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The electric dipole moments~(EDM) of fundamental particles inherently violate parity~(P) and time-reversal~(T) symmetries. By virtue of the CPT theorem in quantum field theory, the latter also implies the violation of the combined charge-conjugation and parity~(CP) symmetry. We aim to measure the EDM of the muon using the frozen-spin technique within a compact storage trap. This method exploits the high effective electric field, \$E \approx 165\$ MV/m, experienced in the rest frame of the muon with a momentum of about 23 MeV/c when it passes through a solenoidal magnetic field of \$|\vec{B}|=2.5\$ T. In this paper, we outline the fundamental considerations for a muon EDM search and present a conceptual design for a demonstration experiment to be conducted at secondary muon beamlines of the Paul Scherrer Institute in Switzerland. In Phase~I, with an anticipated data acquisition period of 200 days, the expected sensitivity to a muon EDM is 4E-21 ecm. In a subsequent phase, Phase~II, we propose to improve the sensitivity to 6E-23 ecm using a dedicated instrument installed on a different beamline that produces muons of momentum 125 MeV/c}., Comment: 34 pages, submitted to EPJC

In this study, we investigate the relationships between film growth conditions, crystalline microstructure, and magnetic properties of epitaxial Yttrium Iron Garnet (Y$_3$Fe$_5$O$_{12}$, YIG) thin films, deposited on Gallium Gadolinium Garnet (Ga$_3$Gd$_5$O$_{12}$, GGG). A direct correlation was observed between the residual epitaxial strain, bulk magnetic properties like saturation magnetization and magnetic damping), and the performance of spin-wave transmission devices based on these films. This correlation offers a pathway for a simplified, rapid assessment of YIG film quality, avoiding the need for complex time-consuming characterization techniques. In addition, we report a comprehensive investigation into the influence of pulsed-laser deposition parameters, including deposition temperature, pressure, laser fluence, frequency, and annealing conditions. Through systematic deposition optimization, state-of-the-art YIG films exhibiting ultralow magnetic damping could be obtained, which is critical for high-performance spintronic applications., Comment: 21 pages, 4 figures. This work has received funding from the Horizon Europe research and innovation program within the project "Spider" (grant agreement no. 101070417) as well as within the MSCA-IF project "Neuromag" (grant agreement no. 793346)

Purpose: Beam angle selection is critical in proton therapy treatment planning, yet automated approaches remain underexplored. This study presents and evaluates GAMBAS, a novel, fast machine learning model for automatic beam angle selection. Methods: The model extracts a predefined set of anatomical features from a patient's CT and structure contours. Using these features, it identifies the most similar patient from a training database and suggests that patient's beam arrangement. A retrospective study with 19 patients was conducted, comparing this model's suggestions to human planners' choices and randomly selected beam arrangements from the training dataset. An expert treatment planner evaluated the plans on quality (scale 1-5), ranked them, and guessed the method used. Results: The number of acceptable (score 4 or 5) plans was comparable between human-chosen 17 (89%) and model-selected 16(84%) beam arrangements. The fully automatic treatment planning took between 4 - 7 min (mean 5 min). Conclusion: The model produces beam arrangements of comparable quality to those chosen by human planners, demonstrating its potential as a fast tool for quality assurance and patient selection, although it is not yet ready for clinical use., Comment: 8 pages, 2 figures, 1 table

The importance of computers is continually increasing in radiotherapy. Efficient algorithms, implementations and the ability to leverage advancements in computer science are crucial to improve cancer care even further and deliver the best treatment to each patient. Yet, the software landscape for radiotherapy is fragmented into proprietary systems that do not share a common interface. Further, the radiotherapy community does not have access to the vast possibilities offered by modern programming languages and their ecosystem of libraries yet. We present JulianA.jl, a novel Julia package for radiotherapy. It aims to provide a modular and flexible foundation for the development and efficient implementation of algorithms and workflows for radiotherapy researchers and clinicians. JulianA.jl can be interfaced with any scriptable treatment planning system, be it commercial, open source or in-house developed. This article highlights our design choices and showcases the package's simplicity and powerful automatic treatment planning capabilities.

Interconnect resistance and reliability have emerged as critical factors limiting the performance of advanced CMOS circuits. With the slowdown of transistor scaling, interconnect scaling has become the primary driver of continued circuit miniaturization. The associated scaling challenges for interconnects are expected to further intensify in future CMOS technology nodes. As interconnect dimensions approach the 10 nm scale, the limitations of conventional Cu dual-damascene metallization are becoming increasingly difficult to overcome, spurring over a decade of focused research into alternative metallization schemes. The selection of alternative metals is a highly complex process, requiring consideration of multiple criteria, including resistivity at reduced dimensions, reliability, thermal performance, process technology readiness, and sustainability. This tutorial introduces the fundamental criteria for benchmarking and selecting alternative metals and reviews the current state of the art in this field. It covers materials nearing adoption in high-volume manufacturing, materials currently under active research, and potential future directions for fundamental study. While early alternatives to Cu metallization have recently been introduced in commercial CMOS devices, the search for the optimal interconnect metal remains ongoing., Comment: 74 pages, 27 figures, 5 Tables

Vico et al. (2016) suggest a fast algorithm for computing volume potentials, beneficial to fields with problems requiring the solution of Poisson's equation with free-space boundary conditions, such as the beam and plasma physics communities. Currently, the standard method for solving the free-space Poisson equation is the algorithm of Hockney and Eastwood (1988), which is second order in convergence at best. The algorithm proposed by Vico et al. converges spectrally for sufficiently smooth functions i.e. faster than any fixed order in the number of grid points. In this paper, we implement a performance portable version of the traditional Hockney-Eastwood and the novel Vico-Greengard Poisson solver as part of the IPPL (Independent Parallel Particle Layer) library. For sufficiently smooth source functions, the Vico-Greengard algorithm achieves higher accuracy than the Hockney-Eastwood method with the same grid size, reducing the computational demands of high resolution simulations since one could use coarser grids to achieve them. More concretely, to get a relative error of $10^{-4}$ between the numerical and analytical solution, one requires only $16^3$ grid points in the former, but $128^3$ in the latter, more than a 99% memory footprint reduction. Additionally, we propose an algorithmic improvement to the Vico-Greengard method which further reduces its memory footprint. This is particularly important for GPUs which have limited memory resources, and should be taken into account when selecting numerical algorithms for performance portable codes. Finally, we showcase performance through GPU and CPU scaling studies on the Perlmutter (NERSC) supercomputer, with efficiencies staying above 50% in the strong scaling case., Comment: 18 pages, 11 figures

Cu$_x$Al$_{1-x}$ thin films with $0.2 \le x \le 0.7$ have been studied as potential alternatives for the metallization of advanced interconnects. First-principles simulations were used to obtain the Cu$_x$Al$_{1-x}$ electronic structure and cohesive energy to benchmark different intermetallics and their prospects for interconnect metallization. Next, thin Cu$_x$Al$_{1-x}$ films were deposited by PVD with thicknesses in the range between 3 and 28 nm. The lowest resistivities of 9.5 $\mu\Omega$cm were obtained for 28 nm thick stochiometric CuAl and CuAl$_2$ after 400$^\circ$C post-deposition annealing. Based on the experimental results, we discuss the main challenges for the studied aluminides from an interconnect point of view, namely the control of the film stoichiometry, the phase separation observed for off-stoichiometric CuAl and CuAl$_2$, as well as the presence of a nonstoichiometric surface oxide., Comment: 24 pages, 7 figures

While Spin Waves (SW) interaction provides natural support for low power Majority (MAJ) gate implementations many hurdles still exists on the road towards the realization of practically relevant SW circuits. In this paper we leave the SW interaction avenue and propose Threshold Logic (TL) inspired SW computing, which relies on successive phase rotations applied to one single SW instead of on the interference of an odd number of SWs. After providing a short TL inside we introduce the SW TL gate concept and discuss the way to mirror TL gate weight and threshold values into physical phase-shifter parameters. Subsequently, we design and demonstrate proper operation of a SW TL based Full Adder (FA) by means of micro-magnetic simulations. We conclude the paper by providing inside on the potential advantages of our proposal by means of a conceptual comparison of MAJ and TL based FA implementations., Comment: This work has received funding from the Horizon Europe research and innovation program within the project "Spider" (grant agreement no. 101070417)

In response to aggressive scaling demands in semiconductor manufacturing and the growing need to apply sustainable practices, this paper presents a holistic sustainability assessment framework for evaluating alternative metals for advanced applications. The framework, consisting of seven sustainability aspects, aims to guide researchers and industry stakeholders towards decisions fostering a more sustainable and secure future for microelectronics. This study applies the framework to assess the sustainability of alternative local interconnect metals. The framework identifies five metals (Ti, Al, Ni, Co, and Mo) with relatively favourable performance in at least six out of nine specific indicators, while others (Pt, Ru, Ir, Rh, and Pd) exhibit poorer sustainability metrics. The study recommends further analyses, suggesting the incorporation of case-specific functional units and the use of normalization and weighting factors for a comprehensive evaluation. Coupled with traditional technological assessments, this framework equips decision-makers with essential tools to broaden criteria for selecting alternative metals, aligning semiconductor manufacturing with broader sustainability objectives., Comment: 20 pages, 5 Figures, 5 Tables, 12 equations

This study introduces a method for the characterization of the magnetoelectric coupling in nanoscale Pb(Zr,Ti)O3/CoFeB thin film composites based on propagating spin-wave spectroscopy. Finite element simulations of the strain distribution in the devices indicated that the magnetoelastic effective field in the CoFeB waveguides was maximized in the Damon - Eshbach configuration. All-electrical broadband propagating spin-wave transmission measurements were conducted on Pb(Zr,Ti)O3/CoFeB magnetoelectric waveguides with lateral dimensions down to 700 nm. The results demonstrated that the spin-wave resonance frequency can be modulated by applying a bias voltage to Pb(Zr,Ti)O3. The modulation is hysteretic due to the ferroelastic behavior of Pb(Zr,Ti)O3. An analytical model was then used to correlate the change in resonance frequency to the induced magnetoelastic field in the magnetostrictive CoFeB waveguide. We observe a hysteresis magnetoelastic field strength with values as large as 5.61 mT, and a non-linear magnetoelectric coupling coefficient with a maximum value of 1.69 mT/V., Comment: This project has received funding from the European Union's Horizon Europe research and innovation programme under grant agreement No 101070536 - project MandMEMS

Al$_x$Sc$_{1-x}$ thin films have been studied with compositions around Al$_3$Sc ($x$ = 0.75) for potential interconnect metallization applications. As-deposited 25 nm thick films were x-ray amorphous but crystallized at 190{\deg}C, followed by recrystallization at 440{\deg}C. After annealing at 500{\deg}C, 24 nm thick stoichiometric Al$_3$Sc showed a resistivity of 12.6 $\mu\Omega$cm, limited by a combination of grain boundary and point defect (disorder) scattering. Together with ab initio calculations that found a mean free path of the charge carriers of 7 nm for stoichiometric Al$_3$Sc, these results indicate that Al$_3$Sc bears promise for future interconnect metallization schemes. Challenges remain in minimizing the formation of secondary phases as well as in the control of the non-stoichiometric surface oxidation and interfacial reactions with underlying dielectrics., Comment: 17 pages, 4 figures. Accepted version

The recently developed method Lasso Monte Carlo (LMC) for uncertainty quantification is applied to the characterisation of spent nuclear fuel. The propagation of nuclear data uncertainties to the output of calculations is an often required procedure in nuclear computations. Commonly used methods such as Monte Carlo, linear error propagation, or surrogate modelling suffer from being computationally intensive, biased, or ill-suited for high-dimensional settings such as in the case of nuclear data. The LMC method combines multilevel Monte Carlo and machine learning to compute unbiased estimates of the uncertainty, at a lower computational cost than Monte Carlo, even in high-dimensional cases. Here LMC is applied to the calculations of decay heat, nuclide concentrations, and criticality of spent nuclear fuel placed in disposal canisters. The uncertainty quantification in this case is crucial to reduce the risks and costs of disposal of spent nuclear fuel. The results show that LMC is unbiased and has a higher accuracy than simple Monte Carlo., Comment: Conference paper from the 12th International Conference on Nuclear Criticality Safety (ICNC), Sendai, Japan, October 2023. Submitted to the Arxiv with the permission of the conference organisers

The accurate calculation and uncertainty quantification of the characteristics of spent nuclear fuel (SNF) play a crucial role in ensuring the safety, efficiency, and sustainability of nuclear energy production, waste management, and nuclear safeguards. State of the art physics-based models, while reliable, are computationally intensive and time-consuming. This paper presents a surrogate modeling approach using neural networks (NN) to predict a number of SNF characteristics with reduced computational costs compared to physics-based models. An NN is trained using data generated from CASMO5 lattice calculations. The trained NN accurately predicts decay heat and nuclide concentrations of SNF, as a function of key input parameters, such as enrichment, burnup, cooling time between cycles, mean boron concentration and fuel temperature. The model is validated against physics-based decay heat simulations and measurements of different uranium oxide fuel assemblies from two different pressurized water reactors. In addition, the NN is used to perform sensitivity analysis and uncertainty quantification. The results are in very good alignment to CASMO5, while the computational costs (taking into account the costs of generating training samples) are reduced by a factor of 10 or more. Our findings demonstrate the feasibility of using NNs as surrogate models for fast characterization of SNF, providing a promising avenue for improving computational efficiency in assessing nuclear fuel behavior and associated risks.

Creating high quality treatment plans is crucial for a successful radiotherapy treatment. However, it demands substantial effort and special training for dosimetrists. Existing automated treatment planning systems typically require either an explicit prioritization of planning objectives, human-assigned objective weights, large amounts of historic plans to train an artificial intelligence or long planning times. Many of the existing auto-planning tools are difficult to extend to new planning goals. A new spot weight optimisation algorithm, called JulianA, was developed. The algorithm minimises a scalar loss function that is built only based on the prescribed dose to the tumour and organs at risk (OARs), but does not rely on historic plans. The objective weights in the loss function have default values that do not need to be changed for the patients in our dataset. The system is a versatile tool for researchers and clinicians without specialised programming skills. Extending it is as easy as adding an additional term to the loss function. JulianA was validated on a dataset of 19 patients with intra- and extracerebral neoplasms within the cranial region that had been treated at our institute. For each patient, a reference plan which was delivered to the cancer patient, was exported from our treatment database. Then JulianA created the auto plan using the same beam arrangement. The reference and auto plans were given to a blinded independent reviewer who assessed the acceptability of each plan, ranked the plans and assigned the human-/machine-made labels. The auto plans were considered acceptable in 16 out of 19 patients and at least as good as the reference plan for 11 patients. Whether a plan was crafted by a dosimetrist or JulianA was only recognised for 9 cases. The median time for the spot weight optimisation is approx. 2 min (range: 0.5 min - 7 min).

We have studied the effect of chemical-mechanical polishing (CMP) on the ferroelectric, piezoelectric, and microwave dielectric properties of Ba-substituted PZT (BPZT), deposited by pulsed laser deposition. CMP allowed for the reduction of the root mean square surface roughness of 600 nm thick BPZT films from 12.1nm to 0.79 nm. Ammonium peroxide (SC-1) cleaning was effective to remove Si CMP residuals. Measurements of the ferroelectric hysteresis after CMP indicated that the ferroelectric properties of BPZT were only weakly affected by CMP, while the piezoelectric d33 coefficient and the microwave permittivity were reduced slightly by 10%. This can be attributed to the formation of a thin dead layer at the BPZT surface. Moreover, the intrinsic dielectric permittivity at microwave frequencies between 1 and 25 GHz was not influenced by CMP, whereas the dead layer series capacitance decreased by 10%. The results indicate that the CMP process can be used to smoothen the BPZT surface without affecting the film properties strongly., Comment: 13 pages of text, 4 tables and 7 figures. This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 801055 "Spin Wave Computing for Ultimately-Scaled Hybrid Low-Power Electronics" - CHIRON

Unforeseen particle accelerator interruptions, also known as interlocks, lead to abrupt operational changes despite being necessary safety measures. These may result in substantial loss of beam time and perhaps even equipment damage. We propose a simple yet powerful binary classification model aiming to forecast such interruptions, in the case of the High Intensity Proton Accelerator complex at the Paul Scherrer Institut. The model is formulated as logistic regression penalized by least absolute shrinkage and selection operator, based on a statistical two sample test to distinguish between unstable and stable states of the accelerator. The primary objective for receiving alarms prior to interlocks is to allow for countermeasures and reduce beam time loss. Hence, a continuous evaluation metric is developed to measure the saved beam time in any period, given the assumption that interlocks could be circumvented by reducing the beam current. The best-performing interlock-to-stable classifier can potentially increase the beam time by around 5 min in a day. Possible instrumentation for fast adjustment of the beam current is also listed and discussed., Comment: 12 pages, 13 figures

A summary of numerical modeling capabilities regarding high power cyclotrons and fixed field alternating gradient machines is presented. This paper focuses on techniques made available by the OPAL simulation code., Comment: arXiv admin note: text overlap with arXiv:2203.07919

Uncertainty quantification (UQ) is an active area of research, and an essential technique used in all fields of science and engineering. The most common methods for UQ are Monte Carlo and surrogate-modelling. The former method is dimensionality independent but has slow convergence, while the latter method has been shown to yield large computational speedups with respect to Monte Carlo. However, surrogate models suffer from the so-called curse of dimensionality, and become costly to train for high-dimensional problems, where UQ might become computationally prohibitive. In this paper we present a new technique, Lasso Monte Carlo (LMC), which combines a Lasso surrogate model with the multifidelity Monte Carlo technique, in order to perform UQ in high-dimensional settings, at a reduced computational cost. We provide mathematical guarantees for the unbiasedness of the method, and show that LMC can be more accurate than simple Monte Carlo. The theory is numerically tested with benchmarks on toy problems, as well as on a real example of UQ from the field of nuclear engineering. In all presented examples LMC is more accurate than simple Monte Carlo and other multifidelity methods. Thanks to LMC, computational costs are reduced by more than a factor of 5 with respect to simple MC, in relevant cases.

Particle accelerators are complex facilities that produce large amounts of structured data and have clear optimization goals as well as precisely defined control requirements. As such they are naturally amenable to data-driven research methodologies. The data from sensors and monitors inside the accelerator form multivariate time series. With fast pre-emptive approaches being highly preferred in accelerator control and diagnostics, the application of data-driven time series forecasting methods is particularly promising. This review formulates the time series forecasting problem and summarizes existing models with applications in various scientific areas. Several current and future attempts in the field of particle accelerators are introduced. The application of time series forecasting to particle accelerators has shown encouraging results and the promise for broader use, and existing problems such as data consistency and compatibility have started to be addressed., Comment: 13 pages, 11 figures

This paper addresses the question: Can spintronic circuits based on Magnetic Tunnel Junction (MTJ) transducers outperform their state-of-the-art CMOS counterparts? To this end, we use the EPFL combinational benchmark sets, synthesize them in 7 nm CMOS and in MTJ-based spintronic technologies, and compare the two implementation methods in terms of Energy-Delay-Product (EDP). To fully utilize the technologies potential, CMOS and spintronic implementations are built upon standard Boolean and Majority Gates, respectively. For the spintronic circuits, we assumed that domain conversion (electric/magnetic to magnetic/electric) is performed by means of MTJs and the computation is accomplished by domain wall based majority gates, and considered two EDP estimation scenarios: (i) Uniform Benchmarking, which ignores the circuit's internal structure and only includes domain transducers power and delay contributions into the calculations, and (ii) Majority-Inverter-Graph Benchmarking, which also embeds the circuit structure, the associated critical path delay and energy consumption by DW propagation. Our results indicate that for the uniform case, the spintronic route is better suited for the implementation of complex circuits with few inputs and outputs. On the other hand, when the circuit structure is also considered via majority and inverter synthesis, our analysis clearly indicates that in order to match and eventually outperform CMOS performance, MTJ efficiency has to be improved by 3-4 orders of magnitude. While it is clear that for the time being the MTJ-based-spintronic way cannot compete with CMOS, further transducer developments may tip the balance, which, when combined with information non-volatility, may make spintronic implementation for certain applications that require a large number of calculations and have a rather limited amount of interaction with the environment., Comment: This work was supported by imec Industrial Affiliation Program on Exploratory Logic Devices. It has also received funding from the European Union Horizon Europe research and innovation programme within the project SPIDER under grant agreement No 101070417

We perform a scaling and performance portability study of the particle-in-cell scheme for plasma physics applications through a set of mini-apps we name "Alpine", which can make use of exascale computing capabilities. The mini-apps are based on Independent Parallel Particle Layer, a framework that is designed around performance portable and dimension independent particles and fields. We benchmark the simulations with varying parameters such as grid resolutions ($512^3$ to $2048^3$) and number of simulation particles ($10^9$ to $10^{11}$) with the following mini-apps: weak and strong Landau damping, bump-on-tail and two-stream instabilities, and the dynamics of an electron bunch in a charge-neutral Penning trap. We show strong and weak scaling and analyze the performance of different components on several pre-exascale architectures such as Piz-Daint, Cori, Summit and Perlmutter. While the scaling and portability study helps identify the performance critical components of the particle-in-cell scheme in the current state-of-the-art computing architectures, the mini-apps by themselves can be used to develop new algorithms and optimize their high performance implementations targeting exascale architectures.

In the early stages of a novel technology development, it is difficult to provide a comprehensive assessment of its potential capabilities and impact. Nevertheless, some preliminary estimates can be drawn and are certainly of great interest and in this paper we follow this line of reasoning within the framework of the Spin Wave (SW) computing paradigm. In particular, we are interested in assessing the technological development horizon that needs to be reached in order to unleash the full SW paradigm potential such that SW circuits can outperform CMOS counterparts in terms of energy consumption. In view of the zero power SWs propagation through ferromagnetic waveguides, the overall SW circuit power consumption is determined by the one associated to SWs generation and sensing by means of transducers. While current antenna based transducers are clearly power hungry recent developments indicate that magneto-electric (ME) cells have a great potential for ultra-low power SW generation and sensing. Given that MEs have been only proposed at the conceptual level and no actual experimental demonstration has been reported we cannot evaluate the impact of their utilization on the SW circuit energy consumption. However, we can perform a reverse engineering alike analysis to determine ME delay and power consumption upper bounds that can place SW circuits in the leading position. To this end, we utilize a 32-bit Brent-Kung Adder (BKA) as discussion vehicle and compute the maximum ME delay and power consumption that could potentially enable a SW implementation able to outperform its 7nm CMOS counterpart. We evaluate different BKA SW implementations that rely on conversion or normalization gate cascading and consider continuous or pulsed SW generation scenarios. 31nW is the maximum transducer power consumption for which a 32-bit BKA SW implementation can outperform its 7nm CMOS counterpart., Comment: This work has received funding from the European Union's Horizon 2020 research and innovation program within the FET-OPEN project CHIRON under grant agreement No. 801055

We derive an analytical model for the power transfer in a magnetoelectric film bulk acoustic resonator consisting of a piezoelectric--magnetostrictive bilayer. The model describes the dynamic magnetostrictive influence on the elastodynamics via an effective frequency-dependent stiffness constant. This allows for the calculation of both the magnetic and elastic power absorption in the resonator as well as of its energy efficiency when such a resonator is considered as a magnetic transducer. The model is then applied to example systems consisting of piezoelectric ScAlN and magnetostrictive CoFeB, Ni, or Terfenol-D layers., Comment: 39 pages, 9 figures. This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 801055 "Spin Wave Computing for Ultimately-Scaled Hybrid Low-Power Electronics" - CHIRON

This whitepaper summarizes and the state of the field of high-power cyclotrons and FFAs as discussed by international experts during a three-day workshop of the same name. The workshop was held online from Sep 7 to Sep 9, 2021 as part of the US Snowmass'21 Community Exercise, specifically the Accelerator Frontier (AF) and the subpanel Accelerators for Neutrinos (AF02). Thus, we put emphasis on the application of high-power cyclotrons in particle physics, specifically neutrino physics, and as drivers for muon production. In the introduction, we discuss the role of cyclotrons for particle physics, and later we highlight existing and planned experiments in the corresponding sections. However, as these same accelerators have important applications in the fields of isotope production - both for research and medicine - and possibly even in energy research, by providing beam to demonstrator experiments in the areas of Accelerator Driven Systems (ADS), we include these far-reaching topics to provide a full picture of the status and applications of high-power cyclotrons. Furthermore, Fixed Field Alternating Gradient accelerators (FFAs) have recently seen renewed interest. They are in many respects (basic operating principles) similar to cyclotrons and have thus been included in this workshop and whitepaper as well. We are discussing current projects and whether FFAs have the prospect of becoming high-intensity machines., Comment: contribution to Snowmass 2021

The computational cost for high energy physics detector simulation in future experimental facilities is going to exceed the current available resources. To overcome this challenge, new ideas on surrogate models using machine learning methods are being explored to replace computationally expensive components. Additionally, differentiable programming has been proposed as a complementary approach, providing controllable and scalable simulation routines. In this document, new and ongoing efforts for surrogate models and differential programming applied to detector simulation are discussed in the context of the 2021 Particle Physics Community Planning Exercise (`Snowmass')., Comment: contribution to Snowmass 2021