We present a method for implementing quantum temperature sensing for extremely low temperatures in a quasi-1D dipolar Bose-Einstein condensate reservoir with a magnetic field-driven impurity atom acting as a quantum sensor. By analyzing the quantum signal-to-noise ratio (QSNR) as a metric for temperature sensing performance, we demonstrate that the presence of an attractive dipolar interaction in the reservoir, which includes the effects of non-Markovian dynamics on the sensor, significantly enhances estimation efficiency. We also investigate the steady-state estimation efficiency for long-encoding times through an analytical expression, which shows that the optimal QSNR depends on the driving magnetic field of the impurity atom. Our method can achieve high-efficiency temperature sensing for any low temperature by tuning the magnetic field. These findings suggest that our approach has potential applications in high-resolution quantum thermometry.
We investigate the quantum sensing performance of a dephasing qubit as a probe in Ohmic environments, characterized by the coupling strength
η, the Ohmicity parameter
s, and the cutoff frequency
ωc to be estimated. The performance is quantified by the dimensionless quantum signal-to-noise ratio
Q. We show that the evolution of
Q with the scaled time
ωct is independent of
ωc, and peaks at an optimal time
topt, yielding optimal sensitivity
Qopt. We analyze how
Qopt depends on
η,
s and the temperature
T. Our results demonstrate that, for any Ohmic environment, provided that
ωctopt≪1,
Qopt always reaches the upper bound:
Qmax=0.648 at zero temperature, and consistently attains
Qmax/4 at high temperatures. Remarkably, we find that increasing the scaled temperature
T/ωc can enhance
Qopt by nearly two orders of magnitude compared to its zero-temperature counterpart for certain Ohmic environments. Our work reveals that temperature can serve as a resource to enhance sensing precision, as it accelerates the encoding of the cutoff frequency information into the probe state, thereby enabling optimal measurement within a short time window.
Accurate measurement at low temperatures is essential for both gaining a fundamental understanding of physical processes and developing technological applications. In this paper, we propose a theoretical framework for quantum temperature sensing in a composite environment with non-Markovian dynamics. Our suggested system uses a single qubit as a temperature sensor to test its sensitivity in calculating the temperature of a composite environment. We show that the temperature sensor's sensitivity can saturate the quantum Cramér-Rao bound by measuring the σ[over ̂]_{z} observable of the probe qubit. Temperature sensing performance is measured using the quantum signal-to-noise ratio. We underline how non-Markovianity can enhance the performance of our thermometers. Furthermore, we emphasize that nonequilibrium conditions do not always result in the best sensitivities in temperature estimation.
We explore the impact of spatial separation between two sensor qubits on quantum sensing performance within a quasi-one-dimensional Bose-Einstein condensate reservoir. By analyzing the quantum Fisher information and quantum signal-to-noise ratio for sensor qubits initialized in both entangled and product states, we reveal distinct behaviors in estimating key reservoir parameters, including spectral density coupling strength and temperature. For coupling strength estimation, smaller spatial distances between the sensor qubits enhance sensing precision. In contrast, for temperature sensing, the spatial separation emerges as a valuable resource, enabling significant improvements in estimation accuracy. Additionally, we discover that product states may outperform entangled states for parameter estimation in quantum reservoir sensing. These findings provide insights into leveraging spatial configurations and state initialization for optimizing quantum sensing protocols in quantum reservoirs.
Quantum thermometry based on single-qubit sensor configurations enables the precise estimation of the temperature of a cosmological Anti-de Sitter (AdS) spacetime. In this work, we characterize the achievable estimation accuracy using the Quantum Fisher Information (QFI) and the associated quantum signal-to-noise ratio. For the first time, we introduce an ancillary Unruh-DeWitt detector between the sensor and the thermal bath, enhancing thermometric sensitivity by channeling temperature-dependent information into the probe qubit's coherence. We examine how detector acceleration in AdS space and the choice of boundary conditions modify the probe's thermal sensitivity. Despite the differing geometries, a unified phenomenology emerges: we characterize the scaling of the QFI with respect to temperature, detector energy gap, spacetime curvature, and interaction time. Finally, we identify optimal state preparation and measurement strategies that maximize the QFI, thereby establishing the fundamental limits of precision for non-Markovian sensing in curved spacetime.
Quantum impurities interacting with quantum environments offer unique insights into many-body systems. Here, we explore the thermometric potential of a neutral impurity immersed in a harmonically trapped bosonic quantum gas below the Bose-Einstein condensation critical temperature
Tc. Using ab-initio Path Integral Monte Carlo simulations at finite temperatures, we analyze the impurity's sensitivity to temperature changes by exploiting experimentally accessible observables such as its spatial distribution. Our results, covering a temperature range of
−1.1⩽T/Tc⩽0.9, reveal that the impurity outperforms estimations based on a one-species bath at lower temperatures, achieving relative precision of 3-4\% for 1000 measurement repetitions. While non-zero boson-impurity interaction strength
gBI slightly reduces the accuracy, the impurity's performance remains robust, especially in the low-temperature regime
T/Tc≲0.45 withing the analyzed interaction strengths
0⩽gBI/g⩽5, where
g is the boson-boson coupling. We confirm that quantum optical models can capture rather well the dependence of the temperature sensor on the impurity-gas interaction. Although our findings are in qualitative agreement with previous studies, our Monte Carlo simulations offer improved precision. We find that the maximum likelihood estimation protocol approaches the precision comparable to the limit set by the Quantum Fisher Information bound. Finally, using the Hellinger distance method, we directly extract the Fisher information and find that, by exploiting the extremum order statistics, impurities far from the trap center are more sensitive to thermal effects than those close to the trap center.