Demonstration of Adiabatic Variational Quantum Computing with a Superconducting Quantum Coprocessor

Adiabatic quantum computing enables the preparation of many-body ground states. This is key for applications in chemistry, materials science, and beyond. Realisation poses major experimental challenges: Direct analog implementation requires complex Hamiltonian engineering, while the digitised version needs deep quantum gate circuits. To bypass these obstacles, we suggest an adiabatic variational hybrid algorithm, which employs short quantum circuits and provides a systematic quantum adiabatic optimisation of the circuit parameters. The quantum adiabatic theorem promises not only the ground state but also that the excited eigenstates can be found. We report the first experimental demonstration that many-body eigenstates can be efficiently prepared by an adiabatic variational algorithm assisted with a multi-qubit superconducting coprocessor. We track the real-time evolution of the ground and exited states of transverse-field Ising spins with a fidelity up that can reach about 99%.Comment: 12 pages, 4 figure

The Impact of Social Movement on Racial Diversification Initiatives: Evidence From the Movie Industry

The movie industry is facing rising advocacy for racially inclusive casting. However, it remains an open question whether the promised benefits of racial diversification will materialize. Using data from 540 movies nested in 258 sequels released from 2008 to 2021, we find that, on average, increasing the number of racial minority actors in the main cast depresses movie evaluations. More importantly, the negative effect of racial diversification attenuates after Black Lives Matter (#BLM), a new media enabled social movement. Further, incorporating insights from tokenism and discrimination theories, we probe the heterogeneity in the bias mitigation effects of #BLM and find movie type and the core production team’s credentials as important boundary conditions. The present research shows that a social movement that seeks to address racial inequality can, indeed, lead to meaningful changes in public opinions toward racial inclusive initiatives. It also provides perspectives for thinking about the mechanisms underlying such changes

The Impact of Social Movement on Racial Diversification Initiatives: Evidence From the Movie Industry

The movie industry is facing rising advocacy for racially inclusive casting. However, it remains an open question whether the promised benefits of racial diversification will materialize. Using data from 540 movies nested in 258 sequels released from 2008 to 2021, we find that, on average, increasing the number of racial minority actors in the main cast depresses movie evaluations. More importantly, the negative effect of racial diversification attenuates after Black Lives Matter (#BLM), a new media enabled social movement. Further, incorporating insights from tokenism and discrimination theories, we probe the heterogeneity in the bias mitigation effects of #BLM and find movie type and the core production team’s credentials as important boundary conditions. The present research shows that a social movement that seeks to address racial inequality can, indeed, lead to meaningful changes in public opinions toward racial inclusive initiatives. It also provides perspectives for thinking about the mechanisms underlying such changes

Fast multi-channel inverse design through augmented partial factorization

Computer-automated design and discovery have led to high-performance nanophotonic devices with diverse functionalities. However, massively multi-channel systems such as metasurfaces controlling many incident angles and photonic-circuit components coupling many waveguide modes still present a challenge. Conventional methods require $M_{\rm in}$ forward simulations and $M_{\rm in}$ adjoint simulations -- $2M_{\rm in}$ simulations in total -- to compute the objective function and its gradient for a design involving the response to $M_{\rm in}$ input channels. By generalizing the adjoint method and the recently proposed augmented partial factorization method, here we show how to obtain both the objective function and its gradient for a massively multi-channel system in a single simulation, achieving over-two-orders-of-magnitude speedup and reduced memory usage. We use this method to inverse design a metasurface beam splitter that separates the incident light to the target diffraction orders for all incident angles of interest, a key component of the dot projector for 3D sensing. This formalism enables efficient inverse design for a wide range of multi-channel optical systems

High-efficiency high-NA metalens designed by maximizing the efficiency limit

Theoretical bounds are commonly used to assess the limitations of photonic design. Here we introduce a more active way to use theoretical bounds, integrating them into part of the design process and identifying optimal system parameters that maximize the efficiency limit itself. As an example, we consider wide-field-of-view high-numerical-aperture metalenses, which can be used for high-resolution imaging in microscopy and endoscopy, but no existing design has achieved a high efficiency. By choosing aperture sizes to maximize an efficiency bound, setting the thickness according to a thickness bound, and then performing inverse design, we come up with high-numerical-aperture (NA = 0.9) metalens designs with record-high 98% transmission efficiency and 92% Strehl ratio across all incident angles within a 60-deg field of view, reaching the maximized bound. This maximizing-efficiency-limit approach applies to any multi-channel system and can help a wide range of optical devices reach their highest possible performance