arXiv subjects

Tan-Ji Zhou

Publications and source records attributed to Tan-Ji Zhou.

4 recordsLinked to original sources

arXiv2026

Carnot Meets Quantum Information: Thermal Machine Driven by Probabilistic Non-orthogonal State Discrimination

While the impossibility of perfectly identifying non-orthogonal states is a cornerstone of quantum information science, their probabilistic discrimination is nonetheless permissible. Here, we propose a two-reservoir quantum machine driven by this mechanism to map its functional boundaries across the parameter space of the state overlap $μ$ and the Carnot efficiency $η_C$. Within this $η_C$-$μ$ plane, the machine exhibits phase-transition-like functional switching among a pure heat-engine phase, a mixed phase, and a dissipative phase. We identify critical thresholds governing these transitions: strong thermal driving ($η_C \ge 0.5$) unconditionally guarantees positive work extraction, whereas weak driving ($η_C \lesssim 0.13$) induces an anomalous reentrant transition, where increasing $μ$ unexpectedly restores engine functionality after a purely dissipative regime. Our results explicitly demonstrate how quantum mechanics and thermodynamics jointly constrain information-to-energy conversion.

quant-ph↗

arXiv2026

Reliability-Safety Trade-off in AI Distillation: A Renormalization-Group Approach

Knowledge distillation transfers more than task competence: it also transmits response propensities, refusal policies, error boundaries, and latent safety biases. We formulate this behavioral inheritance as a coarse-graining model grounded in statistical mechanics, in which the student's answer and refusal decisions define two macrostates, while the teacher induces an effective field that reshapes the student's free-energy landscape. The model yields a reliability-safety trade-off relation controlled by a single parameter K, which we term the hazard discrimination capability. The predicted trade-off is consistent with refusal-token data [arXiv: 2412.06748]. In knowledge distillation, a teacher with strong hazard discrimination improves the student's attainable reliability and safety, whereas poor discrimination limits the attainable trade-off. Repeated distillation acts as an iterated renormalization-group-like transformation, under which K follows a flow across generations. The flow exhibits a tricritical structure separating regimes of K loss, stable transmission, and threshold-dependent inheritance, and yields testable scaling predictions for multigenerational distillation.

cond-mat.stat-mech↗

arXiv2026

Adverse Selection with Quality Variance: A Maximum-Entropy Approach

The adverse-selection mechanism in markets explains how asymmetric information between buyers and sellers can drive high-quality goods out of the market, thereby causing market deterioration. In its simplest formulation, only the mean quality is used to describe the market, and this is insufficient to determine how fast the market deteriorates or how the quality distribution evolves. To resolve the two problems, we describe the adverse selection as a dynamic truncation of the quality distribution: buyers set an upper bound proportional to the mean quality by a rate $ξ$ that is larger than unity, and sellers whose quality exceeds this upper bound reject an offer and exit the market. The retained market is then characterized by the conditional distribution obtained after this truncation, and the corresponding evolution process is iterated until market quality reaches a stable state. This statistical approach gives three results. (i) We identify a mechanism for preventing complete adverse selection, defined as the process where the quality of the market is driven down to the minimum quality floor. (ii) A larger quality variance or a smaller price premium, defined as the amount by which the payment upper bound exceeds the current mean quality, raises the upper bound on the deterioration in mean quality. (iii) A maximum-entropy benchmark shows numerically how quality variance and the payment rate jointly determine market deterioration and the final stable quality platform. This approach also clarifies how market interventions can slow adverse selection: they may raise buyers' payment rate, reduce quality variance, or increase the minimum quality floor.

cond-mat.stat-mech↗

arXiv2023

Finite-Time Optimization of Quantum Szilard heat engine

We propose a finite-time quantum Szilard engine (QSE) with a quantum particle with spin as the working substance (WS) to accelerate the operation of information engines. We introduce a Maxwell's demon (MD) to probe the spin state within a finite measurement time $t_{\rm M}$ to capture the which-way information of the particle, quantified by the mutual information $I(t_{\rm{M}})$ between WS and MD. We establish that the efficiency $η$ of QSE is bounded by $η\leq1-(1-η_{\rm{C}}){\rm ln}2/I(t_{\rm M})$, where $I(t_{\rm M})/\rm{ln}2$ characterizes the ideality of quantum measurement, and approaches $1$ for the Carnot efficiency reached under ideal measurement in quasi-static regime. We find that the power of QSE scales as $P\propto t_{\rm M}^{3}$ in the short-time regime and as $P\propto t_{\rm M}^{-1}$ in the long-time regime. Additionally, considering the energy cost for erasing the MD's memory required by Landauer's principle, there exists a threshold time that guarantees QSE to output positive work.

quant-ph↗