism durability. You could just run them many orders of magnitude slower, but Merkle tackled the issue instead by designing reversible logic families which can dissipate arbitrarily little power per logic operation, only dissipating energy to erase stored bits.
So, there's nothing preventing this kind of mechanism from scaling down to single atoms, and we already have working mechanisms like the atomic force microscope which demonstrate that even intermittent single-atom contact can work mechanically in just the way you'd expect it to from your macroscopic intuition. Moreover, the de Broglie wavelength of a baryon is enormously shorter than the de Broglie wavelength of an electron, so in fact mechanical logic (which works by moving around baryons) can scale down further than electronic logic, which is already running into Heisenberg problems with current semiconductor fabrication technology.
Also, by the way, thanks to the work for which Boyer and Walker got part of the 01997 Nobel Prize in Chemistry, we probably know how ATP synthase works now, and it seems to work in a fairly similar way: https://www.youtube.com/watch?v=kXpzp4RDGJI
[0]https://www.osti.gov/servlets/purl/1767839
https://en.wikipedia.org/wiki/Chemical_clock
(This version can be done at home with halides imho: https://en.wikipedia.org/wiki/Iodine_clock_reaction)
To your question: I suppose all you need is for the halide moieties (Br) in your gates to also couple to the halide ions (Br clock?). The experiment you link was conducted at 7K for the benefit of being able to observe it with STM?
The experiment was conducted at 7K so the molecule would stick to the metal instead of shaking around randomly like a punk in a mosh pit and then flying off into space.
>The experiment was conducted at 7K so the molecule
Br is good at sticking to Ag so I suspect the 7K is mainly (besides issues connected to their AFM^W STM setup) because the Euro dudes love ORNL's cryo engineering :)
Transistors can do more than on and off, there is also the linear region of operation where the gate voltage allows a proportional current to flow.
So you would be constructing an analog computer. Perhaps in operation it would resemble a meat computer (brain) a little more, as the activation potential of a neuron is some analog signal from another neuron. (I think? Because a weak activation might trigger half the outputs of a neuron, and a strong activation might trigger all outputs)
I don’t think we know how to construct such a computer, or how it would perform set computations. Like the weights in the neural net become something like capacitance at the gates of transistors. Computation is I suppose just inference, or thinking?
Maybe with the help of LLM tools we will be able to design such things. So far as I know there is nothing like an analog FPGA where you program the weights instead of whatever you do to an FPGA… making or breaking connections and telling LUTs their identity
For those unaware of these acronyms (me):
TLC = Triple-Layer Cell
QLC = Quad-Level Cell
MLC = Multi-Level Cell
It is already common practice to deliberately inject noise into the network (dropout) at rates up to 50% in order to prevent overfitting.
Another way of looking at it: there are 4 states going in (0 or 1 on 2 pushers) but there are only 2 states of the 'memory' contraption, so you lose a bit on every iteration (like classical Boolean circuits)
Wow! What an absurd claim!
I checked the Wikipedia page and I think you actually meant 10^-21 J :)
P.S. I once calculated the mass of the sun as 0.7kg and got 9/10 points on the questions.
If you start with blank tape then it isn't really reversible computing, you're just doing erasure up front.
Consider the case, for example, of cracking an encryption key; each time you try an incorrect key, you reverse the whole computation. It's only when you hit on the right key that you store a 1 bit indicating success and a copy of the cracked key; then you reverse the last encryption attempt, leaving only the key. Maybe you've done 2¹²⁸ trial encryptions, each requiring 2¹³ bit operations, for a total of 2¹⁴¹ bit operations of reversible computation, but you only need to store 2⁷ bits to get the benefit, a savings of 2¹³⁵×.
Most practical computations don't enjoy quite such a staggering reduction in thermodynamic entropy from reversible computation, but a few orders of magnitude is commonplace.
It sounds like you could benefit from reading an introduction to the field. Though I may be biased, I can recommend Michael Frank's introduction from 20 years ago: https://web1.eng.famu.fsu.edu/~mpf/ip1-Frank.pdf