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We characterise the measurement sensitivity, quantified by the quantum Fisher information (QFI), of a single-fermionic thermometric probe strongly coupled to the sample of interest, a fermionic bath, at temperature T . For nonequilibrium protocols, in which the probe is measured before reaching equilibrium with the sample, we find new behaviour of the measurement sensitivity arising due to non-Markovian dynamics. First, we show that the QFI displays a highly non-monotonic behaviour in time, in contrast to the Markovian case where it grows monotonically until equilibrium, so that non-Markovian revivals can be exploited to reach a higher QFI. Second, the QFI rate is maximised at a finite interrogation time t ∗ , which we characterize, in contrast to the solution t ∗ → 0 known in the Markovian limit (Pavel Sekatski and Martí Perarnau-Llobet 2022 Quantum 6 869). Finally, we consider probes make up of few fermions and discuss different collective enhancements in the measurement precision.

We provide new operational significance of nonclassicality in nonequilibrium temperature estimation of bosonic baths with Gaussian probe states and Gaussian dynamics. We find a bound on the thermometry performance using classical probe states. Then we show that by using nonclassical probe states, single-mode and two-mode squeezed vacuum states, one can profoundly improve the classical limit. Interestingly, we observe that this improvement can also be achieved by using Gaussian measurements. Hence, we propose a fully Gaussian protocol for enhanced thermometry, which can simply be realized and used in quantum optics platforms.

The performances of quantum thermometry in thermal equilibrium together with the output power of certain class of quantum engines share a common characteristic: both are determined by the heat capacity of the probe or working medium. After noticing that the heat capacity of spin ensembles can be significantly modified by collective coupling with a thermal bath, we build on the above observation to investigate the respective impact of such collective effect on quantum thermometry and quantum engines. We find that the precision of the temperature estimation is largely increased at high temperatures, reaching even the Heisenberg scaling-inversely proportional to the number of spins. For Otto engines operating close to the Carnot efficiency, collective coupling always enhances the output power. Some tangible experimental platforms are suggested.

The precise knowledge of the temperature of an ultracold lattice gas simulating a strongly correlated system is a question of both fundamental and technological importance. Here, we address such question by combining tools from quantum metrology together with the study of the quantum correlations embedded in the system at finite temperatures. Within this frame we examine the spin- XY chain, first estimating, by means of the quantum Fisher information, the lowest attainable bound on the temperature precision. We then address the estimation of the temperature of the sample from the analysis of correlations using a quantum non demolishing Faraday spectroscopy method. Remarkably, our results show that the collective quantum correlations can become optimal observables to accurately estimate the temperature of our model in a given range of temperatures.

We extend collisional quantum thermometry schemes to allow for stochasticity in the waiting time between successive collisions. We establish that introducing randomness through a suitable waiting time distribution, the Weibull distribution, allows us to significantly extend the parameter range for which an advantage over the thermal Fisher information is attained. These results are explicitly demonstrated for dephasing interactions and also hold for partial swap interactions. Furthermore, we show that the optimal measurements can be performed locally, thus implying that genuine quantum correlations do not play a role in achieving this advantage. We explicitly confirm this by examining the correlation properties for the deterministic collisional model.

Temperature estimation plays a vital role across natural sciences. A standard approach is provided by probe thermometry, where a probe is brought into contact with the sample and examined after a certain amount of time has passed. In situations where, for example, preparation of the probe is non-trivial or total measurement time of the experiment is the main resource that must be optimized, continuously monitoring the probe may be preferred. Here, we consider a minimal model, where the probe is provided by a two-level system coupled to a thermal reservoir. Monitoring thermally activated transitions enables real-time estimation of temperature with increasing accuracy over time. Within this framework we comprehensively investigate thermometry in both bosonic and fermionic environments employing a Bayesian approach. Furthermore, we explore adaptive strategies and find a significant improvement on the precision. Additionally, we examine the impact of noise and find that adaptive strategies may suffer more than non-adaptive ones for short observation times. While our main focus is on thermometry, our results are easily extended to the estimation of other environmental parameters, such as chemical potentials and transition rates.

We propose a scheme to enhance the range and precision of ultra-low temperature measurements by employing a probe qubit coupled to a chain of ancilla qubits. Specifically, we analyze a qubit chain governed by Heisenberg XX and Dzyaloshinskii–Moriya (DM) interactions. The precision limits of temperature measurements are characterized by evaluating quantum Fisher information (QFI). Our findings demonstrate that the achievable precision bounds, as well as the number of peaks in the QFI as a function of temperature, can be controlled by adjusting the number of ancilla qubits and the system’s model parameters. These results are interpreted in terms of the influence of energy transitions on the range and the number of QFI peaks as a function of temperature. This study highlights the potential of the probe qubit–ancilla chain system as a powerful and precise tool for quantum thermometry in the ultra-low temperature regime.

Homeostasis, which supports and maintains brain function, results from the continuous regulation of thermodynamics within tissue: the balance of heat production, redox oscillations, and vascular convection regulates coherent energy flow within the organ. Neuroinflammation disturbs this balance, creating measurable entropy gradients that precede structural damage to its tissue components. This paper proposes that a thermodynamic unity can be devised that incorporates nanoscale physics, energetic neurophysiology, and systems neuroscience, and can be used to understand and treat neuroinflammatory processes. Using multifactorial modalities such as quantum thermometry, nanoscale calorimetry, and redox oscillometry we define how local entropy production (st), relaxation time (τR), and coherence lengths (λc) allow quantification of the progressive loss of energetic symmetry within neural tissues. It is these variables that provide the basis for the etiology of thermodynamic biomarkers which on a molecular-redox-to-network scale characterize the transitions governing the onset of the neuroinflammatory process as well as the recovery potential of the organism. The entropic probing of systems (PEP) further allows the translation of these parameters into dynamic patient-specific trajectories that model the behavior of individuals by predicting recurrent bouts of instability through the application of machine learning algorithms to the vectors of entropy flux. The parallel development of the nanothermodynamic intervention, which includes thermoplasmonic heat rebalancing, catalytic redox nanoreacting systems, and adaptive field-oscillation synchronicity, shows by example how the corrections that can be applied to the entropy balance of the cell and system as a whole offer a feasible form of restoration of energy coherence. Such closed loop therapy would not function by the suppression of inflammatory signaling, but rather by the re-establishment of reversible energy relations between mitochondrial, glial, and vascular territories. The combination of these factors allows for correction of neuroinflammation, which can now be viewed from a fresh perspective as a dynamic phase disorder that is diagnosable, predictable, and curable through the physics of coherence rather than the molecular suppression of inflammatory signaling. The significance of this set of ideas is considerable as it introduces a feasible and verifiable structure to what must ultimately become the basis of a new branch of science: predictive energetic medicine. It is anticipated that entropy, as a measurable and modifiable variable in therapeutic “inscription”, will be found to be one of the most significant parameters determining the neurorestoration potential in future medical science.

We have developed a novel nanoscale temperature-measurement method using fluorescence in the near-field called Fluorescence Near-field Optics Thermal Nanoscopy (Fluor-NOTN). Fluor-NOTN enables the temperature distributions of nanoscale materials to be measured in vivo/in situ. The proposed method measures temperature by detecting the temperature dependent fluorescence lifetimes of Cd/Se Quantum Dots (QDs). For a high-sensitivity temperature measurement, the auto-fluorescence generated from a fiber probe should be reduced. In order to decrease the noise, we have fabricated a novel near-field optical-fiber probe by fusion-splicing a photonic crystal fiber (PCF) and a conventional single-mode fiber (SMF). The validity of the novel fiber probe was assessed experimentally by evaluating the auto-fluorescence spectra of the PCF. Due to the decrease of auto-fluorescence, a six- to ten-fold increase of S/N in the near-field fluorescence lifetime detection was achieved with the newly fabricated fusion-spliced near-field optical fiber probe. Additionally, the near-field fluorescence lifetime of the quantum dots was successfully measured by the fabricated fusion-spliced near-field optical fiber probe at room temperature, and was estimated to be 10.0 ns.

Understanding the coordination of cell-division timing is one of the outstanding questions in the field of developmental biology. One active control parameter of the cell-cycle duration is temperature, as it can accelerate or decelerate the rate of biochemical reactions. However, controlled experiments at the cellular scale are challenging, due to the limited availability of biocompatible temperature sensors, as well as the lack of practical methods to systematically control local temperatures and cellular dynamics. Here, we demonstrate a method to probe and control the cell-division timing in Caenorhabditis elegans embryos using a combination of local laser heating and nanoscale thermometry. Local infrared laser illumination produces a temperature gradient across the embryo, which is precisely measured by in vivo nanoscale thermometry using quantum defects in nanodiamonds. These techniques enable selective, controlled acceleration of the cell divisions, even enabling an inversion of division order at the two-cell stage. Our data suggest that the cell-cycle timing asynchrony of the early embryonic development in C. elegans is determined independently by individual cells rather than via cell-to-cell communication. Our method can be used to control the development of multicellular organisms and to provide insights into the regulation of cell-division timings as a consequence of local perturbations.