Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and its specialized branch, deep learning (DL). This review paper provides a thorough illustration of these applications using different ML and DL approaches. The first part of the paper examines the basics of various particle physics types and establishes guidelines for assessing particle physics alongside the available learning models. Next, a detailed classification is provided for representing Jets that are reconstructed in high-energy collisions, mainly in proton-proton collisions at well-defined beam energies. This section covers various datasets, preprocessing techniques, and feature extraction and selection methods. The presented techniques can be applied to future hadron−hadron colliders (HHC), such as the high-luminosity LHC (HL-LHC) and the future circular collider−hadron−hadron (FCC-hh). The authors then explore several AI techniques analyses designed specifically for both image and point-cloud (PC) data in HEP. Additionally, a closer look is taken at the classification associated with Jet tagging in hadron collisions. In this review, various state-of-the-art (SOTA) techniques in ML and DL are examined, with a focus on their implications for HEP demands. More precisely, this discussion addresses various applications in extensive detail, such as Jet tagging, Jet tracking, and particle classification. The review concludes with an analysis of the current state of HEP using DL methodologies. It highlights the challenges and potential areas for future research, which are illustrated for each application.
Within the framework of AdS/CFT correspondence, this paper studies the holographic shadow images of charged Phantom AdS black holes. Using a Gaussian oscillator source on the AdS boundary, the test waves generated by this source propagate through the black hole spacetime are detected by the response function on the other side of the boundary. The results show that the amplitude of the response function differs for different wave sources and gravitational parameters. From an optical system with a convex lens, we successfully constructed the shadow image of the black hole. When the wave source is located at the South Pole and the observation inclination is zero, a series of axially symmetric concentric circular patterns are always displayed on the screen. As the observation inclination increases, the brightest ring transforms into a ring with distorted brightness, Eventually collapsing to a bright spot. Additionally, the research finds that the shadow image depends not only on the black hole’s temperature and chemical potential but also on the frequency of the wave source. Based on the geometric optics, the incidence angle of the photon ring is also discussed, and finds that it Matches the angular distance of the Einstein ring obtained by the holographic framework, which validates the effectiveness of studying Einstein rings through AdS/CFT correspondence.
The muonium-to-antimuonium conversion experiment (MACE) is proposed to search for charged lepton flavor violation and increase the sensitivity by more than two orders of magnitude compared to the muonium−antimuonium conversion spectrometer (MACS) experiment at PSI in 1999. A clear signature of this conversion is the positron produced from antimuonium decay. This paper presents a near-
We explored two
Two-dimensional materials offer great potential for addressing the constraints of conventional semiconductors in the post-Moore era; however, the persuit of stable p-type two-dimensional semiconductors with high mobility remains a formidable challenge. Tellurium emerges as a noteworthy candidate for p-type two-dimensional semiconductors due to its high hole mobility, outstanding chemical stability, and polarization-dependent optoelectronic characteristics. Its anisotropic crystal structure and thickness-dependent bandgap render it particularly suitable for next-generation electronic and optoelectronic applications, with recent advancements demonstrating its exceptional performance. Furthermore, the intrinsic topological features of tellurium, such as strong spin−orbit coupling and Weyl points situated below the Fermi level, classify it as a topological semiconductor — a pioneering category of quantum materials that provides innovative avenues for merging topological physics with conventional semiconductor technologies. The remarkable synergy of mobility, stability, and intrinsic topological attributes in tellurium positions it as a transformative material for the advancement of sophisticated electronic, optoelectronic and quantum systems, among other applications.
The interplay of crystal electric field, temperature, and spin–orbit coupling can yield a Kramer ion and thus an effective S = ½ ground state for
Photonic moiré lattices (PMLs), with unique twisted periodic patterns, provide a valuable platform for investigating strongly correlated materials, unconventional superconductivity, and the localization−delocalization transition. However, PMLs created either by the misorientation between lattice layers or by twisted van der Waals materials are typically non-tunable and inherently possess immutable refractive indices. Unlike those in the moiré lattices of twisted two-dimensional materials, our work reports a moiré lattice formed by overlapping two identical sublattices with twisted angles in an ultracold atomic ensemble. This photoinduced moiré lattice with two twisted sublattices exhibits high flexibility and rich periodicity through adjustable twisted angles. Our results indicate that both the absorption/dispersion coefficients and the transmission of the photoinduced moiré lattices can be effectively tuned by photon detuning and Rabi frequency, resulting in amplitude- and phase-type moiré lattices. Based on the Fraunhofer diffraction theory, we have demonstrated that the far-field diffraction efficiency can be adjusted via altering photon detuning, and the rotation angle serves as a control knob for modulating the diffracted intensity distribution, thereby optimizing the performance of the photonic lattice. It is also found that the operation domains of the moiré lattices with different rotation angles remain consistent, allowing for seamless conversion between various moiré period structures. Furthermore, a moiré lattice composed of three twisted sublattices is investigated, revealing that the diffraction energy is uniformly dispersed in a circular distribution, which provides excellent agility in the design of optical devices. Such tunable PML offer a powerful tool for studying light propagation control and the intriguing physics of twisted systems in atomic media.
Pressure serves as a powerful approach to regulating the thermal conductivity of materials. By applying pressure, one can alter the lattice symmetry, atomic spacing, and phonon scattering mechanisms, thereby exerting a profound influence on thermal transport properties. SnS, sharing the same crystal structure as SnSe, has often been overlooked due to its higher lattice thermal conductivity. While extensive efforts have been dedicated to enhancing the power factor of SnS through doping, its thermal transport properties remain underexplored, limiting its potential as a thermoelectric material. In this study, we investigated the impact of pressure modulation on the thermoelectric performance of SnS. Remarkably, the application of negative pressure significantly enhanced its thermal transport characteristics, leading to a reduction in the lattice thermal conductivity (
As a novel computing paradigm that transcends traditional von Neumann architectures, neuromorphic computing integrates learning and memory functions. The ability to mimic multi-input spatiotemporal integration is crucial for achieving efficient neuromorphic computing. In this work, we fabricated a multi-gate solid-state amorphous (SA) electrolyte-gated oxide dendritic transistor, which exhibits in-plane-gate modulatory behaviors and dendritic neural functions. Leveraging unique proton migration, we successfully simulated Ebbinghaus memory forgetting. By applying spatiotemporal dendritic inputs, we mimicked temporal integration and coincidence detection. Additionally, we demonstrated neural multiplication operations using frequency-encoded signals. Furthermore, spatially correlated sensitization and desensitization behaviors of pain perception were implemented on the multi-gate dendritic transistors. Collectively, these results indicate that the present oxide dendritic transistors could serve as fundamental building blocks for advanced cognitive neuromorphic platforms.
The second-order correlation function of photons is the primary means to quantitatively describe the second-order coherence of a light field. In contrast to the stationary second-order correlation function, the temporal second-order correlation function can be used to study the second-order coherence of a transient light field. Based on the Monte Carlo algorithm, we carried out theoretical simulation on the temporal second-order correlation function from the perspective of photon statistics. By introducing experimental factors into the simulation, such as intensity jitter of the light field and time resolution of the instruments, the effects of imperfect experimental conditions on the measurement of second-order correlation function have also been elucidated. Our results provide theoretical guidance and analysis methods for experimental measurements on the second-order coherence of light fields.
We performed the detailed magnetotransport measurements and first principle calculations to study the electronic properties of the transition metal dipnictides ZrAs2, which is a topological nodal-line semimetal. Extremely large unsaturated magnetoresistance (MR) which is up to 1.9 × 104 % at 2 K and 14 T was observed with magnetic field along the c-axis. The nonlinear magnetic field dependence of Hall resistivity indicates the multi-band features, and the electron and hole are nearly compensated according to the analysis of the two-band model, which may account for the extremely large unsaturated MR at low temperatures. The evident Shubnikov-de Haas (SdH) oscillations at low temperatures are observed and four distinct oscillation frequencies are extracted. The first principle calculations and angle-dependent SdH oscillations reveal that the Fermi surface consists of three pockets with different anisotropy. The observed twofold symmetry MR with electric field along the b-axis direction is consistent with our calculated Fermi surface structures. Furthermore, the negative magnetoresistance (NMR) with magnetic field in parallel with electric field is observed, which is an evident feature of the chiral anomaly.
Paramagnetic LaCoSi, a ternary intermetallic electride, consists of CoSi blocks separated by two layers of La atoms. Its structure is similar to that of the widely studied 111 system of iron-based superconductors. Utilizing angle-resolved photoemission spectroscopy and first-principles calculations, we demonstrate the existence of linear bands and flat bands mainly originating from the
There has been a notable surge of interest in neuromorphic network computation, particularly concerning both non-volatile and volatile threshold devices. In this research, we have developed a multi-layer thin film architecture consisting of Al/AlN/Ag/AlN/Pt, which functions as a threshold switching (TS) device characterized by rapid switching speeds of 50 ns and minimal leakage current. We have effectively demonstrated biological neuron-like behaviors, such as threshold-driven spikes, all-or-nothing spikes, intensity-modulated frequency response, and frequency-modulated frequency response, through the deployment of a leaky integrate-and-fire (LIF) artificial neuron circuit, which surpasses earlier neuronal models. The resistance switching mechanism of the device is likely due to the migration of nitrogen vacancies in conjunction with silver filaments. This threshold switching device shows significant potential for applications in next-generation artificial neural networks.
The Rice−Mele model has been a seminal prototypical model for the study of topological phenomena such as Thouless pumping. Here we implement the interacting Rice−Mele model using a superconducting quantum processor comprising a one-dimensional array of 36 qutrits. By adiabatically cycling the qutrit frequencies and hopping strengths in the parametric space, we emulate the Thouless pumping of single and two bounded microwave photons along the qutrit chain. Furthermore, with strong Hubbard interaction inherent in the qutrits we also emulate the intriguing phenomena of resonant tunneling and asymmetric edge-state transport of two interacting photons. Utilizing the interactions and higher energy levels in such fully controlled synthetic quantum simulators, these results demonstrate new opportunities for exploring exotic topological phases and quantum transport phenomena using superconducting quantum circuits.
Fe3GaTe2 has attracted significant interest due to its intrinsic room-temperature ferromagnetism, yet its magnetic interactions remain debated. We thoroughly investigate the magnetism of Fe3GaTe2 using critical analysis, nitrogen−vacancy (NV) center magnetometry, and Density Function Theory (DFT). Our critical phenomenon analysis with exponents [
The rapid rise of artificial intelligence (AI) has catalyzed advancements across various trades and professions. Developing large-scale AI models is now widely regarded as one of the most viable approaches to achieving general-purpose intelligent agents. This pressing demand has made the development of more advanced computing accelerators an enduring goal for the rapid realization of large-scale AI models. However, as transistor scaling approaches physical limits, traditional digital electronic accelerators based on the von Neumann architecture face significant bottlenecks in energy consumption and latency. Optical computing accelerators, leveraging the high bandwidth, low latency, low heat dissipation, and high parallelism of optical devices and transmission over waveguides or free space, offer promising potential to overcome these challenges. In this paper, inspired by the generic architectures of digital electronic accelerators, we conduct a bottom-up review of the principles and applications of optical computing accelerators based on the basic element of computing accelerators − the multiply-accumulate (MAC) unit. Then, we describe how to solve matrix multiplication by composing calculator arrays from different MAC units in diverse architectures, followed by a discussion on the two main applications where optical computing accelerators are reported to have advantages over electronic computing. Finally, the challenges of optical computing and our perspective on its future development are presented. Moreover, we also survey the current state of optical computing in the industry and provide insights into the future commercialization of optical computing.
Significant progress has been made in high-power ultrafast laser technology since the development of diode-pumped solid-state laser systems. Three main types of diode-pumped laser systems, InnoSlab, fiber, and thin disk lasers, offer highly efficient cooling geometries that are essential for high-power ultrafast amplifiers. These systems employ amplifier chain configurations customized to their individual geometries, scaling the low-power seed lasers to high power via multi-pass, multi-stage, and regenerative amplification techniques. The partially end-pumped InnoSlab amplifier is distinguished by its slab-shaped gain medium and a highly compact design. This design offers a large surface-to-volume ratio, moderate gain per pass, and reduced nonlinear effects, facilitating the amplification of low-power ultrafast seed laser pulses to kilowatt-level output power at high repetition rates in the multi-MHz range. This review highlights the characteristics of InnoSlab technology and its amplifier configurations, discussing recent advancements in new cavity designs aimed at enhancing gain and beam quality. Additionally, it covers the mechanisms of generating high peak power few-cycle pulses, including non-linear post-pulse compression. The review also explores the potential applications of InnoSlab systems for generating extreme ultraviolet (XUV) and terahertz (THz) frequencies.
Passively mode-locked fiber lasers find extensive applications in communications, ultrafast science, and materials processing. In this study, carbon nanotubes (CNTs) were employed as saturable absorbers in a passively mode-locked fiber laser. We systematically explored the influence of different dispersion characteristics on the output of mode-locked pulses by precisely adjusting the cavity length. The experimental results clearly indicate that when the dispersion is altered from −0.25 to −0.12 ps2, the pulse width can be effectively reduced from 858 to 645 fs. In addition, we comparatively analyzed the effects of CNT-SA aqueous solution and CNT-PVA-SA on the pulse output of the fiber laser. It was discovered that the morphology of the material exerts a significant impact on the mode-locking threshold, pulse width, and stability of the laser. This discovery offers a crucial theoretical foundation for future material selection in the field of passively mode-locked fiber lasers, facilitating more optimized designs and enhanced performance in related applications.
Due to the potential of quantum advantage to surpass the standard quantum limit (SQL), nonlinear interferometers have garnered significant attention from researchers in the field of precision measurement. However, many practical applications require multiparameter estimation. In this work, we discuss the precision limit of multi-parameter estimation of pure Gaussian states based on nonlinear interferometers, and derive the Holevo Cramér−Rao bound (HCRB) for the case where both modes undergo displacement estimation. Furthermore, we compare our analytical results with the quantum Cramér−Rao bound based on the symmetric logarithmic derivative (SLD-CRB), and with the result of the dual homodyne measurement. Through numerical analysis, we find that the HCRB equals the result of the dual homodyne measurement, whereas SLD-CRB is not saturable at small squeezed parameters. Therefore, this indicates that the HCRB is tight. Additionally, we provide intuitive analysis and visual representation of our numerical results in phase space.
We present a proof-of-principle demonstration of energy-resolved resonant neutron ghost imaging. Based on the resonant absorption dips of different elements, we simultaneously image and distinguish the composition of three differently shaped components of an object. The initial neutron beam is spatially and energy selectively modulated by a series of Hadamard matrix masks of pixel width 100 μm. The spectral intensity transmitted through an object is measured by a 6Li glass single-pixel detector. Through integration of the total counts within resonant dips and correlating them with the corresponding Hadamard patterns, isotope-specific images of In, Ag and W objects are obtained at an effective spatial resolution of ~200 μm. Reconstruction algorithms based on compressed sensing or convolutional neural networks can greatly reduce the data acquisition time by ~70% with respect to the full set of 1024 patterns, as well as enhance the image quality. Incorporating ghost imaging into energy-resolved neutron imaging thus has great potential for the simultaneous realization of fine spatial and spectral resolution, which has important value for the noninvasive analysis of material composition and distribution not only in basic research but also in industrial applications.
As a typical optical measurement technique, the optical frequency comb plays an irreplaceable role in spectroscopy and precision measurement. Recently, the concept of frequency combs has been adapted to the phononic domain, leading to the development of phononic frequency combs (PFCs), which have been utilized in various micro-mechanical systems. However, the realization of PFCs in flexural vibration resonators within the very high frequency (VHF) band − crucial for applications in communications and information processing − remains unachieved. In this study, we report the realization of PFC in carbon nanotube (CNT) mechanical resonators operating within the VHF band for the first time. Additionally, we observe that the system exhibits novel frequency combs and nonlinear enhancement in a two-mode mechanical resonator. Due to the broadband operation, tunable modulation depth, as well as easy fabrication and integration of one-dimensional carbon nanotubes, our investigation into PFCs within the VHF band holds promise for advancing classical and quantum precision measurement techniques, while also deepening our comprehension of nonlinear physics.
A novel cryogenic MgF molecular beam, characterized by high flux and exceptional stability, has been successfully generated within a helium buffer gas environment. This achievement is facilitated by the innovative use of an in-cell stepper motor, which continuously rotates the sample rod during laser ablation. Through meticulous optimization of the ablation laser energy, the position of the ablation spot, and the gas flow rate, among other critical parameters, the resulting MgF beam exhibits a remarkable forward velocity of 209 m/s and an impressive brightness of approximately 1.36 × 1012 molecules per pulse per steradian per internal state. Subsequent attempts at one-dimensional Doppler cooling of the MgF beam have been made, with theoretical calculations closely aligning with experimental outcomes. These findings demonstrate a significant compression in the transverse spatial distribution of the molecular beam, from 7.8 to 6.5 mm, and a substantial cooling of the transverse temperature, from 8.1 to 5.6 mK. This work lays a crucial foundation for the advancement of molecular slowing and magneto-optical trapping techniques for MgF molecules.
