Mathematics Major
A mathematics degree from Harvey Mudd College will prepare students for a variety of careers in business, industry or academics. Mathematical methods are increasingly employed in fields as diverse as finance, biomedical research, management science, the computer industry and most technical and scientific disciplines. To support the academic and professional goals of our majors, we offer a wide selection of courses in both pure and applied mathematics. This selection is enhanced by courses offered in cooperation with the other Claremont Colleges, including graduate courses at the Claremont Graduate University.
Students will have many opportunities to do mathematical research with faculty through independent study, a summer research experience, or their senior capstone experience. Active areas of mathematical research at HMC and The Claremont Colleges include algebra, algebraic geometry, algorithms and computational complexity, combinatorics, differential geometry, dynamical systems, fluid mechanics, graph theory, number theory, numerical analysis, mathematical biology, mathematics education, operations research, partial differential equations, real and complex analysis, statistical methods and analysis, and topology.
The culmination of the degree is the senior capstone research experience: every student experiences a taste of the life of a professional mathematician as part of a team in the Mathematics Clinic Program or by working individually on a Senior Thesis.
The Mathematics Clinic program extends the academic experience of our majors. An educational innovation of HMC, our Clinic Program brings together teams of students to work on a research problem sponsored by business, industry or government. Teams work closely with a faculty advisor and a liaison provided by the sponsoring organization to solve complex realworld problems using mathematical and computational methods. Clinic teams present their results in bound final reports to the sponsors and give several formal presentations on the progress of the work during the academic year.
Our Senior Thesis program provides students with the opportunity to work independently on a problem of their choosing. Advisors and readers may be chosen from the HMC faculty and the other mathematicians at The Claremont Colleges, providing students with a wealth of research opportunities. As with Clinic, the end product of a thesis is a bound volume as well as presentations made at a professional conference or other venue, during the collegewide Presentations Days and throughout the year.
The course of study for a mathematics degree has five components: The Major Core, Computational Mathematics, Clinic or Thesis, Mathematics Forum and Mathematics Colloquium, and the Elective Program. Each of these components to the major program is described below.
The course of study for a mathematics degree has five components: The Major Core, Computational Mathematics, Clinic or Thesis, Mathematics Forum and Mathematics Colloquium, and the Elective Program. Each of these components to the major program is described below.
The Major Core
A set of core courses is required of each mathematics major:

MATH055 HM Discrete Mathematics
Credits: 3
Instructors: Benjamin, Bernoff, Lindo, Martonosi, Orrison, Su
Offered: Fall and spring
Description: Topics include combinatorics (clever ways of counting things), number theory, and graph theory with an emphasis on creative problem solving and learning to read and write rigorous proofs. Possible applications include probability, analysis of algorithms, and cryptography.
Corequisites: MATH073 HM

MATH062 HM Introduction to Probability and Statistics
Credits: 3
Instructors: Haddock, Martonosi, Williams
Offered: Spring
Description: Sample spaces, events, axioms for probabilities; conditional probabilities and Bayes' theorem; random variables and their distributions, discrete and continuous; expected values, means and variances; covariance and correlation; law of large numbers and central limit theorem; point and interval estimation; hypothesis testing; simple linear regression; applications to analyzing real data sets. Possible additional topics include ANOVA, multiple regression, and logistic regression.
Prerequisites: MATH019 HM
Corequisites: MATH073 HM

MATH082 HM Differential Equations
Credits: 3
Instructor: Staff
Offered: Fall
Description: Modeling physical systems, firstorder ordinary differential equations, existence, uniqueness, and longterm behavior of solutions; bifurcations; approximate solutions; secondorder ordinary differential equations and their properties, applications; firstorder systems of ordinary differential equations. Applications to linear systems of ordinary differential equations, matrix exponential; nonlinear systems of differential equations; equilibrium points and their stability. Additional topics.
Prerequisites: (MATH019 HM and MATH073 HM) or equivalent

MATH131 HM Mathematical Analysis I
Credits: 3
Instructors: Castro, de Pillis, Karp, Su, H. ZinnBrooks
Offered: Jointly; fall semester at hmc and pomona, spring semester at hmc and cmc
Description: This course is a rigorous analysis of the real numbers and an introduction to writing and communicating mathematics well. Topics include properties of the rational and the real number fields, the least upper bound property, induction, countable sets, metric spaces, limit points, compactness, connectedness, careful treatment of sequences and series, functions, differentiation and the mean value theorem, and an introduction to sequences of functions. Additional topics as time permits.
Prerequisites: MATH055 HM

MATH171 HM Abstract Algebra I
Credits: 3
Instructors: Karp, Lindo, Omar, Orrison, Staff (CMC), Staff (Pomona)
Offered: Jointly; fall semester at hmc and cmc, spring semester at hmc and pomona
Description: Groups, rings, fields, and additional topics. Topics in group theory include groups, subgroups, quotient groups, Lagrange's theorem, symmetry groups, and the isomorphism theorems. Topics in Ring theory include Euclidean domains, PIDs, UFDs, fields, polynomial rings, ideal theory, and the isomorphism theorems. In recent years, additional topics have included the Sylow theorems, group actions, modules, representations, and introductory category theory.
Prerequisites: MATH073 HM and MATH055 HM

MATH180 HM Introduction to Partial Differential Equations
Credits: 3
Instructors: Bernoff, Jacobsen, H. ZinnBrooks
Offered: Fall
Description: Partial Differential Equations (PDEs) including the heat equation, wave equation, and Laplace's equation; existence and uniqueness of solutions to PDEs via the maximum principle and energy methods; method of characteristics; Fourier series; Fourier transforms and Green's functions; Separation of variables; SturmLiouville theory and orthogonal expansions; Bessel functions.
Prerequisites: MATH082 HM and MATH131 HM
These courses cover a range of fundamental fields of mathematics and position the student to pursue any one of a variety of elective programs to finish the degree.
Computational Mathematics
One course in computational mathematics is required of all mathematics majors, selected from the following list:

CSCI081 HM Computability and Logic
Credits: 3
Instructors: Bang, Montañez, Stone
Offered: Fall and spring
Description: An introduction to some of the mathematical foundations of computer science, particularly logic, automata, and computability theory. Develops skill in constructing and writing proofs, and demonstrates the applications of the aforementioned areas to problems of practical significance.
Prerequisites: (MATH055 HM or MATH055 CM/PZ/SC), and (CSCI060 HM or CSCI042 HM), and (MATH019 HM or MATH032 CM/PO/PZ/SC or MATH032S PO or MATH067 PO), and (MATH073 HM or MATH060 CM/PO/PZ/SC)

CSCI142 HM Complexity Theory
Credits: 3
Instructor: Staff
Description: Brief review of computability theory through Rice's Theorem and the Recursion Theorem followed by a rigorous treatment of complexity theory. The complexity classes P, NP, and the CookLevin Theorem. Approximability of NPcomplete problems. The polynomial hierarchy, PSPACEcompleteness, L and NLcompleteness, #Pcompleteness. IP and Zeroknowledge proofs. Randomized and parallel complexity classes. The speedup, hierarchy, and gap theorems.
Prerequisites: CSCI081 HM

MATH164 HM Scientific Computing
Credits: 3
Instructors: Bernoff, de Pillis, Yong
Description: Computational techniques applied to problems in the sciences and engineering. Modeling of physical problems, computer implementation, analysis of results; use of mathematical software; numerical methods chosen from: solutions of linear and nonlinear algebraic equations, solutions of ordinary and partial differential equations, finite elements, linear programming, optimization algorithms, and fastFourier transforms.
Prerequisites: MATH073 HM, MATH082 HM, and CSCI060 HM

MATH165 HM Numerical Analysis
Credits: 3
Instructors: Bernoff, Haddock, de Pillis, Yong
Offered: Fall
Description: An introduction to the analysis and computer implementation of basic numerical techniques. Solution of linear equations, eigenvalue problems, local and global methods for nonlinear equations, interpolation, approximate integration (quadrature), and numerical solutions to ordinary differential equations.
Prerequisites: MATH073 HM and MATH082 HM

MATH168 HM Algorithms
Credits: 3
Instructors: Boerkoel (Computer Science), Montañez (Computer Science), Schofield (Computer Science), Stone (Computer Science)
Offered: Fall and spring
Description: Algorithm design, computer implementation, and analysis of efficiency. Discrete structures, sorting and searching, time and space complexity, and topics selected from algorithms for arithmetic circuits, sorting networks, parallel algorithms, computational geometry, parsing and patternmatching.
Prerequisites: ((CSCI070 HM and (MATH055 HM/CM/PZ/SC) and (MATH019 HM or MATH032 CM/PO/PZ/SC or MATH032S PO or MATH067 PO) and (MATH073 HM or MATH060 CM/PO/PZ/SC or MATH060C CM)) or ((CSCI060 HM or CSCI042 HM) and MATH131 HM)) or (CSCI062 PO and CSCI054 PO). CSCI081 HM is recommended.
Computational techniques are essential to many fields of modern mathematics and to most mathematical applications in business and industry.
Clinic or Thesis
Two semesters of Mathematics Clinic or two semesters of Senior Thesis are required and taken in the senior year:

MATH193 HM Mathematics Clinic (taken twice)
Credits: 3
Instructor: Staff
Offered: Fall and spring
Description: The Clinic Program brings together teams of students to work on a research problem sponsored by business, industry, or government. Teams work closely with a faculty advisor and a liaison provided by the sponsoring organization to solve complex, realworld problems using mathematical and computational methods. Students are expected to present their work orally and to produce a final report conforming to the publication standards of a professional mathematician. Students are expected to take the two semesters of Clinic within a single academic year.
Prerequisites: Senior standing as a mathematics major or permission of the Mathematics Clinic director.
OR

MATH197 HM Senior Thesis in Mathematics (taken twice)
Credits: 3
Instructor: Staff
Offered: Fall and spring
Description: Senior thesis offers the student, guided by the faculty advisor, a chance to experience a taste of the life of a professional research mathematician. The work is largely independent with guidance from the research advisor. The principal objective of the senior thesis program is to help you develop intellectually and improve your written and verbal communication skills. Students are expected to present their work orally and to produce a thesis conforming to the publication standards of a professional mathematician.
Prerequisites: Senior standing as a mathematics major and permission from the Mathematics Senior Thesis Coordinator.
Clinic and thesis are important capstone experiences for each mathematics major: they represent sustained efforts to solve a complex problem from industry or mathematical research. Clinic teams will be formed in the fall according to the requirements of the projects and student preferences. Students who do Clinic must work on the same Clinic project both semesters.
Mathematics Forum and Mathematics Colloquium
All mathematics majors must take:
One semester of Mathematics Forum:

MATH198 HM Undergraduate Mathematics Forum (generally in the junior year)
Credit: 1
Instructors: Castro, Jacobsen, Orrison, Williams, H. ZinnBrooks
Offered: Fall and spring
Description: The goal of this course is to improve students' ability to communicate mathematics, both to a general and technical audience. Students will present material on assigned topics and have their presentations evaluated by students and faculty. This format simultaneously exposes students to a broad range of topics from modern and classical mathematics. Required for all majors; recommended for all joint CSmath majors and mathematical biology majors, typically in the junior year.
AND
One semester of Mathematics Colloquium:

MATH199 HM Mathematics Colloquium (generally in the junior year)
Credit: 0.5
Instructor: Staff
Offered: Fall and spring
Description: Students will attend weekly Claremont Math Colloquium, offered through the cooperative efforts of the mathematics faculty at The Claremont Colleges. Most of the talks discuss current research in mathematical sciences and are accessible to undergraduates. No more than 2.0 credits can be earned for departmental seminars/colloquia.
The Elective Program
To complete the degree, three elective mathematics courses totaling at least seven credits are required. All electives must be numbered over 100 (some offcampus math courses numbered in the 100s that replicate HMC Core course content may not be counted toward the elective requirement).
The elective program will be designed by the student in consultation with their advisor. Courses outside of mathematics may be counted toward the elective program if approved by petition to the department. Courses that are crosslisted between computer science and mathematics, such as Complexity Theory, which appears as both MATH167 HM and CSCI142 HM, can be taken under either course number.
To assist students in designing their elective program, the department has prepared a variety of sample programs. These sample programs list courses that support a wide range of career goals in academics, business, or industry. About half of our graduates immediately join the workforce and about half enter graduate school. Several sample elective programs are listed below. In each of these samples, the first two courses are strongly recommended; at least one additional course is to be selected in order to complete the elective program. We emphasize that sample elective programs are advisory. Students may follow a sample program or design one of their own.
Theoretical Mathematics

MATH132 HM Mathematical Analysis II
Credits: 3
Instructors: Castro, Omar, Su, Staff (Pomona)
Offered: Jointly; fall semester at hmc, spring semester at pomona
Description: A rigorous study of calculus in Euclidean spaces including multiple Riemann integrals, derivatives of transformations, and the inverse function theorem.
Prerequisites: MATH131 HM

MATH172 HM Abstract Algebra II: Galois Theory
Credits: 3
Instructors: Karp, Omar, Orrison, Su, Staff (Pomona)
Offered: Jointly; spring semester at hmc and pomona
Description: The topics covered will include polynomial rings, field extensions, classical constructions, splitting fields, algebraic closure, separability, Fundamental Theorem of Galois Theory, Galois groups of polynomials, and solvability.
Prerequisites: MATH171 HM
and at least one elective from:

MATH104 HM Graph Theory
Credits: 3
Instructors: Martonosi, Omar, Orrison
Offered: Alternate years
Description: An introduction to graph theory with applications. Theory and applications of trees, matchings, graph coloring, planarity, graph algorithms, and other topics.
Prerequisites: MATH073 HM and MATH055 HM

MATH106 HM Combinatorics
Credits: 3
Instructors: Benjamin, Omar, Orrison
Offered: Alternate years
Description: An introduction to the techniques and ideas of combinatorics, including counting methods, Stirling numbers, Catalan numbers, generating functions, Ramsey theory, and partially ordered sets.
Prerequisites: MATH055 HM

MATH136 HM Complex Variables and Integral Transforms
Credits: 3
Instructors: Bernoff, Castro, Jacobsen, Karp, Yong
Offered: Fall
Description: Complex differentiation, CauchyRiemann equations, Cauchy integral formulas, residue theory, Taylor and Laurent expansions, conformal mapping, Fourier and Laplace transforms, inversion formulas, other integral transforms, applications to solutions of partial differential equations.
Prerequisites: MATH073 HM and MATH082 HM

MATH142 HM Differential Geometry
Credits: 3
Instructors: Gu, Karp, Staff (Pitzer)
Offered: Fall
Description: Curves and surfaces, Gauss curvature; isometries, tensor analysis, covariant differentiation with application to physics and geometry (intended for majors in physics or mathematics).
Prerequisites: MATH073 HM and MATH082 HM

MATH143 HM Seminar in Differential Geometry
Credits: 3
Instructor: Gu
Offered: Spring
Description: Selected topics in Riemannian geometry, low dimensional manifold theory, elementary Lie groups and Lie algebra, and contemporary applications in mathematics and physics.
Prerequisites: MATH131 HM and MATH142 HM; MATH147 HM recommended

MATH147 HM Topology
Credits: 3
Instructors: Karp, Su, Staff (Pomona)
Offered: Jointly with pomona; spring semester
Description: Topology is the study of properties of objects preserved by continuous deformations (much like geometry is the study of properties preserved by rigid motions). Hence, topology is sometimes called "rubbersheet" geometry. This course is an introduction to pointset topology with additional topics chosen from geometric and algebraic topology. It will cover topological spaces, metric spaces, product spaces, quotient spaces, Hausdorff spaces, compactness, connectedness, and path connectedness. Additional topics will be chosen from metrization theorems, fundamental groups, homotopy of maps, covering spaces, the Jordan curve theorem, classification of surfaces, and simplicial homology.
Prerequisites: MATH131 HM

MATH173 HM Advanced Linear Algebra
Credits: 3
Instructors: de Pillis, Gu, Haddock, Orrison
Offered: Jointly in alternate years
Description: Topics from among the following: Similarity of matrices and the Jordan form, the CayleyHamilton theorem, limits of sequences and series of matrices; the PerronFrobenius theory of nonnegative matrices, estimating eigenvalues of matrices; stability of systems of linear differential equations and Lyapunov's Theorem; iterative solutions of large systems of linear algebraic equations.
Prerequisites: MATH131 HM

MATH174 HM Abstract Algebra II: Representation Theory
Credits: 3
Instructors: Karp, Lindo, Omar, Orrison, Su
Offered: Jointly; spring semester at hmc and pomona
Description: The topics covered will include group rings, characters, orthogonality relations, induced representations, applications of representation theory, and other select topics from module theory.
Prerequisites: MATH171 HM

MATH175 HM Number Theory
Credits: 3
Instructors: Benjamin, Omar, Staff (Scripps)
Offered: Spring; offered jointly fall semester at scripps
Description: Properties of integers, congruences, Diophantine problems, quadratic reciprocity, number theoretic functions, primes.
Prerequisites: MATH055 HM
Applied Mathematics

MATH136 HM Complex Variables and Integral Transforms
Credits: 3
Instructors: Bernoff, Castro, Jacobsen, Karp, Yong
Offered: Fall
Description: Complex differentiation, CauchyRiemann equations, Cauchy integral formulas, residue theory, Taylor and Laurent expansions, conformal mapping, Fourier and Laplace transforms, inversion formulas, other integral transforms, applications to solutions of partial differential equations.
Prerequisites: MATH073 HM and MATH082 HM

MATH181 HM Dynamical Systems
Credits: 3
Instructors: Bernoff, Jacobsen, H. ZinnBrooks, Staff (Pomona)
Offered: Jointly; fall semester at pomona, spring semester at hmc in alternate years
Description: Existence and uniqueness theorems for systems of differential equations, dependence on data, linear systems, fundamental matrices, asymptotic behavior of solutions, stability theory, and other selected topics, as time permits.
Prerequisites: MATH180 HM
and at least one elective from:

MATH119 HM Advanced Mathematical Biology
Credits: 3
Instructors: Adolph (Biology), de Pillis, Jacobsen
Description: Further study of mathematical models of biological processes, including discrete and continuous models. Examples are drawn from a variety of areas of biology, which may include physiology, systems biology, cancer biology, epidemiology, ecology, evolution, and spatiotemporal dynamics.
Prerequisites: MCBI118A HM

MATH132 HM Mathematical Analysis II
Credits: 3
Instructors: Castro, Omar, Su, Staff (Pomona)
Offered: Jointly; fall semester at hmc, spring semester at pomona
Description: A rigorous study of calculus in Euclidean spaces including multiple Riemann integrals, derivatives of transformations, and the inverse function theorem.
Prerequisites: MATH131 HM

MATH164 HM Scientific Computing
Credits: 3
Instructors: Bernoff, de Pillis, Yong
Description: Computational techniques applied to problems in the sciences and engineering. Modeling of physical problems, computer implementation, analysis of results; use of mathematical software; numerical methods chosen from: solutions of linear and nonlinear algebraic equations, solutions of ordinary and partial differential equations, finite elements, linear programming, optimization algorithms, and fastFourier transforms.
Prerequisites: MATH073 HM, MATH082 HM, and CSCI060 HM

MATH165 HM Numerical Analysis
Credits: 3
Instructors: Bernoff, Haddock, de Pillis, Yong
Offered: Fall
Description: An introduction to the analysis and computer implementation of basic numerical techniques. Solution of linear equations, eigenvalue problems, local and global methods for nonlinear equations, interpolation, approximate integration (quadrature), and numerical solutions to ordinary differential equations.
Prerequisites: MATH073 HM and MATH082 HM

MATH173 HM Advanced Linear Algebra
Credits: 3
Instructors: de Pillis, Gu, Haddock, Orrison
Offered: Jointly in alternate years
Description: Topics from among the following: Similarity of matrices and the Jordan form, the CayleyHamilton theorem, limits of sequences and series of matrices; the PerronFrobenius theory of nonnegative matrices, estimating eigenvalues of matrices; stability of systems of linear differential equations and Lyapunov's Theorem; iterative solutions of large systems of linear algebraic equations.
Prerequisites: MATH131 HM

MATH184 HM Graduate Partial Differential Equations
Credits: 3
Instructors: Bernoff, Castro, Jacobsen
Offered: Spring, alternate years
Description: Advanced topics in the study of linear and nonlinear partial differential equations. Topics may include the theory of distributions; Hilbert spaces; conservation laws, characteristics and entropy methods; fixed point theory; critical point theory; the calculus of variations and numerical methods. Applications to fluid mechanics, mathematical physics, mathematical biology, and related fields.
Prerequisites: MATH180 HM; recommended MATH132 HM

MATH187 HM Operations Research
Credits: 3
Instructors: Benjamin, Martonosi, Staff (CMC), Staff (Pomona)
Offered: Fall
Description: Linear, integer, nonlinear and dynamic programming, classical optimization problems, and network theory.
Prerequisites: MATH073 HM
 MATH362 CGNumerical Methods for Differential Equations
 MATH368 CGNumerical Methods for Matrix Computations
 MATH382 CGPerturbation and Asymptotic Analysis

MCBI118A HM Introduction to Mathematical Biology
Credits: 1.5
Instructors: Adolph (Biology), de Pillis (Mathematics), DonaldsonMatasci (Biology)
Offered: Spring
Description: An introduction to the field of mathematical biology. Continuous and discrete mathematical models of biological processes and their analytical and computational solutions. Examples may include models in epidemiology, ecology, cancer biology, systems biology, molecular evolution, and phylogenetics.
Prerequisites: MATH073 HM, MATH082 HM, and BIOL046 HM
AND

MCBI118B HM Introduction to Computational Biology
Credits: 1.5
Instructors: Bush (Biology), DonaldsonMatasci (Biology), Wu (Computer Science)
Offered: Spring
Description: An introduction to the field of computational biology. Algorithms for phylogenetic inference and computational methods for solving problems in molecular evolution and population genetics.
Prerequisites: CSCI005 HM and BIOL046 HM
Probability and Statistics

MATH152 HM Statistical Theory
Credits: 3
Instructors: Martonosi, Williams, Staff (Pomona), Staff (CMC)
Offered: Jointly; spring semester at pomona and cmc
Description: An introduction to the general theory of statistical inference, including estimation of parameters, confidence intervals, and tests of hypotheses.
Prerequisites: MATH 157 HM

MATH156 HM Stochastic Processes
Credits: 3
Instructors: Benjamin, Martonosi, Staff (CMC)
Offered: Jointly; fall, alternate years at hmc
Description: This course is particularly wellsuited for those wanting to see how probability theory can be applied to the study of random phenomena in fields such as engineering, management science, the physical and social sciences, and operations research. Topics include conditional expectation, Markov chains, Poisson processes, and queuing theory. Additional applications chosen from such topics as reliability theory, Brownian motion, finance and asset pricing, inventory theory, dynamic programming, and simulation.
Prerequisites: MATH073 HM and MATH157 HM
and at least one elective from:

MATH106 HM Combinatorics
Credits: 3
Instructors: Benjamin, Omar, Orrison
Offered: Alternate years
Description: An introduction to the techniques and ideas of combinatorics, including counting methods, Stirling numbers, Catalan numbers, generating functions, Ramsey theory, and partially ordered sets.
Prerequisites: MATH055 HM

MATH132 HM Mathematical Analysis II
Credits: 3
Instructors: Castro, Omar, Su, Staff (Pomona)
Offered: Jointly; fall semester at hmc, spring semester at pomona
Description: A rigorous study of calculus in Euclidean spaces including multiple Riemann integrals, derivatives of transformations, and the inverse function theorem.
Prerequisites: MATH131 HM

MATH153 HM Bayesian Statistics
Credits: 3
Instructor: Williams
Offered: Spring, alternate years
Description: An introduction to principles of data analysis and advanced statistical modeling using Bayesian inference. Topics include a combination of Bayesian principles and advanced methods; general, conjugate and noninformative priors, posteriors, credible intervals, Markov Chain Monte Carlo methods, and hierarchical models. The emphasis throughout is on the application of Bayesian thinking to problems in data analysis. Statistical software will be used as a tool to implement many of the techniques.
Prerequisites: Permission of instructor

MATH155 HM Time Series
Credits: 3
Instructor: Williams
Offered: Spring, alternate years
Description: An introduction to the theory of statistical time series. Topics include decomposition of time series, seasonal models, forecasting models including causal models, trend models, and smoothing models, autoregressive (AR), moving average (MA), and integrated (ARIMA) forecasting models. Time permitting, we will also discuss state space models, which include Markov processes and hidden Markov processes, and derive the famous Kalman filter, which is a recursive algorithm to compute predictions. Statistical software will be used as a tool to aid calculations required for many of the techniques.
Prerequisites: Permission of instructor

MATH158 HM Statistical Linear Models
Credits: 3
Instructors: Martonosi, Williams, Staff (Pomona)
Offered: Fall, alternate years
Description: An introduction to linear regression including simple linear regression, multiple regression, variable selection, stepwise regression and analysis of residual plots and analysis of variance including oneway and twoway fixed effects ANOVA. Emphasis will be on both methods and applications to data. Statistical software will be used to analyze data.
Prerequisites: Permission of instructor

MATH173 HM Advanced Linear Algebra
Credits: 3
Instructors: de Pillis, Gu, Haddock, Orrison
Offered: Jointly in alternate years
Description: Topics from among the following: Similarity of matrices and the Jordan form, the CayleyHamilton theorem, limits of sequences and series of matrices; the PerronFrobenius theory of nonnegative matrices, estimating eigenvalues of matrices; stability of systems of linear differential equations and Lyapunov's Theorem; iterative solutions of large systems of linear algebraic equations.
Prerequisites: MATH131 HM

MATH187 HM Operations Research
Credits: 3
Instructors: Benjamin, Martonosi, Staff (CMC), Staff (Pomona)
Offered: Fall
Description: Linear, integer, nonlinear and dynamic programming, classical optimization problems, and network theory.
Prerequisites: MATH073 HM
 MATH351 CGTime Series Analysis
 MATH355 CGLinear Statistical Models
Operations Research

MATH156 HM Stochastic Processes
Credits: 3
Instructors: Benjamin, Martonosi, Staff (CMC)
Offered: Jointly; fall, alternate years at hmc
Description: This course is particularly wellsuited for those wanting to see how probability theory can be applied to the study of random phenomena in fields such as engineering, management science, the physical and social sciences, and operations research. Topics include conditional expectation, Markov chains, Poisson processes, and queuing theory. Additional applications chosen from such topics as reliability theory, Brownian motion, finance and asset pricing, inventory theory, dynamic programming, and simulation.
Prerequisites: MATH073 HM and MATH157 HM

MATH187 HM Operations Research
Credits: 3
Instructors: Benjamin, Martonosi, Staff (CMC), Staff (Pomona)
Offered: Fall
Description: Linear, integer, nonlinear and dynamic programming, classical optimization problems, and network theory.
Prerequisites: MATH073 HM
and at least one elective from:

MATH104 HM Graph Theory
Credits: 3
Instructors: Martonosi, Omar, Orrison
Offered: Alternate years
Description: An introduction to graph theory with applications. Theory and applications of trees, matchings, graph coloring, planarity, graph algorithms, and other topics.
Prerequisites: MATH073 HM and MATH055 HM

MATH106 HM Combinatorics
Credits: 3
Instructors: Benjamin, Omar, Orrison
Offered: Alternate years
Description: An introduction to the techniques and ideas of combinatorics, including counting methods, Stirling numbers, Catalan numbers, generating functions, Ramsey theory, and partially ordered sets.
Prerequisites: MATH055 HM

MATH132 HM Mathematical Analysis II
Credits: 3
Instructors: Castro, Omar, Su, Staff (Pomona)
Offered: Jointly; fall semester at hmc, spring semester at pomona
Description: A rigorous study of calculus in Euclidean spaces including multiple Riemann integrals, derivatives of transformations, and the inverse function theorem.
Prerequisites: MATH131 HM

MATH152 HM Statistical Theory
Credits: 3
Instructors: Martonosi, Williams, Staff (Pomona), Staff (CMC)
Offered: Jointly; spring semester at pomona and cmc
Description: An introduction to the general theory of statistical inference, including estimation of parameters, confidence intervals, and tests of hypotheses.
Prerequisites: MATH 157 HM

MATH158 HM Statistical Linear Models
Credits: 3
Instructors: Martonosi, Williams, Staff (Pomona)
Offered: Fall, alternate years
Description: An introduction to linear regression including simple linear regression, multiple regression, variable selection, stepwise regression and analysis of residual plots and analysis of variance including oneway and twoway fixed effects ANOVA. Emphasis will be on both methods and applications to data. Statistical software will be used to analyze data.
Prerequisites: Permission of instructor

MATH165 HM Numerical Analysis
Credits: 3
Instructors: Bernoff, Haddock, de Pillis, Yong
Offered: Fall
Description: An introduction to the analysis and computer implementation of basic numerical techniques. Solution of linear equations, eigenvalue problems, local and global methods for nonlinear equations, interpolation, approximate integration (quadrature), and numerical solutions to ordinary differential equations.
Prerequisites: MATH073 HM and MATH082 HM

MATH168 HM Algorithms
Credits: 3
Instructors: Boerkoel (Computer Science), Montañez (Computer Science), Schofield (Computer Science), Stone (Computer Science)
Offered: Fall and spring
Description: Algorithm design, computer implementation, and analysis of efficiency. Discrete structures, sorting and searching, time and space complexity, and topics selected from algorithms for arithmetic circuits, sorting networks, parallel algorithms, computational geometry, parsing and patternmatching.
Prerequisites: ((CSCI070 HM and (MATH055 HM/CM/PZ/SC) and (MATH019 HM or MATH032 CM/PO/PZ/SC or MATH032S PO or MATH067 PO) and (MATH073 HM or MATH060 CM/PO/PZ/SC or MATH060C CM)) or ((CSCI060 HM or CSCI042 HM) and MATH131 HM)) or (CSCI062 PO and CSCI054 PO). CSCI081 HM is recommended.

MATH188 HM Social Choice and Decision Making
Credits: 3
Instructor: Su
Offered: Spring, alternate years
Description: Basic concepts of game theory and social choice theory, representations of games, Nash equilibria, utility theory, noncooperative games, cooperative games, voting games, paradoxes, Arrow's impossibility theorem, Shapley value, power indices, "fair division" problems and applications.
Corequisites: MATH055 HM recommended
Actuarial or Financial Mathematics

MATH109 CM Introduction to the Mathematics of Finance
Credits: 3
Instructor: Staff (CMC)
Offered: Alternate years
Description: This is a first course in Mathematical Finance sequence. This course introduces the concepts of arbitrage and riskneutral pricing within the context of single and multiperiod financial models. Key elements of stochastic calculus such as Markov processes, martingales, filtration, and stopping times will be developed within this context. Pricing by replication is studied in a multiperiod binomial model. Within this model, the replicating strategies for European and American options are determined.
Prerequisites: MATH073 HM and MATH082 HM

MATH156 HM Stochastic Processes
Credits: 3
Instructors: Benjamin, Martonosi, Staff (CMC)
Offered: Jointly; fall, alternate years at hmc
Description: This course is particularly wellsuited for those wanting to see how probability theory can be applied to the study of random phenomena in fields such as engineering, management science, the physical and social sciences, and operations research. Topics include conditional expectation, Markov chains, Poisson processes, and queuing theory. Additional applications chosen from such topics as reliability theory, Brownian motion, finance and asset pricing, inventory theory, dynamic programming, and simulation.
Prerequisites: MATH073 HM and MATH157 HM
and at least one elective from:

MATH152 HM Statistical Theory
Credits: 3
Instructors: Martonosi, Williams, Staff (Pomona), Staff (CMC)
Offered: Jointly; spring semester at pomona and cmc
Description: An introduction to the general theory of statistical inference, including estimation of parameters, confidence intervals, and tests of hypotheses.
Prerequisites: MATH 157 HM

MATH155 HM Time Series
Credits: 3
Instructor: Williams
Offered: Spring, alternate years
Description: An introduction to the theory of statistical time series. Topics include decomposition of time series, seasonal models, forecasting models including causal models, trend models, and smoothing models, autoregressive (AR), moving average (MA), and integrated (ARIMA) forecasting models. Time permitting, we will also discuss state space models, which include Markov processes and hidden Markov processes, and derive the famous Kalman filter, which is a recursive algorithm to compute predictions. Statistical software will be used as a tool to aid calculations required for many of the techniques.
Prerequisites: Permission of instructor

MATH158 HM Statistical Linear Models
Credits: 3
Instructors: Martonosi, Williams, Staff (Pomona)
Offered: Fall, alternate years
Description: An introduction to linear regression including simple linear regression, multiple regression, variable selection, stepwise regression and analysis of residual plots and analysis of variance including oneway and twoway fixed effects ANOVA. Emphasis will be on both methods and applications to data. Statistical software will be used to analyze data.
Prerequisites: Permission of instructor

MATH165 HM Numerical Analysis
Credits: 3
Instructors: Bernoff, Haddock, de Pillis, Yong
Offered: Fall
Description: An introduction to the analysis and computer implementation of basic numerical techniques. Solution of linear equations, eigenvalue problems, local and global methods for nonlinear equations, interpolation, approximate integration (quadrature), and numerical solutions to ordinary differential equations.
Prerequisites: MATH073 HM and MATH082 HM

MATH187 HM Operations Research
Credits: 3
Instructors: Benjamin, Martonosi, Staff (CMC), Staff (Pomona)
Offered: Fall
Description: Linear, integer, nonlinear and dynamic programming, classical optimization problems, and network theory.
Prerequisites: MATH073 HM
 MATH355 CG Linear Statistical Models
 ECON125 CMEconometrics
 ECON126 CMMicroeconometrics
 ECON167 POEconometrics
 ECON382 CGEconometrics I
 ECON383 CGEconometrics II
 ECON384 CGEconometrics III
Scientific Computing

MATH164 HM Scientific Computing
Credits: 3
Instructors: Bernoff, de Pillis, Yong
Description: Computational techniques applied to problems in the sciences and engineering. Modeling of physical problems, computer implementation, analysis of results; use of mathematical software; numerical methods chosen from: solutions of linear and nonlinear algebraic equations, solutions of ordinary and partial differential equations, finite elements, linear programming, optimization algorithms, and fastFourier transforms.
Prerequisites: MATH073 HM, MATH082 HM, and CSCI060 HM

MATH165 HM Numerical Analysis
Credits: 3
Instructors: Bernoff, Haddock, de Pillis, Yong
Offered: Fall
Description: An introduction to the analysis and computer implementation of basic numerical techniques. Solution of linear equations, eigenvalue problems, local and global methods for nonlinear equations, interpolation, approximate integration (quadrature), and numerical solutions to ordinary differential equations.
Prerequisites: MATH073 HM and MATH082 HM
and at least one elective from:

MATH119 HM Advanced Mathematical Biology
Credits: 3
Instructors: Adolph (Biology), de Pillis, Jacobsen
Description: Further study of mathematical models of biological processes, including discrete and continuous models. Examples are drawn from a variety of areas of biology, which may include physiology, systems biology, cancer biology, epidemiology, ecology, evolution, and spatiotemporal dynamics.
Prerequisites: MCBI118A HM

MATH136 HM Complex Variables and Integral Transforms
Credits: 3
Instructors: Bernoff, Castro, Jacobsen, Karp, Yong
Offered: Fall
Description: Complex differentiation, CauchyRiemann equations, Cauchy integral formulas, residue theory, Taylor and Laurent expansions, conformal mapping, Fourier and Laplace transforms, inversion formulas, other integral transforms, applications to solutions of partial differential equations.
Prerequisites: MATH073 HM and MATH082 HM

MATH168 HM Algorithms
Credits: 3
Instructors: Boerkoel (Computer Science), Montañez (Computer Science), Schofield (Computer Science), Stone (Computer Science)
Offered: Fall and spring
Description: Algorithm design, computer implementation, and analysis of efficiency. Discrete structures, sorting and searching, time and space complexity, and topics selected from algorithms for arithmetic circuits, sorting networks, parallel algorithms, computational geometry, parsing and patternmatching.
Prerequisites: ((CSCI070 HM and (MATH055 HM/CM/PZ/SC) and (MATH019 HM or MATH032 CM/PO/PZ/SC or MATH032S PO or MATH067 PO) and (MATH073 HM or MATH060 CM/PO/PZ/SC or MATH060C CM)) or ((CSCI060 HM or CSCI042 HM) and MATH131 HM)) or (CSCI062 PO and CSCI054 PO). CSCI081 HM is recommended.

MATH173 HM Advanced Linear Algebra
Credits: 3
Instructors: de Pillis, Gu, Haddock, Orrison
Offered: Jointly in alternate years
Description: Topics from among the following: Similarity of matrices and the Jordan form, the CayleyHamilton theorem, limits of sequences and series of matrices; the PerronFrobenius theory of nonnegative matrices, estimating eigenvalues of matrices; stability of systems of linear differential equations and Lyapunov's Theorem; iterative solutions of large systems of linear algebraic equations.
Prerequisites: MATH131 HM

MATH181 HM Dynamical Systems
Credits: 3
Instructors: Bernoff, Jacobsen, H. ZinnBrooks, Staff (Pomona)
Offered: Jointly; fall semester at pomona, spring semester at hmc in alternate years
Description: Existence and uniqueness theorems for systems of differential equations, dependence on data, linear systems, fundamental matrices, asymptotic behavior of solutions, stability theory, and other selected topics, as time permits.
Prerequisites: MATH180 HM

MATH184 HM Graduate Partial Differential Equations
Credits: 3
Instructors: Bernoff, Castro, Jacobsen
Offered: Spring, alternate years
Description: Advanced topics in the study of linear and nonlinear partial differential equations. Topics may include the theory of distributions; Hilbert spaces; conservation laws, characteristics and entropy methods; fixed point theory; critical point theory; the calculus of variations and numerical methods. Applications to fluid mechanics, mathematical physics, mathematical biology, and related fields.
Prerequisites: MATH180 HM; recommended MATH132 HM
 MATH362 CGNumerical Methods for Differential Equations
 MATH368 CGNumerical Methods for Matrix Computations
 MATH382 CGPerturbation and Asymptotic Analysis

MCBI118A HM Introduction to Mathematical Biology
Credits: 1.5
Instructors: Adolph (Biology), de Pillis (Mathematics), DonaldsonMatasci (Biology)
Offered: Spring
Description: An introduction to the field of mathematical biology. Continuous and discrete mathematical models of biological processes and their analytical and computational solutions. Examples may include models in epidemiology, ecology, cancer biology, systems biology, molecular evolution, and phylogenetics.
Prerequisites: MATH073 HM, MATH082 HM, and BIOL046 HM
AND

MCBI118B HM Introduction to Computational Biology
Credits: 1.5
Instructors: Bush (Biology), DonaldsonMatasci (Biology), Wu (Computer Science)
Offered: Spring
Description: An introduction to the field of computational biology. Algorithms for phylogenetic inference and computational methods for solving problems in molecular evolution and population genetics.
Prerequisites: CSCI005 HM and BIOL046 HM
Theoretical Computer Science

CSCI081 HM Computability and Logic
Credits: 3
Instructors: Bang, Montañez, Stone
Offered: Fall and spring
Description: An introduction to some of the mathematical foundations of computer science, particularly logic, automata, and computability theory. Develops skill in constructing and writing proofs, and demonstrates the applications of the aforementioned areas to problems of practical significance.
Prerequisites: (MATH055 HM or MATH055 CM/PZ/SC), and (CSCI060 HM or CSCI042 HM), and (MATH019 HM or MATH032 CM/PO/PZ/SC or MATH032S PO or MATH067 PO), and (MATH073 HM or MATH060 CM/PO/PZ/SC)

MATH168 HM Algorithms
Credits: 3
Instructors: Boerkoel (Computer Science), Montañez (Computer Science), Schofield (Computer Science), Stone (Computer Science)
Offered: Fall and spring
Description: Algorithm design, computer implementation, and analysis of efficiency. Discrete structures, sorting and searching, time and space complexity, and topics selected from algorithms for arithmetic circuits, sorting networks, parallel algorithms, computational geometry, parsing and patternmatching.
Prerequisites: ((CSCI070 HM and (MATH055 HM/CM/PZ/SC) and (MATH019 HM or MATH032 CM/PO/PZ/SC or MATH032S PO or MATH067 PO) and (MATH073 HM or MATH060 CM/PO/PZ/SC or MATH060C CM)) or ((CSCI060 HM or CSCI042 HM) and MATH131 HM)) or (CSCI062 PO and CSCI054 PO). CSCI081 HM is recommended.
and at least one elective from:

CSCI151 HM Artificial Intelligence
Credits: 3
Instructors: Boerkoel, Talvitie, Wu
Description: This course presents a general introduction to the field of Artificial Intelligence. It examines the question: What does (will) it take for computers to perform human tasks? It presents a broad introduction to topics such as knowledge representation, search, learning and reasoning under uncertainty. For each topic, it examines realworld applications of core techniques to problems which may include game playing, text classification and visual pattern recognition.
Prerequisites: CSCI070 HM and (MATH056 HM or MATH062 HM or BIOL154 HM or MATH151 CM/PO/PZ/SC)

CSCI152 HM Neural Networks
Credits: 3
Instructor: Staff
Description: Modeling, simulation, and analysis of artificial neural networks and their relation to biological networks. Design and optimization of discrete and continuous neural networks. Back propagation and other gradient descent methods. Hopfield and Boltzmann networks. Unsupervised learning. Selforganizing feature maps. Applications chosen from function approximation, signal processing, control, computer graphics, pattern recognition, timeseries analysis. Relationship to fuzzy logic, genetic algorithms, and artificial life.
Prerequisites: CSCI070 HM and MATH073 HM and (MATH056 HM or MATH062 HM or BIOL154 HM or MATH151 CM/PO/PZ/SC)

MATH104 HM Graph Theory
Credits: 3
Instructors: Martonosi, Omar, Orrison
Offered: Alternate years
Description: An introduction to graph theory with applications. Theory and applications of trees, matchings, graph coloring, planarity, graph algorithms, and other topics.
Prerequisites: MATH073 HM and MATH055 HM

MATH106 HM Combinatorics
Credits: 3
Instructors: Benjamin, Omar, Orrison
Offered: Alternate years
Description: An introduction to the techniques and ideas of combinatorics, including counting methods, Stirling numbers, Catalan numbers, generating functions, Ramsey theory, and partially ordered sets.
Prerequisites: MATH055 HM

MATH165 HM Numerical Analysis
Credits: 3
Instructors: Bernoff, Haddock, de Pillis, Yong
Offered: Fall
Description: An introduction to the analysis and computer implementation of basic numerical techniques. Solution of linear equations, eigenvalue problems, local and global methods for nonlinear equations, interpolation, approximate integration (quadrature), and numerical solutions to ordinary differential equations.
Prerequisites: MATH073 HM and MATH082 HM

MATH167 HM Complexity Theory
Credits: 3
Instructor: Staff (Pomona)
Offered: Fall
Description: Brief review of computability theory, followed by a rigorous treatment of complexity theory. The complexity classes P, NP, and the CookLevin Theorem. Approximability of NPcomplete problems. The polynomial hierarchy, PSPACEcompleteness, L and NLcompleteness, #Pcompleteness. IP and Zeroknowledge proofs. Randomized and parallel complexity classes. The speedup, hierarchy, and gap theorems.
Prerequisites: (CSCI060 HM or CSCI042 HM) and MATH055 HM

MATH172 HM Abstract Algebra II: Galois Theory
Credits: 3
Instructors: Karp, Omar, Orrison, Su, Staff (Pomona)
Offered: Jointly; spring semester at hmc and pomona
Description: The topics covered will include polynomial rings, field extensions, classical constructions, splitting fields, algebraic closure, separability, Fundamental Theorem of Galois Theory, Galois groups of polynomials, and solvability.
Prerequisites: MATH171 HM

MATH175 HM Number Theory
Credits: 3
Instructors: Benjamin, Omar, Staff (Scripps)
Offered: Spring; offered jointly fall semester at scripps
Description: Properties of integers, congruences, Diophantine problems, quadratic reciprocity, number theoretic functions, primes.
Prerequisites: MATH055 HM
Mathematical Biology

MCBI118A HM Introduction to Mathematical Biology
Credits: 1.5
Instructors: Adolph (Biology), de Pillis (Mathematics), DonaldsonMatasci (Biology)
Offered: Spring
Description: An introduction to the field of mathematical biology. Continuous and discrete mathematical models of biological processes and their analytical and computational solutions. Examples may include models in epidemiology, ecology, cancer biology, systems biology, molecular evolution, and phylogenetics.
Prerequisites: MATH073 HM, MATH082 HM, and BIOL046 HM
AND

MCBI118B HM Introduction to Computational Biology
Credits: 1.5
Instructors: Bush (Biology), DonaldsonMatasci (Biology), Wu (Computer Science)
Offered: Spring
Description: An introduction to the field of computational biology. Algorithms for phylogenetic inference and computational methods for solving problems in molecular evolution and population genetics.
Prerequisites: CSCI005 HM and BIOL046 HM

MATH119 HM Advanced Mathematical Biology
Credits: 3
Instructors: Adolph (Biology), de Pillis, Jacobsen
Description: Further study of mathematical models of biological processes, including discrete and continuous models. Examples are drawn from a variety of areas of biology, which may include physiology, systems biology, cancer biology, epidemiology, ecology, evolution, and spatiotemporal dynamics.
Prerequisites: MCBI118A HM
and at least one elective from:

MATH152 HM Statistical Theory
Credits: 3
Instructors: Martonosi, Williams, Staff (Pomona), Staff (CMC)
Offered: Jointly; spring semester at pomona and cmc
Description: An introduction to the general theory of statistical inference, including estimation of parameters, confidence intervals, and tests of hypotheses.
Prerequisites: MATH 157 HM

MATH156 HM Stochastic Processes
Credits: 3
Instructors: Benjamin, Martonosi, Staff (CMC)
Offered: Jointly; fall, alternate years at hmc
Description: This course is particularly wellsuited for those wanting to see how probability theory can be applied to the study of random phenomena in fields such as engineering, management science, the physical and social sciences, and operations research. Topics include conditional expectation, Markov chains, Poisson processes, and queuing theory. Additional applications chosen from such topics as reliability theory, Brownian motion, finance and asset pricing, inventory theory, dynamic programming, and simulation.
Prerequisites: MATH073 HM and MATH157 HM

MATH158 HM Statistical Linear Models
Credits: 3
Instructors: Martonosi, Williams, Staff (Pomona)
Offered: Fall, alternate years
Description: An introduction to linear regression including simple linear regression, multiple regression, variable selection, stepwise regression and analysis of residual plots and analysis of variance including oneway and twoway fixed effects ANOVA. Emphasis will be on both methods and applications to data. Statistical software will be used to analyze data.
Prerequisites: Permission of instructor

MATH164 HM Scientific Computing
Credits: 3
Instructors: Bernoff, de Pillis, Yong
Description: Computational techniques applied to problems in the sciences and engineering. Modeling of physical problems, computer implementation, analysis of results; use of mathematical software; numerical methods chosen from: solutions of linear and nonlinear algebraic equations, solutions of ordinary and partial differential equations, finite elements, linear programming, optimization algorithms, and fastFourier transforms.
Prerequisites: MATH073 HM, MATH082 HM, and CSCI060 HM

MATH168 HM Algorithms
Credits: 3
Instructors: Boerkoel (Computer Science), Montañez (Computer Science), Schofield (Computer Science), Stone (Computer Science)
Offered: Fall and spring
Description: Algorithm design, computer implementation, and analysis of efficiency. Discrete structures, sorting and searching, time and space complexity, and topics selected from algorithms for arithmetic circuits, sorting networks, parallel algorithms, computational geometry, parsing and patternmatching.
Prerequisites: ((CSCI070 HM and (MATH055 HM/CM/PZ/SC) and (MATH019 HM or MATH032 CM/PO/PZ/SC or MATH032S PO or MATH067 PO) and (MATH073 HM or MATH060 CM/PO/PZ/SC or MATH060C CM)) or ((CSCI060 HM or CSCI042 HM) and MATH131 HM)) or (CSCI062 PO and CSCI054 PO). CSCI081 HM is recommended.

MATH173 HM Advanced Linear Algebra
Credits: 3
Instructors: de Pillis, Gu, Haddock, Orrison
Offered: Jointly in alternate years
Description: Topics from among the following: Similarity of matrices and the Jordan form, the CayleyHamilton theorem, limits of sequences and series of matrices; the PerronFrobenius theory of nonnegative matrices, estimating eigenvalues of matrices; stability of systems of linear differential equations and Lyapunov's Theorem; iterative solutions of large systems of linear algebraic equations.
Prerequisites: MATH131 HM

MATH181 HM Dynamical Systems
Credits: 3
Instructors: Bernoff, Jacobsen, H. ZinnBrooks, Staff (Pomona)
Offered: Jointly; fall semester at pomona, spring semester at hmc in alternate years
Description: Existence and uniqueness theorems for systems of differential equations, dependence on data, linear systems, fundamental matrices, asymptotic behavior of solutions, stability theory, and other selected topics, as time permits.
Prerequisites: MATH180 HM

MATH184 HM Graduate Partial Differential Equations
Credits: 3
Instructors: Bernoff, Castro, Jacobsen
Offered: Spring, alternate years
Description: Advanced topics in the study of linear and nonlinear partial differential equations. Topics may include the theory of distributions; Hilbert spaces; conservation laws, characteristics and entropy methods; fixed point theory; critical point theory; the calculus of variations and numerical methods. Applications to fluid mechanics, mathematical physics, mathematical biology, and related fields.
Prerequisites: MATH180 HM; recommended MATH132 HM

MATH187 HM Operations Research
Credits: 3
Instructors: Benjamin, Martonosi, Staff (CMC), Staff (Pomona)
Offered: Fall
Description: Linear, integer, nonlinear and dynamic programming, classical optimization problems, and network theory.
Prerequisites: MATH073 HM
Comments
Through the Major Core requirement, every major will have a foundation course in several important areas: discrete mathematics, analysis, algebra, differential equations and probability. In addition, every major will have a course relating to computational aspects of mathematics. The Major Core positions each student to move in any of several directions in the design of their elective program. There is a wide range of options to finish the major, supporting a variety of career goals and interests. It is expected that most students will take MATH055 HM – Discrete Mathematics and MATH131 HM – Mathematical Analysis I by the end of the sophomore year, MATH157 HM – Intermediate Probability, MATH171 HM – Abstract Algebra I, MATH180 HM – Introduction to Partial Differential Equations, MATH198 HM – Undergraduate Mathematics Forum, and MATH199 HM – Mathematics Colloquium by the end of the junior year, and MATH193 HM – Mathematics Clinic or MATH197 HM – Senior Thesis in Mathematics during the senior year.
Two semesters of Clinic or thesis are required of each major. All students must declare their intentions by the end of their junior year. Students who wish to take Clinic should inform the Mathematics Clinic Director, and preregister for MATH193 HM – Mathematics Clinic. Students choosing thesis must arrange to have a thesis advisor by the end of the spring semester of their junior year. In consultation with their advisor, the student must prepare a research proposal describing a suitable thesis problem, and submit the proposal to the mathematics department for approval. We expect that students will begin work on their theses immediately in the fall of the senior year. Thesis students will meet weekly as a group, to discuss their progress, make presentations, and exchange ideas. Students enrolled in Clinic who also wish to do thesis will be able to do a onesemester thesis, if desired. They may arrange their thesis in the fall of the senior year.
The faculty in the mathematics department works closely with each student to develop a coherent program of elective courses that meets the student’s professional and academic goals. The entire department meets once each term to discuss and compare all student programs and to discuss student progress.