Hi Vladimir,
Thank you for your kind comments. The central thesis is not quite "that studying the origin of life life requires a new physical paradigm to explain the process why some molecules started self-reproducing" as you state it. I completely agree that this particular aspect of the problem doesn't necessitate invoking any new physics. But, I think one much be very careful to distinguish trivially self-replicating systems from non-trivial self-replication. For an example of the former, one could look at Penrose blocks (Penrose & Penrose Nature 1958) - replication of a given seed structure (blocks aligned in one orientation or the other) is completely determined by local physics and chemistry. Contrast this with the logical structure of something like a von Neumann self-replicating automata (a very rough approximation to the way cells do business), which requires an algorithm to specify how the machine will replicate. In this scenario replication is explicitly programmed in the machine. The machine may therefore be programed to construct specific objects, and does so in some sense independent of direction by the implicit physics and chemistry (although of course adhering to the constraints imposed by physical law). Evolution is distinguished between these two possibilities since for trivial replicators only the physical structure evolves, while for nontrivial replicators you must evolve both the physical structures and the algorithms (e.g. one may loosely think of the dichotomy between genotype and phenotype in living systems and how they cannot be disentangled, leading to highly nontrivial evolutionary dynamics). So life is very different because it has explicit programming. That is the central thesis - we do not see this anywhere outside of the biosphere (computers here are included in the biosphere since they are derivative of it). So the critical question in the origin of life is how does this state of affairs arise in nature? My intuition is that it has everything to do with information transiting to an active cause in the system.
You mention that organisms can have a definite cycle of states and I completely agree! But one trick in biology is that in your example, if you remove G say, which is a cause for A, another element in the system might take over for G. More interesting is that it is not a simple case of a cyclic process, but those states are tightly regulated, you would need information control with reliable protocols interfacing between elements of the system in your example to more accurately capture what biology is actually doing. That makes the situation both much more complicated but also more interesting.
The information control issue is what is critically interesting to me. Top-down causation is a useful concept in this framework because you can more easily articulate the fact that the algorithm(s) play a distinctive role in the dynamics of the system. Everything about the way information is implemented in biology is context-dependent suggesting that these nonphysical or virtual aspects of the systems operation are changing with the states and vice versa and actively influencing the dynamics. To me that suggests that information is a cause in its own right - that is the radical departure from more traditional ways of doing business in physics and indicates that biology is much closer to to the realm of Turing than to the realm of traditional physics. Causation is not the difficult part to define however - so it is not the 'top-down' that is difficult. The difficult part is defining what are the 'levels' and what are the protocols/algorithms? So this is what I meant about difficulty with defining the concept - its a challenge for practical application. I think we are only at the beginning stages of trying to grasp at concrete answers to these questions as molecular biologists are now embarking on mapping regulatory networks in the cell (e.g. just this week with the ENCODE project).
Thank you for the engaging discussion, and I will be sure to look into your BU theory.
Best,
Sara