To submit a request, click below on the link of the version you wish to order. Rules for end-users are available here.
| Program name | Package id | Status | Status date |
|---|---|---|---|
| PHITS-3.X | NEA-1931/01 | Arrived | 16-OCT-2023 |
Machines used:
| Package ID | Orig. computer | Test computer |
|---|---|---|
| NEA-1931/01 | MAC,Linux-based PC,PC Windows |
The PHITS official website is available at https://phits.jaea.go.jp/
A PHITS forum is available at PHITS Forum (kyushu-u.ac.jp)
PHITS can deal with the transport of almost all particles (nucleons, nuclei, mesons, photons, and electrons) over wide energy ranges, using several nuclear reaction models and nuclear data libraries (Iwase et al 2002, Niita et al 2006, Sihver et al 2010, Niita et al 2010, Sato et al 2013, and Sato et al 2018). The accuracy of PHITS has been well verified by various benchmark calculations (Iwamoto et al 2017 and 2021). Geometrical configuration of the simulation can be set with GG (General Geometry). Various quantities such as heat deposition, track length and production yields can be deduced from the simulation, using implemented estimator functions called "tally". The code also has a function to draw 2D and 3D figures of the calculated results as well as the setup geometries, using codes named ANGEL and PHIG-3D.
The physical processes included in PHITS can be divided into transport and collision processes. In the transport process, PHITS can simulate motion of particles under external fields such as magnetic and gravity. Without the external fields, neutral particles move along a straight trajectory with constant energy up to the next collision point. However, charge particles interact many times with electrons in the material losing energy and changing direction. PHITS treats ionization processes not as collision but as a transport process based on the continuous-slowing-down approximation, except when the track-structure algorithm is activated. The average stopping power is given by the charge density of the material and the momentum of the particle taking into account the fluctuations of the energy loss and the angular deviation.
In the collision process, PHITS can simulate the elastic and inelastic interactions as well as decay of particles. The total reaction cross section, or the life time of the particle is an essential quantity in the determination of the mean free path of the transport particle. According to the mean free path, PHITS chooses the next collision point using the Monte Carlo method. To generate the secondary particles of the collision, we need the information of the final states of the collision. For neutron induced reactions in low energy region, PHITS employs the cross sections from evaluated nuclear data libraries JENDL-4.0 (Shibata et al 2011). For high energy neutrons and other particles, we have incorporated several models such as JAM (Nara et al 1999), INCL (Boudard), INCL-ELF (Sawada et al 2012), JQMD (Niita et al 1995, Ogawa et al 2015), and JAMQMD (Ogawa et al 2018) to simulate nuclear reactions up to 1 TeV/u.
The special features of PHITS are the event generator mode (Ogawa et al 2014A) and the microdosimetric function (Sato et al 2009). Owing to the event generator mode, PHITS can determine the profiles of all secondary particles generated from a single nuclear interaction even using nuclear data libraries, taking the momentum and energy conservations into account. The microdosimetric function gives the probability densities of deposition energy in microscopic sites such as lineal energy y and specific energy z, using the mathematical model developed based on the results of the track structure simulation. These features are very important for various purposes such as the estimations of soft-error rates of semi-conductor devices induced by neutrons, and relative biological effectiveness of charged particles.
From version 2.64, Prompt gamma spectrum and isomer production rates can be precisely estimated, owing to the implementation of EBITEM (ENSDF-Based Isomeric Transition and isomEr production Model)(Ogawa et al 2014B). The photo-nuclear reaction model was improved up to 140 MeV.
From version 2.76, electron and photon transport algorithm based on EGS5 (Hirayama et al. 2005) was incorporated. Models for describing photo-nuclear reaction above 140 MeV and muon-nuclear reaction were implemented. Event-generator mode version 2 was developed. Relativistic theory can be considered in the JQMD model.
From version 2.82, the function to read tetrahedral geometry (a kind of polygonal geometry) was implemented. Model for describing nuclear resonance florescence (NRF) was implemented. Point estimator tally (t-point) was developed.
From version 2.88, the functions to output the tally results in xyz-mesh in the input format of ParaView has been implemented. The RI source generation function and weight window generator have also been implemented.
From version 3.33, the following functions, algorithms, and software have been implemented.
Track structure algorithm based on ets-mode, KURBUC, and ITSART (Matsuya et al 2021A and 2021B, Ogawa et al 2021)
Function to generate xyz-mesh distribution source
Function to reproduce cosmic-ray environments in the atmosphere, low-earth orbits, and deep space
PHITS-DCHAIN with updated activation cross section libraries for more precise burnup calculation (Ratliff et al 2020)
JAMQMD for simulating nucleus-nucleus interaction above 3 GeV/n (Ogawa et al 2018)
Function to read magnetic field map written in xyz or r-z grid
Coupling algorithm with thermal analysis software such as ANSYS Fluent
Algorithm for calculating DNA damage yield based on the results of track structure simulation (Matsuya et al 2020)
Function to estimate systematic uncertainties of the tally results based on ANOVA (Hashimoto et al 2019)
New pseudo-random number generator based on xorshift64 (Marsaglia 2003)
New fission model applicable to sub-actinide
Algorithm for adjoint Monte Carlo simulation for photons (Malins et al 2017)
Function to calculate the response function of organic scintillator based on SCINFUL-QMD (Satoh et al 2022)
Function to calculate athermal-recombination-corrected (arc) DPA (Iwamoto et al 2020)
Function to analyze the multiply tally results named anatally
RT-PHITS for applying PHITS to medical physics (Furuta et al 2022, Sato et al 2021)
PHIG-3D for interactively drawing the geometry in 3D
Function to read the nuclear data libraries for deuteron, alpha, and photonuclear reactions
JENDL-5 for some nuclei (Iwamoto et al 2023)
The Monte Carlo method is used. Higher-energy nuclear reactions are generally simulated by either intra-nuclear cascade or quantum-molecular dynamics models coupled with the evaporation model. Low-energy nuclear reactions are generally simulated using nuclear data libraries. Atomic interactions are generally simulated by the condensed-history method, but the algorithms for event-by-event analysis, so-called track-structure simulation, are also implemented. These calculation methods can be changed by input file.
The distribution package includes:
PHIG-3D for visualizing geometry in 3D
ANGEL for visualizing geometry and tally results
DCHAIN-PHITS for burnup calculation
RT-PHITS for radiotherapy purpose such as conversion from DICOM CT and PET/SPECT images to PHITS input format as well as from PHITS output dose distributions to DICOM RT-dose format
The PHITS official website is available at https://phits.jaea.go.jp/
A PHITS forum is available at PHITS Forum (kyushu-u.ac.jp)
A. Boudard, J. Cugnon, J.C. David, S. Leray, and D. Mancusi, New potentialities of the Liege intranuclear cascade model for reactions induced by nucleons and light charged particles, Phys. Rev. C 87, 014606 (2013).
T. Furuta, Y. Koba, S. Hashimoto, W. Chang, S. Yonai, S. Matsumoto, A. Ishikawa, T. Sato, Development of the DICOM-based Monte Carlo dose reconstruction system for a retrospective study on the secondary cancer risk in carbon ion radiotherapy, Phys. Med. Biol. 67 145002 (2022).
S. Hashimoto and T. Sato, Estimation method of systematic uncertainties in Monte Carlo particle transport simulation based on analysis of variance, J. Nucl. Sci. Technol. 56(4), 345-354 (2019).
H. Hirayama, Y. Namito, A.F. Bielajew, S.J. Wilderman and W.R. Nelson: “The EGS5 Code System” SLAC-R-730 (2005) and KEK Report 2005-8 (2005)
O. Iwamoto, N. Iwamoto, S. Kunieda, F. Minato, S. Nakayama, Y. Abe, et al., "Japanese evaluated nuclear data library version 5: JENDL-5", J. Nucl. Sci. Technol., 60(1), 1-60 (2023).
Y. Iwamoto, T. Sato, S. Hashimoto, T. Ogawa, T. Furuta, S. Abe, T. Kai, N. Matsuda, R. Hosoyamada, K. Niita, Benchmark study of the recent version of the PHITS code, J. Nucl. Sci. Technol. 54, 617-635 (2017).
Y. Iwamoto, S. Meigo, H. Hashimoto, Estimation of reliable displacements-per-atom based on athermal-recombination-corrected model in radiation environments at nuclear fission, fusion, and accelerator facilities, J. Nucl. Materials 538, 152261 (2020).
Y. Iwamoto, S. Hashimoto, T. Sato, N. Matsuda, S. Kunieda, Y. Çelik, N. Furutachi, K. Niita, Benchmark study of particle and heavy-ion transport code system using shielding integral benchmark archive and database for accelerator-shielding experiments, J. Nucl. Sci. Technol. 59, 665-675 (2021).
H. Iwase, K. Niita, T. Nakamura: "Development of general-purpose particle and heavy ion transport Monte Carlo code", J. Nucl. Sci. and Technol. 39, 1142 (2002).
A. Malins, M. Machida, K. Niita, Continuous energy adjoint transport for photons in PHITS, EPJ Web of Conferences, 153, p.06001_1-06001_9 (2017).
G. Marsaglia, Xorshift RNGs. Journal of Statistical Software. 8, 14, 1-6 (2003).
Y. Matsuya, T. Nakano, T. Kai, N. Shikazono, K. Akamatsu, Y. Yoshii, T. Sato, A Simplified Cluster Analysis of Electron Track Structure for Estimating Complex DNA Damage Yields, Int. J. Mol. Sci. 21, 1701 (2020)
Y. Matsuya, T. Kai, T. Sato, T. Ogawa, Y. Hirata, Y. Yoshii, A. Parisi, T. Liamsuwan, Track-structure modes in particle and heavy ion transport code system (PHITS): application to radiobiological research, Int. J. Radiat. Biol. (2021A).
Y. Matsuya, T. Kai, T. Sato, T. Liamsuwan, K. Sasaki, H. Nikjoo, Verification of KURBUC-based ion track structure mode for proton and carbon ions in the PHITS code, Phys. Med. Biol. 66, 06NT02 (2021B)
Y. Nara, N. Otuka, A. Ohnishi, K. Niita, S. Chiba: "Relativistic nuclear collisions at 10A GeV energies from p+Be to Au+Au with the hadronic cascade model", Phys. Rev. C61, 024901 (1999).
Y. Sawada, Y. Uozumi, S. Nogamine, T. Yamada, Y. Iwamoto, T. Sato and K. Niita: "Intranuclear cascade with emission of light fragment code implemented in the transport code system PHITS", Nucl. Instr. Meth. B 291, 38-44 (2012).
K. Niita, T. Sato, H. Iwase, H. Nose, H. Nakashima, L. Sihver: "PHITS- a particle and heavy ion transport code system", Radiation Measurements 41, 1080 (2006).
K. Niita, S. Chiba, T. Maruyama, H. Takada, T. Fukahori, Y. Nakahara and A. Iwamoto: "Analysis of the (N,Xn') reactions by quantum molecular dynamics plus statistical decay model", Phys. Rev. C 52, 2620 (1995)
T. Ogawa, T. Sato, S. Hashimoto, K. Niita, Development of a reaction ejectile sampling algorithm to recover kinematic correlations from inclusive cross-section data in Monte-Carlo particle transport simulations, Nucl. Instr. Meth. A 763, 575-590 (2014A).
T. Ogawa, S. Hashimoto, T. Sato, K. Niita, Development of gamma de-excitation model for prediction of prompt gamma-rays and isomer production based on energy-dependent level structure treatment, Nucl. Instr. Meth. B 325, 35-42 (2014B).
T. Ogawa, T. Sato, S. Hashimoto, D. Satoh, S. Tsuda, and K. Niita, Energy-dependent fragmentation cross sections of relativistic 12C, Phys. Rev. C 92, 024614 (2015).
T. Ogawa, T. Sato, S. Hashimoto, K. Niita, Cluster formation in relativistic nucleus-nucleus collisions, Phys. Rev. C 98, 024611 (2018) T. Ogawa, Y. Hirata, Y. Matsuya, T. Kai, Development and validation of proton track-structure model applicable to arbitrary materials, Sci. Rep. 11, 24401 (2021).
H.N. Ratliff, N. Matsuda, S. Abe, T. Miura, T. Furuta, Y. Iwamoto, T. Sato, Modernization of the DCHAIN-PHITS activation code with new features and updated data libraries, Nucl. Instr. Meth. B 484, 29-41 (2020).
T. Sato, Y. Kase, R. Watanabe, K. Niita and L. Sihver: "Biological dose estimation for charged-particle therapy using an improved PHITS code coupled with a microdosimetric kinetic model", Radiat. Res. 171, 107-117 (2009)
T. Sato, K. Niita, N. Matsuda, S. Hashimoto, Y. Iwamoto, S. Noda, T. Ogawa, H. Iwase, H. Nakashima, T. Fukahori, K. Okumura, T. Kai, S. Chiba, T. Furuta and L. Sihver, "Particle and Heavy Ion Transport Code System PHITS, Version 2.52", J. Nucl. Sci. Technol. 50, 913-923 (2013).
T. Sato, Y. Iwamoto, S. Hashimoto, T. Ogawa, T. Furuta, S. Abe, T. Kai, P.E. Tsai, N. Matsuda, H. Iwase, N. Shigyo, L. Sihver and K. Niita, Features of Particle and Heavy Ion Transport Code System PHITS Version 3.02, J. Nucl. Sci. Technol. 55, 684-690 (2018).
T. Sato, T. Furuta, Y. Liu, S. Naka, S. Nagamori, Y. Kanai, T. Watabe, Individual Dosimetry System for Targeted Alpha Therapy Based on PHITS Coupled with Microdosimetric Kinetic Model, EJNMMI Physics 8: 4 (2021).
D. Satoh, T. Sato, Improvements in the particle and heavy-ion transport code system (PHITS) for simulating neutron-response functions and detection efficiencies of a liquid organic scintillator, J. Nucl. Sci. Technol. (2022).
L. Sihver, T. Sato, K. Gustafsson, D. Mancusi, H. Iwase, K. Niita, H. Nakashima, Y. Sakamoto, Y. Iwamoto and N. Matsuda: "An update about recent developments of the PHITS code" Adv. Space Res. 45, 892-899 (2010).
K. Shibata, O. Iwamoto, T. Nakagawa, N. Iwamoto, A. Ichihara, S. Kunieda, S. Chiba, K. Furutaka, N. Otuka, T. Ohsawa, H. Matsunobu, A. Zukeran, S. Kamada and J. Katakura: "JENDL-4.0: A New Library for Nuclear Science and Engineering", J. Nucl. Sci. Technol. 48, 1-30 (2011).
Tatsuhiko Sato, Yosuke Iwamoto, Shintaro Hashimoto, Tatsuhiko Ogawa, Takuya Furuta, Shinichiro Abe, Takeshi Kai, Norihiro Matsuda, Lan Yao, Yusuke Matsuya, Hunter Ratliff*, Pi-En Tsai**
Japan Atomic Energy Agency, Tokai, Ibaraki, Japan
*Current affiliation: Western Norway University of Applied Sciences, Norway
**Current affiliation: Zap Energy, USA
Hiroshi Iwase, Yasuhito Sakaki
High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki, Japan
Nobuhiro Shigyo
Kyushu University, Fukuoka, Japan
Lembit Sihver
Technische Universität Wien, Austria
Koji Niita
Research Organization for Information Science and Technology, Tokai, Ibaraki, Japan
Keywords: Monte Carlo method, heavy ions, nuclear data, nuclear reactions, particle transport.
