The standard Landauer bound W≥kBTln2 sets the fundamental thermodynamic cost for information erasure under ideal conditions: weak system-bath coupling, quasistatic operation, and equilibrium reservoirs. However, realistic quantum error correction (QEC) operates in a profoundly different regime-finite-time syndrome extraction, strong coupling to cryogenic environments, and non-equilibrium dynamics. Here, we develop a unified thermodynamic framework for fault-tolerant quantum computing that incorporates corrections beyond the ideal Landauer limit. We derive a generalized bound on the heat dissipation per QEC cycle: Qmin≥kBTln2+kBTΔISB+ℏτ, and scaling this result to large-scale quantum computers, we find that the total heat load grows polynomially with code distance but remains in the nanowatt range for million-qubit systems-well within the cooling power of modern dilution refrigerators. Applying our model to superconducting qubit architectures, we show that while strong coupling can add up to ∼20% to the ideal cost, finite-time effects contribute approximately 0.55% at 100 ns and 5.5% at 10 ns reset operations. Our results establish that the true thermodynamic cost of fault tolerance, while exceeding the naive Landauer estimate, does not pose a fundamental obstacle to scalability; the dominant engineering challenges lie in the heat load of control electronics and wiring, not in the fundamental dissipation of qubit reset.
The standard Landauer bound W≥kBTln2 sets the fundamental thermodynamic cost for information erasure under ideal conditions: weak system-bath coupling, quasistatic operation, and equilibrium reservoirs. However, realistic quantum error correction (QEC) operates in a profoundly different regime-finite-time syndrome extraction, strong coupling to cryogenic environments, and non-equilibrium dynamics. Here, we develop a unified thermodynamic framework for fault-tolerant quantum computing that incorporates corrections beyond the ideal Landauer limit. We derive a generalized bound on the heat dissipation per QEC cycle: Qmin≥kBTln2+kBTΔISB+ℏτ, and scaling this result to large-scale quantum computers, we find that the total heat load grows polynomially with code distance but remains in the nanowatt range for million-qubit systems-well within the cooling power of modern dilution refrigerators. Applying our model to superconducting qubit architectures, we show that while strong coupling can add up to ∼20% to the ideal cost, finite-time effects contribute approximately 0.55% at 100 ns and 5.5% at 10 ns reset operations. Our results establish that the true thermodynamic cost of fault tolerance, while exceeding the naive Landauer estimate, does not pose a fundamental obstacle to scalability; the dominant engineering challenges lie in the heat load of control electronics and wiring, not in the fundamental dissipation of qubit reset.
Thermodynamic trade-off relations dictate fundamental limits on the performance of thermodynamic tasks through costs such as heat dissipation. Here, we propose a framework called thermodynamic recycling to circumvent these limits in quantum processors by exploiting failure branches of quantum algorithms, which are usually discarded. The key component is an athermal bath naturally generated during the resetting of a failure branch. By coupling this bath to a target system prior to relaxation, thermodynamic tasks can be performed beyond conventional thermodynamic limits. We apply this framework to information erasure and derive the reduction in heat dissipation analytically. As a demonstration, we implement our framework on IBM's superconducting quantum processor by combining the Harrow--Hassidim--Lloyd algorithm with three-qubit quantum error correction, thereby reducing the heat dissipated in erasing syndrome information. Despite substantial noise and errors in current hardware, our method achieves erasure with heat dissipation below the Landauer limit. This work establishes an operational connection between quantum computing and quantum thermodynamics for resource-efficient quantum computation.
We investigate the thermodynamic limits on scaling fault-tolerant quantum computers due to heating from quantum error correction (QEC). Quantum computers require error correction, which accounts for 99.9% of the qubit demand and generates heat through information-erasing processes. This heating increases the error rate, necessitating more rounds of error correction. We introduce a dynamical model that characterizes heat generation and dissipation for arrays of qubits weakly coupled to a refrigerator and identify a dynamical phase transition between two operational regimes: a bounded-error phase, where temperature stabilizes and error rates remain below fault-tolerance thresholds, and an unbounded-error phase, where rising temperatures drive error rates beyond sustainable levels, making fault tolerance infeasible. Applying our model to a superconducting qubit system performing Shor's algorithm to factor 2048-bit RSA integers, we find that current experimental parameters place the system in the bounded-error phase. Our results indicate that, while inherent heating can become significant, this thermodynamic constraint should not limit scalable fault tolerance if current hardware capabilities are maintained as systems scale.
Fault-tolerant quantum computation relies on continuous error-correcting processes to preserve logical identity over time. While fault-tolerance threshold theorems bound logical error rates per operation, the thermodynamic cost of sustaining quantum identity under ongoing maintenance has not been explicitly isolated. In this work, we show that any fault-tolerant quantum system that preserves logical identity through active error correction must dissipate heat at a rate bounded below by the irreversible information processed during syndrome extraction and reset. As a consequence, at fixed temperature and cooling power, there exists an upper bound on the sustained throughput of fault-tolerant quantum identity, independent of code family, decoding strategy, or physical noise model. The result establishes a fundamental persistence–dissipation constraint arising from irreversible maintenance rather than from quantum dynamics themselves. This work is intentionally descriptive and non-operational, identifying a structural thermodynamic bound without proposing mechanisms, architectures, or control strategies.
Quantum error correction (QEC) is widely regarded as the indispensable cornerstone for achieving scalable, fault-tolerant quantum computation. However, conventional fault-tolerance theorems traditionally rely on abstract circuit models that frequently abstract away fundamental physical laws, treating noise channels and error syndromes as purely mathematical parameters. In this paper, we establish the Physical Limit of Quantum Error Correction (PLQEC) framework, investigating whether there exists an absolute, nature-imposed lower bound on the residual error probability, denoted as p_min, below which reliable quantum information preservation becomes physically unattainable due to deeply rooted thermodynamic, informational, and spacetime constraints. By systematically integrating Landauer's principle, von Neumann entropy bounds, the intrinsic thermodynamics of quantum measurement, and holographic gravity principles, we derive universal fundamental limits on quantum error correction thresholds. We demonstrate that physical constraints such as minimal energy dissipation per syndrome extraction cycle, quantum speed limits, decoherence velocities, and spacetime curvature cutoffs impose strict, unyielding boundaries on fault-tolerant quantum architectures. This work bridges the profound gap between abstract quantum information theory and fundamental physical law, opening a new frontier in understanding the ultimate operational boundaries of quantum information processing in our physical universe.
Semiconductor spin qubits offer a promising route to compact and scalable quantum computers, combining long coherence times in isotopically purified silicon with compatibility with semiconductor manufacturing. Beyond computational speedup, their energy efficiency is an important consideration for future large-scale systems. We evaluate the power and energy requirements of a Loss-DiVincenzo spin-qubit quantum computer by analyzing the Quantum Fourier Transform (QFT) and benchmarking it against the classical Fast Fourier Transform (FFT). We develop a detailed energy budget, identifying cryogenic cooling as the dominant baseline contribution before quantum error correction (QEC). The comparison between the QFT and the classical FFT reveals that, for any quantum workload operating under a polynomially bounded sampling regime, the crossover in energy consumption occurs at smaller problem sizes than the crossover in execution time. Thus, quantum computing can become energetically competitive before achieving a speedup in execution time. We then incorporate surface-code QEC and analyze the energy costs of QEC cycles, gate synthesis, and decoding. At scale, instrumentation and decoding become dominant contributions, while cryogenic cooling imposes a constraint on scalability. We show that optimizing the control-signal demultiplexing ratio can reduce the overall energy cost by approximately two orders of magnitude. For a system with about one million physical qubits, we estimate a power consumption of approximately 100 kW, at least one order of magnitude below that of today's highest-performance classical computing systems.
The aim of quantum error correction (QEC) is to counteract the decoherence of qubits,which arises from their unavoidable interaction with the environment. In this work, westudy the lower bound of entropy production in quantum error correction, asking the cen-tral question: Is it possible to fight decoherence in a reversible way?A previous work established that ideal quantum error correction can, in principle,be performed reversibly. In this work, however, we consider fault-tolerant quantum errorcorrection, which explicitly accounts for faults occurring during the correction processitself. We show that when noise affects the circuit during the error-correcting operations,quantum error correction can no longer be reversible, because of unused correlations thatmust be dissipated at each correction cycle.This result can be better understood by drawing an analogy with Maxwell’s demon.In quantum error correction, the goal is to remove entropy from the data qubits. Ancillaryqubits are used to record the occurrence of errors (syndrome diagnosis), and this infor-mation is then employed to correct them (recovery operation). At the end of each cycle,the ancillary qubits are reset in order to start a new cycle. This is closely analogous to aMaxwell demon, which uses a memory to store information about a system, exploits thatinformation to reduce the system’s entropy, and finally resets its memory, dissipating heatinto the environment in accordance with Landauer’s principle.In this analogy, the demon’s memory corresponds to the ancillary qubits, while thesystem corresponds to the data qubits. During syndrome diagnosis, information aboutthe errors is recorded in the ancillary qubits, creating some correlations between dataand ancillary qubits. In the recovery operation, these correlations are used to correctthe errors on the data qubits and thus reduce their entropy. At the end of the cycle, theancillary qubits are reset to |0⟩, which generates a heat flow to the environment as dictatedby Landauer’s principle.For ideal quantum error correction, this process can, in principle, be performed re-versibly, thereby reaching equality in Landauer’s bound.However, when errors occur on the ancillary qubits during the QEC process (in the lan-guage of Maxwell’s demon, when faults affect the demon’s memory before the feedbackstep) these errors propagate to the data qubits, creating unwanted correlations betweendata and ancillas. Such correlations generate an additional finite heat flow to the bath,that prevents reaching equality in Landauer’s principle.