Quantum batteries represent a groundbreaking shift in energy storage, utilizing the counterintuitive principles of quantum mechanics to unlock unparalleled performance. By storing energy in the quantum states of atoms and molecules, these devices promise faster charging, higher energy densities, and unprecedented efficiency compared to classical energy storage systems.
 

At the heart of their innovation lies the exploitation of quantum phenomena such as entanglement and superposition. In a quantum battery, entangled particles exhibit interconnected states, enabling them to transition collectively from low to high energy levels with remarkable speed. Superposition further enhances their capabilities, allowing energy to be stored across multiple quantum states simultaneously, dramatically increasing the energy density in compact designs.
 

The transformative potential of quantum batteries becomes even more apparent at scale. As the number of entangled particles increases, the charging process accelerates, defying classical scaling limitations. Intriguingly, research has shown that certain quantum batteries can charge more effectively when powered by weaker energy sources, challenging conventional notions of energy transfer.

Although still in the experimental phase, the implications of quantum batteries are immense. These devices could revolutionize a range of applications, from rapidly charging electric vehicles to powering portable electronics with unmatched efficiency. Beyond consumer technology, they hold potential for renewable energy systems, grid storage, and even space exploration, where compact, high-capacity energy solutions are critical.
 

By harnessing the strange yet powerful principles of quantum mechanics, quantum batteries offer a vision of instant, highly efficient energy storage. While challenges remain in scaling and implementation, ongoing advancements position quantum batteries as a transformative technology capable of reshaping how we store and use energy in the future.

Time Crystals, a novel phase of matter formed through the spontaneous breaking of temporal symmetry, exhibit robust subharmonic oscillations that persist despite imperfections. These unique properties, arising from many-body interactions, collective synchronization, and broken ergodicity, challenge our fundamental understanding of physics and offer promising applications in quantum computing, sensing, and, potentially, energy storage.

Among the different types of time crystals, Discrete Time Crystals (DTCs) arise in periodically driven systems, characterized by subharmonic frequency oscillations. While dissipation can stabilize DTCs in some regimes, incoherent noise can disrupt their long-term temporal order. This dual role of environmental interactions necessitates a deeper understanding of how DTCs respond to decoherence and how their crystalline order can be preserved.

This project focuses on evaluating the fragility of DTCs to a wide range of noise profiles and developing strategies to mitigate the effects of decoherence. Key objectives include:

• Fragility Analysis: Assessing the susceptibility of DTCs to various decoherence mechanisms and noise profiles.
• Mitigation Strategies: Designing and testing innovative protocols to enhance the robustness of DTCs against environmental perturbations.

To achieve these goals, the project employs state-of-the-art computational methodologies, including exact diagonalization for characterizing small systems, tensor networks and density matrix renormalization group (DMRG) techniques for simulating one-dimensional many-body systems, time-dependent variational principle (TDVP) techniques for real-time dynamics, and quantum trajectory methods for modeling open quantum systems under stochastic noise.

By addressing the challenges of decoherence and stabilizing DTCs, this research aims to unlock their potential for practical quantum technological applications, advancing our understanding of non-equilibrium quantum systems.

Quantum sensing harnesses phenomena like superposition and entanglement to achieve unparalleled precision and sensitivity, enabling the detection of magnetic, electric, and gravitational fields with extraordinary accuracy. These advancements hold transformative potential in fields such as metrology, navigation, medical diagnostics, and environmental monitoring, surpassing classical limitations and revolutionizing measurement techniques.

This research focuses on non-reciprocal quantum sensors, which utilize time-reversal symmetry breaking to achieve directional sensitivity and improved signal control. Nonreciprocity enables one-way signal transmission, prevents interference, and enhances signal-to-noise ratios, providing significant advantages over classical sensors. Leveraging effects such as non-Hermitian dynamics and topological protection, non-reciprocal quantum sensors offer selective and sensitive detection capabilities, with promising applications in areas like magnetometry.

A key innovation of this project is the use of parametric driving to realize non-Hermitian dynamics without external dissipation or post-selection. Non-Hermitian Hamiltonians exhibit unique features, such as exceptional points and parity-time symmetry breaking, which can significantly enhance quantum sensing. While current proposals focus on equilibrium systems, this research extends these concepts to non-equilibrium systems, exploring novel regimes of physics and their potential for advanced sensing applications.

To achieve these objectives, the project employs state-of-the-art computational methodologies, including exact diagonalization, tensor networks, and density matrix renormalization techniques. Additionally, the Kibble-Zurek mechanism provides a theoretical framework to study phase transitions, improving resolution and noise resistance in quantum sensors.

By advancing non-reciprocal quantum sensors, this research promises breakthroughs in quantum sensing, addressing both fundamental questions in non-equilibrium physics and practical challenges in measurement and detection technologies.

Quantum sensing, a cornerstone of quantum technologies, offers unparalleled precision and sensitivity beyond classical limits. These sensors hold transformative potential across numerous applications, including energy, mining, biological imaging, space exploration, and environmental monitoring. Achieving quantum-enhanced sensitivity often relies on exploiting unique quantum features like entanglement and superposition, particularly in multi-particle systems.

Traditional approaches have focused on non-interacting particles in maximally entangled states, but challenges such as decoherence and scalability have shifted attention to strongly correlated many-body systems. These systems, with inherent multipartite entanglement, exhibit robustness against imperfections and promise scalable quantum sensing platforms.

This research focuses on non-equilibrium quantum systems, which operate far from thermal equilibrium, offering new regimes of quantum behavior not accessible in equilibrium conditions. A key focus is on Discrete Time Crystals (DTCs), a novel non-equilibrium phase of matter characterized by unique temporal order, robustness to imperfections, and persistent oscillations. These properties make DTCs promising candidates for advanced quantum sensing.

The study aims to explore critical phenomena and phases in non-equilibrium systems, leveraging mechanisms like disorder, domain-wall confinement, and long-range interactions to develop practical DTC-based quantum sensors. To achieve this, we utilize advanced computational methodologies, including exact diagonalization, tensor networks, and the density matrix renormalization group. The Kibble-Zurek mechanism will guide the theoretical framework, enhancing sensor resolution and noise resistance.

This research aims to pioneer new directions in quantum sensing by harnessing non-equilibrium dynamics, contributing to both fundamental understanding and practical advancements in quantum technologies.

Modern imaging techniques, grounded in classical optics principles, have enabled us to explore microscopic structures with remarkable precision and observe objects millions of light-years away. Despite their success, these classical systems face fundamental limitations, prompting the emergence of quantum-based imaging technologies that offer unprecedented capabilities.

At QC2, we are pioneering quantum imaging experiments that harness the principles of quantum mechanics to transcend the boundaries of classical imaging. Unlike traditional methods relying on lasers or LEDs as light sources, our approach uses spatially and temporally entangled photon pairs. These entangled pairs allow information carried by one photon to be inferred from its twin, exploiting non-classical correlations to achieve breakthroughs in imaging performance.

One of the key advantages of our quantum imaging system is enhanced spatial resolution. By illuminating samples with entangled photons, we effectively achieve imaging with half the wavelength of classical light, enabling super-resolution imaging beyond the diffraction limit. Additionally, since entangled photons are generated through weak nonlinear processes, they induce minimal damage to delicate samples—a critical benefit for biological and material sciences.

Our quantum imaging technique extends its benefits to include high sensitivity, enhanced depth resolution, reduced shot noise, and improved signal-to-noise ratios. It also facilitates advanced applications such as ghost imaging, guidestar-free aberration correction, and time-gated imaging techniques like optical coherence tomography (OCT). These features open the door to a wide range of applications, from biomedical diagnostics to precision materials analysis.

By combining state-of-the-art experimental setups with the transformative potential of quantum mechanics, we aim to redefine imaging standards. Our work positions quantum imaging as a vital tool for the next generation of scientific exploration, addressing challenges that classical systems cannot overcome.

This project focuses on advancing quantum technologies in the areas of computation, communication, and sensing, with a particular emphasis on utilizing color centers in diamonds, specifically nitrogen-vacancy (NV) and silicon-vacancy (SiV) centers. These color centers possess unique properties, such as long-lived spin quantum states and spin-dependent optical transitions, which make them highly suitable for a range of quantum applications.

One of the primary goals of the project is to develop highly sensitive quantum sensors using NV centers. These sensors are capable of detecting extremely subtle magnetic fields, electric fields, and temperature variations, with nanoscale resolution. Such capabilities are crucial for applications in fields like navigation, robotics, biology, and nanotechnology, where precise measurements are essential.

In addition to sensing, the project aims to create scalable quantum processors by leveraging the electron and nuclear spins of NV centers. Through the development of sophisticated optical and microwave techniques, we will perform quantum logic operations and implement quantum error correction schemes. The long coherence times of these spin states, particularly in ultrapure diamond samples, enable the preservation of quantum information over extended periods, which is critical for effective quantum computation.

The project also explores the potential of NV centers in quantum communication networks. By functioning as single-photon sources and detectors, NV centers can support quantum key distribution (QKD) protocols and enable the creation of long-distance quantum communication channels. The ability to coherently couple NV centers to photons is essential for implementing quantum teleportation protocols and extending quantum networks.

Our research is supported by state-of-the-art experimental equipment, including a custom-built confocal microscope, which allows us to conduct cutting-edge experiments. By combining the exceptional properties of color centers with innovative quantum techniques, this project seeks to pioneer scalable quantum technologies with transformative applications in quantum computing, sensing, and communication. Additionally, the project will explore hybrid quantum architectures by integrating NV centers with other quantum systems, such as superconducting circuits or trapped ions, to harness the benefits of different quantum technologies.

Large Language Models (LLMs), such as GPT and BERT, have revolutionized natural language processing (NLP), excelling in tasks like translation, summarization, and sentiment analysis. Powered by advanced transformer architectures and trained on vast datasets, these models achieve impressive performance. However, classical machine learning (ML) approaches face inherent limitations when dealing with the high-dimensional, unstructured, and evolving nature of language, often requiring resource-intensive retraining and fine-tuning to maintain performance.

Quantum Machine Learning (QML) offers promising, though still largely exploratory, solutions to these challenges. By leveraging quantum properties such as superposition and entanglement, QML has the theoretical potential to process complex data spaces more efficiently, offering insights into linguistic patterns and relationships. However, one of the major hurdles in QML remains the efficient handling of large-scale data, as current quantum devices are limited in size and capability.

This project seeks to cautiously explore the integration of QML with LLMs to address some of the latter’s classical limitations. By operating in high-dimensional Hilbert spaces, quantum-enhanced methods could uncover richer linguistic structures and improve NLP applications such as translation and summarization. To achieve this, a hybrid classical-quantum framework will be developed, combining the strengths of both paradigms to address computational bottlenecks in training and optimization.

Custom QML algorithms will also be designed to tackle specific LLM challenges, including efficient training on smaller datasets and optimizing model configurations within the constraints of current quantum hardware. These approaches will be rigorously tested on near-term intermediate-scale quantum (NISQ) devices, with performance benchmarks against classical techniques.

While the field remains in its early stages, this project aims to provide realistic insights into the potential of quantum-enhanced LLMs, carefully addressing existing challenges while contributing foundational knowledge to advance quantum computing in NLP.