Resonance-enhanced integrated acousto-optic beam steering

Abstract

Optical beam steering is a key technology for free-space optical communication, sensing, and imaging. Mechanical beam steering systems suffer from limited scanning speed and bulky form factors, while existing solid-state solutions rely on pixelated synthetic aperture that requires complex fabrication and control architectures. Integrated acousto-optic beam steering (AOBS) is an emerging technology that enables continuous one-dimensional beam steering using integrated acoustic transducers and fixed-wavelength laser sources. Here, we integrate AOBS with an optical ring resonator on the same thin-film lithium niobate (TFLN) platform to significantly enhance beam steering efficiency and system functionality. The resulting device achieves a resonance-enhanced beam steering efficiency of up to 20% over a 18 degrees field of view. Moreover, by leveraging integrated electro-optic control, we dynamically lock the ring-resonator's resonance to a chirped laser frequency, enabling frequency-modulated continuous-wave (FMCW) LiDAR operation. By combining lithium niobate's piezoelectric and electro-optic properties, this work establishes a compact, efficient, and scalable beam-steering platform with co-integrated acousto-optic modulation and electro-optic control for multifunctional applications.

Figures (12)

• Figure 1: Integrated resonance-enhanced acousto-optic beam steering (rAOBS). (a) Schematic diagram of the rAOBS device. A laser is coupled into and circulates within the racetrack resonator, where it undergoes resonance-enhanced acousto-optic scattering induced by acoustic wave generated by chirped IDTs. (b) In a single-pass AOBS, light is scattered by the acoustic wave only once, and the unscattered light is lost. (c) The rAOBS recylces the light in a resonator, which is filled with acosutic waves, to resonantly enhance the acousto-optic scattering efficiency. (d) Simulated optimal steering efficiency of AOBS and rAOBS as functions of the intrinsic $Q$ of the resonator, assuming an acousto-optic interaction length of 1 mm and an acoustic power density of $1\ \mathrm{mW/\mu m}$. (e) Optical microscope image of the rAOBS device. Scale bar: $100\ \mathrm{\mu m}$. (f) Directional coupler of acoustic wave via evanescent coupling between two acoustic waveguides. The upper panel shows optical microscope image of coupler. The lower panel shows the surface vibrometry image of the propagating acoustic wave. Both panels are stitched from two images due to the limited FOV of the imaging system. Scale bar: $10\ \mathrm{\mu m}$.
• Figure 2: Resonance-enhanced acousto-optic scattering. (a) Superimposed image of the steered beams at the focal plane when the acoustic frequencies is swept from $1.63$ to $1.86\ \mathrm{GHz}$. Spots at the left and right edges are aberrated due to the limited numerical aperture (NA) of the objective. (b) Magnified image of the beam profile when the acoustic frequency is $1.70\ \mathrm{GHz}$. The measured angular divergence is $0.180^\circ$ along the scan direction and $0.030^\circ$ perpendicular to the scan direction. (c) Evolution of the transmission spectra of the optical resonator when the RF powers used to excite the acoustic wave is increased gradually from $0$ to $100\ \mathrm{mW}$ at a fixed frequency of $1.70\ \mathrm{GHz}$. The minimum transmission points of each spectrum are projected onto the transmission-RF power plane, illustrating the progressive reduction in resonance extinction ratio with increasing RF power. (d) Measured loaded quality factor of the optical resonator as a function of the RF input power. The line shows a fit to the data. (e) Theoretical on-resonance steering efficiency calculated from panel (d), and experimentally measured on-resonance and single-pass steering efficiencies as functions of RF input power. Blue and green lines represent fits to the corresponding data, and the red line is a guide to the eye. (f) Simulated electric field distribution of the guided optical wave and the corresponding scattered field induced by the AOBS. Purple, blue, and red arrows denote the guided optical wave, acoustic wave, and the scattered fields, respectively. Beam steering occurs both in air and within the silicon substrate.
• Figure 3: Electro-optic resonance locking to a chirped laser source. (a) Illustration of electro-optic resonance locking. When the locking is off, the chirped laser sideband shifts alternately in the frequency domain, while the resonance remains fixed. When locking is on, the resonance follows the chirped sideband, resulting in enhanced beam steering. (b) Measured EO drive voltage from the PID controller, free-space beam power measured by a PD, and the error signal detected by the PID controller when locking is turned on and off. (c) Schematic of the real-time frequencies of the lights involved in the heterodyne measurement between the received anti-Stokes steered beam and a local oscillator generated by downshifting the frequency of the chirped laser sideband using an acousto-optic frequency shifter (AOFS). The Stokes light is omitted for clarity. $\Omega$, $f_A$, $f_B$, $f_E$ and $T$ denote the acoustic angular frequency, AOFS frequency, frequency shift due to propagation delay, chirp excursion, and chirp period, respectively. (d) Measured real-time beat note from the signal recorded by the OSC. The diagram is generated using short-time Fourier transform.
• Figure 4: FMCW LiDAR demonstration. (a) Schematic diagram of the measurement system for resonance locking and FMCW LiDAR demonstration. The detailed diagram of the feedback block can be found in the Supplementary Information \ref{['smsec:locking']}. AWG: arbitrary waveform generator; EOM: electro-optic modulator; EDFA: erbium-doped fiber amplifier; RSA, real-time signal analyzer; BPD: balanced photodetector; (b) Photograph of the LiDAR target. The Husky and W icons are outlined with colored lines. (c) Point cloud of the target captured by the LiDAR. (d) Representative heterodyne beat-note spectra of signals reflected from the Husky and W (points A and B in panel (c)). Each spectrum is centered around its respective acoustic frequency, 1705 MHz for point A and 1720 MHz for point B. The inner and outer pairs of peaks correspond to reflections from the distance reference reflector and the LiDAR target, respectively. (e) Zoomed-in view of two FMCW signals calculated from the data in the dash box in (d).
• Figure S1: Simulated acousto-optic scattering efficiency. (a) Dispersion diagram of rAOBS. acoustic waves (blue arrows) scatter the TE$_0$ light into the free-space light cone via Stokes and anti-Stokes processes. Inset shows the simulated TE$_0$ field and its scattered fields in free space and substrate. Material of layers from bottom to top are silicon, thermal oxide, x-cut lithium niobate, and air. (b) The blue and orange curves correspond to $\alpha_{\mathrm{air}}$ and $\alpha_{\mathrm{sub}}$, respectively. These results are simulated under an acoustic power density of $1\ \mathrm{mW}/\mathrm{\mu m}$, meaning that a $1\ \mathrm{\mu m}$-wide waveguide carries $1\ \mathrm{mW}$ of acoustic power. (c) The ratio of the optical power steered into air to the total power steered into both air and the substrate, as a function of steering angle in air. This results are calculated based on (b).