Landauer's Principle states that the work cost of erasure of one bit of information has a fundamental lower bound of kT ln(2). Here we prove a quantitative Landauer's principle for arbitrary processes, providing a general lower bound on their work cost. This bound is given by the minimum amount of (information theoretical) entropy that has to be dumped into the environment, as measured by the conditional max-entropy. The bound is tight up to a logarithmic term in the failure probability. Our result shows that the minimum amount of work required to carry out a given process depends on how much correlation we wish to retain between the input and the output systems, and that this dependence disappears only if we average the cost over many independent copies of the input state. Our proof is valid in a general framework that specifies the set of possible physical operations compatible with the second law of thermodynamics. We employ the technical toolbox of matrix majorization, which we extend and generalize to a new kind of majorization, called lambda-majorization. This allows us to formulate the problem as a semidefinite program and provide an optimal solution.
Landauer's Principle states that the work cost of erasure of one bit of information has a fundamental lower bound of kT ln(2). Here we prove a quantitative Landauer's principle for arbitrary processes, providing a general lower bound on their work cost. This bound is given by the minimum amount of (information theoretical) entropy that has to be dumped into the environment, as measured by the conditional max-entropy. The bound is tight up to a logarithmic term in the failure probability. Our result shows that the minimum amount of work required to carry out a given process depends on how much correlation we wish to retain between the input and the output systems, and that this dependence disappears only if we average the cost over many independent copies of the input state. Our proof is valid in a general framework that specifies the set of possible physical operations compatible with the second law of thermodynamics. We employ the technical toolbox of matrix majorization, which we extend and generalize to a new kind of majorization, called lambda-majorization. This allows us to formulate the problem as a semidefinite program and provide an optimal solution.
Landauer's erasure principle, which is one of the defining elements of modern information theory, states the minimum work required to erase 1 bit of information is kT ln(2), where T is the temperature of a thermal reservoir and k is Boltzmann's constant [1]. This principle arises from the maximisation of the entropy of the whole system (memory bit plus thermal reservoir) subject to energy conservation. In this talk we explore a different kind of statistical mechanics based on more general constraints other than energy conservation. Such systems have the potential to provide new mechanisms for erasing information, initialising the state of quantum systems and providing novel "heat" engines. We consider a gas of spin-1/2 systems (e.g. energy degenerate two-state atoms) which comes to equilibrium via angular momentum conserving interactions (e.g. elastic collisions). We model the gas as a canonical ensemble of spin particles constrained by the conservation of angular momentum. The gas acts as a spin reservoir whose macrostate is characterised by the total (fixed) average angular momentum of the gas. Our 1 bit memory device is represented by one spin-1/2 particle in an arbitrary mixed state. The state of the memory is erased by performing controlled operations on the memory particle and ancillary spin-1/2 particles and letting the memory and ancilla particles come to equilibrium with the spin reservoir. The cost of erasing 1 bit of memory is shown to be the angular momentum expended in the controlled operations. In principle there is no energy cost. We then apply this erasure mechanism to the Maxwell's demon problem. Imagine the demon is using the hot molecules of a thermal gas to produce mechanical work and we want to erase the demon's memory. If another thermal reservoir is used for the erasure, the associated energy cost will be greater than the mechanical work extracted by the demon [2]. However, we can avoid this energy cost by using the spin-reservoir erasure mechanism. In principle, all the heat can be extracted from the thermal reservoir as mechanical work for zero energy cost. The second law of thermodynamics and energy conservation are not violated by this process. The cost is in terms of angular momentum expended and an increase in the entropy of the spin reservoir. Moreover, the entropy of the whole system is increased in the process. [1] R. Landauer, IBM J. Res. Lett., 67 661 (1961). [2] C.H. Bennett, Int. J. Theor. Phys. 21, 905 (1982).
Quantum state engineering and quantum computation rely on information erasure procedures that, up to some fidelity, prepare a quantum object in a pure state. Such processes occur within Landauer's framework if they rely on an interaction between the object and a thermal reservoir. Landauer's principle dictates that this must dissipate a minimum quantity of heat, proportional to the entropy reduction that is incurred by the object, to the thermal reservoir. However, this lower bound is only reachable for some specific physical situations, and it is not necessarily achievable for any given reservoir. The main task of our work can be stated as the minimisation of heat dissipation given probabilistic information erasure, i.e., minimising the amount of energy transferred to the thermal reservoir as heat if we require that the probability of preparing the object in a specific pure state | φ 1 ⟩ be no smaller than p φ 1 max − δ . Here p φ 1 max is the maximum probability of information erasure that is permissible by the physical context, and δ ⩾ 0 the error. To determine the achievable minimal heat dissipation of quantum information erasure within a given physical context, we explicitly optimise over all possible unitary operators that act on the composite system of object and reservoir. Specifically, we characterise the equivalence class of such optimal unitary operators, using tools from majorisation theory, when we are restricted to finite-dimensional Hilbert spaces. Furthermore, we discuss how pure state preparation processes could be achieved with a smaller heat cost than Landauer's limit, by operating outside of Landauer's framework.
The Landauer's principle, a cornerstone of information thermodynamics, provides a fundamental lower bound on the energetic cost of information erasure in terms of the information content change. However, its traditional formulation is largely confined to systems exchanging solely energy with an ideal thermal bath. In this work, we derive general information-cost trade-off relations that go beyond the scope of Landauer's principle by developing a thermodynamic inference approach based on the maximum entropy principle. These relations require only information about the system and are applicable to complex quantum scenarios involving multiple conserved charges and non-thermal environments. Specifically, we present two key results: (i) In scenarios where only the mean values of observables are accessible, we derive an information-content-informed upper bound on the thermodynamic cost which complements an existing generalized Landauer lower bound. (ii) When second-order fluctuations can also be measured, we obtain an information-content-informed lower bound on the change in variances of observables, thereby extending the Landauer's principle to constrain higher-order fluctuation costs. We numerically validate our information-cost trade-off relations using a coupled-qubit system exchanging energy and excitations, a driven qubit implementing an information erasure process, and a driven double quantum dot system that can operate as an inelastic heat engine. Our results underscore the broad utility of maximum-entropy inference in constraining thermodynamic costs for generic finite-time quantum processes, with direct relevance to quantum information processing and quantum thermodynamic applications.
Quantum complexity measures the difficulty of realizing a quantum process, such as preparing a state or implementing a unitary. We present an approach to quantifying the thermodynamic resources required to implement a process if the process’s complexity is restricted. We focus on the prototypical task of information erasure, or Landauer erasure, wherein an n -qubit memory is reset to the all-zero state. We show that the minimum thermodynamic work required to reset an arbitrary state in our model, via a complexity-constrained process, is quantified by the state’s . The complexity entropy therefore quantifies a trade-off between the work cost and complexity cost of resetting a state. If the qubits have a nontrivial (but product) Hamiltonian, the optimal work cost is determined by the . The complexity entropy quantifies the amount of randomness a system appears to have to a computationally limited observer. Similarly, the complexity relative entropy quantifies such an observer’s ability to distinguish two states. We prove elementary properties of the complexity (relative) entropy. In a random circuit—a simple model for quantum chaotic dynamics—the complexity entropy transitions from zero to its maximal value around the time corresponding to the observer’s computational-power limit. Also, we identify information-theoretic applications of the complexity entropy. The complexity entropy quantifies the resources required for data compression if the compression algorithm must use a restricted number of gates. We further introduce a , which arises naturally in a complexity-constrained variant of information-theoretic decoupling. Assuming that this entropy obeys a conjectured chain rule, we show that the entropy bounds the number of qubits that one can decouple from a reference system, as judged by a computationally bounded referee. Overall, our framework extends the resource-theoretic approach to thermodynamics to integrate a notion of , as quantified by .
The minimum amount of thermodynamic work required in order to implement a quantum computation or a quantum state transformation can be quantified using frameworks based on the resource theory of thermodynamics, deeply rooted in the works of Landauer and Bennett. For instance, the work we need to invest in order to implement n independent and identically distributed (i.i.d.) copies of a quantum channel is quantified by the thermodynamic capacity of the channel when we require the implementation's accuracy to be guaranteed in diamond norm over the n-system input. Recent work showed that work extraction can be implemented universally, meaning the same implementation works for a large class of input states, while achieving a variable work cost that is optimal for each individual i.i.d. input state. Here, we revisit some techniques leading to derivation of the thermodynamic capacity, and leverage them to construct a thermodynamic implementation of n i.i.d. copies of any time-covariant quantum channel, up to some process decoherence that is necessary because the implementation reveals the amount of consumed work. The protocol uses so-called thermal operations and achieves the optimal per-input work cost for any i.i.d. input state; it relies on the conditional erasure protocol in our earlier work, adjusted to yield variable work. We discuss the effect of the work-cost decoherence. While it can significantly corrupt the correlations between the output state and any reference system, we show that for any time-covariant i.i.d. input state, the state on the output system faithfully reproduces that of the desired process to be implemented. As an immediate consequence of our results, we recover recent results for optimal work extraction from i.i.d. states up to the error scaling and implementation specifics, and propose an optimal preparation protocol for time-covariant i.i.d. states.
The Landauer principle states that any logically irreversible information processing must be accompanied by dissipation into the environment. In this Letter, we investigate the heat dissipation associated with finite-time information erasure and the effect of quantum coherence in such processes. By considering a scenario wherein information is encoded in an open quantum system whose dynamics are described by the Markovian Lindblad equation, we show that the dissipated heat is lower bounded by the conventional Landauer cost, as well as a correction term inversely proportional to the operational time. To clarify the relation between quantum coherence and dissipation, we derive a lower bound for heat dissipation in terms of quantum coherence. This bound quantitatively implies that the creation of quantum coherence in the energy eigenbasis during the erasure process inevitably leads to additional heat costs. The obtained bounds hold for arbitrary operational time and control protocol. By following an optimal control theory, we numerically present an optimal protocol and illustrate our findings by using a single-qubit system.