arXiv subjects

Zhen Liu

Publications and source records attributed to Zhen Liu.

At least 199 records · Page 11Linked to original sources

arXiv2022

A superconducting nanowire photon number resolving four-quadrant detector-based Gigabit deep-space laser communication receiver prototype

Deep space explorations require transferring huge amounts of data quickly from very distant targets. Laser communication is a promising technology that can offer a data rate of magnitude faster than conventional microwave communication due to the fundamentally narrow divergence of light. This study demonstrated a photon-sensitive receiver prototype with over Gigabit data rate, immunity to strong background photon noise, and simultaneous tracking ability. The advantages are inherited from a joint-optimized superconducting nanowire single-photon detector (SNSPD) array, designed into a four-quadrant structure with each quadrant capable of resolving six photons. Installed in a free-space coupled and low-vibration cryostat, the system detection efficiency reached 72.7%, the detector efficiency was 97.5%, and the total photon counting rate was 1.6 Gcps. Additionally, communication performance was tested for pulse position modulation (PPM) format. A series of signal processing methods were introduced to maximize the performance of the forward error correction (FEC) code. Consequently, the receiver exhibits a faster data rate and better sensitivity by about twofold (1.76 photons/bit at 800 Mbps and 3.40 photons/bit at 1.2 Gbps) compared to previously reported results (3.18 photon/bit at 622 Mbps for the Lunar Laser Communication Demonstration). Furthermore, communications in strong background noise and with simultaneous tracking ability were demonstrated aimed at the challenges of daylight operation and accurate tracking of dim beacon light in deep space scenarios.

physics.ins-det↗

arXiv2022

Report of the Topical Group on Electroweak Precision Physics and Constraining New Physics for Snowmass 2021

The precise measurement of physics observables and the test of their consistency within the standard model (SM) are an invaluable approach, complemented by direct searches for new particles, to determine the existence of physics beyond the standard model (BSM). Studies of massive electroweak gauge bosons (W and Z bosons) are a promising target for indirect BSM searches, since the interactions of photons and gluons are strongly constrained by the unbroken gauge symmetries. They can be divided into two categories: (a) Fermion scattering processes mediated by s- or t-channel W/Z bosons, also known as electroweak precision measurements; and (b) multi-boson processes, which include production of two or more vector bosons in fermion-antifermion annihilation, as well as vector boson scattering (VBS) processes. The latter categories can test modifications of gauge-boson self-interactions, and the sensitivity is typically improved with increased collision energy. This report evaluates the achievable precision of a range of future experiments, which depend on the statistics of the collected data sample, the experimental and theoretical systematic uncertainties, and their correlations. In addition it presents a combined interpretation of these results, together with similar studies in the Higgs and top sector, in the Standard Model effective field theory (SMEFT) framework. This framework provides a model-independent prescription to put generic constraints on new physics and to study and combine large sets of experimental observables, assuming that the new physics scales are significantly higher than the EW scale.

hep-ph↗

arXiv2022

DINER: Disorder-Invariant Implicit Neural Representation

Implicit neural representation (INR) characterizes the attributes of a signal as a function of corresponding coordinates which emerges as a sharp weapon for solving inverse problems. However, the capacity of INR is limited by the spectral bias in the network training. In this paper, we find that such a frequency-related problem could be largely solved by re-arranging the coordinates of the input signal, for which we propose the disorder-invariant implicit neural representation (DINER) by augmenting a hash-table to a traditional INR backbone. Given discrete signals sharing the same histogram of attributes and different arrangement orders, the hash-table could project the coordinates into the same distribution for which the mapped signal can be better modeled using the subsequent INR network, leading to significantly alleviated spectral bias. Experiments not only reveal the generalization of the DINER for different INR backbones (MLP vs. SIREN) and various tasks (image/video representation, phase retrieval, and refractive index recovery) but also show the superiority over the state-of-the-art algorithms both in quality and speed.

eess.IV↗

arXiv2022

Flavor-changing light bosons with accidental longevity

We consider a model with a complex scalar field that couples to $(e,μ)$ or $(μ,τ)$ within the "longevity" window: $[|m_{l_1} - m_{l_2}|, m_{l_1} + m_{l_2}]$ in which $l_1$ and $l_2$ are the two different charged leptons. Within such a mass window, even a relatively large coupling (e.g. of the size commensurate with the current accuracy/discrepancy in the muon $g-2$ experiment) leads to long lifetimes and macroscopic propagation distance between production and decay points. We propose to exploit several existing neutrino experiments and one future experiment to probe the parameter space of this model. For the $μ-e$ sector, we exploit the muonium decay branching ratio and the production and decay sequence at the LSND experiment, excluding the parametric region suggested by $g_μ-2$ anomaly. For the $τ-μ$ sector, we analyze three main production mechanisms of scalars at beam dump experiments: the Drell-Yan process, the heavy meson decay, and the muon scattering. We explore the constraints from the past CHARM and NuTeV experiments, and evaluate sensitivity for the proposed beam dump experiment, SHiP. The latter can thoroughly probe the parameter space relevant for the $g_μ- 2$ anomaly.

hep-ph↗

arXiv2022

Entanglement-Enhanced Optomechanical Sensing

Optomechanical systems have been exploited in ultrasensitive measurements of force, acceleration, and magnetic fields. The fundamental limits for optomechanical sensing have been extensively studied and now well understood -- the intrinsic uncertainties of the bosonic optical and mechanical modes, together with the backaction noise arising from the interactions between the two, dictate the Standard Quantum Limit (SQL). Advanced techniques based on nonclassical probes, in-situ pondermotive squeezed light, and backaction-evading measurements have been developed to overcome the SQL for individual optomechanical sensors. An alternative, conceptually simpler approach to enhance optomechanical sensing rests upon joint measurements taken by multiple sensors. In this configuration, a pathway toward overcoming the fundamental limits in joint measurements has not been explored. Here, we demonstrate that joint force measurements taken with entangled probes on multiple optomechanical sensors can improve the bandwidth in the thermal-noise-dominant regime or the sensitivity in shot-noise-dominant regime. Moreover, we quantify the overall performance of entangled probes with the sensitivity-bandwidth product and observe a 25% increase compared to that of the classical probes. The demonstrated entanglement-enhanced optomechanical sensing could enable new capabilities for inertial navigation, acoustic imaging, and searches for new physics.

quant-ph↗

arXiv2022

Report of the Topical Group on Physics Beyond the Standard Model at Energy Frontier for Snowmass 2021

This is the Snowmass2021 Energy Frontier (EF) Beyond the Standard Model (BSM) report. It combines the EF topical group reports of EF08 (Model-specific explorations), EF09 (More general explorations), and EF10 (Dark Matter at Colliders). The report includes a general introduction to BSM motivations and the comparative prospects for proposed future experiments for a broad range of potential BSM models and signatures, including compositeness, SUSY, leptoquarks, more general new bosons and fermions, long-lived particles, dark matter, charged-lepton flavor violation, and anomaly detection.

hep-ph↗

arXiv2022

SML:Enhance the Network Smoothness with Skip Meta Logit for CTR Prediction

In light of the smoothness property brought by skip connections in ResNet, this paper proposed the Skip Logit to introduce the skip connection mechanism that fits arbitrary DNN dimensions and embraces similar properties to ResNet. Meta Tanh Normalization (MTN) is designed to learn variance information and stabilize the training process. With these delicate designs, our Skip Meta Logit (SML) brought incremental boosts to the performance of extensive SOTA ctr prediction models on two real-world datasets. In the meantime, we prove that the optimization landscape of arbitrarily deep skip logit networks has no spurious local optima. Finally, SML can be easily added to building blocks and has delivered offline accuracy and online business metrics gains on app ads learning to rank systems at TikTok.

cs.IR↗

arXiv2022

Enhancing Searches for Heavy QCD Axions via Dimuon Final States

Heavy QCD axions are well-motivated extensions of the QCD axion that address the quality problem while still solving the strong CP problem. Owing to the gluon coupling, critical for solving the strong CP problem, these axions can be produced in significant numbers in beam dump and collider environments for axion decay constants as large as PeV, relevant for addressing the axion quality problem. In addition, if these axions have leptonic couplings, they can give rise to long-lived decay into lepton pairs, in particular, dominantly into muons above the dimuon threshold and below the GeV scale in a broad class of axion models. Considering existing constraints, primarily from rare meson decays, we demonstrate that current and future neutrino facilities and long-lived particle searches have the potential to probe significant parts of the heavy QCD axion parameter space via dimuon final states.

hep-ph↗

arXiv2022

Sleptonic SUSY: From UV Framework to IR Phenomenology

We study an attractive scenario, "Sleptonic SUSY", which reconciles the $125$ GeV Higgs scalar and the non-observation of superpartners thus far with potentially pivotal roles for slepton phenomenology: providing viable ongoing targets for LHC discovery, incorporating a co-annihilation partner for detectable thermal relic dark matter, and capable of mediating the potential muon $g-2$ anomaly. This is accomplished by a modestly hierarchical spectrum, with sub-TeV sleptons and electroweakinos and with multi-TeV masses for the other new states. We study new elements in the UV MSSM realization of Sleptonic SUSY based on higher-dimensional sequestering and the synergy between the resulting gaugino-mediation, hypercharge $D$-term mediation and Higgs-mediation of SUSY-breaking, so as to more fully capture the range of possibilities. This framework stands out by harmoniously solving the flavor, CP and $μ- Bμ$ problems of the supersymmetric paradigm. We discuss its extension to orbifold GUTs, including gauge-coupling and $b$-tau unification. We also develop a non-minimal model with extra Higgs fields, in which the electroweak vacuum is more readily cosmologically stable against decay to a charge-breaking vacuum, allowing a broader range of sleptonic spectra than in the MSSM alone. We survey the rich set of signals possible at the LHC and future colliders, covering both $R$-parity conservation and violation, as well as for dark matter detection. While the multi-TeV squarks imply a Little Hierarchy Problem, intriguingly, small changes in parameter space to improve naturalness result in dramatic phase transitions to either electroweak-preservation or charge-breaking. In a Multiverse setting, the modest unnaturalness may then be explained by the "principle of living dangerously".

hep-ph↗

arXiv2022

Enhanced Current Density and Asymmetry of Metal-Insulator-Metal Diodes Based on the Self-Assembly of Pt Nanoparticles for Optical Rectennas

Optical rectennas consist of nano-antennas and nano-scale rectifying diodes, providing extensive prospects for thermal radiation energy harvesting applications. To achieve this, high current density and high asymmetry must be simultaneously obtained in rectifying diodes with ultra-high-speed responses to optical frequencies. In this study, we report a metal-insulator-metal (MIM) diode with a strongly enhanced electric field achieved via the self-assembly of uniform Pt nanoparticles (NPs) using atomic layer deposition. An enhancement of several orders of magnitude in the current density and asymmetry of this system in comparison to conventional MIM diodes was realized by shaping the tunneling barrier. The diode efficiency of the proposed MIM diodes experimentally confirmed that significantly exceeds the MIM diode without NPs by 231 times. Furthermore, the proposed strategy can be integrated with various advanced tunnel diodes to achieve high-performance optical rectennas.

physics.optics↗

arXiv2022

Ghost-free High Dynamic Range Imaging with Context-aware Transformer

High dynamic range (HDR) deghosting algorithms aim to generate ghost-free HDR images with realistic details. Restricted by the locality of the receptive field, existing CNN-based methods are typically prone to producing ghosting artifacts and intensity distortions in the presence of large motion and severe saturation. In this paper, we propose a novel Context-Aware Vision Transformer (CA-ViT) for ghost-free high dynamic range imaging. The CA-ViT is designed as a dual-branch architecture, which can jointly capture both global and local dependencies. Specifically, the global branch employs a window-based Transformer encoder to model long-range object movements and intensity variations to solve ghosting. For the local branch, we design a local context extractor (LCE) to capture short-range image features and use the channel attention mechanism to select informative local details across the extracted features to complement the global branch. By incorporating the CA-ViT as basic components, we further build the HDR-Transformer, a hierarchical network to reconstruct high-quality ghost-free HDR images. Extensive experiments on three benchmark datasets show that our approach outperforms state-of-the-art methods qualitatively and quantitatively with considerably reduced computational budgets. Codes are available at https://github.com/megvii-research/HDR-Transformer

cs.CV↗

arXiv2022

Structural Causal 3D Reconstruction

This paper considers the problem of unsupervised 3D object reconstruction from in-the-wild single-view images. Due to ambiguity and intrinsic ill-posedness, this problem is inherently difficult to solve and therefore requires strong regularization to achieve disentanglement of different latent factors. Unlike existing works that introduce explicit regularizations into objective functions, we look into a different space for implicit regularization -- the structure of latent space. Specifically, we restrict the structure of latent space to capture a topological causal ordering of latent factors (i.e., representing causal dependency as a directed acyclic graph). We first show that different causal orderings matter for 3D reconstruction, and then explore several approaches to find a task-dependent causal factor ordering. Our experiments demonstrate that the latent space structure indeed serves as an implicit regularization and introduces an inductive bias beneficial for reconstruction.

cs.LG↗

arXiv2022

Domain size and charge defects on the polarization switching of antiferroelectric domains

The switching behavior of antiferroelectric domain structures under the applied electric field is not fully understood. In this work, by using the phase field simulation, we have studied the polarization switching property of antiferroelectric domains. Our results indicate that the ferroelectric domains nucleate preferably at the boundaries of the antiferroelectric domains, and antiferroelectrics with larger initial domain sizes possess a higher coercive electric field as demonstrated by hysteresis loops. Moreover, we introduced charge defects into the sample and numerically investigated their influence. It is also shown that charge defects can induce local ferroelectric domains, which could suppress the saturation polarization and narrow the enclosed area of the hysteresis loop. Our results give insights into understanding antiferroelectric phase transformation and optimizing the energy storage property in experiments.

cond-mat.mtrl-sci↗

arXiv2022

Entangled sensor-networks for dark-matter searches

The hypothetical axion particle (of unknown mass) is a leading candidate for dark matter (DM). Many experiments search for axions with microwave cavities, where an axion may convert into a cavity photon, leading to a feeble excess in the output power of the cavity. Recent work [Nature 590, 238 (2021)] has demonstrated that injecting squeezed vacuum into the cavity can substantially accelerate the axion search. Here, we go beyond and provide a theoretical framework to leverage the benefits of quantum squeezing in a network setting consisting of many sensor-cavities. By forming a local sensor network, the signals among the cavities can be combined coherently to boost the axion search. Furthermore, injecting multipartite entanglement across the cavities -- generated by splitting a squeezed vacuum -- enables a global noise reduction. We explore the performance advantage of such a local, entangled sensor-network, which enjoys both coherence between the axion signals and entanglement between the sensors. Our analyses are pertinent to next-generation DM-axion searches aiming to leverage a network of sensors and quantum resources in an optimal way. Finally, we assess the possibility of using a more exotic quantum state, the Gottesman-Kitaev-Preskill (GKP) state. Despite a constant-factor improvement in the scan-time relative to a single-mode squeezed-state in the ideal case, the advantage of employing a GKP state disappears when a practical measurement scheme is considered.

quant-ph↗

arXiv2022

An Improved Lattice-Based Ring Signature with Unclaimable Anonymity in the Standard Model

Ring signatures enable a user to sign messages on behalf of an arbitrary set of users, called the ring, without revealing exactly which member of that ring actually generated the signature. The signer-anonymity property makes ring signatures have been an active research topic. Recently, Park and Sealfon (CRYPTO 19) presented an important anonymity notion named signer-unclaimability and constructed a lattice-based ring signature scheme with unclaimable anonymity in the standard model, however, it did not consider the unforgeable w.r.t. adversarially-chosen-key attack (the public key ring of a signature may contain keys created by an adversary) and the signature size grows quadratically in the size of ring and message. In this work, we propose a new lattice-based ring signature scheme with unclaimable anonymity in the standard model. In particular, our work improves the security and efficiency of Park and Sealfons work, which is unforgeable w.r.t. adversarially-chosen-key attack, and the ring signature size grows linearly in the ring size.

cs.CR↗

arXiv2022

Generative Flow Networks for Discrete Probabilistic Modeling

We present energy-based generative flow networks (EB-GFN), a novel probabilistic modeling algorithm for high-dimensional discrete data. Building upon the theory of generative flow networks (GFlowNets), we model the generation process by a stochastic data construction policy and thus amortize expensive MCMC exploration into a fixed number of actions sampled from a GFlowNet. We show how GFlowNets can approximately perform large-block Gibbs sampling to mix between modes. We propose a framework to jointly train a GFlowNet with an energy function, so that the GFlowNet learns to sample from the energy distribution, while the energy learns with an approximate MLE objective with negative samples from the GFlowNet. We demonstrate EB-GFN's effectiveness on various probabilistic modeling tasks. Code is publicly available at https://github.com/zdhNarsil/EB_GFN.

cs.LG↗

arXiv2022

Strategy for Understanding the Higgs Physics: The Cool Copper Collider

A program to build a lepton-collider Higgs factory, to precisely measure the couplings of the Higgs boson to other particles, followed by a higher energy run to establish the Higgs self-coupling and expand the new physics reach, is widely recognized as a primary focus of modern particle physics. We propose a strategy that focuses on a new technology and preliminary estimates suggest that can lead to a compact, affordable machine. New technology investigations will provide much needed enthusiasm for our field, resulting in trained workforce. This cost-effective, compact design, with technologies useful for a broad range of other accelerator applications, could be realized as a project in the US. Its technology innovations, both in the accelerator and the detector, will offer unique and exciting opportunities to young scientists. Moreover, cost effective compact designs, broadly applicable to other fields of research, are more likely to obtain financial support from our funding agencies.

hep-ex↗

arXiv2022

Muon Collider Physics Summary

The perspective of designing muon colliders with high energy and luminosity, which is being investigated by the International Muon Collider Collaboration, has triggered a growing interest in their physics reach. We present a concise summary of the muon colliders potential to explore new physics, leveraging on the unique possibility of combining high available energy with very precise measurements.

hep-ph↗