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One of the key questions in quantum information is the preparation of desired multipartite quantum states with high fidelity. Adiabatic evolution has been widely explored to achieve state preparation in quantum many-body systems. However, in noisy quantum systems, the adiabatic approach faces a dilemma: either extending the evolution timescales to reduce diabatic transitions or shortening the timescales to mitigate decoherence effects. Various quantum control approaches have been studied to resolve this dilemma. In a few recent works, we utilized Jaynes-Cummings (JC) lattices as a platform to investigate the potential of several quantum control techniques in preparing quantum many-body states, including the optimized adiabatic evolution approach, the quantum optimal control technique, and quantum shortcuts to adiabaticity. Here we first give an overview of our previous results on utilizing quantum optimal control in JC lattices with unit filling and utilizing local counterdiabatic driving in JC lattices with a single excitation. Then we present our results on the energy costs and energy fluctuations in these approaches. Our studies give insights into the implementation of different approaches in practical quantum devices and the connection between the energy costs and the quantum speed limit in preparing desired quantum many-body states for quantum simulation and quantum computation. 

Abstract High-fidelity preparation of quantum states in an interacting many-body system is often hindered by the lack of knowledge of such states and by limited decoherence times. Here, we study a quantum optimal control (QOC) approach for fast generation of quantum ground states in a finite-sized Jaynes-Cummings lattice with unit filling. Our result shows that the QOC approach can generate quantum many-body states with high fidelity when the evolution time is above a threshold time, and it can significantly outperform the adiabatic approach. We study the dependence of the threshold time on the parameter constraints and the connection of the threshold time with the quantum speed limit. We also show that the QOC approach can be robust against control errors. Our result can lead to advances in the application of the QOC to many-body state preparation. 

The human brain represents one of the most complex biological systems, containing billions of neurons interconnected through trillions of synapses. Inherent to the brain is a biochemical complexity involving ions, signaling molecules, and peptides that regulate neuronal activity and allow for short- and long-term adaptations. Large-scale and noninvasive imaging techniques, such as fMRI and EEG, have highlighted brain regions involved in specific functions and visualized connections between different brain areas. A major shortcoming, however, is the need for more information on specific cell types and neurotransmitters involved, as well as poor spatial and temporal resolution. Recent technologies have been advanced for neuronal circuit mapping and implemented in behaving model organisms to address this. Here, we highlight strategies for targeting specific neuronal subtypes, identifying, and releasing signaling molecules, controlling gene expression, and monitoring neuronal circuits in real-timein vivo. Combined, these approaches allow us to establish direct causal links from genes and molecules to the systems level and ultimately to cognitive processes. 

Anxiety disorders are a major public health concern and current treatments are inadequate for many individuals. Anxiety is more common in women than men and this difference arises during puberty. Sex differences in physiological stress responses may contribute to this variability. During puberty, gonadal hormones shape brain structure and function, but the extent to which these changes affect stress sensitivity is unknown. We examined how pubertal androgens shape behavioral and neural responses to social stress in California mice (Peromyscus californicus), a model species for studying sex differences in stress responses. In adults, social defeat reduces social approach and increases social vigilance in females but not males. We show this sex difference is absent in juveniles, and that prepubertal castration sensitizes adult males to social defeat. Adult gonadectomy does not alter behavioral responses to defeat, indicating that gonadal hormones act during puberty to program behavioral responses to stress in adulthood. Calcium imaging in the medioventral bed nucleus of the stria terminalis (BNST) showed that social threats increased neural activity and that prepubertal castration generalized these responses to less threatening social contexts. These results support recent hypotheses that the BNST responds to immediate threats. Prepubertal treatment with the nonaromatizable androgen dihydrotestosterone acts in males and females to reduce the effects of defeat on social approach and vigilance in adults. These data indicate that activation of androgen receptors during puberty is critical for programming behavioral responses to stress in adulthood. 

Abstract Strongly correlated polaritons in Jaynes–Cummings (JC) lattices can exhibit quantum phase transitions between the Mott-insulating and superfluid phases at integer fillings. The prerequisite to observe such phase transitions is to pump polariton excitations into a JC lattice and prepare them into appropriate ground states. Despite previous efforts, it is still challenging to generate many-body states with high accuracy. Here, we present an approach for the robust preparation of many-body ground states of polaritons in finite-sized JC lattices by optimized nonlinear ramping. We apply a Landau–Zener type of estimation to this finite-sized system and derive the optimal ramping index for selected ramping trajectories, which can greatly improve the fidelity of the prepared states. With numerical simulation, we show that by choosing an appropriate ramping trajectory, the fidelity in this approach can remain close to unity in almost the entire parameter space. This approach can shed light on high-fidelity state preparation in quantum simulators and advance the implementation of quantum simulation with practical devices.