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Interest in the thermodynamics of computation has revived in recent years, driven by developments in science, economics and technology. Given the consequences of the growing demand for computational power, the idea of reducing the energy cost of computations has gained new importance. Simultaneously, many biological networks are now interpreted as information-processing or computational systems constrained by their underlying thermodynamics. Indeed, some suggest that low-cost, high-density biological systems may help to mitigate the rising demand for computational power and the "end" of Moore's law of exponential growth in the density of transistors. In this chapter we address widespread misconceptions about thermodynamics and the thermodynamics of computation. In particular, we will argue against the general perception that a measurement or copy operation can be performed at no cost, against the emphasis placed on the significance of erasure operations, and against the careless discussion of heat and work. While not universal, these misconceptions are sufficiently prevalent (particularly within interdisciplinary contexts) to warrant a detailed discussion. In the process, we will argue that explicitly representing fundamental processes is a useful tool, serving to demystify key concepts. We first give a brief overview of thermodynamics, then the history of the thermodynamics of computation - particularly in terms of copy and measurement operations inherent to classic thought experiments. Subsequently, we analyse these ideas via an explicit biochemical representation of the entire cycle of Szilard's engine. In doing so we show that molecular computation is both a promising engineering paradigm, and a valuable tool in providing fundamental understanding.

The Power of Being Explicit: Demystifying Work, Heat, and Free Energy in the Physics of Computation