arXiv subjects

Weijie Ji

Publications and source records attributed to Weijie Ji.

7 recordsLinked to original sources

arXiv2025

Two-photon interference between mutually-detuned resonance fluorescence signals scattered off a semiconductor quantum dot

The radiative linewidth of a two-level emitter (TLE) fundamentally limits the bandwidth available for quantum information processing. Despite its importance, no prior experiment has systematically examined how driving detuning affects the indistinguishability of photons scattered from a TLE - a parameter critical for photonic quantum computing. Here, we perform post-selective two-photon interference measurements between mutually detuned resonance fluorescence signals from an InAs quantum dot embedded in a micropillar cavity. At small mutual laser detunings (<=0.5GHz), the results are accurately described by the pure-state model [Nat. Commun. 16, 6453 (2025)], which treats all resonance-fluorescence photons as spontaneous emission. At larger detunings, we uncover an anomalous feature in the two-photon interference, where the normalised second-order correlation function under orthogonal polarisations yields g2_vert(0) < 0.5.

quant-ph↗

arXiv2025

Dynamic treatment effects: high-dimensional inference under model misspecification

Estimating dynamic treatment effects is crucial across various disciplines, providing insights into the time-dependent causal impact of interventions. However, this estimation poses challenges due to time-varying confounding, leading to potentially biased estimates. Furthermore, accurately specifying the growing number of treatment assignments and outcome models with multiple exposures appears increasingly challenging to accomplish. Double robustness, which permits model misspecification, holds great value in addressing these challenges. This paper introduces a novel "sequential model doubly robust" estimator. We develop novel moment-targeting estimates to account for confounding effects and establish that root-$N$ inference can be achieved as long as at least one nuisance model is correctly specified at each exposure time, despite the presence of high-dimensional covariates. Although the nuisance estimates themselves do not achieve root-$N$ rates, the carefully designed loss functions in our framework ensure final root-$N$ inference for the causal parameter of interest. Unlike off-the-shelf high-dimensional methods, which fail to deliver robust inference under model misspecification even within the doubly robust framework, our newly developed loss functions address this limitation effectively.

stat.ME↗

arXiv2025

Coherence in resonance fluorescence

Resonance fluorescence of a two-level emitter displays persistently anti-bunching irrespective of the excitation intensity, but inherits the driving laser's linewidth under weak monochromatic excitation. These properties are commonly explained in terms of two disjoined pictures, i.e., the emitter's single photon saturation or passively scattering light. Here, we propose a unified model that treats all fluorescence photons as spontaneous emission, one at a time, and can explain simultaneously both the spectral and correlation properties of the emission. We theoretically derive the excitation power dependencies, measurable at the single-photon incidence level, of the first-order coherence of the whole resonance fluorescence and super-bunching of the spectrally filtered, followed by experimental confirmation on a semiconductor quantum dot micro-pillar device. Furthermore, our model explains peculiar coincidence bunching observed in phase-dependent two-photon interference experiments. Our work provides an intuitive understanding of coherent light-matter interaction and may stimulate new applications.

quant-ph↗

arXiv2024

Adaptive Split Balancing for Optimal Random Forest

In this paper, we propose a new random forest algorithm that constructs the trees using a novel adaptive split-balancing method. Rather than relying on the widely-used random feature selection, we propose a permutation-based balanced splitting criterion. The adaptive split balancing forest (ASBF), achieves minimax optimality under the Lipschitz class. Its localized version, which fits local regressions at the leaf level, attains the minimax rate under the broad Hölder class $\mathcal{H}^{q,β}$ of problems for any $q\in\mathbb{N}$ and $β\in(0,1]$. We identify that over-reliance on auxiliary randomness in tree construction may compromise the approximation power of trees, leading to suboptimal results. Conversely, the proposed less random, permutation-based approach demonstrates optimality over a wide range of models. Although random forests are known to perform well empirically, their theoretical convergence rates are slow. Simplified versions that construct trees without data dependence offer faster rates but lack adaptability during tree growth. Our proposed method achieves optimality in simple, smooth scenarios while adaptively learning the tree structure from the data. Additionally, we establish uniform upper bounds and demonstrate that ASBF improves dimensionality dependence in average treatment effect estimation problems. Simulation studies and real-world applications demonstrate our methods' superior performance over existing random forests.

stat.ML↗

arXiv2024

Convert laser light into single photons via interference

Laser light possesses perfect coherence, but cannot be attenuated to single photons via linear optics. An elegant route to convert laser light into single photons is based on photon blockade in a cavity with a single atom in the strong coupling regime. However, the single-photon purity achieved by this method remains relatively low. Here we propose an interference-based approach where laser light can be transformed into single photons by destructively interfering with a weak but super-bunched incoherent field emitted from a cavity coupling to a single quantum emitter. We demonstrate this idea by measuring the reflected light of a laser field which drives a double-sided optical microcavity containing a single artificial atom-quantum dot (QD) in the Purcell regime. The reflected light consists of a superposition of the driving field with the cavity output field. We achieve the second-order autocorrelation g2(0)=0.030+-0.002 and the two-photon interference visibility 94.3%+-0.2. By separating the coherent and incoherent fields in the reflected light, we observe that the incoherent field from the cavity exhibits super-bunching with g2(0)=41+-2 while the coherent field remains Poissonian statistics. By controlling the relative amplitude of coherent and incoherent fields, we verify that photon statistics of reflected light is tuneable from perfect anti-bunching to super-bunching in agreement with our predictions. Our results demonstrate photon statistics of light as a quantum interference phenomenon that a single QD can scatter two photons simultaneously at low driving fields in contrast to the common picture that a single two-level quantum emitter can only scatter (or absorb and emit) single photons. This work opens the door to tailoring photon statistics of laser light via cavity or waveguide quantum electrodynamics and interference.

quant-ph↗

arXiv2023

High-dimensional Inference for Dynamic Treatment Effects

Estimating dynamic treatment effects is a crucial endeavor in causal inference, particularly when confronted with high-dimensional confounders. Doubly robust (DR) approaches have emerged as promising tools for estimating treatment effects due to their flexibility. However, we showcase that the traditional DR approaches that only focus on the DR representation of the expected outcomes may fall short of delivering optimal results. In this paper, we propose a novel DR representation for intermediate conditional outcome models that leads to superior robustness guarantees. The proposed method achieves consistency even with high-dimensional confounders, as long as at least one nuisance function is appropriately parametrized for each exposure time and treatment path. Our results represent a significant step forward as they provide new robustness guarantees. The key to achieving these results is our new DR representation, which offers superior inferential performance while requiring weaker assumptions. Lastly, we confirm our findings in practice through simulations and a real data application.

stat.ME↗

arXiv2023

Ultra-narrowband interference circuits enable low-noise and high-rate photon counting for InGaAs/InP avalanche photodiodes

Afterpulsing noise in InGaAs/InP single photon avalanche photodiodes (APDs) is caused by carrier trapping and can be suppressed successfully through limiting the avalanche charge via sub-nanosecond gating. Detection of faint avalanches requires an electronic circuit that is able to effectively remove the gate-induced capacitive response while keeping photon signals intact. Here we demonstrate a novel ultra-narrowband interference circuit (UNIC) that can reject the capacitive response by up to 80 dB per stage with little distortion to avalanche signals. Cascading two UNIC's in a readout circuit, we were able to enable high count rate of up to 700 MC/s and low afterpulsing of 0.5 % at a detection efficiency of 25.3 % for 1.25 GHz sinusoidally gated InGaAs/InP APDs. At -30 degree C, we measured 1 % afterpulsing at a detection efficiency of 21.2 %.

quant-ph↗