Stark many-body localization with long-range interactions

In one-dimensional (1D) disorder-free interacting systems, a sufficiently strong linear potential can induce localization of the many-body eigenstates, a phenomenon dubbed as Stark many-body localization (MBL). In this paper, we investigate the fate of Stark MBL in 1D spinless fermions systems with long-range interactions, specifically focusing on the role of interaction strength. We obtain the Stark MBL phase diagrams by computing the mean gap ratio and many-body inverse participation ratio at half-filling. We show that, for short-range interactions, there is a qualitative symmetry between the limits of weak and strong interactions. However, this symmetry is absent in the case of long-range interactions, where the system is always Stark many-body localized at strong interactions, regardless of the linear potential strength. Furthermore, we study the dynamics of imbalance and entanglement with various initial states using time-dependent variational principle (TDVP) numerical methods. We reveal that the dynamical quantities display a strong dependence on the initial conditions, which suggests that the Hilbert-space fragmentation precludes thermalization. Our results demonstrate the robustness of Stark MBL even in the presence of long-range interactions and offer an avenue to explore MBL in disorder-free systems with long-range interactions

Short-range interaction of strongly nonlocal spatial optical solitons

A novel phenomenon is discovered that the short-range interaction between strongly nonlocal spatial solitons depends sinusoidally on their phase difference. The two neighbouring solitons at close proximate can be inter-trapped via the strong nonlocality, and propagate together as a whole. The trajectory of the propagation is a straight line with its slope controlled by the phase difference. The experimental results carried out in nematic liquid crystals agree quantitatively with the prediction. Our study suggests that the phenomenon to steer optical beams by controlling the phase difference could be used in all-optical information processing.Comment: 4 pages 6 figure

Regularized Shallow Image Prior for Electrical Impedance Tomography

Untrained Neural Network Prior (UNNP) based algorithms have gained increasing popularity in tomographic imaging, as they offer superior performance compared to hand-crafted priors and do not require training. UNNP-based methods usually rely on deep architectures which are known for their excellent feature extraction ability compared to shallow ones. Contrary to common UNNP-based approaches, we propose a regularized shallow image prior method that combines UNNP with hand-crafted prior for Electrical Impedance Tomography (EIT). Our approach employs a 3-layer Multi-Layer Perceptron (MLP) as the UNNP in regularizing 2D and 3D EIT inversion. We demonstrate the influence of two typical hand-crafted regularizations when representing the conductivity distribution with shallow MLPs. We show considerably improved EIT image quality compared to conventional regularization algorithms, especially in structure preservation. The results suggest that combining the shallow image prior and the hand-crafted regularization can achieve similar performance to the Deep Image Prior (DIP) but with less architectural dependency and complexity of the neural network

Angular Reconstruction of a Lead Scintillating-Fiber Sandwiched Electromagnetic Calorimeter

A new method called Neighbor Cell Deposited Energy Ratio (NCDER) is proposed to reconstruct incidence position in a single layer for a 3-dimensional imaging electromagnetic calorimeter (ECAL).This method was applied to reconstruct the ECAL test beam data for the Alpha Magnetic Spectrometer-02 (AMS-02). The results show that this method can achieve an angular resolution of 7.36\pm 0.08 / \sqrt(E) \oplus 0.28 \pm 0.02 degree in the determination of the photons direction, which is much more precise than that obtained with the commonly-adopted Center of Gravity(COG) method (8.4 \pm 0.1 /sqrt(E) \oplus 0.8\pm0.3 degree). Furthermore, since it uses only the properties of electromagnetic showers, this new method could also be used for other type of fine grain sampling calorimeters.Comment: 6 pages, 8 figure

Online scheduling on three uniform machines

AbstractThis paper investigates the online scheduling on three uniform machines problem. Denote by sj the speed of each machine, j=1,2,3. Assume 0<s1≤s2≤s3, and let s=s2/s1 and t=s3/s2 be two speed ratios. We show the greedy algorithm LS is an optimal online algorithm when the speed ratios (s,t)∈G1∪G2, where G1={(s,t)|1≤t<1+316,s≥3t5+2t−6t2} and G2={(s,t)|s(t−1)t≥1+s,s≥1,t≥1}. The competitive ratio of LS is 1+s+2sts+st when (s,t)∈G1 and 1+sst+1 when (s,t)∈G2. Moreover, for the general speed ratios, we show the competitive ratio of LS is no more than min{1+s+2sts+st,1+sst+1,1+s+3st1+s+st} and its overall competitive ratio is 2 which matches the overall lower bound of the problem